The Minnesota Electronic Health Record Consortium (MNEHRC) was established during the early days of the COVID-19 pandemic to provide data for public health surveillance from the eleven largest health care systems in Minnesota. This is a descriptive study of the Consortium, which is a federated network that implements best practices for governance and data infrastructure to support public health surveillance and clinical research. We conducted an analysis of the Consortium members, governance structure, infrastructure, and the characteristics of the patient population. The Consortium health systems collect information from 105 hospitals, 773 clinics, 100 emergency departments and 29 040 providers. Information about the health systems and the demographic and clinical characteristics of its 5 471 367 patients is provided, which represents more than 90% of the patients in Minnesota. This manuscript also details the MNEHRC governance structure, working groups, data use agreements and technical infrastructure. The Consortium has produced several studies with state-wide impact. One study, Health Trends Across Communities in Minnesota, is described in detail to illustrate aspects of this collaboration. MNEHRC has been a successful collaboration and vital resource for public health surveillance in the state of Minnesota. Initially, the Consortium focused on surveillance related to COVID-19 infections and vaccinations but has recently expanded into other public health and chronic disease research.

Mosquito-borne viruses (MBVs) remain a significant public health concern in Northern Queensland, Australia, with dengue virus (DENV), Ross River virus (RRV), and Barmah Forest virus (BFV) representing the most common pathogens. Wolbachia-based biological control programs have made notable contributions to reducing dengue transmission by suppressing Aedes aegypti vector competence. Recent surveillance data indicates increased MBV activity, with national case numbers nearly doubling between 2023 and 2024 and early 2025 data suggesting sustained transmission during seasonal peak. Traditional surveillance approaches, while highly valuable for disease monitoring, have limitations in detecting novel or divergent viral strains in real time. Over the past decades, more than 919 unclassified flaviviruses have been reported nationwide, including 117 in Queensland. The advent of metagenomic and metatranscriptomic approaches now enable enhanced, field-based detection of both known and emerging arboviruses. Strengthening mosquito control programs through continued Wolbachia releases, alongside integrated genomic surveillance, predictive modelling, and community engagement will enhance early detection, guide targeted interventions, and reduce the MBV burden in Northern Queensland. This integrated framework provides a strategic pathway to sustains and expand vector control effectiveness while safeguarding public health in high-risk regions.

Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections (LRTIs) and hospitalizations in infants, particularly during the first months of life. In December 2023, Argentina introduced maternal RSV immunization with the RSV-preF vaccine into its National Immunization Program. The objective of this study was to evaluate the impact of this strategy, implemented in 2024, on the burden of severe respiratory disease among infants under 6 months of age. We conducted a controlled before-and-after quasi-experimental study using active surveillance data from 3 sentinel pediatric hospitals in Argentina (2022-2024). Hospitalized LRTI cases in children under 5 years were included and stratified into 3 age groups: <6 months (intervention group), 6-11 months and 12-59 months (age-based controls). RSV and human metapneumovirus were confirmed by molecular methods. Hospitalization rates per 1000 all-cause discharges were calculated. Impact was estimated using rate ratios, incidence rate reduction (IRR) and crude difference-in-differences. A total of 4103 hospitalized LRTI cases were included. Among infants <6 months, all-cause LRTI hospitalization rates declined by 41% (IRR: 40.7%; 95% confidence interval: 29.7-49.9), and RSV-associated hospitalizations decreased by 35% (IRR: 34.9%; 95% confidence interval: 16.9-49.0) between pre- and post-intervention periods. An estimated 258 all-cause LRTI and 102 RSV LRTI-related hospitalizations were prevented in this age group. No significant changes were observed in older age groups or in human metapneumovirus-associated hospitalizations. Crude DiD analysis estimated an attributable impact of 15%-16%, although not statistically significant. Maternal RSV immunization was associated with a substantial reduction in LRTI and RSV-related hospitalizations among infants under 6 months. These findings support the use of this strategy to reduce severe respiratory illness during the RSV season.

Risk factors and surveillance for postdischarge surgical site infections: A prospective analysis.

Eighteen-year laboratory-based surveillance of human coronavirus OC43 in a single tertiary hospital in the Republic of Korea: Temporal inflection, seasonal stability, and age-dependent risk.

Ambient PM2.5 exposure and increased dengue case fatality: a global multi-country analysis.

Routine Restaurant Inspections: An Underutilized Data Source for Foodborne Illness Prevention.

ABSTRACT Background This study aimed to update the incidence and mortality of pneumococcal diseases and to evaluate the population-level trends in pneumococcal diseases incidence in Thailand, following PCV13 licensure and during the COVID-19 pandemic, in order to generate evidence supporting its inclusion in the National Immunization Program (NIP). Research design and methods We conducted a quasi-experimental interrupted time-series analysis using sentinel hospital surveillance data from adults aged ≥ 18 years hospitalized with pneumococcal disease in Thailand between 2010 and 2024. Surveillance comprised retrospective passive data collection (2010–July 2023) and prospective active surveillance (August 2023–July 2024), applying consistent case definitions and outcome ascertainment methods throughout. Four epidemiologic periods were predefined based on PCV13 licensure and key phases of the COVID-19 pandemic. Results Among 2069 hospitalized adults, 61.0% were aged ≥ 65 years. Noninvasive pneumococcal pneumonia (NIPP) accounted for 72.8% of cases, while invasive pneumococcal disease (IPD) comprised 27.2%, with a rising trend over time. The overall in-hospital fatality rate was 23.4%, significantly higher in IPD (31.7%) than in NIPP (20.4%, p < 0.001). The incidence of both IPD and NIPP nearly tripled over the study period. IPD increased from 1.43 to 4.05 per 100,000 population, while NIPP rose from 3.23 to 10.92 per 100,000 population, with a marked increase observed during the recent COVID-19 pandemic period. An increasing trend in macrolide resistance was observed in IPD and NIPP, particularly during the COVID-19 pandemic. Serotype analysis showed that PCV13 covered 79% of all isolates, PCV15 covered up to 79–81%, and PCV20 offered the broadest coverage (up to 95%), particularly for IPD. Conclusions The burden of pneumococcal diseases in Thailand remains substantial, especially during the recent COVID-19 pandemic. The majority of disease-causing serotypes remained vaccine-type strains. Given that PCV13 or PCV15 inclusion in the Thai adult NIP should be prioritized to reduce the disease burden and antimicrobial-resistant pneumococcal infections. Clinical trial registration This study was registered with the Thai Clinical Trial Registry (TCTR20230816007).

BackgroundOptimizing cancer screening and surveillance frequency requires accurate information on parameters such as sojourn time and cancer risk from premalignant lesions. These parameters can be estimated using multistate cancer models applied to screening or surveillance data. However, the performance of these models has not been thoroughly investigated in settings in which cancer precursors are treated upon detection, preventing progression to cancer. Our main goal is understanding the performance of available multistate methods in this challenging censoring setting.MethodsWe assumed progression hazards between consecutive health states in a 3-state model (healthy [HE], cancer precursor, and cancer) to be either time independent or dependent on time since state entry and compared 6 methods implemented in R software packages with varying assumptions: time-independent hazards (msm), hazards dependent on time since state entry (msm with a phase-type model, cthmm, smms, BayesTSM), and hazards dependent on time since the start of the process (hmm). Risk estimates from each method were compared in simulations and illustrated using colorectal cancer surveillance data from 734 individuals, classified into 3 health states: HE, non-advanced adenoma (nAA), and advanced neoplasia (AN).ResultsAll methods performed well with time-independent hazards in the simulation study. With hazards dependent on time since state entry, only smms and BayesTSM provided unbiased risk estimates. In the application, only msm,hmm, and BayesTSM yielded converged solutions. The nAA risk estimates were similar between hmm and BayesTSM but differed for msm, while AN risk estimates varied across methods.ConclusionsMethods for multistate cancer models, specifically with unobservable precursor-to-cancer transition, are strongly affected by the time dependency of the hazard. With time-dependent hazards since state entry, BayesTSM provided robust estimates, in both the simulation and application.HighlightsThis study presents the first comprehensive comparison of available multistate modeling options for screening and surveillance data, focusing on the specific setting of a 3-state progressive model (healthy, cancer precursor, cancer) in which cancer precursors are treated upon detection so that the transition to cancer is prevented (censoring after intervention). Sample R code and simulated data demonstrating the compared methods, along with documentation (including installation instructions, manual, and/or worked examples) for the corresponding R software packages, are available at https://github.com/EddymurphyAkwiwu/MultiStateMethods.All methods provide unbiased risk estimates for transition times when the true progression hazards are time independent. With more realistic models in which progression hazards are dependent on time since state entry, only BayesTSM and smms yield unbiased risk estimates for transition times.In situations with weakly identifiable likelihoods, the smms package may suffer from numerical and optimization problems. The BayesTSM package overcomes these problems by applying regularized parameter estimation using weakly informative priors.Methods for multistate cancer models, more specifically with unobservable precursor-to-cancer transition, are strongly affected by the time dependency of the hazard. An inappropriate choice can lead to biased parameter estimates.

Foundation models—large AI systems pretrained on broad, heterogeneous data—are transforming scientific discovery. These models (e.g., GPT, GenCast, AlphaFold) excel at learning generalizable representations and adapting to new tasks with limited data. Yet, epidemic modeling has not experienced a comparable transformation. Traditional models remain pathogen-specific and often struggle to generate rapid insights during emerging outbreaks, as starkly illustrated by the SARS-CoV-2 pandemic. This Perspective asks whether the foundation model paradigm can extend to epidemic science: Can we build a single, pretrained model that captures the shared principles of infectious disease dynamics across pathogens, populations, and settings? Such a model could be fine-tuned to new contexts with minimal data, enabling faster forecasting, inference, and response, especially valuable in resource-limited settings. We argue that the growing convergence of epidemiological insight and modern AI makes this goal both urgent and increasingly plausible. We outline the main challenges in building foundation models for epidemics—nonstationarity, fragmented surveillance data, presence of diverse dynamical regimes, and the need for interpretability. We then propose a roadmap toward epidemic foundation models, emphasizing both algorithmic innovations to address these challenges and progress beyond algorithms, including investments in open datasets and cross-disciplinary training and collaboration. Developing epidemic foundation models offers a potentially transformative opportunity to strengthen global health security, particularly by improving preparedness in underresourced settings. If successful, they will serve as powerful, generalizable tools that complement existing efforts. The process of building these models will itself be valuable, exposing critical data gaps and guiding investments in global surveillance.

Sleep-related infant deaths in the USA have plateaued despite long-standing evidence-based recommendations for safe sleep. Understanding maternal patterns of adherence and associated disparities is critical to improving infant safety. Using nationally representative Pregnancy Risk Assessment Monitoring System (PRAMS) Phase 8 surveillance data (2016-2022), we estimated adherence to four safe sleep recommendations, examined temporal trends and assessed sociodemographic and behavioural correlates of non-adherence. We analysed 125 931 weighted maternal responses (weighted count: 6 372 445) on infant sleep position, location, surface and bedding. Temporal trends were assessed using log-linear regression and expressed as the average annual percentage change (APC). Disparities were examined using multiple logistic regression, reporting adjusted ORs (AORs) and 95% CIs. Adherence was highest for supine sleep position (79.8%; 95% CI 79.4 to 80.2) and lowest for safe bedding (32.8%; 95% CI 32.4 to 33.2). Significant improvements were observed in adherence to safe bedding (APC=11.5%) and safe sleep surfaces (APC=2.8%). Compared with non-Hispanic white mothers, non-Hispanic black mothers had substantially higher odds of unsafe practices, including non-supine position (AOR 3.4; 95% CI 3.2 to 3.7), infant bed-sharing (AOR 2.4; 95% CI 2.3 to 2.6), unsafe sleep surfaces (AOR 1.5; 95% CI 1.4 to 1.6) and loose bedding (AOR 3.6; 95% CI 3.3 to 3.9). Elevated risks were also seen among Hispanic mothers, Medicaid or uninsured, unmarried, smokers and those not receiving healthcare worker advice. Maternal adherence to safe sleep recommendations remains low, with persistent sociodemographic disparities. These findings highlight the need for stronger integration of safe sleep counselling within antenatal and postpartum care.

The purpose of this study was to describe the HIV care continuum postpartum in a cohort of postpartum women with HIV (WWH) in Philadelphia, and assess the impact of the City's perinatal case management (PCM) program on engagement in the HIV care continuum. A cohort of 937 mothers who gave birth between 1/1/2012 and 12/31/2023 and who lived, gave birth, or received perinatal and pediatric care in Philadelphia, PA were enrolled. Using public health surveillance data, the impact of PCM use on engagement in care at 90days postpartum, retention in care at 1-year postpartum, and viral suppression at 1-year postpartum was assessed using logistic regression with robust standard errors. Overall, 51.1%, 65.4%, and 42.0% of the population was engaged in care at 90days, and retained in care and virally suppressed at 1-year, respectively. A larger percentage of PCM users than non-users were engaged in care at 90days (56.4% versus 43.9%) and retained in care (73.2% versus 59.2%) and virally suppressed (48.2% versus 37.1%) at 1year. After controlling for confounders, PCM use was significantly associated with increased engagement in care at 90days (aOR = 1.403 [1.030-1.913]), retention in care at 1year (aOR = 1.576 [1.163-2.136]), and viral suppression at 1year (aOR = 1.412 [1.060-1.881]). Philadelphia's PCM program is effective in improving engagement in the HIV care continuum during the postpartum period. Other US cities, particularly those with high HIV prevalence, should consider adopting a similar city-funded PCM program for pregnant and postpartum WWH.

Interim estimates of state-level influenza vaccine effectiveness (VE) can help guide timely local public health actions for prevention and treatment of influenza. Linked influenza vaccination and public health influenza surveillance data from California allowed estimation of interim influenza VE by comparing the odds of seasonal influenza vaccination among persons who received positive and negative influenza test results reported to the California Department of Public Health (CDPH) using a case-control study design. During October 1, 2025-January 31, 2026, a total of 952,765 influenza laboratory test results were reported to CDPH. These data were analyzed, including results for 86,369 (9%) persons with receipt of a positive influenza test result (case-patients) and 866,396 (91%) with receipt of a negative test result (control patients). Overall, 22% of case-patients and 27% of control patients were vaccinated against influenza. Interim VE against any influenza was 33% for all age groups, 39% for children and adolescents aged 6 months-17 years, and 22% for adults aged ≥65 years; VE was 32% against a positive influenza A test result, and 47% against a positive influenza B test result. These results suggest that influenza vaccination was associated with reduced odds for laboratory-confirmed influenza among children and adults. CDPH recommends annual influenza vaccination for all persons aged ≥6 months to reduce the risk for influenza and influenza-associated adverse health outcomes.

Respiratory syncytial virus (RSV) causes substantial disease burden worldwide, disproportionately affecting infants and young children. Higher susceptibility to RSV infections in young children, interacting with age-varying contact patterns and risk of disease progression, could drive the age-related variations in disease burden, though the extent of the susceptibility differences, and their influence on transmission dynamics and immunisation impact remains unclear. We developed an age-structured deterministic transmission model that integrated virological surveillance data, hospitalisations, and infection rates from the UK. We estimated age-dependent susceptibility coefficients for the 0- < 5years, 5-59year and ≥ 60years by integrating a profile likelihood approach with Markov Chain Monte Carlo (MCMC)-based calibration. Models were fitted to weekly RSV-positive cases in Scotland and infection rate estimates for the UK population. Age-specific infection-hospitalisation ratios (IHRs) were derived by combining modelled infections with RSV-associated hospitalisations. We evaluated multiple paediatric immunisation scenarios by estimating infections and hospitalisations averted, and the number of individuals needed to immunise (NNI) to prevent one RSV hospitalisation at varying coverage and efficacy. We estimated a susceptibility coefficient of 0.38 (95% CI 0.36-0.38) for 5-59years, and 0.38 (0.20-0.40) for ≥ 60years, relative to those under 5years. The overall annual infection rate was 51.8%, with peaked in children aged 12-23months (71.1%) and 0-2months (63.7%) using the best-fitting model, showing a substantial shift in the age distribution compared to the base model. IHRs showed a U-shaped distribution, with the highest rates in infants aged 0-2months and adults aged 75 and above. This model also projected a greater impact from immunisation programmes compared to the base model. For instance, an infant immunisation programme with 80% coverage and 80% efficacy against hospitalisation was projected to prevent 15.2% of hospitalisations, compared to 8.9% in the base model. Broader programmes, such as targeting 0-4-year-olds, resulted in larger reductions in hospitalisations (27.1%), while NNI increased as the programme expanded. The increased RSV susceptibility in children under 5years drives higher baseline transmission rates and disease burden in this subgroup, thereby influencing immunisation programme impact and efficiency.

Population-Based Investigation of DMD Genotype and Neurodevelopmental Concerns in Duchenne Muscular Dystrophy.

Monitoring antimicrobial resistance trends and emerging carbapenemases in Enterobacterales causing companion animal infections: a four-year study.

BackgroundHand, 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.ObjectiveThis study aimed to describe HFMD epidemiological characteristics and to evaluate the population-level effectiveness of the EV71 vaccination program in Jiangsu Province.MethodsWe characterized the temporal distribution of EV71-related HFMD cases based on longitudinal surveillance data collected through the National Notifiable Diseases Surveillance System in Jiangsu Province from 2012 to 2019 and assessed the impact of vaccination using a Bayesian structural time series model under a counterfactual framework. The intervention effect of the EV71 vaccine was estimated by comparing the observed data with predictions from a counterfactual model scenario without vaccination.ResultsA total of 932,274 HFMD cases were reported in Jiangsu from 2012 to 2019, including 5190 (0.56%) severe cases. An estimated 140,876 (15.11%) cases were attributed to EV71. EV71-associated HFMD cases showed a marked decline, with estimated numbers of 22,303, 9796, and 3900 in 2017, 2018, and 2019, respectively. We estimated that 30,117 EV71 cases (95% credible interval −1777 to 93,601) were prevented by the vaccination program from 2017 to 2019, corresponding to a reduction of 45.55% (95% credible interval −5.19% to 72.22%). The effectiveness of vaccination increased annually, with reductions of −1.03% (95% credible interval −94.85% to 48.29%) in 2017, 55.54% (95% credible interval 13.94%-77.56%) in 2018, and 82.28% (95% credible interval 65.77%-90.89%) in 2019. Furthermore, we observed that children younger than 4 years obtained greater benefits compared with those older than 4 years, with the greatest reduction of 57.68% (95% credible interval 13.04%-79.65%) in the 3- to 4-year age group, followed by a 48.09% (95% credible interval 28.00%-62.98%) reduction in the 0- to 2-year age group. In contrast, the reduction was markedly lower, at 16.75 % (95% credible interval −96.53% to 65.47%) in children older than 4 years during the 2017 to 2019 period.ConclusionsEV71 vaccination is an effective measure to prevent HFMD. The sharp decline in EV71-associated HFMD cases following the implementation of the EV71 vaccination program suggests a potential causal relationship. Therefore, strengthening vaccine coverage remains a public health priority.

Abstract Global Cancer Observatory has predicted a staggering 57.5% rise in cancer cases in India by 2040, amounting to an increase of 2.08 million cases. This ever-rising trend of cancer necessitates that we have continuous, robust and unbiased data regarding the occurrence of cancer. An ideal method for this would be compulsory reporting of cancer cases to the public health authorities. For this review, we did a thorough literature search primarily focusing on cancer notification, but we also included documents related to health policies and healthcare challenges faced during cancer care and treatment. Key words searched were ‘cancer’, ‘notification’, ‘mandatory’, ‘compulsory’, ‘notifiable’, ‘statistics’, ‘burden’, ‘cost’, ‘facts and figures’ and ‘policies’. Having cancer as a notifiable disease, we will have reliable and valid data, thereby enabling us to devise our own treatment and management protocols. Accordingly, investment in cancer screening, diagnosis and treatment could yield substantial health and economic benefits. Until December 2024, only 16 Indian states have made notification of cancer mandatory. The coordinated efforts from all the stakeholders will help in establishing a robust cancer surveillance and epidemiological data, marking a pivotal step toward combating the cancer epidemic.

Scalp and neck (SN) melanoma demonstrates the worst prognosis among all cutaneous head and neck melanomas (CHNMs). The objective of this study was to evaluate the melanoma-specific survival (MSS) in SN melanoma compared with other CHNM after the widespread clinical adaptation of sentinel lymph node biopsy in 2011 and asses whether tumor site is associated with distant metastases. A retrospective cohort study was carried out using Surveillance, Epidemiology, and End Result (SEER) data from 2011 to 2020, comprising 13,825 CHNM cases. Cox and multinomial logistic regression models were used to estimate adjusted hazard ratios and adjusted odds ratio (aORs). SN melanoma was associated with significantly worse MSS, with 5-year MSS rates of 76.5% versus 82.7%. Multivariable analysis showed SN melanoma had worse MSS (aHR 1.28; 95% confidence interval [CI] 1.16-1.41) and higher odds of presenting with lung metastases (aOR 2.39; 95% CI 1.35-4.25) and multisite metastases (aOR 2.23; 95% CI 1.28-3.88). A limitation of the study was that the SEER database groups SN together despite previous research suggesting that the scalp component contributes to most of the poor prognoses. SN melanoma is associated with worse MSS among all CHNMs despite the routine use of SLNB. SN melanoma also follows a distinct metastatic pattern to solid organs, particularly to the lungs.

With over 5 million attributed deaths per year, physical inactivity is a major global public health issue. Although the importance of physical activity is well recognized within the scope of obesity and cardiometabolic disease prevention and control, its broader benefits for the health of individuals and societies are yet to be fully harnessed. Furthermore, the role of active leisure, active transport and active labor-primary domains of physical activity-in supporting or hindering social and health equity has been largely overlooked. Here we (1) used a health equity lens to describe global domain-specific physical activity inequalities through an analysis of World Health Organization STEPwise approach to NCD risk factor surveillance (WHO STEPS) data from 68 countries; (2) summarized evidence linking physical activity with health outcomes beyond cardiometabolic disease, including immunity and infectious disease, depression and cancer; and (3) developed a new model reconceptualizing physical activity to better respond to 21st-century public health challenges. Our global, intersectional analysis of gender and socioeconomic physical activity inequalities revealed a 40-percentage-point gap in active leisure-the only domain consistently driven by choice-between historically privileged groups (wealthy men in high-income countries) and historically disadvantaged ones (poor women in low-income countries). Robust evidence supports the benefits of physical activity for immunity and infectious disease, depression and cancer. Our reconceptualized model recognizes the influence of social identities, norms, policies and structures on physical activity for health and wellbeing and emphasizes the urgent need to develop and roll out policies and programs that disseminate and harness the full benefits of physical activity for human, societal and planetary health.