气候变化领域集成服务门户(CCPortal): Predicting malaria risk considering vector control interventions under climate change scenarios

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DOI	10.1038/s41598-024-52724-x
	Predicting malaria risk considering vector control interventions under climate change scenarios
	Sadoine, Margaux L.; Zinszer, Kate; Liu, Ying; Gachon, Philippe; Fournier, Michel; Dueymes, Guillaume; Dorsey, Grant; Llerena, Ana; Namuganga, Jane Frances; Nasri, Bouchra; Smargiassi, Audrey
发表日期	2024
ISSN	2045-2322
起始页码	14
结束页码	1
卷号	14 期号:1
英文摘要	Many studies have projected malaria risks with climate change scenarios by modelling one or two environmental variables and without the consideration of malaria control interventions. We aimed to predict the risk of malaria with climate change considering the influence of rainfall, humidity, temperatures, vegetation, and vector control interventions (indoor residual spraying (IRS) and long-lasting insecticidal nets (LLIN)). We used negative binomial models based on weekly malaria data from six facility-based surveillance sites in Uganda from 2010-2018, to estimate associations between malaria, environmental variables and interventions, accounting for the non-linearity of environmental variables. Associations were applied to future climate scenarios to predict malaria distribution using an ensemble of Regional Climate Models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Predictions including interaction effects between environmental variables and interventions were also explored. The results showed upward trends in the annual malaria cases by 25% to 30% by 2050s in the absence of intervention but there was great variability in the predictions (historical vs RCP 4.5 medians [Min-Max]: 16,785 [9,902-74,382] vs 21,289 [11,796-70,606]). The combination of IRS and LLIN, IRS alone, and LLIN alone would contribute to reducing the malaria burden by 76%, 63% and 35% respectively. Similar conclusions were drawn from the predictions of the models with and without interactions between environmental factors and interventions, suggesting that the interactions have no added value for the predictions. The results highlight the need for maintaining vector control interventions for malaria prevention and control in the context of climate change given the potential public health and economic implications of increasing malaria in Uganda.
语种	英语
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:001158267500069
来源期刊	SCIENTIFIC REPORTS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/308344
作者单位	Universite de Montreal; Universite de Montreal; University of Quebec; University of Quebec Montreal; University of California System; University of California San Francisco; University of Quebec; University of Quebec Montreal
推荐引用方式 GB/T 7714	Sadoine, Margaux L.,Zinszer, Kate,Liu, Ying,et al. Predicting malaria risk considering vector control interventions under climate change scenarios[J],2024,14(1).
APA	Sadoine, Margaux L..,Zinszer, Kate.,Liu, Ying.,Gachon, Philippe.,Fournier, Michel.,...&Smargiassi, Audrey.(2024).Predicting malaria risk considering vector control interventions under climate change scenarios.SCIENTIFIC REPORTS,14(1).
MLA	Sadoine, Margaux L.,et al."Predicting malaria risk considering vector control interventions under climate change scenarios".SCIENTIFIC REPORTS 14.1(2024).