THE EFFECT OF IRRIGATION AND LARGE DAMS ON THE BURDEN …€¦ · the Bura and Mwea irrigation schemes in Kenya, population densities of 223 people/ km2 and 320 people/ km 2 have

THE EFFECT OF IRRIGATION AND LARGE DAMS ON THE BURDEN OF MALARIA

ON GLOBAL AND REGIONAL SCALE Report prepared for the WHO commissioned study Burden of water-related vector-borne diseases: An analysis of the fraction attributable to components of water resources development and management. Based on this report, an article was published in the American Journal of Tropical Medicine and Hygiene (Am J Tr Med Hyg 72(4), 2005: 392-406). Investigators: Jennifer Keiser, Jürg Utzinger, Marcel Tanner

Swiss Tropical Institute, P.O. Box, CH-4002 Basel, Switzerland

Marcia Caldas de Castro, Burton H. Singer

Office of Population Research, Princeton University, Princeton, NJ 08544, USA

Michael F. Maltese

St Antony’s College, Oxford University, Oxford OX2 6JF, UK

Robert Bos, Jamie Bartram and Laurence Haller

Water, Sanitation and Health (WSH/PHE), World Health Organization, Avenue Appia 20, CH-

1211 Geneva 27, Switzerland

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Contents:

Executive summary page 3 Introduction page 4 Material and Methods page 6 Results a.) Causal web page 10 b.) Water project: irrigation page 11 c.) Water project: large dams page 15 Conclusion page 18 Discussion page 19 References page 24 Tables and Figures page 28 Appendix page 43

Executive summary:

Man-made ecological transformations have occurred at an unprecedented magnitude over

the past 50 years. Prominent among them are water resource development projects: an

estimated 40,000 large dams and 800,000 small dams have been built and some 272 million

hectares of land is currently under irrigation worldwide. The development, management and

operation of water resources has a history of modifying the frequency and transmission

dynamics of malaria, but analyses of how changes in the environmental risk factors and in the

incidence and prevalence of malaria are related are sparse.

In this report, we present a comprehensive review of studies that assessed the impact of

irrigation and dam building on malaria incidence or prevalence stratified by the 14 WHO sub-

regions of the world. We link the estimates of disability adjusted life years due to malaria with

statistics on irrigated agriculture and dam sites. We estimate that a maximum of 848.3 million

people live in the close vicinity of irrigation systems and 19.9 million near large dam sites

worldwide. In sub-Saharan Africa, which has 87.9% of the current global malaria burden, only

9.4 million people are living near large dams and irrigation sites. In contrast, the remaining sub-

regions with malaria transmission concentrate of 15.3 million people near large dams and 845

million near irrigation sites, but they represent only 12.1% of the global malaria burden. Whether

an individual water project triggers an increase in malaria transmission largely depends on the

epidemiological setting and socio-economic factors, vector management and health seeking

behaviour.

We conclude that, particularly in unstable malaria endemic areas, a combination of

integrated malaria control measures and sound water management is essential to reduce the

current burden of malaria in locations near irrigation or dam sites sustainably. It is also crucial to

include comprehensive health impact assessment (HIA) procedures in the planning of all water

resources development in malaria endemic areas. The relative dearth of studies that analyse

the complex sequence of events from environmental change to malaria incidence/ prevalence

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rates in a robust, comparative way calls for increased promotion and support of this type of

multidisciplinary research, preferably in the context of new water resources development.

Introduction

The world’s population is predicted to further increase from six billion currently to about 9.4

billion by 2050 and most of the projected global population growth will take place in developing

countries that already suffer from food shortages and health problems (United Nations, 2002).

Irrigation has assisted food production in many parts of the world; from the 1960s to the 1980s

irrigated land accounted for more than 50% of the increase in global food production (World

Bank and United Nations Development Programme, 1990). The construction of dams and

impoundment of reservoirs has been the principal means for the provision of irrigation water. It

is estimated that more than 40,000 large dams, defined as impoundments over 15 m high or

storing at least 3 million m3 of water, and 800,000 small dams have been built worldwide. Most

large dams have been built since 1950, during the post-war development era, when the

construction of large-scale infrastructure was a symbol of patriotic pride and technological

advance. Approximately half of the large dams serve irrigation purposes (Gujja and Perrin,

1999). In 2001 the total area under irrigation worldwide was estimated to be 272 million ha

(http://apps.fao.org/page/collections?subset=agriculture).

Irrigation has numerous potential benefits. Most importantly, it may contribute substantially

to food security and economic progress, which in turn provides rural households with greater

purchasing power for essential commodities, including improved access to health care delivery

services and education. Frequently, irrigation development also implies more general

infrastructural improvements: better roads, (and thus: better access for the health services),

rural electrification and sometimes housing improvements. The development of water projects

and their operation has, however, also a history of facilitating increased transmission of vector-

borne diseases (Service, 1991). The underlying reasons are the creation of new breeding sites

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and enhanced human-vector contacts due to ecological and demographic changes. For

example, surface irrigation, which is mainly used for the flooding of rice fields, creates

temporary shallow water bodies, which form ideal breeding sites for malaria vectors. From the

55 Anopheles species described worldwide acting as potential vectors (Lacey and Lacey, 1990),

several are predominantly rice-field breeders, particularly An. aconitus and An. sinensis.

Irrigation and drainage canals, and the various ancillary hydraulic structures in irrigation

systems, can also become important foci of vector breeding if they provide the right ecological

conditions.

Globally, more than two billion people live in areas where they are at risk of contracting

malaria and the estimated annual incidence of clinical malaria is greater than 300 million cases.

More than one million people die every year from the direct causes of malaria, with children

under the age of five years living in sub-Saharan Africa at highest risk (Breman, 2001). In 2001,

the disease accounted for an estimated loss of 44.7 million disability adjusted life years (DALYs)

with a DALY loss of > 87% occurring in sub-Saharan Africa (WHO, 2003); in 2002 the estimated

malaria burden had increased to 46.5 million DALYs (WHO, 2004). An estimated 90% of this

burden is related to environmental factors (WHO, 1997). Reliable analyses of these

environmental risks to health are therefore fundamental for the prevention and control of the

disease, for evidence-based guidance for health policy and planning and for the incorporation of

health considerations into the policies and programmes of all sectors with responsibilities for

water resources development and management. A detailed analysis of the malaria burden in

relation to the risk factor “development and operation of water projects” has to our knowledge

not been conducted so far.

The purpose of this report is to review the literature on the burden of malaria over the past

25 years in relation to the risk factor “development and operation of water projects”. Particular

emphasis is placed on irrigation and large dams. The report is structured as follows: first, we

provide a causal web, linking malaria with different types of water projects. Secondly, we

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present a comprehensive review of studies that have assessed the impact on malaria

prevalence in different ecological and epidemiological settings, after the introduction of irrigation

schemes. Thirdly, in order to assess the magnitude of irrigation on the burden of malaria on a

regional and global scale, we link current DALY estimates (2002) with the latest statistics on

irrigated agriculture and population at risk of acquiring the disease due to irrigation (2001).

Fourthly, we analyze studies that investigate the impact of dam building on malaria and present

the first estimates of populations living at risk of malaria due to proximity of large dam

reservoirs, applying WHO’s sub-regional stratification of the world. Finally, we discuss the

sensitivity of the assumptions made in our analyses and conclude that, particularly in unstable

malaria endemic areas, a combination of integrated malaria control measures and sound water

management is essential to reduce the current burden of malaria in locations near irrigation or

dam sites sustainably. In addition, it is also crucial to include comprehensive health impact

assessment (HIA) procedures in the planning of all water resources development in malaria

endemic areas.

Materials and methods

Systematic literature review

We systematically reviewed the literature with an emphasis on research findings published

over the past 25 years on any form of water resource development and operation and its impact

on malaria transmission. Publications were searched through Medline (National Institutes of

Health, USA), the Environmental Sciences and Pollution Management Database (Cambridge

Scientific Abstracts, USA) and the website of the World Commission on Dams

(http://www.dams.org/). Pertinent dissertation abstracts, book chapters and unpublished

documents (‘grey literature’) were also consulted. We only included those studies that assessed

malaria prevalence or incidence before and after the construction of a water project, or

compared two or more settings that differed with regard to a water resource project.

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Malaria endemic countries according to WHO sub-regions

We utilized the recent WHO classification of countries into 14 epidemiological sub-regions,

which is based on a combination of WHO regions, and child and adult mortality rates, as

described in the annexes of the annual World Health Report (WHO, 2003). From this list we

included only those countries with high and moderate malaria transmission

(http://www.who.int/ith/chapter05_m08_malaria.html). Countries with low and focal malaria risk (e.g.

Kazakhstan) were excluded. The complete list of countries included in our review is given in

Panel 1.

Irrigated areas and affected population

For each country we compiled data on the total, agricultural, irrigated and rice harvested

areas using the most up to date data from the FAO database at the time of our work (2004)

(http://apps.fao.org/page/form?collection=Production.Crops.Primary&Domain=Production&servlet=1&language=EN&hostname=app

s.fao.org&version=default). The potential area for irrigation in the malaria endemic countries was also

derived from FAO using the following website: http://www.fao.org/ag/agl/aglw/aquastat/dbase/index2.jsp. We

calculated the sum of the areas for each individual sub-region utilizing data for the year 2000.

General population data were obtained from the latest United Nations figures (United

Nations, 2002).

We gathered statistics on population assigned to mixed irrigation schemes (at least 10%

of the area irrigated) from http://www.ilri.cgiar.org/InfoServ/Webpub/fulldocs/mappingPLDW/media/index.html

(Thornton et al., 2002). To have a second range (as the irrigation population provided by

Thornton and colleagues might be overestimated by a factor as high as 10) we based our

calculations on the irrigated area of each country and a hypothetical average population density

of 200 people/km2. Rural population densities vary from province to province and country to

country. For example in South Africa the population density was reported to be 100/km2 in the

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rural areas of the former homelands compared to only 21/km2 in the other parts of the country

(http://www.iwrms.uni-jena.de/watres_sa.html ). Since irrigation schemes are well developed

and highly attractive areas we assume a population density of 200 people/km2. An illustrative

example of population distribution over irrigated and non-irrigated areas comes from Kenya: in

the Bura and Mwea irrigation schemes in Kenya, population densities of 223 people/ km2 and

320 people/ km2 have been reported, respectively, whereas the nation-wide population density

in Kenya is several-fold lower, i.e. 54 people/ km2 in 2002 (Mwadime et al. 1996; Waiyaki 1987).

In order to determine the irrigation population in malaria endemic areas, we retrieved data

for each country on the percentage of the population living in malaria risk areas; the websites

used are presented in Panel 1. For each country we then determined the population at risk by

multiplying the sizes of the populations in irrigated areas by the fraction of the population living

in malaria endemic areas.

Calculation of the mosquito flight range around reservoirs of large dams and of populations at

risk

Components of dams include the reservoir, the upper catchment, possible irrigation

schemes and flood plains. The calculations presented in this report focus on the immediate

environment around the reservoir. An inventory of large dams in malaria endemic WHO sub-

regions, with their date of construction and the size of the reservoir was prepared based on

information obtained from the World Register of Dams (International Commission on Large

Dams, 1998).

First, in order to get an estimate of the population density near dam sites in WHO sub-

regions that are endemic for malaria, we collected information on displacement and

resettlement of population in relation to the size of the reservoir. Through consultation of two

publications available on the Internet we retrieved information on the number of people

relocated near several dam sites (http://www-

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wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/1997/02/01/000009265_3980728144037/Rendered/PDF/multi_page.pdf,

http://www-

wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/1997/01/01/000009265_3980728144045/Rendered/PDF/multi_page.pdf).

We standardized the calculated population density for the individual dams from their year of

construction to the year 2000 by factoring in the rural population growth of each country (United

Nations, 2002) and calculated the median for each of the relevant WHO sub-regions.

We collected data on the area of the reservoirs and the length of the dam for WHO sub-

regions 1 and 2 through consultation of the World Register of Dams. In case of the South

African dams we utilized the geo-referenced database on African dams (FAO, www.fao.org )

and the “Mapping Malaria Risk in Africa” map (MARA; www.arma.org.za ) in order to find out

which dams are located in malaria endemic area.

We classified all large dams in these sub-regions according to their reservoir area into four

groups as follows: (i) < 1 km2, (ii) 1- 10 km2, (iii) 10- 100 km2, and (iv) > 100 km2. Assuming a

reservoir with a hypothetical rectangular shape (see Figure 1) we calculated for each dam the

base (b) of the reservoir according to b=A÷ l, where “A” represents the area of the reservoir and

“l” the length of the dam. To get an idea of the shape of the reservoirs (whether the rectangle

has a long or short perimeter) we then calculated for each group the median of the ratio

base/length of the dams’ reservoirs. Assuming a typical flight range of mosquitoes of two km

(Boyd, 1949) from the borders of these rectangular reservoirs (A=(median b/l) b x b) we

determined for the four categories of large dams the area two km around the reservoirs (see

Figure 1).

We classified all large dams in the countries of WHO sub-regions 4–14 into only two categories

(since there are several thousand dams), namely (i) area of the reservoirs 100 km2, and (ii)

area of the reservoirs >100 km2. For each group we calculated the area of a two-km mosquito

flight range with the aid of two hypothetical rectangles of A1 = 15 l x l (for the small reservoirs

100 km2) and A2 = 500 l x l (for the large reservoirs >100 km2)

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Using the percentage of population in malaria-endemic regions for each country, we obtained an

estimate of the mosquito flight range around large dams in endemic areas. Multiplication of the

mosquito flight range areas with the obtained population density gave an estimate of the

population living within two km of all reservoirs of large dams for each sub- region in malaria

endemic areas.

Results

Causal web

The risk factor “development and operation of water project” comprises a number of

different components that are related to the transmission dynamics of malaria, which collectively

influence morbidity and mortality and hence the malaria burden. Figure 2 illustrates various

levels of causality between malaria and different types of water projects. In this report we focus

on irrigation and large dam sites. Through the generation of new water bodies, new mosquito

larval and adult habitats are created. The hydrological system and, probably to a lesser degree,

the atmospheric system might also be altered. Consequently, this will have an effect on the

development of malaria vector species and Plasmodia, their survival rates and longevity, and

most likely will result in increased mosquito densities. Without accompanying vector control

strategies this is likely to result in a higher risk of disease transmission. Factors such as

economic benefits from water resources development, personal protective measures, health-

seeking behaviour and acquired immunity must also be taken into account, as these factors

might counterbalance negative impacts. Finally, in all instances cultural values have important

implications for personal protection and treatment-seeking behaviour.

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Water projects: irrigation

People at risk and malaria burden

Table 1 summarizes DALYs lost due to malaria, total surface area, agricultural area, irrigated

area, rice harvested area, as well as total population, irrigation population and irrigation

population in malaria endemic areas (“population at risk”) for each of the relevant WHO sub-

regions:

Sub-Saharan Africa (WHO sub-regions 1 and 2)

WHO sub-regions 1 and 2 carry the main burden of malaria; 87.9% as expressed in

DALYs lost (WHO, 2004). In most of the countries of these two sub-regions malaria

transmission is stable, with seasonal or year-round transmission and 100% of the population

living in endemic areas. Exceptions are Botswana, Burundi, Ethiopia, Kenya, Namibia, Rwanda,

South Africa, Swaziland and Zimbabwe, where between 20 and 85% of the total populations live

in malaria endemic areas (data not shown). An. gambiae and An. funestus are the principal

malaria vector species in these sub-regions.

Though the agricultural area is approximately 39% of the total area, at present irrigated

agriculture or rice harvested areas represent only a marginal 0.2- 0.5% of the total surface area

in WHO sub-regions 1 and 2 (Table 1). While some countries have virtually no areas under

irrigation (e.g. Central African Republic: 0.02%), irrigation is more pronounced in others (e.g.

South Africa: 1.5%). As irrigation provides an opportunity for agriculture in arid areas and

stabilizes yields in regions with unpredictable rainfall, areas under irrigation continue to expand

in sub-Saharan Africa: the predicted irrigation potential is 39.3 Mio ha (see Table 1). This would

represent a 10-fold increase of the area currently under irrigation. We estimate that currently in

sub-regions 1 and 2 about 9 million people out of a total population of 605.5 million (1.5%) live

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close to irrigation schemes. Approximately, two thirds of those people live in malaria endemic

areas, and hence are at a risk of the disease.

Southeast Asia (WHO sub-regions 11 and 12)

An estimated 6.0% of the estimated global malaria burden occurs in WHO sub-regions 11

and 12 (WHO, 2004). Major malaria vectors in this region, which are known to breed in rice

fields or irrigation channels, include An. culicifacies, An. fluviatilis, An. philippinensis and An.

splendidus (Singh and Mishra, 2000). The percentage of population living in malaria endemic

areas ranges from 7% in Thailand to 95% in India (data not shown).

In contrast to WHO sub-regions 1 and 2, irrigated agriculture plays a much greater role in

Southeast Asia: 10.6% of the total surface area of these sub-regions is currently irrigated,

mainly with rice agriculture and the area under irrigation is expected to further expand

significantly, potentially up to 22.4% of the total area (Table 1). Between 145.1 and 771 million

people have been assigned to irrigation schemes, 122.9-659.6 million (7.7-41.5% of the total

population) in malaria endemic areas.

Eastern Mediterranean (WHO sub-region 6 and 7)

Subregions 6 and 7 in the WHO Eastern Mediterranean Region bear 4.8% of the current

estimated global malaria burden (WHO, 2004). An. arabiensis, An. subpictus and An. stephensi

are primary malaria vectors in Pakistan (Herrel et al., 2001), Sudan (Hamad et al., 2002),

Afghanistan (Rowland et al., 2002) and Yemen (al-Maktari and Bassiouny, 1999). In Saudi

Arabia, Afghanistan, Yemen and Iraq approximately 20-60% of the population and in all other

countries of these two sub regions 100% of the population live in malaria endemic areas (data

not shown).

Irrigated areas range from 0.04% in Djibouti, 0.45% in Somalia, 0.94% in Yemen, 1.5% in

Sudan, 4.6% in the Islamic Republic of Iran, 6.2% in Afghanistan, 8% in Iraq to 22% in Pakistan.

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This corresponds to an estimated irrigation population ranging from 0.09% in Yemen to 73% in

Pakistan.

An estimated 71.5-143.4 million people (with the great majority in Pakistan) were allocated to

irrigation (Table 1); 49.4-116 million of these live in malaria endemic areas.

The Americas, European and the Western Pacific Regions (WHO sub-regions 4, 5, 9 and 14)

Only an estimated 1.3% of the global malaria burden currently occurs in WHO sub-regions

4, 5, 9 and 14 (WHO, 2004). Irrigated areas account for less than 1% (WHO sub-region 4) up to

6.9% (WHO sub-region 9) of the total surface area (Table 1). In total, a large population (170.4-

982.5 million people) can be associated with irrigation. However, the majority of these live in

parts of the countries where no malaria transmission occurs (e.g. People’s Republic of China);

only 1.2-3.3% of the irrigation population (26.5-69.4 million people) is estimated to live in

malaria endemic areas.

Effect of irrigation on malaria

Our literature search yielded 19 studies that assessed the prevalence or incidence of

malaria in relation to irrigation projects. We have categorized these studies into the different

WHO sub-regions and the predominant epidemiological situations of malaria transmission.

Stable malaria is characterized by year-round transmission with some seasonal variations.

Inhabitants of stable malaria transmission areas have a high natural immunity and epidemics

are unlikely events. In contrast, transmission is not sufficient in the dry season to maintain

immunity in areas of seasonal or unstable malaria. In these areas there is a high potential for

epidemics to occur.

Table 2 summarizes studies carried out in areas of stable malaria transmission that

compared malaria incidence or prevalence rates among people living close to an irrigation

project with those observed in distant villages. Briefly, the majority of the studies revealed that

rice field inhabitants, despite high Anopheles densities throughout the year due to irrigation

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water, often have lower prevalence rates than people in control villages. Immunological as well

as socioeconomic factors and control programs strongly influence the parasitological

parameters. For example in the Kou valley, Burkina Faso, malaria prevalence rates ranged from

16-58% in an irrigated village, compared to 35-83% in a non irrigated village (Boudin et al.,

1992). Furthermore, in Mali, a two-fold reduction in the annual malaria incidence was observed

after the implementation of irrigation, although rice cultivation changed transmission from

seasonal to perennial (Sissoko et al., 2004).

Table 3 shows that in unstable malaria transmission areas, the introduction of irrigation

places the non-immune population at a high risk of acquiring the disease. It might alter malaria

transmission from seasonal to perennial and malaria endemicity from mesoendemic to

hyperendemic, as observed in Rosso, Richard Toll and Podor in the Senegal River Basin

(USAID, 1994) or the Gezira scheme (el Gaddal et al., 1985). A recent study conducted in a dry

coastal area of Peru, found malaria incidence five-fold higher in villages with houses in close

proximity to irrigated fields and irrigation canals, compared with villages in the non-irrigated area

(Guthmann et al., 2002). Irrigated villages in the Rusizi valley of Burundi, an area of unstable

malaria transmission, had higher malaria prevalence rates and a 150-fold higher vectorial

capacity of A. arabiensis when compared to neighboring non-irrigated villages; similar

observations were made for malaria prevalence rates and vectorial capacity of local

anophelines in Sri Lanka and Lao People’s Democratic Republic (Coosemans and Mouchet,

1990; Dixon and Pinikhana, 1994; Kobayashi et al., 2000). In Sri Lanka, a five-fold higher

malaria incidence was reported following the introduction of Mahaweli systems H and B (IIMI,

1986). Another study, comparing the malaria prevalences in four villages, two relatively new

and two ancient, of which two were irrigated and two non-irrigated, showed prevalence rates of

4.8% and 2.5% for irrigated and non-irrigated, respectively. Both the irrigated and non-irrigated

new villages had much higher prevalence rates than the old ones, which was explained by

changing livelihoods, less knowledge on malaria and fewer personal protection measures in the

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new villages (Dixon and Pinikhana, 1994). In a more recent study, irrigated rice cultivation in

the Uda Walawe region in Sri Lanka was found to have a lower malaria risk than non-irrigated

areas (Klinkenberg et al. 2004) – This claim was based on the assumption that communities in

the area where irrigation was developed were originally ecological replicates of the non-irrigated

communities.

Water projects: large dams

Population density near large dam sites

In Table 4 we present data on the number of displaced people in relation to the size of the

reservoir for 71 dams. Between 1,000 (Epupa dam, Namibia) and 1.2 million people (planned

Three Gorges dam, People’s Republic of China) have been or will be displaced due to large

dam building. Standardizing the populations at the year of construction of the individual dams to

the year 2000 we find that densities are as small as 1.2 people/km2 and as large as 2478

people/km2. The median population density calculated for each WHO sub-region ranges

between 25.8 people/km2 in WHO sub-region 2 and 764 people/km2 in WHO sub-region 7.

People at risk and malaria burden

Sub-Saharan Africa (WHO sub-regions 1 and 2)

In Table 5a and 5b we list the number of large dams, the reservoir areas, the estimated

areas of mosquito flight range, and the population at risk for WHO sub-regions 1 and 2. In these

two sub-regions where 87.9% of the malaria burden is concentrated 1,039 large dams have

been constructed. Employing the geo-referenced database provided by FAO, we found that out

of 539 South African dams only 25 are located in the malaria endemic parts of the country. For

287 large dams information on the size of the reservoir and the length of the dams is given in

the World Register of dams (International Commission on Large Dams, 1998). These dams

have, in total, a reservoir size of 24,792 km2. Calculation of the median of the ratio, base/length,

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of their reservoirs revealed that those dams, with a reservoir size < 1 km2 were almost square

shaped (median ratio base/length approximately 1). Those dams with reservoir sizes > 100 km2

had a much longer base than length (median ratio base/length 479 in WHO sub-region 1, and

637 in WHO sub-region 2) (see Table 5a and 5b).

Many African dams serve irrigation purposes. While in WHO sub-region 1 all dams are

located in malaria endemic area, we estimate that in WHO sub-region 2 (excluding South Africa)

95% of the total reservoir area is situated in malaria endemic areas. The mosquito flight range

comprises 45,594 km2 from the borders of the reservoirs at full water level in endemic areas,

corresponding to 3.1 million people at risk.

Southeast Asia (WHO sub-regions 11 and 12)

In WHO sub-regions 11 and 12 there are 4,431 large dams; 4,010 of these are located in

India. The World Register of Dams lists specific data on the reservoirs for 2,789 of these. With

reservoirs filled to full capacity, their combined, maximum surface area comes to 53,265 km2

(Table 6g-h). We estimate that the area at risk covers, at maximum water level, 30,736 km2 and

harbors 10.9 million people.

Eastern Mediterranean (WHO sub-regions 6 and 7)

There are 156 large dams located in the countries selected for WHO sub-region 7. The

majority of these are located in Pakistan (71 dams) and the Islamic Republic of Iran (66). We

estimate that 57% of this area is located in malaria endemic regions. We find that in these sub-

regions 1.9 million people live within the estimated mosquito flight area of 2,509 km2, and hence

might be at risk of acquiring the disease, which is attributable to dam sites.

We could not retrieve data on the size of the reservoirs for the 38 large dams of Saudi Arabia

(WHO sub-region 6).

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The Americas, Europe and the Western Pacific sub-regions (WHO sub-regions 4, 5, 9 and 14)

A total of 4,079 large dams have been constructed in the countries of sub-regions 4, 5, 9 and

14, which we selected for our review. The countries with the highest number of large dams in

these sub-regions are China (1,905), Turkey (625), Brazil (594) and Mexico (536). The reservoir

areas range from 385 km2 (large dams of sub-region 5) to 58,480 km2 (large dams of sub-region

12).

We estimate that in total 2.3 million people live close enough to reservoirs in endemic areas to

be at risk of transmission.

Effect of large dams on malaria

We summarize studies that assessed malaria incidence and prevalence, respectively,

after the construction of a dam in both stable (Tables 6a, 6b), and unstable malaria transmission

areas (Tables 7a, 7b). We compiled studies that investigated malaria in dam sites compared to

a distant site (Tables 6a, 7a) as well as studies that assessed pre- and post-construction

disease transmission parameters (Tables 6b, 7b). Increases in malaria cases near dam sites

were reported both in stable and unstable malaria transmission areas. For example, after the

construction of the Bargi dam in India a 2.4- fold increase in malaria cases and an over four-fold

increase in annual parasite incidence among children were recorded in villages closer to the

dam (head end) compared to more distant villages (tail end) and a strong increase in the

hospital prevalence in partially submerged villages could be detected (Singh et al., 1999; Singh

and Mishra, 2000). In Tigray in northern Ethiopia, numerous small dams and irrigation systems

were put in place at altitudes above 1800 m with the broad aim of reducing dependence on rain-

fed agriculture, and improving overall food production. Comparative appraisal of a series of

cross-sectional malaria surveys among children carried out in villages in close proximity to these

newly constructed small dams and in villages farther away, revealed a seven-fold increase in

malaria risk for those residing near dams (Ghebreyesus et al., 1999).

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It was also found that dam areas displayed a lower malaria transmission compared with

distant settings when integrated vector management or other control interventions have been

applied. For example, in Uttaranchal, India, a study, which compared the parasitological indices

in a dam area to forest or plain areas, recorded a prevalence and annual parasite incidence of

zero in the dam area. Better economic status, insecticide spraying and more awareness

towards health maintenance were described to be the main factors accounting for the lack of

malaria transmission at the dam site (Shukla et al., 2001). In addition, in Thailand no increase of

malaria incidence was observed near the Nong Wai dam and Ubol Ratana dam, probably

because of indoor resildual spraying of all houses with DDT, compared to the Srinagarind dam,

where an increase in malaria prevalence was reported and for which we are not aware of any

vector control measures (Bunnag et al., 1979; Harinasuta et al., 1970).

Conclusion

In Figure 3 we illustrate key numbers. The global population living in close proximity of the

reservoirs of large dams in malaria endemic areas is small: in total, only 18.3 million people, the

majority of them living in India. On the other hand as many as 851.3 million people live in or

close to irrigation systems in malaria endemic areas. In sub-Saharan Africa, which has 87.9% of

the estimated global malaria burden, only 9.4 million people live near large dam reservoirs and

irrigation sites. In contrast the remaining sub-regions have a maximum of 860.3 million people

near large dam and irrigation sites and only 12.1% of the global malaria burden. Thus, on first

sight no clear relationship emerges from this systematic literature review between the risk factor

“development and operation of water projects” and malaria risk. Our review of studies

conducted in these settings confirms that this association is very complex and depends strongly

on the epidemiological setting, socioeconomic parameters and control strategies.

19

Discussion

We have presented the first comprehensive review of the literature with an emphasis on

the global and regional burden of malaria in relation to irrigation and large dams. It was not

possible to quantify the attributable fraction of the malaria burden due to dam building and

irrigation for the individual sub-regions (e.g. employing the methodology of comparative risk

assessment) due to a lack of high-quality data comparing malaria rates before and after

implementation of water resource development projects). Most available studies are based on

the comparison of two villages. Care needs to be taken in the interpretation of these results,

because subtle differences may exist in ecological and epidemiological features, even between

neighbouring villages. Sadly, even the extensive report authored by the World Commission on

Dams, derived from 17 exhaustive reviews on dams, allocates a mere two pages to health

(Sleigh and Jackson, 2001). It is unfortunate that no systematic inventory of small dams and

only very few studies assessing their impact on malaria are currently available. Their number

have been rapidly rising and responsibility for their planning and operation resorts mostly in the

informal sector. For example, about an estimated 15,000 small dams have been constructed in

Zimbabwe, and more than 50,000 small dams were built in Kenya within three years during the

late 1950s (Jewsbury and Imevbore, 1988). Their impact on the frequency and transmission

dynamics of malaria could be significant, as their combined shoreline is much greater than that

of large dams when adjusted for water surface. Furthermore, studies investigating the

consequences of the construction of flood control, water projects for recreational purposes, or

pumps and drains for water supply and sanitation on malaria have, to our knowledge, not been

conducted thus far.

Our calculations depended on a number of assumptions and they are therefore inevitably

subject to uncertainty. The possibility that we have overestimated the risk cannot be ruled out.

First, we assumed that the whole population assigned to irrigation in endemic areas is at

risk from malaria. Not all forms of irrigation, however, present similar risks for the local

20

population. There are three common types of irrigation systems: (i) pressurized distribution

through sprinkler or trickle systems, (ii) gravity flow distribution as surface irrigation, and (iii)

subsurface irrigation. If well maintained, sprinkler, drip irrigation and subsurface irrigation

provide irrigation water without creating suitable breeding sites for mosquito vectors

(Amerasinghe, 1987).

Second, we did not include annual fluctuations of the water level of reservoirs, which in

turn has important implications for the estimation of the population at risk from large dam sites.

At the end of the low water period, the area of the reservoir, and thus the mosquito flight range

area, is, in general, considerably reduced. For example, the reservoir area of the Manantali dam

decreases from 477 km2 to 275 km2 at the minimum operating level of the dam (Jobin, 1999).

Furthermore, it is unlikely that every manmade reservoir actually provide optimal breeding

conditions for malaria vectors. Each Anopheles species is characterized by typical habitat

preferences, including exposure to sunlight, turbidity of the water, presence of vegetation, pH or

nitrate and phosphate concentrations of the water (van der Hoek et al., 1998). These

environmental factors are specific for each dam and its shoreline. In addition, human settlement

around the reservoirs might not be possible at several dam sites due to the local topography.

Third, we have assumed that the population densities around manmade reservoirs are

similar to the ones of the resettled communities and that the population near the reservoir is

subjected to the same population growth as the rural areas of the respective countries.

However, new villages might have been constructed much further away than the two km

estimated mosquito flight range from the reservoir and, consequently, the population would not

be at risk. On the other hand, dams are characterized by marked demographic impacts, in

particular during the construction phase. They attract travelers, miners or farmers, who often

have low immunities to malaria. Thus, during construction the population might be similar or

possibly even greater than before. As the construction work comes to an end, however,

21

temporary workers leave and the population density consequently decreases. New migrants

(e.g. fisher folk) may arrive, attracted by the opportunities offered by the recently filled reservoir.

Fourth, as a geo-referenced database exists only for African dams, it is difficult to

determine the exact population at risk from dams in countries that are only partially endemic for

malaria on the remaining continents. Without knowledge of the geographical coordinates, we

would have presumed that 20% or more than 100 of the 539 South African large dams and their

reservoirs are located in malaria endemic areas. In reality, however, only 25 of these are

located in areas where malaria transmission occurs. Similarly, to calculate the irrigation

population at risk in partially endemic countries we had to assume that the total population and

the population living near irrigation schemes have the same distribution regarding malaria

transmission.

The fact that a large number of people theoretically at risk will not suffer from an increased

malaria burden also needs to be considered. Many inhabitants live in areas with stable malaria

transmission. It has been discussed extensively that in these areas, characterized by

inhabitants with high natural immunity, irrigation or dam building often does not cause an

increase in malaria transmission. Improved socio-economic variables, effective vector control

programmes or changes in health-seeking behavior are also pivotal in determining whether a

water project triggers an increase in malaria transmission (Ijumba et al., 2002). A water

resource development project might also replace the most endophilic and anthropophilic malaria

vectors by new vectors with a lower vectorial capacity, as for example the replacement of An.

funestus by An. arabiensis in irrigation schemes in East Africa (Ijumba and Lindsay, 2001).

Furthermore, in irrigated villages in Mali, high Anopheles densities were correlated with low

anthropophily, low sporozoite indices and low mosquito survival rates. Density dependent

competition for food at the mosquitoes’ larval stages may influence the longevity of adult

mosquitoes. A significant use of mosquito nets or antimalarial drugs due to a greater wealth in

irrigated villages and areas near a dam, or a higher compliance rate in the use of mosquito nets,

22

often driven by the nuisance caused by higher mosquito (not necessarily vector) densities, may

also play an important role in these findings (Dolo et al., 2004). Another explanation for lower

malaria transmission in irrigated villages might be differences in the presence and distribution of

cattle in the villages. Domestic animals are often kept close to the house and insecticide treated

nets might divert mosquitoes away to the unprotected animals (Dolo et al., 2004; Ijumba et al.,

2002).

We have highlighted that in particular countries, characterized by areas with seasonal or

unstable malaria, irrigation might cause epidemics and prolong seasonal transmission. In parts

of India irrigation has changed the malaria transmission area from epidemic to endemic. For

example in the Thar Desert An. culicifacies, which was previously not present, has taken over

from the original vectors causing a high percentage of P. falciparum malaria (Tyagi, 2004). To

the extend that establishment of irrigation schemes and dams in arid and other unstable

transmission areas is not complete, integrated malaria control has to be pursued. Vector control

by means of water management has been carried out with success for several decades

particular in areas with unstable malaria transmission. The first studies on intermittently irrigated

rice fields, which found greatly reduced Anopheles densities and often increased rice yields,

have been carried out more than 70 years ago (Keiser et al., 2002). At the same time,

elimination of mosquito breeding sites have been achieved in rivers and streams of Sri Lanka

and Malaysia by means of different types of siphons and small dams (Konradsen et al., 2004).

Significant reductions of Anopheles breeding were achieved in the cascading reservoirs of the

Tennessee River Valley by implementation of several types of environmental and water

management measures. Among them was an integrated operating rule consisting of a

fluctuation cycle of 0.3 m amplitude over 7-10 day periods (Jobin, 1999).

We conclude that future water resource development should include a comprehensive

assessment of potential health impacts, including malaria. An initial and rudimentary knowledge

base to serve as evidence for such assessments is made up of the literature reviewed for this

23

report. Clearly, more research is needed to strengthen our knowledge base and to allow an

accurate attribution of the fraction of a country’s malaria burden to irrigation schemes and

manmade reservoirs. A combination of integrated malaria control measures and sound water

management is essential to reduce the current burden of malaria in locations near irrigation or

dam sites sustainably.

24

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Panel 1: Countries included in our analysis based on WHO epidemiological sub-regions and propensity for malaria transmission. Africa Percentages of the population in malaria endemic areas available at: http://www.rbm.who.int/amd2003/amr2003/table6.htm WHO sub-region 1: Angola, Benin, Burkina Faso, Cameroon, Chad, Comoros, Equatorial Guinea, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Madagascar, Mali, Mauritania, Niger, Nigeria, Sao Tome and Principe, Senegal, Sierra Leone, Togo WHO sub-region 2: Botswana, Burundi, Central African Republic, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Eritrea, Ethiopia, Kenya, Malawi, Mozambique, Namibia, Rwanda, Swaziland, Uganda, (South Africa), United Republic of Tanzania, Zambia, Zimbabwe The Americas Percentages of the population in malaria endemic areas available at: http://www.emro.who.int WHO sub-region 4: (Argentina), Belize, Brazil, Colombia, Costa Rica, Dominican Republic, French Guiana, Guyana, Honduras, Mexico, (Panama), Paraguay, (Suriname), (Venezuela) WHO sub-region 5: Bolivia, (Ecuador), Guatemala, Haiti, Nicaragua, Peru Eastern Mediterranean Percentages of the population in malaria endemic areas available at http://165.158.1.110/english/hcp/hctmalaria.htm WHO sub-region 6: Saudi Arabia WHO sub-region 7: Afghanistan, Djibouti, (Islamic Republic of Iran), (Iraq), (Somalia), Sudan, Pakistan, Yemen Europe Percentages of the population in malaria endemic areas available at: www.emro.who.int/rbm/meetings/muscat02/Presentations/Sunday/Malaria%20Situation%20in%20EUR%20(M.Ejov).ppt WHO sub-region 9:, Georgia, Tajikistan, Turkey, (Uzbekistan) South-East Asia Percentages of the population in malaria endemic areas available at: http://whqlibdoc.who.int/searo/2002/SEA_MAL_229.pdf WHO sub-region 11: Indonesia, Sri Lanka, (Thailand) WHO sub-region 12: Bangladesh, (Bhutan), Democratic People’s Republic of Korea, India, Myanmar, Nepal Western-Pacific Percentages of the population in malaria endemic areas available at: http://www.wpro.who.int/themes_focuses/theme1/focus2/t1f2country.asp WHO sub-region 14: Cambodia, (China), Lao People’s Democratic Republic, (Malaysia), Papua New Guinea, (Philippines), Solomon Islands, Viet Nam

Countries marked in brackets < 20% of the population at risk of malaria

Table 1: Malaria burden, irrigated areas and population at risk stratified according to 14 WHO sub-regions (2001)

Region DALYS lost due to malariaa

in 2002(x1000)

Total surface area (x103 km2)b

Agricultural area in 2000 (*1000 km2)b

Area Rice paddies in 2000 (x103 km2)b

Irrigated area in 2000 (x103 km2)b

Potential area for irrigation (x103 km2)b

Total Population in 2002 (x106)c

Estimated population in irrigated agricultural area (x106)d

Population at risk (x106)e

WHO sub-region 1

20,070 (43.2%) 9,702 3,853 (39.6%) 50.9 (0.52%) 20.0 (0.21%) 209.2 (2.1%) 278,2 4.0 (1.4%) 4.0 (1.4%)

WHO sub-region 2 20,785 (44.7%) 9,184 4,092 (44.5%) 18.2 (0.20%) 24.7 (0.27%) 183.5 (2.0%) 359.1 4.9 (1.4%) 2.3 (0.6%)

WHO sub-region 4 86 (0.2%) 16,522 6,397 (38.7%) 50.1 (0.30%) 131.7 (0.80%) 591.5 (3.6%) 414.8 26.3-28.8 (6.3-6.9-%) 12-12.9 (2.8-3.1%)

WHO sub-region 5 25 (0.05%) 1,650 889 (53.8%) 9.5 (0.58%) 24.8 (1.50%) 253.3 (15.6%)f 73.8 4.9-5.4 (6.6-7.3%) 3.3- 3.5 (4.4-4.7%)

WHO sub-region 6 92 (0.2%) 2,150 1,737 (80%) No record 16.2 (0.75%) No record 23.5 3.2-3.5 (13.6-14.9%) 1.8- 2.0 (7.6-8.5%)

WHO sub-region 7 2,158 (4.6%) 7,230 3,318 (45.8%) 29.7 (0.41%) 341.5 (4.70%) 105.9 (1.5%)g 327.8 68.3-139.9 (20.8-42.6%) 47.6-114.0 (14.5-34.7%)h

WHO sub-region 9 20 (0.05%) 1,435 742 (51.7%) 2.0 (0.14%) 99.6 (6.90%) 106.1 (7.3%) 107.4 19.7-19.9 (18.3-18.5%) 4.8-6.2 (4.4-5.8%)

WHO sub-region 11 502 (1.1%) 2,483 659 (26.5%) 223.8 (9.0%) 104.7 (4.20%) 275.2 (11.4%) 298.2 20.9-132.3 (7.0-44.3%) 7.0-61.1 (2.3-20.4%)

WHO sub-region 12 2,275 (4.9%) 4,422 2,085 (47.1%) 639.4 (14.5%) 636.0 (14.4%) 1,248.6 (28.2%) 1,291.5 127.2-639.5 (9.8-49.5%) 117.6- 598.5 (9.1-46.3%)

WHO sub-region 14 441 (1.0%) 11,469 5,843 (51.2%) 453.3 (4.10%) 597.6 (5.4%) 745.7 (6.5%) 1,510.7 119.5-928.4 (7.9-61.4%) 6.4-46.8 (0.4-3.1%)

a Source: (WHO, 2004) b: Source: http//www.fao.org c: Source: (United Nations, 2002) d Range obtained from “Mapping people, livestock production systems, livestock and poverty- the global picture” and an estimated population density of 200 people/km2 in irrigated areas e Multiplication with the fraction of population living in malaria endemic areas f The potential irrigation area for Nicaragua was estimated from data on the total potential cultivable area g The potential irrigation area for Pakistan was estimated from the total potential cultivable area, no data for Afghanistan, Yemen, Djibouti and the Islamic Republic of Iran were included h No data on the percentage of the population at risk was available for Iraq, we estimated that approximately 20% of the irrigation population in Iraq is at risk .

30

Table 2: Influence of irrigation on malaria prevalence and/or incidence in areas of stable and seasonal malaria transmission

Study site, period, Reference Population sample

Irrigation scheme or construction

Overall malaria prevalence/incidence in irrigated village

Overall malaria prevalence/incidence in non irrigated village

Comment

Africa (WHO sub-region 1) Kou valley, Burkina Faso, 1985-1986 (Boudin et al., 1992)

Children (aged 0-14 years) from 31 families

Rice fields Prevalence 16% (May)- 58% (October)

Prevalence 35.4% (May)- 82.5% (October)

High consumption of chloroquine due to better socio-economic status

Kou valley, Burkina Faso (Carnevale and Robert, 1987)

2,362 individuals

Rice fields Prevalence 44.5% (January)-33.9% (October)

Prevalence 60.5% (January)-58.49% (October)

Epidemiological paradox: increased use of mosquito nets; shift in biting behaviour?

SEMRY rice development, Cameroon 1981 (Couprie et al., 1985)

924 individuals (all age groups)

SEMRY I, II 35 000 ha lake zone for rice development 5300 ha rice

April 1981: Prevalence 3.0-7.6% (3 villages close to lake and rice irrigation)

April 1981: Prevalence: 3.1% (50km distance from lake)

SEMRY II rice scheme Mayo-Danai Cameroon 1979-85 (Audibert et al., 1990)

4,611 children (aged 2-9 years)

SEMRY I, II 35 000 ha lake zone for rice development 5300 ha rice

Before irrigation: March 1979 prevalence 13.8%- After irrigation: November 1979 prevalence 30.1% (rainy season), March 1981 prevalence 11.5%, November 1981 prevalence 7.1%, April 1985 12.9%

The Gambia 1991 (Thomson et al., 1994) 1,465 children (aged 1-4 years)

River Gambia and rice swamps

Prevalence 34.2% Prevalence 28.7%- 71.2%

Low prevalence rates close to productive breeding sites (could be explained by use of mosquito nets)

Niono, Mali 1995 (Sissoko et al., 2004) 3,669 children (aged 0-14 years)

Rice irrigation Prevalence 31.3% Annual incidence 0.3 (per 1000)

Prevalence 46.5% Annual incidence 0.7 (per 1000)

Senegal river central valley, Senegal (Faye et al., 1993)

Children (aged 0-9 years)

Rice irrigation Prevalence 8.7% (July), 8.3% (November)

Prevalence 16.5% (July), 7.1% (November)

No increased transmission

Ferlo’s water launching, Senegal, 1996 (Faye et al., 1998)


Prevalence 37.6% (September, October)

Prevalence 34.3% (September, October)

Moyamba district, Sierra Leone, 1991 1,106 Rice swamps Prevalence 38.8- 58% Prevalence 57.1%

31

(Gbakima, 1994) individuals (several swamp sites)

Africa (WHO sub-region 2) Côte d’Ivoire (Henry et al., 2003)

Rice production systems Single cropping: annual malaria incidence 0.6 Double cropping: annual malaria incidence 0.8 (per 1000)

No irrigation: annual malaria incidence 0.9 (per 1000)

Different immunity acquisition within the three ecosystems, double cropping system extends malaria risk in the beginning of the dry season

Lower Moshi area Tanzania 1994-1995 (Ijumba et al., 2002)


Rice fields and sugar cane fields

Prevalence 12.5% (rice field) 16.9% (sugar-cane)

Prevalence 29.4% Use of mosquito nets due to better financial status

Sudan (WHO sub-region 7) Gezira, Sudan (el Gaddal et al., 1985) Population

Gezira 2 Million

Rice, groundnut, vegetables

Before introduction of irrigation: Malaria was not an important health problem in the area After introduction of irrigation: Prevalence up to 20%

India (WHO sub-region 12) Gujarat, India 1978 (Jayaraman, 1982; Mistry and Purohit, 1990)

Mahi Kadana project completed 1960

Increase in incidence: Annual parasite index (API) 1961 0.01 API 1969 0.91 API 1971 11.8 API 1975 26.9 API 1976 37.9

Meerut, Gurgaon, India 1982 (Sharma and Uprethy, 1982)

Population 10,048 irrigated village and 10,249 non irrigated villages

Incidence 57 cases (June), 81 cases (October)

Incidence 10 cases (June), 9 cases (October)

32

Table 3: Influence of irrigation on malaria prevalence and/or incidence in areas of unstable malaria transmission

Study site, period, Reference Population sample Irrigation scheme or construction

Overall malaria prevalence/incidence in irrigated village

Overall malaria prevalence/incidence in non irrigated village

Africa (WHO sub-region 2) Burundi, 1981 (Coosemans, 1985) Not given Rice fields Prevalence 24.4% (February)-

69.2% (June) Prevalence 4.5% (January)- 29.6% (July)

South America (WHO sub-region 5) Sullana, Peru 1996-97 (Guthmann et al., 2002)

Population 12,432 Cotton, fruit, maize, rice fields

Incidence rate: 116.7 (per 1000) Incidence rate: 2.9-20.4 (per 1000)

Sri Lanka (WHO sub-region 11) Lunvgamvehera Sri Lanka 1987 (Dixon and Pinikhana, 1994)

1,771 individuals Irrigation project Prevalence 4.8% Prevalence 2.5%

Mahaweli System C (International Irrigation Management Institute, 1986)

Increase in malaria cases: System C: 1982 1,189 pos/7642 exposed System C: 1985 2045 pos /7821 exposed System H and B 5 fold increase

Laos (WHO sub-region 14) Nongceng, Laos 1998 (Kobayashi et al., 2000)

108 individuals Rice fields Prevalence 16.3% (September)-28.6% (February)

Prevalence 5-10% (earlier study)

33

Table 4: Estimation of population density near dam sites standardized for the year 2000 Population density (people/km2)

Region Name of dam (country) Year of

constructionEstimated number of

people displaced

Area reservoir (km2)

Year of dam construction Year 2000

WHO sub-region 1

Akosombo (Ghana) Kpong (Ghana) Manantali (Mali) Selingue (Mali) Dadin Kowa (Nigeria) Kiri (Nigeria) Kainji (Nigeria) Nangbeto (Togo)

1965 1981 1993 1982 1988 1982 1986 1987

80,000 6,000 12,000 12,000 26,000 19,000 50,000 11,000

848 35 477 430 300 110 1,260 180

94.3 171.4 25.1 27.9 86.7 172.7 39.7 61.1

173.6 279.4 28.3 38.7 102.3 305.7 48.0 80.1 Median: 91.2

WHO sub-region 2 Kossou (Côte d’Ivoire) Kiambere (Kenya) Epupa (Namibia) Cahora Bassa (Mozambique) Kariba, Zambia (Zimbabwe)

1972 1988 proposed 1974 1959

75,000 6,000 1,000 25,000 57,000

1,780 25 350 2,660 5,100

42.1 240.0 2.9 9.4 11.2

90.3 291.0 2.9 12.2 25.8 Median: 25.8

WHO sub-region 4 Yacyreta (Argentinia) Aqua Vermelha (Argentina) Piedra del Aguila (Argentina) Salto Grande (Argentina) Tucurui (Brazil) Itaparica (Brazil) Itaipú (Brazil) Sobradinho (Brazil) Ita (Brazil) Foz de Areira (Brazil) Marimbondo (Brazil) Guatape (Colombia) Guavio (Colombia) Upia (Colombia) Cerron Grande (El Salvador) El Cajón (Honduras) La Angostura (Mexico)

1994 1979 1991 1979 1984 1986 1983 1979 1998 1980 1975 NK 1989 NK 1977 1985 1974

50,000 4,345 9,000 8,000 30,000 49,500 59,000 65,000 11,500 8,400 5,500 5,000 5,500 5,000 13,339 4,694 5,500

1,720 643 292 783 2,430 800 1,350 4,150 138 167 438 63 14 396 139 94 644

29.0 6.8 30.8 10.2 12.3 61.8 43.7 15.6 83.3 50.3 12.6 78.8 381.9 12.6 96.0 49.9 8.5

29.0 6.1 30.0 9.1 9.9 45.7 35.0 12.3 83.0 39.7 9.7 78.8 381.0 12.6 95.9 58.1 9.8 Median: 30

WHO sub-region 5 No record WHO sub-region 6 No record

WHO sub-region 7 Tarbela (Pakistan) Mangla (Pakistan)

1976 1967

96,000 90,000

242 253

396.6 357.0

723.8 804.3 Median: 764

WHO sub-region 9 Aslantas (Turkey) Ataturk (Turkey) Sir (Turkey) Keban (Turkey) Karakaya (Turkey)

1984 1991 1991 1974 1987

5,000 40,000 7,000 30,000 20,000

49 817 47.5 675 298

102.0 49.0 147.4 44.4 67.1

97.0 50.3 153.1 43.3 67.0 Median: 67.0

WHO sub-region 11 Kedung Ombo (Indonesia) Cirata (Indonesia) Kota Panjang (Indonesia) Saguling (Indonesia) Victoria (Sri Lanka)

1989 1988 1997 1986 1984

25,000 56,000 24,930 60,000 45,000

46 62 124 49 23

534.5 903.2 201.0 1234.6 1982.3

527.6 892.5 199.0 1,256.0 2,342.7

34

Kothmale (Sri Lanka)Pak Pak Mun (Thailand) Ubol Ratana (Thailand) Srinagarind (Thailand) Khao Laem (Thailand)

1988 1990 1986 1981 1986

13,000 8,000 30,000 6,400 10,800

9.5 60 410 419 388

1368.4 133.3 73.2 15.3 27.8

1,525.7 150.5 88.7 20.0 33.7 Median: 363.3

WHO sub-region 12 Kaptai (Bangladesh) Bargi (India) Sardar Sarovar (India) Kabini (India) Nagarjunasagar (India) Pong (India) Tehri (India) Bedhi (India) Godavari (India) Sapta Kosi (Nepal) Khali Kola (Nepal)

1962 1990 2001 1974 1974 1974 1997 NK NK Proposed Proposed

100,000 113,600 320,000 15,000 28,000 150,000 100,000 5,100 38,100 75,000 40,000

777 809.0 376 61 285 290 42 124 1,008 195 108

128.7 140.4 851.3 245.9 98.3 517.2 2,380.9 41.1 37.8 384.6 370.4

269.5 162.8 851.3 367.5 147.3 773.6 2,478.0 41.1 37.8 384.6 370.4 Median: 367.5

WHO sub-region 14 Sambor (Cambodia) Strung Treng (Cambodia) Three Gorges (China) Shuikoi (China) Yantan (China) Dongiian (China) Sanmenxia (China) Wuqiangxi (China) Longtan (China) Nam Ngum (Lao PDR) Nam Theun 2 (Lao PDR) Nam Ou 2 (Lao PDR)

Proposed Proposed 1994-2008 1993 1995 1989 1960 1996 2005 1994 2007 (planned)2007 (planned)

5,120 9,160 1,200,000 67,000 40,000 53,000 319,000 306,000 73,392 4,400 5,700 26,200

880 640 1,084 94 121 160 799 170 370 58 450 107

5.7 14.3 1,107.0 712.8 330.6 331.2 399.2 1,800.0 198.3 75.9 12.7 244.8

5.7 14.3 1,107.0 695.0 322.1 323.1 591.8 1,746.0 198.3 83.2 12.7 244.8 Median: 244.8

NK = not known

35

Table 5 Number of large dams, reservoir size, estimated area of flight range and population at risk for the different sub-regions a.) WHO sub-region 1 Reservoir sizes (*103 m2)

Number of dams

Total size reservoir (x103m2)

Median base/length of dam Area flight range (x103m2) (full water level)

Area flight range for all large dams (x103m2)* (full water level)

People at risk (full water level)

38-880 10 5,833 0.9 31,821 1,00-9,000 25 123,600 2.5 110,895 11,140-35,000 11 269,145 37.8 426,588 112,000-8482,250 15 12,355,450 479 9,763,761 61 12,754,028 10,333,065 28,932,589 2,638,598 * No data available on the area of the reservoir of 118 dams b.) WHO sub-region 2 Reservoir sizes (*103 m2)

Number of dams a

Total size reservoir (x103m2

Median base/length of dam

Area flight range (x103m2) (full water level)

Area flight range for all large dams (x103m2)* (full water level)

Area flight range for endemic dams (x103m2) (full water level)

People at risk (full water level

25-960 100 47,396 2.5 73,414 1,010-8,700 95 279,681 7.1 215,808 10,000-91,050 23 706,151 36.1 668,796 120,000-5100,000 8 11,005,700 637.4 10,620,121 226 12,038,928 11,578,139 17,725,823 16,662,273 429,887 *No data available on the area of the reservoir of 120 dams. a.) Only the 25 South African dams located in endemic area have been included. c.) WHO sub-region 4 Reservoir sizes (*103 m2)

Number of dams


Estimated Median base/length of dam


Area flight range for all dams (x103m2) (full water level)



25-100,000 516 4,643,105 15 1,138,457 100,000- 53 23,772,133 500 13,830,507 569 28,415,238 14,968,964 36,541,108 12,789,387 383,670 *No data available on the area of the reservoir of 820 dams d.) WHO sub-region 5 Reservoir sizes (*103 m2)

Number of dams






People at risk1 (full water level)

25-100,000 20 115,600 15 190,126 100,000- 1 270,000 500 1,485,089 21 385,600 1,675,215 4,786,331 2,823,935 98,837 No data available on the area of the reservoir of 39 dams 1.) The population density of WHO sub region 4 has been applied e.) WHO sub-region 7 Reservoir sizes (*103 Number Total size Estimated Median Area flight range Area flight range for Area flight range People at risk (full

36

m2) of dams reservoir m2 base/length of dam (x103m2) (full water level)

all dams (x103m2) (full water level)

for endemic dams (x103m2) (full water level)

water level)

25-100,000 23 140,736 15 208,493 100,000- 5 921,860 500 2,733,561 28 1,062,596 2,942,054 6,514,548 4,429,892 Not known 66 1,366,230 1,916,876 No data available on the area of the reservoir of 62 dams f.) WHO sub-region 9 Reservoir sizes (m2) Number

of dams Total size reservoir (x103m2






25-100,000 616 2,832,826 15 1,547,976 100,000- 9 16,425,140 500 11,498,415 627 19,257,966 13,046,391 13,649,812 8,053,389 539,577 *No data available on the area of the reservoir of 29 dams g.) WHO sub-region 11 Reservoir sizes (*103 m2)

Number of dams







25-100,000 279 1,286,097 15 605,069 100,000- 10 3,902,830 500 5,611,354 289 5,188,927 6,216,423 7,442,500 967,525 351,211 *No data available on the area of the reservoir of 57 dams h.) WHO sub-region 12 Reservoir sizes (*103 m2)

Number of dams







25-100,000 2,432 8,304,366 15 1,518,326 100,000- 68 38,472,269 500 17,591,151 2,500 46,776,635 19,109,477 30,689,821 28,846,126 10,600,537 *No data available on the area of the reservoir of 1,515 dams i.) WHO sub-region 14 Reservoir sizes (*103 m2)

Number of dams







25-100,000 186 1,254,770 15 597,807 100,000- 51 57,225,270 500 21,451,561 237 58,480,040 22,049,368 178,813,869 5,626,016 1,377,245 *No data available on the area of the reservoir of 1,685 dams

37

Table 6a: Malaria prevalence or incidence in large dam sites compared to distant sites in stable malaria transmission areas

Study site, period, Reference

Population sample Characteristics of dam Overall malaria prevalence/incidence in dam area

Overall malaria prevalence/incidence in distance to dam

WHO sub-region 12 Uttaranchal, India (Shukla et al., 2001)

56 blood smears from febrile patients in dam area 272 in forest area and 849 in plain area

Nanak Matta dam (Created swampy, marshy conditions)

Prevalence 0% in dam area 48.5% in forest village and 1.8 in plain area

Table 6b: Influence of large dam construction on malaria prevalence or incidence in areas of stable malaria transmission

Study site, period, Reference

Population sample Characteristics of dam Malaria prevalence before construction

Malaria prevalence/incidence after construction

WHO sub-regions 1 Manantali dam area, Mali (Jobin, 1999)

Manantali Dam completed in 1987 to provide hydropower and irrigation

Seasonal transmission, little transmission from January to July

1994: Prevalence up to 47% around the lake in July (suggesting year round transmission) compared to 27.27% and 29.62% downstream of the dam

St. Louis Diama dam, Senegal (Sow et al., 2002)

Diama Dam completed 1986 for irrigation along the river and prevent saline water flowing inland

Great upward trend in number of malaria cases in all districts, however no greater than number of cases in respiratory disease

Africa (WHO sub-region 2)

Tana river lake area Kenya (Roggeri, 1985)

Tana river lakes (e.g Masinga dam 1981)

1981 Aug 143 cases in Riakanau health center

1982 Aug 837 cases from 1981- 1984 the number of cases increased by an annual average rate of 21%

India (WHO sub-region 12)

Jabalpur, Bargi Dam (Singh et al., 1999; Singh and Mishra, 2000; Singh et al., 1997)

2,016 blood smears from fever cases 1,714 blood smears from fever cases, 379 children for mass blood survey active case detection in 10 villages

Bargi dam multi purpose hydropower and irrigation projects completed in 1988

39% Hospital prevalence in dry villages b.) Health post records for Naranyanga district 184 cases/1979

49.4% hospital prevalence in partially submerged villages -In 20 submerged villages: 71.4% hospital prevalence -Health post records for Naranyanga district 4,279/1996 Prevalence 38% in mass survey of children 2.4 more cases in head end (44-50km from dam) compared to tail end villages (75-78km)-

38

Table 7a: Malaria prevalence and/or incidence in large dam sites compared to distant sites in unstable malaria transmission areas Study site, period, Reference Population sample Characteristics of dam Overall malaria

prevalence/incidence in dam area Overall malaria prevalence/incidence in distance to dam

WHO sub-region 1 Bamendjjin dam area, Cameroon (Atangana et al., 1979)

567 individuals Dam with retention lake completed in 1974 in order to regulate Edea hydroelectric power

Village close to lake prevalence of 36% Distant village (14 km from lake) prevalence 25%

39

Table 7b: Influence of large dam construction on malaria prevalence or incidence in areas of unstable malaria transmission

Study site, period, Reference Population sample Characteristics of dam Overall malaria prevalence before dam construction

Overall malaria prevalence after dam construction

Africa (WHO sub-region 1) Gleita dam, Mauretania 1984 (Baudon et al., 1986)].

525 individuals Dam across Gorgol river completed 1980, comprises retention lake 10 km long and 15 km large in order to enable gravity irrigation Displacement of 9,000 people

Unstable malaria transmission (only during rainy season July- September)

Prevalence 0% (5th month of dry season)

Brazil (WHO sub-region 4) Itaipú dam, Paraná state (Consolim et al., 1991; Hunter and Corp Author: World Health, 1993)].

Itaipú dam 176 m height and 1.5 km length Artificial lake completed in 1983

Malaria was epidemic with seasonal episodes after flooding events. In 1975-1976 the positivity index was 1.15%, although it included some municipalities endemic for malaria, only indirectly affected by Itaipú

Precarious control measures in the Paraguayan side contributed to the introduction of cases in the Brazilian side.Number of autochthonous cases: (i) Brazilian side: 43 in 1986, 1084 in 1989. (ii) Paraguayan side: 1707 in 1986, 4883 in 1989 Malaria incidence increased in 1988, and an outbreak was registered in 1989, when DDT spraying was reintroduced

Balbina power plant, Presidente Figueiredo municipality, Brazil (Chagas et al., 1982)].

Construction of the power plant initiated in 1977. In 1981 the reservoir started to be built. In 1989 it started its operation. After registering an API of 192.7 when the first workers came to the area control measures were implemented

In 1972 the population was small and the positivity index was 0.13.

Positivity index was: 6.8 in 1977 and 0.8 in 1982. API was 192.7 in 1977, 131.1 in 1978, 0 in 1980, 7.5 in 1982, and 4.4 in 1989.

Tucuruí Hydropower, Tucuruí municipal district, Pará State, 1975 (World Commission on Dams, 2000)].

Tucuruí dam for hydropower. Phase I construction was started in late-1975 and was completed in 1984. Phase II began in 1998 with the first turbine scheduled to be operational by the end of 2002.

106 positive cases in 1962 and 251 in 1975. API was 29.57 in 1970.

Number of cases start to increase after construction, peaking to more than 10,000 cases in 1984. API was 60.4 in 1980 and 26.7 in 1996.

Thailand (WHO sub-region 11)

Khon Kaen Province, Thailand (Harinasuta et al., 1970)].

8,931 individuals Nong Wai dam, Ubol Ratana dam completed 1966-1967 for irrigation purposes, man-made lakes

1967-1968 prevalence 1.2% (0.4%- 2.1% depending on village) 1968-69 prevalence 0.6% (0.2%-1.1% depending on village) Low prevalence due to DDT spraying

Kanchanari Province, Thailand (Bunnag et al., 1979)].

602 individuals Srinagarind dam completed in 1978 Prevalence 16% 1972 (preliminary survey) Prevalence 25% in 1976 on dam site

India (WHO sub-region 12) Thar desert (Tyagi and Chaudhary, 1997; Tyagi et al., 2001)].

Canalization project with 3 major canal systems (Gang, Sirhind feeder, Indira Ghandi) for irrigation, hydropower, water supply

1961 8,494 positive cases in Rajasthan state 1994 229,772 positive cases in Rajasthan state (population has increased by 2.5%)e.g. 2 villages near Indira Ghandi canal prevalence 85% recent focal malaria outbreak

40

Figure 1: Estimation of area at risk of malaria near dam reservoirs

Reservoir Dam (l)

Area at risk = flight range mosquitoes

Base (b)

41

Figure 2

laborers, migrants

Infected human population

Large dams, artificial lakes Hydropower

Small dams, irrigation schemes

Agriculture

Pumps, drains, Water supply &

sanitation

Pools, artificial lakes

Recreation

Host 1: Domestic animals

Clinical disease

Small dams, ponds

Aquaculture

ChemoprophylaxisVaccination

Susceptibility

Improve household living conditions,

community resources, the local economy,

and health infrastructure

Large dams, river modifications Flood control

Plasmodium development Plasmodium/Anopheles survival rate

Anopheles longevity Increase in Anopheles density

Host 2:Local population,

Vector control Water management

Development and operation of water projects

Large dams, artificial lakes Hydropower

irrigation schemes Agriculture

Water supply & sanitation

lakes Recreation

Host 1: Domestic animals

pondsAquaculture

Personal protection Customs Culture

Immunity

Improve household living conditions,

community resources, the local economy,

and health infrastructure

modifications Flood control

Legend: Positive impact Negative impact

Creation of new breeding sites (e.g. reservoirs, surface irrigation, puddles) Modification of atmospheric system (e.g. humidity)

Modification of ecosystem (e.g. flora, fauna) Modification of hydrological system (e.g. water flow, current, chemistry, sediment)

Creation and influence of larval/adult mosquito habitat

Severe clinical complications Death

Anaemia, undernutrition, low birth weight, increased susceptibility to general infection

Sequelae

42

Figure 3 a, b, c, d: Overview irrigation and large dam associated risk and malaria burden per relevant WHO sub-regions

0 200 400 600 800

1000 1200 1400

100

50

% D

ALY

s

Mill

ion

inha

bita

nts

WHO sub-regions 1, 2

87.9%

6.3

606

0 200 400 600 800

1000 1200 1400

Total population Irrigation

population at risk (maximum value)

DALYs

WHO sub-regions 4, 5, 9, 14

2073

1.3% 69.4

100

50

0 200 400 600 800

1000 1200 1400


4.9%

265

113

100

50

200 400 600 800

1000 1200 1400

0


6.1%

659.6

1513

100

50

3.1

11.3

3.4

2.1

Large dam population at risk

43

Appendix: Summary of studies, compiled for this report WHO sub region 1 Disease Malaria Author Atangana S, Foumbi J, Charlois M, Ambroise-Thomas P,

Ripert C Title Epidemiological study of onchocerciasis and malaria in Bamendjin

dam area (Cameroon). Malacological fauna and risks of

schistosomiasis introduction

Reference Med Trop 1979 Sep-Oct 39(5): 537-43 Language French Country Cameroon Village, district, region Bamileke Province Geographical coordinates WHO sub-region {1-14} 1 Abstract Report of survey in Bamendjin dam area indicates that 25 per 100

of the local population are blood smear positive for malaria (Plasmodium falciparum) and 80 per 100 are positive in theindirect malaria immunofluorescent test. Vector: An. funestus. In male inhabitants 23,2 per 100 of the snip-biopsies are positive for Onchocerca volvulus and 40 per 100 of the indirect immunofluorescent test are positive. In female inhabitants the respective ratios are 14,4 per 100 and 48,8 per 100. There is no urinary or intestinal schistosomiasis in this area but specimens of potential intermediate hosts have been detected.

Water resource development and management project

Bamendjin Dam

Type Year of inception 1974 Before Implementation

During Implementation After Implementation Three villages close to reservoir display overall prevalence of 36%

(386 children 0-5 years) compared to three distant villages 304 children 0-5 years (14 km from reservoir) prevalence of 25%, (21 km from reservoir and altitude1.200m prevalence of 13% and (28 km from the reservoir and altitude 1,800m) 0%

Relative changes, risk (RR) Additional notes Disease Malaria

44

Author Audibert M, Josseran R, Josse R, Adjidji A Title Irrigation, schistosomiasis, and malaria in the Logone Valley,

Cameroon

Reference Am J Trop Med Hyg 1990 June 42(6): 550-60 Language English Country Cameroon Village, district, region Mayo Danai Geographical coordinates 1 WHO sub-region {1-14} Abstract Field studies of a rice irrigation project in Mayo-Danai, North

Cameroon permitted a direct comparison between pre- and post-development data relating to schistosomiasis and malaria infection. A stratified sample of 4,000 inhabitants, representing 8% of the population living in 28 areas at the time of the first survey, was investigated five times between 1979 and 1985. Due to the significant population increase since 1982, 1,500 persons were added to the initial sample. The prevalence of schistosomiasis and malaria remained constant over the sixyears. No changes in the transmission sites were observed. Malacological investigations showed a decrease in the snail population in the project area. Environmental sanitation activities (i.e., drain cleaning and well construction) and decreased rainfall contributed to this situation. The prevalence of infection among the migrants was low. High prevalence of schistosomiasis was found only in villages located along a previously contaminated temporary river.


Rice irrigation project with 35000 ha lake

Type Irrigation Year of inception 1979 Before implementation March 1979 prevalence 13.8% in control village and 9.3% in

“improved” villages (concerned with rice growing) (all age groups)

During Implementation After Implementation Control Improved village

November 1979 36.7 24.7 March 1981 17 5.6 November 1981 5.9 7.3 April 1985 14.7 10.2

Relative changes, risk (RR) Additional notes

45

Disease Malaria Author Baudon D, Robert V, Darriet F, Huerre M Title Impact of building a dam on the transmission of malaria. Malaria

survey conducted in southeast Mauritania

Reference Bull Soc Pathol Exot Filiales 1986 79(1): 123-9 Language French Country Mauritania Village, district, region South east Mauritania Geographical coordinates WHO sub-region {1-14} 1 Abstract Water resource development and management project

Foum Gleita dam

Type Dam Year of inception 1980 Before Implementation Seasonal transmission (July- September)

During Implementation After Implementation Prevalence 0% (5th month after begin of dry season) in 10

villages (523 individuals) Relative changes, risk (RR) Additional notes

46

Disease Malaria Author Boudin C, Robert V, Carnevale P, Ambroise-Thomas P Title Epidemiology of Plasmodium falciparum in a rice field and a

savanna area in Burkina Faso. Comparative study on the acquired immunoprotection in native populations

Reference Acta Trop 1992 Jun 51(2): 103-11 Language English Country Burkina Faso Village, district, region Karankasso, Kou valley Geographical coordinates WHO sub-region {1-14} 1 Abstract A longitudinal study, including entomological, parasitological,

immunological and clinical data, was carried out in a rice field village and a savanna village in Burkina Faso. In this study, the authors followed the evolution of several parasitological parameters in order to compare the level of immunoprotection in children of these two areas. In particular, the percentages of recently 'infected' or 'recovered' children were calculated, during the interval separating two consecutive surveys. In both areas, parasite densities quickly increased in children from 0 to 14 years old, immediately after the beginning of the transmission period. In savanna, during the rainy season (May-October), parasite densities decreased and the proportion of recently 'recovered' children from 0 to 4 years old (becoming parasitologically negative between two consecutive surveys) was very low. On the other hand, parasite densities decreased and the recovery rate was higher in children from 10 to 14 years old before the end of the rainy season, while the transmission was going on. In the rice field area, Plasmodium falciparum densities decreased only at the end of the transmission period (December) and had the same levels as those found in savanna, in spite of a lower inoculation rate. The second peak of transmission seemed neither to increase the proportion of ‘recovered’ children, nor to boost the immunoprotection of these children


Irrigation systems

Type Rice Year of inception

Irrigated village P. falciparum rates March 1985: Age group 1 (0-4 years): 29.8%, Age group 2 (5-9 years): 49.2%, Age group 3 (10-14 years): 34% May 1985: Age group 1 (0-4 years): 16%, Age group 2 (5-9 years) 31.9%, Age group 3 (10-14 years): 30.7%

47

August 1985: Age group 1 (0-4 years): 22.7%, Age group 2 (5-9 years) 33.9%, Age group 3 (10-14 years): 31.5.1% October 1985: Age group 1 (0-4 years): 33.3%, Age group 2 (5-9 years) 58%, Age group 3 (10-14 years): 46.1% December 1985: Age group 1 (0-4 years): 28.9%, Age group 2 (5-9 years) 45.7%, Age group 3 (10-14 years): 38.4% February 1986: Age group 1 (0-4 years): 35.7%, Age group 2 (5-9 years) 29.4%, Age group 3 (10-14 years): 23.9% P. malariae rates March 1985: Age group 1 (0-4 years): 0%, Age group 2 (5-9 years): 6.3%, Age group 3 (10-14 years): 10.6% May 1985: Age group 1 (0-4 years): 0%, Age group 2 (5-9 years) 0%, Age group 3 (10-14 years): 0% August 1985: Age group 1 (0-4 years): 0%, Age group 2 (5-9 years) 7.1%, Age group 3 (10-14 years): 2.6% October 1985: Age group 1 (0-4 years): 3%, Age group 2 (5-9 years) 8%, Age group 3 (10-14 years): 0% December 1985: Age group 1 (0-4 years): 0%, Age group 2 (5-9 years) 1.7%, Age group 3 (10-14 years): 10.3% February 1986: Age group 1 (0-4 years): 4.3%, Age group 2 (5-9 years) 4.4%, Age group 3 (10-14 years): 8.7%

Non irrigated village P. falciparum rates

March 1985: Age group 1 (0-4 years): 58.4%, Age group 2 (5-9 years): 56.9%, Age group 3 (10-14 years): 61% May 1985: Age group 1 (0-4 years): 35.4%, Age group 2 (5-9 years) 48.1%, Age group 3 (10-14 years): 59.6% August 1985: Age group 1 (0-4 years): 72.5%, Age group 2 (5-9 years) 64.1%, Age group 3 (10-14 years): 78.9% October 1985: Age group 1 (0-4 years): 36.3%, Age group 2 (5-9 years) 66%, Age group 3 (10-14 years): 46.1% December 1985: Age group 1 (0-4 years): 73.3%, Age group 2 (5-9 years) 57.3%, Age group 3 (10-14 years): 53.3% February 1986: Age group 1 (0-4 years): 54.8%, Age group 2 (5-9 years) 47%, Age group 3 (10-14 years): 54% P. malariae rates

March 1985: Age group 1 (0-4 years): 3.5%, Age group 2 (5-9 years): 12.3%, Age group 3 (10-14 years): 8.1% May 1985: Age group 1 (0-4 years): 9.2%, Age group 2 (5-9 years) 10.1%, Age group 3 (10-14 years): 14% August 1985: Age group 1 (0-4 years): 8%, Age group 2 (5-9 years) 16.2%, Age group 3 (10-14 years): 13.1% October 1985: Age group 1 (0-4 years): 25%, Age group 2 (5-9

48

years) 22.7%, Age group 3 (10-14 years): 19.1% December 1985: Age group 1 (0-4 years): 25%, Age group 2 (5-9 years) 13.3%, Age group 3 (10-14 years): 6.6% February 1986: Age group 1 (0-4 years): 14.5%, Age group 2 (5-9 years) 9.6%, Age group 3 (10-14 years): 4%

Relative changes, risk (RR) Additional notes High consumption of chloroquine in rice villages?

49

Disease Malaria Author Carnevale P, Robert V Title Introduction of irrigation in Burkina Faso and its effect on

malaria transmission Reference Effects of Agricultural Development on Vector-borne diseases,

FAO 1987 Language English Country Burkina Faso Village, district, region Kou Valley Geographical coordinates WHO sub-region {1-14} 1 Abstract Water resource development and management project

Irrigation systems


Irrigated village Prevalence 44.5% (January), 36.2% (April), 55.5% (July), 33.9%

(October) in children 2-9

Non irrigated village Prevalence 60.5% (January), 76.7% (April), 51.3% (July), 58.4% (October) in children 2-9

Relative changes, risk (RR) Additional notes See also Robert 1985 (Ann Soc) increase An. gambiae densitiy

seven times, transmission reduced four times and Boudin et al.

50

Disease Malaria Author Faye O, N'Dir B, Correa J, Faye O, N'Dir O, Gaye O, Bah IB,

Dieng T, Dieng Y, Diallo S Title Evaluation of parasitic risks related to the rehabilitation of

the Ferlo fossil valley (Senegal) Reference Dakar Med. 1998 43(2): 183-7. Language French Country Senegal Village, district, region Ferlo’s valley water launching Geographical coordinates WHO sub-region {1-14} 1 Abstract In order to assess the parasitic risks related to Ferlo's valley water

development, a study has been carried out from September 15 to October 10, 1996 in 12 villages. Four villages surrounding the Guiers lake, four lower within lower Ferlo already water launched seven years ago, and four villages within upper Ferlo not water launched. Malaria strikes at hypoendemic level in the villages surrounding the Guiers lake (p.i = 6.2%) and at mesoendemic level in the area stretching along lower (P.I = 37.6%) and upper Ferlo (P.I = 34.3%) The prevalence rate of urinary schistosomiasis is 0.002% in the first area, 1.3% in the second one and 14.5% in the third area. In these areas, intestinal parasitoses were prevailing respectively at rates of 38.2%, 36.4% and 22.2%.Although, there is no reason to fear immediately a worsening of the epidemiological situation due to Ferlo's valley rehabilitation project, nevertheless, appropriate steps should be taken right now aiming at tacking the extension of conditions related to hydric medium


17 km canal between Lake Guiers and Senegal river

Type Year of inception

Village at the Lake Guiers Overall prevalence 6.2% (in children 0-9) Villages in the Basin Overall prevalence 37.65% and 34.3% (in children 0-9)


51

Disease Malaria Author Faye O, Gaye O, Herve JP, Diack PA, Diallo S Title Malaria in the Saharan region of Senegal. 2. Parasitological

indices Reference Ann Soc Belg Med Trop 1993 Mar 73(1): 31-36 Language English Country Senegal Village, district, region Senegal river central valley Geographical coordinates WHO sub-region {1-14} 1 Abstract The malaria parasitological indices have been studied in three

villages situated in the Senegal river central valley. Near one of them an irrigated rice field has been operational since July 1989. Each village has its own health care unit and the consumption of antimalarial drugs, especially chloroquine, is important. The parasitological indices in children 0 to 9 years old and in patients presenting symptoms evocative of malarial attacks are low. Irrigation of the rice field area does not seem to be an increasing factor for the malaria parasite rates in the area


Irrigation systems


Irrigated village Prevalence 0% (August), 16.7% (September); 16.7% (November), 22.2% (July) in children 0-9

Non irrigated village Village 1: Prevalence 0% (July, August), 2.5% (September), 13.6% (October), 21.4% (November) in children 0-9 Village 2: Prevalence 0% (July, August), 14.8% (September), 35.7% (October), 11.1% (November) in children 0-9

Relative changes, risk (RR) Additional notes No increased transmission in rice area; due to chloroquine?

52

Disease Malaria Author Gbakima AA Title Inland valley swamp rice development: malaria,

schistosomiasis, onchocerciasis in south central Sierra Leone

Reference Public Health 1994 Mar;108(2):149-57 Language English Country Sierra Leone Village, district, region Moyamba district Geographical coordinates WHO sub-region {1-14} 1 Abstract The prevalence of malaria, schistosomiasis and onchocerciasis

was determined in 1,106 residents of five villages in the Moyamba District, Southern Sierra Leone, to determine whether inland valley swamp (IVS) development was associated with changes in the prevalence of malaria, schistosomiasis and onchocerciasis in these villages. These parasitic diseases were studied in four villages receiving IVS, Food and Agricultural Organization (FAO) assistance and in one village not receiving FAO assistance. Malaria was the most prevalent infection, detected in 42.6% of the persons examined, followed by Onchocerca volvulus (17.7%), Schistosoma haematobium (0.6%) and S. mansoni (0.3%). Plasmodium falciparum accounted for 90.4% of the malaria infections, followed by P. malariae (2.1%), P. ovale (0.5%), and mixed infections (7.0%). The trend of infection to O. volvulusincreased significantly with an increase in age. S. haematobium(0.6%) and S. mansoni (0.3%) infections were low and no Biomphalaria pfeifferi and Bulinus globosus were found in 33 IVS development swamps examined. These data indicate that IVS development is associated with an increase in the prevalence of malaria infection, but not in the prevalence of O. volvulus, S. haematobium and S. mansoni.


Irrigation systems


Irrigated village Overall prevalence 39%-58% in villages representing 3 types of swamp development

Non irrigated village Overall prevalence 38.8% in villages using traditional methods Relative changes, risk (RR) Additional notes

53

Disease Malaria Author Henry MC, Rogier C, Nzeyimana I, Assi SB, Dossou-Yovo J,

Audibert M, Mathonnat J, Keundjian A, Akodo E, Teuscher T, Carnevale P

Title Inland valley rice production systems and malaria infection and disease in the savannah of Cote d'Ivoire

Reference Year of publication Language English Country Cote d’Ivoire Village, district, region Geographical coordinates WHO sub-region {1-14} 1 Abstract In sub-Saharan Africa, lowlands developed for rice cultivation

favour the development of Anopheles gambiae s. l. populations. However, the epidemiological impact is not clearly determined. The importance of malaria was compared in terms of prevalence and parasite density of infections as well as in terms of disease incidence between three agroecosystems: (i) uncultivated lowlands, 'R0', (ii) lowlands with one annual rice cultivation in the rainy season, 'R1' and (iii) developed lowlands with two annual rice cultivation cycles, 'R2'. The study clinically monitored 2000 people of all age groups, selected randomly in each agroecosystem, for 40 days (in eight periods of five consecutive days scheduled every six weeks for one year). During each survey, a systematic blood sample was taken from every sick and asymptomatic person. The three agroecosystems presented a high endemic situation with a malaria transmission rate of 139-158 infective bites per person per year. The age-standardized annual malaria incidence reached 0.9 malaria episodes per person in R0, 0.6 in R1 and 0.8 in R2. Children from 0 to 9-year-old in R0 and R2 had two malarial attacks annually, but this was less in R1 (1.4 malaria episodes per child per year). Malaria incidence varied with season and agroecosystem. In parallel with transmission, a high malaria risk occurs temporarily at the beginning of the dry season in R2, but not in R0 and R1. Development of areas for rice cultivation does not modify the annual incidence of malarial attacks despite their seasonal influence on malaria risk. However, the lower malaria morbidity rate in R1 could be explained by socio-economic and cultural factors.


Rice Irrigation


54

Irrigated village Age standardized Annual malaria incidence R1: 0.6 (single cropping) Annual malaria incidence R2 0.8 (double cropping)

Non irrigated village Annual malaria incidence R0:0.9 .(no irrigation) Relative changes, risk (RR) Additional notes Annual malaria incidence is not modified in irrigated agriculture,

double cropping rice system extends malaria risk in the beginning of the dry season. Also difference between the three ecosytems is the immunity acquisition Also given prevalence data for each age group

55

Disease Malaria Author Jobin, William R Title Dams and disease : ecological design and health impacts of

large dams, canals, and irrigation system

Reference Year of publication Language English Country Mali Village, district, region Geographical coordinates WHO sub-region {1-14} 1 Abstract Water resource development and management project

Manantali dam

Type Hydropower Year of inception 1987 Before Implementation Seasonal transmission, little transmission from January to July

During Implementation After Implementation 1994: Prevalence up to 47% around the lake in July (suggesting

year round transmission) compared to 27.27% and 29.62% downstream of the dam


56

Disease Malaria Author Sow S, de Vlas SJ, Engels D, Gryseels B Title Water-related disease patterns before and after the

construction of the Diama dam in northern Senegal

Reference Ann Trop Med Parasitol 2002 Sep 96(6): 575-86 Language English Country Senegal Village, district, region St. Louis Geographical coordinates WHO sub-region {1-14} 1 Abstract The effects of the construction of the Diama dam (completed in

1986) in the Senegal River on the epidemiology of malaria, urinary and intestinal schistosomiasis, diarrhoea and dysentery were investigated in four districts in northern Senegal. To make allowance for any general trend in reported morbidity (caused by changes in demography or the healthcare system), the numbers of cases of these illnesses reported by the basic healthcare facilities before and after the completion of the dam were compared with those of respiratory disease. Prior to the construction of the dam, malaria was the most encountered water-related disease in the medical records of all districts, followed by diarrhoea, dysentery and urinary schistosomiasis. This order remained the same after the completion of the dam. Despite the optimism of health impact assessment reports prepared prior to the construction of the Diama dam, the unexpected appearance and spread of intestinal schistosomiasis as well as an increase in the incidence of urinary schistosomiasis have aggravated the public health situation in the Senegal River basin. It remains to be judged whether the economic benefits of the dam will counterbalance its adverse effects.


Diama dam

Type Year of inception Before Implementation

During Implementation After Implementation Considerable increase in incidence Relative changes, risk (RR) Additional notes Also upward trend in the rise of respiratory diseases, thus no clear

evidence

57

Disease Malaria Author Thomson MC, D'Alessandro U, Bennett S, Connor SJ,

Langerock P, Jawara M, Todd J, Greenwood BM.. Title Malaria prevalence is inversely related to vector density in

The Gambia, West Africa Reference Trans R Soc Trop Med Hyg 1994 Nov-Dec 88(6): 638-43 Language English Country The Gambia Village, district, region Geographical coordinates WHO sub-region {1-14} 1 Abstract Baseline epidemiological and entomological studies were

conducted in five different areas of The Gambia before the introduction of a national malaria control programme, the objective of which was to treat all the mosquito nets belonging to people living in primary health care villages with insecticide. All malariometric indices used (parasite density, parasite rates, splenomegaly, and packed cell volume) indicated that malaria transmission was more intense in the east of the country than elsewhere. High transmission in the east was associated with a high sporozoite rate but not with the greatest vector abundance; the lowest malaria prevalence rates were found in villages which were close to very productive breeding sites of Anopheles gambiae s.l. Use of mosquito nets was strongly correlated with mosquito density and the highest malaria rates were found in villages where the use of nets was relatively low. These results suggest that in The Gambia malaria prevalence rates are reduced where nuisance biting by mosquitoes is sufficient to encourage the population to protect themselves by sleeping under nets.


Irrigation


Irrigated villages 21 villages (population 20,555 bordering rice fields) March 1991 Prevalence: 34.2% in children age 1-4

Non irrigated village 83 villages representing a different ecological environment: March 1991 Prevalence: 28.7-71.2% in children age 1-4

Relative changes, risk (RR) Additional notes Influence of mosquito nets?

58

WHO sub region 2 Disease Malaria Author Coosemans MH. Title Comparison of malarial endemicity in a rice-growing area and

a cotton-growing area of the Rusizi Plain, Burundi Reference Ann Soc Belg Med Trop 1985 65 Suppl 2:187-200 Language French Country Burundi Village, district, region Geographical coordinates WHO sub-region {1-14} 2 Abstract Water resource development and management project

Rusizi Plain


Irrigated village Prevalence rates (Number people examined between 129- 172): January 1982: 25.7% February 1982 24.4% March 1982 28.7% May 1982 38.4% June 1982: 60.2% August 1982 64.3% September 1982: 60.5% November 1982 48.9% December 1982: 36.8% February 1983 46.5% March 1983 53.3% May 1983 60.3% June 1983 69.2%

Non irrigated village January 1982: 4.5% (Number people examined between 54- 271): March 1982 4.5% April 1982 5.6% June 1982: 20% July 1982 29.6% August 1982 23.3% October 1982: 24.7%

59

December 1982: 23.8%


60

Disease Malaria Author Ghebreyesus TA, Haile M, Witten KH, Getachew A, Yohannes

AM, Yohannes M, Teklehaimanot HD, Lindsay SW, Byass P.

Title Incidence of malaria among children living near dams in northern

Ethiopia: community based incidence survey

Reference BMJ 1999 Sep 11 319(7211): 663-6 Language English Country Ethopia Village, district, region Tigray Geographical coordinates WHO sub-region {1-14} 2 Abstract OBJECTIVE: To assess the impact of construction of microdams

on the incidence of malaria in nearby communities in terms of possibly increasing peak incidence and prolonging transmission. DESIGN: Four quarterly cycles of malaria incidence surveys, each taking 30 days, undertaken in eight at risk communities close to dams paired with eight control villages at similar altitudes but beyond flight range of mosquitoes. SETTING: Tigray province in northern Ethiopia at altitudes of 1800 to 2225 m. SUBJECTS: About 7000 children under 10 years living in villages within threekm of microdams and in control villages 8-10 km distant. MAIN OUTCOME MEASURES: Incidence of malaria in both communities. RESULTS: Overall incidence of malaria for the villages close to dams was 14.0 episodes/1000 child months at risk compared with 1.9 in the control villages-a sevenfold ratio. Incidence was significantly higher in both communities at altitudes below 1900 m. CONCLUSIONS: There is a need for attention to be given to health issues in the implementation of ecological and environmental development programmes, specifically for appropriate malaria control measures to counteract the increased risks near these dams.


Microdams

Type Year of inception Before Implementation

During Implementation After Implementation Overall incidence rate 14 (per 1,000 per year) varies on location

resp. altitude of dam and season (highest incidence in October/November) Overall incidence rate 1.9 (per 1000) in control villages

Relative changes, risk (RR)

61

Additional notes see also Alemayehu et. al (Parasitologia) Maichew Dam (completed in 1984) altitude 1,800m revealed a prevalence of 20%

62

Disease Malaria Author Ijumba JN, Shenton FC, Clarke SE, Mosha FW, Lindsay SW Title Irrigated crop production is associated with less malaria than

traditional agricultural practices in Tanzania Reference Trans R Soc Trop Med Hyg 2002 Sep-Oct 96(5): 476-80 Language English Country Tanzania Village, district, region Lower Moshi area Geographical coordinates 3º21’S and 37º20’E WHO sub-region {1-14} 2 Abstract There is concern that crop irrigation that results in increased

numbers of vector mosquitoes will lead to a rise in malaria in local communities. We evaluated the level of malaria experienced in three communities in northern Tanzania with different agricultural practices: rice irrigation, sugar-cane irrigation and traditional maize cultivation. Five cross-sectional surveys were used to measure the prevalence of infection with falciparum malaria in 1-4 years old children in each community over a period of 12 months. Active case detection was also carried out to record clinical episodes of malaria during the study period. Information on antimalarial measures was also recorded. Results from the cross-sectional surveys showed that the overall prevalence of malaria parasites was less near the rice irrigation (12.5%) and sugar-cane (16.9%) schemes than the savannah village (29.4%). There were also significantly fewer clinical episodes of malaria in the rice village (15 cases/1000 child-weeks at risk [cwar]) than either the sugar-cane (36 cases/1000 cwar) or savannah (40 cases/1000 cwar) villages. Overall, rice irrigation was associated with less malaria than alternative agricultural practices, despite the considerable numbers of vectors produced in the paddies. This finding supports other studies that indicate that irrigation in much of sub-Saharan Africa will not lead to increased malaria. Nonetheless, African governments planning irrigation projects need effective policies to encourage local communities to use personal protection measures, such as insecticide-treated nets, and to ensure that these communities have access to effective antimalarial drugs and efficient health services.


Irrigation systems

Type Rice and sugarcane Year of inception 1985

Irrigated village Prevalence rice village (village close to 1100 ha irrigated rice fields) June 1994 15.8%

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September 1994 15.6% December 1994 10.1% March 1995 7.6% June 1995 10.1% Prevalence Sugar cane village (village close to 6313 ha sugar-cane irrigation system) June 1994 19.8% September 1994 13.9% December 1994 14.1% March 1995 18.3% June 1995 18.8%

Non irrigated village Prevalence Savannah village June 1994 41.0% September 1994 31.2% December 1994 15.6% March 1995 26.2% June 1995 26.6%

Relative changes, risk (RR) Additional notes Use of mosquito nets due to better financial status in rice village

64

Disease Malaria Author Roggeri, Henri Title African dams : impacts in the environment : the social and

environmental impact of dams at the local level : a case study of five man-made lakes in eastern Africa

Reference Environment Liaison Centre African dams : Impacts in the environment : the social and environmental impact of dams of the local level: a case study of five man made lakes in Africa

Year of publication 1985 Language English Country Kenya Village, district, region Tana lakes Geographical coordinates WHO sub-region {1-14} 2 Abstract Water resource development and management project

Masinga dam

Type Irrigation Year of inception 1981 Before Implementation 1981 Aug 143 malaria cases in Riakanau health center

During Implementation After Implementation 1982 Aug 837 cases

1983 Aug 312 cases 1984 Aug 398 cases


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WHO sub region 4 Disease Malaria Author Chagas, J.A. da C.; Barroso, M.A.B.; Amorim, R.D.de S.;

Robles, C.R.Q. Title Controle da malária em projeto hidrelétrico no Estado do

Amazonas Reference Revista Brasileira de Malariologia e Doenças Tropicais, 1982 34:

68-81 Language Portuguese Country Brazil Village, district, region Presidente Figueiredo municipality, Amazonas State, North

Region of Brazil (in the Brazilian Amazon) Geographical coordinates 2o 12’ and 3o 43’ latitude north, and 59o 12’ and 68o 8’ longitude

west (these coordinates define the limits of the project) WHO sub-region {1-14} 4 Abstract SUCAM has followed very closely the construction of Balbina

power house from the preliminary studies until the actual situation, and has maintained the malaria problem under absolute control in the area, avoiding the possibility of troubles with this disease, what could be prejudicial for the development of the construction. This paper briefly describes the project evolution within these first five years (July 1977 – August 1982) presenting also the parallel anti-malarial activities done by SUCAM. Call for attention the perfect fit between the companies involved with the project and SUCAM.


Balbina power plant

Year of inception Early work in the area (topographical and hydrological surveys) started in 1977. In 1981 the reservoir started to be built. In 1989 it started its operation.

Outcome measures: Before The population was very small. In 1972, one of the localities

was examined: out of 15 blood samples, one was infected with P. falciparum and one with P. vivax.

During Data on blood tests: Month exams P. vivax P. falciparum PI July/77 237 34 - 14.3 Aug/77 149 18 - 12.0 Set/77 241 1 1 0.8 Oct/77 136 6 - 4.4 Nov/77 474 8 16 5.0 Dec/77 233 7 9 6.8

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Second semester of 1977 – population of 411 workers; total population equals 519.

In 1978 the positivity index was 5.6% - 1971 exams, 111 positive (77 P. vivax and 34 P. falciparum). In 1979 the index decreased to 0.3% - 2096 tests, with 7 positive for P. vivax.

In 1979 new workers came to the area for the construction of a road and an airport; the population reached 1500 people.

1980 – the road was concluded, population was reduced, and no malaria case was registered.

1981 – population at the end of the year reached 2500 people. The positivity index was 1.1% (out of 1076 tests, 10 were positive for P. vivax and 2 for P. falciparum).

1982 – population reached 4000 people. Data on blood tests in 1982: Month exams P. vivax P. falciparum PI Jan/82 164 2 - 1.2 Feb/82 207 6 - 2.8 Mar/82 349 2 - 0.6 Apr/82 327 4 - 1.2 May/82 643 5 - 0.1 Jun/82 680 1 - 0.1 Jul/82 445 2 1 0.7 Aug/82 959 5 3 0.8 Most of the 31 cases observed in 1982 were imported. In 1982 the density of mosquitos was very small Summary data: Year pop. Exams Posit. vivax falciparum PI API 1977 519 1470 100 74 26 6.8 192.7 1978 847 1971 111 77 34 5.6 131.1 1979 1554 2036 7 7 - 0.3 4.51980 458 899 - - - 0 01981 2521 1076 12 10 2 1.1 4.81982 4130 3774 31 27 4 0.8 7.51983 6760 7.51984 7817 3.81985 7521 3.11986 8282 2.51987 8323 5.01988 8493 7.5

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1989 7564 4.4Notes: PI = positivity index (by 100) API = Annual Parasite index (by 1000) Data for 1983/89 were extracted from the book: Iñiguez Rojas, L. B. and Toledo, L. M. d. (1998). Espaço & Doença: um olhar sobre o Amazonas. Rio de Janeiro, RJ, Ministério da Saúde, Fundação Oswaldo Cruz: Editora FIOCRUZ. However, the numbers are approximations, since the paper has only a graph.

After Relative changes, risk (RR) Additional notes After registering and API of 192.7 when the first workers came to

the area, the health sector implemented control measures in the area of the project in order to protect the health of workers, their families, and the local population. The measures were threefold: (i) early case detection and treatment; (ii) identification and analysis of the geographical distribution of anopheles; (iii) prevention of transmission (larvicide, DDT, and insecticides). Other recommendations included the construction of screened houses for workers, clearing of an area of 500 meters around the worker’s houses, use of mosquito nets by the local population, and training of personnel.

68

Disease Malaria Author Consolim, J.; Luz, E.; Pellegrini, N. J. de M.; Torres, P. B. Title O Anopheles (Nyssorhynchus) darlingi root, 1926 e a malária no

lago de Itaipú, Estado do Paraná, Brasil: uma revisão de dados Anopheles (Nyssorhynchus) darlingi root, 1926 and malaria in the Itaipú lake, Paraná, Brazil: a review

Reference Arquivos de Biologia e Tecnologia, 1991 34(2):263-286 Language Portuguese Country Brazil Village, district, region Paraná State, South region of Brazil

Municipalities on the left shore of the artificial lake: from Guaíra (north) to Foz do Iguaçú (south) – total of 10 municipalities along the border with Paraguay

Geographical coordinates WHO sub-region {1-14} 4 Abstract A review on the incidence of An.darlingi and malaria at both

sides of the Paraná river between the cities of Guaíra and Foz do Iguaçú, before and after the construction of the Itaipú power plant, is presented. The correlation between the recrudescence of the disease in the North of Brazil and on both sides of the dam is investigated. The perspectives on the presence of vectors and malaria transmission in the adjacent area in the next years isdiscussed of transmission on the left shore of the reservoir after the return of the programme of breeding place elimination isdiscussed.


Itaipú power plant (specifically the artificial lake – water volume equals, approximately, 29 billions m3)

Year of inception Artificial lake initiated in October 1982, concluded in August 1983Outcome measures:

Before An.darlingi density was residual until 1983. Malaria was epidemic, with seasonal episodes during the

months after big flooding. This pattern remained the same until 1985.

In 1975-76 the positivity index was 1.15%, although it included some municipalities endemic for malaria, only indirectly affected by Itaipú.

DDT spray suspended in 1976. During After Mosquito density started to increase in 1984, remaining very

high until 1989. The hourly average (number of mosquitoes captured during the year divided by the total amount of hours spend in the capture process) was residual until 1993 (0.02), jumped to approximately 1.5 in 1984, 0.6 in 1985, 0.5 in 1986,

69

1.2 in 1987, 1.3 in 1988, and 1.8 in 1989 (approximations, since the paper has only a graph).

Malaria incidence increased in 1988, and an outbreak was registered in 1989.

Number of malaria cases: A. Autochthonous

On the Brazilian side of the lake – Approximately 15 in 1984/85, 43 in 1986, 77 in 1987, 296 in 1988, 1084 in 1989 (approximations, since the paper has only a graph). On the Paraguayan side of the lake – 225 in 1984, 746 in 1985, 1707 in 1986, 2094 in 1987, 2301 in 1988, 4883 in 1989 (approximations, since the paper has only a graph).

B. Imported cases registered in the municipality of Foz do Iguaçú – 893 in 1984, 925 in 1985, 1099 in 1986, 1788 in 1987, 1522 in 1988, 2291 in 1989 (approximations, since the paper has only a graph).

DDT spraying was reintroduced in the second semester of 1989. During the first semester of 1990 a reduction of approximately 79% in the number of cases was observed, when compared with the same period in 1989. In numbers, 6 cases in jan/89, 16 in feb/89, 190 in mar/89, 285 in apr/89, 301 in may/89, 41 in jun/89, 51 in jan/90, 31 in feb/90, 44 in mar/90, 23 in apr/90, 36 in may/90, 4 in jun/90 (approximations, since the paper has only a graph).

Precarious control measures in the Paraguayan side contributed to the introduction of cases in the Brazilian side.

Returning migration from the North region of Brazil, especially Rondônia, brought significant sources of infection, contributing to the increase in the number of cases.

Relative changes, risk (RR) Additional notes There is also information on the water level of the lake and on

the temperature in the area between 1980 and 1989. Finally there is some data on monthly average of malaria cases (useful for seasonal analysis of transmission).

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Disease Malaria Author La Rovere, E. L. and Mendes, F. E. Title Tucuruí Hydropower Complex, Brazil Reference World Commission on Dams (WCD), Final Report 2002 Language English Country Brazil Village, district, region Town of Tucuruí, Pará State, Brazilian Amazon Geographical coordinates Latitude 3o 45’ South and longitude 49o 41’ West WHO sub-region {1-14} 4 Abstract Water resource development and management project

Tucuruí Hydropower

Year of inception The project was designed to be constructed in two phases, Phase I construction was started on November 24, 1975 and completed on November 10, 1984. The construction on Phase II began in June 1998 with the first turbine scheduled to be operational by December 2002.

Outcome measures: Numbers covering the whole period (before, during, after) 1. Figures for human malaria in the Tucuruí Municipal District (1962. 1998) YEAR Positive P. falciparum P. vivax P. malariae P. falciparum+P. vivax

1962 106 93 13 0 0 1963 93 71 22 0 0 1964 28 12 16 0 0 1965 15 12 3 0 0 1966 152 100 52 0 0 1967 111 78 32 0 1 1968 39 21 18 0 0 1969 8 7 1 0 0 1970 251 198 51 2 0 1971 174 116 44 1 13 1972 210 137 68 0 5 1973 600 327 269 0 4 1974 320 119 201 0 0 1975 251 83 167 0 1 1976 1127 367 745 2 13 1977 3387 941 2453 1 42 1978 2762 613 2133 1 15 1979 4953 1272 3652 2 27

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1980 3691 1280 2382 1 28 1981 4479 1500 2942 0 33 1982 6992 2982 3924 0 86 1983 8519 4732 3691 0 96 1984 10126 6431 3628 0 67 1985 1411 809 589 0 13 1986 650 285 361 0 4 1987 1063 388 669 0 6 1988 2103 1133 954 0 16 1989 2801 1158 1622 0 21 1990 2165 998 1149 0 18 1991 ---- ---- ---- ---- ---- 1992 7058 2983 4036 2 37 1993 6094 2873 3153 0 48 1994 3439 825 2599 1 14 1995 3117 376 2727 0 14 1996 1567 252 1301 0 14 1997 1423 182 1234 2 5 1998 1895 292 1491 0 12 Source: National Health Foundation. 2. Annual Parasite Index rates for the Tucuruí Municipal District. Selected Years Year Positive Cases Population Annual Parasite Index 1960 5 716 1970 251 8 489 29.57 1980 3 961 61 140 60.37 1991 4 612* 81 623 56.50 1996 1 567 58 679 26.70

Source: IBGE, FNS * estimated data (average 1990-1992) 3. Cases of Malaria in the Reservoir Area, 1986 District Positive Cases Population Annual Parasite Index Itupiranga (1) 409 3 013 135.75 Jacundá (2) 482 1 827 263.82

(1) Total of 11 places (2) Total of 13 places

72

Relative changes, risk (RR) Additional notes The malaria studies covered the municipal districts upstream

from the dam: Itupiranga, Jacundá, Breu Branco and Novo Repartimento, with Baião, Mocajuba and Cametá downstream. Epidemiological data show that malaria was not distributed evenly throughout the area of influence on the Tucuruí Hydropower Complex, with high transmission rates predominant upstream, and low transmission risks downstream.

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WHO sub region 5 Disease Malaria Author Guthmann JP, Llanos-Cuentas A, Palacios A, Hall AJ Title Environmental factors as determinants of malaria risk. A

descriptive study on the northern coast of Peru Reference Trop Med Int Health 2002 Jun;7(6):518-25 Language English Country Peru Village, district, region Sullana Geographical coordinates WHO sub-region {1-14} 5 Abstract A series of studies was conducted on the northern Pacific coast of

Peru to determine environmental risk factors for malaria. We report in this paper the results of both a descriptive study of incidence and a prevalence survey of malaria. Both studies showed that the area was at low risk for malaria. The malaria incidence rate was 40/1000 p.a. during the study period, and the prevalence of infection was 0.9% (95% CI: 0.4-1.7) before and 1.4% (95% CI: 0.8-2.2) after the high incidence period. However,the risk of malaria varied according to season, village and even house within a single village. Incidence rates increased from February (2.6/1000 p.a.) to May (12.9/1000 p.a.) and decreased during the second part of the year. Most of the cases were clustered in four villages that constituted only 21% of the total population of the area. Houses where multiple cases were recorded were often located near a source of water. Our observations suggested that environmental factors, and particularly the presence of water for irrigation around villages and houses, played a major role in determining the risk of malaria. These observations were extended through an entomological study and a case-control study, to be published elsewhere.


Irrigation systems

Type Cotton fruit, maize, rice Year of inception

Irrigated village July 1996- June 1997 Green stratum (villages amongst fields and near canals) Incidence rate 116.7 (per 1000/year) (388 cases per 3324 inhabitants all ages

Non irrigated village July 1996- June 1997 Villages in dry stratum (30-60 minutes walk from the fields):

74

Incidence rate 2.9 (per 1000/year) 13 cases per 4510 inhabitants-all ages Intermediate stratum (villages in dry areas surrounded by cultivated fields): Incidence rate: 20.4 (per 1000/year) 94 cases per 4598 inhabitants all ages


75

WHO sub region 9 Disease Malaria Author Gratz, N.G. Title The effect of water development programmes on malaria and

malaria vectors in Turkey Reference Effects of Agricultural Development on Vector borne diseases,

FAO 1987 Language English Country Turkey Village, district, region Çukurova Plain, Adana (southern Turkey) Geographical coordinates WHO sub-region {1-14} 9 Abstract Water resource development and management project

irrigation channels

Type Irrigation Year of inception mid 1970’s Before Implementation API (Turkey): 3 cases per 100,000 inhabitant (1,400 reported

cases in the country with 49 reported cases from Adana)

After Implementation 1977 outbreak (115,512 reported cases from Adana) and API (Çukurova Plain) rose to 278 cases per 100,000 Malaria interventions reduced API (Çukurova Plain) to 67 cases per 100,000 and overall reported cases fell in 1979 to 29,234 1982/1983 refusal to residual spraying: overall cases 62,038 and 66,681 (18,537 resp. 35,919 cases from Adana)


76

WHO sub region 11 Disease Malaria Author Bunnag T, Sornmani S, Pinithpongse S, Harinasuta C. Title Surveillance of water-borne parasitic infections and studies

on the impact of ecological changes on vector mosquitoes of malaria after dam construction

Reference Southeast Asian J Trop Med Public Health 1979 Dec;10(4):656-60

Language English Country Thailand Village, district, region Kanchanaburi Province Geographical coordinates WHO sub-region {1-14} 11 Abstract Water resource development and management project

Srinagrind Dam

Type Year of inception 1978 Before Implementation 1972 Prevalence 16% (1,133 children and adults sampled at dam

site (date not given)

During Implementation After Implementation 1976 overall annual prevalence 25% (602 samples in two villages

near dam site) (seasonal variations Prevalence 0% in May) 1977 overall annual prevalence 24%

Relative changes, risk (RR) Additional notes .

77

Disease Malaria Author Dixon, R.A., Pinikhana, J.P. Title Malaria and proximity to irrigation projects: a parasitaemia

prevalence study from Sri Lanka Reference Mosquito-borne Diseases Bulletin Language English Country Sri Lanka Village, district, region Hambantota district Geographical coordinates WHO sub-region {1-14} 11 Abstract Water resource development and management project

Lunvgamvehera irrigation scheme


Irrigated village Sep- Nov 1987 Prevalence 4.8% (938 examined- all ages) Non irrigated village Sep- Nov 1987 Prevalence 2.5% (833 examined –all ages)

Relative changes, risk (RR) Additional notes Higher prevalence in new village compared to ancient village

(different life style)

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Disease Malaria Author International Irrigation Management Institute Title Proceedings of the workshop on Irrigation and Vector borne

disease transmission

Year of publication 1986 Language English Country Sri Lanka Village, district, region Mahaweli Geographical coordinates WHO sub-region {1-14} 11 Abstract Water resource development and management project

Mahaweli System C

Type Year of inception 1972 Before Implementation No baseline data

During Implementation After Implementation Data given for 1985


79

WHO sub region 12 Disease Malaria Author Hyma S, Ramesh A Title The reappearance of malaria in Santhanaur Reservoir and

environs: Tamil Nadu, India. Reference Soc Sci Med (Med Geogr) 1980 Sep;14D (3):337-44 Language English Country India Village, district, region Tamil Nadu Geographical coordinates WHO sub-region {1-14} Abstract Water resource development and management project

Sathanur dam

Type Year of inception 1958

Prior implementation No information prior to dam construction After implementation Increasing incidence in the state: from 1,602 cases in 1964 to

19,687 cases in 1974 At the dam site: 127 cases in 1974 to 624 cases in 1977 (population 935) After 1977 rapid malaria control measures


80

Disease Malaria Author Mistry, J.F.; Purohit, M.U Title Environmental Effects of the Mahi-Kadana and Dharoi

Projects at Gujarat, India

Reference Water Resources Journal 1990, 164, 93-97 Language English Country India Village, district, region Gujarat Geographical coordinates WHO sub-region {1-14} 12 Abstract Water resource development and management project

Mahi Kadana Project (irrigation, hydropower, water supply) Irrigation potential: 6,000 ha in 1959 201,000 ha in 1980

Type Year of inception Canal system: 1958 Kadana reservoir: 1978 Before Implementation API 0.01 (cases/1000 per year) (1961)

During Implementation After Implementation API 0.91 (1969)

API 11.8 (1971) API 26.9 (1975) API 37.9 (1976), following this outbreak disease control and prevention was stepped up

Relative changes, risk (RR) Additional notes See also Jayaraman T.K (presents the same data and correlation

matrix area irrigated and API)

81

Disease Malaria Author Sharma, V.P., Uprety, H.C. Title Preliminary studies on irrigation malaria Reference Indian Journal of Malariology 1982 Language English Country India Village, district, region Meerut and Gurgaon Geographical coordinates Between 37º15’ and 37º30’ E and 0º20’and 0º45’ S WHO sub-region {1-14} 12 Abstract Water resource development and management project

Rice


Irrigated village Incidence 57 cases (June), 81 cases (October) (Population of about 10,000 of all ages contacted)

Non irrigated village Incidence 10 cases (June), 9 cases (October) (Population of about 10,000 of all ages contacted)

Relative changes, risk (RR) Additional notes Villages of comparable socioeconomic status

82

Disease Malaria Author Singh, N., Mehra, R. K., Sharma, V. P Title Malaria and the Narmada-river development in India: a case study

of the Bargi dam

Reference Ann Trop Med Parasitol 1999 Jul;93(5):477-88 Language English Country India Village, district, region Narmada valley Geographical coordinates 22º56’33N 79º55’33E WHO sub-region {1-14} 12 Abstract The largest river-valley development to be proposed in India is

that in the Narmada valley. The building of the Bargi dam, a multi-purpose irrigation and hydro-electric project, in Jabalpur, in central India, formed part of the first phase of the development of this valley (1974-1988). Many villages and several hectares of land in three districts were submerged as the waters rose behind the dam, the worst affected area being the catchment area of the primary health centre (PHC) at Narayanganj, in Mandla district. Until recently, cases of malaria were relatively rare in Narayanganj. However, an epidemic of malaria in late 1996 claimed hundreds of lives in the area and the outbreak spread, during 1997, to new villages in the region. A review of the records collected by the National Malaria Eradication Programme (NMEP) not only indicated that the slide positivity rate (SPR) for Narayanganj increased > 7.45-fold between 1979 and 1997 but also that the slide falciparum rate (SFR) increased > 32-fold over the same period. The NMEP data available for Mandla district as a whole indicated a doubling in mean SPR and SFR between 1979 and 1997. There is no evidence that a new species of vector has established since 1979. In fact, indoor-resting densities of anophelines and of the most established vector, Anopheles culicifacies, have fallen since the dam was built, but densities of another vector, An. fluviatilis, have increased.


Bargi Dam (multi purpose irrigation and hydroelectric project)

Type Year of inception 1974-1988 (water stored to its full capacity in 1990) Before Implementation 1987 hospital prevalence (418 blood smears from fever cases)

10% (in 5 villages in Naranyangj) API for whole Mandla district in 1979 9,0; for Narayangnj district 1979 API of 3.6.

During Implementation

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After Implementation Hospital prevalence (1,702 blood smears from persons with fever collected) of 39% in 20 dry (not inundated) villages compared to a hospital prevalence of 49.4% in 22 partially submerged villages (314 blood smears) An additional study revealed that the hospital prevalence ranges in 20 submerged (4 completely and 16 partially) villages in adults from 58.9% to 76.5% and in children from 65.1% to 84% depending on the season API for whole Mandla district 1997 25.3; for Narayangnj district 1996 API 58.3 Comparison of head end villages (44-50km from dam site with minor canals; main crop rice, maize wheat) and tail end villages (75-78km from dam site; less irrigated, main crop soybeans ) 2.4 more malaria cases from head end villages, API 216 positive cases/1000/year (children) and 140/1000/year adults in head end villages compared to API of 57 in children and 33 in adults

Relative changes, risk (RR) Additional notes Singh, N. & Mishra, A. K. (2000). Anopheline ecology and malaria

transmission at a new irrigation project area (Bargi Dam) in Jabalpur (Central India). J Am Mosq Control Assoc, 16, 279-287. Singh, N., Shukla, M., Chand, S. & Sharma, V. (1997). Outbreak of falciparum malaria in submerged villages of Narayanganj PHC, district Mandla due to Narmada irrigation project, central India (Madhya Pradesh). Current Science, 73, 686-691.

84

Disease Malaria Author Tyagi, B. K.; Chaudhary, R. C Title Outbreak of falciparum malaria in the Thar Desert (India),

with particular emphasis on physiographic changes brought about by extensive canalization and their impact on vector density and dissemination

Reference Journal of Arid Environment 1999 Language English Country India Village, district, region Thar desert Geographical coordinates 24º30N and 68º-78ºE WHO sub-region {1-14} 12 Abstract Water resource development and management project

Canalization, Indira Ghandi Canal, Gang Canal, Bhakra Sirhind Canal

Type Irrigation, hydropower, water supply Year of inception 1928 (Gang Canal), 1955 (Bhakra Sirhind Canal), 1961-today

(Indira Ghandi Canal) Before Implementation In 1961 8,494 positive P. falciparum cases in Rajasthan state

(entire desert region comprises 11 districts)

Overall Rajasthan prevalence 1.43% (1961) During Implementation After Implementation In 1994 229,772 positive P. falciparum cases in Rajasthan state

(population has increased by 2.5%) Overall Rajasthan prevalence: 5.07% (1994) with maximum prevalence in 1976 (1981: 3.1%; 1986:1.5%; 1991:2.5%)-irregular DDT spraying reported Epidemics occur regularly in districts with irrigation: e.g. in 2 villages (Madassar, Awai) in 1993 near Indira Ghandi Canal prevalence 85%


85

WHO sub region 14 Disease Malaria Author Kobayashi J, Somboon P, Keomanila H, Inthavongsa S,

Nambanya S, Inthakone S, Sato Y, Miyagi I Title Malaria prevalence and a brief entomological survey in a

village surrounded by rice fields in Khammouan province, Lao PDR

Reference Trop Med Int Health 2000 Jan;5(1):17-21 Language English Country Laos Village, district, region Nongceng Geographical coordinates WHO sub-region {1-14} 14 Abstract We surveyed Nongceng, a village in a south-eastern province of

Lao PDR, for malaria and its vectors. Nongceng is situated in a basin and surrounded by rice fields. In February 1998 (dry season), 28.6% of 126 villagers were infected with malaria, and in September 1998 (rainy season), 16.3% of 147 villagers. The prevalence of malaria infection was consistently high in children under 10, and the predominant malaria species was Plasmodium falciparum. In brief surveys of the mosquitoes performed on the same day as the malaria surveys, 2007 Anopheles females from 12 species were collected by means of human bait, animal bait and resting collections. Of the vector species known to be important in transmitting malaria in neighbouring Thailand - An. minimus, An. dirus, and An. maculatus groups - only An. minimuswas found. Its density was, however, very low in both seasons and it was therefore unlikely to be the vector. In fact, An. nivipesaccounted for more than 65% of all mosquitoes collected and was the most common species collected from human baits. The results of this study show that endemic areas of malaria in Lao PDR are not necessarily related to forest. Rather, An. nivipes is suspected to be the most important vector.


Irrigation systems


Irrigated village Prevalence 28.6 (February)-16.3% (September) Non irrigated village Prevalence 5-10% (different study)


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