TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States.

The Omicron wave was the largest wave of COVID-19 pandemic to date, more than doubling any other in terms of cases and hospitalizations in the United States. In this paper, we present a large-scale agent-based model of policy interventions that could have been implemented to mitigate the Omicron wave. Our model takes into account the behaviors of individuals and their interactions with one another within a nationally representative population, as well as the efficacy of various interventions such as social distancing, mask wearing, testing, tracing, and vaccination.

Childhood Sugar-Sweetened Beverage Consumption: an Agent-Based Model of Context-Specific Reduction Efforts.

Introduction: Despite widespread recognition among public health experts that childhood sugar-sweetened beverage consumption should be reduced, doing so has proven to be a challenge. An agent-based model of early childhood sugar-sweetened beverage consumption was applied to data from three high-quality, longitudinal cohort studies to gain insight into potentially effective intervention strategies across contexts.

Methods: From 2021 to 2023, a single agent-based model design was applied to data sets derived from three separate cohorts of children followed from infancy to childhood, with very different populations and environments (participants recruited in 1999-2002; 2003-2010; and 2009-2014).

Understanding Misimplementation in U.S. State Health Departments: An Agent-Based Model.

Introduction: The research goal of this study is to explore why misimplementation occurs in public health agencies and how it can be reduced. Misimplementation is ending effective activities prematurely or continuing ineffective ones, which contributes to wasted resources and suboptimal health outcomes.

Methods: The study team created an agent-based model that represents how information flow, filtered through organizational structure, capacity, culture, and leadership priorities, shapes continuation decisions.

An agent-based model of child sugar-sweetened beverage consumption: implications for policies and practices.

Background: A strong body of evidence links young children's intake of sugar-sweetened beverages (SSBs) with myriad negative outcomes.

Objectives: Our research provides insight into whether and to what extent potential intervention strategies can reduce young children's consumption of SSBs.

Methods: We built an agent-based model (ABM) of SSB consumption representing participants in the Project Viva longitudinal study between ages 2 and 7 y.

Using Agent-Based Modeling to Extrapolate Community-Wide Impact from a Stakeholder-Driven Childhood Obesity Prevention Intervention: Shape Up Under 5.

Whole-of-community interventions are a promising systems-based approach to childhood obesity prevention. A theorized driver of success is "Stakeholder-Driven Community Diffusion" (SDCD): the spread of knowledge about and engagement with obesity prevention efforts from a committee of stakeholder representatives. We focus on the potential of SDCD to affect the broader community.

Using a Microsimulation of Energy Balance to Explore the Influence of Prenatal Sugar-Sweetened Beverage Intake on Child BMI.

Objective: Experiments with animals suggest that high sugar consumption during pregnancy may predispose offspring to obesity, but few human studies have examined this relationship. This study explored the association between the consumption of sugar-sweetened beverages (SSBs) during pregnancy and caloric intake through childhood.

Methods: Using cohort data on child weight, height, and physical activity levels, a lab-validated microsimulation model of energy balance was employed to infer the caloric intake of children through age 11 years.

Activating a Community: An Agent-Based Model of Romp & Chomp, a Whole-of-Community Childhood Obesity Intervention.

Objective: Successful whole-of-community childhood obesity prevention interventions tend to involve community stakeholders in spreading knowledge about and engagement with obesity prevention efforts through the community. This process is referred to by the authors as stakeholder-driven community diffusion (SDCD). This study uses an agent-based model in conjunction with intervention data to increase understanding of how SDCD operates.