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  • These data comprise apparent densities, species and sex and of mosquitos collected in irrigated and non-irrigated areas in Bura, Tana River County Kenya, between September 2013 and November 2014. Sampling was repeated four times over the period to cover the wet season, dry season, irrigation season and fallow periods. Mosquitoes were trapped using carbon dioxide-baited (CDC) light traps. Mosquitoes harvested from each of these traps were immobilized using 99.5% triethyleamine (Sigma-Aldrich, St. Louis, Missouri) and transferred to distinct bar-coded centrifuge tubes or cryogenic vials. The samples were transported in liquid nitrogen to the entomology section of Arbovirus/Viral haemorrhagic fever (VHF) laboratory at the Kenya Medical Research Institute (KEMRI) where they were sorted by species, sex, village, collection date and counted. The study was implemented to assess the impact of land use change (specifically the conversion of pastoral rangeland into crop land) on the suitability of the habitats to mosquito development and colonization. It also aimed to identify relative abundance of mosquitoes associated with Rift Valley fever virus transmission. The data were collected and analysed by experienced researchers from the International Centre of Insect Physiology and Ecology (Kenya), the International Livestock Research Institute (Kenya) and the Kenya Medical Research Institute. 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) Program Agriculture for Nutrition and Health. Full details about this dataset can be found at https://doi.org/10.5285/813f99c4-d07a-42dc-993a-1c35df9f028e

  • 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

  • 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

  • Mosquito trap data from Kilombero Valley in Tanzania - a global hotspot for malaria. Since 2007, field entomologists working at Ifakara Health Institue (IHI) and at the University of Glasgow have been trapping and collecting primary malaria vectors for four villages in the Kilombero Valley: Lupiro, Kidugalo, Minepa and Sagamaganga. Trapped mosquitoes were identified to species level (Anopheles gambiae and A funestus), their sex recorded (male or female) and their abdominal status (fed or unfed) noted. When available, the daily mosquito data was consistently linked to micro climate data logger data (weather conditions on site, including averaged, minimum and maximum daytime and night time values for temperature, humidity and vapour pressure deficit). This long record allows exploring the relationship between malaria vector dynamics and related environmental conditions. Full details about this dataset can be found at https://doi.org/10.5285/89406b06-d0aa-4120-84db-a5f91b616053

  • This dataset contains water chemistry for inlet samples for remediation systems in Bihar, India and associated remediation system efficiency for arsenic removal. The dataset contains paired inlet-outlet data for 31 household and community groundwater remediation systems of different technology types (split into reverse osmosis/RO and non-reverse osmosis) and settings (household and non-household). The chemical data includes the composition of inlet water (concentrations of Fe, P, As, Ca, Mg, Na and Si) and associated arsenic removal. This data was generated as part of the Indo-UK Water Quality Programme Project FAR-GANGA (NE/R003386/1 and DST/TM/INDO-UK/2K17/55(C) & 55(G)). Full details about this dataset can be found at https://doi.org/10.5285/77700f8e-5da6-45ab-9c12-df1a7d20bc32

  • 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 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

  • The dataset provides observational information on events when humans are in contact with poultry in rural and urban Bangladesh. Data were collected during observation periods of three hours duration in three settings where humans and poultry have close interactions: rural households with domestic poultry and small-scale commercial farms in rural areas of Tangail district and market stalls that sell, slaughter and process live poultry in Dhaka city. Observations on hygiene or handwashing behaviours that take place before or after contact with poultry, poultry products (eggs, meat) or poultry waste (bedding, faeces or carcasses) were also recorded. A structured observation sheet was used to record the number of occurrences of pre-defined activities. The objective was to record the types of contact behaviours and proportion of human-poultry interactions that could result in human exposure to antibiotic-resistant bacteria carried by poultry. The research was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance (AMR) 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/10.5285/76f52a38-7a2c-49a3-b86f-cc40205459ef

  • 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

  • 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