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A Quantitative Assessment of Epidemiological Parameters Required to Investigate COVID-19 Burden

Abstract

Solid estimates describing the clinical course of SARS-CoV-2 infections are still lacking due to under-ascertainment of asymptomatic and mild-disease cases. In this work, we quantify age-specific probabilities of transitions between stages defining the natural history of SARS-CoV-2 infection from 1965 SARS-CoV-2 positive individuals identified in Italy between March and April 2020 among contacts of confirmed cases. Infected contacts of cases were confirmed via RT-PCR tests as part of contact tracing activities or retrospectively via IgG serological tests and followed-up for symptoms and clinical outcomes. In addition, we provide estimates of time intervals between key events defining the clinical progression of cases as obtained from a larger sample, consisting of 95,371 infections ascertained between February and July 2020. We found that being older than 60 years of age was associated with a 39.9% (95%CI: 36.2-43.6%) likelihood of developing respiratory symptoms or fever ≥ 37.5 °C after SARS-CoV-2 infection; the 22.3% (95%CI: 19.3-25.6%) of the infections in this age group required hospital care and the 1% (95%CI: 0.4-2.1%) were admitted to an intensive care unit (ICU). The corresponding proportions in individuals younger than 60 years were estimated at 27.9% (95%CI: 25.4-30.4%), 8.8% (95%CI: 7.3-10.5%) and 0.4% (95%CI: 0.1-0.9%), respectively. The infection fatality ratio (IFR) ranged from 0.2% (95%CI: 0.0-0.6%) in individuals younger than 60 years to 12.3% (95%CI: 6.9-19.7%) for those aged 80 years or more; the case fatality ratio (CFR) in these two age classes was 0.6% (95%CI: 0.1-2%) and 19.2% (95%CI: 10.9-30.1%), respectively. The median length of stay in hospital was 10 (IQR: 3-21) days; the length of stay in ICU was 11 (IQR: 6-19) days. The obtained estimates provide insights into the epidemiology of COVID-19 and could be instrumental to refine mathematical modeling work supporting public health decisions.

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References
1.
Yang J, Chen X, Deng X, Chen Z, Gong H, Yan H . Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China. Nat Commun. 2020; 11(1):5411. PMC: 7591855. DOI: 10.1038/s41467-020-19238-2. View

2.
McCombs A, Kadelka C . A model-based evaluation of the efficacy of COVID-19 social distancing, testing and hospital triage policies. PLoS Comput Biol. 2020; 16(10):e1008388. PMC: 7591016. DOI: 10.1371/journal.pcbi.1008388. View

3.
Zhang J, Litvinova M, Liang Y, Wang Y, Wang W, Zhao S . Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science. 2020; 368(6498):1481-1486. PMC: 7199529. DOI: 10.1126/science.abb8001. View

4.
Byambasuren O, Cardona M, Bell K, Clark J, McLaws M, Glasziou P . Estimating the extent of asymptomatic COVID-19 and its potential for community transmission: Systematic review and meta-analysis. J Assoc Med Microbiol Infect Dis Can. 2022; 5(4):223-234. PMC: 9602871. DOI: 10.3138/jammi-2020-0030. View

5.
Kucharski A, Russell T, Diamond C, Liu Y, Edmunds J, Funk S . Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect Dis. 2020; 20(5):553-558. PMC: 7158569. DOI: 10.1016/S1473-3099(20)30144-4. View