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What will be the ratio of fatalities to total estimated infections for COVID-19 by the end of 2020?
Cross-posted on Metaculus.
Novel coronavirus (COVID-19), as denoted by the World Health Organization, also known as Wuhan coronavirus or Wuhan seafood market pneumonia virus, is a positive-sense, single-stranded RNA coronavirus first reported in 2019 and genomically sequenced after nucleic acid testing on a positive patient sample in a patient with pneumonia during the 2019-2020 Wuhan pneumonia outbreak. The virus is at least 70% similar in genetic sequence to SARS-CoV, the virus that causes severe acute respiratory syndrome.
There are already questions about the number of deaths that will be attributed to the disease before 2021, as well as the number of cases and estimated infections that will develop. However, there are some reasons why specific questions about ratios of these values will be useful:
While dividing the median for deaths by the median for estimated infections may give a reasonable point estimate, it doesn't give all the info we want. With this question, we will be able to see the distribution of infection-mortality rates. This cannot be reliably inferred using the distributions for number of cases and number of deaths, because the variables are correlated.
The time-series graph provided by the question will show how predictions about infection-fatality rates change over time.
Resolution: The resolution for this question will be determined by directly dividing the number of fatalities by the total number of cases, using the resolution values given by the following two Metaculus questions:
There may be more sophisticated ways of determining infection-fatality rate, but we would like to stay consistent with the other Metaculus questions.
Edited 2020-03-06 to clarify that this is the infection-fatality ratio rather than the case-fatality ratio.
Edited 2020-04-29 to clarify that this question resolves as the estimated number of deaths before 2021 divided by the estimated number of infections before 2021.
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