Modelling suggests fall in acute admissions with mass COVID-19 vaccinations

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The coronavirus disease 2019 (COVID-19) pandemic led to a high influx of patients suffering from acutely symptomatic infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The sheer volume of such cases inevitably affected routine care of other patients in hospitals, as well as those in COVID-19 wards.

A new study published on the preprint server medRxiv* explores the utility of modeling the impact of mass vaccination on the number of hospital beds occupied by acute COVID-19 cases. This was found to allow for more effective planning and decision-making with respect to healthcare systems.

Study: Modelling The Effect Of COVID-19 Mass Vaccination on Acute Admissions in A Major English Healthcare System. Image Credit: VideoFlow / Shutterstock.com

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Background

The pandemic led to the imposition of multiple restrictions on the ordinary functioning of society, including business closures, the shutting down of in-person schooling, limits on social gatherings, and travel bans. In order to accelerate the return of these areas to some semblance of normalcy, efforts were made towards rapid vaccine development and deployment.

In terms of the load on healthcare systems, the expectation was that mass vaccination would reduce the risk of infection and transmission of SARS-CoV-2, thus allowing non-COVID-19 patients to receive pre-pandemic levels of care for elective therapies.

In order to plan how to use hospital capacity and allot beds, it is necessary to be able to forecast case trends one may expect once vaccines are rolled out on a mass scale. Though national demographics, rural population numbers and distribution, as well as prior infection rates are all available, these are not useful for planning at the level of local authorities, which was found to be limited following a survey of current literature.

About the study

The current study data comes from the South West of England through the BNSSG system, which is a healthcare region that covers Bristol, North Somerset, and South Gloucestershire. A third of the population had received one dose of a COVID-19 vaccine, either the Pfizer/BioNTech or AstraZeneca vaccines.

The planned course of pandemic management envisaged the relaxation of all pandemic restrictions by June 21, 2021. Thus, the researchers estimated the number of new infections occurring by then, as modified by mass vaccination and events that could introduce delays into the process.

The BNSSG healthcare system used a modeling technique to plan for future bed requirements during the pandemic period. This was based on the projections made by a combination of public health information specialists, healthcare planners, academic scientists, and epidemiologists using data on testing, the movement of the public, bed occupancy, and extant restrictions.

Study findings

The data examines the risk of a third wave of COVID-19 during the autumn of 2021 caused by the rapid spread of SARS-CoV-2 within the susceptible population, including children and approximately 5% of the population who have not been vaccinated. This estimate shows that peak occupancy of hospital beds would be during the period from late November to the middle of December 2021, at which point herd immunity would be at its highest from a combination of natural infection and vaccination.

The models showed that with reduced vaccine uptake, delayed vaccine rollout, or both, a third wave would happen, with the peak case incidence and mortality being at different levels depending on the exact parameters. In the most likely cases, the infection trajectories varied from approximately 25 to 250 acute bed users at their peak, with the peak intensive care unit (ICU) bed user being less than 50.

The other three scenarios modeled higher peak demands that were above the second wave peak in January 2021, which is when the acute and ICU bed demand was at 388 and 68 beds, respectively. The highest demand among these three trajectories was at more than 2,000 and 400 acute and ICU beds, respectively. These trajectories were considered unlikely.

Implications

The scientists concluded that high vaccine coverage would be necessary for preventing undue pressure on hospital acute and ICU beds over fall and winter 2021. The target uptake of 95% adult vaccination by the end of July 2021 would not prevent the occurrence of the third wave; however, it would significantly lower peak demand for beds as compared to that observed at the peak of the second wave.

If the uptake was 75%, as expected from a normal vaccination campaign, the result would be excessive demand for acute and ICU beds, the latter being a fifth higher than that in January 2021. The pressure this would put on hospital capacity means that restrictions would probably be required again to control the incidence.

If the uptake of the vaccine occurs at a slower rate, with 95% uptake by September 30, 2021, peak demand would be approximately the same but would be advanced by six weeks due to the increased rate of spread among the non-vaccinated.

Conversely, if vaccine supply were to be reduced and vaccination was delayed by two months, bed demand would increase so slowly that a full reopening would occur. This would, however, lead to a rapid surge in cases until a peak resembling that of January 2021 occurred. Thus, those individuals who are at low risk but can still carry the virus to infect others need to be vaccinated to prevent viral spread to high-risk individuals.

The current study did not consider future variants of the virus or waning antibody titers over time, nor did it consider the variation in immunity after one or two doses. However, the authors here follow the line of earlier studies that suggest the need for restrictions, in addition to vaccination, to contain the virus. In fact, some scientists projected a “rise in acute admissions in the weeks and months after completing the vaccination effort.”

The seven-month gap since the completion of the modeling effort allows comparison with the actual scenario and the model within the BNSSG system. The vaccine uptake was eventually 83%, and the closest scenario shows that the peak demand for acute and ICU beds would be in early November 2021.

In real life, the peak came considerably earlier by the middle of September. The projected versus actual peaks were 138 and 29 for acute and ICU beds as compared to 105 and 21, respectively. At present, COVID-19 hospitalizations continue to wane, and vaccination is now being offered to children, while adults are being encouraged to take the third dose to boost their immunity.

The use of open-source code allows these modeling approaches to help healthcare systems plan their strategies for the best use of their resources.

Future investigators may wish to consider how efforts may be directed at the local level in supporting individual healthcare systems with easy-to-use, locally-configurable and reusable models; recognising that much of the actual on-the-ground decision-making takes place at this level.”

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • Apr 29 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Dr. Liji Thomas

Written by

Dr. Liji Thomas

Dr. Liji Thomas is an OB-GYN, who graduated from the Government Medical College, University of Calicut, Kerala, in 2001. Liji practiced as a full-time consultant in obstetrics/gynecology in a private hospital for a few years following her graduation. She has counseled hundreds of patients facing issues from pregnancy-related problems and infertility, and has been in charge of over 2,000 deliveries, striving always to achieve a normal delivery rather than operative.

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