The Value of Environmental Surveillance for Pandemic Response
Pedro Nascimento de Lima; Sarah Karr; Jing Zhi Lim; Raffaele Vardavas; Derek Roberts; Abigail Kessler; Jalal Awan; Laura J. Faherty; Henry H. Willis
Abstract
Environmental sampling surveillance (ESS) technologies, such as wastewater genomic surveillance and air sensors, have been increasingly adopted during the COVID-19 pandemic to provide valuable information for public health response. However, ESS coverage is not universal, and public health decision-makers need support to choose whether and how to expand and sustain ESS efforts. This paper introduces a model and approach to quantify the value of ESS systems that provide leading epidemiological indicators for pandemic response. Using the COVID-19 pandemic as a base-case scenario, we quantify the value of ESS systems in the first year of a new pandemic and demonstrate how the value of ESS systems depends on biological and societal parameters. Under baseline assumptions, an ESS system that provides a 5-day early warning relative to syndromic surveillance could reduce deaths from 149 (95% prediction interval: 136–169) to 134 (124–144) per 100,000 population during the first year of a new COVID-19-like pandemic, resulting in a net monetary benefit of $1,450 ($609-$2,740) per person. The system's value is higher for more transmissible and deadly pathogens but hinges on the effectiveness of public health interventions. Our findings also suggest that ESS systems would provide net-positive benefits even if they were permanently maintained and pathogens like SARS-Cov-2 emerged once every century or less frequently. Our results can be used to prioritize pathogens for ESS, decide whether and how to expand systems to currently uncovered populations, and determine how to scale surveillance systems' coverage over time.
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@article{nascimentodelimaValueEnvironmentalSurveillance2024,
title = {The {Value} of {Environmental} {Surveillance} for {Pandemic} {Response}},
url = {https://www.rand.org/pubs/working_papers/WRA3263-1.html},
doi = {10.1038/s41598-024-79952-5},
language = {en},
urldate = {2024-06-07},
publisher = {RAND Corporation},
author = {Pedro {Nascimento de Lima} and Karr, Sarah and Lim, Jing Zhi and Vardavas, Raffaele and Roberts, Derek and Kessler, Abigail and Awan, Jalal and Faherty, Laura J. and Willis, Henry H.},
month = jun,
year = {2024},
keywords = {Biosurveillance, Coronavirus Disease 2019 (COVID-19), Epidemic, Infectious Diseases, Modeling and Simulation, Pandemic, Public Health Preparedness, Students}
}