Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

COVID-19 GPH|Home|PHGKB Last data update: Jun 03, 2023 . (Total: 45407 Documents since 2020)

Last Posted: Jun-03-2023 06:33:29
spot light Spotlight

Why the world needs more transparency on the origins of novel pathogens
M Venter, Nature, May 30, 2023

Platforms such as GISAID (the Global Initiative on Sharing All Influenza Data) have enabled important sequencing data to be shared by scientists, with the aim of also protecting researchers’ intellectual property. However, users of these data need to work more closely with the data owners to maintain trust and ensure that sharing continues in the future. Most importantly, we urge scientists and governments to make available all data, research and reports that can help in the identification of the origins of novel pathogens for all outbreaks, epidemics and global health emergencies.

Assessing the potential of polygenic scores to strengthen medical risk prediction models of COVID-19.
Aldo Córdova-Palomera et al. PLoS One 2023 5 (5) e0285991

In UK Biobank participants of European ancestry, the model achieved a relatively high performance (area under the receiver operating characteristic curve ~90%). Polygenic scores for COVID-19 computed from summary statistics of the Covid19 Host Genetics Initiative displayed significant associations with COVID-19 in the UK Biobank (p-values as low as 3.96e-9, all with R2 under 1%), but were unable to robustly improve predictive performance of the non-genetic factors.

Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER program.
M Daniel Brannock et al. Nat Commun 2023 5 (1) 2914

We used electronic health records available through the National COVID Cohort Collaborative to characterize the association between SARS-CoV-2 vaccination and long COVID diagnosis. We found that vaccination was consistently associated with lower odds and rates of long COVID clinical diagnosis and high-confidence computationally derived diagnosis after adjusting for sex, demographics, and medical history.

Use of digital technologies for public health surveillance during the COVID-19 pandemic: A scoping review.
Lorie Donelle et al. Digit Health 2023 5 20552076231173220

The most frequently used technologies included mobile phone devices and applications, location tracking technologies, drones, temperature scanning technologies, and wearable devices. The utility of digital technologies for public health surveillance was impacted by factors including uptake of digital technologies across targeted populations, technological capacity and errors, scope, validity and accuracy of data, guiding legal frameworks, and infrastructure to support technology use.

news Latest News and Publications
An overview of deep learning techniques for COVID-19 detection: methods, challenges, and future works.
Gürsoy Ercan, et al. Multimedia systems 2023 0 0. (3) 1603-1627

New Added Today

Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review.
Dabbagh Rufaidah, et al. Cureus 2023 0 0. (5) e38373

New Added Today

Struggling With Recovery From Opioids: Who Is at Risk During COVID-19?
Keith Diana R, et al. Journal of addiction medicine 2023 0 0. (3) e156-e163

New Added Today

Retracted: IoT-Enabled Framework for Early Detection and Prediction of COVID-19 Suspects by Leveraging Machine Learning in Cloud.
Healthcare Engineering Journal Of, et al. Journal of healthcare engineering 2023 0 0. 9768467

New Added Today

Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.
Menez Steven, et al. American journal of kidney diseases : the official journal of the National Kidney Foundation 2023 0 0.

New Added Today

Strategic and flexible LNG production under uncertain future demand and natural gas prices.
Yusuf Noor, et al. Heliyon 2023 0 0. (6) e16358

New Added Today

Triage and Diagnostic Accuracy of Online Symptom Checkers: Systematic Review.
Riboli-Sasco Eva, et al. Journal of medical Internet research 2023 0 0. e43803

New Added Today

Assessing Health Care Professionals' Mindset in Adopting Telemedicine Post COVID-19: Pilot Questionnaire Study.
Naghdi Rozhin, et al. JMIR formative research 2023 0 0. e44806

New Added Today

The Electronic Surviving Cancer Competently Intervention Program-a Psychosocial Digital Health Intervention for English- and Spanish-Speaking Parents of Children With Cancer: Protocol for Randomized Controlled Trial.
Canter Kimberly S, et al. JMIR research protocols 2023 0 0. e46339

New Added Today

A Web-Based Method for the Identification of IL6-Based Immunotoxicity in Vaccine Candidates.
Dhall Anjali, et al. Methods in molecular biology (Clifton, N.J.) 2023 0 0. 317-327

New Added Today

All Latest

About COVID-19 GPH

COVID-19 GPH is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that capture emerging discoveries and applications of genomics, molecular and other precision medicine and precision public health tools in the investigation and control of COVID-19. Contents include PubMed records via an automated pubmed search algorithm, preprint records from NIH iCite, the relevant information from many media sources picked by experts, and linkages to contents from our curated PHGKB databases.

Site Citation:
Wei Yu, et al. COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response. BMC Infectious Diseases (2022) 22:402.

update trend

Sign up Email Alert


All Records45407
Genomics Precision Health33227
Non-Genomics Precision Health12180

Publication Categories Brand

Variants 13587
Vaccines 11413
Treatment 10726
Mechanism 10493
Diagnosis 7811
Prevention 5435
Surveillance 4040
Forecasting 3555
Transmission 2187
Health Equity 1166

Publication Types

PubMed Records34900
Online News/Reports/Publications433

Genomics Precision Health (GPH): The use of pathogen and human genomics and advanced molecular detection methods in discovery, clinical and public health investigations and response to COVID-19.
Non Genomics Precision Health (non-GPH): The use of big data, data science, digital health, machine learning and predictive analytic methods (not involving genomics) in discovery, clinical and public health investigations and response to COVID-19

Following categories are annotated by LitCovid from NCBI NIH.
MechanismUnderlying cause(s) of covid-19 infections and transmission & possible drug mechanism of action
Transmission Characteristics and modes of covid-19 transmissions, such as human-to-human
DiagnosisDisease assessment through symptoms, test results, and radiological features
PreventionPrevention, control, response and management strategies
Case ReportDescriptions of specific patient cases
ForecastingModelling and estimating the trend of covid-19 spread

Following categories are annotated by the text mining tool from CDC PHGKB
Health EquityRelevant to health equity. Search terms are derived from a list provided by the Association for Territorial Health Officials which include terms such as diversity, health disparities, and others.
VaccineRelevant to vaccine development, evaluation, implementation and impact. For additional information on vaccines and COVID-19. Check out general CDC Information pages
VariantRelevant to SARS-CoV-2 variants and their impact on public health. For additional information on variants COVID-19. Check out CDC New Variants of the Virus that Causes COVID-19 page
SurveillanceRelevant to SARS-CoV-2 public health surveillance and tracking. For additional information on COVID-19 surveillance, check out CDC COVID-19 Data Tracker

Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Genomics and Precision Public Health to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.