Chapter 1.2: Metrics¶
What are the different methods of estimating infections?
Death Rate:¶
Empirical data suggests that the infection fatality rate of COVID 19 is somewhere between 0.1% and 1% (1). Infection fatality rate, or IFR, is the percentage of those infected with the virus that will die. In a world with perfect and complete data, the IFR would be calculated by dividing total deaths by total infections. As neither deaths or infections due to COVID 19 are exact, the IFR is a best estimate. However, it provides a relatively reliable method to determine the true number of infections. By dividing the number of reported deaths by the IFR, an estimate for infections can be derived. This estimate is not free from sources of uncertainty, however. Rather than divide the number of deaths each day by the IFR, the deaths were counted 18 days out. This accounts for the delay between the time of infection and death, which is only an average estimate (2). Deaths don’t always occur in exactly 18 days, so this method is not exact.
Detection Rate:¶
The detection rate is an estimated percentage of the true number of infections that are actually reported. The calculation is quite simple: divide the number of reported cases by the estimated total number of infections. Given the information available to me, I used the death-count/death-rate method to calculate infections.
Antibody tests:¶
Besides viral tests, which determine if a person is currently infected with COVID, cases can be estimated using antibody tests. Antibody tests are used to determine if the virus has ever been present in a patient by testing for the antibodies produced as a result of COVID 19 infection. This suggests that antibody testing data could be helpful in determining true infection rates. However, the tests have practical implications that make the data difficult to use. First, the CDC claims it can take up to 3 weeks after infection for the immune response to build up in a patient’s body. This means that many individuals who have been infected with COVID will still test negative for antibodies. Furthermore, according to Dr. Neeraj Sood, vice dean for research at the USC Price School of Public Policy and infectious disease expert, “The amount of antibodies, especially of people who were infected early on, might be waning overtime, and our test might not be able to detect these lower levels of antibodies”. This creates a relatively small window in the course of an individual’s infection in which antibody testing would be effective and accurate. As a result, antibody tests have a significant margin of error that detracts from their accuracy and scientific weight.