Social determinants of COVID-19 incidence and outcomes: A rapid review.
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ABSTRACT:
SUBMITTER: Upshaw TL
PROVIDER: S-EPMC8011781 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe development of COVID-19 vaccines has been crucial in fighting the pandemic. However, misinformation about the COVID-19 pandemic and vaccines is spread on social media platforms at a rate that has made the World Health Organization coin the phrase infodemic. False claims about adverse vaccine side effects, such as vaccines being the cause of autism, were already considered a threat to global health before the outbreak of COVID-19.ObjectiveWe aimed to synthesize the existing research on misinformation about COVID-19 vaccines spread on social media platforms and its effects. The secondary aim was to gain insight and gather knowledge about whether misinformation about autism and COVID-19 vaccines is being spread on social media platforms.MethodsWe performed a literature search on September 9, 2021, and searched PubMed, PsycINFO, ERIC, EMBASE, Cochrane Library, and the Cochrane COVID-19 Study Register. We included publications in peer-reviewed journals that fulfilled the following criteria: original empirical studies, studies that assessed social media and misinformation, and studies about COVID-19 vaccines. Thematic analysis was used to identify the patterns (themes) of misinformation. Narrative qualitative synthesis was undertaken with the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 Statement and the Synthesis Without Meta-analysis reporting guideline. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal tool. Ratings of the certainty of evidence were based on recommendations from the Grading of Recommendations Assessment, Development and Evaluation Working Group.ResultsThe search yielded 757 records, with 45 articles selected for this review. We identified 3 main themes of misinformation: medical misinformation, vaccine development, and conspiracies. Twitter was the most studied social media platform, followed by Facebook, YouTube, and Instagram. A vast majority of studies were from industrialized Western countries. We identified 19 studies in which the effect of social media misinformation on vaccine hesitancy was measured or discussed. These studies implied that the misinformation spread on social media had a negative effect on vaccine hesitancy and uptake. Only 1 study contained misinformation about autism as a side effect of COVID-19 vaccines.ConclusionsTo prevent these misconceptions from taking hold, health authorities should openly address and discuss these false claims with both cultural and religious awareness in mind. Our review showed that there is a need to examine the effect of social media misinformation on vaccine hesitancy with a more robust experimental design. Furthermore, this review also demonstrated that more studies are needed from the Global South and on social media platforms other than the major platforms such as Twitter and Facebook.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42021277524; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021277524.International registered report identifier (irrid)RR2-10.31219/osf.io/tyevj.
| S-EPMC9359307 | biostudies-literature
Project description:ObjectiveTo synthesize the best available evidence on the relationship between the social determinants of health and health outcomes among adults during the COVID-19 pandemic.IntroductionCOVID-19 has created widespread global transmission. Rapid increase in individuals infected with COVID-19 prompted significant public health responses from governments globally. However, the social and economic impact on communities may leave some individuals more susceptible to the detrimental effects.MethodsA three-step search strategy was used to find published and unpublished papers. Databases searched included: MEDLINE, CINAHL, EMBASE, and Google Scholar. All identified citations were uploaded into Endnote X9, with duplicates removed. Methodological quality of eligible papers was assessed by two reviewers, with meta-synthesis conducted in accordance with JBI methodology.ResultsFifteen papers were included. Three synthesized-conclusions were established (a) Vulnerable populations groups, particularly those from a racial minority and those with low incomes, are more susceptible and have been disproportionately affected by COVID-19 including mortality; (b) Gender inequalities and family violence have been exacerbated by COVID-19, leading to diminished wellbeing among women; and (c) COVID-19 is exacerbating existing social determinants of health through loss of employment/income, disparities in social class leading to lack of access to health care, housing instability, homelessness, and difficulties in physical distancing.ConclusionReflection on social and health policies implemented are necessary to ensure that the COVID-19 pandemic does not exacerbate health inequalities into the future.
| S-EPMC8446962 | biostudies-literature
Project description:Adherence to coronavirus disease 2019 (COVID-19) preventive guidelines (ACPG) is an important strategy to control the COVID-19 pandemic effectively. The present study aimed to identify and summarize the social determinants of ACPG among the general population. A comprehensive review was performed from December 2019 to February 2021 through searching electronic databases. Two independent reviewers assessed and selected relevant studies. Next, the characteristics and main findings of the included studies were summarized. Finally, the World Health Organization's conceptual framework of social determinants of health was used to synthesize the identified social determinants of ACPG. Forty-one of 453 retrieved articles met the inclusion criteria. The study results showed different patterns of ACPG among various communities. Furthermore, 84 social determinants were identified and categorized into structural and intermediary determinants. ACPG is a set of complex behaviors associated with different individual sociodemographic and behavioral characteristics; living and working conditions; COVID-19 knowledge, attitudes, and risk perceptions; exposure to sources and information level; leisure activities; social support; trust; social norms; psychosocial well-being; socio-economic position; and the socio-economic and political context. Interventions to promote ACPG among the general population should consider the identified social determinants of ACPG.
| S-EPMC8721272 | biostudies-literature
Project description:BackgroundPhysical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic.MethodWe conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures.ResultsWe identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults.ConclusionInformation on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.
| S-EPMC8478104 | biostudies-literature
Project description:ObjectiveThis study aimed to determine the ability of retrospective cardiometabolic disease staging (CMDS) and social determinants of health (SDoH) to predict COVID-19 outcomes.MethodsIndividual and neighborhood SDoH and CMDS clinical parameters (BMI, glucose, blood pressure, high-density lipoprotein, triglycerides), collected up to 3 years prior to a positive COVID-19 test, were extracted from the electronic medical record. Bayesian logistic regression was used to model CMDS and SDoH to predict subsequent hospitalization, intensive care unit (ICU) admission, and mortality, and whether adding SDoH to the CMDS model improved prediction was investigated. Models were cross validated, and areas under the curve (AUC) were compared.ResultsA total of 2,873 patients were identified (mean age: 58 years [SD 13.2], 59% were female, 45% were Black). CMDS, insurance status, male sex, and higher glucose values were associated with increased odds of all outcomes; area-level social vulnerability was associated with increased odds of hospitalization (odds ratio: 1.84, 95% CI: 1.38-2.45) and ICU admission (odds ratio 1.98, 95% CI: 1.45-2.85). The AUCs improved when SDoH were added to CMDS (p < 0.001): hospitalization (AUC 0.78 vs. 0.82), ICU admission (AUC 0.77 vs. 0.81), and mortality (AUC 0.77 vs. 0.83).ConclusionsRetrospective clinical markers of cardiometabolic disease and SDoH were independently predictive of COVID-19 outcomes in the population.
| S-EPMC9088642 | biostudies-literature
Project description:ImportanceAs the United States continues to accumulate COVID-19 cases and deaths, and disparities persist, defining the impact of risk factors for poor outcomes across patient groups is imperative.ObjectiveOur objective is to use real-world healthcare data to quantify the impact of demographic, clinical, and social determinants associated with adverse COVID-19 outcomes, to identify high-risk scenarios and dynamics of risk among racial and ethnic groups.DesignA retrospective cohort of COVID-19 patients diagnosed between March 1 and August 20, 2020. Fully adjusted logistical regression models for hospitalization, severe disease and mortality outcomes across 1-the entire cohort and 2-within self-reported race/ethnicity groups.SettingThree sites of the NewYork-Presbyterian health care system serving all boroughs of New York City. Data was obtained through automated data abstraction from electronic medical records.ParticipantsDuring the study timeframe, 110,498 individuals were tested for SARS-CoV-2 in the NewYork-Presbyterian health care system; 11,930 patients were confirmed for COVID-19 by RT-PCR or covid-19 clinical diagnosis.Main outcomes and measuresThe predictors of interest were patient race/ethnicity, and covariates included demographics, comorbidities, and census tract neighborhood socio-economic status. The outcomes of interest were COVID-19 hospitalization, severe disease, and death.ResultsOf confirmed COVID-19 patients, 4,895 were hospitalized, 1,070 developed severe disease and 1,654 suffered COVID-19 related death. Clinical factors had stronger impacts than social determinants and several showed race-group specificities, which varied among outcomes. The most significant factors in our all-patients models included: age over 80 (OR=5.78, p= 2.29×10 -24 ) and hypertension (OR=1.89, p=1.26×10 -10 ) having the highest impact on hospitalization, while Type 2 Diabetes was associated with all three outcomes (hospitalization: OR=1.48, p=1.39×10 -04 ; severe disease: OR=1.46, p=4.47×10 -09 ; mortality: OR=1.27, p=0.001). In race-specific models, COPD increased risk of hospitalization only in Non-Hispanics (NH)-Whites (OR=2.70, p=0.009). Obesity (BMI 30+) showed race-specific risk with severe disease NH-Whites (OR=1.48, p=0.038) and NH-Blacks (OR=1.77, p=0.025). For mortality, Cancer was the only risk factor in Hispanics (OR=1.97, p=0.043), and heart failure was only a risk in NH-Asians (OR=2.62, p=0.001).Conclusions and relevanceComorbidities were more influential on COVID-19 outcomes than social determinants, suggesting clinical factors are more predictive of adverse trajectory than social factors.Key pointsQUESTION: What is the impact of patient self-reported race, ethnicity, socioeconomic status, and clinical profile on COVID-19 hospitalizations, severity, and mortality?FINDINGS: In patients diagnosed with COVID-19, being over 50 years of age, having type 2 diabetes and hypertension were the most important risk factors for hospitalization and severe outcomes regardless of patient race or socioeconomic status.MEANING: In this large sample pf patients diagnosed with COVID-19 in New York City, we found that clinical comorbidity, more so than social determinants of health, was associated with important patient outcomes.
| S-EPMC8043490 | biostudies-literature
Project description:IntroductionInfectious disease models are important tools to inform public health policy decisions. These models are primarily based on an average population approach and often ignore the role of social determinants in predicting the course of a pandemic and the impact of policy interventions. Ignoring social determinants in models may cause or exacerbate inequalities. This limitation has not been previously explored in the context of the current pandemic, where COVID-19 has been found to disproportionately affect marginalised racial, ethnic and socioeconomic groups. Therefore, our primary goal is to identify the extent to which COVID-19 models incorporate the social determinants of health in predicting outcomes of the pandemic.Methods and analysisWe will search MEDLINE, EMBASE, Cochrane Library and Web of Science databases from December 2019 to August 2020. We will assess all infectious disease modelling studies for inclusion of social factors that meet the following criteria: (a) focused on human spread of SARS-CoV-2; (b) modelling studies; (c) interventional or non-interventional studies; and (d) focused on one of the following outcomes: COVID-19-related outcomes (eg, cases, deaths), non-COVID-19-related outcomes (ie, impacts of the pandemic or control policies on other health conditions or health services), or impact of the pandemic or control policies on economic outcomes. Data will only be extracted from models incorporating social factors. We will report the percentage of models that considered social factors, indicate which social factors were considered, and describe how social factors were incorporated into the conceptualisation and implementation of the infectious disease models. The extracted data will also be used to create a narrative synthesis of the results.Ethics and disseminationEthics approval is not required as only secondary data will be collected. The results of this systematic review will be disseminated through peer-reviewed publication and conference proceedings.Prospero registration numberCRD42020207706.
| S-EPMC8260285 | biostudies-literature
Project description:IntroductionThe COVID-19 pandemic has exacerbated health inequalities across the globe, disproportionately affecting those with poor social determinants of health (SDOHs). It is imperative to understand how SDOH influences the transmission and outcomes (positive case, hospitalisation and mortality) of COVID-19. This systematic review will investigate the impact of a wide range of SDOHs across the globe on the transmission and outcomes of COVID-19.Methods and analysisThis review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines. We will search three electronic bibliographical databases (MEDLINE via PubMed, Embase and Scopus), as well as the WHO COVID-19 Global Research on Coronavirus Disease database. We will consider observational studies that report statistical relationships between the SDOHs (as listed in PROGRESS-Plus and Healthy People 2020) and COVID-19 transmission and outcomes. There will be no limitation on the geographical location of publications. The quality of included observational studies will be assessed using a modified version of the Newcastle-Ottawa Scale. A narrative synthesis without meta-analysis reporting standards will be used to report the review findings.Ethics and disseminationThis review will be based on published studies obtained from publicly available sources, and therefore, ethical approval is not required. We will publish the results of this review in a peer-reviewed journal, as well as present the study findings at a national conference.Prospero registration numberCRD42021228818.
| S-EPMC8637315 | biostudies-literature
Project description:As of August 2020, the United States is the global epicenter of the COVID-19 pandemic. Emerging data suggests that "essential" workers, who are disproportionately more likely to be racial/ethnic minorities and immigrants, bear a disproportionate degree of risk. We used publicly available data to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) percentage of individuals engaged in farm work, (2) percentage of households without a fluent, adult English-speaker, (3) percentage of uninsured individuals under the age of 65, and (4) percentage of individuals living at or below the federal poverty line. We further adjusted these models for total population, population density, and number of days since the first reported case in a given county. We found that across all counties that had reported a case of COVID-19 as of July 12, 2020 (n = 3024), a higher percentage of farmworkers, a higher percentage of residents living in poverty, higher density, higher population, and a higher percentage of residents over the age of 65 were all independently and significantly associated with a higher number of deaths in a county. In urban counties (n = 115), a higher percentage of farmworkers, higher density, and larger population were all associated with a higher number of deaths, while lower rates of insurance coverage in a county was independently associated with fewer deaths. In non-urban counties (n = 2909), these same patterns held true, with higher percentages of residents living in poverty and senior residents also significantly associated with more deaths. Taken together, our findings suggest that farm workers may face unique risks of contracting and dying from COVID-19, and that these risks are independent of poverty, insurance, or linguistic accessibility of COVID-19 health campaigns.
| S-EPMC7556498 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic has resulted in millions of patients infected worldwide and indirectly affecting even more individuals through disruption of daily living. Long-term adverse outcomes have been reported with similar diseases from other coronaviruses, namely Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Emerging evidence suggests that COVID-19 adversely affects different systems in the human body. This review summarizes the current evidence on the short-term adverse health outcomes and assesses the risk of potential long-term adverse outcomes of COVID-19. Major adverse outcomes were found to affect different body systems: immune system (including but not limited to Guillain-Barré syndrome and paediatric inflammatory multisystem syndrome), respiratory system (lung fibrosis and pulmonary thromboembolism), cardiovascular system (cardiomyopathy and coagulopathy), neurological system (sensory dysfunction and stroke), as well as cutaneous and gastrointestinal manifestations, impaired hepatic and renal function. Mental health in patients with COVID-19 was also found to be adversely affected. The burden of caring for COVID-19 survivors is likely to be huge. Therefore, it is important for policy makers to develop comprehensive strategies in providing resources and capacity in the healthcare system. Future epidemiological studies are needed to further investigate the long-term impact on COVID-19 survivors.
| S-EPMC7586446 | biostudies-literature