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Sex Bias in COVID-19 Data - Supplementary Table 1

dataset
posted on 28.09.2020 by Hannah Peckham, Nina De Gruijter, Ania Radziszewska, Coziana Ciurtin, Lucy Wedderburn, Charles Raine, Lizzy Rosser, Claire Deakin, Kate Webb

An online search of government websites and published literature was performed for regional data reports on COVID-19 cases that included sex as a variable from 1st January 2020 up until 1st June 2020 (Search terms: COVID-19/case/sex/country/data/death/ICU/ITU). In order to ensure unbiased representation from as many regions as possible, a cross check was done using the list of countries reporting data on ‘Worldometer’, and an attempt was made to include as many regions reporting sex data as possible. Reports were translated using Google translate if they were not in English.

Data selection, extraction and synthesis

Reports were included if they contained sex as a variable in data describing case number, intensive treatment unit (ITU) admission, or mortality. Data were entered directly by individual researchers into an online structured data extraction table. For some sources, counts of male confirmed cases or male deaths were not provided, but percentages of male cases or male deaths were provided instead. To include these sources and avoid biases that might be introduced by their exclusion, we calculated counts of male confirmed cases and male deaths from the reported percentages with rounding to the nearest integer. We acknowledge that this approach assumes that the reported percentages are reflective of the true percentages. For some sources, data included confirmed cases and deaths of unknown sex. For these sources, the reported totals were used where the proportion of unknown sex was small. This approach was preferred to excluding cases of unknown sex in order to avoid bias. The estimates represent the proportion of known male infections and odds ratios for mortality associated with known male sex, and will differ slightly from what the true values would be if the sex had been reported for all cases. Data were available at the level of country or regional summary data representing distinct individuals for each report, but not at the level of covariates for all individuals within a study. Consequently, covariates such as lifestyle, comorbidities, testing method and case type (hospital vs. community) could not be controlled for.

Funding

GCRF-Crick African Network

Medical Research Council

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Versus Arthritis Centre of Excellence Award 21593

MICA: Childhood arthritis and its associated uveitis: stratification through endotypes and mechanism to deliver benefit; the CLUSTER Consortium.

Medical Research Council

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Great Ormond Street Children’s Charity to LRW and NIHR Biomedical Research Centre at University College London Hospital (BRC/III 525)

Medical Research Foundation Lupus Fellowship (MRF-057-0001-RG-ROSS-C079)

NIHR Biomedical Research Centre at Great Ormond Street Hospital

Versus Arthritis Studentship (22203)

History

Department/Unit

Department of Paediatric Rheumatology, School of Child and Adolescent Health, Red Cross War Memorial Children’s Hospital, University of Cape Town, South Africa.

Licence

Exports