Malaria in pregnancy remains a major public health challenge in Ethiopia, contributing to maternal morbidity and adverse birth outcomes. Understanding its spatial distribution and service-related determinants is essential for designing equitable and targeted interventions. This study examined the spatial clustering and determinants of malaria incidence among pregnant women in the Amhara region of Ethiopia from 2018 to 2024. A retrospective spatial analysis was conducted using routine malaria surveillance data on confirmed malaria cases among pregnant women from January 2018 to December 2024 in the Amhara region, Ethiopia. Spatial clusters were identified using SaTScan based on a discrete Poisson model. Malaria incidence (cases per population) was used as the outcome variable in regression analysis. A spatial error model (SEM) was applied to assess associations between malaria incidence and environmental and health service factors while accounting for spatial autocorrelation. Model adequacy was evaluated using diagnostic tests, including Moran’s I for residual spatial dependence. During the study period, 5.8 million pregnant women were under surveillance, with 53,478 confirmed malaria cases—an annual incidence of 9.2 per 1,000 populations. Seven significant high-risk spatial clusters were detected. Spatial regression analysis showed that malaria incidence was negatively associated with ANC4 utilization (IRR = 0.92; 95% CI: 0.91–0.94), soil moisture (IRR = 0.85; 95% CI: 0.80–0.90), API (IRR = 0.98; 95% CI: 0.97–0.99), and temperature (IRR = 0.65; 95% CI: 0.58–0.73), but positively associated with ANC1 utilization (IRR = 1.07; 95% CI: 1.06–1.08). Malaria in pregnancy in the Amhara region exhibits marked spatial heterogeneity influenced by environmental conditions and disparities in antenatal care utilization. Strengthening ANC services and implementing geographically targeted, climate-informed interventions are critical to reducing malaria burden among pregnant women.
Bogale et al. (Mon,) studied this question.