Prioritization of Malaria endemic zones in Arunachal Pradesh: A novel application of self organizing maps (SOM)

Abstract

Malaria continues to pose a serious threat to public health in NorthEastern states of India. Arunachal Pradesh is highly endemic for Malaria predominately with Plasmodium falciparium infections. Despite continuous efforts by government, a desirable level of control has not been achieved. The present study describes the application of self organizing maps (Kohonen maps), a data mining tool for prioritization of malaria endemic zones in this region. 60 PHCs (Public Health Centers) were randomly selected from Arunachal Pradesh and 6 malariometric parameters via Annual Blood Examination rate (ABER), Annual Parasite Incidence (API), Slide Positivity Rate (SPR), Annual Falciparum Incidence (AFI) and Slide Falciparum Rate (SFR) were considered which reflected the intensity of malaria transmission in this region. Self Organizing Maps yielded 9 clusters based on neighborhood distance, which reflects about zones based on status of intensity of malaria epidemiology. Such maps would make it possible to target control measures at high-risk areas and greatly increase the cost efficiency of malaria control programmes.