Evidence map›Paper›PMID 36962677›Full record

ArticlePLOS global public health2022

Management of hospital beds and ventilators in the Gauteng province, South Africa, during the COVID-19 pandemic.

Mahnaz Alavinejad, Bruce Mellado, Ali Asgary, Mduduzi Mbada, Thuso Mathaha, Benjamin Lieberman, Finn Stevenson, Nidhi Tripathi, Abhaya Kumar Swain, James Orbinski and 2 more

Full text read
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Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Rethinking the evidence on COVID-19 in Africa.The Lancet. Infectious diseases · 2025
    Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Mahnaz AlavinejadAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York University, Toronto, Canada.
Bruce MelladoAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), School of Physics, Institute for Collider Particle Physics, University of the Witwatersrand, Johannesburg, South Africa.
Ali AsgaryAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), The Advanced Disaster, Emergency and Rapid Response Program, York University, Toronto, Canada.ORCID https://orcid.org/0000-0002-6253-1021
Mduduzi MbadaHead of Policy at Gauteng Office of the Premier, Johannesburg, South Africa.
Thuso MathahaUniversity of the Witwatersrand, Johannesburg, South Africa.
Benjamin LiebermanUniversity of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0001-5281-8937
Finn StevensonUniversity of the Witwatersrand, Johannesburg, South Africa.
Nidhi TripathiUniversity of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0001-7518-1238
Abhaya Kumar SwainUniversity of the Witwatersrand, Johannesburg, South Africa.
James OrbinskiAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), The Dahdaleh Institute for Global Health Research, York University, Toronto, Canada.ORCID https://orcid.org/0000-0002-0186-1406
Jianhong WuAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York University, Toronto, Canada.
Jude Dzevela KongAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York University, Toronto, Canada.ORCID https://orcid.org/0000-0002-7557-5672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We conducted an observational retrospective study on patients hospitalized with COVID-19, during March 05, 2020, to October 28, 2021, and developed an agent-based model to evaluate effectiveness of recommended healthcare resources (hospital beds and ventilators) management strategies during the COVID-19 pandemic in Gauteng, South Africa. We measured the effectiveness of these strategies by calculating the number of deaths prevented by implementing them. We observed differ ences between the epidemic waves. The length of hospital stay (LOS) during the third wave was lower than the first two waves. The median of the LOS was 6.73 days, 6.63 days and 6.78 days for the first, second and third wave, respectively. A combination of public and private sector provided hospital care to COVID-19 patients requiring ward and Intensive Care Units (ICU) beds. The private sector provided 88.4% of High care (HC)/ICU beds and 49.4% of ward beds, 73.9% and 51.4%, 71.8% and 58.3% during the first, second and third wave, respectively. Our simulation results showed that with a high maximum capacity, i.e., 10,000 general and isolation ward beds, 4,000 high care and ICU beds and 1,200 ventilators, increasing the resource capacity allocated to COVID- 19 patients by 25% was enough to maintain bed availability throughout the epidemic waves. With a medium resource capacity (8,500 general and isolation ward beds, 3,000 high care and ICU beds and 1,000 ventilators) a combination of resource management strategies and their timing and criteria were very effective in maintaining bed availability and therefore preventing excess deaths. With a low number of maximum available resources (7,000 general and isolation ward beds, 2,000 high care and ICU beds and 800 ventilators) and a severe epidemic wave, these strategies were effective in maintaining the bed availability and minimizing the number of excess deaths throughout the epidemic wave.

Identifiers

PMID36962677
PMCPMC10022393

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LicenceCC BY
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identifiers read14
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.