Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.11.01.20222315: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, there are also limitations. During the period covered by this study, the outcome of recorded SARS-CoV-2 infection is mainly based on swab tests taken in community testing centres and healthcare settings that were later transferred to the primary care record. Therefore, results related to testing should be viewed as likely to be heavily influenced by people in high-risk jobs where testing was more easily available. A positive recorded infection combines the risk of being infected with the chance of being tested and this is particularly important for interpreting the interaction by date. Occupation was also an unmeasured confounder both in terms of exposure to SARS-CoV-2 (such as healthcare and other high-risk workers) and degree of contact with children outside the home (such as nursery workers). To explore the potential impact of lack of occupational information we conducted a quantitative bias analysis which did not meaningfully change our results for any outcome. We were not able to adjust for confounding by previous comorbidities that affected ability or choice to have children, and subsequent risk of development of severe outcomes from COVID-19. However, to examine the potential impact of this we show results from models with and without adjusting for baseline comorbidities and again find no important differences. It is likely we have misclassified the degree of contact with children in a number of situations such as for divorced parents, and limitations in the d...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. NCRC

    Our take

    This study of 9,157,814 people in England from February 1 to August 3, 2020, available as a preprint and thus not yet peer reviewed, sought to identify the risk of COVID-19 among adults due to living with children of different age groups. They found adults <65 years old had a reduced hazard of death (26% reduction) if they lived with children 0 to 11 years old than if they did not. They also found that living with children 12 to 18 years old increased the risk of infection by 8%. There was no significant effect of living with children for adults >65 years old on any outcomes. This was a national study from England, which has important policy implications for lockdown restrictions, including potential school closures. Caution in the interpretation is warranted as unaccounted for behavioral differences within families with small children could have affected their risk of infection, and authors did not account for timing of school closures.

    Study design

    prospective-cohort

    Study population and setting

    The study objective was to examine the risk of infection among adults associated with living with children of different age groups, both during and following school lockdown orders in England. The study included 9,157,814 adults between >=18 and <=65 years of age, and an additional cohort of adults >65 years old (N=2,567,671), and assessed the impact on SARS-CoV-2 infection from primary care records in The Phoenix Partnership, COVID-19 hospital admission using data from the Secondary Uses Service, COVID-19 ICU admission from the Intensive Care National Audit & Research Center, and death due to COVID-19 noted in the Office for National Statistics mortality records. This was done on the OpenSAFELY data analytics platform created for the National Health Service (NHS) of England. The study population required individuals to have >=3 months of active follow-up via general practices using the Phoenix Partnerhsip software from February 1, 2020 onwards. Hospital admission data were available until May 1, 2020, while infection outcomes were available through August 3. 2020. Children were linked to households via a household identifier and enumerated based on age, and exposure categories for adults in the study were grouped as: (1) no children under 18 in the house; (2) any child 0 to 11 years of age; (3) no children 0 to 11 years of age but one or more children 12 to 18 years old.

    Summary of main findings

    The study found that living with children 0 to 11 years of age was not associated with an increase in SARS-CoV-2 infection, COVID-19 hospital admission, or ICU admission among adults <65 years old. It did significantly reduce the hazard of death from COVID-19 by 26% (95% CI: 0.60 – 0.90). Living with children 12 to 18 years of age increased the risk of infection by 8% (95% CI: 1.03 – 1.13) but was not associated with any other outcomes. For adults <65 years of age, living with children age 0 to 11 years reduced the risk of death from non-COVID-19 causes by 32% (95% CI: 0.62 – 0.74), and by 27% (95% CI: 0.66 – 0.81) for those living with children 12 to 18 years. For adults >65 years of age, there were no associations with any of the outcomes, including infection, hospital admission, ICU admission, COVID-19-specific death, or non-COVID-19-death.

    Study strengths

    The study was able to use a large sample size based on attendance of a TPP general practice during the study period, which means they likely had power to identify infections and outcomes when they occurred. By linking to a number of registries, it had follow-up for the majority of this large population. They also controlled for many potential confounders, including age, sex, body mass index, smoking status, deprivation index, ethnicity, geographic area, and the total number of individuals in a household. They also controlled for chronic comorbidities associated with severe COVID-19 outcomes, further reducing the potential for confounding in these estimates.

    Limitations

    The largest limitation was data availability—for instance, for hospital admission they only had from February 1 to May 1, 2020, while for the other outcomes, they had longer follow-up until August. Given hospital admission data is focused in the beginning of the pandemic during the first wave, it may not be reflective of more recent trends. Occupation was also unmeasured, which could reflect whether individuals stayed in the house or were essential workers that had to continue contact. There also may be differences between risk behaviors among parents of children compared to those without that may impact their risk of exposure, thereby impacting the risk ratios with unmeasured confounding. Similarly, the study could not adjust for temporality differences such as school closures or other lockdown restrictions imposed, likely due to variability across schools. Finally, their measure of children was based off simply the number of children linked in the record, and may not actually reflect contact due to children residing with a different parent or with other family members.

    Value added

    This is the largest and most comprehensive study from a nation-wide cohort that examines the change in risk of COVID-19 in adults due to contact with children.

  3. ScreenIT

    SciScore for 10.1101/2020.11.01.20222315: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementThis study was approved by the Health Research Authority (REC reference 20/LO/0651) and by the LSHTM Ethics Board (reference 21863).Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    19 Software and Reproducibility We used Python 3.8 and SQL (Server 2016 Enterprise SP2) for data management and Stata 16 for analysis.
    Python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    However, there are also limitations. During the period covered by this study, the outcome of recorded SARS-CoV-2 infection is mainly based on swab tests taken in community testing centres and healthcare settings that were later transferred to the primary care record. Therefore, results related to testing should be viewed as likely to be heavily influenced by people in high-risk jobs where testing was more easily available. A positive recorded infection combines the risk of being infected with the chance of being tested and this is particularly important for interpreting the interaction by date. Occupation was also an unmeasured confounder both in terms of exposure to SARS-CoV-2 (such as healthcare and other highrisk workers) and degree of contact with children outside the home (such as nursery workers). To explore the potential impact of lack of occupational information we conducted a quantitative bias analysis which did not meaningfully change our results for any outcome. We were not able to adjust for confounding by previous comorbidities that affected ability or choice to have children, and subsequent risk of development of severe outcomes from COVID-19. However, to examine the potential impact of this we show results from models with and without adjusting for baseline comorbidities and again find no important differences. It is likely we have misclassified the degree of contact with children in a number of situations such as for divorced parents, and limitations in the da...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version 1 published on medRxiv