ABSTRACT Concurrent crises represent a significant challenge for disaster and public health governance. Activated in response to one threat, governing institutions may be distracted or stretched thin during an emergent crisis. In such crises, governments and communities rely heavily on non‐state service providers such as non‐profit organizations and religious groups. To examine the role of non‐state providers during concurrent crises, we engaged in original survey research, secondary data analysis, and field interviews focused on the overlapping challenges of the COVID‐19 Pandemic and the 2021 Texas Winter Storm Uri as well as the pandemic's delta wave and Hurricane Ida. We considered the impact of local non‐profit capacity on community recovery, the ability of institutions to adapt, and the implications of reliance on non‐state providers for public accountability and resource allocation. Our findings supported the hypothesis that non‐profit assets augment the role of government in responding to crises. We did not find that concurrent crises weakened the ability of non‐profit groups to respond, but instead found evidence consistent with organizational adaptation. We found that closer ties to government were associated with increased transparency/accountability as well as allocation of resources based on standardized measures of need.

A growing literature at the intersection of international relations, public policy, and comparative politics has explored the role that International Governmental Organizations (IGOs) play in influencing domestic policymaking. This literature is grounded in a commonly shared theoretical expectation that policymakers will perceive IGOs as neutral and technocratic purveyors of expert information. Based on this expectation, scholars have assumed that policymakers are likely to employ recommendations from IGOs when making decisions. In this research note, we examine this assumption through an analysis of original survey data on U.S. mayors' responses to COVID-19-related guidance from the World Health Organization (WHO). In contrast to dominant theoretical expectations, we find that mayoral likelihood of considering WHO recommendations in policymaking and of trusting WHO-provided information was largely a function of ideology, an effect that remains after incorporating the interactive effect of Trump vote share. Existe una creciente literatura, que se haya en la intersecci & oacute;n de las relaciones internacionales, las pol & iacute;ticas p & uacute;blicas y la pol & iacute;tica comparada, que ha estudiado el papel que desempe & ntilde;an las Organizaciones Gubernamentales Internacionales (OIG) y su influencia en la formulaci & oacute;n de pol & iacute;ticas nacionales. Esta literatura parte de una expectativa te & oacute;rica, com & uacute;nmente compartida, de que los responsables de la formulaci & oacute;n de pol & iacute;ticas percibir & aacute;n a las OIG como si estas fueran proveedoras neutrales y tecnocr & aacute;ticas de informaci & oacute;n experta. Partiendo de la base de estas expectativas, los acad & eacute;micos han asumido que es probable que los responsables de la formulaci & oacute;n de pol & iacute;ticas empleen las recomendaciones de las OIG a la hora de tomar decisiones. En esta nota de investigaci & oacute;n, analizamos esta suposici & oacute;n a trav & eacute;s de un an & aacute;lisis de los datos de la encuesta original sobre las respuestas de los alcaldes de EE. UU. a las directrices relacionadas con la COVID-19 proporcionadas por la OMS. Concluimos, en contraste con las expectativas te & oacute;ricas dominantes, que la probabilidad de que los alcaldes consideraran las recomendaciones de la OMS para la formulaci & oacute;n de pol & iacute;ticas, as & iacute; como la probabilidad de que confiaran en la informaci & oacute;n proporcionada por la OMS, era, en gran medida, una funci & oacute;n de su ideolog & iacute;a. Este efecto permanece despu & eacute;s de incorporar el efecto interactivo de la proporci & oacute;n de votos obtenida por Trump. & Agrave; l'intersection entre les relations internationales, la politique publique et la politique compar & eacute;e, une litt & eacute;rature croissante s'int & eacute;resse au r & ocirc;le des organisations gouvernementales internationales (OGI) quand il s'agit d'influencer la politique nationale. Cette litt & eacute;rature s'ancre dans une attente th & eacute;orique largement partag & eacute;e selon laquelle les d & eacute;cideurs per & ccedil;oivent les OGI comme & eacute;tant des acteurs neutres et des fournisseurs technocratiques d'expertise. & Agrave; cause de cette hypoth & egrave;se, les chercheurs ont pr & eacute;sum & eacute; qu'il & eacute;tait probable que les d & eacute;cideurs utilisent les recommandations des OGI lorsqu'ils prennent des d & eacute;cisions. Dans cette note de recherche, nous examinons cette hypoth & egrave;se par le biais d'une analyse des donn & eacute;es d'un sondage in & eacute;dit sur les r & eacute;actions de maires am & eacute;ricains aux recommandations relatives & agrave; la COVID-19 de l'Organisation mondiale de la sant & eacute;. & Agrave; l'inverse des attentes th & eacute;oriques dominantes, nous constatons que la probabilit & eacute; que les maires prennent en compte les recommandations de l'OMS lorsqu'ils prenaient leurs d & eacute;cisions et de faire confiance aux informations fournies par l'organisation d & eacute;pendait largement de leur id & eacute;ologie; cet effet persiste une fois que l'on incorpore l'effet interactif de la proportion des votes pour Donald Trump.

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The widespread embrace of Large Language Models (LLMs) integrated with chatbot interfaces, such as ChatGPT, represents a potentially critical moment in the development of risk communication and management. In this article, we consider the implications of the current wave of LLM-based chat programs for risk communication. We examine ChatGPT-generated responses to 24 different hazard situations. We compare these responses to guidelines published for public consumption on the US Department of Homeland Security's Ready.gov website. We find that, although ChatGPT did not generate false or misleading responses, ChatGPT responses were typically less than optimal in terms of their similarity to guidances from the federal government. While delivered in an authoritative tone, these responses at times omitted important information and contained points of emphasis that were substantially different than those from Ready.gov. Moving forward, it is critical that researchers and public officials both seek to harness the power of LLMs to inform the public and acknowledge the challenges represented by a potential shift in information flows away from public officials and experts and towards individuals.

BackgroundLittle is known about representation in trials aimed at addressing Opioid Use Disorder. This is a crucial issue given high mortality rates overall and substantial differences in death rates across racial/ethnic groups.MethodsWe analyzed data from clinical trials, data on Census population, data on new admissions to treatment facilities with a diagnosis of Opioid Use Disorder, and mortality data.ResultsWe found that Native American people (who face the highest opioid-related mortality burden in the United States) were under-represented in clinical trials. Black people (who face the second highest mortality rate) were enrolled at levels that exceeded those expected. Our results suggest the need for increased efforts to include Native Americans in OUD clinical trials and also that researchers should consider the possibility that high levels of enrollment among black Americans may represent an undue burden. We found ambiguous results for Asian American and Hispanic people. Our analysis also suggests that White people were represented at levels below those expected, although they were a majority of clinical trials participants.ConclusionOverall, these findings highlight the importance of equity in clinical trials and major gaps in terms of representation.

I argue that health insurance emerged as an important aspect of Nixon's domestic policy agenda as a result of "policy escalation." By policy escalation, I mean a cascading line of reasoning that causes policy makers focused on one apparently discrete issue to formulate approaches for dealing with other interconnecting policy areas. Policy escalation serves as an internal agenda-setting mechanism: as policy makers contemplate policy changes, they may attempt to imagine the ways in which change will affect the rationale, fiscal position, and execution of programs in other policy areas. In the case of health insurance, the Nixon administration's proposal for replacing Aid to Families with Dependent Children with a guaranteed minimum income forced policy makers to consider how the new program would interact with the existing Medicaid program. Consideration of this question ultimately led them to formulate an approach to overhauling the nation's entire health insurance system.

This study examines the trends in use of unclaimed bodies in medical education in Texas.

We examined the impact of Medicaid expansion and of race/ethnicity on medication-assisted treat-ment (MAT) for opioid use disorder among those referred for treatment through the criminal jus-tice system. Using a cross-sectional design, we combined data from the Substance Use and Mental Health Services Administration's Treatment Episode Data Set with data on Medicaid expansion and age-adjusted mortality for drug poisoning deaths. Logistic regression was performed within state panels from 2012 to 2016, with 2014 excluded due to this being the transitional Medicaid expansion year. We found that Medicaid expansion led to an increase in the use of MAT to treat those referred to substance treatment facilities through the criminal justice system. We also identified key racial disparities in the use of MAT for those referred from the criminal justice system, with Blacks and Hispanics less likely to receive MAT than non-Hispanic Whites.

•White admissions given MOUD were less likely to become unemployed at discharge.•Blacks and Hispanics given MOUD were more likely to remain unemployed at discharge.•Racial disparities associated with MOUD have notable implications for policy.

The Challenges of Public Health Leadership Daniel SledgePhD Affiliation The author is with the Department of Political Science, University of Texas, Arlington. CopyRightCorrespondence should be sent to Daniel Sledge, PhD, 701 S Nedderman Dr, Arlington, TX 76019 (e-mail: danielsledge@gmail.com). Reprints can be ordered at http://www.ajph.org by clicking the "Reprints" link. https://doi.org/10.2105/AJPH.2021.306684 Accepted: December 15, 2021 Published Online: February 23, 2022

Abstract In this article, we examine public perceptions of the importance of different levels of government and of nongovernmental entities in responding to the COVID‐19 pandemic. By analyzing the case of COVID‐19, we illuminate patterns that may be helpful for understanding public perceptions of the response to a broader range of crises, including the impacts of hurricanes, tornadoes, earthquakes, wildfires, and other hazards. We contribute to the public policy literature on public perceptions of government response to crises and expand it to include consideration of the role of nonstate actors. Drawing on a representative survey of 1200 registered voters in Texas, we find that individuals are more likely to view government as extremely important to respond to the pandemic than nonstate actors. We find that perceptions of the role of state and nonstate actors are shaped by risk perception, political ideology and religion, gender, and race/ethnicity. We do not find evidence that direct impacts from the COVID‐19 pandemic consistently shape perceptions of the role of state and nonstate actors.

Dynamic estimation of the reproduction number of COVID-19 is important for assessing the impact of public health measures on virus transmission. State and local decisions about whether to relax or strengthen mitigation measures are being made in part based on whether the reproduction number, Rt, falls below the self-sustaining value of 1. Employing branching point process models and COVID-19 data from Indiana as a case study, we show that estimates of the current value of Rt, and whether it is above or below 1, depend critically on choices about data selection and model specification and estimation. In particular, we find a range of Rt values from 0.47 to 1.20 as we vary the type of estimator and input dataset. We present methods for model comparison and evaluation and then discuss the policy implications of our findings.

The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional-scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.

This book review essay discusses Transparency in Health and Health Care in the United States (2019), edited by Holly Fernandez Lynch, I. Glenn Cohen, Carmel Shachar, and Barbara Evans .

Governments have implemented social distancing measures to address the ongoing COVID-19 pandemic. The measures include instructions that individuals maintain social distance when in public, school closures, limitations on gatherings and business operations, and instructions to remain at home. Social distancing may have an impact on the volume and distribution of crime. Crimes such as residential burglary may decrease as a byproduct of increased guardianship over personal space and property. Crimes such as domestic violence may increase because of extended periods of contact between potential offenders and victims. Understanding the impact of social distancing on crime is critical for ensuring the safety of police and government capacity to deal with the evolving crisis. Understanding how social distancing policies impact crime may also provide insights into whether people are complying with public health measures. Examination of the most recently available data from both Los Angeles, CA, and Indianapolis, IN, shows that social distancing has had a statistically significant impact on a few specific crime types. However, the overall effect is notably less than might be expected given the scale of the disruption to social and economic life.