Effects of Climate Variability on Malaria Transmission in Southern Côte d’Ivoire, West Africa-Reference-Cited by-同舟云学术

Effects of Climate Variability on Malaria Transmission in Southern Côte d’Ivoire, West Africa

Published:2023-11-23 Issue:23 Volume:20 Page:7102
ISSN:1660-4601
Container-title:International Journal of Environmental Research and Public Health
language:en
Short-container-title:IJERPH

Author:

Doumbia Madina¹²^ORCID,Coulibaly Jean Tenena²³^ORCID,Silué Dieudonné Kigbafori²³^ORCID,Cissé Guéladio⁴⁵^ORCID,N’Dione Jacques-André⁶,Koné Brama¹²^ORCID

Affiliation:

1. Unité de Formation et de Recherche des Sciences Biologiques, Université Péléforo Gon Coulibaly, Korhogo BP 1328, Côte d’Ivoire

2. Centre Suisse de Recherches Scientifiques en Côte d’Ivoire (CSRS), Abidjan 01 BP 1303, Côte d’Ivoire

3. Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire

4. Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, CH 4002 Basel, Switzerland

5. Faculty of Science, University of Basel, CH-4003 Basel, Switzerland

6. Centre de Suivi Ecologique, BP 15532, Fann Résidense, Dakar 10700, Senegal

Abstract

Malaria continues to be a major public health concern with a substantial burden in Africa. Even though it has been widely demonstrated that malaria transmission is climate-driven, there have been very few studies assessing the relationship between climate variables and malaria transmission in Côte d’Ivoire. We used the VECTRI model to predict malaria transmission in southern Côte d’Ivoire. First, we tested the suitability of VECTRI in modeling malaria transmission using ERA5 temperature data and ARC2 rainfall data. We then used the projected climatic data pertaining to 2030, 2050, and 2080 from a set of 14 simulations from the CORDEX-Africa database to compute VECTRI outputs. The entomological inoculation rate (EIR) from the VECTRI model was well correlated with the observed malaria cases from 2010 to 2019, including the peaks of malaria cases and the EIR. However, the correlation between the two parameters was not statistically significant. The VECTRI model predicted an increase in malaria transmissions in both scenarios (RCP8.5 and RCP4.5) for the time period 2030 to 2080. The monthly EIR for RCP8.5 was very high (1.74 to 1131.71 bites/person) compared to RCP4.5 (0.48 to 908 bites/person). These findings call for greater efforts to control malaria that take into account the impact of climatic factors.

Funder

African Academy of Sciences

Publisher

MDPI AG

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Link

https://www.mdpi.com/1660-4601/20/23/7102/pdf

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