1. SEARO –CSR Early Warning and Surveillance System Module GIS in EWAR

2. SEARO –CSR Early Warning and Surveillance System Module Surveillance system EWAR Event basedCase based Report signal Report signal Outbreak investigation Evaluation Introduction to surveillance Role of IHR EWAR Structure, Prioritization of diseases, Case definitions Signal generation and verification GIS System evaluation Outbreak investigation Alert Routine weekly, monthly and quarterly reporting

3. SEARO –CSR Early Warning and Surveillance System Module Objectives of this lecture To describe GIS use in EWAR

4. SEARO –CSR Early Warning and Surveillance System Module Spatial epidemiology and GIS Definition 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)

5. SEARO –CSR Early Warning and Surveillance System Module Objectives Definition 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.

6. SEARO –CSR Early Warning and Surveillance System Module Data Definition 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 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)

7. SEARO –CSR Early Warning and Surveillance System Module Data Definition Objectives Types of data Types of maps Graduated Dot density Chart Value Single symbol Disease mapping Clustering Non- spatial data Cases of diseases Roads Districts Elevation Water basins and rivers Real world Spatial data image modified from http://edit.csic.es/OtherResources.html

8. 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

9. SEARO –CSR Early Warning and Surveillance System Module Graduated Maps Definition 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 Applications: representation of health service delivery (e.g. medical consultations per day per health centre) and heath status (prevalence/incidence of disease).

10. SEARO –CSR Early Warning and Surveillance System Module Dot Density Maps Definition 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 Applications: representation of clusters of cases during disease outbreaks

11. SEARO –CSR Early Warning and Surveillance System Module Chart Maps Definition 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 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).

12. SEARO –CSR Early Warning and Surveillance System Module Value Maps Definition 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 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.

13. SEARO –CSR Early Warning and Surveillance System Module Single Symbol Maps Definition 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 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.

14. SEARO –CSR Early Warning and Surveillance System Module Disease mapping Definition 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)

15. 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

16. SEARO –CSR Early Warning and Surveillance System Module Pitfalls Definition 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

17. SEARO –CSR Early Warning and Surveillance System Module Clustering Definition 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

18. 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

19. SEARO –CSR Early Warning and Surveillance System Module Pitfalls Definition Objectives Types of data Types of maps Graduated Dot density Chart Value Single symbol Disease mapping Clustering Data verification, Boundaries, Denominators

20. SEARO –CSR Early Warning and Surveillance System Module Question Time What are the uses of GIS in an EWAR system?