Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations

Abstract For endemic pathogens, seroprevalence mimics overall exposure and is minimally influenced by the time that recent infections take to seroconvert. Simulating spatially-explicit and stochastic outbreaks, we set out to explore how, for emerging pathogens, the mix of exponential growth in infec...

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Autores principales: Francesco Pinotti, Uri Obolski, Paul Wikramaratna, Marta Giovanetti, Robert Paton, Paul Klenerman, Craig Thompson, Sunetra Gupta, José Lourenço
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Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/b006dc9ed2014761b46578b734885a62
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spelling oai:doaj.org-article:b006dc9ed2014761b46578b734885a622021-12-02T11:36:36ZReal-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations10.1038/s41598-021-84672-12045-2322https://doaj.org/article/b006dc9ed2014761b46578b734885a622021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-84672-1https://doaj.org/toc/2045-2322Abstract For endemic pathogens, seroprevalence mimics overall exposure and is minimally influenced by the time that recent infections take to seroconvert. Simulating spatially-explicit and stochastic outbreaks, we set out to explore how, for emerging pathogens, the mix of exponential growth in infection events and a constant rate for seroconversion events could lead to real-time significant differences in the total numbers of exposed versus seropositive. We find that real-time seroprevalence of an emerging pathogen can underestimate exposure depending on measurement time, epidemic doubling time, duration and natural variation in the time to seroconversion among hosts. We formalise mathematically how underestimation increases non-linearly as the host’s time to seroconversion is ever longer than the pathogen’s doubling time, and how more variable time to seroconversion among hosts results in lower underestimation. In practice, assuming that real-time seroprevalence reflects the true exposure to emerging pathogens risks overestimating measures of public health importance (e.g. infection fatality ratio) as well as the epidemic size of future waves. These results contribute to a better understanding and interpretation of real-time serological data collected during the emergence of pathogens in infection-naive host populations.Francesco PinottiUri ObolskiPaul WikramaratnaMarta GiovanettiRobert PatonPaul KlenermanCraig ThompsonSunetra GuptaJosé LourençoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Francesco Pinotti
Uri Obolski
Paul Wikramaratna
Marta Giovanetti
Robert Paton
Paul Klenerman
Craig Thompson
Sunetra Gupta
José Lourenço
Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
description Abstract For endemic pathogens, seroprevalence mimics overall exposure and is minimally influenced by the time that recent infections take to seroconvert. Simulating spatially-explicit and stochastic outbreaks, we set out to explore how, for emerging pathogens, the mix of exponential growth in infection events and a constant rate for seroconversion events could lead to real-time significant differences in the total numbers of exposed versus seropositive. We find that real-time seroprevalence of an emerging pathogen can underestimate exposure depending on measurement time, epidemic doubling time, duration and natural variation in the time to seroconversion among hosts. We formalise mathematically how underestimation increases non-linearly as the host’s time to seroconversion is ever longer than the pathogen’s doubling time, and how more variable time to seroconversion among hosts results in lower underestimation. In practice, assuming that real-time seroprevalence reflects the true exposure to emerging pathogens risks overestimating measures of public health importance (e.g. infection fatality ratio) as well as the epidemic size of future waves. These results contribute to a better understanding and interpretation of real-time serological data collected during the emergence of pathogens in infection-naive host populations.
format article
author Francesco Pinotti
Uri Obolski
Paul Wikramaratna
Marta Giovanetti
Robert Paton
Paul Klenerman
Craig Thompson
Sunetra Gupta
José Lourenço
author_facet Francesco Pinotti
Uri Obolski
Paul Wikramaratna
Marta Giovanetti
Robert Paton
Paul Klenerman
Craig Thompson
Sunetra Gupta
José Lourenço
author_sort Francesco Pinotti
title Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
title_short Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
title_full Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
title_fullStr Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
title_full_unstemmed Real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
title_sort real-time seroprevalence and exposure levels of emerging pathogens in infection-naive host populations
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/b006dc9ed2014761b46578b734885a62
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