Projecting Malaria Incidence Based on Climate Change Modeling Approach: A Systematic Review

Mazni Baharom; Sharifah Saffinas Syed Soffian; Chua Su Peng; Mohd Hafiz Baharudin; Ummi Mirza; Mohd Faizal Madrim; Mohammad Saffree Jeffree; Syed Sharizman Syed Abdul Rahim; Mohd Rohaizat Hassan

doi:10.3889/oamjms.2022.10141

Authors

Mazni Baharom Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia
Sharifah Saffinas Syed Soffian Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia https://orcid.org/0000-0003-2721-3084
Chua Su Peng Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia https://orcid.org/0000-0002-9460-5929
Mohd Hafiz Baharudin Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia
Ummi Mirza Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia https://orcid.org/0000-0001-9170-3155
Mohd Faizal Madrim Department of Public Health Medicine, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
Mohammad Saffree Jeffree Department of Public Health Medicine, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
Syed Sharizman Syed Abdul Rahim Department of Public Health Medicine, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia https://orcid.org/0000-0002-9090-2563
Mohd Rohaizat Hassan Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.3889/oamjms.2022.10141

Keywords:

Projection, Malaria incidence, Climate change, Modelling, Public health

Abstract

BACKGROUND: Climate change will affect the transmission of malaria by shifting the geographical space of the vector.

AIM: The review aims to examine the climate change modeling approach and climatic variables used for malaria projection.

METHODS: Articles were systematically searched from four databases, Scopus, Web of Science, PubMed, and SAGE. The PICO concept was used for formulation search and PRISMA approach to identify the final articles.

RESULTS: A total of 27 articles were retrieved and reviewed. There were six climate factors identified in this review: Temperature, rainfall/precipitation, humidity, wind, solar radiation, and climate change scenarios. Modeling approaches used to project future malarial trend includes mathematical and computational approach.

CONCLUSION: This review provides robust evidence of an association between the impact of climate change and malaria incidence. Prediction on seasonal patterns would be useful for malaria surveillance in public health prevention and mitigation strategies.

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