Influence of future climate scenarios using CMIP 5 data on malaria transmission in India.

Publisher: BioMed Central Country of Publication: England NLM ID: 101139802 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2875 (Electronic) Linking ISSN: 14752875 NLM ISO Abbreviation: Malar J Subsets: MEDLINE

Original Publication: London : BioMed Central, [2002-

Malaria*/transmission ; Malaria*/epidemiology ; Climate Change*; India/epidemiology ; Humans ; Animals ; Mosquito Vectors/physiology ; Anopheles/physiology

Background: Vector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial.
Methods: This study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria's Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. Three RCP scenarios are considered (Representative Concentration Pathways are climate change scenarios that project radiative forcing to 2100 due to future greenhouse gas concentrations). The projections covered the period from 1 Jan, 2020, to 31 Dec, 2029.
Results: The estimated mean EIR for the years 2020-2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each year 0.3 to 2.6 [min-max] EIR/person/day decline is observed with a strong decline in man rainfall ranging from 5 to 17 [min-max] mm/year and associated high temperatures ranging from 0.03 to 0.06 [min-max] °C/year. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk, which kept increasing through RCP scenarios. Thus, it is essential to exercise caution, especially in areas with heavy rainfall.
Conclusion: This research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health.
(© 2024. The Author(s).)

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Keywords: CMIP5 data; Climate change; EIR; Malaria risk; VECTRI model

Date Created: 20241009 Date Completed: 20241010 Latest Revision: 20241012

20241012

PMC11462906

10.1186/s12936-024-05129-0

39385165