Malaria, climate variability, and interventions: modelling transmission dynamics

被引：17

作者：

Beloconi, Anton ^{[1
,2
]}

Nyawanda, Bryan O. ^{[1
,2
,3
]}

Bigogo, Godfrey ^{[3
]}

Khagayi, Sammy ^{[3
]}

Obor, David ^{[3
]}

Danquah, Ina ^{[4
]}

Kariuki, Simon ^{[3
]}

Munga, Stephen ^{[3
]}

Vounatsou, Penelope ^{[1
,2
]}

机构：

[1] Swiss Trop & Publ Hlth Inst, Allschwil, Switzerland

[2] Univ Basel, Basel, Switzerland

[3] Kenya Govt Med Res Ctr, Ctr Global Hlth Res, Kisumu, Kenya

[4] Heidelberg Univ, Med Fac & Univ Hosp, Heidelberg Inst Global Hlth HIGH, Heidelberg, Germany

来源：

SCIENTIFIC REPORTS | 2023年 / 13卷 / 01期

基金：

瑞士国家科学基金会;

关键词：

TEMPERATURE; IMMUNITY; INFERENCE; RAINFALL; DRIVEN; FUTURE; SYSTEM; IMPACT;

D O I：

10.1038/s41598-023-33868-8

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Assessment of the relative impact of climate change on malaria dynamics is a complex problem. Climate is a well-known factor that plays a crucial role in driving malaria outbreaks in epidemic transmission areas. However, its influence in endemic environments with intensive malaria control interventions is not fully understood, mainly due to the scarcity of high-quality, long-term malaria data. The demographic surveillance systems in Africa offer unique platforms for quantifying the relative effects of weather variability on the burden of malaria. Here, using a process-based stochastic transmission model, we show that in the lowlands of malaria endemic western Kenya, variations in climatic factors played a key role in driving malaria incidence during 2008-2019, despite high bed net coverage and use among the population. The model captures some of the main mechanisms of human, parasite, and vector dynamics, and opens the possibility to forecast malaria in endemic regions, taking into account the interaction between future climatic conditions and intervention scenarios.

引用

页数：12

共 51 条

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