Evidence map›Paper›PMID 33033033›Full record

ArticleBMJ open2020

Epidemiological investigation of the first 5685 cases of SARS-CoV-2 infection in Qatar, 28 February-18 April 2020.

Hanan M Al Kuwari, Hanan F Abdul Rahim, Laith J Abu-Raddad, Abdul-Badi Abou-Samra, Zaina Al Kanaani, Abdullatif Al Khal, Einas Al Kuwari, Salih Al Marri, Muna Al Masalmani, Hamad E Al Romaihi and 6 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 5 pooled it
2.2field-weighted citation impact, top 7% 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

60 citing papers in PubMed, 5 syntheses or guidelines pooled it, 90 citations in OpenAlex.

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  12. Sickness absenteeism among primary health care workers in Qatar before and during the COVID-19 pandemic.Journal of occupational medicine and toxicology (London, England) · 2023
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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

16 authors at 5 institutions in 2 countries.

Hanan M Al KuwariOffice of the Minister of Public Health, Ministry of Public Health, Doha, Qatar.
Hanan F Abdul RahimCollege of Health Sciences, QU Health, Qatar University, Doha, Qatar.
Laith J Abu-RaddadInfectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.ORCID 0000-0003-0790-0506
Abdul-Badi Abou-SamraDepartment of Medicine, Hamad Medical Corporation, Doha, Qatar.
Zaina Al KanaaniBusiness Intelligence Unit, Hamad Medical Corporation, Doha, Qatar.
Abdullatif Al KhalDepartment of Medicine, Hamad Medical Corporation, Doha, Qatar.
Einas Al KuwariDepartment of Laboratory Medicine, Hamad Medical Corporation, Doha, Qatar.
Salih Al MarriOffice of the Minister of Public Health, Ministry of Public Health, Doha, Qatar.
Muna Al MasalmaniDepartment of Medicine, Hamad Medical Corporation, Doha, Qatar.
Hamad E Al RomaihiOffice of the Minister of Public Health, Ministry of Public Health, Doha, Qatar.
Mohamed H Al ThaniOffice of the Minister of Public Health, Ministry of Public Health, Doha, Qatar.
Peter V CoyleDepartment of Laboratory Medicine, Hamad Medical Corporation, Doha, Qatar.
Ali N LatifBusiness Intelligence Unit, Hamad Medical Corporation, Doha, Qatar.
Robert OwenNational Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
Roberto BertolliniOffice of the Minister of Public Health, Ministry of Public Health, Doha, Qatar.
Adeel Ajwad ButtDepartment of Medicine, Hamad Medical Corporation, Doha, Qatar aabutt@hamad.qa.ORCID 0000-0002-1118-1826
Hamad Medical Corporation · QAMinistry of Public Health · QACornell University · USQatar University · QAWeill Cornell Medical College in Qatar · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo define the epidemiological curve of COVID-19 in Qatar and determine factors associated with severe or critical illness.

designCase series of first 5685 COVID-19 cases in Qatar. SETTING AND

participantsAll confirmed COVID-19 cases in the State of Qatar between 28 February and 18 April 2020.

main outcome measuresNumber of total and daily new COVID-19 infections; demographic characteristics and comorbidity burden and severity of infection; factors associated with severe or critical illness.

resultsBetween 28 February and 18 April 2020, 5685 cases of COVID-19 were identified. Median age was 34 (IQR 28-43) years, 88.9% were male and 8.7% were Qatari nationals. Overall, 83.6% had no concomitant comorbidity, and 3.0% had three or more comorbidities. The overwhelming majority (90.9%) were asymptomatic or with minimal symptoms, with 2.0% having severe or critical illness. Seven deaths were observed during the time interval studied. Presence of hypertension or diabetes was associated with a higher risk of severe or critical illness, but age was not. The epidemiological curve indicated two distinct patterns of infection, a larger cluster among expatriate craft and manual workers and a smaller one among Qatari nationals returning from abroad during the epidemic.

conclusionCOVID-19 infections in Qatar started in two distinct clusters, but then became more widespread in the population through community transmission. Infections were mostly asymptomatic or with minimal symptoms and associated with very low mortality. Severe/critical illness was associated with presence of hypertension or diabetes but not with increasing age.

Indexed as

PandemicsSeverity of Illness IndexAdolescentAdultAsymptomatic InfectionsBetacoronavirusComorbidityCoronavirus InfectionsCOVID-19Diabetes MellitusDisease OutbreaksFemaleHumansHypertensionMaleMiddle Agedepidemiologypublic health

Identifiers

PMID33033033
PMCPMC7542927
OpenAlexW3092050445

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.