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. 2017 May 25;16(1):220.
doi: 10.1186/s12936-017-1848-2.

Effect of climatic variability on malaria trends in Baringo County, Kenya

Edwin K Kipruto  1   2 , Alfred O Ochieng  3 , Douglas N Anyona  2 , Macrae Mbalanya  2 , Edna N Mutua  4 , Daniel Onguru  5 , Isaac K Nyamongo  4 , Benson B A Estambale  6
Affiliations

Effect of climatic variability on malaria trends in Baringo County, Kenya

Edwin K Kipruto et al. Malar J. .

Abstract

Background: Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya.

Methods: Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases.

Results: Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively.

Conclusion: Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.

Keywords: Baringo County; Kenya; Malaria transmission; Rainfall; Seasonal trends; Temperature.

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Figures

Fig. 1
Fig. 1
a Map of the study area showing the location of Baringo County in Kenya, b the sub-county administrative units within Baringo County with the study area shaded out green, and c the ecological zones within the study area and the health facilities from which malaria prevalence data was collected
Fig. 2
Fig. 2
Long-term yearly malaria cases pattern with a lowess smoothline in the highland, mid-altitude, lowland and riverine zones
Fig. 3
Fig. 3
Monthly averages with 95% confidence intervals depicting malaria peak seasons over the study period (2004–2014)
Fig. 4
Fig. 4
Long-term trends in malaria cases against rainfall and maximum temperature in the highland zone (2004–2013)
Fig. 5
Fig. 5
Long-term trend of malaria cases against rainfall and temperatures in the mid-altitude zone (2004–2013)
Fig. 6
Fig. 6
Long-term trend of malaria cases against rainfall and temperatures in the lowland zone (2005–2013)
Fig. 7
Fig. 7
Long-term trend of malaria cases against rainfall and temperatures in the riverine zone (2006–2014)
See this image and copyright information in PMC

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