Climate Change and Malaria: Impact, Vulnerability, and Adaptation Pathways in Homa Bay County, Kenya
Abstract:
This
paper presents the relationship between climate
change (temperature, rainfall, humidity) and incidence of malaria in Homabay
County, Kenya. Climate change impacts, household exposure, sensitivity, and
adaptive capacity were analysed to inform policy. The study combined ecological
time-series analysis, household surveys, and key informant interviews. It
analysed climate and morbidity data from 2010-2024, supplemented with primary
data from 401 households and insights from 19 stakeholders. Standardized
questionnaires and in-depth interviews guided data collection. The ARDL models
assessed short and long-run climate effects on malaria, logistic regression
examined determinants of household vulnerability, and thematic analysis
generated qualitative insights. The findings showed malaria cases averaged
23,082 per month (SD = 13,402), mean temperature 23.3°C (SD = 1), rainfall
117.7 mm (SD = 67), and humidity 74%. The long-run model showed a significant
baseline incidence and a highly significant first-month lag (IRR ≈ 1.92).
Similarly, short-run results confirmed strong persistence, with first
differenced lag significant (IRR ≈ 1.82). The household survey showed an
overall moderate vulnerability to malaria (median 0.35), driven by high
exposure, moderate sensitivity and adaptive capacity. Sensitivity linked to
older household-head, low education, poor housing, and climate-dependent
livelihoods significantly increased odds of malaria by 52%. Exposure had a
positive effect on malaria incidence (OR ≈ 1.29) while stronger adaptive
capacity lowered malaria risk. The study concluded that climate change has a
significant impact on malaria in Homa Bay County. It highlights the need for
real-time climate-health early warning systems by integrating meteorological
data into IDSR for timely outbreak detection.
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