The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).

Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules.

The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain.

From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers.

In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093).

From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable.

The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandlifeexpectancies/methodologies/opinionsandlifestylesurveyqmi">OPN Quality and Methodology Information webpage.

ONS Opinions and Lifestyle Survey, 2019-2025: Secure Access

The aim of the COVID-19 Module within this study was to help understand the impact of the coronavirus (COVID-19) pandemic on people, households and communities in Great Britain. It was a weekly survey initiated in March 2020, and since August 2021, as COVID-19 restrictions were lifted, the survey has moved to fortnightly data collection, sampling around 5,000 households in each survey wave. The study allows the breakdown of impacts by at-risk age, gender and underlying health condition. The samples are randomly selected from those that had previously completed other ONS surveys (e.g., Labour Market Survey, Annual Population Survey). From each household, one adult is randomly selected but with unequal probability: younger people are given a higher selection probability than older people because of under-estimation in the samples available for the survey.

The study also includes data for the Internet Access Module from 2019 onwards. Data from this module for previous years are available as End User Licence studies within GN 33441. Also included are data from the Winter Lifestyle Survey for January and February 2023.

Latest edition information

For the twelfth edition (November 2025), data and documentation for the main OPN survey for waves to EC to FD-FE (January 2024 - February 2025) have been added. Data and documentation for the Childcare Options Module (July to November 2019 and January - February 2020) have also been added.

The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.

LFS response to COVID-19

From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.

Occupation data for 2021 and 2022 data files

The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

2024 Reweighting

In February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.

End User Licence and Secure Access QLFS data

Two versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).

The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• finer detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address
• other additional detailed variables may also be included.

The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Latest edition information

For the fourth edition (May 2025), the variables DIFFHRS20 and YLESS20 were replaced with new versions, with previously missing imputed values for 'IOUTCOME=6' cases added.

In 2024, around 1,185 petitions were filed with the United States National Injury Compensation Program (VICP) seeking compensation for injury or death caused by vaccines. However, just because a petition was filed seeking compensation for injury or death due to a vaccination does not mean that compensation was awarded. Over half of all such petitions filed in the U.S. since 1988 have been dismissed, and in 60 percent of cases in which compensation was awarded it was still not determined whether the alleged vaccine caused the alleged injury. The impact of vaccinations Vaccinations in the United States have had a significant impact on infectious diseases. For example, as of 2017, there are only about 120 new cases of measles per year, compared to over half a million annual cases before the use of vaccination. Vaccinations in the U.S. have also greatly decreased the number of annual cases of hepatitis A and B, rubella, and tetanus. COVID-19 vaccination hesitancy Vaccine hesitancy is a persistent issue in the United States. The issue became especially pertinent during the COVID-19 pandemic in which many people in the United States expressed reluctance to getting a COVID-19 vaccination. In December 2020, 59 percent of adults in the United States who stated they would definitely not or probably not get a COVID-19 vaccine said so because they were worried about possible side effects, while 55 percent said they probably wouldn’t get a COVID-19 vaccination because they do not trust the government to make sure the vaccine is safe and effective. Shockingly, one survey found that even 29 percent of health care workers stated they would probably or definitely not get a COVID-19 vaccine.

Understanding Society, the UK Household Longitudinal Study, is a longitudinal survey of the members of approximately 40,000 households (at Wave 1) in the United Kingdom. The overall purpose of Understanding Society is to provide high quality longitudinal data about subjects such as health, work, education, income, family, and social life to help understand the long term effects of social and economic change, as well as policy interventions designed to impact upon the general well-being of the UK population. The Understanding Society main survey sample consists of a large General Population Sample plus three other components: the Ethnic Minority Boost Sample, the former British Household Panel Survey sample and the Immigrant and Ethnic Minority Boost Sample.

India SPF: Govt Securities Yield: 10 Years: Next Fiscal Year: Mean data was reported at 6.400 % in Apr 2025. This records a decrease from the previous number of 6.500 % for Feb 2025. India SPF: Govt Securities Yield: 10 Years: Next Fiscal Year: Mean data is updated monthly, averaging 6.800 % from Jun 2014 (Median) to Apr 2025, with 66 observations. The data reached an all-time high of 8.100 % in Jun 2014 and a record low of 6.100 % in Dec 2020. India SPF: Govt Securities Yield: 10 Years: Next Fiscal Year: Mean data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.SH014: Survey of Professional Forecasters (SPF): Reserve Bank of India: Annual Forecasts: Government Securities Yield: 10 Years: End Period. [COVID-19-IMPACT]

As of September 2025, 30 percent of people in Great Britain thought that Keir Starmer was better for the job of Prime Minister than the Leader of the Opposition, Kemi Badenoch, with 21 percent believing she would be better for the job. Although Starmer is currently seen as better suited for the job as Prime Minister, the approval ratings for his government have declined considerably since winning the election, sinking to a low of -61 percent in September 2025. Sunak vs. Starmer Shortly after succeeding Truss as Prime Minister, Rishi Sunak was seen by 30 percent of people as the best person for the job, just four percentage points behind Keir Starmer. Twenty months later, however, on the eve of the 2024 general election, just 19 percent of people thought Sunak was the best choice, compared with 35 percent for Starmer. Despite pledging to address the main issues facing the country at the start of 2023, Sunak struggled to convince voters. Although inflation peaked in 2022, and declined throughout 2023, the cost of living crisis afflicting people in the UK lingered on, while progress on improving the NHS proved elusive. The Conservatives suffered a clear defeat in the 2024 election, winning just 121 seats, compared with 365 in 2019. Scandals and mini budgets After becoming Prime Minister in late 2019, a series of controversies harmed the popularity of Boris Johnson among voters, and eventually forced his resignation. The Partygate scandal, which revealed that senior government officials held parties at Downing Street, during the COVID-19 lockdown, was the most severe. When the issue came to a head in Summer 2022, Johnson survived the initial political backlash, including an attempted vote of no-confidence in his leadership, but he was forced to resign his position after a wave of senior ministers resigned from his government between July 5-7, 2022. Although Liz Truss won the leadership contest that followed the resignation of Johnson, her time in office was by far the shortest of any Prime Minister. After an unorthodox mini-budget resulted in an acute economic crisis, she resigned her position after less than 50 days in the job

Results are reported on an aggregated level in order to protect the privacy and anonymity of individual respondents, to meet social research industry standards, and to ensure the robustness of the results. At the aggregate NSW level, the survey has high levels of accuracy, due to the large sample size (i.e. approximately 1,000 responses per wave). Typically, at the 95% confidence level, the margin of error on the reported survey results is approximately +/- 3% points or less. This means that the difference between two reported results may have to be at least 6% points for the gap to be considered statistically significant. Statistically significant changes over time have been highlighted in the attached survey results, where applicable. External events - such as Covid-19 pandemic related public health orders, extreme weather events in NSW - so far have not impacted the ability to gather sample for the study. However, as this is a social research dataset, it is expected that such external events have an impact on the environmental attitudes and behaviours that the survey has been designed to collect information on, and may explain some of the variance in the results over time.

Household Travel Survey (HTS) is the most comprehensive source of personal travel data for the Sydney Greater Metropolitan Area (GMA). This data explores average weekday travel patterns for residents in Sydney GMA. The Household Travel Survey (HTS) collects information on personal travel behaviour. The study area for the survey is the Sydney Greater Metropolitan Area (GMA) which includes Sydney Greater Capital City Statistical Area (GCCSA), parts of Illawarra and Hunter regions. All residents of occupied private dwellings within the Sydney GMA are considered within scope of the survey and are randomly selected to participate. The HTS has been running continuously since 1997/981 and collects data for all days through the year – including during school and public holidays. Typically, approximately 2,000-3,000 households participate in the survey annually. Data is collected on all trips made over a 24-hour period by all members of the participating households. Annual estimates from the HTS are usually produced on a rolling basis using multiple years of pooled data for each reporting year2. All estimates are weighted to the Australian Bureau of Statistics’ Estimated Resident Population, corresponding to the year of collection3. Unless otherwise stated, all reported estimates are for an average weekday. Due to disruptions in data collection resulting from the lockdowns during the COVID-19 pandemic, post-COVID releases of HTS data are based on a lower sample size than previous HTS releases. To ensure integrity of the results and mitigate risk of sampling errors some post-COVID results have been reported differently to previous years. Please see below for more information on changes to HTS post-COVID (2020/21 onwards). Data collection for the HTS was suspended during lock-down periods announced by the NSW Government due to COVID-19. Exceptions apply to the estimates for 2020/21 which are based on a single year of sample as it was decided not to pool the sample with data collected pre-COVID-19. HTS population estimates are also slightly lower than those reported in the ABS census as the survey excludes overseas visitors and those in non-private dwellings. Changes to HTS post-COVID (2020/21 onwards) HTS was suspended from late March 2020 to early October 2020 due to the impact and restrictions of COVID-19, and again from July 2021 to October 2021 following the Delta wave of COVID-19. Consequently, both the 2020/21 and 2021/22 releases are based on a reduced data collection period and smaller samples. Due to the impact of changed travel behaviours resulting from COVID-19 breaking previous trends, HTS releases since 2020/21 have been separated from pre-COVID-19 samples when pooled. As a result, HTS 2020/21 was based on a single wave of data collection which limited the breadth of geography available for release. Subsequent releases are based on pooled post-COVID samples to expand the geographies included with reliable estimates. Disruption to the data collection during, and post-COVID has led to some adjustments being made to the HTS estimates released post-COVID: SA3 level data has not been released for 2020/21 and 2021/22 due to low sample collection. LGA level data for 2021/22 has been released for selected LGAs when robust Relative Standard Error (RSE) for total trips are achieved Mode categories for all geographies are aggregated differently to the pre-COVID categories Purpose categories for some geographies are aggregated differently across 2020/21 and 2021/22. A new data release – for six cities as defined by the Greater Sydney Commission - is included since 2021/22. Please refer to the Data Document for 2022/23 (PDF, 262.54 KB) for further details. RELEASE NOTE The latest release of HTS data is 15 May 2025. This release includes Region, LGA, SA3 and Six Cities data for 2023/24. Please see 2023/24 Data Document for details. A revised dataset for LGAs and Six Cities for HTS 2022/23 data has also been included in this release on 15 May 2025. If you have downloaded HTS 2022/23 data by LGA and/or Six Cities from this link prior to 15/05/2025, we advise you replace it with the revised tables. If you have been supplied bespoke data tables for 2022/23 LGAs and/or Six Cities, please request updated tables. Revisions to HTS data may be made on previously published data as new sample data is appended to improve reliability of results. Please check this page for release dates to ensure you are using the most current version or create a subscription (https://opendata.transport.nsw.gov.au/subscriptions) to be notified of revisions and future releases.

Polling Software Market Outlook

The global polling software market size was valued at approximately USD 1.5 billion in 2023 and is projected to reach around USD 3.8 billion by 2032, growing at a CAGR of 10.5% during the forecast period from 2024 to 2032. This growth is propelled by the increasing demand for real-time data collection and analysis, which is crucial for decision-making processes in various sectors such as education, corporate, and government.

The burgeoning demand for efficient communication tools in educational institutions stands as a significant growth factor for the polling software market. Schools, colleges, and universities are leveraging polling software to engage students, enhance learning experiences, and streamline administrative tasks. The integration of polling tools in virtual classrooms, particularly in the wake of the COVID-19 pandemic, has further amplified their adoption. Institutions are increasingly recognizing the value of instant feedback and interactive learning environments, which polling software facilitates. Moreover, the ease of integration with existing Learning Management Systems (LMS) has made these tools indispensable in modern education.

Corporate sectors are also contributing substantially to the growth of the polling software market. Businesses are utilizing these tools for various purposes, including employee engagement, training sessions, and feedback collection. The ability to gather real-time insights during meetings and presentations enhances decision-making and fosters a collaborative work environment. Furthermore, polling software helps in gauging employee satisfaction and identifying areas for improvement, thereby contributing to organizational growth. The increasing trend of remote working has also necessitated the need for effective communication tools, further driving the market.

Government entities are another major segment bolstering the market growth for polling software. Governments across the globe are adopting these tools to facilitate public consultations, gather citizen feedback, and conduct surveys on various public policies and programs. The transparency and efficiency offered by polling software help in building trust and engaging citizens more effectively. Additionally, the ability to quickly analyze and interpret data collected through such software aids in informed decision-making and policy formulation. This technological adoption aligns with the broader trend of digital transformation within public administration.

The rise of Online Survey Software has been a game changer in the polling software market. These tools have revolutionized the way organizations collect and analyze data, offering a more streamlined and efficient approach to gathering insights. With the ability to reach a wider audience and gather responses in real-time, online survey software provides organizations with the flexibility to conduct surveys at their convenience, without the constraints of traditional methods. This has been particularly beneficial for educational institutions and businesses looking to engage with their audience more effectively. The integration of online survey software with other digital tools further enhances its utility, making it an indispensable part of modern data collection strategies.

From a regional perspective, North America holds a significant share of the polling software market, driven by the presence of major tech companies and a high adoption rate of advanced digital tools. Europe follows closely, with a growing focus on enhancing communication in educational and corporate sectors. The Asia Pacific region is expected to witness the highest growth rate, attributed to the rapid digitalization and increasing government initiatives to promote e-governance and digital learning. Latin America and the Middle East & Africa regions are also showing promising growth, although at a relatively slower pace, due to increasing investments in technology infrastructure and rising awareness about the benefits of polling software.

Deployment Mode Analysis

The deployment mode segment of the polling software market is divided into on-premises and cloud-based solutions. On-premises deployment involves installing the software on the local servers of an organization, providing complete control over data security and customization. This mode of deployment is preferred by organizations with stringent data security requirements, such as government entities and large corporations. The abili

This factsheet presents analysis of data on self-reported drink driving, drug driving and driver mobile phone use. Data is collected as part of the Crime Survey for England and Wales (CSEW) which is run by the Office for National Statistics (ONS) which covers all types of crime. Latest CSEW results are published by ONS.

Data are published annually, on a financial year basis, except during years affected by the COVID-19 pandemic.

For the year ending March 2025:

• 5.5% of respondents reported that they had driven at least once in the last 12 months when thought to be over the alcohol limit
• 0.4% of respondents reported having driven when thought to be affected by or under the influence of illegal drugs
• male drivers, and those in younger age groups, were more likely to report having driven when over the alcohol limit or under the influence of drugs
• 4.3% of drivers reported using a mobile phone in their hand while driving in the last 12 months

The report and data tables also provide figures for drivers affected by legal highs and medicinal drugs.

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