Background: Optimizing sentinel surveillance site allocation for early pathogen detection remains a challenge, particularly in ensuring coverage of vulnerable and underserved populations. Objective: This study evaluates the current respiratory pathogen surveillance network in Brazil and proposes an optimized sentinel site distribution that balances Indigenous population coverage and national human mobility patterns. Methods: We compiled Indigenous Special Health District (DSEI) locations from the Brazilian Ministry of Health and estimated national mobility routes using the Ford-Fulkerson algorithm, incorporating air, road, and water transportation data. To optimize sentinel site selection, we implemented a linear optimization algorithm that maximizes (1) Indigenous region representation and (2) human mobility coverage. We validated our approach by comparing results with Brazil’s current influenza sentinel network and analyzing the health attraction index from the Brazilian Institute of Geography and Statistics to assess the feasibility and potential benefits of our optimized surveillance network. Results: The current Brazilian network includes 199 municipalities, representing 3.6% of the country’s cities. The optimized sentinel site design, while keeping the same number of municipalities, ensures 100% coverage of all 34 DSEI regions while rearranging 108 cities (58.3%) from the existing flu sentinel system. This achieves a more representative sentinel network, addressing gaps in 9 of 34 previously uncovered DSEI regions, which span 750,515 km² and have a population of 1.11 million. Mobility coverage improves by 16.8 percentage points, from 52.4% (4,598,416 paths out of 8,780,046 total) to 69.2% (6,078,747 paths out of 8,780,046 total). Additionally, all newly selected cities serve as hubs for medium- or high-complexity healthcare, ensuring feasibility for pathogen surveillance. Conclusions: The proposed framework optimizes sentinel site allocation to enhance disease surveillance and early detection. By maximizing DSEI coverage and integrating human mobility patterns, this approach provides a more effective and equitable surveillance network, particularly benefiting underserved Indigenous regions. Clinical Trial: Not applicable.

Background: Black cisgender women (BCW) account for 2% of pre-exposure prophylaxis (PrEP)-eligible people in the United States who use PrEP to prevent HIV. In correlation with low PrEP use, BCW continue to contract HIV more than women from every other racial group. Intervention efforts that can bridge the link between knowing that PrEP prevents HIV and support with access to PrEP are necessary for BCW. Objective: The purpose of the vlogs through the campaign was to share information about ways to prevent HIV using PrEP and fact-based education and provide access to PrEP resources with active links to local PrEP providers at local community health centers. Methods: In Phase I, the study team formerly piloted full-length video blog posts (vlogs) (10-12 minutes each) with 26 women during an emergency department visit. Using the findings from Phase 1, Phase 2 involved a prospective 6-month social media marketing campaign, the study team led a Texas-Development CFAR (TX-DCFAR) funded pilot grant to disseminate brief vlog snippets (30 seconds) of excerpts from the full-length vlogs with a larger group of Black women in Harris County. Community members, who were aged 18 -55 years, usually consume content that is often viewed by BCW (i.e. health/beauty), and reside in neighborhoods (based on zip code) in Harris County where most residents are Black or African American, were shown a series of brief vlog snippets on their social media pages, along with a brief message about PrEP and an active hyperlink to local PrEP resources. The study team was assessed implementation outcomes including feasibility and acceptability, appropriateness of vlogs, access to PrEP resources at local clinics, and clinical outcomes such as increased PrEP awareness among BCW. Results: Within 6 months, the campaign reached 110.8K unique individuals (the number of unique accounts that have seen your content at least once) who identify as women when stratified by age, video plays (the number of times a video starts playing) at 50% of the vlogs (n=30,877) were most common among women ages 18-24 years (n=12,017) and least common among women ages 45-54 years (n=658). Key performance indicators showed that 1,098,629 impressions (the number of times a user saw the vlog) and 1,002,244 total video plays resulted in 15,952 link clicks to local PrEP resources. Conclusions: The campaign demonstrated feasibility and acceptability of this approach with BCW and illustrated preliminary effectiveness at supporting access to local PrEP resources with BCW. Further dissemination and implementation of this approach is necessary to fully assess whether vlog viewership and clicks on links to PrEP resources can meaningfully empower BCW to access to PrEP and/or help them to assess whether PrEP is personally a useful HIV prevention option.

Background: Adoption of eHealth accelerated during the Coronavirus disease 2019 (COVID-19) pandemic. Inequalities in eHealth adoption during the COVID-19 pandemic have been reported, but there are few such studies among people with impairment. Objective: The aim of this study was to investigate use and difficulty in the use of eHealth before the COVID-19 pandemic compared to during late social distancing restrictions in Sweden, among people with and without impairment, as well as between different types of impairment. Methods: A cross-sectional survey was distributed twice by snowball-sampling to people with self-reported impairment and to a general population matched by age, gender and county. Use and difficulty in the use of six eHealth services were compared between groups using Chi2-test and logistic regression with year interaction terms, reported as odds ratio adjusted for gender and age (aOR) with 95% confidence interval (CI). Results: The surveys included 1,631 (in 2019) and 1,410 (in 2021) participants with impairment, and 1,084 (2019) and 1,223 (2021) without. Participants with impairment, compared to those without impairment, reported less use and more difficulty in booking healthcare appointments online, digital identification and the Swedish national web-portal for health information and eHealth services (1177.se), both before and during the pandemic (p=∙003 or lower). Video healthcare appointments was the exception to this disability digital divide in eHealth, as video appointment adoption had the highest odds ratio among participants with attention, executive and memory impairments (interaction term aOR 2·10, CI 1·30–3·39). Non-use and difficulty in the use of eHealth were consistently associated with language impairments and intellectual impairments (e.g. booking healthcare appointments online: use with language impairments aOR 0·64, CI 0·49–0·83 (in 2019) and aOR 0·70, CI 0·54–0·93 (in 2021); avoid use with language impairments aOR 1·64, CI 1·19–2·27 (in 2019) and aOR 1·31, CI 0·94–1·82 (in 2021); use with intellectual impairments aOR 0·28, CI 0·20–0·39 (in 2019) and aOR 0·25, CI 0·17–0·35 (in 2021); avoid use with intellectual impairments aOR 2·88, CI 1·86–4·45 (in 2019) and aOR 2·74, CI 1·74–4·33 (in 2021)). Conclusions: This repeated cross-sectional survey study, among participants with diverse types of impairment and a control group without impairment, reveal persistent disability digital divides, despite an accelerated adoption of eHealth across the pandemic. eHealth services were not accessible to all groups of people who were identified as being at risk of severe disease during the COVID-19 pandemic. Thus, people with impairment have been excluded from eHealth as measures of infection protection.

Background: Immunization is a highly cost-effective strategy for preventing and eliminating infectious diseases in children. However, caregivers' hesitancy toward vaccines may lead to insufficient vaccination coverage. Notably, caregivers of children with special health care needs (CSHCN) exhibit a relatively higher level of vaccine hesitancy than caregivers of healthy children. The outbreak of the COVID-19 pandemic may disturb children's immunization. Little is known about the hesitancy of caregivers of CSHCN before, during, and after the COVID-19 pandemic. Objective: To investigate the changes in caregivers’ vaccination hesitation of children with special health care needs (CSHCN) before, during, and after the COVID-19 pandemic in China, and to identify associated factors for caregivers’ attitudes towards National Immunization Program (NIP) and non-NIP vaccines. Methods: We included 7770 caregivers of CSHCN under the age of 18 years who visited the vaccination consultation clinic in the Children’s Hospital, Zhejiang University School of Medicine (Hangzhou, China) from May 2017 to May 2023. General and clinical information was extracted from the immunization evaluation system for CSHCN and medical records. We used Chi-square tests to compare the differences in caregivers’ willingness and hesitation to vaccinate their children across the three stages of the COVID-19 pandemic. Multinomial logistic regression models were employed to identify independent variables associated with caregivers’ willingness and hesitation towards NIP and non-NIP vaccines. Results: During the COVID-19 pandemic, the percentages of choosing NIP, alternative non-NIP, and non-NIP vaccines are higher (26.03%, 57.37%, and 62.73%, respectively) than those at the other two stages. In comparison, caregivers’ hesitation towards NIP and non-NIP vaccines is lowest (16.60% and 37.27%, respectively). Despite the stages of the COVID-19 pandemic, multiple factors, including children’s age and gender, parents’ educational level, comorbidities, and history of allergy, were significantly associated with caregivers’ attitudes towards NIP and non-NIP vaccines (p values<0.05). Conclusions: The present study demonstrated that caregivers’ willingness to vaccinate their CSHCN with NIP and non-NIP vaccines was highest, and their hesitancy was lowest during the COVID-19 pandemic in China. Additionally, we have identified multiple factors associated with caregivers’ willingness and hesitancy to vaccinate their children. These findings provide evidence-based support for developing personalized health education strategies.

Background: Emerging pathogens and zoonotic spillover highlight the need for One Health surveillance to detect outbreaks as early as possible. Participatory surveillance empowers communities to collect data at the source on the health of animals, people, and the environment. Technological advances increase the use and scope of these systems. This initiative sought to collate information from active participatory surveillance systems to better understand parameters collected across the One Health spectrum. Objective: This study aims to develop a compendium of One Health data parameters by examining participatory surveillance systems active in 2023. The expected outcomes of the compendium were to pinpoint specific parameters related to human, animal, and environmental health collected globally by participatory surveillance systems and to detail how each parameter is collected. The compendium was designed to help understand which parameters are currently collected and serve as a reference for future systems and for data standardization initiatives. Methods: Contacts associated with the 60 systems identified through the One Health Participatory Surveillance System Map were invited by email to provide specific data parameters, methodologies used for data collection, and parameter-specific considerations. Information was received from 38 (63%) active systems. Data were compiled into a searchable spreadsheet-based compendium organized into 5 sections: general, livestock, wildlife, environmental, and human parameters. An advisory group comprising experts in One Health participatory surveillance reviewed the collected parameters, refined the compendium structure, and contributed to the descriptive analysis. Results: A comprehensive compendium of data parameters from a diverse array of single-sector and multisector participatory surveillance systems was collated and reviewed. The compendium includes parameters from 38 systems used in Africa (n=3, 8%), Asia (n=9, 24%), Europe (n=12, 32%), Australia (n=3, 8%), and the Americas (n=12, 32%). Almost one-third of the systems (n=11, 29%) collect data across multiple sectors. Many (n=17, 45%) focus solely on human health. Variations in data collection techniques were observed for commonly used parameters, such as demographics and clinical signs or symptoms. Most human health systems collected parameters from a cohort of users tracking their own health over time, whereas many wildlife and environmental systems incorporated event-based parameters. Conclusions: Several participatory surveillance systems have already adopted a One Health approach, enhancing traditional surveillance by identifying shared health threats among animals, people, and the environment. The compendium reveals substantial variation in how parameters are collected, underscoring the need for further work in system interoperability and data standards to allow for timely data sharing across systems during outbreaks. Parameters collated from across the One Health spectrum represent a valuable resource for informing the development of future systems and identifying opportunities to expand existing systems for multisector surveillance.

Background: To address the challenges of population ageing, WHO has made a great effort to promote Age-Friendly Communities Initiatives(AFCIs). Previous researches evaluating Age-Friendly Communities(AFCs) are often associated with negative health outcomes of the elderly. Objective: This study aims to evaluate different living experience of the elderly in the communities which have adopted age-friendly policies, such as the sense of gain, happiness and security, summarize the deficiencies in the process of constructing AFCs in China, and provide some implications to promote AFCIs in the world. Methods: By using a multistage sampling strategy, 470 community residents between rural and urban areas participated in this study. A self-designed questionnaire was designed to use a standardized method to evaluate the elderlys’ living experience and their community’s age-friendliness. Results: In this research, many community residents(81.3%) were not aware of the relevant concepts of AFCs, most participants highlighted the importance of community support and health services. The results also shown that the degree of the sense of security among five dimensions was the highest, while the degree of social support was the lowest, especially the urban elderlys’ evaluation. Meanwhile, there were significant difference in the evaluation of living experiences from different aged residents in urban areas about three dimensions, including the degree of age-friendly(P＜0.001), the degree of social support(P＜0.001), and the sense of gain in community life(P=0.013). Conclusions: China is in the early stages of becoming age-friendly. We further highlight the importance of continued research on multiply support from from the family, communities, and the government to promote AFCIs. These outcomes have a direct and positive impact on the well‐being of older adults.

Background: Infectious diseases (ID) have a significant detrimental impact on global health. Timely and accurate infectious disease forecasting can result in more informed implementation of control measures and prevention policies. Objective: To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. Methods: We forecasted six diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q-fever, Tick-borne Encephalitis, and Tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n = 2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics - prediction accuracy, computational efficiency, spatio-temporal generalizability, uncertainty quantification, and interpretability - which are essential to strategic data-driven decisions. Results: While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pre-trained model from a similar region with a history of that disease. The data visualization dashboard provides an interactive, clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. Conclusions: As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for prevention and mitigation of future ID outbreaks.

Background: Cervical cancer remains a major global health issue. Personalized, data-driven cervical cancer prevention (CCP) strategies tailored to phenotypic profiles may improve prevention and reduce disease burden. Objective: This study aimed to identify subgroups with differential cervical precancer/cancer risks using machine learning, validate subgroup predictions across datasets, and propose a computational phenomapping strategy to enhance global CCP efforts. Methods: We explored the data-driven CCP subgroups by applying unsupervised machine learning to a deeply phenotyped, population-based discovery cohort. We extracted CCP-specific risks of cervical intraepithelial neoplasia (CIN) and cervical cancer, through weighted logistic regression analyses providing odds ratio (OR) estimates and 95% confidence intervals (CI). We trained supervised machine learning model and developed pathways to classify individuals, before evaluating its diagnostic validity and usability on external cohort. Results: This study included 551,934 women (median age 49 years) in the discovery cohort and 47,130 women (37 years) in the external cohort. Phenotyping identified five CCP subgroups, with CCP4 showing the highest carcinoma prevalence. CCP2–4 had significantly higher risks of CIN2+ (CCP2: OR 2.07 [95% CI: 2.03–2.12], CCP3: 3.88 [3.78–3.97], CCP4: 4.47 [4.33–4.63]) and CIN3+ (CCP2: 2.10 [2.05–2.14], CCP3: 3.92 [3.82–4.02], CCP4: 4.45 [4.31–4.61]) compared to CCP1 (P<.001), consistent with the direction of results observed in the external cohort. The proposed triple strategy was validated as clinically relevant, prioritizing high-risk subgroups (CCP3-4) for colposcopies and scaling HPV screening for CCP1-2. Conclusions: This study underscores the potential of leveraging machine learning algorithms and large-scale routine EHRs to enhance cervical cancer prevention strategies. By identifying key determinants of CIN2+/CIN3+ risk and classifying five distinct subgroups, our study provides a robust, data-driven foundation for the proposed triple strategy. This approach prioritizes tailored prevention efforts for subgroups with varying risks, offering a novel and scalable tool to complement existing cervical cancer screening guidelines. Future work should focus on independent external and prospective validation to maximize the global impact of this strategy.

Background: Young men who have sex with men (YMSM) have a higher risk of HIV infection. However, the evidence of HIV incidence from a large cohort was limited in this key population, especially among Chinese YMSM. Objective: This study aimed to investigate the HIV incidence and its associated risk factors among YMSM aged 16-24 years in Tianjin, China. Methods: We conducted the retrospective cohort study among MSM aged 16-24 years from October 2017 to December 2022 through the largest local non-governmental organization (NGO) serving MSM in Tianjin. Participants who responded to the investigations at least two times during the study period were included. They completed questionnaires on their demographic information, sexual behaviors, psychoactive substance use,and sexually transmitted infection status. At the same time, their blood samples were collected for HIV testing. HIV incidence was calculated by dividing the sum of observed HIV seroconversions by the observed person-years (PYs). A Cox proportional hazards regression model was used to identify risk factors of HIV incidence. Results: A total of 1367 HIV-negative YMSM were included in the cohort, 62 seroconversions occurred among them contributing 2384.2 observed person-years, the total incidence was 2.6 (95% CI: 2.0-3.2) per 100 PYs. The segmented HIV incidence was 3.0 (95% CI: 1.5-4.5 ), 2.4 (95% CI: 1.5-3.3), and 2.7 (95% CI: 1.5-3.9) per 100 PYs in 2017-2018, 2019-2020 and 2021-2022, respectively. Compared to YMSM who had been followed up less than three times, those who had been followed up three times and above had a relatively lower risk of HIV infection [Adjusted hazard ratio (AHR)=0.553, 95% CI: 0.325-0.941]. YMSM who preferred to find sexual partners offline had a higher risk of HIV infection compared to those who preferred to find sexual partners online (AHR=2.207, 95% CI:1.198-4.066). Compared to YMSM without syphilis, those infected with syphilis had an increased risk of HIV incidence (AHR=2.234, 95% CI: 1.137-4.391). YMSM who used psychoactive substances had a higher risk of HIV infection compared to those who did not use such substances (AHR=2.467, 95% CI: 1.408-4.321). Conclusions: Our study complements data on HIV incidence among YMSM in large cities in China. Syphilis infection and the use of psychoactive substances were risk factors associated with HIV occurrence, demonstrating an urgent need for tailored prevention and control interventions for this key population.

Background: Well-designed public health messages can help people make informed choices, while poorly designed messages or persuasive messages can confuse, lead to poorly informed decisions, and diminish trust in health authorities and research. Communicating uncertainties to the public about the results of health research is challenging, necessitating research on effective ways to disseminate this important aspect of randomized trials. Objective: This study aimed to evaluate people’s understanding of overall and statistical uncertainty when presented with alternative ways of expressing randomized trial results. Methods: Two parallel, web-based, individually randomized trials (3×2 factorial designs) were conducted in the United States and Norway. Participants were randomized to 1 of 6 versions of a text (summary) communicating results from a study examining the effects of wearing glasses to prevent COVID-19 infection. The summaries varied in how overall uncertainty (“Grading of Recommendations Assessment, Development and Evaluation [GRADE] language,” “plain language,” or “no explicit language”) and statistical uncertainty (whether a margin of error was shown or not) were presented. Participants completed a web-based questionnaire exploring 4 coprimary outcomes: 3 to measure understanding of overall uncertainty (benefits, harms, and sufficiency of evidence), and one to measure statistical uncertainty. Participants were adults who do not wear glasses recruited from web-based research panels in the United States and Norway. Results of the trials were analyzed separately and combined in a meta-analysis. Results: In the US and Norwegian trials, 730 and 497 individuals were randomized, respectively; data for 543 (74.4%) and 452 (90.9%) were analyzed. More participants had a correct understanding of uncertainty when presented with plain language (United States: 37/99, 37% and Norway: 40/76, 53%) than no explicit language (United States: 18/86, 21% and Norway: 34/80, 42%). Similar positive effect was seen for the GRADE language in the United States (26/79, 33%) but not in Norway (30/71, 42%). There were only small differences between groups for understanding the uncertainty of harms. Plain language improved correct understanding of evidence sufficiency (odds ratio 2.05, 95% CI 1.17-3.57), compared to no explicit language. The effect of GRADE language was inconclusive (odds ratio 1.34, 95% CI 0.79-2.28). The understanding of statistical uncertainty was improved when the participants were shown the margin of error compared to not being shown: Norway: 16/75, 21% to 24/71, 34% vs 1/71, 1% to 2/76, 3% and the United States: 21/101, 21% to 32/90, 36% vs 0/86, 0% to 3/79, 4%). Conclusions: Plain language, but not GRADE language, was better than no explicit language in helping people understand overall uncertainty of benefits and harms. Reporting margin of error improved understanding of statistical uncertainty around the effect of wearing glasses, but only for a minority of participants. Trial Registration: ClinicalTrials.gov NCT05642754; https://tinyurl.com/4mhjsm7s