385 hot topic(s) found with the query "Big data or precision health"
Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections.
Claudia Fredolini et al. Commun Med (Lond) 2024 4 (1) 55
(Posted: Apr 04, 2024 9AM)
From the abstract: "Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives. "
Emerging Opportunities for Genomics to Improve Population Health: Lessons learned from the National Academies Roundtable on Genomics and Precision Health
CDC Webinar, May 22, 2024
(Posted: Mar 21, 2024 1PM)
From the website: " For nearly two decades, the National Academies of Sciences, Engineering, and Medicine’s Roundtable on Genomics and Precision Health has brought together diverse voices to share in dialogue about emerging topics in genomics and precision health. Through its public workshops and proceedings of those workshops, the roundtable seeks to encourage innovation and actions that foster the wide adoption of and equitable access to the benefits of genomics and precision health. The webinar will shed light on the emerging opportunities and challenges for genomics to improve population health. The webinar participants will also discuss the role of public health at state and federal levels in fulfilling the promise of genomics and precision health for all. Specific topics relevant to public health practice will be explored."
We need to stand together on the shoulders of giants: consolidating effective approaches for translating genomics into practice with implementation science.
Stephanie Best et al. Public Health Genomics 2023 12
(Posted: Jan 22, 2024 8AM)
From the article: "Adopting a genomics learning implementation system approach would provide opportunities to bring together clinical and implementation data from observational studies and clinical trials, providing real-world evidence. These findings could be housed in the Digital Implementation Toolshed (DIT), an online bi-directional platform for resources generated from implementation science activity in genomics. The highly curated DIT (Fig. 1) would augment the Centers for Disease Control and Prevention Genomics and Precision Health Weekly Update. " "
Engaging a national-scale cohort of smart thermometer users in participatory surveillance
YJ Tseng et al, NPJ Digital Medicine, September 20, 2023
(Posted: Sep 21, 2023 2PM)
From the abstract: "Participatory surveillance systems crowdsource individual reports to rapidly assess population health phenomena. The value of these systems increases when more people join and persistently contribute. We examine the level of and factors associated with engagement in participatory surveillance among a retrospective, national-scale cohort of individuals using smartphone-connected thermometers with a companion app that allows them to report demographic and symptom information. Between January 1, 2020 and October 29, 2022, 1,325,845 participants took 20,617,435 temperature readings, yielding 3,529,377 episodes of consecutive readings. There were 1,735,805 (49.2%) episodes with self-reported symptoms (including reports of no symptoms). "
Brining it all together: wearable data fusion
Y Celik et al, NPJ Digital Medicine, August 17, 2023
(Posted: Aug 17, 2023 11AM)
Contemporary wearables like smartwatches are often equipped with advanced sensors and have associated algorithms to aid researchers monitor physiological outcomes like physical activity levels, sleep patterns or heart rate in free-living environments. But here’s the catch: all that valuable data is often collected separately because the sensors don’t always play nice with each other, and it’s a real challenge to put all the data together. To get the full picture, we may often need to combine different data streams.
Get up to Speed on the Latest Developments in the Field! Register for the ORISE Current Issues in Genomics and Precision Public Health Online Training Event, September 7–8, 2023.
W White et al, CDC Blog Post, August 9, 2023
(Posted: Aug 09, 2023 11AM)
Advances in genomics, data science, machine learning, and artificial intelligence are transforming practice. Next generation public health and medical workforces need to understand these developments and how they can be used to benefit population health. Recognizing this challenge, Oak Ridge Institute for Science and Education (ORISE) is partnering with the Office of Genomics and Precision Public Health at the Centers for Disease Control and Prevention (CDC) to offer a free 2-day in-person training event covering the latest developments in these fields: Current Issues in Genomics and Precision Public Health – Using Genomics and Big Data to Improve Population Health and Reduce Health Inequities.
Genomics and Precision Public Health Issues Enrichment Event
Oak Ridge Institute for Science Education Enrichment Event, Atlanta, Georgia, September 7-8, 2023
(Posted: Jul 17, 2023 8AM)
In the past decade, genomics, and precision health approaches such as big data science and machine learning have emerged as important tools for public health. Those entering the public health and medical workforces must keep pace with these evolving fields to maximize the benefit to public health. Recognizing this need, ORISE is partnering with the Office of Genomics and Precision Public Health at the Centers for Disease Control and Prevention to offer a two-day in-person enrichment event covering the latest developments in these fields.
Tracking the Contributions of Implementation Science to the Population Health Impact of Genomics and Precision Health: A New Knowledge Base
M Clyne et al, CDC blog post, June 16, 2023
(Posted: Jun 19, 2023 1PM)
Successful implementation of evidence-based genomic and precision health interventions requires an understanding of what works and what doesn’t work within the context of various clinical and public health settings. Research and evaluation that incorporate implementation science tools and methods into the translation of these interventions facilitate this. Here we present a new CDC knowledge base, a collection of these implementation science studies, and a summary of their collective contributions to date.
Cost-Effectiveness Analysis in Public Health Genomics and Precision Health: Recent Findings, Methodologic Issues, and the Path Forward
CDC Public Health Genomics Webinar, October 26, 2023
(Posted: Jun 09, 2023 8AM)
Dr David Veenstra from the University of Washington in Seattle will review the field as a whole and his research projects including evaluation of the cost-effectiveness of population-level genomic screening, pharmacogenomics in diverse populations, decision modeling techniques to assess evidence thresholds, and stakeholder preferences for precision medicine. He will address recent findings, methodologic issues and the path forward.
Harnessing big data for health equity through a comprehensive public database and data collection framework.
Cameron Sabet et al. NPJ Digit Med 2023 5 (1) 91
(Posted: May 23, 2023 11AM)
We examine the reasons behind the delayed adoption of big data for healthcare equity, recent efforts embracing big data tools, and methods to maximize potential without overburdening physicians. We additionally propose a public database for anonymized patient data, introducing diverse metrics and equitable data collection strategies, providing valuable insights for policymakers and health systems to better serve communities.
NIH launches largest precision nutrition research effort of its kind
NIH ALL of Us, May 2023
(Posted: May 17, 2023 11AM)
The National Institutes of Health is now enrolling participants in a landmark initiative to advance nutrition research. Nutrition for Precision Health, powered by the All of Us Research Program (NPH), is working with 14 sites across the United States to engage 10,000 participants from diverse backgrounds and learn more about how our bodies respond differently to food. NPH will use artificial intelligence (AI)-based approaches to analyze information provided by participants in order to develop algorithms that predict responses to dietary patterns. The study’s findings may one day allow healthcare providers to offer more customized nutritional guidance to improve overall health.
Realizing the Potential of Genomics across the Continuum of Precision Health Care: Proceedings of a Workshop (2023)
NASEM, March 30, 2023
(Posted: Mar 30, 2023 10AM)
The National Academies Roundtable on Genomics and Precision Health hosted a public workshop that examined how genomic data are used in health care, outside of the traditional settings for clinical genetics. The workshop identified opportunities for advancement of precision health care delivery. The event also explored how patients, clinicians, and payers assess and act upon the risks and benefits of genomic screening and diagnostic testing. Discussions focused on strategies to ensure that genomic applications are responsibly and equitably adopted to benefit populations as well as individuals over time.
American Life in Realtime: a benchmark registry of health data for equitable precision health.
Ritika R Chaturvedi et al. Nature medicine 2023 2
(Posted: Feb 21, 2023 7AM)
Emerging precision health methods use large-scale person-generated health data from smartphones and wearables to better characterize and, ultimately, improve health and well-being through strategies customized to individual context and need3,4. Applying artificial intelligence and machine learning to person-generated health data allows unprecedented assessment of recursive, networked and latent associations between everyday life and health, including social, structural and environmental exposures, behaviors, biometrics, and health outcomes.
Passive monitoring by smart toilets for precision health.
T Jessie Ge et al. Science translational medicine 2023 2 (681) eabk3489
(Posted: Feb 03, 2023 7AM)
Precision health is an approach to prevent, diagnose, and monitor disease using information gleaned from an individual’s biological information. Passive monitoring in a smart home setting, where appliances and devices are connected and controlled automatically, may provide such biological information. Whereas wearable health sensors must be actively applied and require a certain amount of human intervention, a sensor that performs passively and noninvasively can collect valuable health data in the background of everyday life. Of the possible locations in a smart home, the bathroom, and more specifically the toilet, is particularly well suited for such passive sensors.
Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality
E Stamatakis et al, Nature Medicine, December 8, 2022
(Posted: Dec 09, 2022 6AM)
Here, we examined the association of VILPA with all-cause, cardiovascular disease (CVD) and cancer mortality in 25,241 nonexercisers (mean age 61.8?years, 14,178 women/11,063 men) in the UK Biobank. Over an average follow-up of 6.9?years, during which 852 deaths occurred, VILPA was inversely associated with all three of these outcomes in a near-linear fashion. Compared with participants who engaged in no VILPA, participants who engaged in VILPA at the sample median VILPA frequency of 3?length-standardized bouts per day (lasting 1 or 2?min each) showed a 38%–40% reduction in all-cause and cancer mortality risk and a 48%–49% reduction in CVD mortality risk.
Medicine and health of 21st Century: Not just a high biotech-driven solution.
Assidi Mourad et al. NPJ genomic medicine 2022 11 (1) 67
(Posted: Nov 16, 2022 8AM)
Although the potential of biotechnology is motivating, we should not lose sight of approaches that may not seem as glamorous but can have large impacts on the healthcare of many and across disparate population groups. A balanced approach of “omics and big data” solution in contemporary health systems along with a large scale, simpler, and suitable strategies should be defined with expectations properly managed.
Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction
ZI Attoa et al, Nature Medicine, November 14, 2022
(Posted: Nov 15, 2022 7AM)
Although artificial intelligence (AI) algorithms have been shown to be capable of identifying cardiac dysfunction, defined as ejection fraction (EF) = 40%, from 12-lead electrocardiograms (ECGs), identification of cardiac dysfunction using the single-lead ECG of a smartwatch has yet to be tested. We digitally enrolled 2,454 unique patients from 46 US states and 11 countries, who sent 125,610 ECGs to the data platform between August 2021 and February 2022; 421 participants had at least one watch-classified sinus rhythm ECG within 30?d of an echocardiogram, of whom 16 (3.8%) had an EF?=?40%. The AI algorithm detected patients with low EF with an area under the curve of 0.885.
Evaluation of physical health status beyond daily step count using a wearable activity sensor
Z Xu et al, NPJ Digital Medicine, November 9, 2022
(Posted: Nov 09, 2022 7AM)
Multimodal machine learning in precision health: A scoping review
A Kline et al, NPJ Digital Medicine, November 7, 2022
(Posted: Nov 08, 2022 7AM)
Machine learning is frequently being leveraged to tackle problems in the health sector including utilization for clinical decision-support. Its use has historically been focused on single modal data. Attempts to improve prediction and mimic the multimodal nature of clinical expert decision-making has been met in the biomedical field of machine learning by fusing disparate data. This review was conducted to summarize the current studies in this field and identify topics ripe for future research.
Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission.
Gao Chengcheng et al. NPJ digital medicine 2022 10 (1) 161
(Posted: Oct 29, 2022 11AM)
With the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission. Hence, we collect Internet multisource big data (including retrieval, migration, and media data) and propose comprehensive and relative application strategies to eliminate the impact of national and media data.
Big data and AI in pandemic preparedness
The Lancet Summit: October 27-28, 2022
(Posted: Oct 27, 2022 0PM)
Managing COVID-19 and infectious disease is a global priority over the next few decades. Clinical and research communities are committed to reviewing the global response to the COVID-19 pandemic and a key part has been the unprecedented use and rapid scale of technology. This conference will allow diverse stakeholders to discuss opportunities for new pandemic warning systems based on modelling approaches using AI; advances in real-world surveillance and tracking of disease spread; AI for drug screening and rapid diagnostics; and advances in remote treatment and telehealth.
Unsettled Liability Issues for "Prediagnostic" Wearables and Health-Related Products.
Simon David A et al. JAMA 2022 9
(Posted: Sep 24, 2022 7AM)
Prediagnostic products and other health-related applications are bringing exciting technologies directly to consumers and mesh well with the goal of meeting patients “where they live,” sometimes literally. But these products also present a context that is rife with legal uncertainty
Building Capacity for Implementation Science in Precision Health and Society: Development of a Course for Professional and Graduate Students in Pharmacy
MC Roberts, J Personalized Medicine, September 14, 2022
(Posted: Sep 14, 2022 3AM)
Training in the field of implementation science is critical for future pharmacists and pharmaceutical scientists to successfully implement precision health interventions in pharmacy practice. We developed an elective course for second- and third-year students at the UNC Eshelman School of Pharmacy to develop foundational knowledge in implementation science with a focus on precision health implementation. The eight-week course used a flipped classroom format featuring lecture videos, suggested readings, quizzes, guest lectures from experts, case studies, and a group project.
Big data in basic and translational cancer research.
Jiang Peng et al. Nature reviews. Cancer 2022 9
(Posted: Sep 07, 2022 8AM)
Fast data growth has given rise to an evolving concept of ‘big data’ in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements.
Wearable accelerometer-derived physical activity and incident disease.
Khurshid Shaan et al. NPJ digital medicine 2022 9 (1) 131
(Posted: Sep 04, 2022 8AM)
A wearable ultrasound patch.
O'Leary Karen et al. Nature medicine 2022 8
(Posted: Aug 13, 2022 6PM)
Wearable technologies are advancing rapidly and can provide a multitude of skin-based physical and chemical readouts. However, harnessing wearable technologies for internal imaging applications such as ultrasound – which provides crucial information on organ function and disease – has been challenging.
Now scientists have engineered a stick-on wearable ultrasound device for continuous monitoring.
Bioadhesive ultrasound for long-term continuous imaging of diverse organs.
Wang Chonghe et al. Science (New York, N.Y.) 2022 7 (6605) 517-523
(Posted: Aug 01, 2022 11AM)
Ultrasound is widely used for the noninvasive imaging of tissues and organs, but this method requires close contact between the transducer and the target area. This can make it difficult to acquire images over a long period of time, especially if the patient needs to be mobile. A new study describes a wearable ultrasound imaging device. A rigid piezoelectric probe array is bonded to the skin with an acoustically transparent hydrogel elastomer. In vivo testing showed that the device could be comfortably worn for 48 hours, and hooking the array up to a commercially available ultrasound platform allowed for continuous ultrasound images of the carotid artery, lung, and abdomen.
Predicting Firearm Suicide-Small Steps Forward With Big Data.
Betz Marian E et al. JAMA network open 2022 7 (7) e2223758
(Posted: Jul 24, 2022 11AM)
Precision Health Innovations in the Pandemic Era
D Rasooly et al, CDC Blog Post, July 8, 2022
(Posted: Jul 08, 2022 0PM)
Two recent articles, one in Nature Medicine and another in Nature Biotechnology, highlight areas of health innovation that have been accelerated by the COVID-19 pandemic. This blog post focuses on two precision health applications of technology—(1) genomics and (2) wearable devices and smartphone apps—that are likely to have a lasting impact beyond the pandemic. Increased interest in these applications is reflected in the scientific literature captured by the COVID-19 GPH database
Shaping the future of cardiovascular medicine in the new era of wearable devices.
Gehr Sinje et al. Nature reviews. Cardiology 2022 6
(Posted: Jun 11, 2022 9AM)
Wearable devices are widely used and have a high level of societal acceptance, opening unimagined and unexploited possibilities in cardiovascular medicine. In this Clinical Outlook, we highlight the disruptive potential of wearables for cardiovascular disease prevention, diagnosis and management, and suggest strategies for quickly and safely translating these lifestyle products into medical devices.
COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response
W Yu et al, BMC Infectious Diseases, April 25, 2022
(Posted: Apr 25, 2022 8AM)
To quantify and track the ongoing contributions of genomics and precision health to the COVID-19 response, the Office of Genomics and Precision Public Health at the Centers for Disease Control and Prevention created the COVID-19 Genomics and Precision Health database (COVID-19 GPH), an open access knowledge management system and publications database that is continuously updated through machine learning and manual curation.
This unique knowledge management database makes it easier to explore, describe, and track how the pandemic response is accelerating the applications of genomics and precision health technologies.
Tracking the Scientific Literature on the Impact of Pharmacogenomics on Clinical Practice and Public Health
S Abrishamcar et al, CDC blog Post, April 4 2022
(Posted: Apr 04, 2022 2PM)
Our office has created a comprehensive resource to help researchers, providers, and policy makers track progress and impact of genomics and precision health on population health. The resource features a continuously updated and curated database of scientific literature and other information. One component of this resource is a specific PGx database that focuses on progress in PGx in clinical practice and population health. A quick examination of our PGx database shows significant growth in translation and implementation science in the last decade. The number of published studies in these areas increased from 12 in 2012 to 333 in 2021.
The principles of whole-hospital predictive analytics monitoring for clinical medicine originated in the neonatal ICU
JD Moorman, NPJ Digital Medicine, March 31, 2022
(Posted: Apr 02, 2022 8AM)
In 2011, a multicenter group spearheaded at the University of Virginia demonstrated reduced mortality from real-time continuous cardiorespiratory monitoring in the neonatal ICU using what we now call Artificial Intelligence, Big Data, and Machine Learning. The large, randomized heart rate characteristics trial made real, for the first time that we know of, the promise that early detection of illness would allow earlier and more effective intervention and improved patient outcomes.
Advancing Implementation Science in Precision Public Health: Ensuring Health Equity and Balancing Evolution and Sustainment
Precision Public Health Network webinar, April 27, 2022
(Posted: Mar 22, 2022 7AM)
The rapid development of advances in biomedical research creates levers to improve precision health and health care. However, without complementary attention to a robust agenda on implementation science, we risk replicating the “bench” to “bookshelf” pathway for scientific discoveries. Dr David Chambers will discuss challenges and opportunities, assumptions and ongoing activities toward advancing implementation science in the context of dynamic systems, an evolving evidence base and a desire to sustain effective and equitable health interventions over time.
Artificial Intelligence in Medicine and Public Health: Prospects and Challenges Beyond the Pandemic
D Rasooly et al, CDC Blog Post, March 1, 2022
(Posted: Mar 02, 2022 8AM)
A recent Nature Medicine article discusses promising uses of artificial intelligence in medicine, particularly in medical imaging and big data integration, and considers technical and ethical challenges for their applications in improving human health. Here is a quick summary of the review and the implications for population health.
Real life experience with the wearable cardioverter-defibrillator in an international multicenter Registry.
El-Battrawy Ibrahim et al. Scientific reports 2022 2 (1) 3203
(Posted: Feb 27, 2022 10AM)
Patients at high risk for sudden cardiac death (SCD) may benefit from wearable cardioverter defibrillators (WCD) by avoiding immediate implantable cardioverter defibrillator (ICD) implantation. Different factors play an important role including patient selection, compliance and optimal drug treatment. We aimed to present real world data from 4 centers from Germany and Switzerland. Between 04/2012 and 03/2019, 708 patients were included in this registry. Patients were followed up over a mean time of 28?±?35.5 months. Outcome data including gender differences and different etiologies of cardiomyopathy were analyzed. Out of 708 patients (81.8% males, mean age 61.0?±?14.6), 44.6% of patients had non-ischemic cardiomyopathy, 39.8% ischemic cardiomyopathy, 7.9% myocarditis, 5.4% prior need for ICD explantation and 2.1% channelopathy.
Improving Diversity of the Genomics Workforce
NASEM RoundTable on Genomics and Precision Health, February 18, 2022
(Posted: Feb 18, 2022 0PM)
The workshop, Improving Diversity of the Genomics Workforce, examined the current state of diversity of the genetics and genomics workforce; the structural and social factors associated with the lack of workforce diversity; the impact of diversity in the workforce on access to genetic services and patient outcomes; and possible actions that could lead to a more diverse, equitable, and inclusive genomics workforce. This Proceedings of a Workshop-in Brief highlights the presentations and discussions that occurred during the workshop.
Harnessing big data to characterize immune-related adverse events
Y Jing et al, Nat Rev Clin Oncology, January 2022
(Posted: Jan 26, 2022 7AM)
We summarize the advantages and shortcomings of different sources of ‘big data’ for the study of irAEs and highlight progress made using such data to identify biomarkers of irAE risk, evaluate associations between irAEs and therapeutic efficacy, and characterize the effects of demographic and anthropometric factors on irAE risk. Harnessing big data will accelerate research on irAEs and provide key insights that will improve the clinical management of patients receiving ICIs.
Using big data and mobile health to manage diarrheal disease in children in low-income and middle-income countries: societal barriers and ethical implications
KH Keddy et al, Lancet Inf Dis, December 13, 2021
(Posted: Dec 15, 2021 8AM)
Diarrhea is an important cause of morbidity and mortality in children from low-income and middle-income countries (LMICs), despite advances in the management of this condition. Understanding of the causes of diarrhea in children in LMICs has advanced owing to large multinational studies and big data analytics computing the disease burden, identifying the important variables that have contributed to reducing this burden. The advent of the mobile phone has further enabled the management of childhood diarrhea by providing both clinical support to health-care workers/
A needle for Alzheimer’s in a haystack of claims data
E Gunney et al, Nature Aging, December 2021
(Posted: Dec 12, 2021 9AM)
In the era of big data, looking for insights in large datasets has become the norm — and health data are no exception. Combining systems-biology-driven, endophenotype-based analysis of drug targets with large-scale medical claims data points to sildenafil as a potential treatment opportunity for Alzheimer’s disease.
The Use of Machine Learning in Health Care: No Shortcuts on the Long Road to Evidence-based Precision Health
D Rasooly et al, CDC Blog Post, December 7, 2021
(Posted: Dec 07, 2021 1PM)
Two recent systematic reviews reveal the high risk of bias present in randomized controlled trials (RCTs) and observational studies based on machine learning and artificial intelligence. Given that methodological challenges and risk of biases in ML-based models can occur across different development stages, such as data curation, model selection and implementation, and validation, there is a need for broad discussion of possible solutions.
Insights Into Immune-Mediated Disease and Cancer Risk-Delivering on the Promise of UK Biobank Big Data.
Stewart Douglas R et al. JAMA oncology 2021 12
(Posted: Dec 03, 2021 11AM)
Large, longitudinal data sets derived from the electronic health records are powerful tools for discovery. A recent study extracted from the big data provided by the UK Biobank clinically and scientifically useful insights and estimates of cancer risk associated with immune-mediated disease.
Digital twins for predictive oncology will be a paradigm shift for precision cancer care
TH Boussard et al, Nature Medicine, November 2, 2021
(Posted: Nov 27, 2021 9AM)
Cancer patient digital twins (CPDTs) use emerging computing and biotechnologies to build in silico individual representations that dynamically reflect molecular, physiological and lifestyle status across different treatments and time. We propose a CPDT framework with a continuous life cycle for shared decision-making.
From Public Health Genomics to Precision Public Health: On to the Next Generation!
Muin J. Khoury Video Presentation, at the Transdisciplinary Conference for Future Leaders in Precision Public Health. Posted on November 11, 2021
(Posted: Nov 12, 2021 11AM)
In this presentation Dr Khoury discusses the evolution of the field of public health genomics over the past 25 years into precision medicine and precision public health, which involves applications of genomics , big data and predictive analytics to population health. He also describes ongoing applications of precision public health to the COVID-19 response.
Transdisciplinary Conference for Future Leaders in Precision Public Health
Speakers Slide Presentations, November 2021
(Posted: Nov 12, 2021 7AM)
This virtual event held in October 2021 connected future research leaders around the world interested in the role of genetics and precision health in the promotion of public health. The speakers provided opportunities for early career investigators to discuss new developments in precision public health with leading experts in the field. Attendees heard from expert epidemiologists, behavioral scientists, statisticians, and global public health leaders about topics such as health equity in genetic epidemiology, genetic risk communication in cancer care, and biostatistics and modeling.
Who has long-COVID? A big data approach
ER Plaff et al, MEDRXIV, October 22, 2021
(Posted: Oct 24, 2021 6PM)
Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset
E Grzesiak et al, JAMA Network Open, September 29, 2021
(Posted: Sep 30, 2021 7AM)
In a cohort study of 31 participants inoculated with H1N1 and 18 participants with rhinovirus, infection detection and severity prediction models trained using data on wearable devices were able to distinguish between infection and noninfection with 92% accuracy for H1N1 and 88% accuracy for rhinovirus and were able to distinguish between mild and moderate infection 24 hours prior to symptom onset with 90% accuracy for H1N1 and 89% accuracy for rhinovirus.
Greece used AI to curb COVID: what other nations can learn- Governments are hungry to deploy big data in health emergencies. Scientists must help to lay the legal, ethical and logistical groundwork.
Nature editorial, September 22, 2021
(Posted: Sep 22, 2021 4PM)
During the pandemic, there has been no shortage of ideas on how to deploy big data and AI to improve public health or assess the pandemic’s economic impact. However, relatively few of these ideas have made it into practice. This is partly because companies and governments that hold relevant data — such as mobile-phone records or details of financial transactions — need agreed systems to be in place before they can share the data with researchers. It’s also not clear how consent can be obtained to use such personal data, or how to ensure that these data are stored safely and securely.
Improving Diversity of the Genomics Workforce: A Workshop
NASEM Roundtable on Genomics and Precision Health workshop, October 5, 2021
(Posted: Sep 20, 2021 3PM)
This virtual public workshop that will examine the current state of diversity (e.g., racial, ethnic) of the genetics and genomics workforce, structural issues that have contributed to diversity challenges, and potential steps forward. Workshop discussions may address topics such as the impact of racism on the culture of the fields of genetics and genomics; how the genetics/genomics workforce is or is not uniquely affected by structural racism; and the relationship between the lack of diversity in the workforce and patient access to genetic services.
Diagnostic Errors, Health Disparities, and Artificial Intelligence
A Combination for Health or Harm?
SA Ibrahim et al, JAMA Health Forum
(Posted: Sep 19, 2021 10AM)
The health care industry is emerging as a leader in the adoption of AI through sophisticated machine learning–assisted diagnostic tools. For clinical trials, AI has the potential to support every stage of the process, including finding a trial in which to enroll, addressing patient-centric enrollment issues, and assessing trial medication adherence with remote and digital monitoring. It is equally important to tap into the opportunities provided by big data and AI to detect and address diagnostic disparities in populations at risk for such disparities.
Preventing Glaucoma Vision Loss with ‘Big Data’
F Collins, NIH Director blog, September 16, 2021
(Posted: Sep 17, 2021 6AM)
A recent study analyzed data from more than 1,200 people with glaucoma who participate in NIH’s All of Us Research Program. With consent from the participants, Baxter used their EHRs to train a computer to find telltale patterns within the data and then predict with 80 to 99 percent accuracy who would later require eye surgery.
A systematic literature review of disclosure practices and reported outcomes for medically actionable genomic secondary findings.
Sapp Julie C et al. Genetics in medicine : official journal of the American College of Medical Genetics 2021 8
(Posted: Aug 27, 2021 7AM)
Secondary findings (SFs) are present in 1–4% of individuals undergoing genome/exome sequencing. A review of how SFs are disclosed and what outcomes result from their receipt is urgent and timely.Variation in how SF disclosure and outcomes were described limited our ability to compare findings. We conclude the literature provided limited insight into how the American College of Medical Genetics and Genomics (ACMG) guidelines have been translated into precision health outcomes for SF recipients. Robust studies of SF recipients are needed and should be prioritized for future research.
Personalized lab test models to quantify disease potentials in healthy individuals
NM Cohen et al, Nature Medicine, August 23, 2021
(Posted: Aug 25, 2021 8AM)
Using EHRs, we generated a filtered dataset, including ~0.5 billion lab measurements from 2.8?M individuals. Based on these data we developed tools for multivariate longitudinal analysis and showed that they can predict patients’ within-normal lab trajectories at surprisingly high accuracy. Personalized lab models can then be applied to patients with still-normal lab readouts to evaluate risks for future lab test abnormalities, deterioration toward multiple types of chronic diseases and overall mortality.
The Complementarity of Public Health and Medicine — Achieving “the Highest Attainable Standard of Health”
DJ Hunter, NEJM, August 5, 2021
(Posted: Aug 04, 2021 5PM)
Preventive medicine can be practiced with individual patients in a consulting room or through organized activities such as vaccine outreach, community blood-pressure screening, or health education. Future “big data” analyses may both provide insights into population health as well as permitting more personalized medical care.
Tracking the Scientific Literature on SARS-CoV-2 Variants Using the COVID-19 Genomics and Precision Health Knowledge Base
M Feero et al, CDC blog post, July 27, 2021
(Posted: Jul 27, 2021 1PM)
From December 2020 to January 2021, the number of preprints and journal publications on variants doubled from 106 to 213). By March 2021, more than 300 new publications on variants were appearing each month. Preprints accounted for 37% of the total publications in both 2020 and 2021. Most publications on variants focused on mechanism (e.g., effects of mutations on binding to host receptors) or on potential clinical applications (e.g., diagnosis, treatment, or vaccines). Only a small fraction addressed public health topics, such as surveillance or forecasting, prevention, or health equity.
Mobile health strategies for blood pressure self-management in urban populations with digital barriers: systematic review and meta-analyses
EC Khoong et al, NPJ Digital Medicine, July 22, 2021
(Posted: Jul 23, 2021 7AM)
Mobile health (mHealth) technologies improve hypertension outcomes, but it is unknown if this benefit applies to all populations. This review aimed to describe the impact of mHealth interventions on blood pressure outcomes in populations with disparities in digital health use.
Resources in Genomics and Precision Health to Enhance Public Health Impact of New Technologies
CDC slide set, 2021
(Posted: Jul 19, 2021 2PM)
The presentation reviews the CDC Public Health Genomics and Precision Health Knowledge Base (PHGKB), a suite of searchable databases that includes publications and other resources. It includes: 1) COVID Genomics and Precision Health, a database that includes publications and other resources about the impact of genomics and precision health technologies on the investigation and control of COVID-19; 2) My Family Health Portrait, a family health history collection tool that allows users to save and share their family health history information; and 3) Specialized PHGKB databases such as reproductive and child health, family health history, and health equity.
Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases
N Hurvitz et al, EJHG, July 19, 2021
(Posted: Jul 19, 2021 8AM)
Patients with rare diseases are a major challenge for healthcare systems. These patients face three major obstacles: late diagnosis and misdiagnosis, lack of proper response to therapies, and absence of valid monitoring tools. We reviewed the relevant literature on first-generation artificial intelligence (AI) algorithms which were designed to improve the management of chronic diseases. The shortage of big data resources and the inability to provide patients with clinical value limit the use of these AI platforms by patients and physicians.
Using big data analytics to explore the relationship between government stringency and preventative social behaviour during the COVID-19 pandemic in the United Kingdom
N Al-Zobaidy et al, MERDXIV, July 10,2021
(Posted: Jul 11, 2021 0PM)
Genetics of substance use disorders in the era of big data
J Gelernter et al, Nat Rev Genetics, July 1, 2021
(Posted: Jul 02, 2021 7AM)
The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies — including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples — have revealed multiple risk loci for these common traits
‘It’s hard to know what’s trustworthy’: A new research effort aims to vet digital health data from wearables
K Palmer, Stat News, June 22, 2021
(Posted: Jun 23, 2021 8AM)
Using ‘big data’ to disentangle aging and COVID-19
RR Montgomery et al, Nature Aging, June 14, 2021
(Posted: Jun 15, 2021 8AM)
A new study leverages different types of big data, either generated in house from cohorts of healthy aging and COVID-19, or downloaded from the ever-increasing public data archives, to disentangle the distinct cellular and proteomic mechanisms of COVID-19 and aging.
Continuous health monitoring: An opportunity for precision health.
Gambhir Sanjiv S et al. Science translational medicine 2021 6 (597)
(Posted: Jun 12, 2021 7AM)
Continuous health monitoring and integrated diagnostic devices, worn on the body and used in the home, will help to identify and prevent early manifestations of disease. However, challenges lie ahead in validating new health monitoring technologies and in optimizing data analytics to extract actionable conclusions from continuously obtained health data.
Big data, artificial intelligence, and the opioid crisis
Lancet Digital Health editorial, June 1, 2021
(Posted: May 26, 2021 6AM)
Big data and artificial intelligence can help to target preventive measures (eg, addressing comorbidities and socioeconomic inequalities) to reduce future risks of opioid misuse. Community-level modelling can forecast the number of fatal overdoses that could be avoided through wider availability of key treatments. But model explainability and integration of individual-level factors— clinical and social—are crucial to remove barriers and ensure prevention and treatment efforts are accessible to all.
Wearable sensors enable personalized predictions of clinical laboratory measurements
J Dunn et al, Nature Medicine, May 24, 2021
(Posted: May 25, 2021 7AM)
We examined whether vital signs as measured by consumer wearable devices (that is, continuously monitored heart rate, body temperature, electrodermal activity and movement) can predict clinical laboratory test results using machine learning models, including random forest and Lasso models. Our results demonstrate that vital sign data collected from wearables give a more consistent and precise depiction of resting heart rate than do measurements taken in the clinic
20 years of precision medicine in oncology
The Lancet editorial, May 15, 2021
(Posted: May 19, 2021 8AM)
In the 20 years since the publication of the first draft of the human genome project, the use of genotyping and genomics have become part of standard treatment for some cancers. The desire to go beyond blanket, and often difficult, treatments for patients to a more refined, efficient, and patient-centered approach is an ideal that is hard to oppose. But as precision medicine in oncology expands to include big data, proteomics, transcriptomics, molecular imaging, and more, there are serious challenges ahead to translate that ideal into meaningful and equitable health care for patients.
Mobile Health: making the leap to research and clinics
JP Ku et al, NPJ Digital Medicine, May 14, 2021
(Posted: May 15, 2021 7AM)
Health applications for mobile and wearable devices continue to experience tremendous growth, but their impact on healthcare has yet to be fully realized. This commentary introduces three articles in a special issue that provides guidance on how to successfully address translational barriers to bringing mobile health technologies into clinical research and care. We also discuss how the cross-organizational sharing of data, software, and other digital resources can lower such barriers and accelerate progress across mobile health
Wearables as a tool for measuring therapeutic adherence in behavioral health
L Wedlund et al, NPJ Digital Medicine, May 10, 2021
(Posted: May 11, 2021 8AM)
When the FDA approved digital aripiprazole (an antipsychotic medication containing an ingestible sensor to track consumption), the medical community gained a new tool for measuring compliance, theoretically paving the way for new initiatives to find and help nonadherent patients. However, digital aripiprazole comes with a hefty price tag of $1700 for a 30-day supply (85× the price of generic aripiprazole)4, and with no existing randomized control trials to show how digital aripiprazole changes medication adherence5, it may be difficult to justify the cost.
Precision Health Diagnostic and Surveillance Network uses S Gene Target Failure (SGTF) combined with sequencing technologies to identify emerging SARS-CoV-2 variants.
RG Preston et al, MEDRXIV, May 7, 2021
(Posted: May 08, 2021 6AM)
Several genomic epidemiology tools have been developed to track the public and population health impact of SARS-CoV-2 community spread worldwide. A SARS-CoV-2 Variant of Concern (VOC) B.1.1.7, known as 501Y.V1, which shows increased transmissibility, has rapidly become the dominant VOC in the United States (US). Our objective was to develop an evidenced-based genomic surveillance algorithm that combines RT-PCR and sequencing technologies to identify VOCs.
Ensuring that biomedical AI benefits diverse populations
J Zhou et al, E Biomedicine, May 4, 2021
(Posted: May 04, 2021 3PM)
Artificial Intelligence (AI) can potentially impact many aspects of human health, from basic research discovery to individual health assessment. It is critical that these advances in technology broadly benefit diverse populations from around the world. This can be challenging because AI algorithms are often developed on non-representative samples and evaluated based on narrow metrics. Here we outline key challenges to biomedical AI in outcome design, data collection and technology evaluation, and use examples from precision health to illustrate how bias and health disparity may arise.
Convergence of Precision Medicine and Public Health Into Precision Public Health: Toward a Big Data Perspective.
Velmovitsky Pedro Elkind et al. Frontiers in public health 2021 9561873
(Posted: Apr 27, 2021 9AM)
With the coming of Big Data, the fields of precision medicine and public health are converging into precision public health, the study of biological and genetic factors supported by large amounts of population data. In this paper, we explore through a comprehensive review the data types and use cases found in precision medicine and public health.
Impact of Big Data Analytics on People's Health: Overview of Systematic Reviews and Recommendations for Future Studies.
Borges do Nascimento Israel Júnior et al. Journal of medical Internet research 2021 23(4) e27275
(Posted: Apr 16, 2021 10AM)
Although the overall quality of included studies was limited, big data analytics has shown moderate to high accuracy for the diagnosis of certain diseases, improvement in managing chronic diseases, and support for prompt and real-time analyses of large sets of varied input data to diagnose and predict disease outcomes.
Stool-based Colorectal Cancer Screening in the COVID-19 Era
WD Dotson et al, CDC Blog, April, 12, 2021
(Posted: Apr 13, 2021 7AM)
The broad aftermath of the pandemic will be with us for many years to come. Some of the resulting changes can be positive, including an increased awareness of digital, genomic and other precision health technologies which may provide alternatives to traditional screening methods.
Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational and genetic studies
N Shang et al, NPJ Digital Medicine, April 13, 2021
(Posted: Apr 13, 2021 6AM)
Chronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods.
Remote Patient Monitoring — Overdue or Overused?
K Mecklai et al, NEJM, April 10, 2021
(Posted: Apr 12, 2021 8AM)
The Covid-19 pandemic has challenged clinicians to find innovative ways to provide essential services while minimizing risks for themselves and their patients. These approaches increasingly leverage remote patient monitoring (RPM), using technology to support treatment for chronic conditions. As the use of RPM services grows, clinicians, payers, and patients face important questions regarding the volume, value, and appropriate use of this care model.
AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity.
Majnaric Ljiljana Trtica et al. Journal of clinical medicine 2021 10(4)
(Posted: Mar 09, 2021 9AM)
In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity.
CDC Resources in Genomics and Precision Health to Enhance Public Health Impact of New Technologies
CDC Webinar, March 25,2021
(Posted: Feb 27, 2021 7AM)
Advances in genomics and precision health are ushering a new era of precision medicine and precision public health. The pace of scientific discoveries is accelerating and the applications in research, clinical, and public health practice are multiplying. For just about anyone – researchers, practitioners and the general public alike – staying abreast of the latest news and publications is a daunting task.
Applications of digital health for public health responses to COVID-19: a systematic scoping review of artificial intelligence, telehealth and related technologies
DV Gunasekeran et al, NPJ Digital Medicine, February 26, 2021
(Posted: Feb 27, 2021 7AM)
Although a large quantity of reports investigated applications of artificial intelligence (AI) (44.9%, n?=?111/247) and big data analytics (36.0%, n?=?89/247), weaknesses in study design limit generalizability and translation, highlighting the need for more pragmatic real-world investigations.
Development and Validation of Risk Scores for All-Cause Mortality for a Smartphone-Based "General Health Score" App: Prospective Cohort Study Using the UK Biobank.
Clift Ashley K et al. JMIR mHealth and uHealth 2021 Feb 9(2) e25655
(Posted: Feb 19, 2021 10AM)
The objective of the study was to develop and validate a novel, easily interpretable, points-based health score ("C-Score") derived from metrics measurable using smartphone components and iterations thereof that utilize statistical modeling and machine learning (ML) approaches.A literature review was conducted to identify relevant predictor variables for inclusion in the first iteration of a points-based model. This was followed by a prospective cohort study in a UK Biobank population.
Complicated legacies: The human genome at 20
CM Jones et al, SCience, February 4, 2021
(Posted: Feb 05, 2021 7AM)
Millions of people today have access to their personal genomic information. Direct-to-consumer services and integration with other “big data” increasingly commoditize what was rightly celebrated as a singular achievement in February 2001 when the first draft human genomes were published. But such remarkable technical and scientific progress has not been without its share of missteps and growing pains.
Sustainable targeted interventions to mitigate the COVID-19 pandemic: A big data-driven modeling study in Hong Kong
H Zhou et al, MEDRXIV, February 2, 2021
(Posted: Feb 03, 2021 9AM)
We develop a data-driven agent-based model for 7.55 million Hong Kong residents to evaluate the efficacies of various NPIs in the first 80 days of the initial outbreak. The entire territory of Hong Kong has split into 4,905 500m×500m grids. The model can simulate detailed agent interactions based on the demographics data, public facilities and functional buildings, transportation systems, and travel patterns.
Big Data and Digital Solutions: Laying the Foundation for Cardiovascular Population Management CME .
Nasir Khurram et al. Methodist DeBakey cardiovascular journal 16(4) 272-282
(Posted: Feb 02, 2021 11AM)
Big data analytics and digital application platforms-such as patient care dashboards, clinical decision support systems, mobile patient engagement applications, and key performance indicators-offer unique opportunities for value-based healthcare delivery and efficient cardiovascular population management. Successful implementation of big data solutions must include a multidisciplinary approach.
Precision Nutrition: Research Gaps and Opportunities Workshop
NIH Workshop, January 11-12, 2021
(Posted: Jan 05, 2021 8AM)
Precision nutrition science enables individualized dietary recommendations or therapies based on these factors. This workshop will bring together scientists with diverse expertise to explore how best to address these complex factors. It also will focus on diet-related chronic diseases and how artificial intelligence (AI) and deep-learning techniques may be used to generate individualized dietary recommendations and algorithms.
Public Health Genomics in Action: A State-based Approach to Genomics and Precision Health
CDC Webinar, January 28, 2021
(Posted: Dec 22, 2020 8AM)
To date, there are only a few state-based population-based efforts to leverage new science with capacity of medicine, public health and the private sector in improving health outcomes. This seminar will focus on two such initiatives, the Alabama Genomic Health Initiative (AGHI) and the North Carolina Precision Health Collaborative (NCPHC).
How blockchain and genetic engineering could make food safer for people with allergies
G Poppy, Nature Outlook, December 2020
(Posted: Dec 20, 2020 11AM)
The two technologies might ultimately bring an end to ‘may contain’ food labels, which consumers find confusing. Technology and innovation play a major part in global health challenges, as demonstrated by current efforts to find a vaccine against COVID-19. In the case of food allergies, two technologies spring to mind.
2021: research and medical trends in a post-pandemic world
M May, Nature Medicine, December 7, 2020
(Posted: Dec 10, 2020 11AM)
Goodbye 2020: Research and medical trends in a post-pandemic world include a new normal, open repositories, leaps ahead for immunology, more digital health and better preparedness.
Big data and simple models used to track the spread of COVID-19 in cities
C Ma et al, Nature News, November 10, 2020
(Posted: Nov 11, 2020 3PM)
Understanding the dynamics of SARS-CoV-2 infections could help to limit viral spread. Analyzing mobile-phone data to track human contacts at different city venues offers a way to model infection risks and explain infection disparities.
The intersection of genomics and big data with public health: Opportunities for precision public health.
Khoury Muin J et al. PLoS medicine 2020 Oct 17(10) e1003373
(Posted: Oct 30, 2020 10AM)
Precision public health (PPH) has emerged as a response to the increasing availability of genomics, biobanks, and other sources of big data in healthcare and public health. ?The field has evolved starting with genomics to include multiple practical applications such as pathogen genomics that address population health. ?PPH can expand understanding of health disparities, advance strategic public health science, and demonstrate the need for innovation and workforce development.
Assessing Lifting Risk Factors Using Wearable Motion Sensors
MS Barim et al, NIOSH Blog, October 2020
(Posted: Oct 26, 2020 9AM)
A combination of work-related physical risk factors such as awkward postures or heavy lifting may lead to an increased risk of developing low back issues. Inertial measurement unit- (IMU) based wearable technologies are becoming popular as a tool to track whole body postures for ergonomic risk assessments.
Precision Medicine Leaders Summit
PMLS, North Carolina Precision Health Initiative, October 20-21, 2020
(Posted: Oct 06, 2020 8AM)
Advances in genomics and precision health technologies are changing the practice of medicine and public health. The public health response to genomics and precision health technologies illustrates the current opportunities and challenges of new technologies in improving population health and preventing disease.
Social license for the use of big data in the COVID-19 era
JA Shaw et al, NPJ Digital Medicine, October 2, 2020
(Posted: Oct 03, 2020 5PM)
In this Comment, we outline the importance of earning social license for public approval of big data initiatives, and specify principles of data law and data governance practices that can promote social license. We provide illustrative examples from the United States, Canada, and the United Kingdom.
Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis
MK Szocska et al, MEDRXIV, September 23, 2020
(Posted: Sep 24, 2020 10AM)
Enabling precision rehabilitation interventions using wearable sensors and machine learning to track motor recovery
CA Dester et al, NPJ Digital Medicine, September 21, 2020
(Posted: Sep 22, 2020 10AM)
The approach proposed in this paper relies on machine learning-based algorithms to derive clinical score estimates from wearable sensor data collected during functional motor tasks. Sensor-based score estimates showed strong agreement with those generated by clinicians.
Looking at neurodevelopment through a big data lens.
Briscoe James et al. Science (New York, N.Y.) 2020 Sep (6510)
(Posted: Sep 19, 2020 8PM)
The billions of neurons that make up the adult brain are organized into domains and circuits during development. High-resolution measurements such as those enabled by single-cell molecular profiling have revealed unexpected cellular diversity. Genomic tools are lending insight into mechanisms behind neurodevelopmental disorders.
The Role of Digital Health Technologies in Drug Development: Proceedings of a Workshop
NASEM Roundtable on Genomics and Precision Health Workshop, 2020
(Posted: Aug 28, 2020 10AM)
This workshop explored how virtual clinical trials facilitated by digital health technologies (DHTs) might change the landscape of drug development. Participants considered how DHTs could be applied to achieve the greatest impact—and perhaps even change the face of how clinical trials are conducted—in ways that are also ethical, equitable, safe, and effective.
Wearable-device-measured physical activity and future health risk
T Strain et al, Nature Medicine, August 17, 2020
(Posted: Aug 18, 2020 7AM)
This UK Biobank study shows that higher volumes of activity energy expenditure are associated with lower mortality rates. This approach for converting device-measured activity signals to energy expenditure and relating this to health risk creates a framework for future personalized prevention from wearables.
Rare Diseases and COVID-19
CDC COVID-19 Genomics and Precision Health Portal, August 2020
(Posted: Aug 08, 2020 10AM)
This section of the portal lists all rare diseases, many of which are genetic diseases, that have been connected to COVID-19 in the literature. As of today, there are 84 diseases/conditions from the list of nearly 7,000 rare diseases extracted from the NIH website that are related to COVID-19 literature or news and reports.
Evidence of gender bias in the diagnosis and management of COVID-19 patients: A Big Data analysis of Electronic Health Records
J Ancochea et al, MEDRXIV, July 26, 2020
(Posted: Jul 26, 2020 11AM)
Big Data and Collaboration Seek to Fight COVID-19
E Yazinski, The Scientist, July 21, 2020
(Posted: Jul 26, 2020 7AM)
Researchers try unprecedented data sharing and cooperation to understand COVID-19—and develop a model for diseases beyond the coronavirus pandemic.
White Neighborhoods Have More Access To COVID-19 Testing Sites- But the disease is hitting Black and Hispanic communities hardest.
SR Kim et al, FiveThirtyEight, July 22, 2020
(Posted: Jul 22, 2020 8AM)
Big data analysis is one of the first to look at testing site locations in all 50 states using data provided by the health care navigation company Castlight Health. An assessment of city and state health department websites also revealed fewer testing sites in areas primarily inhabited by racial minorities.
