Integration of environmental, social and health data using GIS: Lessons learned from three disease outbreaks investigat

1. Integration of environmental, social and health data using GIS: Lessons learned from three disease outbreaks investigations in rural areas Christovam Barcellos Walter Ramalho Waneska Alves Brazilian Health Ministry

2. Objectives • 3 Outbreak investigations • Structure of Brazilian health surveillance system • Low cost alternatives for data acquisition and analysis

3. Leishmaniosis outbreak • Rural settlement since 1998 • 706 inhabitants • Family farm • 70 suspected cases during 2002

4. Outbreak dimensions • Total population: 706 • Number of cases: 20 • Households with cases: 16 • Attack rate: 3%

5. Settlement characteristics Subtropical climate Recent provisonary settlement Landless Workers' Movement (MST) Close contact with animals (dogs, chicken, pig) Proximity to forest (rain forest and riparian vegetation) (use of wood and hunting)

6. Mapping and questionnaire Case location and habits characterization Interactions people and environment Pavlovski, 1939, theory of natural nidality of transmissible diseases Methodology

7. GIS was employed to • Characterize local landscape (RS) • Measure distance between houses and suspected risk sources • Identify clusters of disease (spatial statistics)

8. Dual kernel rate smoothing Primary layer: households with cases Secondary layer: All households Clusters of disease Red – households with cases Yellow – households without cases

9. Investigation participants and partners • Brazilian Health Ministry • Paraná State Health Secretary (SES) • Mariluz Municipal Health Secretary (SMS) • Research Institutes (Fiocruz, Brasilia University, Maringá University) • Landless Workers' Movement (MST)

10. Unusual acute toxoplasmosis cases in an urban area • Mapping the city water supply system • Residence location used as a proxy of exposure Waterborne Toxoplasmosis, Brazil

11. Water reservoir contamination by cat faeces Waterborne Toxoplasmosis, BrazilMoura et al. (2006) Emerging Infectious Diseases, CDC Santa Isabel do Ivai 138 (88%) of cases lived in the area served by reservoir A and 17 individuals lived in area served by reservoir B

12. Hantavirosis transmission foci identification Rio Grande do Sul • Hantavirus Pulmonary Syndrome (HPS) is a disease of increasing incidence in Rio Grande do Sul state • The spatial distribution of cases is apparently scattered in the state • The aim of spatial analysis was to investigate the role of agriculture activities and changing ecosystem in the virus transmission Case location > Transmission pattern identification > Preventive measures Henkes, 2004

13. Hantavirosis transmission foci identification Rio Grande do Sul The majority of cases occurred during spring, in highland areas dominated by secondary vegetation and agricultural activity An example of mapping and deciding in a regional level Henkes, 2004

14. Information flux and Health Surveillance Network Epidemiological investigation and technical support Data consolidation and analysis Laboratory confirmation Primary epidemiological investigation Case diagnostic and notification • Highly hierarchical (different roles in each level) • Decentralized (present in all municipalities) • Unequal (different capabilities and resources)

15. Live newborn Information system – SINASC • National Disease Notification System – SINAN • Mortality Information system – SIM • Hospital Information system – SIH Health information systems Plenty of data But... Poor quality, Incomplete coverage Low capacity to analysis

16. National disease surveillance Imediate notification of: • Suspected or confirmed case of: Botulism, Carbuncle or Anthrax, Cholera, Yellow Fever, West Nile Fever, Hantavirus, Human Influenza by a new sub-type, Plague, Poliomyelitis, Human Rabies, Measles, Acute Icterohemorrhagic Fever, SARS, Smallpox and Tularemia • Outbreak or clustering of cases or deaths by: Unusual aggravations (unknown disease or epidemiologic changes in known diseases), Diphtheria, Acute Chagas Disease, Meningococcal Disease • Epizootic and/or death of animals that could precede the occurrence of diseases in humans: Epizootic in non-human primates, other epizootics of epidemiologic importance

17. Peopleware (Courses) Software (Free and open) Dataware (Health, population and cartographical data) Technological and methodological development GIS and RS demands for Public Health RIPSA, 2003

18. Brazilian free (and user-friendly) programs TerraReads images andshapefiles, several spatial analysis tools. TabwinCalculates health indicators and produces simple thematic maps

19. Coordenadas do centro do aglomerado Raio de 1 km Other available programs

20. Available satellite images Embrapa: Composed Landsat-TM bands 3, 4 and 5 INPE: Raw and classified CBERS images

21. Alarm Investigation Analysis Knowledge Gathering data Spatial analysis Interpretation Field work Geocoding A long and winding road… The agricultural activities provide intensive contact with the virus. The degradation of naturally forested areas and the invasion of intensive agriculture practices alter the habitat of rodents, increasing food availability due to grain storage. • What kind of data we need? Where are them? • Which objects must be mapped and how to georeference data? • What kind of statistics do we use? Which software?

22. Free data and softwareAll data used are free and available Decentralized and coordinated actionsOutbreaks are detected, investigated and followed by local health authorities, supported by a national task force and accompanied by NGO Theory-driven investigationsInstead of technology-driven Necessities