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 clim...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-05-01
|
| Series: | Parasite Epidemiology and Control |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405673123000144 |
| _version_ | 1797827777824555008 |
|---|---|
| author | 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 |
| author_facet | 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 |
| author_sort | Bryan O. Nyawanda |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-09T12:53:48Z |
| format | Article |
| id | doaj.art-6edb8ae998ac4048871951147e25df15 |
| institution | Directory Open Access Journal |
| issn | 2405-6731 |
| language | English |
| last_indexed | 2024-04-09T12:53:48Z |
| publishDate | 2023-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Parasite Epidemiology and Control |
| spelling | doaj.art-6edb8ae998ac4048871951147e25df152023-05-14T04:29:08ZengElsevierParasite Epidemiology and Control2405-67312023-05-0121e00297The 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 2019Bryan O. Nyawanda0Anton Beloconi1Sammy Khagayi2Godfrey Bigogo3David Obor4Nancy A. Otieno5Stefan Lange6Jonas Franke7Rainer Sauerborn8Jürg Utzinger9Simon Kariuki10Stephen Munga11Penelope Vounatsou12Kenya Medical Research Institute - Centre for Global Health Research, Kisumu, Kenya; Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, SwitzerlandSwiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, SwitzerlandKenya Medical Research Institute - Centre for Global Health Research, Kisumu, KenyaKenya Medical Research Institute - Centre for Global Health Research, Kisumu, KenyaKenya Medical Research Institute - Centre for Global Health Research, Kisumu, KenyaKenya Medical Research Institute - Centre for Global Health Research, Kisumu, KenyaPotsdam Institute for Climate Impact Research, Potsdam, GermanyRemote Sensing Solutions GmbH, Munich, GermanyHeidelberg Institute of Global Health, Heidelberg University, Heidelberg, GermanySwiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, SwitzerlandKenya Medical Research Institute - Centre for Global Health Research, Kisumu, KenyaKenya Medical Research Institute - Centre for Global Health Research, Kisumu, KenyaSwiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland; Corresponding author at: Swiss Tropical and Public Health Institute, Allschwil, Switzerland.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.http://www.sciencedirect.com/science/article/pii/S2405673123000144AdaptationBayesian modellingBed net useClimate changeEarly warning systemsIncidence |
| spellingShingle | 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 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 Adaptation Bayesian modelling Bed net use Climate change Early warning systems Incidence |
| 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | Adaptation Bayesian modelling Bed net use Climate change Early warning systems Incidence |
| url | http://www.sciencedirect.com/science/article/pii/S2405673123000144 |
| work_keys_str_mv | AT bryanonyawanda therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT antonbeloconi therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT sammykhagayi therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT godfreybigogo therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT davidobor therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT nancyaotieno therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT stefanlange therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT jonasfranke therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT rainersauerborn therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT jurgutzinger therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT simonkariuki therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT stephenmunga therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT penelopevounatsou therelativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT bryanonyawanda relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT antonbeloconi relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT sammykhagayi relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT godfreybigogo relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT davidobor relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT nancyaotieno relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT stefanlange relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT jonasfranke relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT rainersauerborn relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT jurgutzinger relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT simonkariuki relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT stephenmunga relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 AT penelopevounatsou relativeeffectofclimatevariabilityonmalariaincidenceafterscaleupofinterventionsinwesternkenyaatimeseriesanalysisofmonthlyincidencedatafrom2008to2019 |