%0 Journal Article %@ 1947-2579 %I JMIR Publications %V 17 %N %P e63560 %T Quantifying Patient Demand for Orthopedics Care by Region Through Google Trends Analysis: Descriptive Epidemiology Study %A Qiu,Abram %A Meadows,Kristopher %A Ye,Fei %A Iyawe,Osasu %A Kenneth-Nwosa,Kenneth %K orthopedics %K geographic factors %K health care disparities %K medical schools %K internship and residency %K epidemiology %K public health informatics %K physicians %K assessment of health care needs %K resource allocation %D 2025 %7 31.1.2025 %9 %J Online J Public Health Inform %G English %X Background: There is a growing gap between the supply of surgeons and the demand for orthopedic services in the United States. Objective: We analyzed publicly available online data to assess the correlation between the supply of orthopedic surgeons and patient demand across the United States. The geographic trends of this gap were assessed by using the relative demand index (RDI) to guide precision public health interventions such as resource allocation, residency program expansion, and workforce planning to specific regions. Methods: The data used were from the US Census Bureau, Association of American Medical Colleges (AAMC) through their 2024 Electronic Residency Application Service (ERAS) directory, AAMC State Physician Workforce Data Report, and Google Trends. We calculated the normalized relative search volume (RSV) and the RDI and compared them to the densities of orthopedic surgeons across the United States. We examined the disparities with the Spearman rank correlation coefficient. Results: The supply of orthopedic surgeons varied greatly across the United States, with a significantly higher demand for them in southern states (P=.02). The orthopedic surgeon concentration, normalized to the highest density, was the highest in Alaska (n=100), the District of Columbia (n=96), and Wyoming (n=72); and the lowest in Texas (n=0), Arkansas (n=6), and Oklahoma (n=64). The highest RDI values were observed in Utah (n=97), Florida (n=88), and Texas (n=83), while the lowest were observed in Alaska (n=0), the District of Columbia (n=5), and New Hampshire (n=7). The 7 states of Alaska, Maine, South Dakota, Wyoming, Montana, Delaware, and Idaho lacked orthopedic surgery residencies. In 2023, New York (n=19), Michigan (n=17), Ohio (n=17), Pennsylvania (n=16), and California (n=16) had the most residency programs. Demand and supply, represented by the RDI and orthopedic surgeon concentration, respectively, were strongly correlated negatively (ρ=−0.791, P<.001). States that were in the top quartile of residency programs (≥4 residency programs) exhibited a high demand for orthopedic surgeons (ρ=.6035, P=.02). Conclusions: This study showed that regional disparities in access to orthopedic care can be addressed by increasing orthopedic residencies. The study highlights the novel application of the RDI to mapping the regional need for orthopedics, and this map allows for better targeted resource allocation to expand orthopedic surgery training. %R 10.2196/63560 %U https://ojphi.jmir.org/2025/1/e63560 %U https://doi.org/10.2196/63560 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e52404 %T Construction and Application of a Private 5G Standalone Medical Network in a Smart Health Environment: Exploratory Practice From China %A Chen,Baozhan %A Shi,Xiaobing %A Feng,Tianyi %A Jiang,Shuai %A Zhai,Yunkai %A Ren,Mingxing %A Liu,Dongqing %A Wang,Chengzeng %A Gao,Jinghong %+ The First Affiliated Hospital of Zhengzhou University, Number 1, Longhu Middle Ring Road, Jinshui District, Zhengzhou, 450000, China, 86 371 66964536, fccgaojh@zzu.edu.cn %K 5G %K medical private network %K construction %K application %K performance test %D 2024 %7 24.10.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: To date, the differentiated requirements for network performance in various health care service scenarios—within, outside, and between hospitals—remain a key challenge that restricts the development and implementation of digital medical services. Objective: This study aims to construct and implement a private 5G (the 5th generation mobile communication technology) standalone (SA) medical network in a smart health environment to meet the diverse needs of various medical services. Methods: Based on an analysis of network differentiation requirements in medical applications, the system architecture and functional positioning of the proposed private 5G SA medical network are designed and implemented. The system architecture includes the development of exclusive and preferential channels for medical use, as well as an ordinary user channel. A 3-layer network function architecture is designed, encompassing resource, control, and intelligent operation layers to facilitate management arrangements and provide network open services. Core technologies, including edge cloud collaboration; service awareness; and slicing of access, bearer, and core networks, are employed in the construction and application of the 5G SA network. Results: The construction of the private 5G SA medical network primarily involves system architecture, standards, and security measures. The system, featuring exclusive, preferential, and common channels, supports a variety of medical applications. Relevant standards are adhered to in order to ensure the interaction and sharing of medical service information. Security is achieved through mechanisms such as authentication, abnormal behavior analysis, and dynamic access control. Three typical medical applications that rely on the 5G network in intrahospital, interhospital, and out-of-hospital scenarios—namely, mobile ward rounds, remote first aid, and remote ultrasound—were conducted. Testing of the 5G-enabled mobile ward rounds showed an average download rate of 790 Mbps and an average upload rate of 91 Mbps. Compared with 4G, the 5G network more effectively meets the diverse requirements of various business applications in prehospital emergency scenarios. For remote ultrasound, the average downlink rate of the 5G network is 4.82 Mbps, and the average uplink rate is 2 Mbps, with an average fluctuation of approximately 8 ms. The bandwidth, performance, and delay of the 5G SA network were also examined and confirmed to be effective. Conclusions: The proposed 5G SA medical network demonstrates strong performance in typical medical applications. Its construction and application could lead to the development of new medical service models and provide valuable references for the further advancement and implementation of 5G networks in other industries, both in China and globally. %M 39446419 %R 10.2196/52404 %U https://www.jmir.org/2024/1/e52404 %U https://doi.org/10.2196/52404 %U http://www.ncbi.nlm.nih.gov/pubmed/39446419 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e49871 %T Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study %A Martonik,Rachel %A Oleson,Caitlin %A Marder,Ellyn %+ Deloitte, 1919 North Lynn Street, Arlington, VA, 22209, United States, 1 7032039550, rachel.martonik@gmail.com %K COVID-19 %K cluster detection %K disease outbreaks %K surveillance %K SaTScan %K space-time surveillance %K spatiotemporal %K United States %K outbreak %K outbreaks %K pandemic %K real-time surveillance %K detection %K tool %K tools %K effectiveness %K public health %K intervention %K interventions %K community settings %K outbreak detection %D 2024 %7 16.10.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: During the peak of the winter 2020-2021 surge, the number of weekly reported COVID-19 outbreaks in Washington State was 231; the majority occurred in high-priority settings such as workplaces, community settings, and schools. The Washington State Department of Health used automated address matching to identify clusters at health care facilities. No other systematic, statewide outbreak detection methods were in place. This was a gap given the high volume of cases, which delayed investigations and decreased data completeness, potentially leading to undetected outbreaks. We initiated statewide cluster detection using SaTScan, implementing a space-time permutation model to identify COVID-19 clusters for investigation. Objective: To improve outbreak detection, the Washington State Department of Health initiated a systematic cluster detection model to identify timely and actionable COVID-19 clusters for local health jurisdiction (LHJ) investigation and resource prioritization. This report details the model’s implementation and the assessment of the tool’s effectiveness. Methods: In total, 6 LHJs participated in a pilot to test model parameters including analysis type, geographic aggregation, cluster radius, and data lag. Parameters were determined through heuristic criteria to detect clusters early when they are smaller, making interventions more feasible. This study reviews all clusters detected after statewide implementation from July 17 to December 17, 2021. The clusters were analyzed by LHJ population and disease incidence. Clusters were compared with reported outbreaks. Results: A weekly, LHJ-specific retrospective space-time permutation model identified 2874 new clusters during this period. While the weekly analysis included case data from the prior 3 weeks, 58.25% (n=1674) of all clusters identified were timely—having occurred within 1 week of the analysis and early enough for intervention to prevent further transmission. There were 2874 reported outbreaks during this same period. Of those, 363 (12.63%) matched to at least one SaTScan cluster. The most frequent settings among reported and matched outbreaks were schools and youth programs (n=825, 28.71% and n=108, 29.8%), workplaces (n=617, 21.46% and n=56, 15%), and long-term care facilities (n=541, 18.82% and n=99, 27.3%). Settings with the highest percentage of clusters that matched outbreaks were community settings (16/72, 22%) and congregate housing (44/212, 20.8%). The model identified approximately one-third (119/363, 32.8%) of matched outbreaks before cases were associated with the outbreak event in our surveillance system. Conclusions: Our goal was to routinely and systematically identify timely and actionable COVID-19 clusters statewide. Regardless of population or incidence, the model identified reasonably sized, timely clusters statewide, meeting the objective. Among some high-priority settings subject to public health interventions throughout the pandemic, such as schools and community settings, the model identified clusters that were matched to reported outbreaks. In workplaces, another high-priority setting, results suggest the model might be able to identify outbreaks sooner than existing outbreak detection methods. %M 39412839 %R 10.2196/49871 %U https://publichealth.jmir.org/2024/1/e49871 %U https://doi.org/10.2196/49871 %U http://www.ncbi.nlm.nih.gov/pubmed/39412839 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e56343 %T Application of Spatial Analysis on Electronic Health Records to Characterize Patient Phenotypes: Systematic Review %A Mollalo,Abolfazl %A Hamidi,Bashir %A Lenert,Leslie A %A Alekseyenko,Alexander V %+ Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina, 22 Westedge Street, Suite 200, Charleston, SC, 29403, United States, 1 8437922970, mollalo@musc.edu %K clinical phenotypes %K electronic health records %K geocoding %K geographic information systems %K patient phenotypes %K spatial analysis %D 2024 %7 15.10.2024 %9 Review %J JMIR Med Inform %G English %X Background: Electronic health records (EHRs) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHRs in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes. Objective: This study reviews advanced spatial analyses that used individual-level health data from EHRs within the United States to characterize patient phenotypes. Methods: We systematically evaluated English-language, peer-reviewed studies from the PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on study design or specific health domains. Results: A substantial proportion of studies (>85%) were limited to geocoding or basic mapping without implementing advanced spatial statistical analysis, leaving only 49 studies that met the eligibility criteria. These studies used diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were less common. A noteworthy surge (n=42, 86%) in publications was observed after 2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were limited. Conclusions: This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. We suggest that future research should focus on addressing these gaps and harnessing spatial analysis to enhance individual patient contexts and clinical decision support. %M 39405525 %R 10.2196/56343 %U https://medinform.jmir.org/2024/1/e56343 %U https://doi.org/10.2196/56343 %U http://www.ncbi.nlm.nih.gov/pubmed/39405525 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e56510 %T The Automatic Context Measurement Tool (ACMT) to Compile Participant-Specific Built and Social Environment Measures for Health Research: Development and Usability Study %A Zhou,Weipeng %A Youngbloom,Amy %A Ren,Xinyang %A Saelens,Brian E %A Mooney,Sean D %A Mooney,Stephen J %+ Department of Epidemiology, Hans Rosling Center for Population Health, University of Washington, 3980 15th Ave NE, Seattle, WA, 98105, United States, 1 206 685 1643, sjm2186@uw.edu %K built environment %K social environment %K geocoding %K GIS %K geographic information systems %K ACMT %K automatic context measurement tool %K linkage %K privacy %D 2024 %7 4.10.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The environment shapes health behaviors and outcomes. Studies exploring this influence have been limited to research groups with the geographic information systems expertise required to develop built and social environment measures (eg, groups that include a researcher with geographic information system expertise). Objective: The goal of this study was to develop an open-source, user-friendly, and privacy-preserving tool for conveniently linking built, social, and natural environmental variables to study participant addresses. Methods: We built the automatic context measurement tool (ACMT). The ACMT comprises two components: (1) a geocoder, which identifies a latitude and longitude given an address (currently limited to the United States), and (2) a context measure assembler, which computes measures from publicly available data sources linked to a latitude and longitude. ACMT users access both of these components using an RStudio/RShiny-based web interface that is hosted within a Docker container, which runs on a local computer and keeps user data stored in local to protect sensitive data. We illustrate ACMT with 2 use cases: one comparing population density patterns within several major US cities, and one identifying correlates of cannabis licensure status in Washington State. Results: In the population density analysis, we created a line plot showing the population density (x-axis) in relation to distance from the center of the city (y-axis, using city hall location as a proxy) for Seattle, Los Angeles, Chicago, New York City, Nashville, Houston, and Boston with the distances being 1000, 2000, 3000, 4000, and 5000 m. We found the population density tended to decrease as distance from city hall increased except for Nashville and Houston, 2 cities that are notably more sprawling than the others. New York City had a significantly higher population density than the others. We also observed that Los Angeles and Seattle had similarly low population densities within up to 2500 m of City Hall. In the cannabis licensure status analysis, we gathered neighborhood measures such as age, sex, commute time, and education. We found the strongest predictive characteristic of cannabis license approval to be the count of female children aged 5 to 9 years and the proportion of females aged 62 to 64 years who were not in the labor force. However, after accounting for Bonferroni error correction, none of the measures were significantly associated with cannabis retail license approval status. Conclusions: The ACMT can be used to compile environmental measures to study the influence of environmental context on population health. The portable and flexible nature of ACMT makes it optimal for neighborhood study research seeking to attribute environmental data to specific locations within the United States. %M 39365663 %R 10.2196/56510 %U https://formative.jmir.org/2024/1/e56510 %U https://doi.org/10.2196/56510 %U http://www.ncbi.nlm.nih.gov/pubmed/39365663 %0 Journal Article %@ 2369-2960 %I %V 10 %N %P e51883 %T Impact of Ambient Temperature on Mortality Burden and Spatial Heterogeneity in 16 Prefecture-Level Cities of a Low-Latitude Plateau Area in Yunnan Province: Time-Series Study %A Chen,Yang %A Zhou,Lidan %A Zha,Yuanyi %A Wang,Yujin %A Wang,Kai %A Lu,Lvliang %A Guo,Pi %A Zhang,Qingying %K mortality burden %K nonaccidental deaths %K multivariate meta-analysis %K distributed lagged nonlinear mode %K attributable risk %K climate change %K human health %K association %K temperature %K mortality %K nonaccidental death %K spatial heterogeneity %K meteorological data %K temperature esposure %K heterogeneous %K spatial planning %K environmental temperature %K prefecture-level %K resource allocation %D 2024 %7 23.7.2024 %9 %J JMIR Public Health Surveill %G English %X Background: The relation between climate change and human health has become one of the major worldwide public health issues. However, the evidence for low-latitude plateau regions is limited, where the climate is unique and diverse with a complex geography and topography. Objectives: This study aimed to evaluate the effect of ambient temperature on the mortality burden of nonaccidental deaths in Yunnan Province and to further explore its spatial heterogeneity among different regions. Methods: We collected mortality and meteorological data from all 129 counties in Yunnan Province from 2014 to 2020, and 16 prefecture-level cities were analyzed as units. A distributed lagged nonlinear model was used to estimate the effect of temperature exposure on years of life lost (YLL) for nonaccidental deaths in each prefecture-level city. The attributable fraction of YLL due to ambient temperature was calculated. A multivariate meta-analysis was used to obtain an overall aggregated estimate of effects, and spatial heterogeneity among 16 prefecture-level cities was evaluated by adjusting the city-specific geographical characteristics, demographic characteristics, economic factors, and health resources factors. Results: The temperature-YLL association was nonlinear and followed slide-shaped curves in all regions. The cumulative cold and heat effect estimates along lag 0‐21 days on YLL for nonaccidental deaths were 403.16 (95% empirical confidence interval [eCI] 148.14‐615.18) and 247.83 (95% eCI 45.73‐418.85), respectively. The attributable fraction for nonaccidental mortality due to daily mean temperature was 7.45% (95% eCI 3.73%‐10.38%). Cold temperature was responsible for most of the mortality burden (4.61%, 95% eCI 1.70‐7.04), whereas the burden due to heat was 2.84% (95% eCI 0.58‐4.83). The vulnerable subpopulations include male individuals, people aged <75 years, people with education below junior college level, farmers, nonmarried individuals, and ethnic minorities. In the cause-specific subgroup analysis, the total attributable fraction (%) for mean temperature was 13.97% (95% eCI 6.70‐14.02) for heart disease, 11.12% (95% eCI 2.52‐16.82) for respiratory disease, 10.85% (95% eCI 6.70‐14.02) for cardiovascular disease, and 10.13% (95% eCI 6.03‐13.18) for stroke. The attributable risk of cold effect for cardiovascular disease was higher than that for respiratory disease cause of death (9.71% vs 4.54%). Furthermore, we found 48.2% heterogeneity in the effect of mean temperature on YLL after considering the inherent characteristics of the 16 prefecture-level cities, with urbanization rate accounting for the highest proportion of heterogeneity (15.7%) among urban characteristics. Conclusions: This study suggests that the cold effect dominated the total effect of temperature on mortality burden in Yunnan Province, and its effect was heterogeneous among different regions, which provides a basis for spatial planning and health policy formulation for disease prevention. %R 10.2196/51883 %U https://publichealth.jmir.org/2024/1/e51883 %U https://doi.org/10.2196/51883 %0 Journal Article %@ 2369-2960 %I %V 10 %N %P e58761 %T Moderation Effects of Streetscape Perceptions on the Associations Between Accessibility, Land Use Mix, and Bike-Sharing Use: Cross-Sectional Study %A Guo,Huagui %A Zhang,Shuyu %A Xie,Xinwei %A Liu,Jiang %A Ho,Hung Chak %K built environment %K streetscape perceptions %K bike-sharing use %K cycling %K moderation effect %K China %D 2024 %7 3.7.2024 %9 %J JMIR Public Health Surveill %G English %X Background: Cycling is known to be beneficial for human health. Studies have suggested significant associations of physical activity with macroscale built environments and streetscapes. However, whether good streetscapes can amplify the benefits of a favorable built environment on physical activity remains unknown. Objective: This study examines whether streetscape perceptions can modify the associations between accessibility, land use mix, and bike-sharing use. Methods: This cross-sectional study used data from 18,019,266 bike-sharing orders during weekends in Shanghai, China. A 500 × 500 m grid was selected as the analysis unit to allocate data. Bike-sharing use was defined as the number of bike-sharing origins. Street view images and a human-machine adversarial scoring framework were combined to evaluate lively, safety, and wealthy perceptions. Negative binomial regression was developed to examine the independent effects of the three perceptual factors in both the univariate model and fully adjusted model, controlling for population density, average building height, distance to nearest transit, number of bus stations, number of points of interest, distance to the nearest park, and distance to the central business district. The moderation effect was then investigated through the interaction term between streetscape perception and accessibility and land use mix, based on the fully adjusted model. We also tested whether the findings of streetscape moderation effects are robust when examinations are performed at different geographic scales, using a small-sample statistics approach and different operationalizations of land use mix and accessibility. Results: High levels of lively, safety, and wealthy perceptions were correlated with more bike-sharing activities. There were negative effects for the interactions between the land use Herfindahl-Hirschman index with the lively perception (β=–0.63; P=.01) and safety perception (β=–0.52; P=.001). The interaction between the lively perception and road intersection density was positively associated with the number of bike-sharing uses (β=0.43; P=.08). Among these, the lively perception showed the greatest independent effect (β=1.29; P<.001), followed by the safety perception (β=1.22; P=.001) and wealthy perception (β=0.72; P=.001). The findings were robust in the three sensitivity analyses. Conclusions: A safer and livelier streetscape can enhance the benefits of land use mix in promoting bike-sharing use, with a safer streetscape also intensifying the effect of accessibility. Interventions focused on streetscape perceptions can encourage cycling behavior and enhance the benefits of accessibility and land use mix. This study also contributes to the literature on potential moderators of built environment healthy behavior associations from the perspective of microscale environmental perceptions. %R 10.2196/58761 %U https://publichealth.jmir.org/2024/1/e58761 %U https://doi.org/10.2196/58761 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e57209 %T Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis %A Lai,Peixuan %A Cai,Weicong %A Qu,Lin %A Hong,Chuangyue %A Lin,Kaihao %A Tan,Weiguo %A Zhao,Zhiguang %+ Shenzhen Center for Chronic Disease Control, No. 2021 Buxin Road, Shenzhen, 518020, China, 86 0755 2561 8781, 1498384005@qq.com %K tuberculosis %K spatial analysis %K spatial-temporal cluster %K Shenzhen %K China %D 2024 %7 14.6.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Pulmonary tuberculosis (PTB) is a chronic communicable disease of major public health and social concern. Although spatial-temporal analysis has been widely used to describe distribution characteristics and transmission patterns, few studies have revealed the changes in the small-scale clustering of PTB at the street level. Objective: The aim of this study was to analyze the temporal and spatial distribution characteristics and clusters of PTB at the street level in the Shenzhen municipality of China to provide a reference for PTB prevention and control. Methods: Data of reported PTB cases in Shenzhen from January 2010 to December 2019 were extracted from the China Information System for Disease Control and Prevention to describe the epidemiological characteristics. Time-series, spatial-autocorrelation, and spatial-temporal scanning analyses were performed to identify the spatial and temporal patterns and high-risk areas at the street level. Results: A total of 58,122 PTB cases from 2010 to 2019 were notified in Shenzhen. The annual notification rate of PTB decreased significantly from 64.97 per 100,000 population in 2010 to 43.43 per 100,000 population in 2019. PTB cases exhibited seasonal variations with peaks in late spring and summer each year. The PTB notification rate was nonrandomly distributed and spatially clustered with a Moran I value of 0.134 (P=.02). One most-likely cluster and 10 secondary clusters were detected, and the most-likely clustering area was centered at Nanshan Street of Nanshan District covering 6 streets, with the clustering time spanning from January 2010 to November 2012. Conclusions: This study identified seasonal patterns and spatial-temporal clusters of PTB cases at the street level in the Shenzhen municipality of China. Resources should be prioritized to the identified high-risk areas for PTB prevention and control. %M 38875687 %R 10.2196/57209 %U https://publichealth.jmir.org/2024/1/e57209 %U https://doi.org/10.2196/57209 %U http://www.ncbi.nlm.nih.gov/pubmed/38875687 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 13 %N 3 %P e11617 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2021 %7 ..2021 %9 %J Online J Public Health Inform %G English %X Background: The initial limited supply of COVID-19 vaccine in the U.S. presented significant allocation, distribution, and delivery challenges. Information that can assist health officials, hospital administrators and other decision makers with readily identifying who and where to target vaccine resources and efforts can improve public health response.Objective: The objective of this project was to develop a publicly available geographical information system (GIS) web mapping tool that would assist North Carolina health officials readily identify high-risk, high priority population groups and facilities in the immunization decision making process.Methods: Publicly available data were used to identify 14 key health and socio-demographic variables and 5 differing themes (social and economic status; minority status and language; housing situation; at risk population; and health status). Vaccine priority population index (VPI) scores were created by calculating a percentile rank for each variable over each N.C. Census tract. All Census tracts (N = 2,195) values were ranked from lowest to highest (0.0 to 1.0) with a non-zero population and mapped using ArcGIS.Results: The VPI tool was made publicly available (https://enchealth.org/) during the pandemic to readily assist with identifying high risk population priority areas in N.C. for the planning, distribution, and delivery of COVID-19 vaccine.Discussion: While health officials may have benefitted by using the VPI tool during the pandemic, a more formal evaluation process is needed to fully assess its usefulness, functionality, and limitations.Conclusion: When considering COVID-19 immunization efforts, the VPI tool can serve as an added component in the decision-making process. %M 35082975 %R 10.5210/ojphi.v13i3.11617 %U %U https://doi.org/10.5210/ojphi.v13i3.11617 %U http://www.ncbi.nlm.nih.gov/pubmed/35082975 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 13 %N 1 %P e11621 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2021 %7 ..2021 %9 %J Online J Public Health Inform %G English %X Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic. %M 33936526 %R 10.5210/ojphi.v13i1.11621 %U %U https://doi.org/10.5210/ojphi.v13i1.11621 %U http://www.ncbi.nlm.nih.gov/pubmed/33936526 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 11 %N 2 %P e10155 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2019 %7 ..2019 %9 %J Online J Public Health Inform %G English %X IntroductionHealth inequality measurements are vital in understanding disease patterns to identify high-risk patients and implementing effective intervention programs in treating and managing sexually transmitted diseases. Our study seeks to measure and identify inequalities among chlamydia and gonorrhea rates using Gini coefficient measurements and spatial visualization mapping from geographical information systems. Additionally, we seek to examine trends of disease rate distribution longitudinally over a ten-year period for an urbanized county.MethodsChlamydia and gonorrhea data from January 2005 to December 2014 were collected from the Indiana Network for Patient Care, a health information exchange system that gathers patient data from electronic health records. The Gini coefficient was used to calculate the magnitude of inequality in disease rates. Spatial visualization mapping and decile categorization of disease rates were conducted to identify locations where high and low rates of disease persisted and to visualize differences in inequality. A multiple comparisons ANOVA test was conducted to determine if Gini coefficient values were statistically different between townships and time periods during the study.ResultsOur analyses show that chlamydia and gonorrhea rates are not evenly distributed. Inequalities in disease rates existed for different areas of the county with higher disease rates occurring near the center of the county. Inequality in gonorrhea rates were higher than chlamydia rates. Disease rates were statistically different when geographical locations or townships were compared to each other (p < 0.0001) but not for different years or time periods (p = 0.5152).ConclusionThe ability to use Gini coefficients combined with spatial visualization techniques presented a valuable opportunity to analyze information from health information systems in investigating health inequalities. Knowledge from this study can benefit and improve health quality, delivery of services, and intervention programs while managing healthcare costs. %M 31632602 %R 10.5210/ojphi.v11i2.10155 %U %U https://doi.org/10.5210/ojphi.v11i2.10155 %U http://www.ncbi.nlm.nih.gov/pubmed/31632602 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 9 %N 1 %P e7758 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2017 %7 ..2017 %9 %J Online J Public Health Inform %G English %X IntroductionTechnology that combines traditional manipulations with databasesand complete visualization of geographic (spatial) analysis employingmaps has been developed in order to explore the possibilities forGeographical Information Systems (GIS) to be used in sanitaryand epidemiological surveillance system based on the analysis ofmorbidity and identification of influence of hazardous chemicalenvironmental factors on human health.MethodsGraphical analytic method of information processing allowedvisual establishing of mathematically determined cause-and-effectrelationships between levels of air chemical pollution and morbiditylevels for purulent bacterial meningitis.ResultsCalculated average annual contaminations of atmosphere of 20administrative rayons and seven cities of Lviv oblast with carbonoxide, lead, sulfur dioxide, and dust during the period 2006-2014were the objects of the study. During a year, 1,920 air samples werecollected per each ingredient for each rayon and city according tolaboratory data of facilities of the State Sanitary and EpidemiologicalService in Lviv oblast. Average annual levels of the chemicalsubstances were determined within the M.A.C. in all rayons and cities.However, 4-6% of individual samples in the rayons and 8-10% ofindividual samples in the cities exceeded the allowed concentrations,which imposed a real ecological danger.Fig. 1.Levels of carbon oxide air contamination within rayons ofLviv oblastMorbidity intensity rates for purulent bacterial meningitis weredetermined for the same period according to statistical reports oninfectious disease morbidity in Lviv oblast. In different years, humanmorbidity fluctuated from 0.7 to 2.3 per 100 thousand of populationin the oblast.The study found the correlation between the concentrations ofcarbon monoxide, lead, sulfur dioxide, and dust in the air and levels ofincidence of bacterial meningitis in people in the cities of Lviv oblastwith 1,092 thousand inhabitants, which compose 42.3% of all oblastpopulation. Correlation coefficients are r = 0.78 (p<0.001), r = 0.70(p<0.001), r = 0.51 (p<0.005), and r =0.68 (p<0.02), respectively.Fig. 2.Correlation dependencies between air contamination andpopulation morbidity rates for purulent bacterial meningitis withinrayons of Lviv oblast.The search for a correlation between chemical contaminationof atmosphere and the morbidity level the rayon population of theoblast for purulent bacterial meningitis testified the existence of astatistically significant dependence between the level of morbidityfor all population layers and atmosphere contamination with sulfurdioxide, lead, carbon monoxide, and dust. The correlation coefficientsare r = 0.62 (p<0.002), r = 0.52 (p<0.005), r = 0.63 (p<0.005), r = 0.56(p<0.05), correspondingly.The study found the correlation between the concentrationsof sulfur dioxide, and lead in the air of Lviv oblast and levels ofincidence of purulent bacterial meningitis in children. Correlationcoefficients are r = 0.55 (p<0.05) and r = 0.57 (p<0.001), respectively.ConclusionsUsing GIS approach, the study resulted in the development ofmedical-geographical maps of administrative rayons of Lviv oblast.The maps include peculiarities for each year of surveillance. Cause-and-effect relationships between the levels of the anthropogenicpollution of the air basin of Lviv oblast and morbidity levels forpurulent bacterial meningitis for the oblast population have beenspatially and temporally visualized as a study result. %R 10.5210/ojphi.v9i1.7758 %U %U https://doi.org/10.5210/ojphi.v9i1.7758 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 7 %N 1 %P e5686 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2015 %7 ..2015 %9 %J Online J Public Health Inform %G English %X Bovine cysticercosis is a zoonotic foodborne disease caused by \"Taenia saginata\" involving cattle as the intermediate host and humans as the final host. Due to the slow development of cysticercosis cysts in cattle muscles and the complexity of cattle movements, there is a strong bias to consider the last farm location before slaughter as the location of infection for spatial analysis. This study presents an innovative approach to spatial analysis that takes into account uncertainty regarding the location where the animal was infected. An animal-herd-level weighted analysis was used and applied to bovine cysticercosis in France. %R 10.5210/ojphi.v7i1.5686 %U %U https://doi.org/10.5210/ojphi.v7i1.5686 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 3 %P e4982 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2014 %7 ..2014 %9 %J Online J Public Health Inform %G English %X OBJECTIVE: To determine whether the availability of mammography resources affected breast cancer incidence rates, stage of disease at initial diagnosis, mortality rates and/or mortality-to-incidence ratios throughout Mississippi.METHODS: Mammography facilities were geocoded and the numbers of residents residing within a thirty minute drive of a mammography facility were calculated. Other data were extracted from the Mississippi Cancer Registry, the U.S. Census, and the Mississippi Behavioral Risk Factor Surveillance Survey (BRFSS).RESULTS & DISCUSSION: There were no statistically-significant differences between breast cancer incidence rates in Black versus White females in Mississippi; however, there were significant differences in the use of mammography, percentages of advanced-stage initial diagnoses, mortality rates, and mortality-to-incidence ratios, where Black females fared worse in each category. Both the use and availability of mammography were negatively correlated with advanced stage of disease at initial diagnosis. No significant correlation was observed between breast cancer mortality and the availability of mammography facilities. By combining Black and White subsets, a correlation between mammography use and improved survival was detected; this was not apparent in either subset alone. There was also a correlation between breast cancer mortality-to-incidence ratios and the percentage of the population living below the poverty level.CONCLUSIONS: The accessibility and use of mammography resources has a greater impact on breast cancer in Mississippi than does the geographic resource distribution per se. Therefore, intensified mammography campaigns to reduce the percentage of advanced-stage breast cancers initially diagnosed in Black women, especially in communities with high levels of poverty, are warranted in Mississippi. %M 24678379 %R 10.5210/ojphi.v5i3.4982 %U %U https://doi.org/10.5210/ojphi.v5i3.4982 %U http://www.ncbi.nlm.nih.gov/pubmed/24678379 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 2 %P e4587 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X Improving survival rates at the neighborhood level is increasingly seen as priority for reducing overall rates of out-of-hospital cardiac arrest (OHCA) in the United States. Since wide disparities exist in OHCA rates at the neighborhood level, it is important for public health officials and residents to be able to quickly locate neighborhoods where people are at elevated risk for cardiac arrest and to target these areas for educational outreach and other mitigation strategies. This paper describes an OHCA web mapping application that was developed to provide users with interactive maps and data for them to quickly visualize and analyze the geographic pattern of cardiac arrest rates, bystander CPR rates, and survival rates at the neighborhood level in different U.S. cities. The data comes from the Cares Registry and is provided over a period spanning several years so users can visualize trends in neighborhood out-of-hospital cardiac arrest patterns. Users can also visualize areas that are statistical hot and cold spots for cardiac arrest and compare OHCA and bystander CPR rates in the hot and cold spots. Although not designed as a public participation GIS (PPGIS), this application seeks to provide a forum around which data and maps about local patterns of OHCA can be shared, analyzed and discussed with a view of empowering local communities to take action to address the high rates of OHCA in their vicinity. %M 23923097 %R 10.5210/ojphi.v5i2.4587 %U %U https://doi.org/10.5210/ojphi.v5i2.4587 %U http://www.ncbi.nlm.nih.gov/pubmed/23923097 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 1 %P e4397 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X This study was to elucidate the spatio-temporal correlations between the mild and severe enterovirus cases through integrating enterovirus-related three surveillance systems, including the sentinel physician, national notifiable diseases and laboratory surveillance systems in Taiwan. With these fully understanding epidemiological characteristics, hopefuly, we can develop better measures and indicators from mild cases to provide early warning signals and thus minimizing subsequent numbers of severe cases. Taiwan‰Û ªs surveillance data indicate that public health professionals can monitor the trends in the numbers of mild EV cases in community to provide early warning signals for local residents to prevent the severity of future waves. %R 10.5210/ojphi.v5i1.4397 %U %U https://doi.org/10.5210/ojphi.v5i1.4397 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 1 %P e4420 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X Multiple data sources are essential to provide more reliable information regarding the emergence of potential health threats, compared to single source methods. However, only ad hoc procedures have been devised to address the problem of locating, among the many potential solutions, which is the most likely cluster, and determining its significance. We incorporate information from multiple data streams of disease surveillance to achieve more coherent spatial cluster detection by using statistical tools from multi-criteria analysis. Our approach defines in an optimal way, how spatial disease clusters found by the spatial scan statistic can be interpreted in terms of their significance. %R 10.5210/ojphi.v5i1.4420 %U %U https://doi.org/10.5210/ojphi.v5i1.4420 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 1 %P e4443 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X Use GIS to illustrate and understand the association between environmental factors and spread of infectious diseases. Our case studies like analyzing the association between meteorological factors and Lyme disease risk in humans in Texas, elucidating factors that contribute to contamination of produce at preharvest level and identifying disease clusters in an fungal zoonotic disease like Valley fever, examine the relationship between environmental conditions, such as climate and location, and vector distribution and abundance. The above studies show spatial epidemiology being an invaluable field in the research and surveillance of infectious disease. %R 10.5210/ojphi.v5i1.4443 %U %U https://doi.org/10.5210/ojphi.v5i1.4443 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 1 %P e4459 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X This paper explored the development and implementation of the Global Positioning System/ Geographic Information System (GPS/GIS) enabled mobile-based disease surveillance system as a feasible and effective way to support and strengthen preparedness for H1N1 Influenza A during the 2009 Hajj. It demonstrates mobile computing technology can provide rapid and accurate data collection for public health decision-making during mass gatherings. The GIS-based interactive mapping tool provided a pioneering example of the power of a geographically based internet-accessible surveillance system with real-time data visualization. The technical challenges in the process of implementation and in the field were also identified. %R 10.5210/ojphi.v5i1.4459 %U %U https://doi.org/10.5210/ojphi.v5i1.4459 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 1 %P e4379 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X In this work, Spatio-Temporal Data Mining of disease surveillance data is done, to describe the underlying patterns in disease occurrences across populations and to identify possible causes that could explain them; for better disease core prediction, detection and management. MiSTIC algorithm is used to determine spatial spread of disease core regions (scale of disease prevalence), and the frequency & regularity of occurrence of different locations in space as disease cores. The results show good correlation between the etiologic factors of Salmonellosis and the detected core locations, in addition to the significant observation of highly localized nature of disease prevalence. %R 10.5210/ojphi.v5i1.4379 %U %U https://doi.org/10.5210/ojphi.v5i1.4379 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 5 %N 1 %P e4380 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2013 %7 ..2013 %9 %J Online J Public Health Inform %G English %X We present a disease mapping method that accounts for spatially uncertain data by informatively weighting the locations of interest. This method is applied to programmatic tuberculosis data collected over three years in Lima, Peru, with the goal of identifying potential hotspots of drug-resistance transmission. The flexibility of this method, which accommodates any general weighting scheme, allows us to examine the affects of different assumptions regarding the uncertainty present in the data. %R 10.5210/ojphi.v5i1.4380 %U %U https://doi.org/10.5210/ojphi.v5i1.4380 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 2 %N 1 %P e2893 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2010 %7 ..2010 %9 %J Online J Public Health Inform %G English %X Objective: We sought to identify and map the geographic distribution of available colorectal cancer screening resources, following identification of this priority within a needs assessment of a local community-academic collaborative to reduce cancer health disparities in medically underserved communities.Methods: We used geographic information systems (GIS) and asset mapping tools to visually depict resources in the context of geography and a population of interest. We illustrate two examples, offer step-by-step directions for mapping, and discuss the challenges, lessons learned, and future directions for research and practice.Results: Our positive asset driven, community-based approach illustrated the distribution of existing colonoscopy screening facilities and locations of populations and organizations who might use these resources. A need for additional affordable and accessible colonoscopy resources was identified.Conclusion: These transdisciplinary community mapping efforts highlight the benefit of innovative community-academic partnerships for addressing cancer health disparities by bolstering infrastructure and community capacity-building for increased access to colonoscopies. %M 23569578 %R 10.5210/ojphi.v2i1.2893 %U %U https://doi.org/10.5210/ojphi.v2i1.2893 %U http://www.ncbi.nlm.nih.gov/pubmed/23569578 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 2 %N 1 %P e2910 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2010 %7 ..2010 %9 %J Online J Public Health Inform %G English %X By using cloud computing it is possible to provision on- demand resources for epidemic analysis using computer intensive applications like SaTScan. Using 15 virtual machines (VM) on the Nimbus cloud we were able to reduce the total execution time for the same ensemble run from 8896 seconds in a single machine to 842 seconds in the cloud. Using the caBIG tools and our iterative software development methodology the time required to complete the implementation of the SaTScan cloud system took approximately 200 man-hours, which represents an effort that can be secured within the resources available at State Health Departments. The approach proposed here is technically advantageous and practically possible. %M 23569576 %R 10.5210/ojphi.v2i1.2910 %U %U https://doi.org/10.5210/ojphi.v2i1.2910 %U http://www.ncbi.nlm.nih.gov/pubmed/23569576 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 1 %N 1 %P e2771 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2009 %7 ..2009 %9 %J Online J Public Health Inform %G English %X Chlamydia trachomatis is the most prevalent infectious disease in the United States. Complications include pelvic inflammatory disease (PID), ectopic pregnancy, and infertility. The cost of PID in 1998 was estimated at greater than $1.9 billion. Screening intervention strategies are often consumed by those at low risk. The objective of this study is the development of a more cost-effective intervention strategy by employing Geographic Information Systems and Census Bureau demographic data in selected Local Health Departments in Illinois. %M 23569571 %R 10.5210/ojphi.v1i1.2771 %U %U https://doi.org/10.5210/ojphi.v1i1.2771 %U http://www.ncbi.nlm.nih.gov/pubmed/23569571