Speaker
Description
Background: Malaria in pregnancy (MiP) remains a major contributor to maternal morbidity, adverse birth outcomes, and neonatal mortality in sub-Saharan Africa. Despite ongoing control efforts in Ethiopia, limited evidence exists on the spatiotemporal distribution of MiP and its predictors remains limited.
Objective: This study assessed the spatiotemporal pattern, clustering, and predictors of malaria in pregnancy in the Amhara region from 2018 to 2024.
Methods: We analyzed routine health facility data on laboratory-confirmed MiP cases, linked with antenatal care (ANC) coverage and district-level environmental covariates. Annual incidence trends were calculated, purely temporal and spatiotemporal clusters were detected using SaTScan, and predictors were identified through ARMAX (1,0,4) time-series modeling. Model fit was assessed using AIC, BIC, and residual diagnostics.
Results: A total of 63,354 MiP cases were reported across the study period, with an overall mean incidence of 9.2 (SD = 3.38). A temporal escalation occurred from 2022 to 2024, when incidence increased nearly ten-fold compared to 2018. One significant temporal cluster (2022–2024) was identified (RR = 3.74; p < 0.001), accounting for a 70% excess burden. Spatiotemporal analysis revealed seven clusters (2018–2020) were localized, while later clusters expanded to cover North western and central Amhara, with pregnant women facing up to seven-fold higher risk. MiP incidence will remain elevated through 2025, with seasonal peaks. ARMAX results identified malaria transmission intensity, average temperature, and relative humidity as significant positive predictors, while soil moisture and elevation reduced MiP risk.
Conclusion: MiP incidence in Amhara has escalated in recent years with spatiotemporal clustering. Climatic factors—including temperature, relative humidity, soil moisture and elevation—along with underlying transmission intensity were strongly associated with incidence trends with indicating a sustained risk of recurrent upsurges. These findings underscore the urgent need for climate-informed interventions, early-warning systems, and strengthened ANC-based prevention to curb the growing burden.
