key: cord-0430341-a3efmczu authors: Elbanna, A. title: Estimation of the Ascertainment Bias in Covid Case Detection During the Omicron Wave date: 2022-04-23 journal: nan DOI: 10.1101/2022.04.22.22274198 sha: d394e13bf65bcb49c08fe3423796b27f5b06217e doc_id: 430341 cord_uid: a3efmczu Covid cases in the general population have been historically underreported due to a variety of reasons including limited access to PCR testing at the start of the pandemic, lack of nation-wide surveillance testing, and discouraged testing unless symptomatic. Concerns about underreporting have increased during the Omicron surge due to the expanded use of at-home rapid tests which are not required to be officially reported. For the state of Illinois, we have found that reported cases constituted only 50%-70% of the actual cases during the pre-Omicron waves (August 2020-December 2021). During the first Omicron (BA1) wave, this fraction dropped to 20-25% (i.e., only 1 in 4 to 1 in 5 cases are reported). During the ongoing second Omicron (BA2) surge, this fraction has further decreased to 10-15% (i.e., only 1 in 7 to 1 in 10 cases are reported). These estimates have important implications on understanding the extent of the Omicron surge at the state and national levels. Note that both the numerator and denominator in this ratio are known sufficiently well. Using the Johns Hopkins database (through divoc-91 website) 1 the CFR in August/September 2020 was estimated to be on average equal to 1%. The first estimate for infection fatality ratio (IFR) came from Wuhan 2 in January 2020 to be on average 1%. As more data was collected from around the world, it became clear that the infection fatality ratio has a steep age dependence 3 . By late summer 2020, the estimate . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted April 23, 2022. ; https://doi.org/10.1101/2022.04.22.22274198 doi: medRxiv preprint for the population-wide averaged infection fatality ratio (IFR) most probably ranged between 0.5% and 0.7% 3 . With these two numbers we compute the ascertainment ratio in case detection as follows: Detection ratio = 8123+)/(# 8$4(4 90-7$, 8$4(4 x 100 = :;< 8;< x 100 = 50% -70% Our next step is to relate cases on campus, where surveillance testing is available, to cases in the state. Data on cases for faculty/staff at UIUC is accessible through the campus dashboard 4 . Cases at the state level is recorded by IDPH 5 . We have found a strong correlation between cases in the faculty/Staff cohort and cases in the state. Figure 1 illustrates this remarkable correlation. Interestingly, the case rate per 100k in faculty/staff agrees reasonably well with the confirmed case rate per 100k for the general population in the state for all the pre-Omicron waves. We assert that the detected case rate in the faculty/staff cohort is very close to their actual case rate. This is because during 2020-2021 academic year, UIUC was testing everyone who needed campus access. In Fall 2021, while mandatory testing was no longer required for vaccinated . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 23, 2022. ; https://doi.org/10.1101/2022.04.22.22274198 doi: medRxiv preprint faculty/staff, the convenient covidShield test was still widely accessible and most faculty/staff took advantage of this. Therefore, while it is possible that the detected case rate in faculty/staff during the Delta and Omicron waves is different from the actual case rate, we may still assume that this difference is small and that the detected case rate may be taken as a proxy for prevalence in this subpopulation. This assertion gives us an opportunity to determine the ratio between faculty/staff case rate and the case rate at the state level. Specifically, by using the detection ratio above (for Fall 2020) and the observation that the actual case rate in faculty/staff is equal to the confirmed case rate at the state level during that period, we arrive at the following conclusion: Actual case rate in the state = This is the key relation that we will be using in estimating the underreporting at the state level by tracking case rate in faculty/staff. This relation should approximately hold at any time during the pandemic. This is because the exposure patterns and the social dynamics of faculty/staff are similar to those of the general population. What may change, however, is the fraction f of actual cases at the state level that gets officially reported. We are now at a position to estimate this fraction f for the different epidemic waves. That is, approximately, only 1 in 2 cases (or perhaps only 2 in 3 cases) was reported at the state level before the Omicron surge. Confirmed case rate in the state = 0.38 x Actual case rate in faculty/staff Actual case rate in the state = (1.4 to 2) x Actual case rate in faculty/staff = (3.7 to 5. 3) x Confirmed case rate in the state . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. That is, approximately, only 1 in 7 to 1 in 10 cases is reported at the state level during the ongoing Omicron BA2 surge. This reduction in reporting is consistent with the expanded use of rapid tests, the limited access to PCR testing due to closure of some free testing sites, as well as the role of vaccination or prior infection in reducing the symptoms to a milder degree thus discouraging seeking PCR testing. 1-During pre-Omicron waves (August 2020-December 2021): 1 in 2 cases got to be reported officially at the state level 2-During Omicron BA1 wave (December 2021-January 2022): Only 1 in 4 or 1 in 5 cases got to be reported officially at the state level. 3-During Omicron BA2 wave (April 2022): Only 1 in 7 or 1 in 10 cases are reported officially at the state level. This is also consistent with the CDC surveillance data 6 that suggests the use of rapid at home tests were tripled between late 2021 and March 2022 DIVOC-91: Flipping the script on The epidemiological character-istics of an outbreak of 2019 novel coronavirus diseases (COVID-19)-China, 2020 A systematic review and meta-analysis of published research data on COVID-19 infection fatality rates UIUC COVID-19 dashboard archived database IDPH COVID-19 data on daily cases, tests and deaths Use of At-Home COVID-19 Tests-United States A.E acknowledges the UIUC Shield testing program which conducted more than 2.7 million tests on the Urbana-Champaign campus since July 2020 and continues to provide high-quality surveillance data on COVID-19 transmission dynamics.