Journal article
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 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, 3.0MB, Terms of use)
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- Publisher copy:
- 10.1038/s41598-021-84672-1
Authors
- Publisher:
- Springer Nature
- Journal:
- Scientific Reports More from this journal
- Volume:
- 11
- Issue:
- 1
- Article number:
- 5825
- Publication date:
- 2021-03-12
- Acceptance date:
- 2021-02-19
- DOI:
- EISSN:
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2045-2322
- Language:
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English
- Keywords:
- Pubs id:
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1163002
- Local pid:
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pubs:1163002
- Deposit date:
-
2021-02-22
Terms of use
- Copyright holder:
- F Pinotti et al.
- Copyright date:
- 2021
- Rights statement:
- © The Author(s) 2021. Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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