Estimating Prevalence and time Course of Sars-Cov-2 Based on new Hospital Admissions and PCR Tests: Relevance to Vaccination Program Tactical Planning

  1. Jose E. Gonzalez

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Abstract

Data posted in the COVID 19 tracking website for RT-PCR (PCR) results and hospital admissions are used to estimate the time course of the SARS-CoV-2 pandemic in the United States (1) and individual states. Hospital admissions mitigate positive sampling bias in PCR tests since these were limited in numbers initially. Additionally, their intent was as a diagnostic rather than a surveying tool.

By September 17, the United States’ cumulative recovered population is estimated at 45% or 149 million. The remaining susceptible population is 55%, or 50%, excepting the currently infected 5% population. The estimated mortality rate of the cumulative of the total affected population is 0.13% death.

States have followed diverse epidemic time courses. New Jersey and New York show SARS-CoV-2 prevalence of 95% and 82%, respectively. Likewise, each state exhibits relatively low current positive PCR results at 1.2 % and 0.8%. Also, these states show about twice the mortality rate of the nation. By comparison, Florida, California, and Texas showed recovered populations percent around 50%, and higher current PCR positive test results ranging from 5% to 9%.

This novel approach provides an improved source of information on the pandemic’s full-time course in terms of precision and accuracy in contrast to serological testing, which only views a narrow time slice of its history due to the transient nature of the antibody response and its graduated expression dependency on the severity of the disease. The deficiency of serological testing to estimate the recovered population is made even more acute due to the large proportion of asymptomatic and sub-clinical cases in the COVID-19 pandemic (2,3). T-cell testing, reputedly capable of long-term detection of previously infected individuals, will provide a complete view of the recovered population when it becomes available for large scale use.

This New Hospital Admission based method informs a more effective and efficient deployment of a vaccination program since it provides not only a reliable estimate of the susceptible population by state, but it can also provide visibility down to the county level based on COVID-19 hospitalization record independent of PCR testing.

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  1. Version published to 10.1101/2020.08.15.20175653v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.08.15.20175653: (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

    Antibodies
    SentencesResources
    Comparison of SARS-CoV-2 Antibodies longitudinal time course versus cumulation of recovered COVID-19 cases: SARS-CoV-2 antibodies fail to cumulate effectively in the recovered population falling below the detectability level over time (2,3).
    SARS-CoV-2
    suggested: None
    Similar behavior is apparent in South Carolina and Texas, where antibody cumulation fails to account for the daily infection rate (see Figure 5c and 5d, respectively).
    Texas,
    suggested: None

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

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  3. Version published to 10.1101/2020.08.15.20175653v1 on medRxiv