@Article{info:doi/10.2196/59217,
author="Mandel, L. Hannah
and Shah, N. Shruti
and Bailey, Charles L.
and Carton, Thomas
and Chen, Yu
and Esquenazi-Karonika, Shari
and Haendel, Melissa
and Hornig, Mady
and Kaushal, Rainu
and Oliveira, R. Carlos
and Perlowski, A. Alice
and Pfaff, Emily
and Rao, Suchitra
and Razzaghi, Hanieh
and Seibert, Elle
and Thomas, L. Gelise
and Weiner, G. Mark
and Thorpe, E. Lorna
and Divers, Jasmin
and ",
title="Opportunities and Challenges in Using Electronic Health Record Systems to Study Postacute Sequelae of SARS-CoV-2 Infection: Insights From the NIH RECOVER Initiative",
journal="J Med Internet Res",
year="2025",
month="Mar",
day="5",
volume="27",
pages="e59217",
keywords="COVID-19",
keywords="SARS-CoV-2",
keywords="Long COVID, post-acute COVID-19 syndrome",
keywords="electronic health records",
keywords="machine learning",
keywords="public health surveillance",
keywords="post-infection syndrome",
keywords="medical informatics",
keywords="electronic medical record",
keywords="electronic health record network",
keywords="electronic health record data",
keywords="clinical research network",
keywords="clinical data research network",
keywords="common data model",
keywords="digital health",
keywords="infection",
keywords="respiratory",
keywords="infectious",
keywords="epidemiological",
keywords="pandemic",
doi="10.2196/59217",
url="https://www.jmir.org/2025/1/e59217",
url="http://www.ncbi.nlm.nih.gov/pubmed/40053748"
}


@Article{info:doi/10.2196/57457,
author="Iera, Jessica
and Isonne, Claudia
and Seghieri, Chiara
and Tavoschi, Lara
and Ceparano, Mariateresa
and Sciurti, Antonio
and D'Alisera, Alessia
and Sane Schepisi, Monica
and Migliara, Giuseppe
and Marzuillo, Carolina
and Villari, Paolo
and D'Ancona, Fortunato
and Baccolini, Valentina",
title="Availability and Key Characteristics of National Early Warning Systems for Emerging Profiles of Antimicrobial Resistance in High-Income Countries: Systematic Review",
journal="JMIR Public Health Surveill",
year="2025",
month="Jan",
day="15",
volume="11",
pages="e57457",
keywords="early warning system",
keywords="surveillance",
keywords="emerging AMR",
keywords="high-income countries",
keywords="antimicrobial resistance",
abstract="Background: The World Health Organization (WHO) recently advocated an urgent need for implementing national surveillance systems for the timely detection and reporting of emerging antimicrobial resistance (AMR). However, public information on the existing national early warning systems (EWSs) is often incomplete, and a comprehensive overview on this topic is currently lacking. Objective: This review aimed to map the availability of EWSs for emerging AMR in high-income countries and describe their main characteristics. Methods: A systematic review was performed on bibliographic databases, and a targeted search was conducted on national websites. Any article, report, or web page describing national EWSs in high-income countries was eligible for inclusion. EWSs were identified considering the emerging AMR-reporting WHO framework. Results: We identified 7 national EWSs from 72 high-income countries: 2 in the East Asia and Pacific Region (Australia and Japan), 3 in Europe and Central Asia (France, Sweden, and the United Kingdom), and 2 in North America (the United States and Canada). The systems were established quite recently; in most cases, they covered both community and hospital settings, but their main characteristics varied widely across countries in terms of the organization and microorganisms under surveillance, with also different definitions of emerging AMR and alert functioning. A formal system assessment was available only in Australia. Conclusions: A broader implementation and investment of national surveillance systems for the early detection of emerging AMR are still needed to establish EWSs in countries and regions lacking such capabilities. More standardized data collection and reporting are also advisable to improve cooperation on a global scale. Further research is required to provide an in-depth analysis of EWSs, as this study is limited to publicly available data in high-income countries. ",
doi="10.2196/57457",
url="https://publichealth.jmir.org/2025/1/e57457"
}


@Article{info:doi/10.2196/56495,
author="Rohrer, Rebecca
and Wilson, Allegra
and Baumgartner, Jennifer
and Burton, Nicole
and Ortiz, R. Ray
and Dorsinville, Alan
and Jones, E. Lucretia
and Greene, K. Sharon",
title="Nowcasting to Monitor Real-Time Mpox Trends During the 2022 Outbreak in New York City: Evaluation Using Reportable Disease Data Stratified by Race or Ethnicity",
journal="Online J Public Health Inform",
year="2025",
month="Jan",
day="14",
volume="17",
pages="e56495",
keywords="data quality",
keywords="epidemiology",
keywords="forecasting",
keywords="infectious disease",
keywords="morbidity and mortality trends",
keywords="mpox",
keywords="nowcasting",
keywords="public health practice",
keywords="surveillance",
abstract="Background: Applying nowcasting methods to partially accrued reportable disease data can help policymakers interpret recent epidemic trends despite data lags and quickly identify and remediate health inequities. During the 2022 mpox outbreak in New York City, we applied Nowcasting by Bayesian Smoothing (NobBS) to estimate recent cases, citywide and stratified by race or ethnicity (Black or African American, Hispanic or Latino, and White). However, in real time, it was unclear if the estimates were accurate. Objective: We evaluated the accuracy of estimated mpox case counts across a range of NobBS implementation options. Methods: We evaluated NobBS performance for New York City residents with a confirmed or probable mpox diagnosis or illness onset from July 8 through September 30, 2022, as compared with fully accrued cases. We used the exponentiated average log score (average score) to compare moving window lengths, stratifying or not by race or ethnicity, diagnosis and onset dates, and daily and weekly aggregation. Results: During the study period, 3305 New York City residents were diagnosed with mpox (median 4, IQR 3-5 days from diagnosis to diagnosis report). Of these, 812 (25\%) had missing onset dates, and of these, 230 (28\%) had unknown race or ethnicity. The median lag in days from onset to onset report was 10 (IQR 7-14). For daily hindcasts by diagnosis date, the average score was 0.27 for the 14-day moving window used in real time. Average scores improved (increased) with longer moving windows (maximum: 0.47 for 49-day window). Stratifying by race or ethnicity improved performance, with an overall average score of 0.38 for the 14-day moving window (maximum: 0.57 for 49 day-window). Hindcasts for White patients performed best, with average scores of 0.45 for the 14-day window and 0.75 for the 49-day window. For unstratified, daily hindcasts by onset date, the average score ranged from 0.16 for the 42-day window to 0.30 for the 14-day window. Performance was not improved by weekly aggregation. Hindcasts underestimated diagnoses in early August after the epidemic peaked, then overestimated diagnoses in late August as the epidemic waned. Estimates were most accurate during September when cases were low and stable. Conclusions: Performance was better when hindcasting by diagnosis date than by onset date, consistent with shorter lags and higher completeness for diagnoses. For daily hindcasts by diagnosis date, longer moving windows performed better, but direct comparisons are limited because longer windows could only be assessed after case counts in this outbreak had stabilized. Stratification by race or ethnicity improved performance and identified differences in epidemic trends across patient groups. Contributors to differences in performance across strata might include differences in case volume, epidemic trends, delay distributions, and interview success rates. Health departments need reliable nowcasting and rapid evaluation tools, particularly to promote health equity by ensuring accurate estimates within all strata. ",
doi="10.2196/56495",
url="https://ojphi.jmir.org/2025/1/e56495"
}


@Article{info:doi/10.2196/60022,
author="Atchison, J. Christina
and Gilby, Nicholas
and Pantelidou, Galini
and Clemens, Sam
and Pickering, Kevin
and Chadeau-Hyam, Marc
and Ashby, Deborah
and Barclay, S. Wendy
and Cooke, S. Graham
and Darzi, Ara
and Riley, Steven
and Donnelly, A. Christl
and Ward, Helen
and Elliott, Paul",
title="Strategies to Increase Response Rate and Reduce Nonresponse Bias in Population Health Research: Analysis of a Series of Randomized Controlled Experiments during a Large COVID-19 Study",
journal="JMIR Public Health Surveill",
year="2025",
month="Jan",
day="9",
volume="11",
pages="e60022",
keywords="study recruitment",
keywords="response rate",
keywords="population-based research",
keywords="COVID-19",
keywords="SARS-CoV-2",
keywords="web-based questionnaires",
abstract="Background: High response rates are needed in population-based studies, as nonresponse reduces effective sample size and bias affects accuracy and decreases the generalizability of the study findings. Objective: We tested different strategies to improve response rate and reduce nonresponse bias in a national population--based COVID-19 surveillance program in England, United Kingdom. Methods: Over 19 rounds, a random sample of individuals aged 5 years and older from the general population in England were invited by mail to complete a web-based questionnaire and return a swab for SARS-CoV-2 testing. We carried out several nested randomized controlled experiments to measure the impact on response rates of different interventions, including (1) variations in invitation and reminder letters and SMS text messages and (2) the offer of a conditional monetary incentive to return a swab, reporting absolute changes in response and relative response rate (95\% CIs). Results: Monetary incentives increased the response rate (completed swabs returned as a proportion of the number of individuals invited) across all age groups, sex at birth, and area deprivation with the biggest increase among the lowest responders, namely teenagers and young adults and those living in more deprived areas. With no monetary incentive, the response rate was 3.4\% in participants aged 18?22 years, increasing to 8.1\% with a {\textsterling}10 (US \$12.5) incentive, 11.9\% with {\textsterling}20 (US \$25.0), and 18.2\% with {\textsterling}30 (US \$37.5) (relative response rate 2.4 [95\% CI 2.0-2.9], 3.5 [95\% CI 3.0-4.2], and 5.4 [95\% CI 4.4-6.7], respectively). Nonmonetary strategies had a modest, if any, impact on response rate. The largest effect was observed for sending an additional swab reminder (SMS text message or email). For example, those receiving an additional SMS text message were more likely to return a completed swab compared to those receiving the standard email-SMS approach, 73.3\% versus 70.2\%: percentage difference 3.1\% (95\% CI 2.2\%-4.0\%). Conclusions: Conditional monetary incentives improved response rates to a web-based survey, which required the return of a swab test, particularly for younger age groups. Used in a selective way, incentives may be an effective strategy for improving sample response and representativeness in population-based studies. ",
doi="10.2196/60022",
url="https://publichealth.jmir.org/2025/1/e60022"
}


@Article{info:doi/10.2196/55376,
author="Swets, C. Maaike
and Kerr, R. Steven
and MacKenna, Brian
and Fisher, Louis
and van Wijnen, Merel
and Brandwagt, Diederik
and Schenk, W. Paul
and Fraaij, Pieter
and Visser, G. Leonardus
and Bacon, Sebastian
and Mehrkar, Amir
and Nichol, Alistair
and Twomey, Patrick
and Matthews, C. Philippa
and 
and Semple, G. Malcolm
and Groeneveld, H. Geert
and Goldacre, Ben
and Jones, Iain
and Baillie, Kenneth J.",
title="Using Laboratory Test Results for Surveillance During a New Outbreak of Acute Hepatitis in 3-Week- to 5-Year-Old Children in the United Kingdom, the Netherlands, Ireland, and Cura{\c{c}}ao: Observational Cohort Study",
journal="JMIR Public Health Surveill",
year="2024",
month="Dec",
day="23",
volume="10",
pages="e55376",
keywords="pediatric hepatitis",
keywords="disease surveillance",
keywords="outbreak detection",
keywords="pandemic preparedness",
keywords="acute hepatitis",
keywords="children",
keywords="data analytics",
keywords="hospital",
keywords="laboratory",
keywords="all age groups",
keywords="pre-pandemic",
keywords="United Kingdom",
keywords="Netherlands",
keywords="Ireland Curacao",
keywords="single center",
keywords="federated analytics",
keywords="pandemic surveillance",
keywords="outbreaks",
keywords="public health",
abstract="Background: In March 2022, a concerning rise in cases of unexplained pediatric hepatitis was reported in multiple countries. Cases were defined as acute hepatitis with serum transaminases >500 U/L (aspartate transaminase [AST] or alanine transaminase [ALT]) in children aged 16 years or younger. We explored a simple federated data analytics method to search for evidence of unreported cases using routinely held data. We conducted a pragmatic survey to analyze changes in the proportion of hospitalized children with elevated AST or ALT over time. In addition, we studied the feasibility of using routinely collected clinical laboratory results to detect or follow-up the outbreak of an infectious disease. Objective: We explored a simple federated data analytics method to search for evidence of unreported cases using routinely held data. Methods: We provided hospitals with a simple computational tool to enable laboratories to share nondisclosive summary-level data. Summary statistics for AST and ALT measurements were collected from the last 10 years across all age groups. Measurements were considered elevated if ALT or AST was >200 U/L. The rate of elevated AST or ALT test for 3-week- to 5-year-olds was compared between a period of interest in which cases of hepatitis were reported (December 1, 2021, to August 31, 2022) and a prepandemic baseline period (January 1, 2012, to December 31, 2019). We calculated a z score, which measures the extent to which the rate for elevated ALT or AST was higher or lower in the period of interest compared to a baseline period, for the 3-week- to 5-year-olds. Results: Our approach of sharing a simple software tool for local use enabled rapid, federated data analysis. A total of 34 hospitals in the United Kingdom, the Netherlands, Ireland, and Cura{\c{c}}ao were asked to contribute summary data, and 30 (88\%) submitted their data. For all locations combined, the rate of elevated AST or ALT measurements in the period of interest was not elevated (z score=?0.46; P=.64). Results from individual regions were discordant, with a higher rate of elevated AST or ALT values in the Netherlands (z score=4.48; P<.001), driven by results from a single center in Utrecht. We did not observe any clear indication of changes in primary care activity or test results in the same period. Conclusions: Hospital laboratories collect large amounts of data on a daily basis that can potentially be of use for disease surveillance, but these are currently not optimally used. Federated analytics using nondisclosive, summary-level laboratory data sharing was successful, safe, and efficient. The approach holds potential as a tool for pandemic surveillance in future outbreaks. Our findings do not indicate the presence of a broader outbreak of mild hepatitis cases among young children, although there was an increase in elevated AST or ALT values locally in the Netherlands. ",
doi="10.2196/55376",
url="https://publichealth.jmir.org/2024/1/e55376"
}


@Article{info:doi/10.2196/60140,
author="Poncet, R{\'e}my
and Gargominy, Olivier",
title="In the Shadow of Medicine: The Glaring Absence of Occurrence Records of Human-Hosted Biodiversity",
journal="Online J Public Health Inform",
year="2024",
month="Dec",
day="9",
volume="16",
pages="e60140",
keywords="human microbiome",
keywords="bacterial occurrence data",
keywords="public health",
keywords="one health",
keywords="biodiversity data gap",
keywords="medical data integration",
keywords="medical data",
keywords="microbiome",
keywords="bacterial",
keywords="bacteria",
keywords="biodiversity",
keywords="disease prevention",
keywords="pathogens",
keywords="user-friendly",
keywords="bacterial pathogens",
doi="10.2196/60140",
url="https://ojphi.jmir.org/2024/1/e60140"
}


@Article{info:doi/10.2196/56926,
author="Tor{\'a}n-Monserrat, Pere
and Lamonja-Vicente, Noem{\'i}
and Costa-Garrido, Anna
and Carrasco-Ribelles, A. Luc{\'i}a
and Quirant, Bibiana
and Boigues, Marc
and Molina, Xaviera
and Chac{\'o}n, Carla
and Dacosta-Aguayo, Rosalia
and Arm{\'e}star, Fernando
and Mart{\'i}nez C{\'a}ceres, Mar{\'i}a Eva
and Prado, G. Julia
and Viol{\'a}n, Concepci{\'o}n
and ",
title="SARS-CoV-2 Infection Risk by Vaccine Doses and Prior Infections Over 24 Months: ProHEpiC-19 Longitudinal Study",
journal="JMIR Public Health Surveill",
year="2024",
month="Nov",
day="22",
volume="10",
pages="e56926",
keywords="SARS-CoV-2",
keywords="COVID-19",
keywords="health care workers",
keywords="cohort",
keywords="extended Cox models",
keywords="coronavirus",
keywords="epidemiology",
keywords="epidemiological",
keywords="risks",
keywords="infectious",
keywords="respiratory",
keywords="longitudinal",
keywords="vaccines",
keywords="vaccination",
keywords="vaccinated",
abstract="Background: As the vaccination campaign against COVID-19 progresses, it becomes crucial to comprehend the lasting effects of vaccination on safeguarding against new infections or reinfections. Objective: This study aimed to assess the risk of new SARS-CoV-2 infections based on the number of vaccine doses, prior infections, and other clinical characteristics. Methods: We defined a cohort of 800 health care workers in a 24-month study (March 2020 to December 2022) in northern Barcelona to determine new infections by SARS-CoV-2. We used extended Cox models, specifically Andersen-Gill (AG) and Prentice-Williams-Peterson, and we examined the risk of new infections. The AG model incorporated variables such as sex, age, job title, number of chronic conditions, vaccine doses, and prior infections. Additionally, 2 Prentice-Williams-Peterson models were adjusted, one for those individuals with no or 1 infection and another for those with 2 or 3 infections, both with the same covariates as the AG model. Results: The 800 participants (n=605, 75.6\% women) received 1, 2, 3, and 4 doses of the vaccine. Compared to those who were unvaccinated, the number of vaccine doses significantly reduced (P<.001) the risk of infection by 66\%, 81\%, 89\%, and 99\%, respectively. Unit increase in the number of prior infections reduced the risk of infection by 75\% (P<.001). When separating individuals by number of previous infections, risk was significantly reduced for those with no or 1 infection by 61\% (P=.02), and by 88\%, 93\%, and 99\% (P<.001) with 1, 2, 3, or 4 doses, respectively. In contrast, for those with 2 or 3 previous infections, the reduction was only significant with the fourth dose, at 98\% (P<.001). The number of chronic diseases only increased the risk by 28\%?31\% (P<.001) for individuals with 0?1 previous infections. Conclusions: The study suggests that both prior infections and vaccination status significantly contribute to SARS-CoV-2 immunity, supporting vaccine effectiveness in reducing risk of reinfection for up to 24 months after follow-up from the onset of the pandemic. These insights contribute to our understanding of long-term immunity dynamics and inform strategies for mitigating the impact of COVID-19. Trial Registration: ClinicalTrials.gov NCT04885478; http://clinicaltrials.gov/ct2/show/NCT04885478 ",
doi="10.2196/56926",
url="https://publichealth.jmir.org/2024/1/e56926"
}


@Article{info:doi/10.2196/57265,
author="Guti{\'e}rrez-Salme{\'a}n, Gabriela
and Miranda-Alatriste, Vanessa Paola
and Ben{\'i}tez-Alday, Patricio
and Orozco-Rivera, Enrique Luis
and Islas-Vargas, Nurit
and Espinosa-Cuevas, {\'A}ngeles
and Correa-Rotter, Ricardo
and Colin-Ramirez, Eloisa",
title="Knowledge, Attitudes, and Behaviors Toward Salt Consumption and Its Association With 24-Hour Urinary Sodium and Potassium Excretion in Adults Living in Mexico City: Cross-Sectional Study",
journal="Interact J Med Res",
year="2024",
month="Nov",
day="18",
volume="13",
pages="e57265",
keywords="beliefs",
keywords="attitudes",
keywords="hypertension",
keywords="knowledge",
keywords="salt consumption",
keywords="sodium intake",
keywords="potassium intake",
keywords="Mexico",
abstract="Background: The World Health Organization recommends a daily sodium intake of less than 2000 mg for adults; however, the Mexican population, like many others globally, consumes more sodium than this recommended amount. Excessive sodium intake is often accompanied by inadequate potassium intake. The association between knowledge, attitudes, and behaviors (KAB) and actual sodium intake has yielded mixed results across various populations. In Mexico, however, salt/sodium-related KAB and its relationship with sodium and potassium intake have not been evaluated. Objective: This study primarily aims to describe salt/sodium-related KAB in a Mexican population and, secondarily, to explore the association between KAB and 24-hour urinary sodium and potassium excretion. Methods: We conducted a cross-sectional study in an adult population from Mexico City and the surrounding metropolitan area. Self-reported KAB related to salt/sodium intake was assessed using a survey developed by the Pan American Health Organization. Anthropometric measurements were taken, and 24-hour urinary sodium and potassium excretion levels were determined. Descriptive statistics were stratified by sex and presented as means (SD) or median (25th-75th percentiles) for continuous variables, and as absolute and relative frequencies for categorical variables. The associations between KAB and sodium and potassium excretion were assessed using analysis of covariance, adjusting for age, sex, BMI, and daily energy intake as covariates, with the {\vS}id{\'a}k correction applied for multiple comparisons. Results: Overall, 232 participants were recruited (women, n=184, 79.3\%). The mean urinary sodium and potassium excretion were estimated to be 2582.5 and 1493.5 mg/day, respectively. A higher proportion of men did not know the amount of sodium they consumed compared with women (12/48, 25\%, vs 15/184, 8.2\%, P=.01). More women reported knowing that there is a recommended amount for daily sodium intake than men (46/184, 25\%, vs 10/48, 20.8\%, P=.02). Additionally, more than half of men (30/48, 62.5\%) reported never or rarely reading food labels, compared with women (96/184, 52.1\%, P=.04). Better salt/sodium-related KAB was associated with higher adjusted mean sodium and potassium excretion. For example, mean sodium excretion was 3011.5 (95\% CI 2640.1-3382.9) mg/day among participants who reported knowing the difference between salt and sodium, compared with 2592.8 (95\% CI 2417.2-2768.3) mg/day in those who reported not knowing this difference (P=.049). Similarly, potassium excretion was 1864.9 (95\% CI 1669.6-2060.3) mg/day for those who knew the difference, compared with 1512.5 (95\% CI 1420.1-1604.8) mg/day for those who did not (P=.002). Additionally, higher urinary sodium excretion was observed among participants who reported consuming too much sodium (3216.0 mg/day, 95\% CI 2867.1-3565.0 mg/day) compared with those who claimed to eat just the right amount (2584.3 mg/day, 95\% CI 2384.9-2783.7 mg/day, P=.01). Conclusions: Salt/sodium-related KAB was poor in this study sample. Moreover, KAB had a greater impact on potassium excretion than on sodium excretion, highlighting the need for more strategies to improve KAB related to salt/sodium intake. Additionally, it is important to consider other strategies aimed at modifying the sodium content of foods. ",
doi="10.2196/57265",
url="https://www.i-jmr.org/2024/1/e57265",
url="http://www.ncbi.nlm.nih.gov/pubmed/39556832"
}


@Article{info:doi/10.2196/58176,
author="Zhang, Pengfei
and Kamitaki, K. Brad
and Do, Phu Thien",
title="Crowdsourcing Adverse Events Associated With Monoclonal Antibodies Targeting Calcitonin Gene--Related Peptide Signaling for Migraine Prevention: Natural Language Processing Analysis of Social Media",
journal="JMIR Form Res",
year="2024",
month="Nov",
day="8",
volume="8",
pages="e58176",
keywords="internet",
keywords="patient reported outcome",
keywords="headache",
keywords="health information",
keywords="Reddit",
keywords="registry",
keywords="monoclonal antibody",
keywords="crowdsourcing",
keywords="postmarketing",
keywords="safety",
keywords="surveillance",
keywords="migraine",
keywords="preventives",
keywords="prevention",
keywords="self-reported",
keywords="calcitonin gene--related peptide",
keywords="calcitonin",
keywords="therapeutics",
keywords="social media",
keywords="medication-related",
keywords="posts",
keywords="propranolol",
keywords="topiramate",
keywords="erenumab",
keywords="fremanezumab",
keywords="cross-sectional",
keywords="surveys",
abstract="Background: Clinical trials demonstrate the efficacy and tolerability of medications targeting calcitonin gene--related peptide (CGRP) signaling for migraine prevention. However, these trials may not accurately reflect the real-world experiences of more diverse and heterogeneous patient populations, who often have higher disease burden and more comorbidities. Therefore, postmarketing safety surveillance is warranted. Regulatory organizations encourage marketing authorization holders to screen digital media for suspected adverse reactions, applying the same requirements as for spontaneous reports. Real-world data from social media platforms constitute a potential venue to capture diverse patient experiences and help detect treatment-related adverse events. However, while social media holds promise for this purpose, its use in pharmacovigilance is still in its early stages. Computational linguistics, which involves the automatic manipulation and quantitative analysis of oral or written language, offers a potential method for exploring this content. Objective: This study aims to characterize adverse events related to monoclonal antibodies targeting CGRP signaling on Reddit, a large online social media forum, by using computational linguistics. Methods: We examined differences in word frequencies from medication-related posts on the Reddit subforum r/Migraine over a 10-year period (2010-2020) using computational linguistics. The study had 2 phases: a validation phase and an application phase. In the validation phase, we compared posts about propranolol and topiramate, as well as posts about each medication against randomly selected posts, to identify known and expected adverse events. In the application phase, we analyzed posts discussing 2 monoclonal antibodies targeting CGRP signaling---erenumab and fremanezumab---to identify potential adverse events for these medications. Results: From 22,467 Reddit r/Migraine posts, we extracted 402 (2\%) propranolol posts, 1423 (6.33\%) topiramate posts, 468 (2.08\%) erenumab posts, and 73 (0.32\%) fremanezumab posts. Comparing topiramate against propranolol identified several expected adverse events, for example, ``appetite,'' ``weight,'' ``taste,'' ``foggy,'' ``forgetful,'' and ``dizziness.'' Comparing erenumab against a random selection of terms identified ``constipation'' as a recurring keyword. Comparing erenumab against fremanezumab identified ``constipation,'' ``depression,'' ``vomiting,'' and ``muscle'' as keywords. No adverse events were identified for fremanezumab. Conclusions: The validation phase of our study accurately identified common adverse events for oral migraine preventive medications. For example, typical adverse events such as ``appetite'' and ``dizziness'' were mentioned in posts about topiramate. When we applied this methodology to monoclonal antibodies targeting CGRP or its receptor---fremanezumab and erenumab, respectively---we found no definite adverse events for fremanezumab. However, notable flagged words for erenumab included ``constipation,'' ``depression,'' and ``vomiting.'' In conclusion, computational linguistics applied to social media may help identify potential adverse events for novel therapeutics. While social media data show promise for pharmacovigilance, further work is needed to improve its reliability and usability. ",
doi="10.2196/58176",
url="https://formative.jmir.org/2024/1/e58176"
}


@Article{info:doi/10.2196/58732,
author="Nguyen, Minh Hieu
and Anderson, William
and Chou, Shih-Hsiung
and McWilliams, Andrew
and Zhao, Jing
and Pajewski, Nicholas
and Taylor, Yhenneko",
title="Predictive Models for Sustained, Uncontrolled Hypertension and Hypertensive Crisis Based on Electronic Health Record Data: Algorithm Development and Validation",
journal="JMIR Med Inform",
year="2024",
month="Oct",
day="28",
volume="12",
pages="e58732",
keywords="machine learning",
keywords="risk prediction",
keywords="predictive model",
keywords="decision support",
keywords="blood pressure",
keywords="cardiovascular",
keywords="electronic health record",
abstract="Background: Assessing disease progression among patients with uncontrolled hypertension is important for identifying opportunities for intervention. Objective: We aim to develop and validate 2 models, one to predict sustained, uncontrolled hypertension (?2 blood pressure [BP] readings ?140/90 mm Hg or ?1 BP reading ?180/120 mm Hg) and one to predict hypertensive crisis (?1 BP reading ?180/120 mm Hg) within 1 year of an index visit (outpatient or ambulatory encounter in which an uncontrolled BP reading was recorded). Methods: Data from 142,897 patients with uncontrolled hypertension within Atrium Health Greater Charlotte in 2018 were used. Electronic health record--based predictors were based on the 1-year period before a patient's index visit. The dataset was randomly split (80:20) into a training set and a validation set. In total, 4 machine learning frameworks were considered: L2-regularized logistic regression, multilayer perceptron, gradient boosting machines, and random forest. Model selection was performed with 10-fold cross-validation. The final models were assessed on discrimination (C-statistic), calibration (eg, integrated calibration index), and net benefit (with decision curve analysis). Additionally, internal-external cross-validation was performed at the county level to assess performance with new populations and summarized using random-effect meta-analyses. Results: In internal validation, the C-statistic and integrated calibration index were 0.72 (95\% CI 0.71?0.72) and 0.015 (95\% CI 0.012?0.020) for the sustained, uncontrolled hypertension model, and 0.81 (95\% CI 0.79?0.82) and 0.009 (95\% CI 0.007?0.011) for the hypertensive crisis model. The models had higher net benefit than the default policies (ie, treat-all and treat-none) across different decision thresholds. In internal-external cross-validation, the pooled performance was consistent with internal validation results; in particular, the pooled C-statistics were 0.70 (95\% CI 0.69?0.71) and 0.79 (95\% CI 0.78?0.81) for the sustained, uncontrolled hypertension model and hypertensive crisis model, respectively. Conclusions: An electronic health record--based model predicted hypertensive crisis reasonably well in internal and internal-external validations. The model can potentially be used to support population health surveillance and hypertension management. Further studies are needed to improve the ability to predict sustained, uncontrolled hypertension. ",
doi="10.2196/58732",
url="https://medinform.jmir.org/2024/1/e58732"
}


@Article{info:doi/10.2196/53711,
author="Lim, Sachiko
and Johannesson, Paul",
title="An Ontology to Bridge the Clinical Management of Patients and Public Health Responses for Strengthening Infectious Disease Surveillance: Design Science Study",
journal="JMIR Form Res",
year="2024",
month="Sep",
day="26",
volume="8",
pages="e53711",
keywords="infectious disease",
keywords="ontology",
keywords="IoT",
keywords="infectious disease surveillance",
keywords="patient monitoring",
keywords="infectious disease management",
keywords="risk analysis",
keywords="early warning",
keywords="data integration",
keywords="semantic interoperability",
keywords="public health",
abstract="Background: Novel surveillance approaches using digital technologies, including the Internet of Things (IoT), have evolved, enhancing traditional infectious disease surveillance systems by enabling real-time detection of outbreaks and reaching a wider population. However, disparate, heterogenous infectious disease surveillance systems often operate in silos due to a lack of interoperability. As a life-changing clinical use case, the COVID-19 pandemic has manifested that a lack of interoperability can severely inhibit public health responses to emerging infectious diseases. Interoperability is thus critical for building a robust ecosystem of infectious disease surveillance and enhancing preparedness for future outbreaks. The primary enabler for semantic interoperability is ontology. Objective: This study aims to design the IoT-based management of infectious disease ontology (IoT-MIDO) to enhance data sharing and integration of data collected from IoT-driven patient health monitoring, clinical management of individual patients, and disparate heterogeneous infectious disease surveillance. Methods: The ontology modeling approach was chosen for its semantic richness in knowledge representation, flexibility, ease of extensibility, and capability for knowledge inference and reasoning. The IoT-MIDO was developed using the basic formal ontology (BFO) as the top-level ontology. We reused the classes from existing BFO-based ontologies as much as possible to maximize the interoperability with other BFO-based ontologies and databases that rely on them. We formulated the competency questions as requirements for the ontology to achieve the intended goals. Results: We designed an ontology to integrate data from heterogeneous sources, including IoT-driven patient monitoring, clinical management of individual patients, and infectious disease surveillance systems. This integration aims to facilitate the collaboration between clinical care and public health domains. We also demonstrate five use cases using the simplified ontological models to show the potential applications of IoT-MIDO: (1) IoT-driven patient monitoring, risk assessment, early warning, and risk management; (2) clinical management of patients with infectious diseases; (3) epidemic risk analysis for timely response at the public health level; (4) infectious disease surveillance; and (5) transforming patient information into surveillance information. Conclusions: The development of the IoT-MIDO was driven by competency questions. Being able to answer all the formulated competency questions, we successfully demonstrated that our ontology has the potential to facilitate data sharing and integration for orchestrating IoT-driven patient health monitoring in the context of an infectious disease epidemic, clinical patient management, infectious disease surveillance, and epidemic risk analysis. The novelty and uniqueness of the ontology lie in building a bridge to link IoT-based individual patient monitoring and early warning based on patient risk assessment to infectious disease epidemic surveillance at the public health level. The ontology can also serve as a starting point to enable potential decision support systems, providing actionable insights to support public health organizations and practitioners in making informed decisions in a timely manner. ",
doi="10.2196/53711",
url="https://formative.jmir.org/2024/1/e53711",
url="http://www.ncbi.nlm.nih.gov/pubmed/39325530"
}


@Article{info:doi/10.2196/54503,
author="Cabrera Alvargonzalez, J. Jorge
and Larra{\~n}aga, Ana
and Martinez, Javier
and P{\'e}rez Castro, Sonia
and Rey Cao, Sonia
and Davi{\~n}a Nu{\~n}ez, Carlos
and Del Campo P{\'e}rez, V{\'i}ctor
and Duran Parrondo, Carmen
and Suarez Luque, Silvia
and Gonz{\'a}lez Alonso, Elena
and Silva Tojo, Jos{\'e} Alfredo
and Porteiro, Jacobo
and Regueiro, Benito",
title="Assessment of the Effective Sensitivity of SARS-CoV-2 Sample Pooling Based on a Large-Scale Screening Experience: Retrospective Analysis",
journal="JMIR Public Health Surveill",
year="2024",
month="Sep",
day="24",
volume="10",
pages="e54503",
keywords="pooling",
keywords="sensitivity",
keywords="SARS-CoV-2",
keywords="PCR",
keywords="saliva",
keywords="screening",
keywords="surveillance",
keywords="COVID-19",
keywords="nonsymptomatic",
keywords="transmission control",
abstract="Background: The development of new large-scale saliva pooling detection strategies can significantly enhance testing capacity and frequency for asymptomatic individuals, which is crucial for containing SARS-CoV-2. Objective: This study aims to implement and scale-up a SARS-CoV-2 screening method using pooled saliva samples to control the virus in critical areas and assess its effectiveness in detecting asymptomatic infections. Methods: Between August 2020 and February 2022, our laboratory received a total of 928,357 samples. Participants collected at least 1 mL of saliva using a self-sampling kit and registered their samples via a smartphone app. All samples were directly processed using AutoMate 2550 for preanalytical steps and then transferred to Microlab STAR, managed with the HAMILTON Pooling software for pooling. The standard pool preset size was 20 samples but was adjusted to 5 when the prevalence exceeded 2\% in any group. Real-time polymerase chain reaction (RT-PCR) was conducted using the Allplex SARS-CoV-2 Assay until July 2021, followed by the Allplex SARS-CoV-2 FluA/FluB/RSV assay for the remainder of the study period. Results: Of the 928,357 samples received, 887,926 (95.64\%) were fully processed into 56,126 pools. Of these pools, 4863 tested positive, detecting 5720 asymptomatic infections. This allowed for a comprehensive analysis of pooling's impact on RT-PCR sensitivity and false-negative rate (FNR), including data on positive samples per pool (PPP). We defined Ctref as the minimum cycle threshold (Ct) of each data set from a sample or pool and compared these Ctref results from pooled samples with those of the individual tests ($\Delta$CtP). We then examined their deviation from the expected offset due to dilution [$\Delta$$\Delta$CtP = $\Delta$CtP -- log2]. In this work, the $\Delta$CtP and $\Delta$$\Delta$CtP were 2.23 versus 3.33 and --0.89 versus 0.23, respectively, comparing global results with results for pools with 1 positive sample per pool. Therefore, depending on the number of genes used in the test and the size of the pool, we can evaluate the FNR and effective sensitivity (1 -- FNR) of the test configuration. In our scenario, with a maximum of 20 samples per pool and 3 target genes, statistical observations indicated an effective sensitivity exceeding 99\%. From an economic perspective, the focus is on pooling efficiency, measured by the effective number of persons that can be tested with 1 test, referred to as persons per test (PPT). In this study, the global PPT was 8.66, reflecting savings of over 20 million euros (US \$22 million) based on our reagent prices. Conclusions: Our results demonstrate that, as expected, pooling reduces the sensitivity of RT-PCR. However, with the appropriate pool size and the use of multiple target genes, effective sensitivity can remain above 99\%. Saliva pooling may be a valuable tool for screening and surveillance in asymptomatic individuals and can aid in controlling SARS-CoV-2 transmission. Further studies are needed to assess the effectiveness of these strategies for SARS-CoV-2 and their application to other microorganisms or biomarkers detected by PCR. ",
doi="10.2196/54503",
url="https://publichealth.jmir.org/2024/1/e54503",
url="http://www.ncbi.nlm.nih.gov/pubmed/39316785"
}


@Article{info:doi/10.2196/56571,
author="Jones, S. Brie
and DeWitt, E. Michael
and Wenner, J. Jennifer
and Sanders, W. John",
title="Lyme Disease Under-Ascertainment During the COVID-19 Pandemic in the United States: Retrospective Study",
journal="JMIR Public Health Surveill",
year="2024",
month="Sep",
day="12",
volume="10",
pages="e56571",
keywords="surveillance",
keywords="ascertainment",
keywords="Lyme diseases",
keywords="vector-borne diseases",
keywords="vector-borne disease",
keywords="vector-borne pathogens",
keywords="public health",
keywords="Lyme disease",
keywords="United States",
keywords="North Carolina",
keywords="COVID-19",
keywords="pandemic",
keywords="hospital",
keywords="hospitals",
keywords="clinic-based",
keywords="surveillance program",
keywords="geospatial model",
keywords="spatiotemporal",
abstract="Background: The COVID-19 pandemic resulted in a massive disruption in access to care and thus passive, hospital- and clinic-based surveillance programs. In 2020, the reported cases of Lyme disease were the lowest both across the United States and North Carolina in recent years. During this period, human contact patterns began to shift with higher rates of greenspace utilization and outdoor activities, putting more people into contact with potential vectors and associated vector-borne diseases. Lyme disease reporting relies on passive surveillance systems, which were likely disrupted by changes in health care--seeking behavior during the pandemic. Objective: This study aimed to quantify the likely under-ascertainment of cases of Lyme disease during the COVID-19 pandemic in the United States and North Carolina. Methods: We fitted publicly available, reported Lyme disease cases for both the United States and North Carolina prior to the year 2020 to predict the number of anticipated Lyme disease cases in the absence of the pandemic using a Bayesian modeling approach. We then compared the ratio of reported cases divided by the predicted cases to quantify the number of likely under-ascertained cases. We then fitted geospatial models to further quantify the spatial distribution of the likely under-ascertained cases and characterize spatial dynamics at local scales. Results: Reported cases of Lyme Disease were lower in 2020 in both the United States and North Carolina than prior years. Our findings suggest that roughly 14,200 cases may have gone undetected given historical trends prior to the pandemic. Furthermore, we estimate that only 40\% to 80\% of Lyme diseases cases were detected in North Carolina between August 2020 and February 2021, the peak months of the COVID-19 pandemic in both the United States and North Carolina, with prior ascertainment rates returning to normal levels after this period. Our models suggest both strong temporal effects with higher numbers of cases reported in the summer months as well as strong geographic effects. Conclusions: Ascertainment rates of Lyme disease were highly variable during the pandemic period both at national and subnational scales. Our findings suggest that there may have been a substantial number of unreported Lyme disease cases despite an apparent increase in greenspace utilization. The use of counterfactual modeling using spatial and historical trends can provide insight into the likely numbers of missed cases. Variable ascertainment of cases has implications for passive surveillance programs, especially in the trending of disease morbidity and outbreak detection, suggesting that other methods may be appropriate for outbreak detection during disturbances to these passive surveillance systems. ",
doi="10.2196/56571",
url="https://publichealth.jmir.org/2024/1/e56571"
}


@Article{info:doi/10.5210/ojphi.v11i1.9730,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9730",
doi="10.5210/ojphi.v11i1.9730",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9735,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9735",
doi="10.5210/ojphi.v11i1.9735",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9736,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9736",
doi="10.5210/ojphi.v11i1.9736",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9737,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9737",
doi="10.5210/ojphi.v11i1.9737",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9738,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9738",
doi="10.5210/ojphi.v11i1.9738",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9739,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9739",
doi="10.5210/ojphi.v11i1.9739",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9740,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9740",
doi="10.5210/ojphi.v11i1.9740",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9741,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9741",
doi="10.5210/ojphi.v11i1.9741",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9742,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9742",
doi="10.5210/ojphi.v11i1.9742",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9743,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9743",
doi="10.5210/ojphi.v11i1.9743",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9744,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9744",
doi="10.5210/ojphi.v11i1.9744",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9745,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9745",
doi="10.5210/ojphi.v11i1.9745",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9746,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9746",
doi="10.5210/ojphi.v11i1.9746",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9747,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9747",
doi="10.5210/ojphi.v11i1.9747",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9748,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9748",
doi="10.5210/ojphi.v11i1.9748",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9749,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9749",
doi="10.5210/ojphi.v11i1.9749",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9750,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9750",
doi="10.5210/ojphi.v11i1.9750",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9751,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9751",
doi="10.5210/ojphi.v11i1.9751",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9752,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9752",
doi="10.5210/ojphi.v11i1.9752",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9753,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9753",
doi="10.5210/ojphi.v11i1.9753",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9754,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9754",
doi="10.5210/ojphi.v11i1.9754",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9756,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9756",
doi="10.5210/ojphi.v11i1.9756",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9757,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9757",
doi="10.5210/ojphi.v11i1.9757",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9758,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9758",
doi="10.5210/ojphi.v11i1.9758",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9759,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9759",
doi="10.5210/ojphi.v11i1.9759",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9760,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9760",
doi="10.5210/ojphi.v11i1.9760",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9761,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9761",
doi="10.5210/ojphi.v11i1.9761",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9762,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9762",
doi="10.5210/ojphi.v11i1.9762",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9763,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9763",
doi="10.5210/ojphi.v11i1.9763",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9764,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9764",
doi="10.5210/ojphi.v11i1.9764",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9765,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9765",
doi="10.5210/ojphi.v11i1.9765",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9766,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9766",
doi="10.5210/ojphi.v11i1.9766",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9767,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9767",
doi="10.5210/ojphi.v11i1.9767",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9768,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9768",
doi="10.5210/ojphi.v11i1.9768",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9769,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9769",
doi="10.5210/ojphi.v11i1.9769",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9770,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9770",
doi="10.5210/ojphi.v11i1.9770",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9771,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9771",
doi="10.5210/ojphi.v11i1.9771",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9772,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9772",
doi="10.5210/ojphi.v11i1.9772",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9773,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9773",
doi="10.5210/ojphi.v11i1.9773",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9774,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9774",
doi="10.5210/ojphi.v11i1.9774",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9776,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9776",
doi="10.5210/ojphi.v11i1.9776",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9779,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9779",
doi="10.5210/ojphi.v11i1.9779",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9780,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9780",
doi="10.5210/ojphi.v11i1.9780",
url=""
}


@Article{info:doi/10.5210/ojphi.v11i1.9789,
title="Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review",
journal="Online J Public Health Inform",
year="2019",
volume="11",
number="1",
pages="e9789",
doi="10.5210/ojphi.v11i1.9789",
url=""
}


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