Communities adjacent to concentrated areas of industrial land use (CAILU) are exposed to elevated levels of pollutants during flood disasters. Many CAILU are also characterized by insufficient infrastructure, poor environmental quality, and socially vulnerable populations. Manchester, TX is a marginalized CAILU neighborhood proximate to several petrochemical industrial sites that is prone to frequent flooding. Pollutants from stormwater runoff discharge from industrial land uses into residential areas have created increased toxicant exposures. Working with local organizations, centers/institutes, stakeholders, and residents, public health researchers sampled air, water, indoor dust, and outdoor soil while researchers from landscape architecture and urban planning applied these findings to develop a community-scaled master plan. The plan utilizes land use and built environment changes to increase flood resiliency and decrease exposure to contaminants. Using a combination of models to assess the performance, costs, and benefits of green infrastructure and pollutant load impacts, the master plan is projected to capture 147,456 cubic feet of runoff, and create $331,400 of annual green benefits by reducing air pollution and energy use, providing pollution treatment, increase carbon dioxide sequestration, and improve groundwater replenishment. Simultaneously, there is a 41% decrease across all analyzed pollutants, reducing exposure to and transferal of toxic materials.  Many neighborhoods located along the Houston Ship Channel, including Manchester, TX, have been documented as having excess risks of exposure to acute pollution, emergency chemical spills and incidents, and high-impact natural and manmade disaster events ,2,3,4. TAs with many other underserved communities in the US, Manchester residents—who are 98% minority, 65% low-income, and 37% living at or below poverty line . In response to these and other documented excess exposure and health inequities, this study aims to use community engaged research and citizen science methods to derive data-driven community master plans to reduce toxic exposure and enhance resilience. Manchester neighborhood residents and affiliated organizations, such as Texas Environmental Justice Advocacy Services (t.e.j.a.s.), have long been involved in community engagement activities around environmental justice issues. Working with local organizations and residents, faculty, engagement staff, and students from the fields of public health, landscape architecture, and urban planning (1) conducted air, dust, and water sampling and analysis within the neighborhood to assess current exposure conditions, (2) developed a master plan to assist in lessening the risks of potential environmental exposures to the community’s residents in the future, and (3) used performance models to project the impacts of the master plan on future flooding and contamination. Through this approach, we seek to determine how citizen science informed environmental and spatial data can be best applied as evidence for design and planning decisions that reduce exposure to flooding and associated contamination during flood events. Located within one mile of 21 facilities that report to the Environmental Protection Agency’s (EPA) Toxic Release Inventory , the neighborhood of Manchester, TX is one of many communities adjacent to concentrated areas of industrial land use (CAILU) near the Houston Ship Channel. Manchester is located at the nexus of exposures to hazardous toxic substances and highly socially and physically vulnerable to the impacts of natural disasters, including flooding. Flooding associated with tropical cyclones and inland precipitation events is a major concern for many communities located along the Texas Gulf Coast, including Manchester. According to records, the return period of a normal hurricane along any 50-mile segment of the Texas coast is once every 5 years, with a major hurricane occurring nearly every 15 years . HoweverTo better understand potential causal pathways between flood exposures and health outcomes and to inform design decisions that may reduce risks, an interdisciplinary group of researchers and designers engaged in a deep participatory process with Manchester residents, stakeholders, and local organizations. Results from a December 2015 community health assessment conducted by the Texas A&M University Institute for Sustainable Communities and t.e.j.a.s. provided support for the hypothesis that hazardous environmental exposures and poor health status were at the forefront of the community’s concerns ,18. TherIn November 2016, surface water in 30 public areas across the Manchester neighborhood was sampled and tested for metal(iod)s. These areas were identified by residents as being prone to water pooling after rainfall . Tap watIn addition to sampling air, water, and soil in Manchester, sampling was conducted in the Ship Channel area following a petrochemical fire. In March of 2019, outdoor air samples (N = 30) were collected from affected public areas to rapidly quantify total volatile organic compounds (TVOC).Findings from environmental samples highlight a need for additional research to understand the scope of these potential exposures. Research translation was aided by geocoding  the locaThe number of participatory urban design projects has increased in underserved communities in recent years, in part to address problems associated with environmental justice . Urban dService-learning projects typically involve a series of collaborative actions with communities, including consultation, information sessions, data gathering, and feedback loops ,32,33. TFirst, an introductory meeting allowed the design team to discuss site-specific problems, initiating a general discussion to help identify high risk areas based on local knowledge, as well as pinpoint current and future flood vulnerable areas. A second meeting presented City of Houston officials with findings from the initial site analysis. Feedback from Manchester residents not only provided further insight that identified unseen conditions but also generated ideas for future land use functions to be incorporated into conceptual design scenarios. A third and fourth meeting involved a feedback loop between community members and design teams in which a series of design scenarios were presented and critiqued by neighborhood residents. Responses from the community to the design team were then used to combine the scenarios into one unified community-scaled master plan. Quantification of the performance of planning scenarios has become an essential component of flood mitigation . In thisThe Long-Term Hydrologic Impact Assessment (L-THIA) model estimates the average annual runoff and pollutant loads for land use configurations based on more than 30 years of daily precipitation data, soils, and land use data for an area . The L-T2. Analysis of indoor dust samples identified markers of petroleum in all homes  as well as presence of all 16 priority PAHs and the subgroup of 7 probable human carcinogens. The concentration of total PAHs in each soil sample ranged from 54.7 to 4378.3 μg/kg. Results suggested that the dominant source of both indoor and outdoor PAHs was combustion, which could be attributed to the major transportation infrastructure, 24-line railyard, and industrial complexes that are in close proximity to the neighborhood. Concentrations in excess of the US EPA’s National Recommended Water Quality Criteria for chronic exposure in freshwater aquatic life for arsenic (150 μg/L) and mercury (0.77 μg/L) were found in pooled water samples collected from two locations, while twelve locations exceeded the recommended limit for lead of 3.2 μg/L [Results from environmental sampling and testing found evidence that some pollutants exceeded federal guidelines . The con3.2 μg/L . Detecta3.2 μg/L , all samThe design sought to recognize resident concerns related to limiting the dislocation of current residents while simultaneously shield residents from issues related to contaminant collection and transport. Three primary sources of toxicant transferal were identified from the engagement: (1) byproducts from industrial stormwater runoff, (2) hydrologic discharge from the highway overpass, and (3) emissions from railyard traffic and rail deliveries into the neighborhood carrying toxic chemicals for industries see . To addrTo assess the impacts of the master plan and design strategies in pollutant reduction during a flood disaster, we used the Center for Neighborhood Technology’s (CNT) GVC and the L-THIA model that were developed for evaluating the effects of green infrastructure on stormwater runoff and pollutant loads. The GVC was used to assess the performance, costs, and benefits of the green infrastructure utilized within the community-scaled master plan. The L-THIA was used to assess the projected performance of the master plan on pollutant totals See . OverallThis project sought to improve our understanding of how citizen science-informed spatial data could be combined with limited data available from environmental sampling and landscape performance calculators to provide evidence for design and planning decisions that reduce exposure to flooding and flood-mobilized contaminants among residents of a Houston environmental justice community. Developing new approaches to mitigate the impacts of flooding will become more important because, as the frequency and severity of both nuisance and major flooding increases globally, the threats to human and environmental health, particularly in CAILU neighborhoods, will also intensify. For example, even relatively small increases in the global mean sea level are predicted to double the frequency of both coastal and tidal flooding over the next several decades ,50. IncrA major methodological contribution of this research is the integration of primary environmental assessments with pre-design analysis, design development, and post-design evaluation. Existing (secondary) data are often too coarse in spatiotemporal resolution to address context-specific problems and inform actionable design decisions. The field sampling identified site-specific issues, pinpointed the spatial extent, quantified the severity of different pollutants in the neighborhood, and suggested possible environmental risk factors and infrastructure deficiencies that could be addressed in the design phase. Guided by this fine-grained data, the master plan is developed to target specific hazardous conditions and toxic materials. The performance evaluation process allows different design alternatives to be compared and the post design reductions of the pollutants to be quantified. Such a process ensures quantifiable metrics are truly integrated into the design and enhances the rigor of community engaged design research that has inherent subjectivity.In addition to the quantifiable assessments, this project also demonstrates how service-learning programs can be used to integrate community-sourced data into interdisciplinary design projects and used for design decision making. In this case, the deep community engagement enabled by linkages between communities and a group of centers, institutes, and programs at Texas A & M University allowed for the alignment of a design program with the community’s self-identified needs. This meant that projects could have a stronger positive impact on annual economic benefits, stormwater retention, and contaminant reduction. Citizen scientists served several important roles that supported these outputs. First, citizen science informed the rationale for design decision making. Too often, designers and planners simply rely on aesthetics and existing frameworks to develop master plans. The use of engagement and locally generated evidence to reinforce decision making clearly produces stronger, and more relevant results. Second, it focused the plan by identifying specific issues of priority to the community that could be directly treated through design. This provided a series of targeted actions for which strategies could be developed to solve. Third, the dissemination of findings from our research helped improve the community’s understanding of the causes and effects of environmental contamination. This form of educating residents of CAILU neighborhoods through visualization and presentation of results works as part of a feedback loop and allows communities to make better decisions through engagement. Fourth, participation in this process—and the related implicit valuation of local knowledge—spilled over into other aspects of engagement and assisted the research team in understanding conditions that we were unable to see by not living, working, and socializing in the neighborhood on a daily basis. Finally, the products generated through these processes were able to both identify and suggest provisions for community toxic transferal issues and provide hope moving forward. The documents created can be used by neighborhood advocates to support their case to policy makers to help improve conditions in the future. This approach is not without limitations. First, both the research team and the community must be both flexible and highly dedicated to the project since community engaged design can take longer to complete than a design that is not informed by local knowledge, deep local involvement, and multiple opportunities for feedback. Community timelines are not based on the academic semester but are generated by their own priorities, meaning that community members may not always available to participate in research activities on an academic timeline. When working with a diverse set of community stakeholders, research and engagement staff must be prepared for the reality that the concerns and priorities of community stakeholders will not be uniform and may in fact be at odds with one another. University faculty, staff, and students often require cultural competency training to break down assumptions and address stereotypes. Therefore, working with experienced engagement staff like those at the University’s Center for Housing and Urban Development, Texas Target Communities, and Institute for Sustainable Communities who have developed trust with partner communities is critical to ensure that neighborhood representatives feel comfortable and empowered in sharing information. In the long-term, ongoing engagement supported through institutional resources that allow for sustained communication between community leaders and academic partners ensures more credible inputs and fosters more reliable outputs. Engagement partners are more hesitant to engage with researchers in short-term or one-off projects that operate based on a grant funding cycle since they are unlikely to realize real change on those externally driven timelines. If these challenges can be addressed and participatory activities adequately prepared for, citizen involvement can improve chances for success of this type of sustainability research while accomplishing dual goals that extend scientific knowledge and build local capacity to enacting positive change within communities. Our study offers new insights into addressing contaminant exposure of vulnerable communities and tests a methodological framework that integrates community engaged research, citizen science environmental assessments, and community plan development using a CAILU neighborhood prone to frequent flood  as a testbed. The research is novel in that it combines the interdisciplinary fields of public health, landscape architecture, and urban planning with local-scaled citizen science to solve issues related to contamination and flooding. The research aims to develop actionable plans through land use and environmental modifications to transform CAILU neighborhoods through reduction of toxic exposure and flooding. The research approach can easily be applied to other neighborhoods experiencing similar circumstances, as these are ubiquitous problems across many urban areas. To achieve this, it is important to develop trust and long-term relationships with local community members and organizations across transdisciplinary fields of research and allow the communities to understand what each field can help them achieve. Specific tasks need to be developed for each discipline, with a focus on how each can build off and integrate with one another. Our findings demonstrate the importance of environmental sampling data and community engagement processes to inform planning and design. As a result of these processes, the plan achieves the goals of reducing runoff, air and water pollutions, increasing carbon dioxide sequestration, and facilitating groundwater replenishment. The plan also leads to an average of 41% decrease across all analyzed pollutants, reducing potential exposure to and transferal of toxic materials. Taken together, our findings illustrate the strength of community engaged research to identify environmental features important to residents and create action-oriented solutions towards environmental justice, health, and resilience.


There is little information about the diet, lifestyle and parental characteristics associated with habitual sugar-sweetened beverage (SSB) consumption in Asian children. The aim of the present study was to assess cross-sectional associations between habitual SSB consumption and preschoolers’ diet, physical activity, sedentary behaviour as well as parental and child characteristics in Malaysian preschoolers aged 3 to 6 y.A total of 590 preschoolers, comprising 317 boys and 273 girls were included. Pre-pilot parental questionnaires were used to assess diet, physical activity (PA) and sedentary behaviour practices and anthropometry was assessed in preschoolers and their parents.p < 0.001] and monthly fast food consumption , were associated with higher SSB intake (≥5 days in a week), after adjustments of potential confounders. Preschoolers with higher daily fruit and vegetable intake had lower SSB intake . A positive association of higher weekly vigorous PA  and daily screen-based practices  on habitual SSBs intake was also substantiated.Multiple logistic regression analyses showed that preschoolers with more frequent weekly intake of snacks [OR 2.7; 95% CI, 1.6–4.4; Multiple diet, physical activity and sedentary behaviour factors were significantly associated with SSB intake among Malaysian preschoolers. Continued effort is required to encourage healthier beverage choices, as well as healthy diet and active lifestyle practices among children during the critical early years of growth and development. Over recent decades, the prevalence of childhood obesity has increased more rapidly in low- and middle-income countries than in developed countries . The worThere is an urgent need for a comprehensive understanding of the potential diet and lifestyle determinants of excess weight gain and risk of obesity in preschoolers. The preschool years are a critical period of rapid growth and development with implications for life-long health status , 6. For Research to date has attempted to identify the influence of diet, physical activity and sedentary-related factors of children as well as parental socio-demographic characteristics on SSB consumption, but research has focused mainly on older children and adolescents , 17, 20.n = 539). Each completed parental questionnaire was checked by trained nutrition students for completeness and accuracy. The present study was approved by the Human Research Ethics Committee of the Universiti Sains Malaysia (USM). Written informed consent was obtained from either the parent or guardian of the children prior to the study.Preschoolers aged 3 to 6 y (317 boys and 273 girls) were recruited from urban and suburban areas of the district of Kota Bharu, Kelantan, Malaysia. Children were recruited from 16 preschool centers, randomly selected from 169 kindergartens registered with the State Education Department of Kelantan, Malaysia. Of these, about 8 kindergartens were randomly selected for Malay preschoolers; whereas 8 kindergartens from a total of 13, with at least 50% Chinese children, were randomly selected to recruit Chinese children. Parents or guardians of children selected were invited to participate in the study. Detailed explanations and discussions were conducted with the person-in-charge of selected preschool centers such as the principal and/or teachers, and parents or guardians. This included the nature, purpose, and the detailed measurement procedures used in the study and data collection was carried-out during the school day. Children were eligible to participate in this study if they met the following inclusion criteria: 3 to 6 years, being healthy and physically active i.e., free from any physical or mental disability, and not taking any long-term medication associated with any medical health problems that could influence their nutritional and health status. The two different measurements, a self-administered parental questionnaire and anthropometric measurements of the children were carried-out by researchers either at school or in the home. The questionnaire was completed by a parent (94.9%), mainly by the mother (2). Waist and hip circumference were measured with an inelastic measuring tape. All anthropometric measurements were taken twice and an average value was calculated. For the parental anthropometry assessment, BMI of parents were calculated based on their self-reported height and weight and categorized in accordance with the WHO standard for adults  than those with three or fewer siblings. For dietary practices, children with higher snack intakes of 5 times or more in a week  and monthly intake of fast food of at least once per week  had significantly higher odds of SSB intake compared to those with lower intakes of snack and fast food groups, respectively. On the contrary, preschoolers with higher fruit and vegetable intake (2 servings or more in a day) had significantly lower intake of SSBs  compared to those with lower daily intake. Children who either reported weekly participation in vigorous PA  or 2 h or more of daily screen time , had significantly higher weekly intake of SSBs, after full adjustment of all potential confounders.Table The main findings of the study indicate that high intakes of fast food and snacks, low intake of fruit and vegetables, high weekly vigorous PA, and high daily use of screen-based media as well as having more than three siblings were significantly associated with more frequent intake of SSBs. This was after full adjustment for age, gender, ethnicity, BMI, parental socio-demographic and economic status, diet, physical activity and screen-based sedentary practice confounders. This result suggests that multiple factors are associated with SSB intake in this group of preschoolers. To the best of our knowledge, this is the first study to document the diet, physical activity and sedentary practices of preschoolers, as well as parental weight status and socio-economic characteristics on SSB intake. Other studies have been more limited in focus and assessed a limited range of nutrients or foods and socio-demographic status , 23, 29,Fast food and snack consumption were significantly associated with greater consumption of SSB, similar to findings of several studies conducted in Western countries , 31. ThiBased on the current pattern of SSB consumption of preschoolers, conventional sugar-added beverages such as coffee, tea, malted and other conventional flavored beverages were still very popular, however, the commercial availability of ready-to-drink SSBs is increasing. Almost 54% of children reported consuming SSBs each week, a consumption pattern consistent with reports from other countries. For example, non-traditional sugar-added beverages such as fruit drinks and sports/energy-related beverages are becoming a common choice compared to soda beverages among children aged 2 to 11 years in the United States , Australp < 0.0001), whereas no such significance was found between maternal BMI and a child’s BMI (data not shown). This finding suggested that higher levels of maternal education were significantly associated with lower risk of being underweight. Moreover, maternal educational status of preschool boys was significantly higher compared to girls, which could possibly explain the relatively high number of girls who were underweight. Therefore, the present finding emphasises the need for nutritional and health promotion intervention programs of younger children tailored to families with a low level of education.Significant gender differences on BMI, household size, measures of eating practices, and sedentary practices, and parental BMI and educational status were also found. For instance, the percentage of girls who were underweight is very high at 29.7%, twice that of boys (12.9%). In addition, girls were less likely to consume breakfast at least 5 days a week, and were more likely to eat snacks. This raises nutritional concerns about the possible underfeeding of young girls and the preferential feeding of young boys. Although the precise mechanisms are not understood, it is generally agreed that underweight in children is significantly associated with socioeconomic hardship at the household level. In the present study, there was a significant inverse association between maternal education status and a child’s BMI  of consumption of SSBs from various places such as at home, nursery or preschool centers. Thirdly, parental weight and height were self-reported and this may have resulted in some misclassification of overweight and obesity. Fourthly, it is generally agreed that any epidemiological research involving recall is prone to recall bias or errors caused by systematic differences in the accuracy or completeness of recollections by study parents regarding events or experiences from the past. In the present study, recall bias was minimised because of the relatively short recall duration of the past week. Recalling the dietary habits and lifestyle practices across the previous week was a relatively low burden to the parents or guardians and provided an accurate assessment of the pattern of food consumption and lifestyle practice of children. Such an approach takes into account day-to-day variation attributed to interactions between biologic and environmental influences such as appetite, weekday, weekends, physical activity, leisure time, and personal economic conditions and is consistent with previous studies among young children , 45 and A large proportion of preschool-aged children in Malaysia consume SSBs every week with consumption significantly associated with intake of fast food, snacks, low fruit and vegetable intake, vigorous physical activity, sedentary practices, and number of siblings after adjusting for potential confounding factors. Based on the current findings, ongoing efforts are needed to provide healthy eating environments, both at home and at preschool centers. This would include the provision of a variety of fruit and/or vegetables as snack intake for preschoolers in order to decrease the intake of SSB, with the consequent benefit of preventing adverse health effects such as excessive weight gain, and the risk of obesity and cardiometabolic disorders during childhood and in later life. Further research is needed to confirm these findings in a large population and to explore possible dietary and lifestyle intervention strategies to reduce the habitual consumption of SSB among growing children during the preschool years.


Professional networks are critical for PhD students and early career faculty, yet there is scant research on the development of their professional networks. Social network analysis is a useful approach to describe the development of professional networks. This methodological paper explains its use and benefits, using a social network analysis of alumni from the first three cohorts of the Association of Gerontological Education in Social Work (AGESW)’s Pre-Dissertation Fellowship Program (PDFP) as an example. We present results, challenges, and recommendations. Alumni (n = 12) reported meeting an average of 20 scholars (SD = 13.2) through AGESW. These professional relationships led to collaborations on conference presentations and manuscripts as well as opportunities to leverage the relationships for future professional needs. Suggested applications of social network analysis for program evaluation, such as co-author and citation networks, are also presented with a focus on training programs designed to support robust professional network development.


Sentences reporting mutation or differential expression in cancer were extracted from more than 40,000 publications, and healthy gene expression data with samples mapped to organs are available for both human genes and their mouse orthologs.OncoMX has prioritized user feedback as a means of guiding development priorities. By mapping to and integrating data from several cancer genomics resources, it is hoped that OncoMX will foster a dynamic engagement between bioinformaticians and cancer biomarker researchers. This engagement should culminate in a community resource that substantially improves the ability and efficiency of exploring cancer biomarker data and related multidimensional data. Cancer biomarkers are commonly individual genes or proteins, multigene/protein panels, or biomolecules, like glycans, analyzed from urine, blood, stool, or other biologic sample. Biomarker diversity is ever growing and may also include findings from image analyses,5 gut microbiome abundance,6 and others.Cancer biomarkers are molecules that can be assayed from bodily fluids or tissues whose presence indicates some process(es) associated with cancer.8 Paired with increased funding opportunities, such as those enabled through the Precision Medicine Initiative of 2015, it is not surprising to find increased reports of potentially novel cancer biomarkers.9 However, reproducibility of initial findings, clinical validation, and access to harmonized biomarker and associated data remain formidable challenges.7Attempts at molecular characterization of cancer samples have increased as a result of advances in high-throughput sequencing and other technologic progress.10; CBD—the Colorectal Cancer Biomarker Database containing colorectal cancer biomarkers reported from articles in PubMed;11 ResMarkerDB—the database of biomarkers of drug response to monoclonal antibody therapy in breast and colorectal cancer,12 and more.13 Additional current and past efforts exist, such as those belonging to the Cancer Biomarkers Research Group of the National Cancer Institute Division of Cancer Prevention, including the Alliance of Glycobiologists for Cancer Research,14 the Consortium for Imaging and Biomarkers (CIB),15 and others,16 and more biomarker information can be obtained directly from the literature or other published sources. Although not always biomarker centric, the National Cancer Institute Informatics Technology for Cancer Research (ITCR) program funds a number of resources, including HemOnc,17 the Cancer Proteome Atlas (TCPA),18 the Patient-Specific Drug-Gene Networks for Recommending Targeted Therapies (CDGNet),19 and others, that describe, generate, analyze, or link cancer data that could provide additional evidence for biomarker relevance. It seems logical, then, that these various data could be combined into a meta-resource for the search and exploration of cancer biomarker–related information.While issues of reproducibility and clinical validation must be addressed by biomarker research and regulatory communities, usability and accessibility of findings can be addressed in the public domain. In fact, a number of research groups already make cancer biomarker data available, including EDRN—the Early Detection Research Network focusing on the research and development of biomarkers and technologies for the clinical application of early cancer detection strategiesKey objective:To develop a data model and central, unified, integrated Web resource to enable improved exploration of cancer biomarkers in the context of related evidence.Knowledge generated:A data model was developed to describe cancer biomarker evidence and that was capable of accommodating heterogeneously structured extant data and extensible to diverse new data types. Data integrated and unified through this model were made available through OncoMX, a knowledgebase and Web portal for exploring cancer biomarker data and related evidence.Relevance:Cancer biomarker evidence can be accumulated across various resources from a single access point through OncoMX to generate summary reports for a given gene, including available information on clinical status and relevance. Furthermore, OncoMX is linking to several other resources, improving the reach of each resource reciprocally and increasing the utility of any given data set.However, the above-mentioned data sets are highly variable in scope, developed for specific biological applications, specific to certain cancer types, limited by regulatory status, or pertinent to specific clinical populations. Furthermore, data formats are frequently heterogeneous, lacking common attributes to enable integration. Improved modeling of cancer biomarker data would facilitate the integration of interscope biomarker data. Ontology unification and mapping through common resource accessions would improve the quality of integration, downstream assertions, and reasoning. Improved data provenance tracking would transparently communicate parametric configurations and assumptions made during processing and retrieval, and the availability of integrated data  would enhance the usability of the underlying biomarker data.) into the OncoMX knowledgebase and Web portal for cancer biomarker exploration. Integrated data types include cancer mutation, cancer differential expression (mRNA and miRNA), cancer expression specificity (single cell RNA [scRNA] sequencing), healthy expression (mRNA from human and mouse), literature mining for cancer mutation and expression, EDRN biomarkers, and FDA-approved breast cancer biomarkers2.To address these issues, the OncoMX group developed a data model to integrate public biomarker data from EDRN and the US Food and Drug Administration (FDA) and additional related data around persistent accessions and identifiers. The resulting model provides the foundation for integration of heterogeneous biomarker evidence (using the BioCompute Object [BCO] framework22 and mutation in cancer from Extraction of Mutation Association to Diseases (DiMeX) (University of Delaware)23; RNA sequencing–derived healthy expression calls and ranks for human and mouse from Bgee, a Database for Gene Expression Evolution (SIB Swiss Institute of Bioinformatics)24; and the FDA-approved breast cancer biomarkers and cancer cell–type expression specificity from scRNA sequencing (George Washington University). Data were pulled from external consortium databases for public biomarker data from EDRN,10 cancer mutation data from BioMuta,26 cancer differential expression of mRNA and miRNA from BioXpress,27 and Reactome.28 The Data Supplement provides a summary of data access and pertinent details for OncoMX and contributing resources.Data were provided as .txt, .tsv, or .csv files for the following: literature mining for differential expression in cancer from DEXTER—Disease-Expression Relation Extraction from Text29 terms for disease names and through Uberon Anatomical Entity Terms30 for anatomic structure names. Data not already annotated with the UniProt Knowledgebase (UniProtKB)31 accessions (AC) were mapped to the canonical set of UniProtKB AC through gene symbol, transcript, biomarker name, or genes included in a biomarker panel, and AC were filtered if existing outside the canonical set. An OncoMX field dictionary was created that leveraged field names and ontology terms of existing resources ,33 and so on), and headers were uniformly formatted and mapped to existing OncoMX field names. Resulting files were checked for completeness and adherence to expected content and subjected to automated quality check to ensure integrity and format sanity. Pipeline steps, provenance details, and other metadata were captured using the BCO20 specification and output in JavaScript Object Notation (JSON) and .txt formats. All processed data and corresponding metadata objects were entered into a database and subjected to version control. Additional processing considerations for specific data sets are described below.Many data sets used by OncoMX were initially processed by external pipelines documented in source resources. A summary of relevant preprocessing details for cancer mutation, cancer differential expression, healthy expression, and biomarkers is included in the Data Supplement, along with links to documentation. Data sets were unified through Cancer Disease Ontology (CDO) slim26 A new pipeline was developed for cancer mutation to improve the tracking of downloaded content, unify data in .vcf format, subject resulting information to automated quality check, automate mapping of disease terms to CDO slim terms and genes/transcripts to UniProtKB AC using gene symbols or alternate accessions, generate frequency across sources, and automate site annotation and functional impact prediction. Minor updates were made to the differential expression analysis pipeline, including updating the analysis package to DESeq2,34 mapping cancer subtypes to parent CDO slim terms, and quantifying patient ratios for each direction of expression change . Resulting data were subjected to the general OncoMX processing steps outlined above before integration.Earlier versions of the cancer mutation and differential expression data sets were updated to include additional data , and the expression data set was updated to include miRNA analysis.35 and used to map human genes to orthologous mouse genes .A custom format of healthy (wild type) expression data was devised for RNA sequencing–derived expression calls for human and mouse. Data were limited to tissue types that had at least one reported association in the cancer mutation or differential expression data sets, as determined through mapping between CDO slim and Uberon Anatomical Entity. Data were further limited to adult developmental life stages. Analyzed expression values were ranked in two series for each species: one compared the expression of a given gene with that of all genes in a given tissue and the other compared the expression of a given gene with that of the same gene across all tissues. To enable cross-species exploration of expression profiles, the set of 1:1 orthologs between human and mouse were retrieved from the Orthologous MAtrix (OMA) database22 an automated text-mining tool, was applied on Medline abstracts to extract gene, disease, expression level, experimental context, and conditions being compared. Customized for OncoMX, DEXTER extracted expression differences in cancer compared with normal/control tissues and verified whether the normal tissue came from the same patient or not. DEXTER was applied on a comprehensive set of cancer-related abstracts identified using the PubMed query “cancer OR cancers OR carcinoma OR carcinomas OR neoplasm OR neoplasms,” which returned 3,717,745 abstracts (as of March 2018). Abstracts were filtered for those that contained words or phrases pertinent to expression, which reduced the number of abstracts to 1,750,928.DEXTER,23 is a tool that detects different types of connections between mutations and disease in the literature. For OncoMX, less reliable connections, such as those extracted on the basis of comentions, were dropped while maintaining association relations between mutation and a disease aspect. The mutation detection module of DiMeX was improved by integration with tmVar36 after performance evaluation of several mutation detection tools on a range of well-known corpora. The resulting integration enabled the reduction of false negatives without increasing false positives. DiMeX’s relation extraction module was also refined and improved by integrating more recent parsing technology.DiMeXPublic biomarker records were retrieved from EDRN, and a new data set of FDA-approved biomarkers in breast cancer was generated by manual search across Web resources (details are provided in the Data Supplement). The generation and integration of these data sets enabled the OncoMX team to troubleshoot issues of extension, facilitated augmentation of infrastructure to ensure interoperability between data of differing types, and demonstrated the immediate utility of newly added data and views available to the end user. A new, easily extensible, biomarker-centered data model was developed to describe a biomarker evidence data object, accounting for the relationships between data sets reporting clinical status of known and/or actively studied biomarkers (EDRN and/or FDA) and other biomarker evidence data types.37 and integrated into OncoMX (details are provided in the Data Supplement). Count tables were filtered for low-quality cells and low-abundance genes by filtering out samples with library sizes and features that expressed fewer than three median absolute deviations from the median value of each quality control metric computed from mitochondrial gene expression across all samples. Cell-specific biases between samples were normalized with a deconvolution approach38 in which pooled counts from multiple samples are used to compute size factors that are deconvolved to infer size factors for each sample. Data sets were filtered for target cell sequencing runs, and dimensionality reduction was performed using principal component analysis (PCA), t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection (UMAP). scRNA sequencing gene-level count matrices were analyzed for cell type–specific expression using Preferential Expression Measure (PEM), a metric designed for tissue-level expression specificity analysis,39 and qualitative annotations of specificity were computationally determined for each PEM score. Resulting data were mapped to UniProtKB AC, HGNC gene IDs, Ensembl gene IDs,41 DOIDs, and DO names, and were subjected to OncoMX processing steps described above.Expression of 10 cancer cell types across the brain, lung, and colon were analyzed from scRNA sequencing data from three studies retrieved from recount2All data were mapped to UniProtKB AC directly or through HGNC gene ID and/or Ensembl gene ID to UniProtKB AC. A data model describing a biomarker evidence object was devised such that an object of type biomarker evidence can be diverse  and is currently expected to map to information about one or many genes.42 was dockerized into a container, which allowed easy transfer and deployment across servers while maintaining a consistent architectural environment.OncoMX was developed within the virtual machine environment, configured using a 32-GB ram and 12 CPU virtual machine running under the CentOS Linux 7 operating system. The database was built under the MariaDB version 5.5.60 engine, running under the same server as and connected directly to the application, developed using Python Django framework integrating bootstrap 3 for user interface design and jQuery for interactive capabilities. The application was designed with user login security based on the Django authentication library and built to use RESTful Web services to expose the underlying database for external access. The application environment, including the Django framework,https://data.oncomx.org.Resulting data sets encompassed 939 and 96 unique biomarkers from EDRN and FDA, respectively, mapped to 20,576 genes with available mutation and/or differential expression in cancer. Sentences reporting mutation in cancer were extracted from 14,360 PubMed publications, and those reporting differential expression in cancer were extracted from 25,865 publications. Healthy expression data for 33,753 human and 45,879 mouse Ensembl gene IDs were retrieved, mapping to 19,555 canonical human genes, 15,349 with mouse orthologs. Integration of EDRN and FDA data sets solidified the need to describe both clinical assertions related to actively characterized cancer biomarkers along with other information that could be leveraged as biomarker evidence. A data model was developed to describe a biomarker evidence object that is extensible to any number of components but currently has components for provenance, genomic variation, gene expression, clinical status, and literature mining. Although not required, the current core of the provenance domain is the gene symbol as available biomarker related data contain or link to one or many genes or miRNAs. Granularity of biomarker-level details was retained without sacrificing gene-level detail for panels that contained multiple genes by mapping to each unique gene. The resulting model  accommodP value thresholds or specific disease labels. Other features include a landing page with search bar and quick links for data set exploration; a dashboard for visualizing statistics and summaries; a table viewer rendered dynamically on the basis of user interaction; various types of user documentation; and a contact form to solicit user feedback.Early Web development focused on basic gene search functionality such that a string search query results in the display of all visual and tabular information for a specified gene. Combinatorial filtering and analysis on the integrated data layer allow filtering by PCA3 is a long, noncoding RNA that is overexpressed in most prostate cancer PCa cells and is involved in regulating the expression of epithelial–mesenchymal transition markers, androgen receptor cofactors, and PCa suppressor PRUNE2.45 As depicted in PCA3 in prostate cancer. In fact, 49 of 52 samples have a logtwo-fold change increase in PCA3 expression in the tumor sample compared with its adjacent normal. Biomarker description, aliases, and publications reported by EDRN can be viewed in the biomarker details tab. Moreover, there are 14 literature evidences reporting upregulated PCA3 in prostate cancer. Of note, PCA3 expression in healthy samples is qualified as “MEDIUM” for earlier adult stages, but “HIGH” for later stages, which implies an association between PCA3 expression and age.https://www.nanostring.com/diagnostics/prosigna/technology/prosigna-algorithm). Clicking on the Biomarkers button from the landing page will redirect the user to the data exploration table that can be toggled between biomarker data sets and filtered for various attributes. Search for “ERBB2” in this table shows that this gene, well known for its indications for treatment and prognosis in breast cancer,48 is included in 10 FDA-approved biomarker products—nine individual amplification markers and one panel, the Prosigna multigene prediction panel. In the detailed search view, there are multiple evidences for ERBB2 in the literature, both for differential expression and mutation. Of interest, whereas the majority of differential expression evidences (n = 48) indicate upregulation, there are two evidences for downregulation. Exploration of the underlying data shows that downregulation has been observed in response to pertuzumab treatment in mouse xenograft studies49 and has been observed to be lower in obese patients with early-stage breast cancer.50 Visualization of available information shows that this gene is approved for various indications, including prognosis, prediction, and companion diagnosis ,52 CDGnet (CANCER Drug Gene Network),19 CDSA ,54 CIViC,53 HemOnc,17 iPTMnet,55 PDX (patient-derived tumor xenograft) finder,56 and TCPA (The Cancer Proteome Atlas). This model promotes the extensibility and sustainability of OncoMX and referenced resources by allowing OncoMX to focus on harmonization, integration, annotation mapping, evidence tagging, and database maintenance while outsourcing data set creation and curation to collaborators and other experts.OncoMX was designed to combine existing and newly generated data, establishing a strong application customized for cancer biomarker research. Although other multidimensional, integrated cancer resources exist, such as the OncoMX is actively seeking new data and types, such as imaging, glycan biomarkers, drug targets, methylation, alternative splicing, and more. Work in progress includes extending the data model to new types, integrating FDA data sets for additional cancers upon user request, improving healthy expression and cross-species visualization, and expanding cross references to key cancer resources. The OncoMX team will continue hosting workshops to ensure that development is shaped by users, facilitating engagement between stakeholders and ultimately resulting in an adaptable resource for the improved exploration and potential discovery of cancer biomarkers.


Family caregivers provide the bulk of unpaid care to older adults. The typical family caregiver is a 49-year-old woman who works full time and simultaneously provides an average of 24 hours of care per week for an older relative. Unfortunately, their caregiving duties places them at risk for lost wages and termination due to frequent interruptions at work, especially in the absence of a national paid family leave policy. It is possible that such a policy could mitigate these risks; however, the United States is the only developed nation that lacks a national paid family leave policy for all workers. This symposium will highlight the psychosocial, economic, and health issues experienced by working caregivers, and conclude by linking presenters’ findings to implications for a national paid leave policy. To start, presenter one will describe findings from a scoping review on workplace experiences of female family caregivers. Next, presenter two will describe findings from a systematic review to explore predictors of the adoption and implementation of state-level paid family leave policies. Presenter three’s study examines interest in supportive services among working and non-working Black caregivers in the Deep South. Presenter four will describe factors associated with healthcare utilization of working caregivers using data from the Regional Healthcare Partnership – Region 17 Health Assessment Survey. The final presenter, HHS Advisory Council to Support Grandparents Raising Grandchildren co-chair, will describe development of policy initiatives to identify, coordinate, and promote information, resources, and best practices for working grandparents raising grandchildren.


COVID-19 is the fifth and most significant infectious disease epidemic this century. Primary health care providers, which include those working in primary care and public health roles, have critical responsibilities in the management of health emergencies.To synthesize accounts of primary care lessons learnt from past epidemics and their relevance to COVID-19.We conducted a review of lessons learnt from previous infectious disease epidemics for primary care, and their relevance to COVID-19. We searched PubMed/MEDLINE, PROQUEST and Google Scholar, hand-searched reference lists of included studies, and included research identified through professional contacts.Of 173 publications identified, 31 publications describing experiences of four epidemics in 11 countries were included. Synthesis of findings identified six key lessons: (i) improve collaboration, communication and integration between public health and primary care; (ii) strengthen the primary health care system; (iii) provide consistent, coordinated and reliable information emanating from a trusted source; (iv) define the role of primary care during pandemics; (v) protect the primary care workforce and the community and (vi) evaluate the effectiveness of interventions.Evidence highlights distinct challenges to integrating and supporting primary care in response to infectious disease epidemics that have persisted over time, emerging again during COVID-19. These insights provide an opportunity for strengthening, and improved preparedness, that cannot be ignored in a world where the frequency, virility and global reach of infectious disease outbreaks are increasing. It is not too soon to plan for the next pandemic, which may already be on the horizon. Infectious disease epidemics are increasing in frequency and spread. Primary health care providers are at the forefront of community health care, and have an important role in managing health emergencies such as infectious disease epidemics. It is important to use lessons learnt from past epidemics to inform current health system responses. We examined evidence from past epidemics and identified six key lessons that have emerged in 11 countries during four previous epidemics and again during the COVID-19 pandemic. These lessons highlight the importance of integrating pandemic responses across health care disciplines, strengthening the primary health care system, defining the role of primary care during epidemics, protecting the health care workforce and the community, providing clear and consistent information and evaluating the effectiveness of health care responses. Health system weaknesses are exposed to health emergencies. Identification of these recurring lessons for primary health care provides an opportunity to definitively prepare for future infectious disease epidemics. The most notable include Severe Acute Respiratory Syndrome (SARS) during 2002–03 ; a novelThe World Health Organization (WHO) considers that comprehensive primary health care (PHC) is the ‘cornerstone’ of achieving universal health coverage and securing the health of populations around the world . PHC encSeveral reports and research studies have examined the PC response to infectious disease outbreaks and the impact of these on primary care providers (PCP) and communities. However, we were unable to locate any reviews that synthesized accounts of lessons learnt from past epidemics and their relevance to PC. This paper aimed to fill this gap and to determine what can be learnt from previous infectious disease epidemics for PC, and how these lessons are relevant to COVID-19.We conducted a rapid review of the literature, searching PubMed/MEDLINE and PROQUEST without date restrictions for English language material relating to  AND [‘primary care’ OR ‘primary health care’ OR ‘general practice’ OR ‘family medicine’] AND [SARS OR MERS OR coronavirus OR Zika OR pandemic OR epidemic] AND (AND ‘lessons’ OR “problems). We also searched Google Scholar and hand-searched reference lists of included studies and included grey literature sources known to the authors or identified through professional contacts. We used modified systematic review methods similar to those used in previous rapid reviews ,9. SpeedWe included publications that reflected on experiences during previous pandemics or epidemics and discussed PC lessons learnt or provided PC recommendations for future responses. We included peer-reviewed primary research or commentary as well as reports of reviews or investigations into national responses. We excluded publications reporting hospital or emergency department responses, public health surveillance and descriptive articles about epidemics or COVID-19 responses. While there was no date restriction applied to searches, we noted that no publications before 2001 were identified. We checked the sensitivity of our search strategy by re-conducting searches substituting the MeSH term ‘health systems, international’ for ‘health system response’, identifying earlier publications but none were suitable for inclusion.We defined PC as the service domain in which first-contact, ambulatory, biomedical care is provided to individuals in the community, including preventive services, curative and secondary care. PCPs include family doctors , nurses, nurse practitioners, community health workers and allied health practitioners. We defined PH as the service domain in which preventive and protective care is provided to communities, including surveillance, monitoring response preparedness, disease prevention, health protection and health promotion . PH and Each publication was examined and key PC lessons or recommendations arising from the experiences described were identified. These were synthesized and presented thematically. The themes arising from the analysis were discussed at length by two reviewers (JD and SH), with particular attention to the potential for bias.173 articles were identified, of which 31 were included in the review see , one theSix themes and associated sub-themes were identified and are described below. Eighteen studies highlighted the need to improve collaboration and day-to-day communication between PH and PC ,38,40, bInclusion of PCPs in pandemic response planning was advocated to recognize the essential role of PC in service delivery for communities, to contextualize responses to local circumstances and ensure adequate support and protection ,34,37–41Eight studies recommended strengthening the PC system in tandem with PH capability ,38,41, iExpert reviews of responses to SARS in Canada and Hong Kong, referred to a need to support the key sentinel role of primary care , throughExperiences from SARS ,33–35, HCommunity members also grappled with inconsistent messaging regarding risk and protective behaviours, resulting in fear and sometimes unwarranted presentation to health services . TargeteThe need for PC role definition was referred to in studies examining SARS ,25,35,36The need to consider pandemic preparedness plan implementation was emphasized, including formalized protocols and explicit mechanisms for distributing information and supplies to all PCPs, including ambulance paramedics . StudiesDuring the SARS outbreak, family doctors in Ontario reported not having the appropriate knowledge and skills to protect themselves, their patients, staff and their families ,36; cancThe need to clarify pathways of care ,38,39,41The need to consider the consequences of an epidemic on all aspects of care to avoid loss of services and unwarranted morbidity and mortality was identified after the African EVD epidemic ,21. FearNineteen studies from SARS ,30,33–36Identification and protection of staff and patients at greater risk of a poor outcome from infectious disease was recommended , includiDuring the SARS outbreak, PCPs in Singapore ,27, HongDuring SARS, many PCPs in Hong Kong delayed or avoided quarantining themselves or staff until an infectious state was confirmed, perceived to be due to fear of lost income, especially for solo practitioners . CentralThe provision of relevant information and training, and associated use of PPE, was considered one way to alleviate stress ,36. OthePublications about SARS in Canada , SingapoRigorous assessment of the disease response, including training and supervision of health workers, accessibility and medication supplies was recommended , as was This review describes PC experiences during four infectious disease outbreaks  in 11 countries over 14 years. Six key lessons emerged from these accounts. Epidemics and pandemics demand rapid system response to a new and uncertain clinical and epidemiological context, with a potentially high risk of morbidity and mortality of PCPs and their patients . In thesThe challenge of integrating PH, PC and the broader health system has been exposed during COVID-19 , and faiWhile most studies identified the need for improved collaboration and communication between governments, PH and PC, two studies ,31 identThe need to strengthen health systems, particularly PC, and the importance of PC in supporting each nation’s pandemic response has been exemplified as the world grapples with COVID-19 ,52. RepoWhile it is not unusual for experts to have differing opinions during a pandemic, the need for consistent, coordinated and reliable information, emanating from trusted sources, was resounding in the papers included in our review. The importance of consistent and trustworthy advice has been emphasized again during COVID-19 . EnglishThis review suggests that the PC role could be clarified and strengthened by each nation, recognising and supporting PCPs’ dual roles in providing clinical care and supporting PH control measures. A synthesis of PCPs’ experiences in 68 countries reported that PCPs in Singapore, Taiwan, Hong Kong and South Korea were well-prepared as a result of lessons learnt from SARS and MERS epidemics; however, PCPs in all other countries reviewed were ill-prepared and felt ill-informed of how to fulfil their roles . DespiteOur review emphasizes the critical importance of clarifying pathways of care for preventing disease transmission and ensuring safe and continued access to regular health care. International health system responses to COVID-19 have worked to maintain access to regular health care ,58, inclAlthough only one study in our review highlighted the importance of identifying and protecting vulnerable individuals, inequity and social disadvantage contribute to both infectious disease spread and amplification of the effects of a pandemic . Early rProtecting the health care workforce is critical during a pandemic. Despite relative early success in suppressing COVID-19 transmission, approximately 15% of cases in Victoria, Australia in August 2020 were health care workers . IsolatiStudies included in this review revealed high levels psychological distress and fear in PCPs related to fear of exposure to the infectious agent and of transmitting the infection to others; lack of access to appropriate PPE; lack of PC-relevant training and guidelines impacting safe work practices; and lack of clear and consistent information from reliable sources. Unfortunately, similar issues have arisen among PCPs during COVID-19, particularly related to insomnia, anxiety and depression , loss ofWhile only two studies included in our review referred to the need for evaluation of pandemic responses, we believe the evaluation is critical. Noting that many lessons from the past have re-emerged during COVID-19, the need to embed research, evaluation and continuous quality improvement into PHC efforts can accelerate progress and provide real-time feedback and guidance to inform policy . ContinuStrategies that can be developed to address the six key lesson identified in this review are mostly underpinned by the need to improved integration of PC and PH functions. Provision of consistent, coordinated and reliable information, clarifying PC roles and protection of vulnerable people, including health care workers, are all dependent on a critical starting point of effective collaboration and joint preparedness planning between PC and PH agencies. However, this is not without challenges and ambitious strategies such as the real-time extraction of sentinel data are dependent on factors such as individual provider and practice capability, and may not be feasible across all health systems.A focus of our review has been on the interaction between PC and PH as components of PHC, a lens which necessarily removes the focus from other parts of the health system and other sectors. A broader perspective on PHC might also identify intersectoral issues arising from infectious disease outbreaks, inclusive of the education, transport, labour market and food sectors, referred to as intersectoral action for health . A systeThe search strategy may have excluded papers with lessons of relevance to PC that were framed from a PH perspective but did not explicitly refer to PC settings. Meta-analysis was not possible due to the qualitative nature of most included studies. The use of one reviewer to screen and extract data may have introduced bias into this review, which is a limitation and trade-off in rapid review methods.We did not find a particular emphasis on health inequity and vulnerability in this review, although these issues have been a strong theme in the emerging literature on the impact of COVID-19 . People Despite the harm caused and lessons documented from past epidemics, COVID-19 has exposed the same PHC health system weaknesses. Our review demonstrates the ongoing challenges of integrating PC and PH, the case for strengthening PC involvement in pandemic planning and response - with clear PC and PH role definition, the importance of providing clear and consistent information, and the importance of protecting the health care workforce and the community. The visible reminder of these weaknesses provides an opportunity for action; one that should not be ignored in a world where the frequency, virility and global reach of infectious disease outbreaks are increasing.


The ubiquitous and openly accessible information produced by the public on the Internet has sparked an increasing interest in developing digital public health surveillance (DPHS) systems. We conducted a systematic scoping review in accordance with the PRISMA extension for scoping reviews to consolidate and characterize the existing research on DPHS and identify areas for further research. We used Natural Language Processing and content analysis to define the search strings and searched Global Health, Web of Science, PubMed, and Google Scholar from 2005 to January 2020 for peer-reviewed articles on DPHS, with extensive hand searching. Seven hundred fifty-five articles were included in this review. The studies were from 54 countries and utilized 26 digital platforms to study 208 sub-categories of 49 categories associated with 16 public health surveillance (PHS) themes. Most studies were conducted by researchers from the United States  and dominated by communicable diseases-related topics , followed by behavioural risk factors . While this review discusses the potentials of using Internet-based data as an affordable and instantaneous resource for DPHS, it highlights the paucity of longitudinal studies and the methodological and inherent practical limitations underpinning the successful implementation of a DPHS system. Little work studied Internet users’ demographics when developing DPHS systems, and 39% (291) of studies did not stratify their results by geographic region. A clear methodology by which the results of DPHS can be linked to public health action has yet to be established, as only six (0.8%) studies deployed their system into a PHS context. Today, 97% of Internet users worldwide are active on social media, and the number of social media accounts per average Internet users has grown from 6.2 in 2015 to around 8 in 20192. The low-cost data stream available on social media and other Internet-based sources is increasingly harnessed by clinicians, patients, and the general public to disseminate insights into disease trends and promote healthy lifestyles and health policies4. Every minute, people around the world are publicly sharing volumes of personal and communal health information on different digital platforms5, such as social media, discussion forums and blogs, and Internet search engines. Digital surveillance data, inspired by the definition of digital epidemiology data by Salathé6, is the publicly available user-contributed data not generated with the primary goal of surveillance. This data can provide an inlet to impervious populaces and has become integral to digital public health surveillance (DPHS). Public health surveillance (PHS), as a tool for monitoring and targeting interventions7, is the ongoing systematic collection, analysis, and interpretation of data, tightly integrated with the timely dissemination of these data to those who can undertake effective prevention and control activities9. Apart from the unprecedented volume of digital data, when used appropriately, these online resources can provide an increasingly clear picture of the dynamics and complexities of traditional PHS processes10. Compared to the data captured through traditional PHS channels, digital resources contain information that can be harnessed to reduce the time to outbreak detection, add more transparency to outbreak information published by the governments, and facilitate public health (PH) responses to emerging diseases and population-related risk factors10. These resources can be either used for infodemiology–utilizing digital data for mining, analysis, and information aggregation with the ultimate aim to inform PH and public policy or used for infoveillance– infodemiology methods with the main focus on surveillance11. Infodemiology was first formally introduced by Gunther Eysenbach in 2002 to describe the distribution of health information and misinformation on digital platforms12 and was later extended to other areas of utilizing digital data for PH research, such as outbreak detection, substance use, and drug utilization13.Internet technology is now a part of almost everyone’s life. Internet usage among US adults has steadily been increasing from 52% in 2000 to 90% in 201914, mining patient’s narratives about drug experiences on open-access forums15, geospatial tracking of the population during disease outbreaks, providing local and near real-time information to recognition of an outbreak17, and population-based clustering of behavioural risk factors such as physical inactivity, substance use, and poor diet in large population19 are examples of realizations of such opportunities.The interactivity of the Internet and the highly networked, hyperlocal, and contextualized nature of digital data offer an unparalleled opportunity for the public, patients, and health officials alike to communicate and address health issues. Profiling vaccine criticisms26. Bernardo et al. reviewed 32 studies published between 2002 and 2011 that utilized search queries and social media data for infectious diseases surveillance20. The authors concluded that even though there are challenges associated with the quality of digital data, there have been successful applications of digital disease surveillance since 2006 and their performances in terms of cost, time, and accuracy compare favourably with those of traditional surveillance systems. This was confirmed by a recent scoping review on using web-data for disease surveillance and epidemiology in which Mavragani studied 338 articles from 2009 to 2018 and highlighted the potential of digital surveillance in health informatics research26. Newer reviews on this subject have dealt with the popularity of different surveillance domains over time and summarized recent methodological developments mapped to each domain28. The most recent and extensive digital surveillance review28 has pictured a timeline, tracking interest online for PH and solely focused on ethical and validity issues ripe in the digital health monitoring revolution. While the topics covered in our review encapsulate those mentioned, this review will expand on the notion of DPHS by exploring more platforms and a broader context within the PH field. Moreover, a systematic evaluation is absent in the existing reviews, and most encapsulate only certain platforms or diseases/disorders. Therefore, we aimed to provide a comprehensive synthesis of evidence to add to the extant literature filling both of these needs while providing a proportional topic saturation level. Our scoping review also provides details on utilizing digital media in different aspects of PHS. This allows future researchers to identify where the need for future work is ripe and what untapped potentials need more attention in the digital surveillance sphere.Effective DPHS requires an understanding of the potentials and pitfalls of digital data for monitoring PH and exploring disease dynamics. Several narrative reviews of the application of digital media in PHS and epidemiology have been published29. While there are other well-established guidelines for conducting systematic scoping reviews32, the detailed reporting guideline, demonstrative examples, and best-practices for large-scale scoping reviews provided by PRISMA-ScR were ideal for our review. The search yielded 4249 articles. Excluding duplicates, we found 2907 studies from which we selected 755 studies of 16 PHS themes, associated with 49 PH categories and 208 sub-categories Table The surveillance theme with the most number of publications was the ‘communicable disease’ surveillance at 25% (187). The stark rise in the volume of communicable disease publications coincides with the 2016 Zika outbreaks. In 2016, ILI-focused studies were the most common ‘communicable disease’ studies (53%), following a similar distribution to the overall trend of all such studies. In 2017, Zika-focused studies were the most common (36%). Publications in 2017 saw a greater variety of health events studied  of the studies included in this review were published by researchers from the USA (426), UK (51), Australia (44), Canada (36), and Italy (36). The most common surveillance theme researched among these countries include communicable diseases, BRFs, chronic disease, drug utilization, and mental health  of the studies involved authors affiliated with academia, from which 460 studies are only academia affiliated. Only 3% (23) of studies have an author affiliated with governments, with ten of them studied communicable diseases, and three studied the general aspects of PH  Trends (GT and GFT) are utilized by 41% (76) of publications on communicable diseases, among which 57% (43) of studies aimed to predict outbreaks and seasonal diseases. From 69 studies that utilized Twitter to study communicable diseases, 32% (22) mined tweets for outbreak prediction. Facebook, Instagram, and YouTube were mainly utilized to study BRFs, focusing on smoking, substance use, and lifestyle. Fifty percent of studies that used Yelp investigated topics related to ‘health services’, while this number for Facebook, YouTube, Instagram, and GT is less than 2%  of publications on communicable diseases are infoveillance studies. This could be because of the great potentials of the existing digital data such as search queries and access logs to explore the public’s digital behaviour and detect epidemic outbreaks. The main objectives of infodemiology publications were to mine user’s status updates , and the most common finding was providing baseline data . Conversely, the infoveillance studies were dominated by the ones that showed the predictability  and applicability  of digital data for outbreak detection .We classified the studies based on their overall data collection and analysis methodology Fig. . StudiesFrom the manual content analysis of the objectives and findings of the included studies, eighteen distinct strands of investigations emerged. ‘Providing baseline information’ on risk patterns and trends in the occurrence of various health events 22%, 163), exploring the ‘applicability’ of utilizing web-based platforms in PHS systems , and ‘identifying user’s digital behaviour’ for evaluating the correlation between online activity and incidence and temporal trends of risk factors  are the top three  is the second most frequent objective associated with BRFs publications, with 89% 16) of them related to smoking (69%: e-cigarette/JUUL and LCC). Seventy five percent (12) of these publications showed the prevalence of advertising smoking behaviour (F14), and 19% (3) explored the marketing strategies used by smoking vendors (F10). This implies the utilization of digital resources as marketing platforms for different smoking brands, which may carry major PH risks  of mental health studies reported risk indicators (F7), from which 73% (14) were related to self-harm or suicide attempts. Applying linguistic analysis methods,37. Thirty eight percent (5) of studies placed in the [Cancer/F4] category used GT,,,,,Twenty one percent (13) of publications on drug post-marketing/utilization reported on the applicability (F1) of using Internet-based data in exploring drug safety/adverse drug reaction (ADR) (85%), post-marketing (8%), and drug abuse (7%). Interestingly, two studies showed that Twitter might not be a useful platform for this system, as the ADR reports on Twitter usually underrepresent specific drugs and often do not meet the FDA criteria required for reporting an ADR9, analyzing time, demographics , and place is a critical component of any PHS system35. Since the rise of Internet-based data usage in PHS, great strides have been made in identifying place, gender, and age from anonymous self-reported information on the Internet. Mining users’ profile information,,,,,38, and under-counting caused by sampling bias39 are challenges that still need to be addressed. The data analysis of 61% (460) of studies reflects the results of a specific time window, which, excluding communicable diseases, is the most common type of temporal analysis in all reported surveillance systems. Conversely, temporal analysis of the ‘epidemic occurrence’ of a disease and ‘seasonal patterns’ have been the commonly used inferential analytic approaches in analyzing communicable diseases data  of studies evaluated the usefulness of their proposed DPHS system by drawing a mapping between the system’s objectives and outcomes. Among these, 361  studies were evaluated subjectively, 116 (15%) used quantitative methods such as statistical analysis and machine learning (ML) techniques, and 85 (11%) used surveys/qualitative analysis methods. Twenty-five percent (192) of studies used the ‘representativeness’ approach to explore the extent to which the characteristics of reported events can accurately represent the incidence of actual health events1 of studFigure We report a comprehensive scoping review to summarize and synthesize evidence from a large and heterogeneous body of literature studying DPHS. The growing body of evidence of DPHS reflects the chronological availability of new digital platforms and new data mining and ML techniques. Our findings show the huge effect of mass media on the public’s information-seeking behaviour. Exploring these behaviours can help PH officials tailor their messages to address PH interests and improve healthcare delivery.Digital data can help portray the dynamics of PHS systems and allow PH professionals to pinpoint the general concerns or needs of the public during infectious disease events to create location-specific campaigns. For example, the finding that there is no association between dental caries and toothache-related information-seeking behaviours among South American Google users can reinforce the unfamiliarity of this population about the relationship between dental pain and the final stages of chronic oral diseasesOur findings show a higher prevalence of digital surveillance systems for communicable diseases . One possible reason for this is that topics such as seasonal outbreaks and epidemics, sexually transmitted and infectious diseases, can be coalesced in this category, making it a far-reaching one. Another reason may be the ease of using relative search volumes for various outbreak-related and infectious diseases using Google Trends, access logs on other social media platforms, as well as the fear/hype surrounding infectious diseases and different epidemics such as H1N1, Ebola, and Zika. Very few papers dealt with ‘disease burden’ (0.3%) and ‘occupational safety’ (0.5%), which came as a surprise given the excellent availability of Google Trends data.41. Although cannabis remains the most commonly used illicit drug in both countries, Australia has seen a drastic rise in the use of amphetamines and other illicit drugs since 2012. The USA holds the largest market for e-cigarettes. Also, it has the most reported vaping-related illness, particularly in young people. Furthermore, both countries have significantly more overweight or obese people. Recent reports show that 67% of Australian adults and 71% of American adults (over the age of 20) are overweight. Indeed, these factors, combined, may contribute to increased research in smoking, lifestyle habits and illicit substance use, which in turn increases the proportion of behavioural risk factor publications.The surveillance themes studied by each country appear to follow international trends Fig. a. Intere28. Given the limited length of data , different language styles between Internet users, and no restriction on their writing style, user-generated content often contains a high amount of noise, making the automatic information extraction and classification of free-text data challenging and time-consuming. Moreover, many concerns have been raised about the correctness and the quality of health-related digital data and the detrimental effects that misinformation can have on PH42. This concern with misinformation was also apparent during the 2014 Ebola outbreak,,,While the use of user-generated information on the Internet certainly shows promises, especially from the standpoint of providing an alternative and inexpensive solution to PHS, questions remain regarding the validity and generalizability of social media and Internet data35.First, we found that 61% (460) of studies conducted cross-sectional analysis  had an exploratory nature and attempted to gather information and data to inform PH officials about the potential of DPHS in different areas of PHS  of studies were limited by sample size and scope, as they used labour-intensive methods such as manual coding and qualitative analysis. The majority of the 219 studies that applied NLP methods used rule-based and lexical matching techniques such as topic modelling, sentiment analysis, and language modelling. These methods can only extract abstract themes at a high level, and the subjectivity in the interpretation of their results might limit the generalizability and the accuracy of the findings of these studies.Fourth, the content bias is another limitation of the included studies in our review. User-generated content on the Internet is highly biased as it reflects information that people are comfortable having revealed and may not represent the real spectrum of their feelings/experiences. In addition to this, our study’s results show that among the 554 studies that used text, image, or video data types, only 20% (111) took into account whether their findings were associated with the user’s personal experience  or not. Thus, there is a clear need for studies capable of determining and mitigating content biases that affect the formation and adoption of digital data for PHS.Fifth, the final link in the surveillance chain is the timely dissemination of the system’s findings to the general public or PH officials for action. Of the articles included in this review, only six (0.8%) linked their results for public health action. While there is a clear need for rigorous methodologies by which the results of DPHS systems can be converted into usable information, vigilance is still needed regarding the efficacy and safety of these findings to forgo the unintended consequences of these results on PH decisions.44, the difficulty of ascertaining demographics poses several unresolved questions regarding the inherent population biases of Internet users with different cultural background or socioeconomic status. Demographics for most digital platforms are not nationally representative and skewed toward younger age groups and users with higher levels of education46. We found that no studies assessed digital media utilization for vulnerable populations  who are underpresented on different digital platforms. Studies on detecting social bots are scarce. Considering the radically increasing rate of childhood obesity with the subsequent adolescent onset of nutrition-related chronic conditions such as diabetes and cardiovascular diseases48, which could be due to the massive exposure of adults and children to unhealthy food and beverages through product placements and promotional advertisements on different digital platforms51, this topic is vastly underreported by the research on DPHS.Sixth, while the anonymity of Internet users enables individuals with discreditable stigma to reap the benefits of supportive communication on digital mediaSeventh, among the 379 studies that utilized Twitter, Facebook, and Instagram, 41% (156) confined their analysis to content that was attributed with specific hashtag(s). These studies represent a biased population of users, and they may have skewed the data by excluding contents relevant to the health event under study. Furthermore, from the full-text of the 581 studies that did not use hashtags, we manually extracted the methodologies they employed to query the Internet or filter their collected data and found that the majority  used only their subjective opinion and 10% (57) used the existing literature to define their search keywords. Trend analysis  and ontology-based keyword extraction were used by 6% (37) and 5%(29) of the studies, respectively. Only 1% (7) of studies used automatic algorithms such as ML, NLP, or lexical analysis to extract context-sensitive keywords. Considering the rapid changes in web search behaviours, the uncertainty regarding the representativeness of pre-defined keywords, and the highly context-sensitive nature of health-related events, keyword querying alone might not be suitable in DPHSEighth, furthering the population bias of the social media data, 82% (619) of studies analyzed only one platform, potentially leading to false positives. For example, Twitter content on poliomyelitis differs significantly from other English-language media content52, the results of 36% (274) of the studies reported in this review were not segmented by geographic location, thus limiting the conclusiveness of their results. For example, while search engine data may be a useful tool to study the temporal dynamics of the pollen seasons in Ukraine and China,–,Ninth, although the health outcomes of different PHS systems are highly location-dependent and might vary based on local healthcare policiesof 36% 27 of the s53. Figure Despite the improvements enabled by digital technologies, the overall process of PHS research has remained constant and contains five main systematic and iterative activitiesThis study has some limitations. First, the terminology in the context of DPHS is not yet established in a consistent way, and our search strings may not have captured all the existing evidence. To mitigate this, in addition to a literature review and involving domain experts, we used language modelling and lexical analysis to find the context-sensitive terms that present the field. Second, papers excluded based on our criteria may yet prove relevant to DPHS, despite decisions made by three reviewers. Finally, although we have tried to discuss some of the most important findings in the literature through intuitive and detailed visualization techniques, it is impossible in a limited space to detail all the aspects of the studies utilized digital media for PHS. The supplementary dashboard we present alongside this study presents more interactive results. However, we believe that a more broadly based review of each of the surveillance systems presented in this paper provides necessary contexts for DPHS.54 set of 80 articles. These articles were selected manually from studies published in four public health journals from 2017 to 2018 , including language modelling  and lexical association analysis , to explore the context-sensitive terms relating to DPHS ; Internet search data  Trends); collaborative websites ; content sharing websites ; and blogs and forums 55. Thus, we excluded all PHS studies that actively collected data by conducting online surveys, digital polls, and interviews. Moreover, articles that used digital data for personal surveillance  were excluded from this review. We also excluded studies that utilized digital data for purposes other than PHS. For example, studies that reported on leveraging the social structures of digital platforms for health education and research recruitment, or studies that only contributed to developing new ML techniques for PHS were not eligible for inclusion. Full details of the inclusion/exclusion criteria are listed in Supplementary Note We included all studies published in English and investigated digital data to implement a surveillance system directly (infoveillance) or mined, analyzed, and aggregated information from digital resources to inform PH and public policy for PHS purposes (infodemiology). Digital data in this paper, regardless of its type, refer to the publicly available user-contributed content on the Internet that was not generated with the main purpose of supporting PHSThe titles and abstracts of the articles identified by the search strategy were manually screened by three reviewers independently for eligibility according to the inclusion and exclusion criteria. Disagreements about eligibility were settled by discussion among the three reviewers. One reviewer manually assessed the full text of included publication and identified additional papers that did not meet the eligibility requirements.A data extraction form was developed and independently piloted on 50 publications by three reviewers. Seven reviewers extracted data from the included articles and two reviewers manually reviewed all fields of the data extraction form and resolved discrepancies by reviewing the full text of the included studies. The following data were extracted from the included papers: authors’ affiliation, number of authors, year of publication, country of authors, country of data collection, platform(s) under study, surveillance theme and (sub) category, objective and findings, the temporal trend of data analysis, surveillance type, age/gender/place mapped to the data, the language of data, analysis methods , data type , duration/start of data collection, evaluation methods, and the methodology of using digital resources for PHS.56. A qualitative analysis was also conducted using NVivo 1057, a software programme for qualitative analysis, to chart the descriptive results and findings of the included studies. We tabulated a hierarchy of digital surveillance systems reported by the included studies and used narrative visualizations to report the findings of this review. We also developed an interactive visual dashboard (available at https://rpubs.com/zshakeri/dphs_dashboard) to provide insights into the findings with a multidimensional and more granular conceptual structure that is difficult to articulate in text alone. More details about the dashboard are provided in Supplementary Note To summarize the extracted data from the included articles, we used a descriptive-analytical method to extract contextual and process-oriented information from each studyAs the primary purpose of this study was to perform scientific paper profiling on internet-based user-generated data in the PHS context, we did not critically appraise the methodological quality of the included studies. However, we will comment on the methodological limitations that could have affected their results and implications.Supplementary Information