Enhancing Understanding of the Impact of Climate Change on Malaria in West Africa Using the Vector-Borne Disease Community Model of the International Center for Theoretical Physics (VECTRI) and the Bias-Corrected Phase 6 Coupled Model Intercomparison Project Data (CMIP6)

IF 2.1 Q3 MICROBIOLOGY

Microbiology Research Pub Date : 2023-12-18 DOI:10.3390/microbiolres14040145

Papa Fall, Ibrahima Diouf, A. Deme, Sémou Diouf, D. Sène, Benjamin Sultan, Serge Janicot

{"title":"Enhancing Understanding of the Impact of Climate Change on Malaria in West Africa Using the Vector-Borne Disease Community Model of the International Center for Theoretical Physics (VECTRI) and the Bias-Corrected Phase 6 Coupled Model Intercomparison Project Data (CMIP6)","authors":"Papa Fall, Ibrahima Diouf, A. Deme, Sémou Diouf, D. Sène, Benjamin Sultan, Serge Janicot","doi":"10.3390/microbiolres14040145","DOIUrl":null,"url":null,"abstract":"In sub-Saharan Africa, temperatures are generally conducive to malaria transmission, and rainfall provides mosquitoes with optimal breeding conditions. The objective of this study is to assess the impact of future climate change on malaria transmission in West Africa using community-based vector-borne disease models, TRIeste (VECTRI). This VECTRI model, based on bias-corrected data from the Phase 6 Coupled Model Intercomparison Project (CMIP6), was used to simulate malaria parameters, such as the entomological inoculation rate (EIR). Due to the lack of data on confirmed malaria cases throughout West Africa, we first validated the forced VECTRI model with CMIP6 data in Senegal. This comparative study between observed malaria data from the National Malaria Control Program in Senegal (Programme National de Lutte contre le Paludisme, PNLP, PNLP) and malaria simulation data with the VECTRI (EIR) model has shown the ability of the biological model to simulate malaria transmission in Senegal. We then used the VECTRI model to reproduce the historical characteristics of malaria in West Africa and quantify the projected changes with two Shared Socio-economic Pathways (SSPs). The method adopted consists of first studying the climate in West Africa for a historical period (1950–2014), then evaluating the performance of VECTRI to simulate malaria over the same period (1950–2014), and finally studying the impact of projected climate change on malaria in a future period (2015–2100) according to the ssp245 ssp585 scenario. The results showed that low-latitude (southern) regions with abundant rainfall are the areas most affected by malaria transmission. Two transmission peaks are observed in June and October, with a period of high transmission extending from May to November. In contrast to regions with high latitudes in the north, semi-arid zones experience a relatively brief transmission period that occurs between August, September, and October, with the peak observed in September. Regarding projections based on the ssp585 scenario, the results indicate that, in general, malaria prevalence will gradually decrease in West Africa in the distant future. But the period of high transmission will tend to expand in the future. In addition, the shift of malaria prevalence from already affected areas to more suitable areas due to climate change is observed. Similar results were also observed with the ssp245 scenario regarding the projection of malaria prevalence. In contrast, the ssp245 scenario predicts an increase in malaria prevalence in the distant future, while the ssp585 scenario predicts a decrease. These findings are valuable for decision makers in developing public health initiatives in West Africa to mitigate the impact of this disease in the region in the context of climate change.","PeriodicalId":43788,"journal":{"name":"Microbiology Research","volume":"27 7","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbiology Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/microbiolres14040145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MICROBIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

In sub-Saharan Africa, temperatures are generally conducive to malaria transmission, and rainfall provides mosquitoes with optimal breeding conditions. The objective of this study is to assess the impact of future climate change on malaria transmission in West Africa using community-based vector-borne disease models, TRIeste (VECTRI). This VECTRI model, based on bias-corrected data from the Phase 6 Coupled Model Intercomparison Project (CMIP6), was used to simulate malaria parameters, such as the entomological inoculation rate (EIR). Due to the lack of data on confirmed malaria cases throughout West Africa, we first validated the forced VECTRI model with CMIP6 data in Senegal. This comparative study between observed malaria data from the National Malaria Control Program in Senegal (Programme National de Lutte contre le Paludisme, PNLP, PNLP) and malaria simulation data with the VECTRI (EIR) model has shown the ability of the biological model to simulate malaria transmission in Senegal. We then used the VECTRI model to reproduce the historical characteristics of malaria in West Africa and quantify the projected changes with two Shared Socio-economic Pathways (SSPs). The method adopted consists of first studying the climate in West Africa for a historical period (1950–2014), then evaluating the performance of VECTRI to simulate malaria over the same period (1950–2014), and finally studying the impact of projected climate change on malaria in a future period (2015–2100) according to the ssp245 ssp585 scenario. The results showed that low-latitude (southern) regions with abundant rainfall are the areas most affected by malaria transmission. Two transmission peaks are observed in June and October, with a period of high transmission extending from May to November. In contrast to regions with high latitudes in the north, semi-arid zones experience a relatively brief transmission period that occurs between August, September, and October, with the peak observed in September. Regarding projections based on the ssp585 scenario, the results indicate that, in general, malaria prevalence will gradually decrease in West Africa in the distant future. But the period of high transmission will tend to expand in the future. In addition, the shift of malaria prevalence from already affected areas to more suitable areas due to climate change is observed. Similar results were also observed with the ssp245 scenario regarding the projection of malaria prevalence. In contrast, the ssp245 scenario predicts an increase in malaria prevalence in the distant future, while the ssp585 scenario predicts a decrease. These findings are valuable for decision makers in developing public health initiatives in West Africa to mitigate the impact of this disease in the region in the context of climate change.

查看原文本刊更多论文

利用国际理论物理中心（VECTRI）的病媒传染病群落模型和经偏差校正的第 6 阶段耦合模型相互比较项目数据（CMIP6），加深理解气候变化对西非疟疾的影响

在撒哈拉以南非洲地区，气温通常有利于疟疾的传播，而降雨则为蚊子提供了最佳的繁殖条件。这项研究的目的是利用基于社区的病媒传播疾病模型 TRIeste（VECTRI），评估未来气候变化对西非疟疾传播的影响。该 VECTRI 模型基于第六阶段耦合模型相互比较项目（CMIP6）的偏差校正数据，用于模拟疟疾参数，如昆虫接种率（EIR）。由于缺乏整个西非的疟疾确诊病例数据，我们首先在塞内加尔利用 CMIP6 数据验证了 VECTRI 强制模型。塞内加尔国家疟疾控制项目（PNLP）的疟疾观测数据与 VECTRI（EIR）模型的疟疾模拟数据之间的比较研究表明，生物模型有能力模拟塞内加尔的疟疾传播情况。随后，我们利用 VECTRI 模型再现了西非疟疾的历史特征，并量化了两种共享社会经济路径（SSP）的预测变化。所采用的方法包括：首先研究西非历史时期（1950-2014 年）的气候，然后评估 VECTRI 模拟同一时期（1950-2014 年）疟疾的性能，最后根据 ssp245 ssp585 情景研究预测气候变化对未来时期（2015-2100 年）疟疾的影响。结果表明，降雨丰富的低纬度（南部）地区是疟疾传播最严重的地区。6 月和 10 月出现两个传播高峰，5 月至 11 月为高传播期。与北部高纬度地区相比，半干旱地区的传播期相对较短，在 8 月、9 月和 10 月之间，传播高峰期出现在 9 月。关于基于 ssp585 情景的预测，结果表明，总体而言，在遥远的未来，西非的疟疾流行率将逐渐下降。但高传播期在未来将有扩大的趋势。此外，由于气候变化，疟疾流行将从已受影响的地区转移到更合适的地区。在 ssp245 情景下，对疟疾流行率的预测也出现了类似的结果。相比之下，sp245 情景预测在遥远的未来疟疾流行率会上升，而 ssp585 情景则预测会下降。这些发现对决策者在气候变化背景下制定西非公共卫生倡议以减轻该地区疟疾影响很有价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Microbiology Research MICROBIOLOGY-

CiteScore

1.90

自引率

6.70%

发文量

审稿时长

10 weeks

期刊介绍： Microbiology Research is an international, online-only, open access peer-reviewed journal which publishes original research, review articles, editorials, perspectives, case reports and brief reports to benefit researchers, microbiologists, physicians, veterinarians. Microbiology Research publishes ‘Clinic’ and ‘Research’ papers divided into two different skill and proficiency levels: ‘Junior’ and ‘Professional’. The aim of this four quadrant grid is to encourage younger researchers, physicians and veterinarians to submit their results even if their studies encompass just a limited set of observations or rely on basic statistical approach, yet upholding the customary sound approach of every scientific article.