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  The relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya: A time-series analysis of monthly incidence data from 2008 to 2019

Nyawanda, B. O., Beloconi, A., Khagayi, S., Bigogo, G., Obor, D., Otieno, N. A., Lange, S., Franke, J., Sauerborn, R., Utzinger, J., Kariuki, S., Munga, S., Vounatsou, P. (2023): The relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya: A time-series analysis of monthly incidence data from 2008 to 2019. - Parasite Epidemiology and Control, 21, e00297.
https://doi.org/10.1016/j.parepi.2023.e00297

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???ViewItemFull_lblCiteItemAs???: https://publications.pik-potsdam.de/pubman/item/item_28233 ???ViewItemFull_lblCiteItemVersionAs???: https://publications.pik-potsdam.de/pubman/item/item_28233_2
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 ???ViewItemFull_lblCreators???:
Nyawanda, Bryan O.1, ???ENUM_CREATORROLE_AUTHOR???
Beloconi, Anton1, ???ENUM_CREATORROLE_AUTHOR???
Khagayi, Sammy1, ???ENUM_CREATORROLE_AUTHOR???
Bigogo, Godfrey1, ???ENUM_CREATORROLE_AUTHOR???
Obor, David1, ???ENUM_CREATORROLE_AUTHOR???
Otieno, Nancy A.1, ???ENUM_CREATORROLE_AUTHOR???
Lange, Stefan2, ???ENUM_CREATORROLE_AUTHOR???           
Franke, Jonas1, ???ENUM_CREATORROLE_AUTHOR???
Sauerborn, Rainer1, ???ENUM_CREATORROLE_AUTHOR???
Utzinger, Jürg1, ???ENUM_CREATORROLE_AUTHOR???
Kariuki, Simon1, ???ENUM_CREATORROLE_AUTHOR???
Munga, Stephen1, ???ENUM_CREATORROLE_AUTHOR???
Vounatsou, Penelope1, ???ENUM_CREATORROLE_AUTHOR???
???ViewItemFull_lblAffiliations???:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 ???ViewItemFull_lblAbstract???: Background:
Despite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya. -
Methods:
Bayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital between 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence. -
Results:
Malaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59–0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10–1.44). Bed net use was associated with a decline in malaria incidence in children aged 6–59 months (IRR = 0.78, 95% BCI: 0.70–0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population. -
Conclusions:
Variability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6–59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.

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???ViewItemFull_lblLanguages???: eng - English
 ???ViewItemFull_lblDates???: 2022-10-222023-03-122023-03-152023-05
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1016/j.parepi.2023.e00297
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD3 - Transformation Pathways
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???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Data-Centric Modeling of Cross-Sectoral Impacts
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???ENUM_IDENTIFIERTYPE_REGIONALK???: Africa
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Climate impacts
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Health
???ENUM_IDENTIFIERTYPE_MODELMETHOD???: Quantitative Methods
???ENUM_IDENTIFIERTYPE_OATYPE???: Gold Open Access
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???ViewItemFull_lblSourceTitle???: Parasite Epidemiology and Control
???ViewItemFull_lblSourceGenre???: ???ENUM_GENRE_JOURNAL???, Scopus, oa
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