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Estimating the infection and case fatality ratio for COVID-19

Researchers at the Centre for Mathematical Modelling of Infectious Diseases have tried to estimate the infection and case fatality ratio for COVID-19 using data from the outbreak on the Diamond Princess cruise ship. The study has not yet been peer-reviewed.

Abstract
Aim: To estimate the infection and case fatality ratio of COVID-19, using data from passengers of the Diamond Princess cruise ship while correcting for delays between confirmation-and-death, and age-structure of the population.
Abstract: Adjusting for delay from confirmation-to-death, we estimated case and infection fatality ratios (CFR, IFR) for COVID-19 on the Diamond Princess ship as 2.3% (0.75%–5.3%) and 1.2% (0.38–2.7%). Comparing deaths onboard with expected deaths based on naive CFR estimates using China data, we estimate IFR and CFR in China to be 0.5% (95% CI: 0.2–1.2%) and 1.1% (95% CI: 0.3–2.4%) respectively.

Main text: In real-time, estimates of the case fatality ratio (CFR) and infection fatality ratio (IFR) can be biased upwards by under-reporting of cases and downwards by failure to account for the delay from confirmation-to-death. Collecting detailed epidemiological information from a closed population such as the quarantined Diamond Princess can produce a more comprehensive description of asymptomatic and symptomatic cases and their subsequent outcomes. Using data from the Diamond Princess, and adjusting for delay from confirmation-to-outcome and age-structure of the ship’s occupants, we estimated the IFR and CFR for the outbreak in China. As of 3rd March 2020, there have been 92,809 confirmed cases of coronavirus disease 2019 (COVID-19), with 3,164 deaths [1]. On 1st February 2020, a patient tested positive for COVID-19 in Hong Kong; they disembarked from the Diamond Princess cruise ship on the 25th January [2,3]. This patient had onset of symptoms on the 19th January, one day before boarding the ship [2]. Upon returning to Yokohama, Japan, on February 3rd, the ship was held in quarantine, during which testing was performed in order to measure COVID-19 infections among the 3,711 passengers and crew members onboard. Passengers were initially to be held in quarantine for 14 days. However, those that had intense exposure to the confirmed case-patient, such as sharing a cabin, were held in quarantine beyond the initial 14-day window [3]. By 20th February, there were 634 confirmed cases onboard (17%), with 328 of these asymptomatic (asymptomatic cases were either self-assessed or tested positive before symptom onset) [3]. Overall 3,063 PCR tests were performed among passengers and crew members. Testing started among the elderly passengers, descending by age [3]. For details on the testing procedure, see [2] and [3].
Adjusting for outcome delay in CFR estimates: During an outbreak, the so-called naive CFR (nCFR), i.e. the ratio of reported deaths date to reported cases to date, will underestimate the true CFR because the outcome (recovery or death) is not known for all cases [4]. We can therefore estimate the true denominator for the CFR (i.e. the number of cases with known outcomes) by accounting for the delay from confirmation-to-death [5]. We assumed the delay from confirmation-to-death followed the same distribution as estimated hospitalisation-to-death, based on data from the COVID-19 outbreak in Wuhan, China, between the 17th December 2019 and the 22th January 2020, accounting right-censoring in the data as a result of as-yet-unknown disease outcomes (Figure 1, panels A and B) [6]. As a sensitivity analysis, we also consider raw “non-truncated” distributions, which do not account for censoring; the raw and truncated distributions have a mean of 8.6 days and 13 days respectively.

To correct the CFR, we use the case and death incidence data to estimate the number of cases with known outcomes where ctct is the daily case incidence at time, tt, ftft is the proportion of cases with delay between onset or hospitalisation and death. utut represents the underestimation of the known outcomes [5] and is used to scale the value of the cumulative number of cases in the denominator in the calculation of the cCFR. Finally, we used the measured proportions of asymptomatic to symptomatic cases on the Diamond Princess to scale the corrected CFR (cCFR) to estimate the infection fatality ratio (IFR).

Authors
Timothy W Russell, Joel Hellewell, Christopher I Jarvis, Kevin van Zandvoort, Sam Abbott, Ruwan Ratnayake, Stefan Flasche, Rosalind Eggo, W John Edmunds, Adam J Kucharski

[link url="https://cmmid.github.io/topics/covid19/severity/diamond_cruise_cfr_estimates.html"]CMMID research[/link]

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