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Open AccessArticle

Differences of Rainfall–Malaria Associations in Lowland and Highland in Western Kenya

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Department of Paediatric Infectious Diseases, Institute of Tropical Medicine (NEKKEN), Nagasaki University. Nagasaki 852-8523, Japan
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Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki 852-8523, Japan
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Department of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
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School of Tropical Medicine and Global Health (TMGH), Nagasaki University, Nagasaki 852-8523, Japan
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Division of Electrical Engineering and Computer Science, Graduate School of Engineering, Nagasaki University, Nagasaki 852-8521, Japan
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Remote Sensing Technology Center of Japan (RESTEC), Tokyo 105-0001, Japan
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Japan Aerospace Exploration Agency (JAXA), Tokyo 101-8008, Japan
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Centre for Research and Technology Development Maseno University, Kisumu 40100, Kenya
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Department of Vector Ecology and Environment, Institute of Tropical Medicine, Nagasaki University, Nagasaki 852-8523, Japan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(19), 3693; https://doi.org/10.3390/ijerph16193693
Received: 11 September 2019 / Revised: 24 September 2019 / Accepted: 26 September 2019 / Published: 30 September 2019
(This article belongs to the Section Environmental Health)
Many studies have reported a relationship between climate factors and malaria. However, results were inconsistent across the areas. We examined associations between climate factors and malaria in two geographically different areas: lowland (lakeside area) and highland in Western Kenya. Associations between climate factors (rainfall, land surface temperature (LST), and lake water level (LWL)) and monthly malaria cases from 2000 to 2013 in six hospitals (two in lowland and four in highland) were analyzed using time-series regression analysis with a distributed lag nonlinear model (DLNM) and multivariate meta-analysis. We found positive rainfall–malaria overall associations in lowland with a peak at 120 mm of monthly rainfall with a relative risk (RR) of 7.32 (95% CI: 2.74, 19.56) (reference 0 mm), whereas similar associations were not found in highland. Positive associations were observed at lags of 2 to 4 months at rainfall around 100–200 mm in both lowland and highland. The RRs at 150 mm rainfall were 1.42 (95% CI: 1.18, 1.71) in lowland and 1.20 (95% CI: 1.07, 1.33) in highland (at a lag of 3 months). LST and LWL did not show significant association with malaria. The results suggest that geographical characteristics can influence climate–malaria relationships. View Full-Text
Keywords: time-series analysis; distributed lag nonlinear model (DLNM), lagged effect; heterogeneity time-series analysis; distributed lag nonlinear model (DLNM), lagged effect; heterogeneity
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MDPI and ACS Style

Matsushita, N.; Kim, Y.; Ng, C.F.S.; Moriyama, M.; Igarashi, T.; Yamamoto, K.; Otieno, W.; Minakawa, N.; Hashizume, M. Differences of Rainfall–Malaria Associations in Lowland and Highland in Western Kenya. Int. J. Environ. Res. Public Health 2019, 16, 3693. https://doi.org/10.3390/ijerph16193693

AMA Style

Matsushita N, Kim Y, Ng CFS, Moriyama M, Igarashi T, Yamamoto K, Otieno W, Minakawa N, Hashizume M. Differences of Rainfall–Malaria Associations in Lowland and Highland in Western Kenya. International Journal of Environmental Research and Public Health. 2019; 16(19):3693. https://doi.org/10.3390/ijerph16193693

Chicago/Turabian Style

Matsushita, Naohiko; Kim, Yoonhee; Ng, Chris F.S.; Moriyama, Masao; Igarashi, Tamotsu; Yamamoto, Kazuhide; Otieno, Wellington; Minakawa, Noboru; Hashizume, Masahiro. 2019. "Differences of Rainfall–Malaria Associations in Lowland and Highland in Western Kenya" Int. J. Environ. Res. Public Health 16, no. 19: 3693. https://doi.org/10.3390/ijerph16193693

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