Optimizing spatial distribution of wastewater-based epidemiology to advance health equity.

Autor:	Daza-Torres ML; Department of Public Health Sciences, University of California Davis, CA 95616, United States., Montesinos-López JC; Department of Public Health Sciences, University of California Davis, CA 95616, United States., Herrera C; Department of Mathematics, Purdue University, IN 47907, United States., García YE; Department of Public Health Sciences, University of California Davis, CA 95616, United States., Naughton CC; Department of Civil and Environmental Engineering, University of California Merced, Merced, CA, USA., Bischel HN; Department of Civil and Environmental Engineering, University of California Davis, Davis, CA, USA., Nuño M; Department of Public Health Sciences, University of California Davis, CA 95616, United States. Electronic address: mnuno@ucdavis.edu.
Jazyk:	angličtina
Zdroj:	Epidemics [Epidemics] 2024 Dec; Vol. 49, pp. 100804. Date of Electronic Publication: 2024 Nov 10.
DOI:	10.1016/j.epidem.2024.100804
Abstrakt:	In 2022, the US Centers for Disease Control and Prevention commissioned the National Academies of Sciences, Engineering, and Medicine to assess the role of community-level wastewater-based epidemiology (WBE) beyond COVID-19. WBE is recognized as a promising mechanism for promptly identifying infectious diseases, including COVID-19 and other novel pathogens. An important conclusion from this initiative is the critical importance of maintaining equity and expanding access to fully realize the benefits of wastewater surveillance for marginalized communities. To address this need, we propose an optimization framework that strategically allocates wastewater monitoring resources at the wastewater treatment plant (WWTP) level, ensuring more effective and equitable distribution of surveillance efforts to serve underserved populations. The purpose of the framework is to obtain a balanced spatial distribution, inclusive population coverage, and efficient representation of disadvantaged groups in the allocation of resources for WBE. Furthermore, the framework concentrates on areas with high population density and gives priority to vulnerable regions, as well as identifying signals that display significant variations from other monitored sources. The optimization objective is to maximize a weighted combination of these critical factors. This problem is formulated as an integer optimization problem and solved using simulated annealing. We evaluate various scenarios, considering different weighting factors, to optimize the allocation of WWTPs with monitoring systems. This optimization framework provides an opportunity to enhance WBE by providing customized monitoring strategies created to address specific priorities and situations, thus enhancing the decision-making processes in public health responses. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2024. Published by Elsevier B.V.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu