Using geographical and malaria information systems for enhanced malaria control
ABSTRACT Introduction The use of information systems to understand the dynamics of malaria disease and inform decisions on control proved valuable to a malaria control programme. Development of simple practical and sustainable information system tools has been slow in coming for many resource-poor environments. This thesis addresses many issues relating to the conceptual development and implementation of simple tools and their integration into operational malaria control to support decision making and advocacy. Methods A basic Microsoft Access malaria data collection and repository tool has been in existence since 1997 focussing mainly on case reporting alone. Better utilization of data and further expansion to include outbreak identification and response, cluster detection and intervention monitoring has been the main focus over time. Eight years of retrospective malaria case data from Mpumalanga Province, South Africa were used to explore disease dynamics including spatial as well as temporal variation in malaria epidemiology. The identification of specific risk areas and the confirmation of the unstable nature of malaria occurrence lead to the conceptualization and development of an outbreak model using binomial statistics. The novel three tier outbreak identification and response system was field tested over a two season period to establish acceptance and the ability to direct resources in times of elevated case loads. Comparison against other existing malaria outbreak systems was conducted. SaTScan freely available software was used to detect spatial and spacetime disease clusters within towns in the highest risk area of the province. A malaria case control study was conducted in seven localities/towns/villages to explore risk and protective characteristics of household structure and practices, including the use of impregnated nets. The micro economic status of households as a determinant of malaria risk was also explored. A spray operations component as part of the malaria information system was developed and implemented during the time to allow for routine monitoring and historical exploration of indoor residual spray activities. Results Retrospective malaria case data analysis identified heterogeneity of malaria risk in the Province and spatial analysis identified significant clusters at small geographical area resolution rejecting the hypothesis that malaria is homogeneously distributed over space and time. The importance of intervention monitoring to identify low coverage areas, over or under application of insecticides, and assessment of the productivity of spray operators was identified. The outbreak identification and response system was successfully implemented, integrated and sustained with a set of response activities developed for implementation at defined threshold levels. The outbreak systems can be considered for utilization in other low transmission settings.Results of the case control study indicated that malaria risk was associated with living in traditional housing and the practice of re-opening windows at night when peak biting behaviour of the main mosquito vector, Anopoheles arabiensis is expected. Higher household socio economic status (SES) profile was associated with a lower risk of malaria. Conclusions The conceptualization, development and implementation of operationally feasible malaria information management tools in a rural African environment proved useful for enhancing malaria control. The novel malaria outbreak identification and response, cluster detection as well as the spray monitoring systems were successfully implemented and adopted as an integral part of the routine malaria control programme monitoring and surveillance system. This research has enabled more informed real-time decision-making for effective programme management.
Information systems , GIS , Malaria , Control