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Data for modelling policy decisions to mitigate risk of emerging arboviral diseases under ecological change in Uganda

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Important usage condition: Use and redistribution are governed by CC0 1.0. Review and comply with the license before using the data.
Persistent identifier
doi:10.60507/FK2/HJPDE6
Published version
1.0
Publication date
2025-12-19
License
CC0 1.0

Description

In this study, we applied Bayesian Decision Modelling to evaluate how different policy interventions may reduce arboviral disease risk in Uganda. This dataset comprises the results of the policy analysis we conducted to identify and compare the potential Ugandan policy options that could reduce the risk of arboviral disease emergence. During workshops, multidisciplinary experts reviewed these policies and identified disease preventive interventions. 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.

Creators

Keywords

Emerging arboviral diseases, land use change, One Health, climate change, decision modeling, Uganda

Files

Before downloading: Use and redistribution are governed by CC0 1.0. Review and comply with the license before using the data.
FileTypeBytesChecksum
Conditional_Probabilities_Preventive_Actions.xlsxapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheet591449MD5 5b4f135aa52f7e18b06cd34cfdd6dca5
Policy_Analysis.xlsxapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheet29710MD5 7379d3c8487fe8b3cfeb6f7c4f43ca2d
ReadMe.txttext/plain6353MD5 ec68371c088ba9232299614deb18777e

Citation

Nabatanzi, Maureen, 2025-12-19, Data for modelling policy decisions to mitigate risk of emerging arboviral diseases under ecological change in Uganda, doi:10.60507/FK2/HJPDE6, V1.0

Additional Dataverse fields

Id476
Dataset Typedataset
Internal Version Number21
Latest Version Publishing StateRELEASED
Production Date2025
Release Time2025-12-19T09:34:39Z
Create Time2025-09-04T19:54:46Z
Citation Date2025-12-19
File Access RequestTrue

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Complete Dataverse metadata

Citation Metadata

Title title
Data for modelling policy decisions to mitigate risk of emerging arboviral diseases under ecological change in Uganda
Author author
  1. Author Name
    Nabatanzi, Maureen
    Author Affiliation
    University of Bonn
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0002-9801-4210
    Expandedvalue
    Person Name
    Nabatanzi, Maureen
    @id
    https://orcid.org/0000-0002-9801-4210
    Scheme
    ORCID
    @type
    https://schema.org/Person
Dataset Contact datasetContact
  1. Dataset Contact Name
    Nabatanzi, Maureen
    Dataset Contact Affiliation
    University of Bonn
    Dataset Contact Email
    s65mnaba@uni-bonn.de
Ds Description dsDescription
  1. Ds Description Value
    In this study, we applied Bayesian Decision Modelling to evaluate how different policy interventions may reduce arboviral disease risk in Uganda. This dataset comprises the results of the policy analysis we conducted to identify and compare the potential Ugandan policy options that could reduce the risk of arboviral disease emergence. During workshops, multidisciplinary experts reviewed these policies and identified disease preventive interventions. 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.
    Ds Description Date
    2025-09-04
Subject subject
  1. Agricultural Sciences
  2. Earth and Environmental Sciences
  3. Medicine, Health and Life Sciences
Free Keyword freeKeyword
  1. Free Keyword Value
    Emerging arboviral diseases, land use change, One Health, climate change, decision modeling, Uganda
Language language
  1. English
Production Date productionDate
2025
Production Place productionPlace
Uganda
Contributor contributor
  1. Contributor Type
    Project Leader
    Contributor Name
    Prof. Dr. Lisa Biber-Freudenberger
Grant Number grantNumber
  1. Grant Number Agency
    German Research Foundation (DFG)
Depositor depositor
Nabatanzi, Maureen
Date Of Deposit dateOfDeposit
2025-09-04
Kind Of Data kindOfData
  1. Qualitative and quantitative
Software software
  1. Software Name
    Microsoft Excel
    Software Version
    2019

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