Bryan O. Nyawanda , Anton Beloconi , Sammy Khagayi , Godfrey Bigogo , David Obor , Nancy A. Otieno , Stefan Lange , Jonas Franke , Rainer Sauerborn , Jürg Utzinger , Simon Kariuki , Stephen Munga , Penelope Vounatsou
{"title":"肯尼亚西部扩大干预措施后气候变化对疟疾发病率的相对影响：2008年至2019年月度发病率数据的时间序列分析","authors":"Bryan O. Nyawanda , Anton Beloconi , Sammy Khagayi , Godfrey Bigogo , David Obor , Nancy A. Otieno , Stefan Lange , Jonas Franke , Rainer Sauerborn , Jürg Utzinger , Simon Kariuki , Stephen Munga , Penelope Vounatsou","doi":"10.1016/j.parepi.2023.e00297","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>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.</p></div><div><h3>Conclusions</h3><p>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.</p></div>","PeriodicalId":37873,"journal":{"name":"Parasite Epidemiology and Control","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068258/pdf/main.pdf","citationCount":"1","resultStr":"{\"title\":\"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\",\"authors\":\"Bryan O. Nyawanda , Anton Beloconi , Sammy Khagayi , Godfrey Bigogo , David Obor , Nancy A. Otieno , Stefan Lange , Jonas Franke , Rainer Sauerborn , Jürg Utzinger , Simon Kariuki , Stephen Munga , Penelope Vounatsou\",\"doi\":\"10.1016/j.parepi.2023.e00297\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>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.</p></div><div><h3>Conclusions</h3><p>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.</p></div>\",\"PeriodicalId\":37873,\"journal\":{\"name\":\"Parasite Epidemiology and Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068258/pdf/main.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Parasite Epidemiology and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405673123000144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parasite Epidemiology and Control","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405673123000144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
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
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.
期刊介绍：
Parasite Epidemiology and Control is an Open Access journal. There is an increasing amount of research in the parasitology area that analyses the patterns, causes, and effects of health and disease conditions in defined populations. This epidemiology of parasite infectious diseases is predominantly studied in human populations but also spans other major hosts of parasitic infections and as such this journal will have a broad remit. We will focus on the major areas of epidemiological study including disease etiology, disease surveillance, drug resistance and geographical spread and screening, biomonitoring, and comparisons of treatment effects in clinical trials for both human and other animals. We will also look at the epidemiology and control of vector insects. The journal will also cover the use of geographic information systems (Epi-GIS) for epidemiological surveillance which is a rapidly growing area of research in infectious diseases. Molecular epidemiological approaches are also particularly encouraged.
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