Evidence map›Paper›PMID 39385165›Full record

ArticleMalaria journal2024

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

Subrahmanya Hari Prasad Peri

Abstract read
In one paragraph

Article in Malaria journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

1 author.

Subrahmanya Hari Prasad PeriCentre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, Kharagpur, 721 302, India. pshari19@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVector-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.

methodsThis 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.

resultsThe 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.

conclusionThis 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.

Indexed as

Climate ChangeMalariaAnimalsAnophelesHumansIndiaMosquito VectorsClimate changeCMIP5 dataEIRMalaria riskVECTRI model

Identifiers

PMID39385165
PMCPMC11462906

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.