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Annotated Bibliography on using simulations for policymaking

Freebairn, L., Atkinson, J., Kelly, P., McDonnell, G., & Rychetnik, L. (2018). Decision-makers’ experience of participatory dynamic simulation modeling: methods for public health policy. BMC Medical Informatics and Decision Making, 18(31). Retrieved from https://doi.org/10.1186/s12911-018-0707-6

The source shows a report on the kind of experience the end-user decision-makers have after participating in a simulation modeling for diabetes in pregnancy, alcohol-related harm, and childhood obesity prevention health policy and how the participants perceive the simulation in health situations. The report offers a systematic analysis and study through semi-structured interviews with the participants and establishes that such a co-produced situation of the participatory method is of high value.

Through the simulation, it was possible to evaluate how risk factors, integrated interventions, and scaling up of interventions were efficiently done. It was also possible to have a detailed mapping of evidence and prioritize the gap in research. The report is written in a scholarly way with proper organization, detailed referencing, appropriate format, and clearly defined terms that make anyone interested in the topic understand all ideas. With vast evidence and reliable evidence in the report, it is recommendable that any researcher interested in studying simulations for policymaking explores it.

Gilbert, N., Ahrwiler, P., Barbrook-Johnson, P., Narasimhan, K.P., & Wilkinson, H. (2018). computational modeling of public policy: reflections on practice. Journal of Artificial Societies and Social Simulation, 21(1). doi:10.18564/jasss.3669

The article indicates an argumentative usage of computational modeling in development, implementation, and evaluation of public policy hence reports from the first-person experience on how such models are used. Using various recent researchers, the authors show how an exploration of computational models is a potential study area, hence focus on what role such models serve in policymaking and issues which have to be overcome for the models to effectively serve in the policymaking process. Among the lessons the article offers are that when computational models are used it is easy to understand the policy realm, as long as a suitable abstraction level is undertaken. It is also possible to have limited calibration and validation of data, yet collaboration and involvement of stakeholders are high. The numbered and segmented parts of the paper as well as clearly labeled titles in varied fonts perfectly direct the reader into the following the information in the article. The inclusion of policy pilots offers exemplary policy implementation, models, and lessons through simulations together with adequate sources are adequate data for someone interested in studying the usage of simulation models for policymaking.

Atkinson, J., Knowles, D., Wiggers, J., Livingston, M., Room, R., Prodan, A., & McDonnell, G. et al. (2017). Harnessing advances in computer simulation to inform policy and planning to reduce alcohol-related harms. International Journal of Public Health, 63(4), 537–546. Retrieved from https://link.springer.com/article/10.1007/s00038-017-1041-y

The article covers an exploration of how feasible usage of a transparent and participatory agent-based modeling strategy in the development of a strong decision support tool for testing alcohol policy scenarios before implementation in the actual world. The authors use case studies to examine the functionality and establish that through simulation there is effective implementation of the policy.

Looking at the article a detailed abstract, outlining of keywords, an informing introduction, and breakdown of titles serve in the following up of every detail in the study. Besides diagrams, charts, discussions, and several references show the viability of data here. The references used are both contemporary and ancient, hence they offer reliable information and an overview of how simulation serve in making policies. The simulation experiments conducted too show evidence of how such models serve in policymaking and the output related to the process. The weakness of the article is the missing conclusion and usage of large paragraphs which would require a lot of concentration before one understands ideas within it.

Atkinson, J.M., Wells, R., Page, A., Dominello, A., Haines, M., & Wilson, A. (2015). Applications of system dynamics modeling to support health policy to support health policy. Public Health Res Pract, 25(3). doi: http://dx.doi.org/10.17061/phrp2531531

This article is quite resourceful due to how it handles the topic of simulation usage of policymaking. The authors offer a detailed abstract that offers limelight into the study and argues that there is increased recognition of how science modeling strategies offer value in the health sector, specifically in the improvement of operation aspects, analysis of policy options, and offering of participatory approaches that are parallel to the stakeholder objectives. In determining the effectiveness of simulations for health policy, the article shows how advances in software have permitted the extension of the model into complex policymaking provision with powerful tools to back up the targeted design as communication, documentation, and evaluation becomes easy.

A detailed systematic search of several databases offers up to date data out of 6 papers that particularly give the usage while many others offer supporting evidence about systematic modeling and policy-making. The authors account for the choice of methodology and an extensive discussion. Unlike other studies, this is qualitative evidence on the topic and it might require integration with quantitative studies as well as reading into referenced sources to have a detailed overview of the topic.

Lamé, G. & Simmons, R.K., (2018). From behavioral simulation to computer models: how simulation can be used to improve healthcare management and policy. BMJ Stel. 0:1–8. doi:10.1136/bmjstel-2018-000377

Lame and Simmons explore into how computer models build after behavioral simulation are serving in the betterment of the healthcare policy and management. The article provides a definition of simulation and why it is used. reasoning that simulations offer an integrative overview of the current approaches such as Vivo behavioral and silico computer types, the article indicates the complexity of health systems due to having diverse participants, resources, and actions. Detailed literature shows the dispersal of simulations within policy-making and management after which a review of simulation approaches is explored.

A focus on constructive, live, discreet-event and virtual simulations offers a clear picture into the application of these simulations and how the integration of various simulations can boost healthcare policy-making and management, A detailed table and narration into an evaluation of simulation, steps that serve in utilization of simulation, and the conclusive sections can help a researcher understand usage of simulation models for policymaking. Similarly, the many scholarly sources used in the article can guide a reader into situations in the study area.