This dataset contains the answers gathered from the 806 participants who successfully finished an on-line survey on risk perception of environment-associated risks. The survey was launched on the 15th of February 2018 and ran for five days. The survey contained best worst scaling (BWS) to understand people's perceptions to certain risks. In this study sixteen risks were included in the BWS including four air-, food- and waterborne illnesses and twelve other hazards. The BWS was run in two blocks to consider two factors: first the respondents selected which risk they fear the most/least and in the second block they selected the risk they believed they had the most/least control. The survey also contained a detailed questionnaire on the participants eating habits and health status. Participants were also asked about their knowledge on enteric pathogens and whether they have ever sought or would consider seeking advice on the symptoms. Respondents were also asked whether they have experienced the hazards described in the BWS and whether they have done anything to reduce the risks in their life. The data were collected to gather information on people perceptions on environment-associated risks. This was done to understand the common knowledge on environment-associated pollutants and enlighten issues regarding risk management and mitigation. The data were collected as part of the VIRAQUA project was funded by the Natural Environment Research Council (NERC) under the Environmental Microbiology and Human Health (EMHH) Programme (NE/M010996/1). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/0869d961-99ca-4946-9192-f35afccdda38

Data comprise results of social surveys carried out in China during 2016 – 2018 to environmental scientists and the local stakeholders (farmers and village to county level officials) to understand their knowledge learning dynamics and preference. Surveys were conducted in the rural villages in Puding County, Guizhou Province, Changwu County, Shaanxi Province, and Yujiang County, Jiangxi Province. Full details about this dataset can be found at https://doi.org/10.5285/e674e08c-fbf5-411b-940c-7e31014f0e76

Data comprise results of social surveys carried out in China during 2016 – 2018 to the local stakeholders (farmers and village to county level officials) to understand their knowledge learning dynamics and preference. Surveys were conducted in the rural villages in Puding County, Guizhou Province and in Yujiang County, Jiangxi Province. The study was funded by the grant NE/N007425/1 which was awarded by the UK Natural Environment Research Council (NERC), and through cooperation with grant 41571130074 awarded by the National Natural Science Foundation (NSFC) of China, as part of the UK – China Critical Zone Observatory (CZO). Full details about this dataset can be found at https://doi.org/10.5285/9c14948d-cf58-4194-9fef-c2cb56818667

A cross-sectional, interviewer-administered survey was conducted in 2017 in rural households, poultry farms and urban food markets. Survey data for each setting comprise three datafiles. The rural households and poultry farms (broiler chickens) were located in Mirzapur, Tangail district; urban food markets were located in Dhaka city, Bangladesh. In each setting, the survey included participants that had high exposure to poultry, and a comparison group that had lower exposure to poultry. The aim of the survey was to assess potential sources of exposure to antibiotic-resistant bacteria, particularly commensal bacteria that colonise the gastrointestinal tract of humans and poultry. The survey also assessed the use of antibiotics for human participants and practices relating to their poultry such as type of feed, housing, use of antibiotics for poultry and hygiene practices before and after being in contact with poultry. The survey was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance Transmission from the Outdoor Environment to Humans in Urban and Rural Bangladesh. The research was funded by NERC/BBSRC/MRC on behalf of the Antimicrobial Resistance Cross-Council Initiative, award NE/N019555/1. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/b4a90182-8b9c-4da8-8b95-bcd5acc727d1