BMC public health · 2026
Household malaria risk perception in Ethiopia: multilevel and spatial analysis using the 2022-2023 National Health Equity Survey.
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Leul Yitayh, Ararso Desalegn, Girmay Aderajew Mekonnen, Zeru Arega, Taye Girum, Bahre Weldemariam, Berhanu Kelem, Lemlem Akberet, Getachew Tsegaye, Achamyeleh Hiwot, Shibiru Yirgalem, Alemu Afewerk, Tadele Ashenif, Wasie Abebaw, Molla Gebeyaw, Getachew Fikreselassie, Tadele Wogayehu, Beshah Senait Alemayehu, Tesfaye Hanim, Zelalem Desalew, Sori Seboka Abebe, Ayele Sinafikish, Dagne Tesfaye, Kabeta Teshome, Belay Yihalem Abebe, Terefe Bililign, Fekadu Lelisa, Tiru Gemu, Tollera Getachew
Аннотация
BACKGROUND: Malaria remains a major public health challenge in Ethiopia, affecting more than two‑thirds of the population living in endemic regions. Although local studies have explored community perceptions, nationally representative evidence on household‑level malaria risk perception is limited. OBJECTIVES: To examine socioeconomic and geographic correlates of household malaria risk perception in Ethiopia. METHODS: We analyzed data from 9,157 households in the 2022–2023 Ethiopian National Health Equity Survey (NHES) using multilevel mixed‑effects logistic regression to account for clustering at region, zone, and woreda‑levels. Spatial analysis was conducted using Global Moran's I, and Getis Ord Gi* was used to identify geographic patterns. RESULTS: Overall, 76.4% of households reported feeling at risk of malaria (95% CI: 74.9–77.9). Rural households had 54% higher odds of perceiving risk compared to urban households (AOR = 1.54, 95% CI: 1.22–1.95). Households with higher education were nearly twice as likely to perceive risk (AOR = 1.89, 95% CI: 1.36–2.63), while older household heads were about half as likely (AOR = 0.49, 95% CI: 0.35–0.67). Households without a mobile phone (AOR = 0.59, 95% CI: 0.51–0.69) or bank/microfinance account (AOR = 0.59, 95% CI: 0.50–0.70) were less likely to perceive risk. Approximately 38% of the variability in malaria risk perception occurred between woredas, indicating strong local geographic clustering. Approximately 38% of the variability in perception occurred between woredas, with a Median Odds Ratio of 2.62, indicating strong local clustering. Spatial autocorrelation was significant (Global Moran’s I = 0.42, p < 0.001), with 11% of areas identified as High–High clusters. CONCLUSIONS: Household malaria risk perception in Ethiopia is shaped by socioeconomic disparities and geographic clustering. Integrating perception indicators into malaria surveillance and control strategies will strengthen precision public health and support equitable progress toward malaria elimination.