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Open accessJournal ArticleDOI: 10.1080/15265161.2020.1851808

Structural Racism in the COVID-19 Pandemic: Moving Forward.

04 Mar 2021-American Journal of Bioethics (Informa UK Limited)-Vol. 21, Iss: 3, pp 56-74
Abstract: The COVID-19 pandemic has taken a substantial human, social and economic toll globally, but its impact on Black/African Americans, Latinx, and American Indian/Alaska Native communities in the U.S. is unconscionable. As the U.S. continues to combat the current COVID-19 cycle and prepares for future pandemics, it will be critical to learn from and rectify past and contemporary wrongs. Drawing on experiences in genomic research and intersecting areas in medical ethics, health disparities, and human rights, this article considers three key COVID-19-related issues: research to identify remedies; testing, contact tracing and surveillance; and lingering health needs and disability. It provides a pathway for the future: community engagement to develop culturally-sensitive responses to the myriad genomic/bioethical dilemmas that arise, and the establishment of a Truth and Reconciliation Commission to transition the country from its contemporary state of segregation in healthcare and health outcomes into an equitable and prosperous society for all.

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Topics: Health equity (54%), Community engagement (52%), Human rights (51%) ... read more
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Open access
01 Jan 2013-
Abstract: We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts) Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice. © 2012 Wiley Periodicals, Inc.

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575 Citations


Journal ArticleDOI: 10.2139/SSRN.3741179
Nader Alber1, Refaat A1Institutions (1)
Abstract: This paper attempts to investigate the effects of Coronavirus spread on stock markets using panel data analysis, on daily basis over the period from March 1, 2020 until September 30, 2020. Coronavirus spread has been measured by daily cases and daily deaths per million of population, while stock return is measured by Δ in sectoral indices. This has been conducted after dividing the research period into 6 months from March to September and has been applied on 17 sectors in the Egyptian Exchange. Using panel data analysis, results indicate significant negative industry effects for each of banking sector (BANK), Food, Beverages and Tobacco sector (FOBT) and Health Care & Pharmaceuticals sector (HLTH). Besides, findings show significant positive industry effects for each of Contracting & Construction Engineering sector (COCE), Energy & Support Services sector (ENGY), IT, Media & Communication Services sector (IMCS), Shipping & Transportation Services sector (SHTS) and Trade & Distributors sector (TRDB). The robustness check supports the significant negative industry effects for each of Food, Beverages and Tobacco (FOBT) and Health Care & Pharmaceuticals (HLTH) (as losers) and the significant positive industry effects for each of Energy & Support Services (ENGY), Shipping & Transportation Services (SHTS) and Trade & Distributors (TRDB) (as winners).

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Topics: Population (51%)

102 Citations


Open accessJournal ArticleDOI: 10.1007/S11524-021-00532-3
Abstract: Geographic inequalities in COVID-19 diagnosis are now well documented. However, we do not sufficiently know whether inequalities are related to social characteristics of communities, such as collective engagement. We tested whether neighborhood social cohesion is associated with inequalities in COVID-19 diagnosis rate and the extent the association varies across neighborhood racial composition. We calculated COVID-19 diagnosis rates in Philadelphia, PA, per 10,000 general population across 46 ZIP codes, as of April 2020. Social cohesion measures were from the Southeastern Pennsylvania Household Health Survey, 2018. We estimated Poisson regressions to quantify associations between social cohesion and COVID-19 diagnosis rate, testing a multiplicative interaction with Black racial composition in the neighborhood, which we operationalize via a binary indicator of ZIP codes above vs. below the city-wide average (41%) Black population. Two social cohesion indicators were significantly associated with COVID-19 diagnosis. Associations varied across Black neighborhood racial composition (p <0.05 for the interaction test). In ZIP codes with ≥41% of Black people, higher collective engagement was associated with an 18% higher COVID-19 diagnosis rate (IRR=1.18, 95%CI=1.11, 1.26). In contrast, areas with <41% of Black people, higher engagement was associated with a 26% lower diagnosis rate (IRR=0.74, 95%CI=0.67, 0.82). Neighborhood social cohesion is associated with both higher and lower COVID-19 diagnosis rates, and the extent of associations varies across Black neighborhood racial composition. We recommend some strategies for reducing inequalities based on the segmentation model within the social cohesion and public health intervention framework.

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Topics: Population (53%)

4 Citations


Open accessPosted Content
Jason Kreag1Institutions (1)
Abstract: The FBI’s two-decade-long dominance of the use of genetic surveillance for law enforcement purposes is ending In its place, local police departments are creating DNA databases that operate outside of the FBI’s national DNA database network These local databases, which until now have remained unexamined, promise local law enforcement agencies freedom from the federal laws and regulations that govern the FBI’s national network This Article relies on original qualitative empirical research to describe why agencies created local databases and how these databases operate It finds that while local DNA databases offer promise as a crime-solving tool, they generate harms that so far have been ignored These harms include exacerbating racial inequities, threatening privacy and dignity interests, and undermining the legitimacy of the police Because law enforcement agencies have not internalized these harms, the self-imposed regulations that currently restrain law enforcement’s use of local DNA databases are insufficient This Article proposes several modest, yet effective, reforms that will minimize the harms generated by local DNA databases, while at the same time preserving law enforcement’s ability to wield this tool

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4 Citations


Journal ArticleDOI: 10.1080/15265161.2020.1870773
Ruqaiijah Yearby1Institutions (1)
Abstract: This commentary discusses how racism can be perpetuated in two of the areas discussed in Sabatello et al: research for identifying remedies and contact tracing. Racism is a social system where the ...

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Topics: Racism (51%)

3 Citations


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152 results found


Open accessJournal ArticleDOI: 10.17265/2159-5313/2016.09.003
28 Sep 2016-Philosophy study
Abstract: There has been a shift from the general presumption that “doctor knows best” to a heightened respect for patient autonomy. Medical ethics remains one-sided, however. It tends (incorrectly) to interpret patient autonomy as mere participation in decisions, rather than a willingness to take the consequences. In this respect, medical ethics remains largely paternalistic, requiring doctors to protect patients from the consequences of their decisions. This is reflected in a one-sided account of duties in medical ethics. Medical ethics may exempt patients from obligations because they are the weaker or more vulnerable party in the doctor-patient relationship. We argue that vulnerability does not exclude obligation. We also look at others ways in which patients’ responsibilities flow from general ethics: for instance, from responsibilities to others and to the self, from duties of citizens, and from the responsibilities of those who solicit advice. Finally, we argue that certain duties of patients counterbalance an otherwise unfair captivity of doctors as helpers.

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Topics: Nursing ethics (83%), Medical ethics (65%)

9,859 Citations


Open accessJournal ArticleDOI: 10.1001/JAMANETWORKOPEN.2020.3976
Jianbo Lai1, Simeng Ma2, Ying Wang2, Zhongxiang Cai2  +14 moreInstitutions (2)
02 Mar 2020-
Abstract: Importance Health care workers exposed to coronavirus disease 2019 (COVID-19) could be psychologically stressed. Objective To assess the magnitude of mental health outcomes and associated factors among health care workers treating patients exposed to COVID-19 in China. Design, Settings, and Participants This cross-sectional, survey-based, region-stratified study collected demographic data and mental health measurements from 1257 health care workers in 34 hospitals from January 29, 2020, to February 3, 2020, in China. Health care workers in hospitals equipped with fever clinics or wards for patients with COVID-19 were eligible. Main Outcomes and Measures The degree of symptoms of depression, anxiety, insomnia, and distress was assessed by the Chinese versions of the 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder scale, the 7-item Insomnia Severity Index, and the 22-item Impact of Event Scale–Revised, respectively. Multivariable logistic regression analysis was performed to identify factors associated with mental health outcomes. Results A total of 1257 of 1830 contacted individuals completed the survey, with a participation rate of 68.7%. A total of 813 (64.7%) were aged 26 to 40 years, and 964 (76.7%) were women. Of all participants, 764 (60.8%) were nurses, and 493 (39.2%) were physicians; 760 (60.5%) worked in hospitals in Wuhan, and 522 (41.5%) were frontline health care workers. A considerable proportion of participants reported symptoms of depression (634 [50.4%]), anxiety (560 [44.6%]), insomnia (427 [34.0%]), and distress (899 [71.5%]). Nurses, women, frontline health care workers, and those working in Wuhan, China, reported more severe degrees of all measurements of mental health symptoms than other health care workers (eg, median [IQR] Patient Health Questionnaire scores among physicians vs nurses: 4.0 [1.0-7.0] vs 5.0 [2.0-8.0];P = .007; median [interquartile range {IQR}] Generalized Anxiety Disorder scale scores among men vs women: 2.0 [0-6.0] vs 4.0 [1.0-7.0];P Conclusions and Relevance In this survey of heath care workers in hospitals equipped with fever clinics or wards for patients with COVID-19 in Wuhan and other regions in China, participants reported experiencing psychological burden, especially nurses, women, those in Wuhan, and frontline health care workers directly engaged in the diagnosis, treatment, and care for patients with COVID-19.

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Topics: Health care (62%), Patient Health Questionnaire (55%), Mental health (54%) ... read more

3,098 Citations


Journal ArticleDOI: 10.1126/SCIENCE.1078311
20 Dec 2002-Science
Abstract: We studied human population structure using genotypes at 377 autosomal microsatellite loci in 1056 individuals from 52 populations. Within-population differences among individuals account for 93 to 95% of genetic variation; differences among major groups constitute only 3 to 5%. Nevertheless, without using prior information about the origins of individuals, we identified six main genetic clusters, five of which correspond to major geographic regions, and subclusters that often correspond to individual populations. General agreement of genetic and predefined populations suggests that self-reported ancestry can facilitate assessments of epidemiological risks but does not obviate the need to use genetic information in genetic association studies.

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Topics: Genetic variability (63%), Genetic structure (60%), Genetic variation (59%) ... read more

2,509 Citations


Open accessJournal ArticleDOI: 10.1016/S2214-109X(20)30074-7
Joel Hellewell1, Sam Abbott1, Amy Gimma1, Nikos I Bosse1  +18 moreInstitutions (1)
Abstract: Summary Background Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings Simulated outbreaks starting with five initial cases, an R0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R0 of 2·5 more than 70% of contacts had to be traced, and for an R0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R0 was 1·5. For R0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.

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Topics: Contact tracing (55%)

1,624 Citations


Open accessJournal ArticleDOI: 10.15585/MMWR.MM6915E3
Shikha Garg1, Shikha Garg2, Lindsay Kim2, Michael Whitaker  +36 moreInstitutions (14)
Abstract: Since SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in December 2019 (1), approximately 1.3 million cases have been reported worldwide (2), including approximately 330,000 in the United States (3). To conduct population-based surveillance for laboratory-confirmed COVID-19-associated hospitalizations in the United States, the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) was created using the existing infrastructure of the Influenza Hospitalization Surveillance Network (FluSurv-NET) (4) and the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET). This report presents age-stratified COVID-19-associated hospitalization rates for patients admitted during March 1-28, 2020, and clinical data on patients admitted during March 1-30, 2020, the first month of U.S. surveillance. Among 1,482 patients hospitalized with COVID-19, 74.5% were aged ≥50 years, and 54.4% were male. The hospitalization rate among patients identified through COVID-NET during this 4-week period was 4.6 per 100,000 population. Rates were highest (13.8) among adults aged ≥65 years. Among 178 (12%) adult patients with data on underlying conditions as of March 30, 2020, 89.3% had one or more underlying conditions; the most common were hypertension (49.7%), obesity (48.3%), chronic lung disease (34.6%), diabetes mellitus (28.3%), and cardiovascular disease (27.8%). These findings suggest that older adults have elevated rates of COVID-19-associated hospitalization and the majority of persons hospitalized with COVID-19 have underlying medical conditions. These findings underscore the importance of preventive measures (e.g., social distancing, respiratory hygiene, and wearing face coverings in public settings where social distancing measures are difficult to maintain)† to protect older adults and persons with underlying medical conditions, as well as the general public. In addition, older adults and persons with serious underlying medical conditions should avoid contact with persons who are ill and immediately contact their health care provider(s) if they have symptoms consistent with COVID-19 (https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html) (5). Ongoing monitoring of hospitalization rates, clinical characteristics, and outcomes of hospitalized patients will be important to better understand the evolving epidemiology of COVID-19 in the United States and the clinical spectrum of disease, and to help guide planning and prioritization of health care system resources.

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Topics: Population (54%), Epidemiology (52%), Public health surveillance (51%)

1,502 Citations


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