Sex-disaggregated data is reported by Public Health England – Authors' reply
Bibliographic record
Abstract
We are pleased that Public Health England, in their response to our Correspondence,1Hawkes S Tanaka S Pantazis A et al.Recorded but not revealed: exploring the relationship between sex and gender, country income level, and COVID-19.Lancet Glob Health. 2021; 9: e751-e752Summary Full Text Full Text PDF PubMed Scopus (6) Google Scholar have emphasised the importance of sex and gender in the COVID-19 pandemic. We are aware of the sex-disaggregated data produced by Public Health England, which is used in our COVID-19 sex-disaggregated data tracker.2Global Health 50/50 The COVID-19 sex-disaggregated data tracker.https://globalhealth5050.org/the-sex-gender-and-covid-19-project/Date accessed: April 30, 2021Google Scholar While recognising the availability of the data included in our tracker, our Correspondence1Hawkes S Tanaka S Pantazis A et al.Recorded but not revealed: exploring the relationship between sex and gender, country income level, and COVID-19.Lancet Glob Health. 2021; 9: e751-e752Summary Full Text Full Text PDF PubMed Scopus (6) Google Scholar highlighted issues regarding the regularity and accessibility of Public Health England reporting of sex-disaggregated data. The statement in our Correspondence, which we affirm, was informed by what were labelled as official Public Health England responses to our emails, as well as more than a year of experience searching for and collecting sex-disaggregated data from the Public Health England website. Public reporting of sex-disaggregated data from England did not appear until the end of April, 2020, months into the COVID-19 pandemic, and data were provided in a format that was time-consuming to extract.3Public Health EnglandNational COVID-19 Surveillance Reports.https://www.gov.uk/government/publications/national-covid-19-surveillance-reportsDate accessed: April 30, 2021Google Scholar COVID-19 data were subsequently moved to a new reporting format,4Public Health EnglandNational flu and COVID-19 surveillance reports.https://www.gov.uk/government/statistics/national-flu-and-covid-19-surveillance-reportsDate accessed: April 30, 2021Google Scholar which at first no longer included any extractable sex-disaggregated death data. Email correspondence in November, 2020, with members of the Public Health England influenza team who were responsible for these reports informed us that a decision had been made to stop reporting sex-disaggregated death data. Therefore, for a period of months, we could not report sex-disaggregated COVID-19 death data from England. We later wrote to the official email address provided for the Government's COVID-19 dashboard with a request that additional sex-disaggregated data be included. However, we were informed that such data were not included because sex “does not appear to be an important risk factor for COVID”. We wrote back to this email but have not received a response. The example of England referenced in our Correspondence1Hawkes S Tanaka S Pantazis A et al.Recorded but not revealed: exploring the relationship between sex and gender, country income level, and COVID-19.Lancet Glob Health. 2021; 9: e751-e752Summary Full Text Full Text PDF PubMed Scopus (6) Google Scholar illustrates an important and recurring issue we have seen globally concerning the consistent reporting sex-disaggregated data in the pandemic, including by countries with the resources to do so. This is illustrative of a larger problem across the health and medical sector in which sex and gender are frequently overlooked or ignored.5Gupta GR, Oomman N, Grown C, et al. Gender equality and gender norms: framing the opportunities for health. Lancet 393: 2550–62.Google Scholar We are grateful to Public Health England for taking the time to respond to our Correspondence and for their engagement over the preceding and exceedingly challenging months. As an accountability mechanism, our objective is not to criticise national responses, but to raise national and global awareness of the importance of sex and gender in designing effective and equitable pandemic responses that reach everyone. We are pleased that Public Health England is rising to this challenge. SH reports grants and personal fees from the Bill & Melinda Gates Foundation during the conduct of the study. SK-M, KB, and AP report grants from the Bill & Melinda Gates Foundation during the conduct of the study. ST declares no competing interests. Recorded but not revealed: exploring the relationship between sex and gender, country income level, and COVID-19In 2020 we witnessed a seeming exponential spread of information about COVID-19. From understanding the pathogen to understanding its effect on populations, we have a wealth of evidence for decision making in pandemic control. Nonetheless, there remain some fundamental areas of investigation and response for which evidence remains oddly and inconsistently absent. The role of sex and gender in understanding the testing-to-outcome pathway of the pandemic is one such area. Full-Text PDF Open AccessSex-disaggregated data is reported by Public Health EnglandWe agree with Sarah Hawkes and colleagues (June, 2021)1 who state that reporting COVID-19 outcomes by sex is an important component of global pandemic surveillance and monitoring of inequalities, and we congratulate them on establishing the COVID-19 sex-disaggregated data tracker. In June, 2020, a comprehensive Public Health England report showed that sex was a risk factor for COVID-19 infection, hospitalisation (including critical care and lower level of care), death, and excess mortality.2 In an article published in 2021, we confirmed that male sex was a risk factor for poorer outcomes from COVID-19 and considered the implications for vaccination prioritisation. Full-Text PDF Open Access
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.011 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".