JMIR Public Health and Surveillance最新文献

{"title":"Molecular Transmission Clustering and Pretreatment Drug Resistance Among Men Infected With HIV-1 Who Have Sex With Men in Baotou, China: A Cross-Sectional Subgroup Analysis.","authors":"Hanping Li, Yu Liu, Hong Yang, Jiao Wu, Ziwei Liu, Baobao Bai, Yongjian Liu, Lei Jia, Jingwan Han, Bohan Zhang, Xiaolin Wang, Xiangchun Li, Lin Li","doi":"10.2196/82208","DOIUrl":"https://doi.org/10.2196/82208","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>We analyzed factors associated with molecular transmission clustering and pretreatment drug resistance (PDR) among newly reported HIV-1-infected MSM in Baotou, China, and to provide locally relevant evidence for targeted public health interventions.</p><p><strong>Methods: </strong>We conducted a subgroup cross-sectional molecular epidemiological analysis of all newly reported HIV-1 cases attributed to homosexual transmission in Baotou between January 2022 and December 2024. The sample comprised 213 treatment-naïve MSM, from whom plasma samples were obtained. A 1.3-kb fragment of the HIV-1 pol gene was amplified and sequenced using next-generation sequencing. Inclusion criteria were a newly reported HIV-1 infection, no antiretroviral therapy at the time of this writing, and self-reported same-sex sexual behavior. Primary outcomes were clustering in a genetic distance-based molecular transmission network and the presence of PDR according to the Stanford HIV Drug Resistance Database.</p><p><strong>Results: </strong>In total, 176 pol gene sequences were successfully obtained, with circulating recombinant form (CRF)-07_BC being the most prevalent subtype, accounting for 56.82% of the total sequences. The molecular transmission network was constructed using a pairwise genetic distance of 1.30%, with 52 of 176 (29.55%) sequences forming 19 clusters within the network. The network exhibited significant assortative mixing by age (ra=0.41; <i>P</i>=.001), marital status (ra=0.408; <i>P</i>=.002), and educational attainment (ra=0.385; <i>P</i>=.001), rather than random mixing. Multivariate logistic regression analysis revealed that CRF07_BC subtype-infected individuals had a significantly higher risk of clustering (AOR 4.98; 95% CI 1.92-12.94; <i>P</i><.01). Compared to never-married individuals, divorced or widowed individuals were less likely to have clustered cases (AOR 0.27; 95% CI 0.08-0.92; <i>P</i><.05). The prevalence of PDR was 6.57% (n=14). Nonnucleoside reverse transcriptase inhibitor resistance was the most common (n=8, 3.76%), followed by protease inhibitor resistance (n=5, 2.35%), and nucleoside reverse transcriptase inhibitor resistance (n=3, 1.14%). Drug-resistant strains were more frequently detected among individuals infected with the CRF07_BC subtype (<i>χ</i><sup>2</sup><sub>8</sub>=90.44; <i>P<</i>.001).</p><p><strong>Conclusions: </strong>Unlike previous studies primarily focused on high-burden southeastern coastal regions of China, we investigated the molecular transmission characteristics of HIV-1 among MSM in the Inner Mongolia Autonomous Region. Our findings demonstrate that transmission clustering and drug resistance patterns previously observed are als","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e82208"},"PeriodicalIF":4.4,"publicationDate":"2026-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149357450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Pilot Surveillance Program to Identify Emerging SARS-CoV-2 Variants in International Travelers Arriving at a Major International Airport: Prospective Cohort Evaluation.","authors":"Eric M Foote, Ellen L Bouchard, Elizabeth F Baylis, Shiffen Getabecha, Phacharee Arunleung, Maria Salas, Gautham Gautham, Christina Morales, Debra A Wadford, Kathleen Jacobson","doi":"10.2196/96414","DOIUrl":"10.2196/96414","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This paper aimed to describe a pilot surveillance program to identify SARS-CoV-2 variants in arriving international travelers at San Francisco International Airport (SFO).</p><p><strong>Methods: </strong>The California Department of Public Health implemented a pilot program at SFO to voluntarily test arriving international travelers for COVID-19 from June 2021 to November 2021 to identify SARS-CoV-2 variants. Arriving international travelers were offered self-collect COVID-19 antigen tests upon arrival at SFO. Travelers with positive COVID-19 antigen tests or with COVID-19 symptoms were recommended to self-collect and mail an additional specimen for diagnostic molecular testing. WGS of SARS-CoV-2 was performed on RNA extracts from positive tests to identify variants.</p><p><strong>Results: </strong>In total, 2.1% (19,008/892,558) of all arriving international travelers at SFO from 133 different countries of departure enrolled in the program. The COVID-19 test positivity among this group was 0.7% (33/5038), and the weekly test positivity range, 0% to 1.5%, was lower than the weekly test positivity across the state of California during the same time frame. Arriving international travelers departing from Turkey (3/145, 2.1%), Mexico (7/602, 1.2%), and the United Kingdom (6/626, 1.0%) had the highest test positivity. Of the 14 positive molecular tests, 10 (71.4%) were sequenced, and all were found to belong to the SARS-CoV-2 Delta B.1.617.2 lineage, the most prevalent SARS-CoV-2 variant in California and worldwide at the time.</p><p><strong>Conclusions: </strong>Voluntary testing of arriving international travelers paired with WGS was operationally and logistically feasible. Although the number of sequenced positive COVID-19 specimens in this program was limited, the lessons learned from this pilot informed improvements to subsequent iterations of traveler viral genomic surveillance in California and highlighted the potential value of traveler viral genomic surveillance to support early identification and characterization of emerging infectious diseases entering a region.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e96414"},"PeriodicalIF":4.4,"publicationDate":"2026-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13743065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149357449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Community Risk, Mobility Patterns, and COVID-19 Hospitalization Risk in Texas: ZIP Code-Level Ecological Longitudinal Study.","authors":"Jose Herrera-Diestra, Dongah Kim, Shraddha Ramdas Bandekar, Emily Javan, Spencer J Fox, Remy Pasco, Lauren Ancel Meyers","doi":"10.2196/97405","DOIUrl":"10.2196/97405","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study assessed how community-level risk shapes heterogeneity in precautionary mobility behavior within cities and whether these differences are associated with subsequent COVID-19 hospitalization risk.</p><p><strong>Methods: </strong>We analyzed anonymized mobile device data from 623 ZIP codes in the 20 most populous counties in Texas and COVID-19 hospitalization records comprising 65,474 hospital admissions from 620 ZIP codes (February-July 2020). We constructed a ZIP code-level measure of precautionary mobility reduction (PMR) and linked it to a composite community risk score derived from US Centers for Disease Control and Prevention social vulnerability indicators. Generalized additive mixed models estimated associations among community risk, mobility patterns, and weekly hospitalization rates, adjusting for epidemic timing, population size, and spatial clustering.</p><p><strong>Results: </strong>Mobility declined by approximately 73% relative to baseline following statewide stay-at-home orders but varied substantially across ZIP codes. On April 2, 2020, PMR was negatively associated with community risk (slope -0.16, 95% CI -0.19 to -0.13; <i>P</i><.001). At peak divergence, high-risk ZIP codes reduced mobility by 12 to 13 percentage points less than low-risk ZIP codes (95% CI 11 to 15). Greater PMR was associated with lower subsequent hospitalization risk (incidence rate ratio [IRR] 0.41, 95% CI 0.31 to 0.53; <i>P</i><.001), whereas higher community risk was associated with increased hospitalization risk (IRR 3.03, 95% CI 2.57 to 3.58; <i>P</i><.001). The protective association of mobility reduction was attenuated in higher-risk communities (interaction IRR 2.79, 95% CI 2.08 to 3.73; <i>P</i><.001).</p><p><strong>Conclusions: </strong>Mobility data can support real-time surveillance of behavioral responses during epidemics. Within-city differences in mobility reduction were associated with subsequent hospitalization risk, but their protective association was weaker in higher-risk communities. Integrating digital mobility data with community risk metrics may improve targeted and equitable public health responses.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e97405"},"PeriodicalIF":4.4,"publicationDate":"2026-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13734555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149333963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Individual-Level Syndromic Surveillance Data Into Infectious Disease Modeling for COVID-19 Forecasting in Sweden: Comparative Modeling Study.","authors":"Shomaila Mazhar, Jonas Björk, Dominik Dietler","doi":"10.2196/104804","DOIUrl":"https://doi.org/10.2196/104804","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to evaluate the effect of integrating syndromic surveillance data on short-term COVID-19 forecast accuracy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed a novel epidemiological model named SI&lt;sub&gt;s&lt;/sub&gt;I&lt;sub&gt;c&lt;/sub&gt;HRD (susceptible-infected&lt;sub&gt;suspected&lt;/sub&gt;-infected&lt;sub&gt;confirmed&lt;/sub&gt; -hospitalized-recovered-deceased), incorporating data from the 1177 health care helpline cross-linked with national registers on COVID-19 testing, hospitalizations, and deaths. In the novel model, the population with infection is divided into suspected infections (I&lt;sub&gt;s&lt;/sub&gt;; those reporting symptoms to 1177) and confirmed infections (I&lt;sub&gt;c&lt;/sub&gt;; those who tested positive). Accuracy metrics of this model are compared to a model without data from the 1177 health care helpline. To evaluate model performance across different pandemic phases between March 2 and December 31, 2020, we used a daily rolling-window approach with a 60-day fitting period to predict confirmed infections, hospitalizations, and deaths over the subsequent 30 days. Prediction performance was evaluated using mean absolute error and mean absolute percentage error (MAPE).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The proposed SI&lt;sub&gt;s&lt;/sub&gt;I&lt;sub&gt;c&lt;/sub&gt;HRD model successfully captured the temporal dynamics of confirmed, hospitalized, and death cases. The model achieved a median mean MAPE of 61.6% (IQR 37.6%-79.6%) for confirmed cases, 37.5% (IQR 18.9%-57.5%) for hospitalizations and for deaths, the model achieved a median MAPE of 0.65% (IQR 0.3%-1.9%), indicating substantially higher predictive accuracy for severe outcomes compared to confirmed infections and hospital admissions. Compared to the model without syndromic surveillance data, short-term forecasting performance of the SI&lt;sub&gt;s&lt;/sub&gt;I&lt;sub&gt;c&lt;/sub&gt;HRD model reduced MAPE by an average of 15.7 percentage points for confirmed cases, 8.17 percentage points for hospitalizations, and 1.99 percentage points for deaths. Overall, the results demonstrate predictive stability for severe outcomes during the early phase of the pandemic.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The proposed model demonstrated predictive performance by integrating individual-level data with health care helpline syndromic data on testing and severe disease outcomes, capturing early signals from symptomatic individuals and distinguishing suspected cases from ","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e104804"},"PeriodicalIF":4.4,"publicationDate":"2026-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149297547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age-Specific Pertussis Transmission Dynamics and Impact of Immunization Schedule Revision in Hunan, China: Age-Structured Mathematical Modeling Study.","authors":"Yue He, Ziyan Liu, Yanhua Yang, Kangguo Li, Yao Wang, Yuqing Wu, Zheni Bu, Yuyang Liu, Yanhua Su, Qiuping Chen, Zeyu Zhao, Jia Rui, Kaiwei Luo, Tianmu Chen","doi":"10.2196/104376","DOIUrl":"https://doi.org/10.2196/104376","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to characterize the shifting age-specific transmission dynamics of Bordetella pertussis under changing immunization landscapes and evaluate the population-level impact of the 2025 Chinese immunization schedule.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;An age-structured Vaccinated-Susceptible-Exposed-Infectious-Recovered model incorporating vaccination, waning immunity, and demographic structures was calibrated using surveillance data from Hunan Province (2010-2025). The next-generation matrix approach estimated the effective reproduction numbers across 5 epidemic phases. Multiscenario simulations were used to assess the impact of a 6-year booster dose at varying coverage levels.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among 47,300 reported cases (2010-2025), a marked resurgence peaked at 6743 cases in April 2024, with consistent spring seasonality. The case distribution shifted from infant-dominated (0-6 months: 293/552, 53.07%, 2010-2017) to school-age-dominated (6-10 years: 9814/30,589, 32.08%, 2024-2025). This study period was stratified into 5 temporal phases based on the epidemic dynamics: phase 1 (2010-2017), phase 2 (2018-2019), phase 3 (2020-2023), phase 4 (2024), and phase 5 (2025). Segmented fitting analyses were conducted for monthly pertussis cases across age groups within each phase of this study. The model demonstrated high fitting consistency across all age groups, with an overall R&lt;sup&gt;2&lt;/sup&gt; of 0.96. Adults emerged as the dominant transmission source in 2023-2024 (R&lt;sub&gt;eff&lt;/sub&gt; to infants: 2.717). A booster administered at the age of 6 years with full coverage is expected to decrease the 10-year cumulative incidence by 24.15% (24,972.58/103,408.95). Children between 6 and 10 years of age are expected to experience the most significant monthly decrease, at 45.06% (335.49/744.51), whereas infants are predicted to gain 28.91% (170.92/591.19) indirect protection.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Pertussis resurgence is driven by age-structured heterogeneity and waning immunity. Administering a booster shot to children at the age of 6 years can reduce the spread of infections across different age groups and offer indirect protection to infants who are at high risk. However, for long-term control, it may be necessary to implement broader strategies that involve vaccinating adol","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e104376"},"PeriodicalIF":4.4,"publicationDate":"2026-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149286988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geo-Analytic Decision Support for Federal Behavioral Health Prioritization Among American Indian and Alaska Native Populations: Exploratory Study.","authors":"David M Paschane, Michael Ontiveros, John E Snyder","doi":"10.2196/87265","DOIUrl":"10.2196/87265","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study aims to identify candidate federal priorities for intergovernmental and interagency cooperation using exploratory geo-analytic decision-support frameworks, specifically related to behavioral health risks and services among tribal populations.</p><p><strong>Methods: </strong>We tested illustrative federal decision parameters within 3 exploratory geo-analytic frameworks using publicly available US data. These included alcohol-related and drug-related mortality data from 2018 to 2023 from the Centers for Disease Control and Prevention (CDC); facility locations, operating hours, and Euclidean-distance approximations of physical access to behavioral health services from the Indian Health Service (IHS); and federal transportation and rest stop data used to examine hypothesized interpersonal-risk conditions. Analyses were performed from February through August 2025.</p><p><strong>Results: </strong>The exploratory analyses identified 78 counties across 13 states as prioritized investigation areas based on elevated and increasing alcohol-related or drug-related death rates. The 6-year pooled crude death rates ranged from 1197.8 to 1848.7 per 100,000 American Indian or Alaska Native (AI/AN) persons. Two regional analyses demonstrated methods for further prioritization. One analysis estimated that 22,029 and 234,852 AI/AN persons resided in low physical access areas for services during typical and nontypical business hours, respectively. Another analysis identified 12 potential interpersonal risk-exposure locations within a region of 28 rest stop facilities among 80 AI/AN communities.</p><p><strong>Conclusions: </strong>Three exploratory geo-analytic frameworks demonstrate methodological feasibility for identifying candidate geographic priorities that could inform federal-tribal and interagency investigations, service access barriers, and interpersonal risk events. The recommendation is to validate and expand the methodology with rural and tribal systems, leading to a candidate federal decision-support model for future interagency initiatives.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e87265"},"PeriodicalIF":4.4,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13706252/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149267614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal Patterns of Multimorbidity Progression Among Inpatients With a Recorded Hypertension Diagnosis Across Three Counties in Rural Henan, China: Retrospective Cohort Study Using Temporal Network Analysis.","authors":"Yifei Wang, Yanna Mao, Xi Wang, Rongmei Liu, Manman Cui, Ruihua Feng","doi":"10.2196/93217","DOIUrl":"10.2196/93217","url":null,"abstract":"<p><strong>Background: </strong>Hypertension is a key driver of multimorbidity; however, its role in shaping dynamic disease progression, especially in rural populations, remains underexplored.</p><p><strong>Objective: </strong>This study aimed to characterize temporal patterns of multimorbidity progression among inpatients with a recorded hypertension diagnosis and to examine whether these patterns differed by sex, age, insurance type, and county.</p><p><strong>Methods: </strong>We analyzed electronic health record data from 34,099 inpatients with a recorded hypertension diagnosis across 3 rural counties in Henan, China (2019-2023), constructing a temporal comorbidity network of 250 disease nodes and 1512 disease transitions. Statistical validation was performed using bootstrap resampling, case-dropping, and permutation tests. Subgroup analyses were conducted by sex, age, insurance type, and county.</p><p><strong>Results: </strong>The temporal comorbidity network revealed a densely interconnected core involving hypertension, atherosclerotic heart disease, and cerebral infarction, with type 2 diabetes occupying a bridging position between cardiovascular and multisystem disease clusters. The ordering of dominant recorded pathways differed by sex (earlier coronary involvement among female inpatients vs more direct progression to stroke among male inpatients), was more complex in inpatients older than 70 years of age, and was more diffuse among those covered by urban-rural resident insurance compared with urban employee insurance.</p><p><strong>Conclusions: </strong>Multimorbidity among inpatients with recorded hypertension followed structured and heterogeneous temporal patterns that differed by sex, age, insurance type, and county. Cardiovascular and cerebrovascular conditions formed the principal recorded progression pathways, while type 2 diabetes connected cardiovascular pathways with broader multisystem complications. These findings support further evaluation of risk-stratified and locally adapted approaches to chronic disease prevention and longitudinal care.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e93217"},"PeriodicalIF":4.4,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13693825/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149244505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public Awareness, Attitudes, and Practices Toward Digital Health Surveillance in Malawi: Cross-Sectional Study.","authors":"Patricia Kamanga, Jeremot Masoambeta, Vincent Kamforzi, Bertha Banda Kayuni, Isaach Ndemera, Chriswell Nkoloma, Lusungu Chisesa, Atusaye Mwalwanda, Selemani Ngwira, Hope Kalichero, Alex Thawani, Robina Chirwa Vokhiwa, Dzinkambani Kambalame, Hamdan Saidi, Peter Salilika, Tsung-Shu Joseph Wu","doi":"10.2196/91033","DOIUrl":"10.2196/91033","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>The aim of the study was to assess the awareness, attitudes, and practices of adult Malawians toward digital surveillance during pandemics and epidemics.</p><p><strong>Methods: </strong>A cross-sectional quantitative study design was used. Data were collected in 10 selected districts (Chitipa, Mzimba South, Kasungu, Lilongwe, Salima, Balaka, Thyolo, Phalombe, Blantyre, and Chikwawa) of Malawi that had high and low levels of cholera and COVID-19 disease burden. The survey recruited 1174 participants who were 18 years or older at the time of data collection. Descriptive statistics were computed using R statistical software. Ethical approval was obtained from the National Health Sciences Research Committee prior to data collection.</p><p><strong>Results: </strong>A total of 1174 participants were surveyed, 65% (n=768) were female, and the mean age was 36.9 (SD 14.26) years. Only 59% (n=697) demonstrated awareness of digital surveillance systems, though 51% (n=603) had smartphones and 41% (n=477) used mobile phones. A positive attitude was observed in 89% (n=1044) of respondents, with most believing digital reporting could improve outbreak control, and 80% (n=939) were confident in privacy and data security. Practices related to digital reporting were low, with only 18% (n=211) having ever reported health symptoms through any digital platform.</p><p><strong>Conclusions: </strong>Enhancing digital health surveillance literacy, promoting inclusivity, and ensuring accountability will improve readiness for future pandemics through digital surveillance systems. Hence, there is a need for nationwide community sensitization programs to raise awareness about the benefits of digital health surveillance.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e91033"},"PeriodicalIF":4.4,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13690335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149244495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Over-the-Counter Retail Medication Sales to Detect and Track Influenza-Like Illnesses Including Novel Diseases: Surveillance Modeling Study.","authors":"Ye Ye, Jessi Espino, John M Aronis, Harry Hochheiser, Marian G Michaels, Gregory F Cooper","doi":"10.2196/91163","DOIUrl":"10.2196/91163","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study evaluated the use of NRDM data for detecting and tracking influenza-like illness (ILI), including purchasing patterns suggestive of novel disease outbreaks.</p><p><strong>Methods: </strong>NRDM data from Allegheny County, Pennsylvania, collected between 2016 and 2021, were analyzed using a probabilistic modeling framework to estimate daily ILI activity from OTC purchasing patterns. An expectation-maximization algorithm was applied to data from the training period (June 2016-May 2019) to estimate conditional probabilities of OTC product purchases under ILI and non-ILI conditions. These estimates were then applied to daily sales data from the test period (June 2019-December 2021) to infer daily ILI counts. The framework was further extended into a monitoring system, termed NRDM Tracker, which uses daily log-likelihoods and false discovery rate-adjusted <i>P</i> values to detect statistically significant anomalies in purchasing behavior.</p><p><strong>Results: </strong>NRDM-derived ILI estimates were moderately correlated with emergency department (ED)-based ILI counts (<i>r</i>=0.66). Compared with other OTC product categories (eg, thermometers and antifever medications), cough and cold medications showed the strongest association with ILI-related purchasing behavior and higher estimated purchase probability under ILI conditions (0.792) than under non-ILI conditions (0.695). During the early phase of the COVID-19 pandemic in March 2020 in Allegheny County, when COVID-19 testing capacity was limited and public awareness and health-seeking behaviors were rapidly evolving, NRDM-based ILI signals increased before corresponding rises in confirmed ED-based COVID-19 counts. Moreover, NRDM Tracker identified significant anomalies in OTC purchasing behavior during major outbreak periods, including a pronounced decline in log-likelihood in March 2020 corresponding to the onset of the COVID-19 pandemic. Multiple product categories exhibited statistically significant deviations in sales during these periods.</p><p><strong>Conclusions: </strong>OTC product sales data, analyzed using probabilistic modeling and anomaly detection methods, can provide timely insights into population-level health activity and may help identify anomalies associated with emerging disease outbreaks. NRDM-based surveillance systems may complement traditional clinical surveillance and strengthen local and national biosurveillance capabilities.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e91163"},"PeriodicalIF":4.4,"publicationDate":"2026-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13686242/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149238411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiological Characteristics and Incidence Trends of Hemorrhagic Fever With Renal Syndrome in Shandong Province, China: Retrospective Observational Study With Forecasting.","authors":"Qing Duan, Ti Liu, Yinlong Li, Suying Guo, Shiyi Huang, Jing Xu, Ruixiao Li, Zengqiang Kou","doi":"10.2196/99524","DOIUrl":"10.2196/99524","url":null,"abstract":"<p><strong>Background: </strong>Hemorrhagic fever with renal syndrome (HFRS) is a severe natural focal infectious disease that remains a major public health concern in Shandong Province, China. Understanding the epidemiological characteristics of HFRS and forecasting its incidence are crucial to provide guidance for policymaking and implement timely interventions against this disease.</p><p><strong>Objective: </strong>This study examined the long-term epidemiological characteristics of HFRS based on 15 years of surveillance data; the analysis used 4 time series models to predict its incidence trends. The aim was to provide a scientific basis for local disease control departments, thereby supporting more accurate prediction and effective prevention and control of HFRS in this region.</p><p><strong>Methods: </strong>HFRS case surveillance data in Shandong Province from 2010 to 2024 were collected through the China Information System for Disease Control and Prevention. Descriptive epidemiological methods were used to analyze the basic characteristics of HFRS. Four forecasting models, namely, seasonal autoregressive integrated moving average, Prophet, the Holt-Winters exponential smoothing method, and Extreme Gradient Boosting, were implemented in R to fit the time series and generate predictions. Their predictive performance was evaluated and compared using the root mean squared error, mean absolute error, and mean absolute percentage error.</p><p><strong>Results: </strong>From 2010 to 2024, a total of 15,184 HFRS cases were reported in Shandong Province, with 188 deaths. The annual incidence rate ranged from 0.45 to 1.84 per 100,000 population, showing an overall fluctuating downward trend. The peak incidence occurred during the autumn and winter months from October to December each year. Spatially, the eastern and southeastern regions of Shandong Province were the primary high-incidence areas. Demographically, the high-risk populations were mainly middle-aged and older adults, male individuals, and farmers. In the 2024 test set, the Holt-Winters model yielded the lowest prediction error metrics among the 4 models, with root mean squared error, mean absolute error, and mean absolute percentage error values of 7.56, 6.43, and 34.56%, respectively.</p><p><strong>Conclusions: </strong>The Holt-Winters model showed the lowest prediction error metrics among the 4 models, suggesting its potential utility for forecasting HFRS incidence. It is recommended to apply this model to enhance precise monitoring and implement targeted prevention and control measures focusing on key areas, peak periods, and high-risk populations.</p>","PeriodicalId":14765,"journal":{"name":"JMIR Public Health and Surveillance","volume":"12 ","pages":"e99524"},"PeriodicalIF":4.4,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13722926/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149206856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}