The Influence of COVID-19 Vaccination on Daily Cases, Hospitalization, and Death Rate in Tennessee, United States: Case Study

  1. Ali Roghani

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Abstract

The COVID-19 outbreak highlights our vulnerability to novel infections, and vaccination remains a foreseeable method to return to normal life. However, infrastructure is inadequate for the immediate vaccination of the whole population. Therefore, policies have adopted a strategy to vaccinate older adults and vulnerable populations while delaying vaccination for others.

Objective

This study aimed to understand how age-specific vaccination strategies reduce daily cases, hospitalizations, and death rates using official statistics for Tennessee, United States.

Methods

This study used publicly available data on COVID-19, including vaccination rates, positive cases, hospitalizations, and deaths from the Tennessee Department of Health. Data from the first date of vaccination (December 17, 2020) to March 3, 2021, were retrieved. The rates were adjusted by 2019 data from the US Census Bureau, and age groups were stratified into 10-year intervals starting with 21 years of age.

Results

The findings showed that vaccination strategy can reduce the numbers of patients with COVID-19 in all age groups, with lower hospitalization and death rates in older populations. Older adults had a 95% lower death rate from December to March; no change in the death rate of other age groups was observed. The hospitalization rate was reduced by 80% for people aged ≥80 years, while people who were 50 to 70 years old had nearly the same hospitalization rate as prior to vaccination.

Conclusions

This research indicates that targeting older age groups for vaccination is the optimal way to avoid higher transmissions and reduce hospitalization and death rates.

Article activity feed

  1. Version published to 10.2196/29324
  2. Version published to 10.2196/preprints.29324
  3. ScreenIT

    SciScore for 10.1101/2021.03.16.21253767: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    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 findings should be considered in the context of several data limitations. I did not derive individual-level data to estimate hospitalization risks, mortality rate, and COVID-19 transmission. Moreover, several studies (6, 7) indicate racial and ethnic disparity by health systems increases the risk of getting sick, hospitalized, and dying from COVID-19. Future studies should examine vaccination in different races by age group to estimate who should get the vaccine first. Additionally, the data does not include nonpharmaceutical public health control measures, which would be an essential indicator to control daily cases (8). Conclusion: The vaccination was started at the beginning of a “3rd wave“in Tennessee, and by December, and January SARS-CoV2 positive cases and hospitalizations increased considerably. This work has concentrated on the Tennessee’s dynamics COVID-19. It concludes that the vaccine should be optimally targeted at the elderly in the first step, indicating that vaccination reduces daily cases for the whole population, while reduces hospitalization and death rate in the older population. This study, consistent with the previous studies (8), shows mRNA Covid-19 vaccines have a protective effect for blocking transmission even after a single dose. This study also indicates that prioritizing the vaccination of the elderly is a practical approach for reducing the number of deaths and hospitalization.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2021.03.16.21253767v1 on medRxiv