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

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Abstract

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; R2: 0.944) and Tripura (RMSE: 0.0451; R2: 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.

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Acknowledgements

The authors are grateful to the Directors of the Council of Scientific and Industrial Research-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad, and 4PI, Bangalore, for their encouragement and support. Srinivasa Rao Mutheneni is grateful to the MoEF & CC (Ministry of Environment Forest & Climate Change), Govt. of India, for EIACP Centre on Climate Change & Public Health. CSIR-IICT communication number of the article is IICT/Pubs./2022/398.

Funding

The present work is supported by the DST (Department of Science and Technology) under Epidemiology Data Analytics (EDA) of Interdisciplinary Cyber-Physical Systems (ICPS) program (Grant number: DST/ICPS/EDA/2018), Govt. of India.

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Authors and Affiliations

  1. EIACP Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, Telangana, 500007, India

    Nikhila Yaladanda, Rajasekhar Mopuri, Hariprasad Vavilala, Madhusudhan Rao Kadiri & Srinivasa Rao Mutheneni

  2. Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India

    Nikhila Yaladanda, Hariprasad Vavilala & Srinivasa Rao Mutheneni

  3. CSIR-Fourth Paradigm Institute, NAL Belur Campus, Bangalore, Karnataka, 560037, India

    Kantha Rao Bhimala & Krushna Chandra Gouda

  4. National Institute of Pharmaceutical Education and Research (NIPER), Sila Katamur, Halugurisuk, Changsari, Kamrup, Assam, 781101, India

    Suryanarayana Murty Upadhyayula

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  1. Nikhila Yaladanda
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Contributions

All authors contributed to the study design, data analysis, and manuscript preparation. NY, RM, HV, MRK, and SRM are involved in data compilation and preprocessing; NY and SRM were involved in data analysis and model development; RM was involved in spatial mapping; NY, RM, and SRM were involved in draft manuscript preparation; KRB, KCG, SMU, and SRM were involved in draft manuscript correction; overall work was supervised by SRM.

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Correspondence to Srinivasa Rao Mutheneni.

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Yaladanda, N., Mopuri, R., Vavilala, H. et al. The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India. Environ Sci Pollut Res 30, 59194–59211 (2023). https://doi.org/10.1007/s11356-023-26672-4

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