Kovacevic, Aleksandra; Eggo, Rosalind M; Baguelin, Marc; Domenech de Cellès, Matthieu; Opatowski, Lulla; (2021) The Impact of Cocirculating Pathogens on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/Coronavirus Disease 2019 Surveillance: How Concurrent Epidemics May Introduce Bias and Decrease the Observed SARS-CoV-2 Percentage Positivity. The Journal of Infectious Diseases, 225 (2). pp. 199-207. ISSN 0022-1899 DOI: https://doi.org/10.1093/infdis/jiab459
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Abstract
BACKGROUND: Circulation of seasonal non-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) respiratory viruses with syndromic overlap during the coronavirus disease 2019 (COVID-19) pandemic may alter the quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures. METHODS: Using a multipathogen susceptible-exposed-infectious-recovered (SEIR) transmission model formalizing cocirculation of SARS-CoV-2 and another respiratory virus, we assessed how an outbreak of secondary virus may affect 2 COVID-19 surveillance indicators: testing demand and positivity. Using simulation, we assessed to what extent the use of multiplex polymerase chain reaction tests on a subsample of symptomatic individuals can help correct the observed SARS-CoV-2 percentage positivity and improve surveillance quality. RESULTS: We find that a non-SARS-CoV-2 epidemic strongly increases SARS-CoV-2 daily testing demand and artificially reduces the observed SARS-CoV-2 percentage positivity for the duration of the outbreak. We estimate that performing 1 multiplex test for every 1000 COVID-19 tests on symptomatic individuals could be sufficient to maintain surveillance of other respiratory viruses in the population and correct the observed SARS-CoV-2 percentage positivity. CONCLUSIONS: This study showed that cocirculating respiratory viruses can distort SARS-CoV-2 surveillance. Correction of the positivity rate can be achieved by using multiplex polymerase chain reaction tests, and a low number of samples is sufficient to avoid bias in SARS-CoV-2 surveillance.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
Research Centre |
Covid-19 Research Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 34514500 |
Elements ID | 166115 |
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Filename: Kovacevic_etal_2021_The-impact-of-cocirculating-pathogens.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
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