A Narrative Review of High Throughput Wastewater Sample Processing for Infectious Disease Surveillance: Challenges, Progress, and Future Opportunities
- PMID: 39595699
- PMCID: PMC11593539
- DOI: 10.3390/ijerph21111432
A Narrative Review of High Throughput Wastewater Sample Processing for Infectious Disease Surveillance: Challenges, Progress, and Future Opportunities
Abstract
During the recent COVID-19 pandemic, wastewater-based epidemiological (WBE) surveillance played a crucial role in evaluating infection rates, analyzing variants, and identifying hot spots in a community. This expanded the possibilities for using wastewater to monitor the prevalence of infectious diseases. The full potential of WBE remains hindered by several factors, such as a lack of information on the survival of pathogens in sewage, heterogenicity of wastewater matrices, inconsistent sampling practices, lack of standard test methods, and variable sensitivity of analytical techniques. In this study, we review the aforementioned challenges, cost implications, process automation, and prospects of WBE for full-fledged wastewater-based community health screening. A comprehensive literature survey was conducted using relevant keywords, and peer reviewed articles pertinent to our research focus were selected for this review with the aim of serving as a reference for research related to wastewater monitoring for early epidemic detection.
Keywords: artificial intelligence; automation; disease surveillance; operational challenges; pandemic preparedness; wastewater-based epidemiology (WBE).
Conflict of interest statement
Authors Bhuvanesh Kumar Shanmugam, Maryam AlQaydi, Degan Abdisalam, Monika Shukla, Helio Santos, Ranya Samour, Lawrence Petalidis, Grzegorz Brudecki, Wael Elamin were employed by the company ‘M42 healthcare’, UAE. Charles Matthew Oliver was employed by Mubadala Health, UAE, and Samara Bin Salem was employed by Abu Dhabi Quality and Conformity Council (ADQCC), UAE.
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