Computational analysis of SARS-CoV-2/COVID-19 surveillance by wastewater-based epidemiology locally and globally: Feasibility, economy, opportunities and challenges
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Abstract
With the economic and practical limits of medical screening for SARS-CoV-2/COVID-19 coming sharply into focus
worldwide, scientists are turning now to wastewater-based epidemiology (WBE) as a potential tool for assessing
and managing the pandemic. We employed computational analysis and modeling to examine the feasibility,
economy, opportunities and challenges of enumerating active coronavirus infections locally and globally using
WBE. Depending on local conditions, detection in community wastewater of one symptomatic/asymptomatic infected case per 100 to 2,000,000 non-infected people is theoretically feasible, with some practical successes now
being reported from around the world. Computer simulations for past, present and emerging epidemic hotspots
(e.g., Wuhan, Milan, Madrid, New York City, Teheran, Seattle, Detroit and New Orleans) identified temperature,
average in-sewer travel time and per-capita water use as key variables. WBE surveillance of populations is shown
to be orders of magnitude cheaper and faster than clinical screening, yet cannot fully replace it. Cost savings
worldwide for one-time national surveillance campaigns are estimated to be in the million to billion US dollar
range (US$), depending on a nation's population size and number of testing rounds conducted. For resource
poor regions and nations, WBE may represent the only viable means of effective surveillance. Important limitations of WBE rest with its inability to identify individuals and to pinpoint their specific locations. Not compensating for temperature effects renders WBE data vulnerable to severe under-/over-estimation of infected cases.
Effective surveillance may be envisioned as a two-step process in which WBE serves to identify and enumerate infected cases, where after clinical testing then serves to identify infected individuals in WBE-revealed hotspots.
Data provided here demonstrate this approach to save money, be broadly applicable worldwide, and potentially
aid in precision management of the pandemic, thereby helping to accelerate the global economic recovery that
billions of people rely upon for their livelihoods.
Palabras clave
Wastewater-based epidemiology; Modeling; Global health; CoronavirusLink to resource
https://doi.org/10.1016/j.scitotenv.2020.138875Collections
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