Assessment of potential microbial risk caused by spread of waterborne infectious diseases in a river area with intensive water use

The necessity to raise effectiveness of activities aimed at preventing spread of waterborne intestinal infections requires improvement of methods and technologies applied in sanitary-microbiological monitoring as a part of the system for sociohygienic monitoring.

The aim of this study was to assess dynamics of potential microbial risks caused by spread of waterborne acute intestinal infections in the Lower Don River area with intensive water use. Microbial communities in water of the Don River in Azov City over 2005–2020 were selected as research objects. The study relied on using results obtained by bacteriological tests of 540 river water samples as well as 1800 water samples taken at outlets from water treatment facilities and in distribution networks of the municipal water supply system. The tests involved identifying sanitary-indicative microorganisms (total levels, fecal and glucose-positive coliform bacteria), potentially pathogenic microorganisms (Klebsiella and Pseudomonas aeruginosa), and pathogenic enterobacteriaceae (Salmonella).

Comprehensive assessment of potential microbial risk associated with waterborne infectious diseases was performed including retrospective analysis of its trends and seasonal characteristics. Accuracy of medium-term extrapolation prediction of microbial risk was comparatively analyzed using regression and neural network models. A complex indicator was calculated for water in the Lower Don River in 2005–2020 for two sanitary-hygienic factors (Sources of Centralized Household and Drinking Water Supply and Recreational Water Use). Its value based on a five-level classifier amounted to 0.612. This made it possible to determine a very high level of potential microbial risk associated with spread of waterborne infections with its typical summer-autumn seasonal rise.

Due to optimization measures, a stable favorable trend was formed per the factor ‘Centralized Household and Drinking Water Supply’. The value of the three-factor complex indicator (0.525) made it possible to establish a high level of potential microbial risk associated with spread of waterborne intestinal infections. A statistically significant (p < 0.01) direct medium correlation was established between incidence of acute intestinal infections and salmonellosis and the level of potential microbial risk. Neural network models were confirmed to provide higher accuracy for medium-term microbial risk predictions.