This file was generated on 2025-12-16 by MAUREEN NABATANZI A GENERAL INFORMATION 1. Title of the dataset: Data for modelling policy decisions to mitigate risk of emerging arboviral diseases under ecological change in Uganda 2. Brief description of the research project and its aims: This dataset comprises the results of the policy analysis we conducted to identify and compare Ugandan policy options which could potentially reduce the risk of arboviral disease emergence. During workshops, multidisciplinary experts reviewed these policies and identified disease preventive interventions/actions. Experts also assessed the influence of 29 preventive actions on disease risk under four policy options and made decisions on their probability of implementation under the policy options. We present the experts' conditional probabilities that were subsequently used in Bayesian Decision Modelling. 3. Author Information A. Investigator Contact Information Name: Maureen Nabatanzi Institution: Center for Development Research (ZEF), University of Bonn Address: Genscherallee 3, 53113, Bonn Email: maureen.nabatanzi@uni-bonn.de; mnabatanzi@musph.ac.ug; mrbnabatanzi@gmail.com B. Project Supervisor (Principal Investigator) Contact Information Name: Prof. Lisa Biber-Freudenberger Institution: Center for Development Research (ZEF), University of Bonn Address: Genscherallee 3, 53113, Bonn Email: lfreuden@uni-bonn.de C. In case of questions related to this dataset, please contact: Name: Maureen Nabatanzi Institution: Center for Development Research (ZEF), University of Bonn Address: Genscherallee 3, 53113, Bonn Email: maureen.nabatanzi@uni-bonn.de; mnabatanzi@musph.ac.ug; mrbnabatanzi@gmail.com 4. Date of data collection: 03-01-2025 - 30-04-2025 5. Information about funding sources that supported the collection of the data: This study was funded by the German Research Foundation (DFG) under the grant titled, “The Effects of Biodiversity loss and Land-Use Change on the Occurrence of Novel Infectious Diseases”, project number, 458328858. 6. Language of the dataset: English 7. Geographic location of data collection: Uganda B DATA & FILE OVERVIEW 1. File List: a) Conditional_Probabilities_Preventive_Actions.xlsx: Conditional probabilities of preventive actions given different policy options as estimated by experts b) Policy_Analysis.xlsx: Results of policy analysis 2. Are there multiple versions of the dataset? no 3. Relationship between files: Policy_Analysis.xlsx informed the generation of the conditional probabilities. 4. Additional related data collected that was not included in the current data package: N/A C SHARING/ACCESS INFORMATION 1. Was data derived from another source?: no 2. Licenses/restrictions placed on the data: N/A 3. Links to publications that cite or use the data : N/A 4. Links to other publicly accessible locations of the data : N/A 5. Links/relationships to ancillary datasets : N/A D METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: a) Policy_Analysis: During February – March 2025, we conducted a policy analysis involving a review of publicly available policies by the Government of Uganda concerning arboviral/zoonotic diseases and public health. We collated preventive interventions or actions per policy. b) Conditional_Probabilities_Preventive_Actions: Policy analysis findings informed the generation of an impact pathway with policy options and preventive actions likely to reduce arboviral disease risk in Uganda. During workshops, experts from the Agriculture, Health, Wildlife and Environment sectors discussed these results and made decisions on the policy options and preventive actions most likely to reduce arboviral disease risk. 2. Methods for processing the data: The data were cleaned in Microsoft Excel. 3. Instrument- and/or software-specific information needed to interpret the data: Microsoft Excel 4. People involved in sample collection, processing, analysis and/or submission: Maureen Nabatanzi was involved in data collection, extraction, analysis and submission. E DATA-SPECIFIC INFORMATION FOR: Policy_Analysis.xlsx 1. Variable list including full names and definitions (please spell out abbreviated words) of column headings for tabular data: Column names represent the preventive attributes or actions per policy/guideline/strategy analysed. 2. Units of measurement used: N/A 3. Missing data codes/symbols: N/A 4. Specialized formats or other abbreviations used: Rapid Response Team (RRT); PoE = Points of Entry; OH = One Health; AMR = Antimicrobial resistance; MAAIF = Ministry of Agriculture, Animal Fisheries and Industry; NAPHS = National Action Plan for Health Security; MWE = Ministry of Water and Environment; EIA = Environmental Impact Assessment; DHIS2 = District Health Information System 2; NEMA = National Environment Management Authority; NADDEC = National Animal Diseases Diagnostics Epidemiology Center; CCHF = Crimean Congo Haemorrhagic Fever; Integrated Disease Surveillance and Response (IDSR); UWA = Uganda Wildlife Authority; PHES = Public Health Emergencies; CAOs = Chief Administrative Officers; ToR = Terms of reference; OPM = Office of the Prime Minister (ToR); IPC = Infection Prevention and Control E DATA-SPECIFIC INFORMATION FOR: Conditional_Probabilities_Preventive_Actions.xlsx 1. Variable list including full names and definitions (please spell out abbreviated words) of column headings for tabular data: N/A a) Policy Options: 1) Do nothing = Counterfactual scenario, 2) Biodiversity_only = Increase biodiversity conservation, 3) Health_only = Implement human and animal health measures, 4) Biodiversity_Health_both = apply a One Health approach combining biodiversity conservation and health measures b) Preventive Action Scenarios: Expert estimated conditional probabilities for the influence of 29 preventive actions on disease risk under the four policy options. Yes and No probabilities per preventive action add up to 1. 2. Units of measurement used: N/A 3. Missing data codes/symbols: N/A 4. Specialized formats or other abbreviations used: N/A