JMIR Public Health and Surveillance

Synthetic population and persona datasets can provide artificial individual-level records without exposing personal data. However, for surveillance use, they must preserve the joint profiles that define vulnerable groups, not only marginal distributions.

Tick-borne diseases (TBDs) in the United States are increasing due to ecological and climate changes. However, national surveillance data are principally available only at aggregate state and federal levels, limiting granular analysis and constraining TBD diagnosis, prevention, and public health communication. From a One Health perspective, recognizing the shared environments of people and animals and integrating canine serological data with human surveillance can improve geographic risk assessment and reduce reporting bias. Oklahoma offers a useful case in point: several TBDs are endemic, the state contains significant vulnerable populations, and public health records date to 1928, providing a longitudinal record examinable at the county level.

The COVID-19 pandemic generated a notable emotional impact on the general population, yet its effects on incarcerated individuals have been far less explored, despite the particular vulnerabilities associated with prison environments.

In the Inner Mongolia Autonomous Region, men who have sex with men (MSM) have become a high-risk group for HIV transmission due to their complex, secretive sexual relationships, posing challenges to HIV-1 prevention.

Testing arriving international travelers for COVID-19 paired with whole-genome sequencing (WGS) may identify new introductions of SARS-CoV-2 variants of concern in California, enabling a timely public health response. Traveler genomic surveillance may be a way to improve gaps in worldwide disease genomic surveillance.

The COVID-19 pandemic revealed substantial disparities in health outcomes across US communities. High-resolution mobility data offer new opportunities for real-time surveillance of behavioral responses, yet less is known about how precautionary behavior varied within cities and how these differences were associated with subsequent COVID-19 hospitalization risk.

The COVID-19 pandemic has triggered major global challenges, highlighting the need for timely surveillance and accurate forecasting to curb disease transmission and reduce the health burden. Traditional modeling approaches usually rely on aggregated data on confirmed cases. However, testing data can be unreliable due to low availability and uptake, as well as registration delays. In Sweden, the 1177 health care helpline provides valuable syndromic surveillance data that can capture early signals of infection prior to confirmation through testing.

Despite extensive vaccination efforts, pertussis has experienced a global resurgence, with China alone reporting over 470,000 cases in 2024. The age distribution of cases has shifted markedly from infants to school-age children and adults, likely driven by waning acellular pertussis vaccine (DTaP [Diphtheria, Tetanus Toxoids, and Acellular Pertussis Vaccine])–induced immunity. In response, China revised its immunization schedule in 2025 to include a booster dose at the age of 6 years; however, the population-level impact of this strategy on age-specific transmission dynamics remains unclear.

Chronic diseases, including behavioral health topics, impose a significant burden on health systems, especially among rural and tribal communities. In response, federal agencies require reliable data-driven decision-support for investigating emerging needs, prioritizing responses, and conducting surveillance. Federal decision-support models may benefit from geo-analytic methods capable of integrating multicriteria evidence, interagency policy-driven parameters, and disparate jurisdictional interests.

Hypertension is a key driver of multimorbidity; however, its role in shaping dynamic disease progression, especially in rural populations, remains underexplored.

Digital surveillance systems are increasingly recognized as essential tools for enhancing early outbreak detection, reporting, and response, especially in low-resource settings. The COVID-19 pandemic unveiled the critical role of digital health surveillance systems in timely detection, monitoring, and responses to public health threats. However, successful implementation depends on public awareness, acceptance, and willingness to participate. Limited evidence exists on how the public perceives and interacts with digital surveillance in Malawi.

Traditional disease surveillance systems often rely on clinical or laboratory-confirmed data, which may delay detection of emerging outbreaks. The National Retail Data Monitor (NRDM), established in 2002, collects anonymized over-the-counter (OTC) health product sales data from more than 28,000 retail outlets across the United States and provides a complementary data source for syndromic surveillance.