Spatiotemporal trends and predictors of malaria in pregnancy in the Amhara region, Ethiopia: evidence from ARMAX analysis

Malaria in pregnancy (MiP) remains a major public health challenge in Ethiopia, contributing to maternal morbidity, adverse birth outcomes, and neonatal mortality. Despite intensified control efforts, evidence on temporal dynamics and key determinants remains limited. This study examined the spatiotemporal patterns, clustering, and environmental and health service-related predictors of malaria in pregnancy (MiP) in the Amhara region of Ethiopia from 2018 to 2024. A retrospective analysis was conducted using routine health facility data on MiP, linked with antenatal care coverage and district-level environmental variables. Annual incidence rates were computed. Temporal and spatiotemporal clusters were identified using SaTScan with a discrete Poisson model. Predictors, including climatic factors and malaria transmission intensity, were examined using an autoregressive moving average model with exogenous variables (ARMAX [1,0,4]). Model performance was evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and residual diagnostics. A total of 53,478 MiP cases were reported during the study period, with a mean incidence of 9.2 per 1,000 population (SD = 3.38). A significant temporal cluster was identified between 2022 and 2024 (RR = 3.74; p < 0.001). Seven spatiotemporal clusters were detected; early clusters (2018–2020) were geographically localized, whereas later clusters (2022–2024) showed marked spatial expansion. Projections indicate that MiP incidence will remain elevated through 2026. Significant predictors included malaria transmission intensity (β = 0.001; p < 0.001), temperature (β = 0.031; p = 0.019), and relative humidity (β = 0.029; p < 0.001). In contrast, soil moisture (β = −0.044; p < 0.001) and elevation (β = −0.001; p < 0.001) were negatively associated with MiP incidence. MiP in the Amhara region has increased substantially, with clear spatiotemporal clustering and persistence. The observed escalation coinciding with conflict periods underscores the need for conflict-sensitive, climate-informed, and geographically targeted malaria control strategies.