These data include results from serological analysis carried out on serum collected from randomly recruited subjects, merged with household and subject level data about the subjects. The subject and household data collected included occupation of the household head, size of the household, and occupation, gender and age of the subject. Samples were collected from 303 people based in irrigated areas, 728 people from pastoral areas and 81 people from riverine areas along River Tana in Tana River and Garissa counties, Kenya. Field surveys were implemented in December 2013 to February 2014 and laboratory analyses were completed in June 2015. Serum samples were harvested from blood samples obtained from randomly recruited subjects and screened for anti-RVF virus immunoglobulin G using inhibition ELISA (enzyme-linked immunosorbent assay) immunoassay. The household and subject metadata was collected using Open Data Kit (ODK) (https://opendatakit.org) loaded into smart phones. The aim of the project was to determine the risk of Rift Valley Fever virus exposure in people living in areas with different land use and socio-ecological settings. The data were collected by experienced researchers from the International Livestock Research Institute (Kenya), the Department of Disease Surveillance and Response, Kenyatta National Hospital This dataset is part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC). The research was funded by NERC project no NE/J001570/1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). Additional funding was provided by the Consultative Group on International Agricultural Research (CGIAR) Research Program Agriculture for Nutrition and Health. Full details about this dataset can be found at https://doi.org/10.5285/8a668a4f-3526-4443-9e77-cea67f04ca19

These dataset files show the calibration of a sensor for mercury (II) ions using a Fluorimeter and either HgCl2 or HgNO3. A range of different sample conditions are tested, including sensor concentrations and relative proportions of water and a methanol co-solvent (required for solubility of the probe). Also tested was the ability of acid to affect the probes sensitivity to mercury as nitric acid is needed for the stability of HgNO3 as an analyte. File names listed show the concentration of sensor and the ratio of water to methanol tested. Inductively coupled plasma mass spectrometry (ICP-MS) data are also given these are used to validate the sensors calibration and also to monitor the levels of soluble mercury content of dental amalgam samples held at either (11⁰C or 37⁰C) in water and saliva. The supernatant of these suspensions is filtered and measured using ICP-MS to give the data as reported. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/bc82f15b-8db6-4398-bfec-655a1eecf2d7

Antibiotic susceptibility tests are presented as the zone of inhibition using the disc-diffusion method, and categorized as resistant, intermediate or susceptible. DNA samples from antibiotic-resistant bacteria were analysed for the presence or absence of resistance genes using polymerase chain reaction (PCR). Laboratory analyses were conducted by trained staff at the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). The aim of the study was to identify the antibiotic-susceptibility profiles and resistance genes of bacteria (Escherichia coli) obtained from humans, poultry and the environment. Bacterial isolates previously identified with resistance to third-generation cephalosporins or carbapenems were included in the analysis. Bacterial samples originated from rural households and poultry farms (broiler chickens) in Mirzapur, Tangail district; and urban food markets in Dhaka city, Bangladesh. Environmental samples included surface water, water supply, wastewater, soil, animal faeces (poultry and cattle) and solid waste. 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 dataset can be found at https://doi.org/10.5285/dda6dd55-f955-4dd5-bc03-b07cc8548a3d

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

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 16 risks were included in the BWS including four air-, food- and waterborne illnesses and 12 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

Concentrations of SARS-CoV-2 RNA and physichochemical data on wastewater samples collected from six sites across England and Wales between March and July 2020. Also included are the number of COVID-19 positive tests and COVID-19 related deaths for the same period collated from publicly available records. COVID-19 data relate to the lower tier local authority that the wastewater treatment plant was located within. Full details about this dataset can be found at https://doi.org/10.5285/ce40e62a-21ae-45b9-ba5b-031639a504f7

These data provide results from serological analysis carried out on serum collected from cattle (sample number = 460), goats (sample number = 949) and sheep (Sample number = 574) combined with data collected at the household and subject/animal levels at the time of serum sampling. The data collected at the household and subject/animal levels were: the total number of livestock owned by a household, altitude, geographical coordinates of the sampling sites; and breed, age, sex and body condition score of an animal. The research was carried out in irrigated and non-irrigated areas in Tana River County, Kenya. Field surveys were implemented in August to November 2013 and laboratory analyses were completed in June 2015. Serum samples were harvested from blood samples obtained from animals and screened for anti-Rift Valley Fever (RVF) virus immunoglobulin G using inhibition (enzyme-linked immunosorbent assay) ELISA immunoassay. The household data was collected using Open Data Kit (ODK) loaded into smart phones. The serological analysis was performed to determine the risk of Rift Valley Fever virus exposure in cattle, sheep and goats. The aim of the survey was to investigate whether land use change, specifically the conversion of rangeland into cropland, affected RVF exposure pattern in livestock. The data were collected by experienced researchers from the Ministry of Livestock Development Nairobi, Kenya and the International Livestock Research Institute (Kenya). This dataset is part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC). The research was funded by NERC project no NE-J001570-1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). Additional funding was provided by Consultative Group on International Agricultural Research (CGIAR) Research Program Agriculture for Nutrition and Health led by International Food Policy Research Institute (IFPRI). Full details about this dataset can be found at https://doi.org/10.5285/b9756c4c-9894-4147-a260-a79067604a06

The resource consists of genome sequence data for the Drosophila C virus that has been serially passaged through different species of Drosophila in the laboratory. The genomes were sequenced and aligned to the reference genome. The frequency of variants at both biallelic and triallelic sites was then calculated. We also generated a phylogeny of the species involved using published data. This data was generated to understand how viruses adapt to new host species by Francis Jiggins and his co workers. The work was carried out between July 2016 and September 2017 and was funded by NERC under award reference NE/L004232/1 Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/4434a27d-5288-4f2e-88ac-4b1372e4d073

This resource contains anonymised policy interviews on trypanosomiasis in Zambia from 2013 conducted by Catherine Grant (Institute of Development Studies) and Noreen Machila (University of Zambia, Department of Disease Control). These interviews explore the differing opinions of various stakeholders in relation to trypanosomiasis, a widespread and potentially fatal disease spread by tsetse flies which affects both humans and animals. It is an important time to examine this issue as human population growth and other factors have led to migration into new areas which are populated by tsetse flies and this may affect disease levels. This means that there is a greater risk to people and their livestock. Opinions on the best way to manage the disease are deeply divided (Source: Author Summary- Grant, C, Anderson, N and Machila, N [Accepted] Stakeholder narratives on trypanosomiasis, their effect on policy and the scope for One Health, Public Library of Science Neglected Tropical Diseases (PLOS NTD). This was part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC) and these interviews contributed to this consortium. The research was funded by NERC project no NE/J001570/1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). Full details about this dataset can be found at https://doi.org/10.5285/727c1c4e-e097-44a4-abc7-74a4cc9acbfc

This dataset contains pH, turbidity, conductivity and viral concentration information in river and estuarine water, wastewater, sediment and mussel samples collected in the Conwy River and estuary. The aim of data collection was to monitor wastewater contamination in the freshwater-marine continuum. Samples were collected by trained members of staff from Bangor University at four weekly between March 2016 and August 2017. Treated and untreated wastewater samples were collected at four wastewater treatment plants along the Conwy River. Surface water samples were collected at four sites, sediments at three sites and mussels at two sites. 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 dataset can be found at https://doi.org/10.5285/5d19f6e2-1383-41ed-92d2-138d95bf4c72