Dedicated to the work of the register-based large-scale national population study to monitor COVID-19 vaccination effectiveness and safety (RECOVAC) project.

The National Social Life, Health and Aging Project (NSHAP) is a population-based study of health and social factors on a national scale, aiming to understand the well-being of older, community-dwelling Americans by examining the interactions among physical health, illness, medication use, cognitive function, emotional health, sensory function, health behaviors, and social connectedness. It is designed to provide health providers, policy makers, and individuals with useful information and insights into these factors, particularly on social and intimate relationships. The National Opinion Research Center (NORC), along with Principal Investigators at the University of Chicago, conducted more than 3,000 interviews during 2005 and 2006 with a nationally representative sample of adults aged 57 to 85. Face-to-face interviews and biomeasure collection took place in respondents' homes. Round 3 was conducted from September 2015 through November 2016, where 2,409 surviving Round 2 respondents were re-interviewed, and a New Cohort consisting of adults born between 1948 and 1965 together with their spouses or co-resident partners was added. All together, 4,777 respondents were interviewed in Round 3. The following files constitute Round 3: Core Data, Social Networks Data, Disposition of Returning Respondent Partner Data, and Proxy Data. Included in the Core files (Datasets 1 and 2) are demographic characteristics, such as gender, age, education, race, and ethnicity. Other topics covered respondents' social networks, social and cultural activity, physical and mental health including cognition, well-being, illness, history of sexual and intimate partnerships and patient-physician communication, in addition to bereavement items. In addition data on a panel of biomeasures including, weight, waist circumference, height, and blood pressure was collected. The Social Networks (Datasets 3 and 4) files detail respondents' current relationship status with each person identified on the network roster. The Disposition of Returning Respondent Partner (Datasets 5 and 6) files detail information derived from Section 6A items regarding the partner from Rounds 1 and 2 within the questionnaire. This provides a complete history for respondent partners across both rounds. The Proxy (Datasets 7 and 8) files contain final health data for Round 1 and Round 2 respondents who could not participate in NSHAP due to disability or death. The COVID-19 sub-study, administered to NSHAP R3 respondents in the Fall of 2020, was a brief self-report questionnaire that probed how the coronavirus pandemic changed older adults' lives. The COVID-19 sub-study questionnaire was limited to assessing specific domains in which respondents may have been affected by the coronavirus pandemic, including: (1) COVID experiences, (2) health and health care, (3) job and finances, (4) social support, (5) marital status and relationship quality, (6) social activity and engagement, (7) living arrangements, (8) household composition and size, (9) mental health, (10) elder mistreatment, (11) health behaviors, and (12) positive impacts of the coronavirus pandemic. Questions about engagement in racial justice issues since the death of George Floyd in police custody were also added to facilitate analysis of the independent and compounding effects of both the COVID-19 pandemic and reckoning with longstanding racial injustice in America.

To control the spread of COVID-19 in India and to aid the efforts of the Ministry of Health and Family Welfare (MOHFW), the Population Council and other non-governmental organizations are conducting research to assess residents’ ability to follow sanitation and social distancing precautions under a countrywide lockdown. The Population Council COVID-19 study team is implementing rapid phone-based surveys to collect information on knowledge, attitudes and practices, as well as needs, among 2,041 young people (ages 19–23 years) and/or an adult household member, sampled from an existing prospective cohort study with a total sample size of 20,594 in Bihar (n=10,433) and Uttar Pradesh (n=10,161). Baseline was conducted from April 3–22; subsequent iterations of the survey are planned to be conducted on a monthly basis. Baseline findings on awareness of COVID-19 symptoms, perceived risk, awareness of and ability to carry out preventive behaviors, misconceptions, and fears will inform the development of government and other stakeholders’ interventions and/or strategies. We are committed to openly sharing the latest versions of the study description, questionnaires, de-identified or aggregated datasets, and preliminary results. Data and findings can also be shared with partners working on the COVID-19 response.

Characteristics of study participants enrolled in the Zurich SARS-CoV-2 cohort study.

In the context of COVID-19, RAND and the Robert Wood Johnson Foundation partnered again to build from the National Survey of Health Attitudes to implement a longitudinal survey to understand how these health views and values have been affected by the experience of the pandemic, with particular focus on populations deemed vulnerable or underserved, including people of color and those from low- to moderate-income backgrounds. The questions in this COVID-19 survey focused specifically on experiences related to the pandemic (e.g., financial, physical, emotional), how respondents viewed the disproportionate impacts of the pandemic, whether and how respondents' views and priorities regarding health actions and investments are changing (including the roles of government and the private sector), and how general values about such issues as freedom and racism may be related to pandemic views and response expectations. This study includes the results for Wave 4 for the general population. Demographic information includes sex, marital status, household size, race and ethnicity, family income, employment status, age, and census region.

A. SUMMARY This archived dataset includes data for population characteristics that are no longer being reported publicly. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.

B. HOW THE DATASET IS CREATED Data on the population characteristics of COVID-19 cases are from:  * Case interviews  * Laboratories  * Medical providers    These multiple streams of data are merged, deduplicated, and undergo data verification processes.  

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases. * The population estimates for the "Other" or “Multi-racial” groups should be considered with caution. The Census definition is likely not exactly aligned with how the City collects this data. For that reason, we do not recommend calculating population rates for these groups.

Gender * The City collects information on gender identity using these guidelines.

Skilled Nursing Facility (SNF) occupancy * A Skilled Nursing Facility (SNF) is a type of long-term care facility that provides care to individuals, generally in their 60s and older, who need functional assistance in their daily lives.  * This dataset includes data for COVID-19 cases reported in Skilled Nursing Facilities (SNFs) through 12/31/2022, archived on 1/5/2023. These data were identified where “Characteristic_Type” = ‘Skilled Nursing Facility Occupancy’.

Sexual orientation * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to the California Department of Public Health, Virtual Assistant information gathering beginning December 2021. The Virtual Assistant is only sent to adults who are 18+ years old. https://www.sfdph.org/dph/files/PoliciesProcedures/COM9_SexualOrientationGuidelines.pdf">Learn more about our data collection guidelines pertaining to sexual orientation.

Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

Homelessness Persons are identified as homeless based on several data sources: * self-reported living situation * the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures. These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions.

Single Room Occupancy (SRO) tenancy * SRO buildings are defined by the San Francisco Housing Code as having six or more "residential guest rooms" which may be attached to shared bathrooms, kitchens, and living spaces. * The details of a person's living arrangements are verified during case interviews.

Transmission Type * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown.

C. UPDATE PROCESS This dataset has been archived and will no longer update as of 9/11/2023.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).

This dataset includes many different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cases on each date.

New cases are the count of cases within that characteristic group where the positive tests were collected on that specific specimen collection date. Cumulative cases are the running total of all San Francisco cases in that characteristic group up to the specimen collection date listed.

This data may not be immediately available for recently reported cases. Data updates as more information becomes available.

To explore data on the total number of cases, use the ARCHIVED: COVID-19 Cases Over Time dataset.

E. CHANGE LOG

• 9/11/2023 - data on COVID-19 cases by population characteristics over time are no longer being updated. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.
• 6/6/2023 - data on cases by transmission type have been removed. See section ARCHIVED DATA for more detail.
• 5/16/2023 - data on cases by sexual orientation, comorbidities, homelessness, and single room occupancy have been removed. See section ARCHIVED DATA for more detail.
• 4/6/2023 - the State implemented system updates to improve the integrity of historical data.
• 2/21/2023 - system updates to improve reliability and accuracy of cases data were implemented.
• 1/31/2023 - updated “population_estimate” column to reflect the 2020 Census Bureau American Community Survey (ACS) San Francisco Population estimates.
• 1/5/2023 - data on SNF cases removed. See section ARCHIVED DATA for more detail.
• 3/23/2022 - ‘Native American’ changed to ‘American Indian or Alaska Native’ to align with the census.
• 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.
• 7/15/2022 - reinfections added to cases dataset. See section SUMMARY for more information on how reinfections are identified.

COVID-19 related characteristics of participants (N = 811).

Non-random convenience sampling using online platform were used to collect 10,067 data from a representative sample of 64 districts of Bangladesh. The survey questionnaire was delivered via social media platform (i.e., Facebook, What’s app, Twitter, Snapchat etc.), email and via other communicable means. The dataset comprises (i) socio-demographic characteristics (e.g., gender, age group, educational status, occupational status, data discipline, residence area, marital status, comorbidities, current health condition, smoking status, alcohol-drinking status, frequency of social media use, etc.); (ii) sources from where participants get information regarding COVID-19 (e.g., social media, YouTube, newspaper, television, health-related website, and other sources) ; (iii); participants’ knowledge concerning COVID-19; (iv) participants’ behavior in preventing COVID-19; (v) lockdown-related questions ; (vi) assessment of fear of COVID-19 among participants; (vii) assessment of severity of insomnia among participants; (viii) assessment of depression among participants; and (ix) suicidal ideation in relation to COVID-19 among participants .

Coping with COVID-19 Pandemic: A Population-Based Study in Bangladesh

Background: As of October 2020, COVID-19 has caused 1,000,000 deaths worldwide. However, large-scale studies of COVID-19 mortality and new-onset comorbidity compared to individuals tested negative for COVID-19 and individuals tested for influenza A/B are lacking. We investigated COVID-19 30-day mortality and new-onset comorbidity compared to individuals with negative COVID-19 test results and individuals tested for influenza A/B.Methods and findings: This population-based cohort study utilized electronic health records covering roughly half (n = 2,647,229) of Denmark's population, with nationwide linkage of microbiology test results and death records. All individuals ≥18 years tested for COVID-19 and individuals tested for influenza A/B were followed from 11/2017 to 06/2020. Main outcome was 30-day mortality after a test for either COVID-19 or influenza. Secondary outcomes were major comorbidity diagnoses 30-days after the test for either COVID-19 or influenza A/B. In total, 224,639 individuals were tested for COVID-19. To enhance comparability, we stratified the population for in- and outpatient status at the time of testing. Among inpatients positive for COVID-19, 356 of 1,657 (21%) died within 30 days, which was a 3.0 to 3.1-fold increased 30-day mortality rate, when compared to influenza and COVID-19-negative inpatients (all p < 0.001). For outpatients, 128 of 6,263 (2%) COVID-19-positive patients died within 30 days, which was a 5.5 to 6.9-fold increased mortality rate compared to individuals tested negative for COVID-19 or individuals tested positive or negative for influenza, respectively (all p < 0.001). Compared to hospitalized patients with influenza A/B, new-onset ischemic stroke, diabetes and nephropathy occurred more frequently in inpatients with COVID-19 (all p < 0.05).Conclusions: In this population-based study comparing COVID-19 positive with COVID-19 negative individuals and individuals tested for influenza, COVID-19 was associated with increased rates of major systemic and vascular comorbidity and substantially higher mortality. Results should be interpreted with caution because of differences in test strategies for COVID-19 and influenza, use of aggregated data, the limited 30-day follow-up and the possibility for changing mortality rates as the pandemic unfolds. However, the true COVID-19 mortality may even be higher than the stated 3.0 to 5.5-fold increase, owing to more extensive testing for COVID-19.

Association between coping and demographic characteristics.

This was a cross-sectional nationwide survey of adults in the US conducted between April 24 and May 13, 2020. The survey targeted a representative sample of approximately 5,000 respondents. The rate of COVID-19 cases and testing, most frequently reported symptoms, symptom severity, treatment received, impact of COVID-19 on mental and physical health, and factors predictive of testing positive were assessed.

Methods Data was collected through an on-line cross-sectional survey of adults (18 years or older) in the US. The survey was conducted in accordance with Acumen Health Research Institute's (AHRI) established SOPs. A random stratified sampling framework ensured a community-based sample with a demographic composition representative of the US adult population by region, gender, age, and race, according to the US Census (US Census American Community Survey 5-year estimate, 2011-2015). To participate in the study, respondents were required to be 18 years old or older, reside in the United States, and confirm their voluntarily agreement to participate (participants were informed they could leave the survey at any time). The survey was open to the general population and not restricted to patients hospitalized with COVID-19. Participants were recruited through AHRI’s online research panels. Analysis was carried out with SPSS v27.0.1.0.

Characteristics of patients pre COVID-19 (March 16-September 23, 2019) compared to post COVID-19 public health measures (March 16-September 23, 2020).

Overview of the study population, number of COVID-19 cases, and person-days of absences.

Further information is available from the Natsal website.

Natsal-COVID:

The COVID-19 pandemic disrupted many aspects of sexual lifestyles, triggering an urgent need for population-level data on sexual behaviour, relationships, and service use at a time when gold-standard in-person, household-based surveys with probability sampling were not feasible. The Natsal-COVID study was designed to understand the impact of COVID-19 on the nation's sexual and reproductive health (SRH) and assessed the sample representativeness. The study was funded by the Chief Scientist Office, the Wellcome Trust (with contributions from ESRC and NIHR), the UCL Covid-19 Rapid Response Fund and the Medical Research Council. The Natsal-COVID Wave 1 survey and qualitative follow-up interviews were conducted in 2020. The Wave 2 survey was designed to capture one-year prevalence estimates for key SRH outcomes and measure changes over the first year of the pandemic.

Methods:

• The Natsal-COVID Wave 1 survey was conducted four months after the announcement of Britain's first national lockdown (23 March 2020), between 29 July and 10 August 2020. Wave 1 was an online web-panel survey administered by survey research company, Ipsos MORI. Eligible participants were resident in Britain, aged 18-59 years, and the sample included a boost of those aged 18-29. Questions covered participants' sexual behaviour, relationships, and SRH service use. Quotas and weighting were used to achieve a quasi-representative sample of the British general population. Participants meeting the criteria of interest and agreeing to recontact were selected for qualitative follow-up interviews. Comparisons were made with contemporaneous national probability surveys and Natsal-3 (2010-2012) (see SN 7799) to understand bias.
• Wave 2 was conducted March-April 2021, approximately one year after the start of Britain’s first national lockdown. Data were collected using an online web-panel survey administered by Ipsos. The sample comprised a longitudinal sample of Wave 1 participants who had agreed to re-contact plus a sample of participants residing in Britain, aged 18-59, including a boost sample comprising people aged 18-29. Questions covered reproductive health, relationships, sexual behaviour and SRH service use. Quotas and weighting were used to achieve a quasi-representative sample of the British population.

Results:

• Wave 1: 6,654 participants completed the survey and 45 completed follow-up interviews. The weighted Natsal-COVID sample was similar to the general population in terms of gender, age, ethnicity, rurality, and, among sexually-active participants, the number of sexual partners in the past year. However, the sample was more educated, contained more sexually-inexperienced people, and included more people in poorer health.
• Wave 2: A total of 6,658 individuals completed the survey. In terms of gender, age, ethnicity, and rurality, the weighted Natsal-COVID Wave 2 sample was like the general population. Participants were less likely to be married or to report being in good health than the general population. The longitudinal sample (n=2,098) was broadly similar to participants who only took part in Wave 1 but were older. Among the sexually active, longitudinal participants were less likely to report multiple sexual partners or a new sexual partner in the past year compared to those who only took part in Wave 1.

Conclusions:

• Wave 1 rapidly collected quasi-representative population data to enable evaluation of the early population-level impact of COVID-19 and lockdown measures on SRH in Britain and inform policy. Although sampling was less representative than the decennial Natsal surveys, Natsal-COVID will complement national surveillance data and Natsal-4 (planned for 2022).
• Wave 2 collected longitudinal, quasi-representative population data to enable evaluation of the population-level impact of COVID-19 on SRH and to inform policy.

Latest edition information

For the second edition (January 2023), data and documentation for Wave 2 were added to the study.

The impact of the coronavirus 2019 (COVID-19) pandemic on different countries and populations is well documented in quantitative studies, with some studies showing stable mental health symptoms and others showing fluctuating symptoms. However, the reasons behind why some symptoms are stable and others change are under-explored, which in turn makes identifying the types of support needed by participants themselves challenging. To address these gaps, this study thematically analysed 925 qualitative responses from five open-ended responses collected in the UCL-Penn Global COVID Study between 17 April to 31 July 2021 (wave 3). Three key themes comprised of 13 codes were reported by participants across countries and ages regarding the impact of COVID-19 on their health, both mental and physical, and livelihoods. These include: 1) Outlook on self/life, 2) Self-improvement, and 3) Loved ones (friends and family). In terms of support, while 2.91% did not require additional support, 91% wanted support beyond financial. Other unexpected new themes were also discussed regarding vulnerable populations suffering disproportionately. The pandemic has brought into sharp focus various changes in people’s mental health, physical health, and relationships. Greater policy considerations should be given to supporting citizens’ continued access to mental health when considering pandemic recovery.

The study population was all residents of Qazvin province who lived in cities (Qazvin-Takestan-Avaj-Alborz-Buin Zahra- Abyek) and villages of this province.

A population-based COVID-19 cohort was set up in the Netherlands to gain comprehensive insight in the short- and long-term effects of COVID-19 in the general population. A subset of this data, deposited and described here, was used for the aims to describe the methodology and infrastructure used to recruit individuals with COVID-19 and the representativeness of the population-based cohort and to characterize the population by description of their symptoms and health care usage during the acute COVID-19 phase.The starting point of the set-up of the cohort was to recruit participants in routinely recorded, general practice electronic health records (EHR) data, which are sent to the Netherlands Institute for Health Services Research Primary Care Database (Nivel-PCD) on a weekly basis. Patients registered with COVID-19 were flagged in the Nivel-PCD based on their COVID-19 diagnoses. Flagged patients were invited for participation by their general practitioner via a trusted third party. Participating patients received a series of four questionnaires over the duration of one year allowing for a combination of data from patient reported outcomes and EHRs.The Nivel Corona Cohort consists of 442 participants and here a subset of the data from the first questionnaire is shown. The Nivel Corona Cohort is population-based, containing a complete image of severity of symptoms from patients with none or hardly any symptoms to those who were hospitalized due to the COVID-19. The five most prevalent symptoms during the acute COVID-19 phase were fatigue (90.5%), reduced condition (88.2%), coughing/sneezing/stuffy nose (79.3%), headache (75.4%), and myalgia (66.7%). The population-based Nivel Corona Cohort provides ample opportunities for future studies to gain comprehensive insight in the short- and long-term effects of COVID-19 by combining patients’ perspectives and clinical parameters via the EHRs within a long-term follow-up of the cohort.

NOTE: As of 2/16/2023, this page is no longer being updated. This table shows the number and percent of people that have initiated COVID-19 vaccination and are fully vaccinated by race / ethnicity and town. It includes people of all ages. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. A person who has received at least one dose of any vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if they have completed a primary series by receiving 2 doses of the Pfizer, Novavax or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. Race and ethnicity data may be self-reported or taken from an existing electronic health care record. Reported race and ethnicity information is used to create a single race/ethnicity variable. People with Hispanic ethnicity are classified as Hispanic regardless of reported race. People with a missing ethnicity are classified as non-Hispanic. People with more than one race are classified as multiple race. A vaccine coverage percentage cannot be calculated for people classified as NH Other race or NH Unknown race since there are not population size estimates for these groups. Data quality assurance activities suggest that NH Other may represent a missing value. Vaccine coverage estimates in specific race/ethnicity groups may be underestimated as result of the exclusion of records classified as NH Unknown Race or NH Other Race. Town of residence is verified by geocoding the reported address and then mapping it a town using municipal boundaries. If an address cannot be geocoded, the reported town is used. Town-level coverage estimates have been capped at 100%. Observed coverage may be greater than 100% for multiple reasons, including census denominator data not including all individuals that currently reside in the town (e.g., part time residents, change in population size since the census) or potential data reporting errors. The population denominators for these town- and age-specific coverage estimates are based on 2014 census estimates. This is the most recent year for which reliable town- and age-specific estimates are available. (https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Town-Population-with-Demographics). Changes in the size and composition of the population between 2014 and 2021 may results in inaccuracy in vaccine coverage estimates. For example, the size of the Hispanic population may be underestimated in a town given the reported increase in the size of the Hispanic population between the 2010 and 2020 censuses resulting in inflated vaccine coverage estimates. The 2014 census data are grouped in 5-year age bands. For vaccine coverage age groupings not consistent with a standard 5-year age band, each age was assumed to be 20% of the total within a 5-year age band. However, given the large deviation from this assumption for Mansfield because of the presence of the University of Connecticut, the age distribution observed in the 2010 census for the age bands 15 to 19 and 20 to 24 was used to estimate the population denominators. This table does not included doses administered to CT residents by out-of-state providers or by some Federal entities (including Department of Defense, Department of Correction, Department of Veteran’s Affairs, Indian Health Service) because they are not yet reported to CT WiZ (the CT immunization Information System). It is expected that these data will be added in the future. Caution should be used when interpreting coverage estimates for towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while study

Full edition for scientific use. The Center for Social Health Innovation (CSHI) has conducted an online two-wave panel survey to investigate potential social consequences of the COVID-19 epidemic. In the first wave, 1024 Austrian individuals were surveyed. The second wave was conducted in June 2020. The study contains indicators on people’s information habits, their attitudes toward COVID-19 policies, their knowledge, and the fears related to the crisis. About the data. The data collection was implemented by Dynata, a private market research company. We used predefined quotes based on Statistics Austria population data. The composition of the sample largely represents the population structure of Austria. Even though the composition is similar to the Austrian population, this is not a random sample, thus we cannot make precise predictions about population distributions. The survey was conducted between April 1 and April 7, 2020. Response rate. The survey received 1800 klicks and 1725 individuals started the survey. Of those 1725 individuals, 33 individuals did not agree to participate after reading the informed consent, 555 were screened out due to full quotas, and 113 individuals did not complete the survey for other reasons. A total of 1024 individuals completed the survey. Wave 2. The second wave was collected between June 2 and June 10. Invitations were sent out to wave 1 participants only. The second wave received 769 clicks and 632 completed the survey. Of those, 320 were female, 312 were male. 105 had compulsory school degrees only, 305 went to vocational school, 115 had high school degrees, and 104 a college degree. Mean age was 49.30 (SD = 17.53).