Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review and meta-analysis

Abstract

AbstractWe conducted a systematic review (PROSPERO CRD42023393345) of severe acute respiratory syndrome (SARS) transmission models and parameters characterising its transmission, evolution, natural history, severity, risk factors and seroprevalence. Information was extracted using a custom database and quality assessment tool.We extracted 519 parameters, 243 risk factors, and 112 models from 288 papers. Our analyses show SARS is characterised by high lethality (case fatality ratio 10.9%), transmissibility (R0range 1.1-4.59), and is prone to superspreading (20% top infectors causing up to 91% of infections). Infection risk was highest among healthcare workers and close contacts of infected individuals. Severe disease and death were associated with age and existing comorbidities. SARS’s natural history is poorly characterised, except for the incubation period and mean onset-to-hospitalisation.Our associated R package, epireview, contains this database, which can continue to be updated to maintain a living review of SARS epidemiology and models, thus providing a key resource for informing response to future coronavirus outbreaks.