Minor Consent Laws for Sexually Transmitted Infection and Human Immunodeficiency Virus Services in the United States: A Comprehensive, Longitudinal Survey of US State Laws.

Objectives. To assess changes in minor consent laws for sexually transmitted infection (STI) and HIV testing, treatment, and prevention services in all 50 US states and the District of Columbia from 1900 to 2021. Methods. We coded laws into minor consent for (1) health care generally; (2) STI testing, treatment, and prevention; (3) HIV testing, treatment, and prevention; and (4) pre- or postexposure prophylaxis for HIV prevention. We also coded confidentiality protections and required conditions (e.g., threshold clinician judgments). Results. The largest increase in states allowing minors to consent to STI services occurred during the 1960s and 1970s. By 2021, minors could consent independently to STI and HIV testing and treatment in all 50 states plus DC, STI prevention services in 32 jurisdictions, and HIV prevention services in 33 jurisdictions. Confidentiality protections for minors are rare. Prerequisites are common. Conclusions. Although the number of states allowing minors to consent independently to STI and HIV services has increased considerably, these laws have substantial limitations, including high complexity, prerequisites requiring clinician judgments, and neglect of confidentiality concerns. (Am J Public Health. 2023;113(4):397-407. https://doi.org/10.2105/AJPH.2022.307199).

A database of US state policies to mitigate COVID-19 and its economic consequences.

BACKGROUND: Since COVID-19 first appeared in the United States (US) in January 2020, US states have pursued a wide range of policies to mitigate the spread of the virus and its economic ramifications. Without unified federal guidance, states have been the front lines of the policy response. MAIN TEXT: We created the COVID-19 US State Policy (CUSP) database ( https://statepolicies.com/ ) to document the dates and components of economic relief and public health measures issued at the state level in response to the COVID-19 pandemic. Documented interventions included school and business closures, face mask mandates, directives on vaccine eligibility, eviction moratoria, and expanded unemployment insurance benefits. By providing continually updated information, CUSP was designed to inform rapid-response, policy-relevant research in the context of the COVID-19 pandemic and has been widely used to investigate the impact of state policies on population health and health equity. This paper introduces the CUSP database and highlights how it is already informing the COVID-19 pandemic response in the US. CONCLUSION: CUSP is the most comprehensive publicly available policy database of health, social, and economic policies in response to the COVID-19 pandemic in the US. CUSP documents widespread variation in state policy decisions and implementation dates across the US and serves as a freely available and valuable resource to policymakers and researchers.

Disparities Made Invisible: Gaps in COVID-19 Data for American Indian and Alaska Native Populations.

Introduction: Complete COVID-19 data for American Indian/Alaska Native (AI/AN) populations are critical to equitable pandemic response. Methods: We used the COVID-19 U.S. State Policy database to document gaps in COVID-19 data reporting for AI/AN people. Results: Sixty-four percent of states do not report AI/AN data for at least one COVID-19 health metric: cases, hospitalizations, deaths, or vaccinations. Discussion: The lack of AI/AN-specific data masks the disproportionate burden of COVID-19 and presents challenges to COVID-19 prevention, policy implementation, and health equity. Conclusions: Public-facing data disaggregated by race may facilitate rapid response COVID-19 research and policymaking to support AI/AN communities.

Quantifying Uncertainty in Ecotoxicological Risk Assessment: MUST, a Modular Uncertainty Scoring Tool.

Whether conducting a risk, hazard, or alternatives assessment, one invariably struggles with the task of reconciling multiple available values of toxicological thresholds into a single outcome. When combining multiple pieces of evidence from many different sources, it is important to consider the role of data uncertainty. Uncertainty is inherent to all scientific data. However, in toxicological assessments, controversies and uncertainties are typically understated; they lack methodological transparency; or they poorly integrate qualitative and quantitative sources of information. Similarly, in model development, data curation is rarely performed with sufficient rigor, particularly when applying big data statistics. To overcome the hurdles of a decision process that must reconcile divergent data, we developed an uncertainty scoring tool that can be trained to reproduce specific decision-making paradigms and ensure consistency in the practitioner's judgment across complex scenarios. While designed to aid with ecotoxicological assessments and predictive model development, the tool's applicability extends to any decision-making process that calls for synthesis of incongruent data. Here, we highlight the development process, as well as demonstrate the method's utility in several prototypical ecotoxicological case studies.