Abstract
Although Serbia is recognized as an haemorrhagic fever with renal syndrome endemic country, long-term epidemiological data from subnational regions remain limited. This study aimed to describe temporal, spatial, seasonal and demographic patterns of this disease in the Autonomous Province of Vojvodina, northern Serbia, over a 32-year period (1992-2023), and to assess potential associations between disease occurrence and selected climatic parameters. We conducted a retrospective descriptive study based on routine surveillance data. Annual crude and age- and gender-specific incidence rates were calculated. Geographic clustering was assessed at the district and municipality levels. Correlations between disease incidence and temperature, precipitation, relative humidity and number of rainy days were evaluated using Spearman’s rank correlation coefficient. Over the study period, a total of 82 cases were reported (average annual incidence: 0.13/100,000; 95%CI: 0.10-0.16), characterized by sporadic occurrence and substantial interannual variability, with two deaths recorded. The highest annual incidences were recorded in 2012 (0.41/100,000) and 2014 (0.52/100,000). Incidence exhibited marked spatial heterogeneity, with highest long-term rates in South Bačka and Srem districts, and municipal hotspots (Beočin, Irig, Sremski Karlovci). Males aged 20–39 years experienced the highest incidence rate, whereas cases were rare among children. A pronounced seasonal peak was observed in June, accounting for 24.4% of all reported cases. No statistically significant associations were found between annual incidence and climatic parameters. Monthly analysis revealed a positive correlation between number of cases and temperature (ρ=0.606, p=0.037) and a negative correlation with relative humidity (ρ=–0.621, p=0.031). Our findings indicate that haemorrhagic fever with renal syndrome remains a low-incidence but endemic zoonosis in AP Vojvodina, characterised by distinct geographic hotspots, well-defined demographic patterns, and stable early-summer seasonality. Enhanced integrated surveillance, improved diagnostic coverage and integration of ecological and environmental data are needed to better understand localized risk and support timely public health interventions.
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