Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

The Reintegration of Sexual Offenders

This paper, presented as the 9th Martin Tansey Memorial Lecture in April 2016, considers current and future approaches to sex offender reintegration. It critically examines the core models of reintegration in terms of risk-based and strengths-based approaches in the criminal justice context as well as barriers to reintegration, chiefly in terms of the community and negative public attitudes. It also presents an overview of new findings from recent empirical research on sex offender desistance, generally referred to the as the process of slowing down or ceasing of criminal behaviour. Finally, the paper presents an optimum vision in terms of re-thinking sex offender reintegration, and what I term ‘inverting the risk paradigm’, drawing out the key challenges and implications for criminal justice as well as society more broadly.

A Collaborative Multiagent Framework based on Online Risk-Aware Planning and Decision-Making

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions. 

Selective serotonin reuptake inhibitor antidepressant use in first trimester pregnancy and risk of specific congenital anomalies: a European register-based study

Evidence of an association between early pregnancy exposure to selective serotonin reuptake inhibitors (SSRI) and congenital heart defects (CHD) has contributed to recommendations to weigh benefits and risks carefully. The objective of this study was to determine the specificity of association between first trimester exposure to SSRIs and specific CHD and other congenital anomalies (CA) associated with SSRI exposure in the literature (signals). A population-based case-malformed control study was conducted in 12 EUROCAT CA registries covering 2.1 million births 1995-2009 including livebirths, fetal deaths from 20 weeks gestation and terminations of pregnancy for fetal anomaly. Babies/fetuses with specific CHD (n = 12,876) and non-CHD signal CA (n = 13,024), were compared with malformed controls whose diagnosed CA have not been associated with SSRI in the literature (n = 17,083). SSRI exposure in first trimester pregnancy was associated with CHD overall (OR adjusted for registry 1.41, 95% CI 1.07-1.86, fluoxetine adjOR 1.43 95% CI 0.85-2.40, paroxetine adjOR 1.53, 95% CI 0.91-2.58) and with severe CHD (adjOR 1.56, 95% CI 1.02-2.39), particularly Tetralogy of Fallot (adjOR 3.16, 95% CI 1.52-6.58) and Ebstein's anomaly (adjOR 8.23, 95% CI 2.92-23.16). Significant associations with SSRI exposure were also found for ano-rectal atresia/stenosis (adjOR 2.46, 95% CI 1.06-5.68), gastroschisis (adjOR 2.42, 95% CI 1.10-5.29), renal dysplasia (adjOR 3.01, 95% CI 1.61-5.61), and clubfoot (adjOR 2.41, 95% CI 1.59-3.65). These data support a teratogenic effect of SSRIs specific to certain anomalies, but cannot exclude confounding by indication or associated factors.