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1.
JAMA ; 328(16): 1639-1641, 2022 10 25.
Article in English | MEDLINE | ID: covidwho-2094108

ABSTRACT

This study examines changes in unemployment among US health care workers from January 2015 to April 2022, before and after the onset of the COVID-19 pandemic.


Subject(s)
COVID-19 , Health Personnel , Health Workforce , Unemployment , Humans , COVID-19/epidemiology , Health Personnel/statistics & numerical data , Pandemics/statistics & numerical data , SARS-CoV-2 , Unemployment/statistics & numerical data , Health Workforce/statistics & numerical data
3.
Ophthalmic Epidemiol ; 29(6): 613-620, 2022 12.
Article in English | MEDLINE | ID: covidwho-1569401

ABSTRACT

PURPOSE: To explore individual and community factors associated with adherence to physician recommended urgent eye visits via a tele-triage system during the COVID-19 pandemic. METHOD: We retrospectively reviewed acute visit requests and medical exam data between April 6, 2020 and June 6, 2020. Patient demographics and adherence to visit were examined. Census tract level community characteristics from the U.S. Census Bureau and zip code level COVID-19 related death data from the Cook County Medical Examiner's Office were appended to each geocoded patient address. Descriptive statistics, t-tests, and logistic regression analyses were performed to explore the effects of individual and community variables on adherence to visit. RESULTS: Of 229 patients recommended an urgent visit, 216 had matching criteria on chart review, and 192 (88.9%) adhered to their visit. No difference in adherence was found based on individual characteristics including: age (p = .24), gender (p = .94), race (p = .56), insurance (p = .28), nor new versus established patient status (p = .20). However, individuals who did not adhere were more likely to reside in neighborhoods with a greater proportion of Blacks (59.4% vs. 33.4%; p = .03), greater unemployment rates (17.5% vs. 10.7%; p < .01), and greater cumulative deaths from COVID-19 (56 vs. 31; p = .01). Unemployment rate continued to be statistically significant after controlling for race and cumulative deaths from COVID-19 (p = .04). CONCLUSION: We found that as community unemployment rate increases, adherence to urgent eye visits decreases, after controlling for relevant neighborhood characteristics. Unemployment rates were highest in predominantly Black neighborhoods early in the pandemic, which may have contributed to existing racial disparities in eye care.


Subject(s)
COVID-19 , Eye , Office Visits , Ophthalmology , Patient Compliance , Humans , COVID-19/epidemiology , Pandemics , Residence Characteristics/statistics & numerical data , Retrospective Studies , Patient Compliance/ethnology , Patient Compliance/statistics & numerical data , Triage/methods , Telemedicine/methods , Healthcare Disparities/economics , Healthcare Disparities/ethnology , Healthcare Disparities/statistics & numerical data , Office Visits/economics , Office Visits/statistics & numerical data , Ophthalmology/statistics & numerical data , Unemployment/statistics & numerical data , Physical Examination/economics , Physical Examination/statistics & numerical data
4.
Am J Public Health ; 111(11): 1950-1959, 2021 11.
Article in English | MEDLINE | ID: covidwho-1538296

ABSTRACT

Objectives. To determine whether unemployment and bankruptcy rates are related to increased excess deaths during the COVID-19 recession and to examine whether the current recession-based mortality rate not only is dependent on COVID-19 but also continues the pattern of recessions, especially the Great Recession, in relation to chronic disease mortality rates and mental health disturbances (e.g., including suicide) from 2000 to 2018. Methods. This study used pooled cross-sectional time series analysis to determine the impact of unemployment and bankruptcy rates on excess deaths from February to November 2020 for US states. The study used a second pooled cross-sectional time series analysis to determine whether the COVID-19‒ era recessional mortality continues the impact of prepandemic recessions (2000-2018) on multiple causes of mortality. Results. Ten percent unemployment was associated with approximately 48[thin space]149 excess deaths, while, jointly with bankruptcies, their combined effect produced 35 700 and 144 483 excess deaths, for unemployment and bankruptcies, respectively. These health-damaging COVID-19‒recessional findings suggest a reiteration of the significantly increased major cause‒specific mortality during 2000 to 2018, mitigated by the size of the health care workforce. Conclusions. Minimization of deaths attributable to the COVID-19 recession requires ample funding for the unemployed and underemployed, especially Black and Hispanic communities, along with significant investments in the health workforce. (Am J Public Health. 2021;111(11):1950-1959. https://doi.org/10.2105/AJPH.2021.306490).


Subject(s)
Bankruptcy/statistics & numerical data , COVID-19 , Cause of Death , Economic Recession , Mortality/trends , Unemployment/statistics & numerical data , Cross-Sectional Studies , Ethnicity/statistics & numerical data , Female , Humans , Male , Suicide/psychology , United States
5.
Gac Med Mex ; 157(3): 263-270, 2021.
Article in English | MEDLINE | ID: covidwho-1535083

ABSTRACT

INTRODUCTION: Historically, pandemics have resulted in higher mortality rates in the most vulnerable populations. Social determinants of health (SDH) have been associated with people morbidity and mortality at different levels. OBJECTIVE: To determine the relationship between SDH and COVID-19 severity and mortality. METHODS: Retrospective study, where data from patients with COVID-19 were collected at a public hospital in Chile. Sociodemographic variables related to structural SDH were classified according to the following categories: gender, age (< 65 years, ≥ 65 years), secondary education (completed or not), work status (active, inactive) and income (< USD 320, ≥ USD 320). RESULTS: A total of 1,012 laboratory-confirmed COVID-19 cases were included. Average age was 64.2 ± 17.5 years. Mortality of the entire sample was 14.5 %. Age, level of education, unemployment and income had a strong association with mortality (p < 0.001). CONCLUSIONS: The findings reinforce the idea that SDH should be considered a public health priority, which is why political efforts should focus on reducing health inequalities for future generations.


INTRODUCCIÓN: Históricamente, las pandemias han tenido como resultado tasas de mortalidad más altas en las poblaciones más vulnerables. Los determinantes sociales de la salud (DSS) se han asociado a la morbimortalidad de las personas en diferentes niveles. OBJETIVO: Determinar la relación entre los DSS, la severidad de COVID-19 y la mortalidad por esta enfermedad. MÉTODOS: Estudio retrospectivo en el que se recolectaron datos de pacientes con COVID-19 en un hospital público de Chile. Las variables sociodemográficas relacionadas con los DSS estructurales se clasificaron según las siguientes categorías: sexo, edad (< 65 años, ≥ 65 años), educación secundaria (completada o no), condición de trabajo (activo, inactivo) e ingreso económico (< USD 320, ≥ USD 320). RESULTADOS: Fueron incluidos 1012 casos con COVID-19 confirmados por laboratorio. La edad promedio fue de 64.2 ± 17.5 años. La mortalidad de la muestra total fue de 14.5 %. La edad, nivel educativo, desempleo e ingresos tuvieron fuerte asociación con la mortalidad (p < 0.001). CONCLUSIONES: Los hallazgos refuerzan la idea de que los DSS deben considerarse una prioridad de salud pública, por lo que los esfuerzos políticos deben centrarse en reducir las desigualdades en salud para las generaciones futuras.


Subject(s)
COVID-19/epidemiology , Social Determinants of Health , Age Factors , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/physiopathology , Chile/epidemiology , Educational Status , Female , Hospitals, Public , Humans , Income/statistics & numerical data , Male , Middle Aged , Retrospective Studies , Risk Factors , Severity of Illness Index , Unemployment/statistics & numerical data
7.
Saudi Med J ; 42(4): 384-390, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1513255

ABSTRACT

OBJECTIVES: To measure the Saudi population's sleep quality during the lockdown of COVID-19. METHODS: An internet-based questionnaire that was performed during the lockdown of the COVID-19 pandemic among the Saudi population over 2 weeks from April 1 to April 15, 2020. We used the instant messaging application WhatsApp and Twitter to reach the targeted population. Saudi citizens and non-Saudi residents who can read and understand the questionnaire were recruited. Data were analyzed using Stata and SPSS. RESULTS: A total of 790 responses were included. The majority of participants were the Saudi population 735 (92.9%). The prevalence of insomnia and poor sleep quality were 54.4% and 55.5%, respectively. Saudi citizenship was associated with longer sleep duration (p=0.031). Female gender and being married were associated with worse global PSQI, sleep quality, sleep distribution, sleep latency, and daytime dysfunction. CONCLUSION: Our findings showed that during the COVID-19 pandemic, the Saudi population had a high prevalence of insomnia and poor sleep quality. Routine monitoring of the psychological impact of life-threatening outbreaks and the adoption of effective early mental health actions should be considered.


Subject(s)
COVID-19 , Disorders of Excessive Somnolence/epidemiology , Sleep Initiation and Maintenance Disorders/epidemiology , Sleep , Adult , Communicable Disease Control , Cross-Sectional Studies , Educational Status , Female , Humans , Male , Marital Status/statistics & numerical data , Middle Aged , Prevalence , Public Policy , Risk Factors , SARS-CoV-2 , Saudi Arabia/epidemiology , Sex Factors , Sleep Latency , Surveys and Questionnaires , Unemployment/statistics & numerical data
8.
Am J Public Health ; 111(S3): S215-S223, 2021 10.
Article in English | MEDLINE | ID: covidwho-1496725

ABSTRACT

Public Health 3.0 approaches are critical for monitoring disparities in economic, social, and overall health impacts following the COVID-19 pandemic and its associated policy changes to slow community spread. Timely, cross-sector data as identified using this approach help decisionmakers identify changes, track racial disparities, and address unintended consequences during a pandemic. We applied a monitoring and evaluation framework that combined policy changes with timely, relevant cross-sector data and community review. Indicators covered unemployment, basic needs, family violence, education, childcare, access to health care, and mental, physical, and behavioral health. In response to increasing COVID-19 cases, nonpharmaceutical intervention strategies were implemented in March 2020 in King County, Washington. By December 2020, 554 000 unemployment claims were filed. Social service calls increased 100%, behavioral health crisis calls increased 25%, and domestic violence calls increased 25%, with disproportionate impact on communities of color. This framework can be replicated by local jurisdictions to inform and address racial inequities in ongoing COVID-19 mitigation and recovery. Cross-sector collaboration between public health and sectors addressing the social determinants of health are an essential first step to have an impact on long-standing racial inequities. (Am J Public Health. 2021;111(S3):S215-S223. https://doi.org/10.2105/AJPH.2021.306422).


Subject(s)
COVID-19 , Health Policy , Health Services Accessibility , Health Status Disparities , Public Health , COVID-19/economics , COVID-19/prevention & control , Humans , Mental Health , Population Surveillance , Unemployment/statistics & numerical data , Washington
9.
Crit Care Med ; 49(11): e1157-e1162, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1467424

ABSTRACT

OBJECTIVES: Joblessness is common in survivors from critical care. Our aim was to describe rates of return to work versus unemployment following coronavirus disease 2019 acute respiratory distress syndrome requiring intensive care admission. DESIGN: Single-center, prospective case series. SETTING: Critical Care Follow-Up Clinic, Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy. PATIENTS: One hundred and one consecutive laboratory-confirmed coronavirus disease 2019 patients were discharged from our hospital following an ICU stay between March 1, 2020, and June 30, 2020. Twenty-five died in the ICU. Seventy-six were discharged alive from hospital. Two patients refused participation, while three were unreachable. The remaining 71 were alive at 6 months and interviewed. INTERVENTIONS: Baseline and outcome healthcare data were extracted from the electronic patient records. Employment data were collected using a previously published structured interview instrument that included current and previous employment status, hours worked per week, and timing of return to work. Health-related quality of life status was assessed using the Italian EQ-5D-5L questionnaire. MEASUREMENTS AND MAIN RESULTS: Of the 71 interviewed patients, 45 (63%) were employed prior to coronavirus disease 2019, of which 40 (89%) of them worked full-time. Thirty-three (73%) of the previously employed survivors had returned to work by 6 months, 10 (22%) were unemployed, and 2 (5%) were newly retired. Among those who returned to work, 20 (85%) of them reported reduced effectiveness at work. Those who did not return to work were either still on sick leave or lost their job as a consequence of coronavirus disease 2019. Reported quality of life of survivors not returning to work was worse than of those returning to work. CONCLUSIONS: The majority of coronavirus disease 2019 survivors following ICU in our cohort had returned to work by 6 months of follow-up. However, most of them reported reduced work effectiveness. Prolonged sick leave and unemployment were common findings in those not returning.


Subject(s)
COVID-19/epidemiology , Critical Care/statistics & numerical data , Respiratory Distress Syndrome/epidemiology , Return to Work/statistics & numerical data , Unemployment/statistics & numerical data , Age Factors , Aged , Comorbidity , Female , Frailty/epidemiology , Humans , Length of Stay , Male , Middle Aged , Patient Discharge/statistics & numerical data , Quality of Life , Retirement/statistics & numerical data , SARS-CoV-2 , Severity of Illness Index , Sex Factors , Socioeconomic Factors
11.
Health Serv Res ; 57(1): 15-26, 2022 02.
Article in English | MEDLINE | ID: covidwho-1405159

ABSTRACT

OBJECTIVE: To estimate the impact of the $600 per week Federal Pandemic Unemployment Compensation (FPUC) payments on health care services spending during the Covid pandemic and to investigate if this impact varied by state Medicaid expansion status. DATA SOURCES: This study leverages novel, publicly available data from Opportunity Insights capturing consumer credit and debit card spending on health care services for January 18-August 15, 2020 as well as information on unemployment insurance claims, Covid cases, and state policy changes. STUDY DESIGN: Using triple-differences estimation, we leverage two sources of variation-within-state change in the unemployment insurance claims rate and the introduction of FPUC payments-to estimate the moderating effect of FPUC on health care spending losses as unemployment rises. Results are stratified by state Medicaid expansion status. EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: For each percentage point increase in the unemployment insurance claims rate, health care spending declined by 1.0% (<0.05) in Medicaid expansion states and by 2.0% (<0.01) in nonexpansion states. However, FPUC partially mitigated this association, boosting spending by 0.8% (<0.001) and 1.3% (<0.05) in Medicaid expansion and nonexpansion states, respectively, for every percentage point increase in the unemployment insurance claims rate. CONCLUSIONS: We find that FPUC bolstered health care spending during the Covid pandemic, but that both the negative consequences of unemployment and moderating effects of federal income supports were greatest in states that did not adopt Medicaid expansion. These results indicate that emergency federal spending helped to sustain health care spending during a period of rising unemployment. Yet, the effectiveness of this program also suggests possible unmet demand for health care services, particularly in states that did not adopt Medicaid expansion.


Subject(s)
COVID-19/economics , Health Expenditures/statistics & numerical data , Health Services Accessibility/economics , Medicaid/economics , Unemployment/statistics & numerical data , COVID-19/epidemiology , Humans , Patient Protection and Affordable Care Act , United States
13.
J Appl Psychol ; 106(4): 518-529, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1236065

ABSTRACT

The purpose of this article is to simultaneously advance theory and practice by understanding how the Coronavirus disease 2019 (COVID-19) pandemic relates to new hire engagement. Prior research suggests starting a new job is an uncertain experience; we theorize that the COVID-19 pandemic creates additional environmental stressors that affect new hire engagement. First, we hypothesize that the occurrence of COVID-19 and unemployment rates relate negatively to engagement. Second, we theorize that the effects of the pandemic become more disruptive on new hire engagement as they gain tenure within the organization. Third, drawing from strategic management theory, we test whether States that introduce stronger COVID-19 policies help enhance the engagement of new hires. Examining a U.S. national sample of 12,577 newly hired (90 days or less) quick service restaurant employees across 9 months (January-September, 2020), we find support for these hypotheses. Subsequent model comparisons suggest there may be health stressors that shape engagement more strongly than purely economic stressors. These findings may be important because they highlight the experiences of workers more likely to be exposed to the pandemic and affected by COVID-related policies. Should the results generalize to other samples and jobs, this study offers potentially new research directions for understanding relationships between macro stressors and new hire perceptions and socialization. It also offers practical implications by helping organizations understand the importance of explicitly managing job insecurity, particularly in terms of COVID-19 policy. (PsycInfo Database Record (c) 2021 APA, all rights reserved).


Subject(s)
COVID-19/psychology , Pandemics/legislation & jurisprudence , State Government , Unemployment/statistics & numerical data , Work Engagement , Workplace/legislation & jurisprudence , Adult , Aged , Female , Humans , Male , Middle Aged , Personnel Selection/statistics & numerical data , SARS-CoV-2 , Time Factors , Unemployment/psychology , United States , Young Adult
14.
New Solut ; 31(2): 107-112, 2021 08.
Article in English | MEDLINE | ID: covidwho-1232404

ABSTRACT

The global political economy is generating new forms and growing shares of informal, insecure, and precarious labor, adding to histories of insecure work and an externalization of social costs. The COVID-19 pandemic has highlighted the consequences of ignoring such signals in terms of the increased risk and vulnerability of insecure labor. This paper explores how such trends are generating intersecting adverse health outcomes for workers, communities, and environments and the implications for breaking siloes and building links between the paradigms, science, practice, and tools for occupational health, public health, and eco-health. Applying the principle of controlling hazards at the source is argued in this context to call for an understanding of the upstream production and socio-political factors that are jointly affecting the nature of work and employment and their impact on the health of workers, the public, and the planet.


Subject(s)
Employment , Occupational Health/trends , Adolescent , Africa, Eastern , Africa, Southern , COVID-19/epidemiology , Employment/psychology , Employment/standards , Employment/statistics & numerical data , Female , Humans , Male , Politics , Public Health , Unemployment/psychology , Unemployment/statistics & numerical data , Workplace/psychology , Workplace/standards , Young Adult
15.
Scand J Public Health ; 49(1): 64-68, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1207558

ABSTRACT

BACKGROUND AND AIMS: Interventions to suppress the coronavirus pandemic have led to economic recession and higher unemployment, which will increase mortality and decrease quality of life. The aim of this article is to estimate the consequences on mortality and life expectancy of increased unemployment rates due to the coronavirus pandemic in Sweden and other countries. METHODS: Based on recent increases and expected future unemployment rates due to the coronavirus pandemic, results from a systematic review and data from vital statistics in Sweden, the number of premature deaths due to unemployment in Sweden have been estimated. RESULTS: Based on our assumptions, the calculations show that if the number of unemployed persons in Sweden increases by 100,000, one may expect some 1800 more premature deaths during the following 9 years. If the duration of the recession is limited to 4 years, excess deaths due to unemployment may be around 800. On average, the unemployed will lose 2 years of their remaining life expectancy. In many other countries unemployment rates have or are estimated to rise more than in Sweden, sometimes two- or threefold, suggesting hundreds of thousands of excess deaths due to unemployment. CONCLUSIONS: Interventions to suppress the coronavirus pandemic include the shut-down of economic activities and lead to increased all-cause mortality. These public health effects must be considered in the decision-making process and should be added to overall estimates of the effects of the pandemic on public health.


Subject(s)
COVID-19/prevention & control , Mortality, Premature , Unemployment/statistics & numerical data , COVID-19/epidemiology , Economic Recession , Humans , Life Expectancy , Sweden/epidemiology
16.
Nat Commun ; 12(1): 2274, 2021 04 15.
Article in English | MEDLINE | ID: covidwho-1189224

ABSTRACT

Massive unemployment during the COVID-19 pandemic could result in an eviction crisis in US cities. Here we model the effect of evictions on SARS-CoV-2 epidemics, simulating viral transmission within and among households in a theoretical metropolitan area. We recreate a range of urban epidemic trajectories and project the course of the epidemic under two counterfactual scenarios, one in which a strict moratorium on evictions is in place and enforced, and another in which evictions are allowed to resume at baseline or increased rates. We find, across scenarios, that evictions lead to significant increases in infections. Applying our model to Philadelphia using locally-specific parameters shows that the increase is especially profound in models that consider realistically heterogenous cities in which both evictions and contacts occur more frequently in poorer neighborhoods. Our results provide a basis to assess eviction moratoria and show that policies to stem evictions are a warranted and important component of COVID-19 control.


Subject(s)
COVID-19/transmission , Communicable Disease Control/methods , Housing/legislation & jurisprudence , Pandemics/prevention & control , Policy , COVID-19/economics , COVID-19/epidemiology , COVID-19/virology , Cities/legislation & jurisprudence , Cities/statistics & numerical data , Communicable Disease Control/legislation & jurisprudence , Computer Simulation , Housing/economics , Humans , Models, Statistical , Philadelphia/epidemiology , SARS-CoV-2/pathogenicity , Unemployment/statistics & numerical data , Urban Population/statistics & numerical data
17.
JAMA Netw Open ; 4(4): e217373, 2021 04 01.
Article in English | MEDLINE | ID: covidwho-1171508

ABSTRACT

Importance: An accurate understanding of the distributional implications of public health policies is critical for ensuring equitable responses to the COVID-19 pandemic and future public health threats. Objective: To identify and quantify the association of race/ethnicity-based, sex-based, and income-based inequities of state-specific lockdowns with 6 well-being dimensions in the United States. Design, Setting, and Participants: This pooled, repeated cross-sectional study used data from 14 187 762 households who participated in phase 1 of the population-representative US 2020 Household Pulse Survey (HPS). Households were invited to participate by email, text message, and/or telephone as many as 3 times. Data were collected via an online questionnaire from April 23 to July 21, 2020, and participants lived in all 50 US states and the District of Columbia. Exposures: Indicators of race/ethnicity, sex, and income and their intersections. Main Outcomes and Measures: Unemployment; food insufficiency; mental health problems; no medical care received for health problems; default on last month's rent or mortgage; and class cancellations with no distance learning. Race/ethnicity, sex, income, and their intersections were used to measure distributional implications across historically marginalized populations; state-specific, time-varying population mobility was used to measure lockdown intensity. Logistic regression models with pooled repeated cross-sections were used to estimate risk of dichotomous outcomes by social group, adjusted for confounding variables. Results: The 1 088 314 respondents (561 570 [51.6%; 95% CI, 51.4%-51.9%] women) were aged 18 to 88 years (mean [SD], 51.55 [15.74] years), and 826 039 (62.8%; 95% CI, 62.5%-63.1%) were non-Hispanic White individuals; 86 958 (12.5%; 95% CI, 12.4%-12.7%), African American individuals; 86 062 (15.2%; 95% CI, 15.0%-15.4%), Hispanic individuals; and 50 227 (5.6%; 95% CI, 5.5%-5.7%), Asian individuals. On average, every 10% reduction in mobility was associated with higher odds of unemployment (odds ratio [OR], 1.3; 95% CI, 1.2-1.4), food insufficiency (OR, 1.1; 95% CI, 1.1-1.2), mental health problems (OR, 1.04; 95% CI, 1.0-1.1), and class cancellations (OR, 1.1; 95% CI, 1.1-1.2). Across most dimensions compared with White men with high income, African American individuals with low income experienced the highest risks (eg, food insufficiency, men: OR, 3.3; 95% CI, 2.8-3.7; mental health problems, women: OR, 1.9; 95% CI, 1.8-2.1; medical care inaccessibility, women: OR, 1.7; 95% CI, 1.6-1.9; unemployment, men: OR, 2.8; 95% CI, 2.5-3.2; rent/mortgage defaults, men: OR, 5.7; 95% CI, 4.7-7.1). Other high-risk groups were Hispanic individuals (eg, unemployment, Hispanic men with low income: OR, 2.9; 95% CI, 2.5-3.4) and women with low income across all races/ethnicities (eg, medical care inaccessibility, non-Hispanic White women: OR, 1.8; 95% CI, 1.7-2.0). Conclusions and Relevance: In this cross-sectional study, African American and Hispanic individuals, women, and households with low income had higher odds of experiencing adverse outcomes associated with the COVID-19 pandemic and stay-at-home orders. Blanket public health policies ignoring existing distributions of risk to well-being may be associated with increased race/ethnicity-based, sex-based, and income-based inequities.


Subject(s)
COVID-19 , Communicable Disease Control/statistics & numerical data , Ethnicity/statistics & numerical data , Income/statistics & numerical data , Racial Groups/statistics & numerical data , Sex Factors , Adolescent , Adult , Aged , Aged, 80 and over , Cross-Sectional Studies , Family Characteristics , Female , Food Security/statistics & numerical data , Health Status Disparities , Humans , Male , Middle Aged , SARS-CoV-2 , Unemployment/statistics & numerical data , United States , Young Adult
18.
Ann Med ; 53(1): 581-586, 2021 12.
Article in English | MEDLINE | ID: covidwho-1171161

ABSTRACT

Although coronavirus disease 2019 (COVID-19) is a pandemic, it has several specificities influencing its outcomes due to the entwinement of several factors, which anthropologists have called "syndemics". Drawing upon Singer and Clair's syndemics model, I focus on synergistic interaction among chronic kidney disease (CKD), diabetes, and COVID-19 in Pakistan. I argue that over 36 million people in Pakistan are standing at a higher risk of contracting COVID-19, developing severe complications, and losing their lives. These two diseases, but several other socio-cultural, economic, and political factors contributing to structured vulnerabilities, would function as confounders. To deal with the critical effects of these syndemics the government needs appropriate policies and their implementation during the pandemic and post-pandemic. To eliminate or at least minimize various vulnerabilities, Pakistan needs drastic changes, especially to overcome (formal) illiteracy, unemployment, poverty, gender difference, and rural and urban difference.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus/epidemiology , Pandemics/prevention & control , Renal Insufficiency, Chronic/epidemiology , Syndemic , COVID-19/prevention & control , Climate Change/economics , Climate Change/statistics & numerical data , Confounding Factors, Epidemiologic , Developing Countries/economics , Developing Countries/statistics & numerical data , Diabetes Mellitus/economics , Diabetes Mellitus/prevention & control , Food Supply/economics , Food Supply/statistics & numerical data , Health Literacy/economics , Health Literacy/statistics & numerical data , Humans , Pakistan/epidemiology , Pandemics/economics , Politics , Poverty/economics , Poverty/statistics & numerical data , Renal Insufficiency, Chronic/economics , Renal Insufficiency, Chronic/prevention & control , Unemployment/statistics & numerical data
20.
J Rural Health ; 37(2): 278-286, 2021 03.
Article in English | MEDLINE | ID: covidwho-1160529

ABSTRACT

PURPOSE: To identify the county-level effects of social determinants of health (SDoH) on COVID-19 (corona virus disease 2019) mortality rates by rural-urban residence and estimate county-level exceedance probabilities for detecting clusters. METHODS: The county-level data on COVID-19 death counts as of October 23, 2020, were obtained from the Johns Hopkins University. SDoH data were collected from the County Health Ranking and Roadmaps, the US Department of Agriculture, and the Bureau of Labor Statistics. Semiparametric negative binomial regressions with expected counts based on standardized mortality rates as offset variables were fitted using integrated Laplace approximation. Bayesian significance was assessed by 95% credible intervals (CrI) of risk ratios (RR). County-level mortality hotspots were identified by exceedance probabilities. FINDINGS: The COVID-19 mortality rates per 100,000 were 65.43 for the urban and 50.78 for the rural counties. Percent of Blacks, HIV, and diabetes rates were significantly associated with higher mortality in rural and urban counties, whereas the unemployment rate (adjusted RR = 1.479, CrI = 1.171, 1.867) and residential segregation (adjusted RR = 1.034, CrI = 1.019, 1.050) were associated with increased mortality in urban counties. Counties with a higher percentage of college or associate degrees had lower COVID-19 mortality rates. CONCLUSIONS: SDoH plays an important role in explaining differential COVID-19 mortality rates and should be considered for resource allocations and policy decisions on operational needs for businesses and schools at county levels.


Subject(s)
COVID-19/mortality , Rural Population/statistics & numerical data , Social Determinants of Health , Urban Population/statistics & numerical data , Black People/statistics & numerical data , Diabetes Mellitus/epidemiology , Female , HIV Infections/epidemiology , Humans , Male , Social Segregation , Unemployment/statistics & numerical data , United States/epidemiology
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