Modeling Adolescent Health Care Decision-Making for Vaccines: A Community- Based Participatory Approach

ABSTRACT In the US, state and local laws allowing minors to consent to medical care can directly impact population health. Prior research suggests increased vaccine uptake among adolescents in states that allow minors to receive vaccines without parental consent. However, the impact of real-world effects (e.g., vaccine hesitancy, access to vaccine providers) on this association is unclear. It is also unknown if this association holds true for COVID-19 vaccines. Currently, the percent of fully vaccinated 12-17-year-olds largely differs by state (from 11 to 61%), increasing the risk of spread and negative health outcomes. Traditional efforts that apply mathematical models to examine population-level outcomes do not account for different vaccine consent (VC) laws, geospatial effects (e.g., spread within schools), local sociodemographics, or individual be- haviors (e.g., vaccine hesitancy). To accurately study the impact VC laws as well as other real- world effects have on COVID-19 transmission and mortality, researchers need to apply a com- prehensive framework that integrates legal policy with health outcomes. Our proposed model will apply a legal epidemiology framework that integrates legal and health data. It will leverage US census data in an agent-based simulation (Framework for Reconstructing Epidemiological Dynamics; FRED), which was designed to include system-level, sociodemographic, geospatial, and individual effects in its simulation models. Our multidisciplinary team-with expertise in ado- lescent health, health law, and computational modeling-will merge state- and local-level VC laws with nationally representative census data within FRED. We will collaborate with commu- nity partners-including minors, parents, school employees, and pediatricians, among others- to understand the impact of VC laws on COVID-19 vaccine uptake, explore potential interven- tions with different legal restrictions, and inform a simulation model. First, we will develop a comprehensive legal dataset of state- and local-level VC laws for minors. Second, we will col- laborate with community partners to understand the impact of VC laws and design potential in- terventions. Third, we will model the effects of various laws, real-world effects, and potential in- terventions in FRED to assess the impact of these factors on COVID-19 transmission. In sum- mary, this project will result in a comprehensive legal dataset of VC laws for minors and an evi- dence-based predictive model of COVID-19 spread and mortality in real-world conditions. The model's flexibility can inform researchers on the impact of various VC laws and other real-world effects that can impact population health.