Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
SARS-CoV-1 was the first documented coronavirus to cause an acute epidemic in humans and remains a priority pathogen owing to the risk of re-emergence. Robust estimates of key epidemiological parameters are essential to guide outbreak responses and inform mathematical models. Existing systematic reviews have been limited in scope, warranting a comprehensive and up-to-date review. We conducted a systematic review (PROSPERO CRD42023393345) of studies of severe acute respiratory syndrome (SARS) transmission models and parameters characterising the transmission, evolution, natural history, severity, risk factors, and seroprevalence of SARS-CoV-1. Information was extracted using a custom database and quality assessment tool. We extracted data on 519 parameters, 243 risk factors, and 112 models from 289 papers. We found that SARS is characterised by high lethality (case-fatality ratio, 10·9%), transmissibility (R0 range, 1·1–4·59), and superspreading events (approximately 91% of SARS-CoV-1 infections can be attributed to 20% of individuals who were most infectious). Infection risk was the highest among health-care workers and close contacts of infected individuals. Severe disease and death were associated with age and existing comorbidities. The natural history of SARS was poorly characterised, except for the incubation and mean onset-to-hospitalisation delays. The extracted data were compiled into our associated R package, epireview, which can be updated to incorporate novel findings, thus providing a key resource for informing response to future coronavirus outbreaks. By making data accessible through an updatable database, we support rapid, evidence-informed responses to potential re-emergence of SARS-CoV-1 or related coronaviruses.
Date Issued
2025-09-01
Date Acceptance
2025-04-01
Citation
The Lancet Microbe, 2025, 6 (9)
ISSN
2666-5247
Publisher
Elsevier
Journal / Book Title
The Lancet Microbe
Volume
6
Issue
9
Copyright Statement
© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/ by/4.0/).
License URL
Publication Status
Published
Article Number
101144
Date Publish Online
2025-07-23