Fine-scale spatial mapping of anaemia within two sentinel study communities associated with urogenital schistosomiasis in Malawi

While a causal link between urogenital schistosomiasis (Schistosoma haematobium) and anaemia is well established, quantitative associations between infection intensity and haemoglobin levels across endemic communities, at fine spatial scales, remain insufficiently characterized. As part of the broader Hybridisation in Urogenital Schistosomiasis (HUGS) investigation, we studied the micro-epidemiology of anaemia within two study communities in southern Malawi where S. haematobium remains endemic. Urine samples were examined by microscopy to quantify S. haematobium infection intensity, categorised as low (0-9 eggs/10 mL), moderate (10-49 eggs/10 mL), and heavy ([≥]50 eggs/10 mL). Individual haemoglobin concentrations were measured using a HemoCue photometer in 1,149 participants from Samama village (Mangochi District) and 977 participants from Mthawira village (Nsanje District). Linear geostatistical models incorporating individual-level characteristics and spatial covariates were used to estimate anaemia prevalence at fine geographical scales. Moderate anaemia (Hb 80-109 g/L) was most prevalent among children aged 6-12 years (45.30% in Samama and 39.54% in Mthawira), while severe anaemia was more frequent among adults aged [≥]19 years in both villages. Increasing S. haematobium infection intensity was associated with lower haemoglobin levels, with individuals harbouring heavy infections being at greater risk of moderate-to-severe anaemia. Spatial modelling revealed longer-range spatial correlation in Nsanje ({phi} = 66.7 km) than in Mangochi ({phi} = 25.5 km), indicating more spatially persistent risk in Nsanje and more localised heterogeneity in Mangochi. Predicted anaemia prevalence among female children aged 6-12 years with moderate infection intensity ranged from 25-65% in Mangochi and 64-76% in Nsanje. At the micro-epidemiological level, S. haematobium infection intensity was associated with the severity of anaemia, with substantial spatial heterogeneity within and between villages. Identification of high-risk clusters supports targeted interventions, including stepped-up preventive chemotherapy, improved water and sanitation, and iron supplementation.