Dataset Information

COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response.

ABSTRACT: The scientific response to the COVID-19 pandemic has produced an abundance of publications, including peer-reviewed articles and preprints, across a wide array of disciplines, from microbiology to medicine and social sciences. Genomics and precision health (GPH) technologies have had a particularly prominent role in medical and public health investigations and response; however, these domains are not simply defined and it is difficult to search for relevant information using traditional strategies. To quantify and track the ongoing contributions of GPH 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. As of February 11, 2022, COVID-GPH contained 31,597 articles, mostly on pathogen and human genomics (72%). The database also includes articles describing applications of machine learning and artificial intelligence to the investigation and control of COVID-19 (28%). COVID-GPH represents about 10% (22983/221241) of the literature on COVID-19 on PubMed. 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. COVID-19 GPH can be freely accessed via https://phgkb.cdc.gov/PHGKB/coVInfoStartPage.action .

SUBMITTER: Yu W

PROVIDER: S-EPMC9035978 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response.

Yu Wei W Drzymalla Emily E Gwinn Marta M Khoury Muin J MJ

BMC infectious diseases 20220425 1

The scientific response to the COVID-19 pandemic has produced an abundance of publications, including peer-reviewed articles and preprints, across a wide array of disciplines, from microbiology to medicine and social sciences. Genomics and precision health (GPH) technologies have had a particularly prominent role in medical and public health investigations and response; however, these domains are not simply defined and it is difficult to search for relevant information using traditional strategi ...[more]

PMID: 35468755

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Project description:ImportanceThe health care sector lost millions of workers during the COVID-19 pandemic and job recovery has been slow, particularly in long-term care.ObjectiveTo identify which health care workers were at highest risk of exiting the health care workforce during the COVID-19 pandemic.Design setting and participantsThis was an observational cross-sectional study conducted among individuals employed full-time in health care jobs from 2019 to 2021 in the US. Using the data from the Current Population Survey (CPS), we compared turnover rates before the pandemic (preperiod, January 2019-March 2020; 71 843 observations from CPS) with the first 9 months (postperiod 1, April 2020-December 2020; 38 556 observations) and latter 8 months of the pandemic (postperiod 2, January 2021-October 2021; 44 389 observations).Main outcomes and measuresHealth care workforce exits (also referred to as turnover) defined as a health care worker's response to the CPS as being unemployed or out of the labor force in a month subsequent to a month when they reported being actively employed in the health care workforce. The probability of exiting the health care workforce was estimated using a logistic regression model controlling for health care occupation, health care setting, being female, having a child younger than 5 years old in the household, race and ethnicity, age and age squared, citizenship status, being married, having less than a bachelor's degree, living in a metropolitan area, identifier for those reporting employment status at the first peak of COVID-19, and select interaction terms with time periods (postperiods 1 and 2). Data analyses were conducted from March 1, 2021, to January 31, 2022.ResultsThe study population comprised 125 717 unique health care workers with a mean (SD) age of 42.3 (12.1) years; 96 802 (77.0%) were women; 84 733 (67.4%) were White individuals. Estimated health care turnover rates peaked in postperiod 1, but largely recovered by postperiod 2, except for among long-term care workers and physicians. We found a 4-fold difference in turnover rates between physicians and health aides or assistants. Rates were also higher for health workers with young children (<5 years), for both sexes and highest among women. By race and ethnicity, persistently higher turnover rates were found among American Indian/Alaska Native/Pacific Islander workers; White workers had persistently lower rates; and Black and Latino workers experienced the slowest job recovery rates.Conclusions and relevanceThe findings of this observational cross-sectional study suggest that although much of the health care workforce is on track to recover to prepandemic turnover rates, these rates have been persistently high and slow to recover among long-term care workers, health aides and assistants, workers of minoritized racial and ethnic groups, and women with young children. Given the high demand for long-term care workers, targeted attention is needed to recruit job-seeking health care workers and to retain those currently in these jobs to lessen turnover.

Project description:BackgroundNepal established the health partner coordination for COVID-19 response based on national and international plans and framework to support information-sharing for decision- making and course correction. This paper aims to assess the performance of COVID-19 Health Partner Coordination response in Nepal by adopting coordination best practices and tools from the international humanitarian cluster system.MethodsSecondary data from unpublished documents on health partner coordination for COVID-19 response in Nepal was collected and analysed from April 2023 to May 2023. The secondary data were from the review of the health partner coordination meetings conducted for COVID-19 response using a researcher-developed document review tool, responses of health partners on a survey tool adapted from the cluster coordination performance monitoring tool from the Global Health Cluster, and transcript of Focused Group Discussion among health partners. Descriptive analysis of quantitative information and thematic analysis with predefined themes of qualitative information were performed using MS Excel and MS Word respectively. A written approval from the Ministry of Health and Population and an ethical clearance from the Nepal Health Research Council was obtained before conducting the study.ResultsMore than three-fifths of the meetings showed good results in conduction, process, participation, and documentation of meeting action points with improvement required for follow-up (22.2%). Assessment of health partner coordination subfunctions resulted in either 'good' (>75.0%) or 'satisfactory' (50.1%-75.0%) except for prioritization based on analyses, which was 'unsatisfactory' (<50%). Partners admired good practices of health partner coordination, pointed out some issues, and provided recommendations.ConclusionCOVID-19 has highlighted the importance of effective coordination of health sector for response to a pandemic. Continuation of this practice after addressing the areas for improvement will contribute to health preparedness and readiness for future disasters or public health emergencies.

Dataset Information

COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response.

Publications

COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response.

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