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This is a commentary on Reisner et al’s Analyzing multiple types of discrimination using implicit and explicit measures, comparing target vs. Dominant groups, in a study of smoking/vaping among community health center members in Boston, Massachusetts (2020–2022). This manuscript is a study of the intersection of multiple forms of discrimination–racism, sexism, heterosexism, cissexism, ageism, and sizeism–and measures of implicit and explicit bias in the context of current smoking and vaping behavior among patients from targeted versus dominant groups at community health centers in Boston, Massachusetts (USA) from 2020 to 2022. The authors used logistic regression to assess smoking and vaping behavior with each type of discrimination, and then extended this analysis employing a meta-regression approach to better understand relationships across all types of discrimination under consideration in their study. Recently, the grant from the US National Institutes of Health, which supported this research was terminated in progress for ideological reasons by the current US administration under President Donald J. Trump for simply focusing on discrimination. While this study was among the first to be terminated by the Trump administration, hundreds of grants from the NIH and other US research funders have been cancelled in the first half of 2025. Reisner et al’s paper is an important piece of research, but it represents the start of a sophisticated inquiry into discrimination and bias, and future work by this team and in this area of research is necessary and sadly, now impossible to do with federal scientific funding. Work on discrimination and bias has always faced obstacles, but the scope and scale of attacks on science in the US require all scientists to push back against this censorship and political interference in the funding and conduct of research.

We report a cluster of clade I monkeypox virus infections linked to sexual contact in the Democratic Republic of the Congo. Case investigations resulted in 5 reverse transcription PCR-confirmed infections; genome sequencing suggest they belonged to the same transmission chain. This finding demonstrates that mpox transmission through sexual contact extends beyond clade IIb.

Expanding beyond practices for Covid-19, the U.S. government could require systematic data collection and public reporting for all vaccine-preventable infectious diseases in migrant detention centers.

There is a public health need to understand how different frequencies of COVID-19 booster vaccines may mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age and immune status. By analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, here we show that more frequent COVID-19 booster vaccination (every 6–12 months) in older age groups and the immunocompromised population would effectively reduce the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit against severe disease. In persons 75+ years, the model estimated that annual boosters would reduce absolute annual risk of severe COVID-19 by 199 (uncertainty interval: 183–232) cases per 100,000 persons, compared to a one-time booster vaccination. In contrast, for persons 18–49 years, the model estimated that annual boosters would reduce this risk by 14 (10–19) cases per 100,000 persons. Those with prior infection had lower benefit of more frequent boosting, and immunocompromised persons had larger benefit. Scenarios with emerging variants with immune evasion increased the benefit of more frequent variant-targeted boosters. This study underscores the benefit of considering key risk factors to inform frequency of COVID-19 booster vaccines in public health guidance and ensuring at least annual boosters in high-risk populations. The optimal frequency of COVID-19 booster vaccination is unclear. Here, the authors use a microsimulation model to assess the impact of different vaccine schedules on severe disease and show that regular boosters have large benefits for older and immunocompromised individuals but less so for younger age groups.

The initial marketing of the opioid analgesic OxyContin in 1996 increased fatal drug overdoses over the course of the opioid epidemic in the US. However, the long-term impacts of this marketing on complications of injection drug use, a key feature of the ongoing crisis, are undetermined. This study evaluated the effects of exposure to initial OxyContin marketing on the long-term trajectories of injection drug use-related outcomes in the US. We used a difference-in-differences analysis to compare outcomes in states with high versus low exposure to initial marketing before and after the 2010 reformulation of OxyContin, which facilitated the use of illicit drugs and the spread of infectious disease. Exposure to initial OxyContin marketing statistically significantly increased rates of fatal synthetic opioid-related overdoses; acute hepatitis A, B, and C viral infections; and infective endocarditis-related deaths. The greatest burden of adverse long-term outcomes has been in states that experienced the highest exposure to early OxyContin marketing. Our findings indicate that OxyContin marketing decisions from the mid-1990s increased viral and bacterial complications of injection drug use and illicit opioid-related overdose deaths twenty-five years later.

Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic. We used a publicly available data set of suspected heroin-related emergency calls (n = 6,246) to map overdose incidents to 280 census block groups in Cincinnati between August 1, 2015, and January 30, 2019. We used a Bayesian space-time Poisson regression model to examine the relationship between demographic and environmental characteristics and the number of calls within block groups. Higher numbers of heroin-related incidents were found to be associated with features of the built environment, including the proportion of parks (relative risk [RR] = 2.233; 95% credible interval [CI]: [1.075-4.643]), commercial (RR = 13.200; 95% CI: [4.584-38.169]), manufacturing (RR = 4.775; 95% CI: [1.958-11.683]), and downtown development zones (RR = 11.362; 95% CI: [3.796-34.015]). The number of suspected heroin-related emergency calls was also positively associated with the proportion of male population, the population aged 35-49 years, and distance to pharmacies and was negatively associated with the proportion aged 18-24 years, the proportion of the population with a bachelor's degree or higher, median household income, the number of fast food restaurants, distance to hospitals, and distance to opioid treatment programs. Significant spatial and temporal heterogeneity in the risks of incidents remained after adjusting for covariates. Limitations of this study include lack of information about the nature of incidents after dispatch, which may differ from the initial classification of being related to heroin, and lack of information on local policy changes and interventions. We identified areas with high numbers of reported heroin-related incidents and features of the built environment and demographic characteristics that are associated with these events in the city of Cincinnati. Publicly available information about opiate overdoses, combined with data on spatiotemporal risk factors, may help municipalities plan, implement, and target harm-reduction measures. In the US, more work is necessary to improve data availability in other cities and states and the compatibility of data from different sources in order to adequately measure and monitor the risk of overdose and inform health policies.

The federal government’s initial response to H5N1 avian influenza suggests that elected officials and other key decision makers may not be heeding the lessons from Covid-19.

Sexual violence is a major public health issue, affecting 35% of women worldwide. Major risk factors for sexual assault include inadequate indoor sanitation and the need to travel to outdoor toilet facilities. We estimated how increasing the number of toilets in an urban township (Khayelitsha, South Africa) might reduce both economic costs and the incidence and social burden of sexual assault. We developed a mathematical model that links risk of sexual assault to the number of sanitation facilities and the time a woman must spend walking to a toilet. We defined a composite societal cost function, comprising both the burden of sexual assault and the costs of installing and maintaining public chemical toilets. By expressing total social costs as a function of the number of available toilets, we were able to identify an optimal (i.e., cost-minimizing) social investment in toilet facilities. There are currently an estimated 5600 toilets in Khayelitsha. This results in 635 sexual assaults and US$40 million in combined social costs each year. Increasing the number of toilets to 11300 would minimize total costs ($35 million) and reduce sexual assaults to 446. Higher toilet installation and maintenance costs would be more than offset by lower sexual assault costs. Probabilistic sensitivity analysis shows that the optimal number of toilets exceeds the original allocation of toilets in the township in over 80% of the 5000 iterations of the model. Improving access to sanitation facilities in urban settlements will simultaneously reduce the incidence of sexual assaults and overall cost to society. Since our analysis ignores the many additional health benefits of improving sanitation in resource-constrained urban areas (e.g., potential reductions in waterborne infectious diseases), the optimal number of toilets identified here should be interpreted as conservative.

He downplayed the risk and delayed action, costing countless avertable deaths