4.7 Article

The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 30, Issue 21, Pages 59194-59211

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-023-26672-4

Keywords

Malaria; Climate; GAM; Prediction; Meghalaya and Tripura

Ask authors/readers for more resources

This study explores the epidemiological profile and quantifies the climate-induced influence on malaria in the northeast region of India. Monthly malaria cases and meteorological data were collected from Meghalaya and Tripura, and the nonlinear associations between meteorological factors and malaria cases were assessed. The study found that both individual climatic factors and synergistic effects can significantly increase the risk of malaria transmission.
The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively. The nonlinear associations between individual and synergistic effect of meteorological factors and malaria cases were assessed, and climate-based malaria prediction models were developed using the generalized additive model (GAM) with Gaussian distribution. During the study period, a total of 216,943 and 125,926 cases were recorded in Meghalaya and Tripura, respectively, and majority of the cases occurred due to the infection of Plasmodium falciparum in both the states. The temperature and relative humidity in Meghalaya and temperature, rainfall, relative humidity, and soil moisture in Tripura showed a significant nonlinear effect on malaria; moreover, the synergistic effects of temperature and relative humidity (SI=2.37, RERI=0.58, AP=0.29) and temperature and rainfall (SI=6.09, RERI=2.25, AP=0.61) were found to be the key determinants of malaria transmission in Meghalaya and Tripura, respectively. The developed climate-based malaria prediction models are able to predict the malaria cases accurately in both Meghalaya (RMSE: 0.0889; R-2: 0.944) and Tripura (RMSE: 0.0451; R-2: 0.884). The study found that not only the individual climatic factors can significantly increase the risk of malaria transmission but also the synergistic effects of climatic factors can drive the malaria transmission multifold. This reminds the policymakers to pay attention to the control of malaria in situations with high temperature and relative humidity and high temperature and rainfall in Meghalaya and Tripura, respectively.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available