Evidence map›Paper›PMID 34252381›Full record

ArticleThe Lancet. Global health2021

Difference in mortality among individuals admitted to hospital with COVID-19 during the first and second waves in South Africa: a cohort study.

Waasila Jassat, Caroline Mudara, Lovelyn Ozougwu, Stefano Tempia, Lucille Blumberg, Mary-Ann Davies, Yogan Pillay, Terence Carter, Ramphelane Morewane, Milani Wolmarans and 5 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed, 1 pooled it
14.6field-weighted citation impact, top 1% of its field
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

114 citing papers in PubMed, 1 synthesis or guideline pooled it, 176 citations in OpenAlex.

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54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 6 institutions in 2 countries.

Waasila JassatNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa. Electronic address: waasilaj@nicd.ac.za.
Caroline MudaraNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
Lovelyn OzougwuNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
Stefano TempiaNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
Lucille BlumbergNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
Mary-Ann DaviesHealth Impact Assessment Directorate, Western Cape Government, Cape Town, South Africa.
Yogan PillayClinton Health Access Initiative, Pretoria, South Africa.
Terence CarterClinton Health Access Initiative, Pretoria, South Africa.
Ramphelane MorewaneNational Department of Health, Pretoria, South Africa.
Milani WolmaransNational Department of Health, Pretoria, South Africa.
Anne von GottbergNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
Jinal N BhimanNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
Sibongile WalazaNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
Cheryl CohenNational Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
DATCOV author group
National Health Laboratory Service · ZAUniversity of the Witwatersrand · ZADepartment of Health · ZAWestern Cape Department of Health · ZANational Center for Communicable Diseases · MNNational Institute for Communicable Diseases

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves.

methodsIn this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression.

findingsPeak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240·4 cases per 100 000 people vs 136·0 cases per 100 000 people; admissions, 27·9 admissions per 100 000 people vs 16·1 admissions per 100 000 people; deaths, 8·3 deaths per 100 000 people vs 3·6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1·19, 95% CI 1·18-1·20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40-64 years (adjusted odds ratio [aOR] 1·22, 95% CI 1·14-1·31), and older than 65 years (aOR 1·38, 1·25-1·52), compared with younger than 40 years; of Mixed race (aOR 1·21, 1·06-1·38) compared with White race; and admitted in the public sector (aOR 1·65, 1·41-1·92); and less likely to be Black (aOR 0·53, 0·47-0·60) and Indian (aOR 0·77, 0·66-0·91), compared with White; and have a comorbid condition (aOR 0·60, 0·55-0·67). For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1·31, 95% CI 1·28-1·35). In-hospital case-fatality risk increased from 17·7% in weeks of low admission (<3500 admissions) to 26·9% in weeks of very high admission (>8000 admissions; aOR 1·24, 1·17-1·32).

interpretationIn South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage.

fundingDATCOV as a national surveillance system is funded by the National Institute for Communicable Diseases and the South African National Government.

Indexed as

AdultAgedCOVID-19FemaleHospitalizationHospital MortalityHumansMaleMiddle AgedProspective StudiesRisk FactorsSouth Africa

Identifiers

PMID34252381
PMCPMC8270522
OpenAlexW3182013552

What OpenQuestion holds

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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.