Designing an evidence-based Bayesian network for estimating the risk versus benefits of AstraZeneca COVID-19 vaccine

Uncertainty surrounding the risk of developing and dying from Thrombosis and Thromobocytopenia Syndrome (TTS) associated with the AstraZeneca (AZ) COVID-19 vaccine may contribute to vaccine hesitancy. A model is urgently needed to combine and effectively communicate the existing evidence on the risks versus benefits of the AZ vaccine. We developed a Bayesian network to consolidate the existing evidence on risks and benefits of the AZ vaccine, and parameterised the model using data from a range of empirical studies, government reports, and expert advisory groups. Expert judgement was used to interpret the available evidence and determine the structure of the model, relevant variables, data to be included, and how these data were used to inform the model. The model can be used as a decision support tool to generate scenarios based on age, sex, virus variant and community transmission rates, making it a useful for individuals, clinicians, and researchers to assess the chances of different health outcomes. Model outputs include the risk of dying from TTS following the AZ COVID-19 vaccine, the risk of dying from COVID-19 or COVID-19-associated atypical severe blood clots under different scenarios. Although the model is focused on Australia, it can be easily adaptable to international settings by re-parameterising it with local data. This paper provides detailed description of the model-building methodology, which can used to expand the scope of the model to include other COVID-19 vaccines, booster doses, comorbidities and other health outcomes (e.g., long COVID) to ensure the model remains relevant in the face of constantly changing discussion on risks versus benefits of COVID-19 vaccination.

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Performance assessment of alternative SSS networks by combining KPIs and factor-cluster analysis

European Transport Research Review ◽

10.1186/s12544-020-00449-z ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Patrizia Serra ◽

Gianfranco Fancello

Keyword(s):

Cluster Analysis ◽

Performance Assessment ◽

Decision Support Tool ◽

Transport Systems ◽

Quantitative Methodology ◽

Support Tool ◽

Performance Benchmarking ◽

Relevant Variables ◽

Quantitative Results

Abstract Performance assessment is a fundamental tool to successfully monitor and manage logistics and transport systems. In the field of Short Sea Shipping (SSS), the performance of the various maritime initiatives should be analyzed to assess the best way to achieve efficiency and guide related policies. This study proposes a quantitative methodology which can serve as a decision-support tool in the preliminary assessment and comparison of alternative SSS networks. The research is executed via a Mediterranean case study that compares a hypothetical Mediterranean ro-ro SSS network developed in the framework of a past Euro-Mediterranean cooperation project with the network of existing ro-ro liner services operating in the area. Performance benchmarking of the two networks is performed using a set of quantitative Key Performance Indicators (KPIs) and applying a factor-cluster analysis to produce homogeneous clusters of services based on the relevant variables while accounting for sample heterogeneity. Quantitative results mostly confirm the overall better performance of the prospective network and demonstrate that using KPIs and factor-cluster analysis to investigate the performance of maritime networks can provide policymakers with a preliminary wealth of knowledge that can help in setting targeted policy for SSS-oriented initiatives.

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Modeling COVID-19 Nonpharmaceutical Interventions: Exploring periodic NPI strategies

10.1101/2021.02.28.21252642 ◽

2021 ◽

Author(s):

Raffaele Vardavas ◽

Pedro Nascimento de Lima ◽

Lawrence Baker

Keyword(s):

Health Outcomes ◽

Interdisciplinary Approach ◽

Decision Support Tool ◽

Health Interventions ◽

Quantitative Modeling ◽

Sensitivity Analyses ◽

Transmission Model ◽

Web Based ◽

Support Tool ◽

Nonpharmaceutical Interventions

AbstractWe developed a COVID-19 transmission model used as part of RAND’s web-based COVID-19 decision support tool that compares the effects of nonpharmaceutical public health interventions (NPIs) on health and economic outcomes. An interdisciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health/economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). This paper provides further details of our model, describes extensions, presents sensitivity analyses, and analyzes strategies that periodically switch between a base NPI level and a higher NPI level. We find that a periodic strategy, if implemented with perfect compliance, could have produced similar health outcomes as static strategies but might have produced better outcomes when considering other measures of social welfare. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies.

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Participatory methods for developing a Bayesian network model for simulating catchment resilience under future scenarios.

10.5194/egusphere-egu21-9876 ◽

2021 ◽

Author(s):

Kerr Adams ◽

Miriam Glendell ◽

Marc Metzger ◽

Rachel Helliwell ◽

Christopher (Kit) Macleod ◽

...

Keyword(s):

Land Use ◽

Bayesian Network ◽

Population Change ◽

Decision Support Tool ◽

Future Scenarios ◽

Cumulative Impacts ◽

Support Tool ◽

Arable Farming ◽

User Friendly ◽

Participatory Method

<p>The cumulative impacts of future climatic and socio-economic change have the potential to threaten the resilience of freshwater catchments and the important socio-ecological services they provide. Working with stakeholder groups from Scottish Water (statutory corporation that provides water and sewerage services across Scotland) and the Scottish Environment Protection Agency (environmental regulator), we established a participatory method for developing a Bayesian Network (BN) model to simulate the resilience of the Eden catchment, in eastern Scotland, to future pressures. The Eden catchment spans approximately 319km<sup>2</sup>, arable farming is the major land use, and the catchment falls within the Strathmore, Fife and Angus Nitrate Vulnerable Zone. The participatory method involves co-developing a BN model structure by conceptually mapping land management, water resource and wastewater services.&#160; Working with stakeholders, appropriate baseline data is identified to define and parameterise variables that represent the Eden catchment system and future scenarios. Key factors including climate, land-use and population change were combined in future scenarios and are represented in the BN through causal relationships. Scenarios consider shocks and changes to the catchment system in a 2050-time horizon. Resilience is measured by simulating the impacts of the future scenarios and their influence on natural, social and manufactured capitals within a probabilistic framework. Relationships between specific components of the catchment system can be evaluated using sensitivity analysis and strength of influence to better understand the interactions between specific variables. The participatory modelling improved the structure of the BN through collaborative learning with stakeholders, increasing understanding of the catchment system and stakeholder confidence in the probabilistic outputs. This participatory method delivered a purpose built, user-friendly decision support tool to help stakeholders understand the cumulative impacts of both climatic and socio-economic factors on catchment resilience.</p>

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A decision support tool for rural water supply planning

Journal of Water Sanitation and Hygiene for Development ◽

10.2166/washdev.2020.017 ◽

2020 ◽

Vol 10 (3) ◽

pp. 447-457

Author(s):

Joseph Cook ◽

Jake Wagner ◽

Gunnar Newell

Keyword(s):

Decision Support ◽

Water Supply ◽

Current Model ◽

Decision Support Tool ◽

Community Members ◽

Rural Water Supply ◽

Support Tool ◽

Rural Water ◽

Supply Planning ◽

Using Data

Abstract Over a dozen studies have examined how households who travel to collect water (about one-quarter of humanity) make choices about where and how much to collect. There is little evidence, however, that these studies have informed rural water supply planning in anything but a qualitative way. In this paper, we describe a new web-based decision support tool that planners or community members can use to simulate scenarios such as (1) price, quality, or placement changes of existing sources, (2) the closure of an existing source, or (3) the addition of a new source. We describe the analytical structure of the model and then demonstrate its possibilities using data from a recent study in rural Meru County, Kenya. We discuss some limits of the current model, and encourage readers and practitioners to explore it and suggest ways in which it could be improved or used most effectively.

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An application of the use of safe minimum standards in the conservation of livestock biodiversity

Environment and Development Economics ◽

10.1017/s1355770x05002640 ◽

2006 ◽

Vol 11 (1) ◽

pp. 77-94 ◽

Cited By ~ 11

Author(s):

ADAM G. DRUCKER

Keyword(s):

Decision Support ◽

Sustainable Use ◽

Policy Decision ◽

Decision Support Tool ◽

Cost Ratio ◽

Support Tool ◽

Benefit Cost Ratio ◽

Livestock Sector ◽

Animal Genetic Resource ◽

Using Data

This paper adapts the safe minimum standard (SMS) approach so as to explore its use as a potential policy decision support tool that can be applied to issues related to the conservation and sustainable use of farm animal genetic resource (AnGR) diversity. Empirical SMS cost estimates are obtained using data from three AnGR economics case studies in Mexico and Italy. The findings support our hypothesis that the costs of implementing an SMS are low, both when compared with the size of subsidies currently being provided to the livestock sector (<1 percent of the total subsidy) and with regard to the benefits of conservation (benefit-cost ratio of >2.9).Nevertheless, despite providing a potentially useful AnGR conservation decision support tool, a critical assessment of the application reveals that a much more extensive quantification of the components required to determine SMS costs needs to be undertaken before this tool can be applied in practice.

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A Decision Support Tool for Credit Domains: Bayesian Network with a Variable Selector Based on Imprecise Probabilities

International Journal of Fuzzy Systems ◽

10.1007/s40815-021-01079-w ◽

2021 ◽

Author(s):

Javier G. Castellano ◽

Serafín Moral-García ◽

Carlos J. Mantas ◽

María D. Benítez ◽

Joaquín Abellán

Keyword(s):

Decision Support ◽

Bayesian Network ◽

Decision Support Tool ◽

Imprecise Probabilities ◽

Support Tool

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Assessment of urban vulnerability towards floods using an indicator-based approach – a case study for Santiago de Chile

Natural Hazards and Earth System Science ◽

10.5194/nhess-11-2107-2011 ◽

2011 ◽

Vol 11 (8) ◽

pp. 2107-2123 ◽

Cited By ~ 71

Author(s):

A. Müller ◽

J. Reiter ◽

U. Weiland

Keyword(s):

Remote Sensing Data ◽

Decision Support Tool ◽

Capital City ◽

Flood Events ◽

Prevention Measures ◽

Support Tool ◽

Santiago De Chile ◽

Relevant Variables ◽

Local Decision ◽

Individual Household

Abstract. Regularly occurring flood events do have a history in Santiago de Chile, the capital city of Chile and study area for this research. The analysis of flood events, the resulting damage and its causes are crucial prerequisites for the development of risk prevention measures. The goal of this research is to empirically investigate the vulnerability towards floods in Santiago de Chile as one component of flood risk. The analysis and assessment of vulnerability is based on the application of a multi-scale (individual, household, municipal level) set of indicators and the use of a broad range of data. The case-specific set of indicators developed in this study shows the relevant variables and their interrelations influencing the flood vulnerability in the study area. It provides a decision support tool for stakeholders and allows for monitoring and evaluating changes over time. The paper outlines how GIS, census, and remote sensing data as well as household surveys and expert interviews are used as an information base for the derivation of a vulnerability map for two municipalities located in the eastern part of Santiago de Chile. The generation of vulnerability maps representing the two different perspectives of local decision makers (experts) and affected households is exemplified and discussed using the developed methodology.

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PostGeoOlap: an Open-Source Tool for Decision Support

10.5753/sbsi.2005.14976 ◽

2005 ◽

Author(s):

Giovanni Colonese ◽

Rodrigo Soares Manhães ◽

Sahudy Montenegro González ◽

Rogério Atem De Carvalho ◽

Asterio Kiyoshi Tanaka

Keyword(s):

Decision Support ◽

Open Source ◽

Decision Support Tool ◽

General Purpose ◽

Geographical Information ◽

Support Tool ◽

On Line ◽

Analytical Processing ◽

Using Data ◽

Application Developers

This work describes PostGeoOlap, a decision support tool that integrates OLAP (On-Line Analytical Processing) and GIS (Geographical Information System) technologies in a single application. PostGeoOlap is an open source and a general-purpose tool to be used by application developers to easily develop their decision support applications. This tool works on the PostGreSQL DBMS using its spatial extensions (PostGIS) and performs the analytical and geographical functionalities using data warehouses.

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