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Evaluating the theoretical performance of aircraft wastewater monitoring as a tool for SARS-CoV-2 surveillance (preprint)
medrxiv; 2023.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2023.03.07.23286894
ABSTRACT
Background Air travel plays an import role in the cross-border spread of infectious diseases. During the SARS-CoV-2 pandemic many countries introduced strict border testing protocols to monitor the incursion of the virus. However, the high implementation cost and significant inconvenience to passengers has led public health authorities to consider alternative methods of disease surveillance at borders. Aircraft wastewater monitoring has been proposed as one such alternative. In this paper we assess the theoretical limits of aircraft wastewater monitoring and compare its performance to post-arrival border screening approaches. Methods We use an infectious disease model to simulate an unmitigated SARS-CoV-2 epidemic in a seed country. Seeding of the epidemic into the United Kingdom (UK) is simulated through daily flights between the two countries. We use a probabilistic approach to estimate the time of first detection of the disease in the UK in both aircraft wastewater and respiratory swab screening at the border. Results For simulations across a broad range of model parameters, our analysis indicates that the median time between the first incursion of a pathogen and its detection in wastewater would be approximately 17 days (IQR 7 - 28 days), resulting in a median of 25 cumulative cases (IQR 6 - 84 cases) in the UK at the point of detection. Comparisons to respiratory swab screening suggest that aircraft wastewater monitoring is as effective as screening of 20% of passengers at the border, using a test with 95% sensitivity. For testing regimes with sensitivity of 85% or less, the required coverage to outperform wastewater monitoring increases to 30%. These results demonstrate the potential use cases of aircraft wastewater monitoring and its utility in a wider system of public health surveillance.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
Communicable Diseases
/
Severe Acute Respiratory Syndrome
Language:
English
Year:
2023
Document Type:
Preprint
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