Public Health added value of GIS/spatial analysis for some infectious diseases

National Institutefor Public Healthand the Environment

Public Health added value of GIS/spatial analysis for some infectious diseases.

Wilfrid van Pelt, Agnetha Hofhuis, Ingrid Friesema, Jan van de Kassteele and many many others

1. Simple type of clustering in space and time implemented in 1999 with an internet interface, of 1000 salmonella types for weekly signaling and retrospective inspection.

2. Simple ecologic analysis of Lyme disease among NL general practices (1995, 2001 en 2006).

3. Provisional Bayesian analysis of regional densities of cattle, pigs and poultry and the occurrence of patients with STEC (1999-2007).

Hotel Mitland, 5 mrt 2009EUROHEIS2 GIS workshop, Wilfrid van Pelt et al.


Course avian influenza epidemic, 2003poultryfarms, contaminated, culled

Thanks to Michiel van Boven



Rubella notifications by 4 digit postal code The Netherlands, 1-9-2004 – 13-9-2005


MMR-1 coverage by municipality The Netherlands, 2004


Votes for SGP party by municipality National Elections, The Netherlands, 2003

Percentage of those allowed to vote

Thanks to Susan Hahne


Outbreak detection by searching for clusters in region & time for

Salmonella


Intranet Catalogue / Atlas since Mai 1998

• human/ animal/ food/ environment

• All sero and phagetypes

• Resistance

• Actual trends, Early Warning, GIS-clusters

Each week backcalculated starting in 1984

• >10.000 Tables and Figures



Explosions of S. Typhimurium ft 20

october 1997Groningen

April 1998Roermond October 1999

Twente

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7-Ja

n

17-M

ar

26-M

ay

4-Aug

13-O

ct

22-D

ec

2-M

ar

11-M

ay

20-J

ul

28-S

ep

7-Dec

15-F

eb

26-A

pr5-

Jul

13-S

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22-N

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31-J

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11-A

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29-A

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7-Nov

16-J

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26-M

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4-Ju

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13-A

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22-O

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31-D

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11-M

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20-M

ay

29-J

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week

Fre

qu

en

cy

16

PH

L's

(4

-wk

su

m)

ObservedExpectedTolerance

Region clusters

Age deviating

Time clusters

Early-Warning application


1st step signal verification:

region

Silver wedding:

• Case-control study rPHA

• Coburgerham, salting process insufficient


1st stepsignalverification:

region-crossing

Place, Age, Gender


1st step signalverification:

precedent

No cause found:

• RIVM trawling questionnair, too late

• Animal Health Service, no clou in region


Say CHEESE


Explosion of Salmonella Typhimurium DT7 cases

In January 2006 up to April 2007 an explosion of S.T. DT7 infections occurred, resulting in an extra 297 lab-confirmed cases of salmonellosis.

(tip of the Iceberg).

Labconfirmed: 297 cases

Hospitalized: 60-75 cases

Death (<2jr): 5 - 6

Symptomatic InfectedGeneral population

General Practices

Laboratories

Hospital

†

Doctor visits: +/- 650

General Population:+/- 4455 GE-cases

COI: € 0.6 milj

DALY: 54

Schattingen!!



1 jan 2006

half mei 2006

april 2007

Automatische geografische outbreak detectieKaas affaire Twente Salmonella Typhimurium Ft561


Automated geographic outbreak detectionKaas affaire Twente Salmonella Typhimurium Ft561

Januari to half

mei 2006

half mai to

end 2006


Not automated, by hand for publication,

looks better

Kaas affaire Twente Salmonella Typhimurium Ft561/DT7januari-december 2006



Lyme disease in the NetherlandsAgnetha Hofhuis & Wilfrid van Pelt and many others



Lyme disease in Europe is caused by the Borrelia burgdorferi sensu lato group;

B. burgdorferi sensu stricto, B. afzelii, B. garinii

Transmission of Lyme disease

Transmission by the sheep tick (Ixodes ricinus).



Lyme disease

Early local infection:

erythema migrans (EM) 75 - 90% of B. burgdorferi infections

Early disseminated infection:

manifestations in nervous system, skin, joints and heart

Chronic Lyme borreliosis…



retrospective studies among general practitioners (GP’s)

? Incidence of tick bites and erythema migrans

? Geographical distribution in the Netherlands

? Ecological risk factors for tick bites and erythema migrans

retrospective analysis of hospital admissions for Lyme disease

? Occurrence of hospital admissions for Lyme disease

? Seasonal and annual trends in hospital admissions for Lyme disease

collecting ticks in 4 different biotopes

? Density of ticks & infection rate of ticks with Borrelia

? Seasonal & annual trends

Studies on Lyme disease in the Netherlands



All (± 8.000) general practitioners (GP’s) in 1995, 2002 & 2006

received pre-coded questionnaire about previous year

1. How many patients with tick bites have you seen?

2. How many erythema migrans case-patients have you seen?

3. How many people are included in your practice population?

Retrospective GP-study postal questionnaire



74,3

103,8

38,6

371,9

446,3

191,3

0

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100

120

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160

1994 1996 1998 2000 2002 2004 2006

0

50

100

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Response, coverage: 88% in 1994

68% in 2001

71% in 2005

Tick bite consultations:

1994 30.000

2005 73.000

EM consultations:

1994 6.000

2005 17.000

Retrospective GP-study results

Incidence of EM & tick bites per 100.000 inhabitants



Information on risk factors per municipality

Roe deerRabbitsHorsesSheep & goatsCattleWoodsDegree of urbanizationTourist nights per yearPrecipitationParks & public gardensSandy soilUncultivated wet soilUncultivated dry soilDunes

Retrospective GP-study ecological risk factors

Risk analysis for GP-studies of 1994, 2001 & 2005 together:

Poisson regression: (offset: city population) city repeated measure year “confounder” no random (un)structered effects, sofar no Bayesian smoothing, sofar



Retrospective GP-study ecological risk factors

Risk factors for tick bites

area with sandy soil

mean precipitation

density of roe deer

rural areas ( houses/ km2)

tourist areas

cattle / km2

rabbits / km2

Risk factors for erythema migrans

area covered with woods

area with sandy soil

mean precipitation

roe deer / km2

rural area ( houses/ km2)

tourist areas



Geographical distribution of STEC in the Netherlands

Wilfrid van Pelt ,Loes Bertens, Ingrid Friesema, Jan van de Kassteele (spatial statistician)



Known, mentioned riskfactors: Consumption raw milk/cheese (16%) Contact farmanimal (21%) Person-to-person transmission (18%) Consumption ready-to-eat vegetables (28%)

Most important reservoir: Dairy cattle and veals

Acute gastroenteritis with Complications HUS (15%) and Hospital-uptake (41%), accent 0-4 year

olds

Generalities STEC-O157 infections

Provisionary analysis:Spatial relation Cattle density and STEC incidence



STEC season in Veals (1st), 1-2 weeks later in Humans and Dairy cattle

1999-2007

0

1

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3

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5

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7

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9

1-4 5-8 9-12 13-16 17-20 21-24 25-28 29-32 33-36 37-40 41-44 45-48 49-52

4-weekly periods

Hu

man

ST

EC

O15

7 / 4

wk,

199

9-20

07

0%

3%

6%

9%

12%

15%

18%

21%

24%

jan feb mrt apr mei jun jul aug sep okt nov dec

Po

siti

ve s

tap

les

Dairy Cattle

Veals



Average (1997-2006) densities of farm animals / km2

Poultry densityAnimals / km2

[0,974](974-2700](2700-5440](5440-9400](9400,15500](15500-23500](23500-28800]

Poultry densityAnimals / km2

[0,974](974-2700](2700-5440](5440-9400](9400,15500](15500-23500](23500-28800]

Pigs densityAnimals/ km2

[0-204](204-561](561-1040](1040-1770](1770-2490](2490-3290](3290-4760]

Pigs densityAnimals/ km2

[0-204](204-561](561-1040](1040-1770](1770-2490](2490-3290](3290-4760]

Cattle densityAnimals / km2

[0,35.7](35.7,75.4](75.4,121](121,172](172,230](230,325](325,547]

[0,35.7](35.7,75.4](75.4,121](121,172](172,230](230,325](325,547]



RR P2.5 P97.5(Intercept) 0,6 0,4 0,8Cattle: 1000/km2 6,4 1,0 45,2Pig: 1000/km2 1,0 0,7 1,4Poultry:1000/km2 1,0 0,9 1,0Age 0-4 4,5 3,4 5,9Age 5-9 1,6 1,2 2,1Age 10-49 0,5 0,4 0,7Age 50+ 1,0

Males 1,0Females 1,3 1,0 1,6

Neighbour matrix of 496 communities

WinBUGS model called from R using R2WinBUGS library Model results



RR total

[0.202,0.734](0.734,0.969](0.969,1.24](1.24,1.6](1.6,2.11](2.11,3](3,4.25]

STEC casesIncidence / 1.000.000

[0,1.62](1.62,4.7](4.7,7.34](7.34,11.1](11.1,16.8](16.8,22.4](22.4,31.6]

STEC-O157 in NL 1999-2006 (2.4 / 106 inhabitants; 40-50 / yr.; N=400)

Bayesian “smoothed” version (SMR)



STEC-O157 model:Structured and unstructured random effects (residuals)

RR unstructured

[0.418,0.975](0.975,1.19](1.19,1.41](1.41,1.68](1.68,2.05](2.05,2.55](2.55,3.62]

RR structured

[0.356,0.614](0.614,0.878](0.878,1.02](1.02,1.14](1.14,1.26](1.26,1.48](1.48,10.3]



Web-based GIS-tool for questioning both numerators (disease, risk

factor) and denominators (underlying population size):

• Physicians (EU wide): practice size (denominator), number of Lyme

consults (numerator)

• Children DayCare Centres (NL): weekly reporting children at risk

(denominator) and absenteism infectious diseases (numerator) Immediately mapping and feeding back the rates to GP or DCC,

regional PH-body (GGD) and national PH-body (RIVM)• Accurate incidence figures for regional comparison and analysis of regional

risk factors Condition:

• Small, fast web-based application ignoring the artistic selfrespect of GIS developers

GIS wishes


Documents

Public Health added value of GIS/spatial analysis for some infectious diseases