JMIR Public Health and Surveillance

In 2023, Esco Bars was the second most commonly reported e-cigarette brand used among US middle and high school student e-cigarette users. These products have not been authorized for sale in the United States by the US Food and Drug Administration (FDA). On May 12, 2025, and May 25, 2023, the FDA issued an import alert and a warning letter, respectively, to the manufacturer requiring them to immediately remove these unauthorized products from the market. On June 22, 2023, and July 27, 2023, the FDA also issued warning letters to US retailers and distributors, respectively, regarding the illicit sale of these unauthorized products. This study evaluated the impact of these advisory and enforcement actions on retail sales of Esco Bars in the United States.

A large wave of COVID-19 caused by SARS-CoV-2 Omicron subvariants began in Beijing in early December 2022.

Acute stress disorder (ASD) among people ever infected with COVID-19 is prevalent and may lead to posttraumatic stress disorder. Soon after China relaxed their COVID-19 control measures in November 2022 or December 2022, the infection rate surged rapidly, creating huge uncertainty and stressful situations. Little is known about situations regarding ASD at the ending phase of the pandemic.

Hand, foot, and mouth disease (HFMD), a common childhood illness caused by various enteroviruses, poses a significant public health threat in the Asia-Pacific region, where severe cases associated with enterovirus A71 (EV71) are a major concern. The EV71 vaccination program was introduced in China in late 2016. Although randomized controlled trials have established the robust efficacy and safety of these vaccines, assessing their real-world performance remains crucial. Subsequent studies have evaluated its real-world effectiveness in several provinces, including Zhejiang and Guangdong. However, evidence on its real-world impact in reducing EV71-associated HFMD in Jiangsu Province remains limited.

Men who have sex with men remain disproportionately affected by HIV globally and in China. Despite the availability of pre-exposure prophylaxis (PrEP) and postexposure prophylaxis (PEP), their uptake remains suboptimal. Previous studies have rarely integrated both sexual behavioral factors and prevention-related cognitive factors. A clearer understanding of heterogeneity in HIV exposure and prevention literacy is needed to inform targeted HIV prevention strategies.

As South Korea transitions into a super-aged society, understanding regional disparities in subjective health among older adults is critical to addressing health inequalities and supporting healthy aging.

A growing body of research supports the efficacy of text messaging programs to help tobacco users quit, but texting as a strategy for recruiting tobacco users into other evidence-based cessation services, such as quitline coaching, is less well understood. Texting to offer treatment could increase use of cessation resources, an important consideration for health systems trying to improve their quality metric performance on tobacco assessment and counseling.

Vitamin D and weight status are key determinants for neurodevelopmental outcomes in children. However, their independent and interactive associations with neurodevelopmental outcomes represent a critical yet insufficiently explored issue in pediatric health.

In today’s unstable funding climate, alternative research funding mechanisms are essential. Investigators are facing novel barriers to acquiring funding for their research. Early-stage investigators, in particular those who are beginning their careers in research, are especially vulnerable to these funding disruptions. Currently, finding alternative funding is especially relevant for scientists studying historically and intentionally excluded communities, such as lesbian, gay, bisexual, transgender, queer, or other sexual and/or gender expansive (LGBTQ+) populations, as many investigators have had their LGBTQ+ grants revoked by the Trump administration. Crowdfunding for research studies is a potential funding avenue that has grown in popularity, with more than US $12 million raised since 2012. This Viewpoint highlights crowdfunding as a potential funding model for LGBTQ+ cancer research, specifically to support the collection of preliminary data for predoctoral students and early-stage investigators. We describe the benefits and challenges of using crowdfunding as the sole funding mechanism for a mixed methods observational study among LGBTQ+ survivors of cancer. Despite challenges, crowdfunding can fund rigorous research on health disparities, notably in historically and intentionally excluded communities.

Diverse survey methodologies are essential to ensure equitable representation in public health research, particularly among minority populations. This study evaluates demographic differences among Vietnamese Americans who completed paper versus electronic surveys while administering the National Institutes of Health Community Engagement Alliance Common Survey 2, which focused on COVID-19–related topics.

Social determinants of health continue to drive persistent disparities in perioperative care. Our team has previously demonstrated racial and socioeconomic disparities in perioperative processes, notably in the administration of antiemetic prophylaxis, in several large perioperative registries. Given how neighborhoods are socially segregated in the United States, we examined geospatial clustering of perioperative antiemetic disparities.

Artificial intelligence (AI) is rapidly reshaping the landscape of health care, from clinical diagnostics and disease surveillance to the prediction of individual health risks. Yet, its immense promise will only materialize if the tools we deploy work for everyone. Algorithms trained on incomplete or biased datasets risk embedding historical health disparities and can replicate patterns of uneven data representation, thereby limiting accuracy and generalizability across population groups. Addressing algorithmic bias should be treated as a core health quality standard, comparable in importance to safety and efficacy evaluations, to ensure consistent performance across all segments of the population. This paper aims to frame algorithmic bias in health-related AI as a quality, safety, and governance challenge for health systems rather than solely a technical problem for developers. It aims to inform policymakers, regulators, health system leaders, and developers by translating existing scientific evidence and regulatory guidance into operational governance considerations, with particular attention to the realities of low- and middle-income settings in the region of the Americas. This paper synthesizes existing knowledge and institutional experience into a practical, regionally grounded policy perspective. To operationalize this perspective, this paper first outlines the main forms of algorithmic bias relevant to health systems—including representation, measurement, aggregation, and deployment biases—and illustrates how each can emerge across the AI lifecycle. It then situates these technical challenges within the broader digital health context, where structural, commercial, and social dynamics may amplify inequities. This paper discusses the implications of biased data for emerging areas such as precision medicine before proposing a governance-oriented framework for bias mitigation that spans design, validation, deployment, and postmarket monitoring. It concludes with priority governance actions for policymakers, regulators, and health system leaders to embed fairness as a measurable component of health system performance.