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Background <p>Malaria continues to plague sub-Saharan Africa despite great efforts geared towards its mitigation. In Kenya alone, 70% of the population remains at risk for malaria every year. Malaria is spread by <i>Anopheles</i> mosquitoes carrying the <i>Plasmodium</i> parasite, and displays a complex ecology with various socio-economic, biophysical factors and meteorological predictors, particularly temperature and precipitation, associated with the occurrence of the disease.</p> Methods <p>This study estimated the empirical relationship of temperature and precipitation on the temporal population dynamics of symptomatic malaria cases in Kenyan children living in Ukunda (on Kenyan southern coast), and Kisumu (on Kenyan lake zone) between 2014 and 2022 using daily malaria incidence data collected during a febrile illness surveillance study, merged with daily climatological data collected from ground devices. Generalized additive mixed models (GAMMs) were used to explore the relationship between malaria cases and temperature and precipitation, with Poisson, zero-inflated Poisson and negative binomial distribution&#xa0;and a logarithmic link function. The cross-correlation function assessed the time lags with peak correlations between malaria incidence, precipitation and temperature.</p> Results <p>The data showed 673 positive malaria incident cases amongst children in Kisumu compared to 1209 cases in Ukunda. The results indicate a positive correlation of malaria incidence with rainfall and temperature in Kisumu and a positive correlation between malaria incidence and rainfall and a negative correlation between malaria incidence and temperature in Ukunda. The lags between malaria incidence and rainfall were similar for Kisumu and Ukunda and estimated between 7 and 15&#xa0;weeks.&#xa0;With a time lag of 15&#xa0;weeks in Ukunda, GAMM depicted a steady relationship between rainfall and malaria cases until rainfall reaches 150&#xa0;mm and the relationship between malaria cases and temperature peaks at 26–27&#xa0;°C. In Kisumu using a time lag of 15&#xa0;weeks in the GAMM, a steady relationship between rainfall and malaria cases was observed until almost 120&#xa0;mm of rainfall, peaking at 160&#xa0;mm of rainfall and the relationship between malaria cases and temperature remained steady between 22 and 30&#xa0;°C.</p> Conclusion <p>Assessing the changes in malaria case incidence due to changing seasonality and weather patterns provides policymakers with updated information to strategize malaria control policies.</p>

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Modelling the effects of precipitation and temperature on malaria incidence in coastal and western Kenya

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Amna Tariq,
  • Donal Bisanzio,
  • Francis Mutuku,
  • Bryson Ndenga,
  • Zainab Jembe,
  • Priscilla Maina,
  • Philip Chebii,
  • Charles Ronga,
  • Victoria Okuta,
  • A. Desiree LaBeaud

摘要

Background

Malaria continues to plague sub-Saharan Africa despite great efforts geared towards its mitigation. In Kenya alone, 70% of the population remains at risk for malaria every year. Malaria is spread by Anopheles mosquitoes carrying the Plasmodium parasite, and displays a complex ecology with various socio-economic, biophysical factors and meteorological predictors, particularly temperature and precipitation, associated with the occurrence of the disease.

Methods

This study estimated the empirical relationship of temperature and precipitation on the temporal population dynamics of symptomatic malaria cases in Kenyan children living in Ukunda (on Kenyan southern coast), and Kisumu (on Kenyan lake zone) between 2014 and 2022 using daily malaria incidence data collected during a febrile illness surveillance study, merged with daily climatological data collected from ground devices. Generalized additive mixed models (GAMMs) were used to explore the relationship between malaria cases and temperature and precipitation, with Poisson, zero-inflated Poisson and negative binomial distribution and a logarithmic link function. The cross-correlation function assessed the time lags with peak correlations between malaria incidence, precipitation and temperature.

Results

The data showed 673 positive malaria incident cases amongst children in Kisumu compared to 1209 cases in Ukunda. The results indicate a positive correlation of malaria incidence with rainfall and temperature in Kisumu and a positive correlation between malaria incidence and rainfall and a negative correlation between malaria incidence and temperature in Ukunda. The lags between malaria incidence and rainfall were similar for Kisumu and Ukunda and estimated between 7 and 15 weeks. With a time lag of 15 weeks in Ukunda, GAMM depicted a steady relationship between rainfall and malaria cases until rainfall reaches 150 mm and the relationship between malaria cases and temperature peaks at 26–27 °C. In Kisumu using a time lag of 15 weeks in the GAMM, a steady relationship between rainfall and malaria cases was observed until almost 120 mm of rainfall, peaking at 160 mm of rainfall and the relationship between malaria cases and temperature remained steady between 22 and 30 °C.

Conclusion

Assessing the changes in malaria case incidence due to changing seasonality and weather patterns provides policymakers with updated information to strategize malaria control policies.