Evidence map›Paper›PMID 40017867›Full record

ArticleBMJ public health2023

Turning point in COVID-19 severity and fatality during the pandemic: a national cohort study in Qatar.

Hiam Chemaitelly, Houssein H Ayoub, Jeremy Samuel Faust, Peter Coyle, Patrick Tang, Mohammad R Hasan, Hadi M Yassine, Hebah A Al-Khatib, Asmaa A Al Thani, Zaina Al-Kanaani and 14 more

Abstract read
In one paragraph

Article in BMJ public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

24 authors.

Hiam ChemaitellyInfectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.
Houssein H AyoubMathematics Program, Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar.
Jeremy Samuel FaustDepartment of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Peter CoyleHamad Medical Corporation, Doha, Qatar.
Patrick TangDepartment of Pathology, Sidra Medicine, Doha, Qatar.
Mohammad R HasanDepartment of Pathology, Sidra Medicine, Doha, Qatar.
Hadi M YassineBiomedical Research Center, QU Health, Qatar University, Doha, Qatar.
Hebah A Al-KhatibBiomedical Research Center, QU Health, Qatar University, Doha, Qatar.
Asmaa A Al ThaniBiomedical Research Center, QU Health, Qatar University, Doha, Qatar.
Zaina Al-KanaaniHamad Medical Corporation, Doha, Qatar.
Einas Al-KuwariHamad Medical Corporation, Doha, Qatar.
Andrew JeremijenkoHamad Medical Corporation, Doha, Qatar.
Anvar Hassan KaleeckalHamad Medical Corporation, Doha, Qatar.
Ali LatifHamad Medical Corporation, Doha, Qatar.
Riyazuddin Mohammad ShaikHamad Medical Corporation, Doha, Qatar.
Hanan F Abdul-RahimDepartment of Public Health, College of Health Sciences, Qatar University, Doha, Qatar.
Gheyath K NasrallahBiomedical Research Center, QU Health, Qatar University, Doha, Qatar.
Mohamed Ghaith Al-KuwariPrimary Health Care Corporation, Doha, Qatar.
Adeel Ajwad ButtDepartment of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA.
Hamad Al-RomaihiMinistry of Public Health, Doha, Qatar.
Mohamed H Al-ThaniMinistry of Public Health, Doha, Qatar.
Abdullatif Al-KhalHamad Medical Corporation, Doha, Qatar.
Roberto BertolliniMinistry of Public Health, Doha, Qatar.
Laith J Abu-RaddadInfectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.ORCID 0000-0003-0790-0506

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess the evolution of COVID-19 severity and fatality in a unique setting that consistently applied, throughout the pandemic, rigorous and standardised criteria for defining severe COVID-19 outcomes. Methods and analysis: We conducted a national cohort study on 312 109 Qatari citizens to investigate incidence of severe, critical or fatal COVID-19 classified according to the WHO criteria between 28 February 2020 and 21 April 2023. Incidence rates for severe, critical or fatal COVID-19 were estimated during the pre-omicron phase, first omicron wave, combined phases and throughout the pandemic. Results: Cumulative incidence of severe, critical or fatal COVID-19 after 3.14 years of follow-up was 0.45% (95% CI 0.43% to 0.47%). Incidence rate for severe, critical or fatal COVID-19 throughout the pandemic was 1.43 (95% CI 1.35 to 1.50) per 1000 person years. In the pre-omicron phase, first omicron wave, and combined phases, it was 2.01 (95% CI 1.90 to 2.13), 3.70 (95% CI 3.25 to 4.22) and 2.18 (95% CI 2.07 to 2.30) per 1000 person years, respectively. The post-first omicron phase saw a drastic drop to 0.10 (95% CI 0.08 to 0.14) per 1000 person years, a 95.4% reduction. Among all severe, critical and fatal cases, 99.5% occurred during the primary infection. Cumulative incidence of fatal COVID-19 was 0.042% (95% CI 0.036% to 0.050%), with an incidence rate of 0.13 (95% CI 0.11 to 0.16) per 1000 person years. In the post-first omicron phase, incidence rate of fatal COVID-19 decreased by 90.0% compared with earlier stages. Both severity and fatality exhibited an exponential increase with age and a linear increase with the number of coexisting conditions. Conclusion: The conclusion of the first omicron wave was a turning point in the severity of the pandemic. While vaccination and enhanced case management reduced severity gradually, the rapid accumulation of natural immunity during the first omicron wave appears to have played a critical role in driving this shift in severity.

Indexed as

COVID-19epidemiologySARS-CoV-2

Identifiers

PMID40017867
PMCPMC11812731

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.