Abstract
The future implications of climate change on malaria transmission at the global level have already been reported, however such evidences are scarce and limited in India. Here our study aims to assess, identify and map the potential effects of climate change on Plasmodium vivax (Pv) and Plasmodium falciparum (Pf) malaria transmission in India. A Fuzzy-based Climate Suitability Malaria Transmission (FCSMT) model under the GIS environment was generated using Temperature and Relative Humidity data, extracted from CORDEX South Asia for Baseline (1976–2005) and RCP 4.5 scenario for future projection by the 2030s (2021–2040). National malaria data were used at the model analysis stage. Model outcomes suggest that climate change may significantly increase the spatial spread of Pv and Pf malaria with a numerical increase in the transmission window’s (TW) months, and a shift in the months of transmission. Some areas of the western Himalayan states are likely to have new foci of Pv malaria transmission. Interior parts of some southern and eastern states are likely to become more suitable for Pf malaria transmission. Study has also identified the regions with a reduction in transmission months by the 2030s, leading to unstable malaria, and having the potential for malaria outbreaks.
Highlights
Malaria is still a major public health challenge in India, where around one million cases are reported annually [1]
Model outcomes suggest that climate change may significantly increase the spatial spread of Plasmodium vivax (Pv) and Plasmodium falciparum (Pf) malaria with a numerical increase in the transmission window’s (TW) months, and a shift in the months of transmission
Climatic suitability maps for Pv and Pf (Figures 3 and 4) show that the northern half of India remains least suitable for malaria transmission in both baseline and projected periods during first six months of the year
Summary
Malaria is still a major public health challenge in India, where around one million cases are reported annually [1]. Humidity (RH), Dhiman et al, 2011 [22] had projected the climate suitability of malaria transmission with respect to climate change by the year 2030 These regional models were developed on traditional threshold-based hard partitioning. Soft partitioning approaches like Fuzzy logic-based climate suitability models have been applied to define suitable and unsuitable areas for malaria transmission in many studies [3,23,24,25,26] around the globe, but not in India. While resolving the uncertainty in defining distinct thresholds of most suitable to least suitability, the present study adopts the soft partitioning approach using Temperature and RH to map potential malaria transmission vulnerability in the context of climate change. The near-future projected malaria transmission scenario in the present study is limited to the 2030s for two reasons: One, climate sensitivity uncertainty increases in the long term projections; and two, this study is an initiative towards the Government of India’s National Framework for Malaria Elimination in India 2016–2030 Program [27]
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