key: cord-0727208-wmyn0b4z authors: Smith, Daniel; Bowring, Claire; Wells, Nicholas; Crawford, Michael; Timpson, Nicholas John; Northstone, Kate title: The Avon Longitudinal Study of Parents and Children - A resource for COVID-19 research: Questionnaire data capture November 2020 – March 2021 date: 2021-06-16 journal: Wellcome Open Res DOI: 10.12688/wellcomeopenres.16950.1 sha: 081b9f38f3b113b2537ea1d99c5967b3f6ed8021 doc_id: 727208 cord_uid: wmyn0b4z The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1990-1992 and has followed these women, their partners (Generation 0; G0) and their offspring (Generation 1; G1) ever since. The study has reacted rapidly and repeatedly to the coronavirus disease 2019 (COVID-19) pandemic, deploying online questionnaires throughout the pandemic. In November/December 2020, a fourth questionnaire was deployed asking about physical and mental health, lifestyle and behaviours, employment and finances. G0 participants were offered an online questionnaire between 17 (th) November 2020 and 7 (th) February 2021, while G1 participants were offered both online and paper questionnaires between 1 (st) December 2020 and 19 (th) March 2021. Of 15,844 invitations, 8,643 (55%) participants returned the questionnaire (3,101 original mothers [mean age 58.6 years], 1,172 original fathers/partners [mean age 61.5 years] and 4,370 offspring [mean age 28.4 years]). Of these 8,643 participants, 2,012 (23%) had not returned a previous COVID-19 questionnaire, while 3,575 (41%) had returned all three previous questionnaires. In this questionnaire, 300 participants (3.5%) reported a previous positive COVID-19 test, 110 (1.3%) had been told by a doctor they likely had COVID-19, and 759 (8.8%) suspected that they had had COVID-19. Based on self-reported symptoms, between October 2020 and February 2021 359 participants (4.2%) were predicted COVID-19 cases. COVID data is being complemented with linkage to health records and Public Health England pillar testing results as they become available. Data has been released as an update to the previous COVID-19 datasets. It comprises: 1) a standard dataset containing all participant responses to both questionnaires with key sociodemographic factors; and 2) as a composite release coordinating data from the existing resource, thus enabling bespoke research across all areas supported by the study. This data note describes the fourth questionnaire and the data obtained from it. At the time of writing (May 2021), we are over a year into the coronavirus disease 2019 (COVID- 19) pandemic. The global impact has been considerable, with over 165 million confirmed cases -and over three million deaths -to date (WHO COVID-19 Dashboard). Despite the roll-out of vaccines, many countries are still under some form of restrictions, including local or national lockdowns. In the UK, mitigation strategies against the COVID-19 pandemic have changed repeatedly since March 2020, from an initial comprehensive set of restrictions on normal life (termed the 'lockdown') which took effect on March 23 rd 2020, to easing throughout summer 2020, followed by more targeted 'local' restrictions in Autumn 2020, back to second (in November 2020) and third (from early January 2021) nationwide lockdowns (with differing rules in different UK nations). More detailed information on the COVID timeline in the UK can be viewed here. Since 29 th March 2021, a gradual lifting of the restrictions has been introduced in the UK, such as a return to school and groups of up to six people being allowed to meet outdoors (whilst adhering to social distancing). The impact of the COVID-19 pandemic and its management, including continuing restrictions, has lasted over a year; the long-term impact of COVID-19 on current and future employment, physical and mental health, financial activity and personal relationships is therefore likely to be substantial. It is vital that longitudinal, population-based studies continue to prospectively measure the impact of lockdowns and various management strategies on their participants. Such studies are needed to understand the ongoing effects of mitigation strategies on health and well-being 1 and identifying inequalities in response to the pandemic 2 . The Avon Longitudinal Study of Parents and Children (ALSPAC) is a unique three-generational study, comprising 'G0': the cohort of original pregnant women and the fathers/partners of these women; 'G1': the cohort of index children; and 'G2': the cohort of offspring of the index children. The study has a wealth of biological, genetic and phenotypic data across these generations [3] [4] [5] [6] . ALSPAC has been well placed to capture information across key parts of the population during the COVID-19 pandemic -in particular the contrast between those in higher risk (the G0 cohort; mean age ~59 years) and lower risk (the G1 cohort; mean age ~28 years) groups. We have been able to collect repeat data quickly using our existing infrastructure for online data collection. So far, ALSPAC has conducted three COVID-19 questionnaires using G0 and G1 data: the first between 9 th April to 15 th May 2020 7 , the second between 26 th May to 5 th July 2020 8 ; and the third, with an antibody test, between 3 rd and 20 th October 2020 9 . As part of the second questionnaire, parents of G2 children also completed a questionnaire for each of their children 10 . The wider COVID-19 data collection in ALSPAC will include data from three main sources: self-reported data from questionnaires, data from clinical services based on linkage to medical and other records (such as Public Health England Pillar testing 11 ) and information from biological samples. The data from these sources are intended to be complementary and help address different potential research questions around COVID-19. This data note describes the data collected via our fourth questionnaire between 17 th November 2020 and 19 th March 2021 and provides a summary of the participants who responded. The update to the datasets obtained from our previous questionnaires 7-9 is described here, together with any variables that have been derived using multiple sets of questionnaire data. We also present a brief assessment of the factors associated with returning the fourth COVID questionnaire, but not any of the previous three, in order to explore who these 'new' participants are. ALSPAC is an intergenerational longitudinal cohort that recruited pregnant women residing in Avon, UK with expected dates of delivery 1 st April 1991 to 31 st December 1992 3,4 . The initial cohort consisted of 14,541 pregnancies resulting in 14,062 live births and 13,988 children who were alive at one year of age. From the age of seven onwards, the initial sample was bolstered with eligible cases who had originally failed to join the study and there were subsequently 14,901 children alive at one year of age following this further recruitment 5 . Please note, the study website contains details of all the data that is available through a fully searchable data dictionary and variable search tool. In response to the COVID-19 pandemic it was necessary to develop a data collection strategy which was practical, would yield data quickly and could be updated and repeated if necessary. For these reasons, we initially chose to use an online-only data collection approach for this, restricting our invites to those participants with a valid email address (and coordinated with a systematic communications/outreach campaign to obtain updated information from participants). For the fourth COVID-19 questionnaire, G0 data collection was again online-only. However, for G1 participants this COVID questionnaire was embedded within the wider 'Life@28' questionnaire as part of ALSPAC's annual questionnaire strategy; this questionnaire was therefore available to G1 participants in both online and paper formats. This meant that, unlike previous questionnaires, G1 participants without a valid email address were sent a physical invitation letter through the post. For G0 participants, invites were only sent to those with a valid email address. The online questionnaire was developed and deployed using Research Electronic Data Capture (REDCap) tools 12 ); a secure web application for building and managing online data collection exercises, hosted at the University of Bristol. Paper questionnaires were designed, scanned and verified using Teleform data capture software (version 16.5 (19) 22/10/2018). As this COVID-19 questionnaire was part of the usual ALSPAC annual data collection strategy for G1 we did not collect data from parents of G2 children not enrolled as G1 offspring (i.e., G1 partners). Content for our fourth questionnaire was selected to address three needs: 1. The need to track changes in health and wellbeing over time using repeated measures. To address this, we repeated a panel of questions from our previous questionnaires (e.g., health symptoms, recent contacts, mental health). By repeating questions, we are also able to capture information about participants who did not complete the previous COVID questionnaires. 2. The need to harmonize data collection with other cohorts to facilitate co-ordinated analyses as part of the National Core Studies Longitudinal Health and Wealth work programme. We addressed this by incorporating content from a coordinated and freely available COVID-19 questionnaire co-developed by ALSPAC. This questionnaire was developed in consultation with a network of UK and international longitudinal population studies and partners through a process facilitated by Wellcome. 3. The need to gather data to investigate specific hypotheses which could not be tested using the previous questionnaires. These topics were suggested by our collaborators and are detailed below. The questionnaire included six sections, and captured information on the following (if the questions come from a standardised questionnaire, the source and reference has been provided in brackets; questions asked repeated from previous COVID-19 questionnaires The final questionnaire (REDCap PDF) used is available with the associated data dictionary (which includes frequencies of all variables that are available) as Extended data 18 . Unlike previous ALSPAC COVID questionnaires, the invitation and reminder strategies differed for G0 and G1 cohorts, so will be explained here in turn. In all cases, participants were not contacted if our administrative database record indicated that they were deceased, had withdrawn from the study, had declined further contact or had declined to complete questionnaires. On the 26 th and 27 th November 2020, all G0 participants for whom we had an active email address were sent an invitation to complete the questionnaire (n=6,721; note that this includes 12 G0 mother participants sent a questionnaire after this date as a result of outreach work undertaken by the ALSPAC team). On the 10 th December 2020 and 6 th January 2021, any nonresponders were sent a reminder email or text respectively to complete the questionnaire, and a final text message was sent on 22 nd January 2021 to those for whom we had a current mobile phone number. The questionnaire survey was live on the online platform for nearly three months, with G0 questionnaire data collection turned off on 7 th February 2021. All G1 participants with an active email address or known home address, and who had not withdrawn from the study, were sent an invitation to complete the online questionnaire on 2 nd December 2020 (n=9,123; including five G1 participants sent a questionnaire after this date as a result of outreach work undertaken by the ALSPAC team). On the 15 th December 2020 and 5 th January 2021, any non-responders were sent a reminder email to complete the online questionnaire. As part of our general questionnaire strategy, and in an effort to reduce paper printing, we elected to only send paper-based questionnaires to those participants who were deemed more likely to complete on paper. We defined this as participants who had completed at least one of the last three annual questionnaires on paper. Just over 1,000 paper questionnaires were sent out on 6 th January 2021. A letter was sent between 18 th and 22 nd January and finally a text reminder on the 29 th January to nonresponders. The questionnaire was live on the online platform for nearly three months, with G1 questionnaire data collection turned off on 15 th February 2021. ALSPAC stopped counting paper questionnaires on 19 th March 2021. In addition, traditional (print, radio, television) and social media (Facebook, Instagram and Twitter) were used to inform participants that the questionnaire was live, asking them to contact us if they had not received it and to encourage completion. These communication channels were also used to encourage re-engagement of friends and family back into the study. Unlike our standard questionnaires (usually completed annually), we did not provide any incentive for G0 completion. As the fourth COVID questionnaire was embedded within the wider annual questionnaire, G1 participants were offered an incentive (a £10 shopping voucher) for returning a questionnaire. For both G0 and G1, we offered a prize draw (three prizes of £100) for those who completed their questionnaire by 31 st January 2021 (for G0 participants) or 7 th February 2021 (for G1 participants). Response rate A total of 15,844 invitations were sent out and responses were received from 8,643 participants (overall response rate of 55%). As with our previous COVID questionnaires, female G1 participants were much more likely to respond than male G1 participants. Table 1 summarises the response rate within each group organised by cohort structure. Response rate amongst G0s was higher for the fourth questionnaire (64%; 4,273/6,721) compared to the first (57%; 3,720/6,393) and second (58%; 3,678/6,467). Response rate for the G1 cohort (48%; 4,370/9,123) was slightly higher than for the second COVID-19 questionnaire (44%; 2,711/6,148), but lower than response to the first questionnaire (51%; 2,973/5,842). At face value, the £10 gift voucher incentive for G1s did not appear to increase response rates for this questionnaire. However, this may be explained by the fact that earlier COVID-19 questionnaires only went out to those with valid email addresses, whereas this questionnaire was also sent to G1 participants via post, meaning this fourth COVID-19 questionnaire was sent to a larger sample of G1 participants. These 'new' participants may be less engaged with the study, and hence less likely to return a questionnaire, which may balance out the benefit of having an incentive. Supporting this idea, if we split the G1 data according to whether they were sent an invitation for the second COVID-19 questionnaire, of the 6,143 participants who were sent both the second and fourth COVID-19 questionnaire invitations, 4,005 (65%) returned the fourth COVID-19 questionnaire. In contrast, of the 2,980 participants who were not invited to complete the second COVID-19 questionnaire but were invited to complete the fourth COVID-19 questionnaire, only 365 (12%) returned one. Of the 8,643 respondents, 2,012 (23%) had not returned a previous COVID questionnaire, 3,575 (41%) had returned all three of the previous COVID questionnaires, with 3,056 (35%) returning one or two (but not all three) of the previous COVID questionnaires ( Table 2 ). Of those who returned a fourth COVID questionnaire, G1 participants were more likely to have not completed a previous COVID questionnaire (31% of G1s, vs 16% of G0 mothers and 15% of G0 fathers/partners). Characteristics of responders according to key variables that will be released with the complete dataset can be seen in Table 3 . The population who responded were predominantly white (> 96%) and the majority had at least A-level qualifications (optional exams in the UK sat at the age of 18 years), with 54% of G0 mothers, 70% of G0 partners/fathers and 74% of G1 offspring in this category. G0 partners/fathers were three years older on average than G0 mothers (61.5 years vs 58.6 years), with G1 offspring having an average age of 28.4 years. As with the previous questionnaires, participants were asked whether they thought they have had COVID-19. Options were: 'Yes, confirmed by a positive test', 'Yes, suspected by a doctor but not tested', 'Yes, my own suspicions' or 'No'. In the fourth questionnaire, 300 (3.5%) respondents reported that they had tested positive to COVID-19, 110 (1.3%) reported that COVID-19 was suspected by a doctor but not tested and 759 (8.8%) believed they had COVID-19 due to their own suspicions. Table 4 summarises the responses to this question by cohort structure. Data taken from pregnancy questionnaires for G0 and from most recent questionnaire for G1 where available. 3 Data taken from pregnancy questionnaires for all. 4 This sample size is lower than the total number of G1's who returned a questionnaire (n = 4,370) as data for four triplet/quadruplet pregnancies have been coded as missing in the release dataset for confidentiality reasons. BMI, body mass index; BP, blood pressure; sd, standard deviation. As with the previous questionnaires, we applied the algorithm derived by Menni and colleagues 19 to predict 'probable infection' using data collected from an app-based symptom tracker 20 . This algorithm uses four symptoms: loss of smell and taste, severe or significant persistent cough, severe fatigue and skipped meals (coded as 1 if present and 0 otherwise), together with age and sex (1 male; 0 female). We had slight differences in wording and thus the algorithm (using the same weightings) applied was as follows: Probable COVID-19 cases were obtained by applying an exp(x)/[1+(exp(x)] transformation and coding values >0.5 as probable cases. We applied this algorithm to our monthly symptom data collected in questionnaire 4 which asked about symptoms experienced from October 2020 until February 2021. The proportion of predicted cases decreased slightly over time, with 1.9% and 2.3% of predicted cases in October and November 2020, respectively, and 1.6-1.8% of predicted cases in December 2020 to February 2021 ( Figure 1 ). These monthly percentages are lower than the peak in March 2020 (4.2%) observed from our first COVID-19 questionnaires 7 . Combining all of the questionnaire 4 data together, 359 of 8,587 (4.2%) of participants were predicted to be COVID-19 cases between October 2020 and February 2021. As with our previous use of this algorithm, we note that these predictions are subject to important assumptions, which we discussed in more detail in our previous data notes 7,8 : 1) the baseline risk of having COVID-19 (intercept term) is the same as in the Menni study population; 2) the slight difference in the wording of symptoms captures the same information as those in the Menni study; and 3) the association of these symptoms with COVID-19 (fixed-effect terms) are the same as in the Menni study population. As these data have been collected repeatedly, we can combine these results across each of the COVID questionnaires. For self-reported COVID-19 status, of those who completed this question for any of the four COVID questionnaires, 499 participants (5.1%) have either had a positive test or a doctor suspected that they had had COVID-19. G1s were more likely to report having had a positive COVID-19 test or doctorsuspected symptoms, compared to the G0 generation (Table 5 ). If we include 'own suspicions' in our case definition of COVID-19 infection, the number of participants who may have had COVID-19 increases to 2,231 (23.0%). Similar analyses based on predicted COVID-19 cases from the Menni algorithm from March 2020 onwards show that 961 (9.9%) were predicted cases. These results are broadly similar -albeit slightly lower -if we restrict our analysis to those who responded to all four COVID questionnaires; by doing so we remove any potential bias due to: i) differences in COVID-19 testing, since widespread testing was not available during the time of the first COVID-19 questionnaire; and ii) the time available to be infected, which could bias results if only including those who responded to the early COVID questionnaires (Table 5) . To assess potential reasons for non-completion of the fourth COVID questionnaire, which could bias comparisons between questionnaire waves, we explored whether various sociodemographic factors were associated with returning the fourth COVID questionnaire, but not any of the previous three (to explore who these 'new' participants were). Results are displayed in Figure 2 . Returning only the fourth questionnaire was strongly associated with age/generation such that younger/G1 participants were much more likely to have only returned Q4 (most likely a result of the different G1 data collection strategy, which included mailing paper invitations to participants, and hence invited additional G1 participants not invited to the previous COVID-19 questionnaires). After adjusting for generation (G0 vs G1), response to only the fourth COVID questionnaire was associated with several factors: male participants, those with lower educational attainment (a proxy for socioeconomic position), and participants with an ethnicity other than white were more likely to only have fourth COVID questionnaire data. Participants who only returned the fourth COVID questionnaire were also more likely to self-report that they either had a positive COVID-19 test or had their own suspicions they had had COVID-19, relative to a reference group of 'not had COVID-19' (no difference for 'doctor suspected COVID-19 infection' was reported). These participants were also more likely to be a predicted COVID-19 case, based on their reported symptoms, using the Menni algorithm 19 . Few differences in physical or mental health were noted, although participants who only completed the fourth COVID questionnaire had higher systolic blood pressure, and a somewhat elevated risk of potential depression. This data collection has a number of strengths. Firstly, the timelines within which the collection occurred allows comparisons to be made between the stringent mitigation measures early on in the pandemic and later easing of lockdown measures; users should ensure they are aware of completion dates for this dataset, as England went into second national lockdown between 5 th November and 2 nd December 2020, and a third national lockdown again on January 6 th 2021 (with local tiered restrictions between these dates). Secondly, the availability of repeat data obtained over time throughout the pandemic, along with pre-pandemic baseline measures, allows assessment of longitudinal changes in health and wellbeing. For example, we have already been able to demonstrate the short-term impact the pandemic has had on mental health during the first lockdown in April-June 2020 1,21 . This is the fourth ALSPAC COVID-19 questionnaire, meaning there is a wealth of longitudinal data to draw upon to explore the impact of the COVID-19 pandemic and its management on population health. These questionnaires are also supplemented by serology testing 9 (with further testing currently being conducted [as of April/May 2021]), linking to Public Health England Pillar testing records 11 , and targeted data collections (such as a long COVID-specific questionnaire currently in development). Thirdly, the alignment of measures with other UK studies provides potential for cross-cohort comparisons. This was achieved through the set of core questions developed by the Wellcome coordinated group and has already facilitated a co-ordinated analysis of mental health measures in ALSPAC and Generation Scotland 1 . ALSPAC is currently working on several cross-cohort Finally, we achieved an excellent response rate despite the lack of incentive in G0 and calling on our participants to take part in data collection for the fourth time in less than a year. As we have described previously, it should be noted that our online-only strategy will likely have affected response rates from our G0 mothers who historically have tended to use paper questionnaires more than other sub-groups when completing questionnaires and for whom we are least likely to hold a current email address. However, the pandemic has led to a number of participants reaching out and getting in touch to provide these details, and indeed to re-engage with the study having dropped out previously. In addition, members of the study team have been contacting participants to ensure we have up to date email addresses. Throughout the pandemic, ALSPAC has also conducted outreach work to encourage participation of 'disengaged' study participants. A key limitation of this data collection is that, in some cases, the data recorded is potentially identifiable. As with previous COVID-19 questionnaires, we have gone through each individual variable and made decisions as to whether we need to combine categories. This has only been carried out where we believe the data provides a high risk of potential disclosure (as detailed in the supplementary documentation file). Another limitation is that the response rate was non-random with regard to age, sex and socio-economic status; this could potentially introduce bias into analyses 22 . We acknowledge there is a risk for people with severe COVID-19 to be under-represented in the study if they were too unwell to respond to questionnaires. The reverse may also be true, however; participants who have had COVID-19 (or believe that they have), may be more engaged with this research given their personal experience. For instance, in the first serology test (COVID questionnaire 3), participants who previously self-reported that they had had COVID-19 were more likely to participate in this research 9 . We will be investigating this further using linkage to health records. Finally, we acknowledge that the predicted case status will contain measurement error. We will address this by providing more accurate measures of COVID-19 status in the future using a combination of serological testing and data linkage 11 . In summary, this ALSPAC data obtained during the first year of the COVID-19 pandemic will enable researchers to capture changes in many aspects of people's lives as we optimistically consider the pandemic abating and national mitigation strategies continuing to reduce. These data are available for researchers as described below. Completion of the questionnaire was optional and choosing to complete the questionnaire is considered informed consent for the questionnaire. Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time. Study participants have the right to withdraw their consent for elements of the study or from the study entirely at any time. Full details of the ALSPAC consent procedures are available on the study website. Underlying data ALSPAC data access is through a system of managed open access. The steps below highlight how to apply for access to the data included in this data note and all other ALSPAC data: 1. Please read the ALSPAC access policy which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. 2. You may also find it useful to browse our fully searchable research proposals database, which lists all research projects that have been approved since April 2011. 3. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. Please note that a standard COVID-19 dataset will be made available at no charge (see description below); however, costs for required paperwork and any bespoke datasets required additional variables will apply. Data from the fourth ALSPAC COVID-19 questionnaire is available in two ways. 1. A freely available standard set of data containing all participants together with key sociodemographic variables (where available) is available on request (see data availability section). This dataset also includes data obtained from the previous COVID questionnaires. Subject to the relevant paperwork being completed (costs may apply to cover administration) this dataset will be made freely available to any bona fide researcher requesting it. Variable names will follow the format covid4_xxxx where xxxx is a four-digit number. A full list of variables released is available as Extended data 18 . Frequencies of variable and details of any coding/editing decisions and derived variables are also available in the data dictionary as Extended data 18 . 2. Formal release files have been created for G0 mothers, G0 fathers and G1 participants in the usual way and now form part of the ALSPAC resource. These datasets (or sections therein) can be requested in the usual way. Variable names will replicate those in 1) above but as each variable in ALSPAC is uniquely defined we have added markers to denote the source of the variable. For example, in the fourth COVID-19 questionnaire dataset, the age of the participant at completion (in years) is denoted by covid4_9650. In the G0 mother's dataset this will be denoted by covid4m_9650, for G0 fathers/partner this will be covid4p_9650 and for the G1 generation it will be covid4yp_9650. Frequencies for all variables for each participant group are available in the data dictionary in the usual way. Text data and other potentially disclosive information will not be released until they have been coded appropriately. Table 6 describes the data that is withheld at the time of first release. Data will be incorporated back into both file sets as they become available. We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. Open Peer Review infection status, given that many of the participants could have obtained the vaccines. Should the vaccine information be included in the questionnaires? Perhaps the authors could consider adding the major challenges and a future perspective in the context of COVID-19 pandemic. Is the rationale for creating the dataset(s) clearly described? Yes Are the protocols appropriate and is the work technically sound? Yes Are the datasets clearly presented in a useable and accessible format? Yes Mental health before and during the COVID-19 pandemic in two longitudinal UK population cohorts PubMed Abstract | Publisher Full Text | Free Full Text Mental health inequalities in healthcare, economic, and housing disruption during COVID-19: an investigation in 12 longitudinal studies Cohort profile: The 'Children of the 90s'--The index offspring of the avon longitudinal study of parents and children PubMed Abstract | Publisher Full Text | Free Full Text Cohort profile: The avon longitudinal study of parents and children: ALSPAC mothers cohort PubMed Abstract | Publisher Full Text | Free Full Text The Avon Longitudinal Study of Parents and Children (ALSPAC): an update on the enrolled sample of index children in 2019 PubMed Abstract | Publisher Full Text | Free Full Text The second generation of the avon longitudinal study of parents and children (ALSPAC-G2): A cohort profile The Avon Longitudinal Study of Parents and Children -A resource for COVID-19 research: Questionnaire data capture The Avon Longitudinal Study of Parents and Children -A resource for COVID-19 research: Questionnaire data capture The Avon Longitudinal Study of Parents and Children -A resource for COVID-19 research: Home-based antibody testing results The Avon Longitudinal Study of Parents and Children -A resource for COVID-19 research: Generation 2 questionnaire data capture The Avon Longitudinal Study of Parents and Children -a resource for COVID-19 research: approaches to the identification of cases Research electronic data capture (REDCap)--A metadata-driven methodology and workflow process for providing translational research informatics support PubMed Abstract | Publisher Full Text | Free Full Text Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents A brief measure for assessing generalized anxiety disorder: The GAD-7 The Warwick-Edinburgh mental wellbeing scale (WEMWBS): Development and UK validation The obsessive-compulsive inventory: Development and validation of a short version A Global Measure of Perceived Stress ALSPAC COVID-19 Data collections Real-time tracking of self-reported symptoms to predict potential COVID-19 Rapid implementation of mobile technology for real-time epidemiology of COVID-19 PubMed Abstract | Publisher Full Text | Free Full Text Longitudinal evidence for persistent anxiety in young adults through COVID-19 restrictions Publisher Full Text Collider bias undermines our understanding of COVID-19 disease risk and severity The authors described the content and the implementation of the 4 th survey during COVID-19 pandemic, and also showed the response rate and the COVID-19 status according to different types of participants. This longitudinal study with repeated investigations may help to assess the impact of COVID-19, either from the disease per se or the public management measures, on the changes in many aspects for participants of different generations. This article has a very clear and comprehensive description of the study design.I have some minor inquiries and suggestions.The authors collected data from G0 only via online questionnaire, whereas from G1 via both online and post in the 4 th survey, which was also different from the previous COVID-19 surveys. We noticed that the authors also have mentioned a larger sample of G1 participants in the 4 th survey may explain the change of the G1 response rate as compared to previous surveys. The authors should further discuss the potential influence of this issue. Please provide references when comparing the response rates between different surveys. In addition, it was not quite clear what data were collected from the previous three surveys. Therefore, a table to summarize all variables or data in the four surveys might be helpful. I am not quite convinced to use the variable "predicted COVID-19 cases", particularly if this was the outcome variable. Sensitivity and specificity of the variable should be provided. I am not sure whether the authors could use serological testing in the future to know the 4. No competing interests were disclosed. We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Reviewer Report 08 September 2021 https://doi.org/10.21956/wellcomeopenres.18704.r45565 © 2021 Hope H. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Centre for Women's Mental Health, School of Health Sciences, University of Manchester, Oxford Rd, Manchester, UK This report describes the fourth COVID survey issued to the ALSPAC cohort. The data note describes the survey, the COVID related information captured, and the survey respondents.Overall this is well written and the limitations of these data are addressed, particularly with reference to determination of COVID cases.My only comment would be that I found it confusing that this is the 4th COVID questionnaire. And that some respondents completed up to 3 previously in the past year.Based on the methods it appears that responses may overlap -and i wonder if there is a plan to derive variable across the four surveys.A sentence/table describing when the four COVID surveys were conducted and to what extent (if at all) they overlap, temporally, would be helpful. Are the protocols appropriate and is the work technically sound? Yes Competing Interests: No competing interests were disclosed.Reviewer Expertise: Epidemiology, behavioural science I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.