Spatiotemporal distribution of rift valley fever and malaria vectors in Baringo County, Kenya: Implications on vector control
Alfred O. Ochieng, Fred Amimo, Christopher Oludhe, Isaac K. Nyamongo, Benson Estambale
Abstract
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Alfred O. Ochieng, Fred Amimo, Christopher Oludhe, Isaac K. Nyamongo, Benson Estambale
Abstract
Open-access reader
Rift Valley Fever and malaria are zoonotic and human diseases respectively that pose major production and health challenges to pastoralists. This study aimed to determine the spatiotemporal distribution of mosquito vectors of these two diseases in Baringo County, Kenya. A longitudinal study design was used to collect mosquitoes from twenty four sites. Rainfall seasonality was determined using rainfall data from the WorldClim database. Negative binomial and zero-inflated negative binomial regression models were used to determine the effect of rainfall seasonality and ecogeographical conditions on vector distribution. Spatio-temporal maps showing vector distribution were made using the sf package in R. Four Rift Valley Fever vector species and four malaria vector species were collected and were predominantly found in the lowland and riverine zones. Vector control interventions against the two diseases should therefore target these two zones. The study also recommends integrated vector management methods targeting both larval and adult stages.
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Rift Valley Fever and malaria are zoonotic and human diseases respectively that pose major production and health challenges to pastoralists. This study aimed to determine the spatiotemporal distribution of mosquito vectors of these two diseases in Baringo County, Kenya. A longitudinal study design was used to collect mosquitoes from twenty four sites. Rainfall seasonality was determined using rainfall data from the WorldClim database. Negative binomial and zero-inflated negative binomial regression models were used to determine the effect of rainfall seasonality and ecogeographical conditions on vector distribution. Spatio-temporal maps showing vector distribution were made using the sf package in R. Four Rift Valley Fever vector species and four malaria vector species were collected and were predominantly found in the lowland and riverine zones. Vector control interventions against the two diseases should therefore target these two zones. The study also recommends integrated vector management methods targeting both larval and adult stages.
Key concepts: Rift Valley fever, Vector (molecular biology), Malaria, Rift valley, Geography, Distribution (mathematics), Seasonality, Vector control