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气候多变对西非科特迪瓦南部疟疾传播的影响。

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

机构信息

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

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

出版信息

Int J Environ Res Public Health. 2023 Nov 23;20(23):7102. doi: 10.3390/ijerph20237102.

DOI:10.3390/ijerph20237102
PMID:38063532
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10706663/
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.

摘要

疟疾仍然是一个主要的公共卫生关注点，在非洲造成了巨大的负担。尽管已经广泛证明疟疾传播是受气候驱动的，但很少有研究评估科特迪瓦气候变量与疟疾传播之间的关系。我们使用 VECTRI 模型来预测科特迪瓦南部的疟疾传播。首先，我们使用 ERA5 温度数据和 ARC2 降雨数据测试了 VECTRI 模型在模拟疟疾传播方面的适用性。然后，我们使用来自 CORDEX-Africa 数据库的 14 个模拟中的一组预测数据来计算 VECTRI 输出，这些数据涉及 2030 年、2050 年和 2080 年的气候。VECTRI 模型的昆虫接种率（EIR）与 2010 年至 2019 年观察到的疟疾病例很好地相关，包括疟疾病例和 EIR 的峰值。然而，这两个参数之间的相关性没有统计学意义。VECTRI 模型预测，在 2030 年至 2080 年期间，两种情景（RCP8.5 和 RCP4.5）的疟疾传播都会增加。RCP8.5 的每月 EIR 非常高（1.74 到 1131.71 次/人），而 RCP4.5 为（0.48 到 908 次/人）。这些发现呼吁加大控制疟疾的力度，要考虑到气候因素的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c23c60362281/ijerph-20-07102-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/418a03aa6606/ijerph-20-07102-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/02eab1a2f6d4/ijerph-20-07102-g0A2a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/0e867dcd7860/ijerph-20-07102-g0A3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/30bdac3f156c/ijerph-20-07102-g0A4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/fbafaa7ed339/ijerph-20-07102-g0A5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c36077b2ced4/ijerph-20-07102-g0A6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/cc4c02f3ed2c/ijerph-20-07102-g0A7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/853a2f2976fd/ijerph-20-07102-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c241f0c435e7/ijerph-20-07102-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/0e80ee2f7f17/ijerph-20-07102-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/77cf365f9e80/ijerph-20-07102-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/bf6d5a58d795/ijerph-20-07102-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/23b2844c1a93/ijerph-20-07102-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c23c60362281/ijerph-20-07102-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/418a03aa6606/ijerph-20-07102-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/02eab1a2f6d4/ijerph-20-07102-g0A2a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/0e867dcd7860/ijerph-20-07102-g0A3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/30bdac3f156c/ijerph-20-07102-g0A4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/fbafaa7ed339/ijerph-20-07102-g0A5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c36077b2ced4/ijerph-20-07102-g0A6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/cc4c02f3ed2c/ijerph-20-07102-g0A7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/853a2f2976fd/ijerph-20-07102-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c241f0c435e7/ijerph-20-07102-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/0e80ee2f7f17/ijerph-20-07102-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/77cf365f9e80/ijerph-20-07102-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/bf6d5a58d795/ijerph-20-07102-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/23b2844c1a93/ijerph-20-07102-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6436/10706663/c23c60362281/ijerph-20-07102-g007.jpg

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