Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposal

Early warning Emerging infectious diseases Genetic Algorithm Wastewater-Based Epidemiological Monitoring Wastewater-based epidemiology COVID-19 Wastewater 01 natural sciences 6. Clean water 3. Good health Good Health and Well Being Emerging Infectious Diseases Genetic algorithm Early Warning Humans Bisection Method Bisection method Wastewater-based Epidemiology Environmental Sciences Research Article 0105 earth and related environmental sciences
DOI: 10.1016/j.jenvman.2022.115806 Publication Date: 2022-08-01T22:15:23Z
ABSTRACT
Wastewater-based epidemiology (WBE) is drawing increasing attention as a promising tool for an early warning of emerging infectious diseases such as COVID-19. This study demonstrated the utility of a spatial bisection method (SBM) and a global optimization algorithm (i.e., genetic algorithm, GA), to support better designing and operating a WBE program for disease surveillance and source identification. The performances of SBM and GA were compared in determining the optimal locations of sewer monitoring manholes to minimize the difference among the effective spatial monitoring scales of the selected manholes. While GA was more flexible in determining the spatial resolution of the monitoring areas, SBM allows stepwise selection of optimal sampling manholes with equiareal subcatchments and lowers computational cost. Upon detecting disease outbreaks at a regular sewer monitoring site, additional manholes within the catchment can be selected and monitored to identify source areas with a required spatial resolution. SBM offered an efficient method for rapidly searching for the optimal locations of additional sampling manholes to identify the source areas. This study provides strategic and technical elements of WBE including sampling site selection with required spatial resolution and a source identification method.
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