Demand for hospitalization services for COVID-19 patients in Brazil

  1. Marcia C. Castro
  2. Lucas Resende de Carvalho
  3. Taylor Chin
  4. Rebecca Kahn
  5. Giovanny V. A. França
  6. Eduardo Marques Macário
  7. Wanderson Kleber de Oliveira

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

COVID-19 is now a pandemic and many of the affected countries face severe shortages of hospital resources. In Brazil, the first case was reported on February 26. As the number of cases grows in the country, there is a concern that the health system may become overwhelmed, resulting in shortages of hospital beds, intensive care unit beds, and mechanical ventilators. The timing of shortage is likely to vary geographically depending on the observed onset and pace of transmission observed, on the availability of resources, and on the actions implemented. Here we consider the daily number of cases reported in municipalities in Brazil to simulate twelve alternative scenarios of the likely timing of shortage, based on parameters consistently reported for China and Italy, on rates of hospital occupancy for other health conditions observed in Brazil in 2019, and on assumptions of allocation of patients in public and private facilities. Results show that hospital services could start to experience shortages of hospital beds, ICU beds, and ventilators in early April, the most critical situation observed for ICU beds. Increasing the allocation of beds for COVID-19 (in lieu of other conditions) or temporarily placing all resources under the administration of the state delays the anticipated start of shortages by a week. This suggests that solutions adopted by the Brazilian government must aim at expanding the available capacity (e.g., makeshift hospitals), and not simply prioritizing the allocation of available resources to COVID-19.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.30.20047662: (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

    Software and Algorithms
    SentencesResources
    All analyses were performed with the use of R software, version 3·6·3, and Rstudio, version 1·2·5033 (R Foundation for Statistical Computing).
    Rstudio
    suggested: (RStudio, RRID:SCR_000432)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    By drawing on available evidence of how COVID-19 has and is evolving across the globe, our results rely on and reflect the limitations of the parameters observed in China and on unique patterns reported in Italy. Given the significant uncertainty in parameter estimates at this phase of the epidemic and the simplifying assumptions of an exponential model, results from our simulated scenarios should not be used as precise estimates for the exact timing and extent of capacity thresholds being reached. Instead, they aim to inform planning and prompt response and do send three important messages. First, the epidemic of COVID-19 is likely to exacerbate existing inequalities if those that solely rely on the SUS are hit the hardest. In communities with high population density and poor infrastructure, it is unfeasible to practice social isolation. In those areas, the transmission is likely to occur fast and the population mostly relies only on the SUS, quickly overwhelming the health system. One alternative to alleviate the is to temporarily put all private hospitals under the control of the state, a measure adopted by Spain.26 Yet, our results show that this would postpone shortages by about a week. In fact, solutions that do not involve the opening of new facilities will have a very short effect on the timing of shortage. Second, there is a short window of opportunity to prepare. The response must be immediate, and it will demand a concerted effort from society. Repurposing large sp...

    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.

  2. Version published to 10.1101/2020.03.30.20047662v1 on medRxiv