Malaria risk map for India based on climate, ecology and geographical modelling
Mapping the malaria risk at various geographical levels is often undertaken considering climate suitability, infection rate and/or malaria vector distribution, while the ecological factors related to topography and vegetation cover are generally neglected. The present study abides a holistic approach to risk mapping by including topographic, climatic and vegetation components into the framework of malaria risk modelling. This work attempts to delineate the areas of Plasmodium falciparum and Plasmodium vivax malaria transmission risk in India using seven geo-ecological indicators: temperature, relative humidity, rainfall, forest cover, soil, slope, altitude and the normalized difference vegetation index using multi-criteria decision analysis based on geographical information system (GIS). The weight of the risk indicators was assigned by an analytical hierarchical process with the climate suitability (temperature and humidity) data generated using fuzzy logic. Model validation was done through both primary and secondary datasets. The spatio-ecological model was based on GIS to classify the country into five zones characterized by various levels of malaria transmission risk (very high; high; moderate; low; and very low. The study found that about 13% of the country is under very high malaria risk, which includes the malaria- endemic districts of the states of Chhattisgarh, Odisha, Jharkhand, Tripura, Assam, Meghalaya and Manipur. The study also showed that the transmission risk suitability for P. vivax is higher than that for P. falciparum in the Himalayan region. The field study corroborates the identified malaria risk zones and highlights that the low to moderate risk zones are outbreak-prone. It is expected that this information will help the National Vector Borne Disease Control Programme in India to undertake improved surveillance and conduct target based interventions.
- Abstract views: 907
- PDF: 523
- HTML: 16
Copyright (c) 2019 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.