The variant‐specific burden of SARS‐CoV‐2 in Michigan: March 2020 through November 2021
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Abstract
Accurate estimates of the total burden of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) are needed to inform policy, planning, and response. We sought to quantify SARS‐CoV‐2 cases, hospitalizations, and deaths by age in Michigan. Coronavirus disease 2019 cases reported to the Michigan Disease Surveillance System were multiplied by age and time‐specific adjustment factors to correct for under‐detection. Adjustment factors were estimated in a model fit to incidence data and seroprevalence estimates. Age‐specific incidence of SARS‐CoV‐2 hospitalization, death, vaccination, and variant proportions were estimated from publicly available data. We estimated substantial under‐detection of infection that varied by age and time. Accounting for under‐detection, we estimate the cumulative incidence of infection in Michigan reached 75% by mid‐November 2021, and over 87% of Michigan residents were estimated to have had ≥1 vaccination dose and/or previous infection. Comparing pandemic waves, the relative burden among children increased over time. In general, the proportion of cases who were hospitalized or who died decreased over time. Our results highlight the ongoing risk of periods of high SARS‐CoV‐2 incidence despite widespread prior infection and vaccination. This underscores the need for long‐term planning for surveillance, vaccination, and other mitigation measures amidst continued response to the acute pandemic.
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SciScore for 10.1101/2022.03.16.22272497: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The results should be interpreted in the context of multiple other limitations. 1) We were unable to account for reinfection, and prior infection was assumed to be independent of the likelihood of being vaccinated. 2) We relied on Michigan-specific data from the Nationwide Commercial Lab Seroprevalence study to calculate case adjustment …
SciScore for 10.1101/2022.03.16.22272497: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The results should be interpreted in the context of multiple other limitations. 1) We were unable to account for reinfection, and prior infection was assumed to be independent of the likelihood of being vaccinated. 2) We relied on Michigan-specific data from the Nationwide Commercial Lab Seroprevalence study to calculate case adjustment factors to correct for under-detection. That seroprevalence study has its own limitations4,8, and the representativeness of its sample to the Michigan population as a whole is unclear. 3) The calculated case adjustment factors were sensitive to assumptions about the rate of antibody waning. We found that the average time from seroconversion to seroreversion could not be estimated simultaneously with the adjustment factors due to identifiability issues, so we specified the former parameter from the existing literature. It is possible that rates of antibody waning could differ by age which is something we were unable to account for. 4) The case adjustment factors were our main source of uncertainty in this analysis. There are other sources of uncertainty that we were unable to propagate or account for. 5) SARS-CoV-2 sequence data reported to GISAID may not reflect true community variant proportions, particularly shortly after emergence when sampling may be biased toward outbreaks. Our results highlight the ongoing risk of periods of high SARS-CoV-2 incidence despite widespread prior infection and vaccination in the population. This underscores t...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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