E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

GIS in EWAR

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Surveillance system

EWAR

Event based Case based

Report

signal

Report

signal

Outbreak investigationEvaluation

Introduction to surveillance

Role of IHR

EWAR •Structure,•Prioritization of diseases,•Case definitions

Signal generation

and verification

GIS

System evaluation

Outbreak investigation

Alert

Routineweekly, monthly and quarterly reporting

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Objectives of this lecture

To describe GIS use in EWAR

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Spatial epidemiology and GISDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Spatial epidemiology is the description and analysis of the geographical distribution of disease.

(Andrew B. Lawson Statistical Methods in Spatial

Epidemiology, II Edition)

Spatial epidemiology is the description and analysis of the geographical distribution of disease.

(Andrew B. Lawson Statistical Methods in Spatial

Epidemiology, II Edition)

Geographic information systems (GIS) are computer-aided database

management and mapping technologies that organise and store large amounts

of multi-purpose information.

(WHO GIS and public health mapping)

Geographic information systems (GIS) are computer-aided database

management and mapping technologies that organise and store large amounts

of multi-purpose information.

(WHO GIS and public health mapping)

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

ObjectivesDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

•Representing geographic distribution of diseases,

• Monitoring diseases and interventions over time,

•Tracking the spread of infectious and environmentally

caused diseases,

• Analyzing spatial and temporal trends,

• Mapping populations at risk,

• Stratifying risk factors,

• Assessing resource allocation, and

• Planning and targeting interventions.

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

DataDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

The GIS works with two kinds of data:

Non-spatial dataNon-spatial dataSpatial dataSpatial data

Thematic maps are maps that show not only the location and shape of a feature, but also one or more values associated with

the feature.(UNESCO Bangkok Thematic maps and labels - a student handout)

 

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

DataDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

No

n-

spatial

data

No

n-

spatial

data

Cases of diseases

Roads

Districts

Elevation

Water basins and rivers

Real world

Sp

atial data

Sp

atial data

image modified from http://edit.csic.es/OtherResources.html

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Types of Thematic Maps

• Designed to show spatial variations in the distribution of a given variable,

• Univariate/bivariate/multivariate,

• 5 types:– The graduated maps– The dot density maps– The chart maps– The value maps– The single symbol maps

Definition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Graduated MapsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Principle: data is divided into distinct ranges and assigned a colour code usually according to a colour

gradient

Principle: data is divided into distinct ranges and assigned a colour code usually according to a colour

gradient

Applications: representation of health service delivery (e.g. medical consultations per day per health centre) and heath status (prevalence/incidence of disease).

Applications: representation of health service delivery (e.g. medical consultations per day per health centre) and heath status (prevalence/incidence of disease).

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Dot Density MapsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Principle: numeric valued are featured as a point randomly distributed in a geographical area

Principle: numeric valued are featured as a point randomly distributed in a geographical area

Applications: representation of clusters of cases during disease outbreaks

Applications: representation of clusters of cases during disease outbreaks

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Chart MapsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Principle: variables are expressed as a proportion with columns or pies

Principle: variables are expressed as a proportion with columns or pies

Applications: representation of health service delivery (e.g. proportion beneficiaries in reproductive age

accessing family planning) and heath status (proportion of a population group affected by hypertension or

diabetes).

Applications: representation of health service delivery (e.g. proportion beneficiaries in reproductive age

accessing family planning) and heath status (proportion of a population group affected by hypertension or

diabetes).

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Value MapsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Principle: variables are Boolean (yes/no) or are unique values that are represented with different colours (e.g.

red endemic, blue non-endemic) or symbol

Principle: variables are Boolean (yes/no) or are unique values that are represented with different colours (e.g.

red endemic, blue non-endemic) or symbol

Applications: this type of map has been used for health service (location of health facilities by size) or health status (endemicity of disease by country) mapping.

Applications: this type of map has been used for health service (location of health facilities by size) or health status (endemicity of disease by country) mapping.

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Single Symbol MapsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Principle: All the features in these maps are shown using the same colours and symbols

Principle: All the features in these maps are shown using the same colours and symbols

Applications: It’s a suitable technique to show where physical; features are located such as refugee

camps and health centres.

Applications: It’s a suitable technique to show where physical; features are located such as refugee

camps and health centres.

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Disease mappingDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Disease maps provide a rapid visual summary of complex geographic information and may identify subtle patterns in the data that are

missed in tabular presentations.

They are used variously for descriptive purposes, to generate hypotheses as to

aetiology, for surveillance to highlight areas at apparently high risk, and to aid policy

formation and resource allocation. (Elliott and Wartenberg , 2004)

Disease maps provide a rapid visual summary of complex geographic information and may identify subtle patterns in the data that are

missed in tabular presentations.

They are used variously for descriptive purposes, to generate hypotheses as to

aetiology, for surveillance to highlight areas at apparently high risk, and to aid policy

formation and resource allocation. (Elliott and Wartenberg , 2004)

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Definition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Cases/100,000

Notification Rate of Tuberculosis in France, 1996

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

PitfallsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

• Artefact disease patterns can emerge

and real patterns can be lost,

• Quality of the data,

• Modifiable area

unit problem

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

ClusteringDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

When analysing disease clusters we are in the situation where we observe

an excess of cases of a defined disease in a specific time and place, assuming that background risk for the condition

in the area we take into account is homogeneous and will not influence

the clustering itself

When analysing disease clusters we are in the situation where we observe

an excess of cases of a defined disease in a specific time and place, assuming that background risk for the condition

in the area we take into account is homogeneous and will not influence

the clustering itself

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Definition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

Distribution of cases of Botulism France, Week 42-45, 2000

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

PitfallsDefinition

Objectives

Types of data

Types of maps•Graduated•Dot density•Chart•Value•Single symbol

Disease mapping

Clustering

• Data verification,

• Boundaries,

• Denominators

E P I D E M I C A L E R T A N D R E S P O N S E SEARO –CSR Early Warning and Surveillance System Module

Question Time

What are the uses of GIS in an EWAR system?