bims-simosr Biomed News
on Simulation models in health service research
Issue of 2026–04–12
two papers selected by
Eunice T. Adwubi, University of Newcastle



  1. Epidemics. 2026 Apr 04. pii: S1755-4365(26)00025-3. [Epub ahead of print]55 100909
      Plasmodium falciparum is responsible for the majority of malaria morbidity and mortality each year. Malaria transmission rates vary by location and time of year due to climate and environmental conditions. We show the impact of these factors by developing a stochastic spatiotemporal agent-based malaria model that captures the impact of spatially distributed interventions on malaria transmission. Our model uses spatiotemporal estimates of mosquito climatic suitability and household location data to model the interaction between human and mosquito agents. We apply our model to investigate how strategies for distributing interventions to households in Vietnam impact the disease burden. Our study suggests that providing some level of protection to a wide range of households could reduce malaria prevalence more compared to providing a strong level of protection to a limited number of households.
    Keywords:  Agent-based model; P. falciparum malaria; Spatio-temporal modelling; Vector intervention
    DOI:  https://doi.org/10.1016/j.epidem.2026.100909
  2. Health Expect. 2026 Apr;29(2): e70608
       BACKGROUND: Deliberative democratic methods are increasingly being used to involve the public in health policy decision-making. These methods are rooted in deliberative democratic theory, which proposes the methods as democratic, inclusive and relevant ways to involve the public in policy decisions. Many practitioners have created methods for evaluating aspects of deliberative democratic engagement, but there are few practical guidelines for evaluating the quality of deliberative democratic processes as a whole. The aim of this study was to develop and pilot a framework for evaluating the quality of Citizens' Juries based on the OECD's Evaluation Guidelines for Representative Deliberative Processes.
    METHODS: We developed the Citizens' Jury Rigour and Improvement (C-JuRI) framework based on the OECD's criteria for evaluating deliberative democratic processes. We justified each criterion with respect to the theoretical literature on deliberative democracy. We describe the process of piloting the framework on the artificial intelligence (AI) in Healthcare Jury-the first national Citizens' Jury on using AI in healthcare.
    RESULTS: The C-JuRI framework was an effective tool for evaluating the AI in Healthcare Jury. Using the framework, we identified and reported on several strengths of the AI in Healthcare jury, as well as some opportunities to make changes to future processes to better work towards a deliberative democratic ideal. Post hoc additions to the framework may have assisted us in identifying more opportunities for improvement.
    CONCLUSION: The C-JuRI framework is a useful tool for researchers and practitioners aiming to design high-quality Citizens' Jury processes and for policymakers assessing the quality and rigour of deliberative democratic processes.
    PATIENT OR PUBLIC CONTRIBUTION: This framework is designed to evaluate the quality of initiatives to involve the public in decision-making. The framework was piloted on a jury in which 28 members of the public deliberated about the use of AI in healthcare.
    DOI:  https://doi.org/10.1111/hex.70608