Immigrants facing Covid 19 containment in France : An ordinary hardship of disaffiliation.
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ABSTRACT:
SUBMITTER: Carillon S
PROVIDER: S-EPMC8351997 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundImmigrants and ethnic/racialized minorities have been identified as being at higher risk of coronavirus disease-19 (COVID-19) infection, but few studies report on their exposures and prevention behaviours. This study aims to examine the social distribution of COVID-19 exposure (overcrowding, working outside the home, use of public transport to go to work) and prevention behaviours (use of face masks, washing hands, respect for physical distance) in France during the first wave of the epidemic.MethodsWe used the EpiCov population-based survey from a random sample of individuals aged 15 years or more. We determined the distribution of the self-reported outcomes according to migratory status and sex, using χ2 tests. We modelled the probability of outcomes with logistic regression. Finally, we focused the analysis on the Greater Paris area and accounted for neighbourhood characteristics.ResultsA total of 111 824 participants were included in the study. Overall, immigrant groups from non-European countries were more exposed to COVID-19-related factors and more respectful of prevention measures. The probability of overcrowding and the use of public transport was higher for immigrants from sub-Saharan Africa [adjusted odds ratio (aOR) = 3.71 (3.19; 4.32), aOR = 6.36 (4.86; 8.32)] than for the majority population. Immigrant groups were less likely to have a non-systematic use of face masks and to breach physical distancing than the majority population [for immigrants from sub-Saharan Africa, aOR = 0.32 (0.28; 0.37) and aOR = 0.71 (0.61; 0.81), respectively]. Living in a neighbourhood with a higher share of immigrants was associated with higher exposure and better prevention behaviours.ConclusionsIn France, immigrants had a higher exposure to COVID-19-related factors and more systematic prevention behaviours.
| S-EPMC9341671 | biostudies-literature
Project description:Countries worldwide have confirmed a staggering number of COVID-19 cases, and it is now clear that no country is immune to the SARS-CoV-2 infection. Resource-poor countries with weaker health systems are struggling with epidemics of their own and are now in a more uncertain situation with this rapidly spreading infection. Frontline healthcare workers are succumbing to the infection in their efforts to save lives. There is an urgency to develop treatments for COVID-19, yet there is limited clinical data on the efficacy of potential drug treatments. Countries worldwide implemented a stay-at-home order to "flatten the curve" and relieve the pressure on the health system, but it is uncertain how this will unfold after the economy reopens. Trehalose, a natural glucose disaccharide, is known to impair viral function through the autophagy system. Here, we propose trehalose as a potential preventative treatment for SARS-CoV-2 infection and transmission.
| S-EPMC7358456 | biostudies-literature
Project description:The COVID-19 economic crash is idiosyncratic because of its virtual standstill of economic activity. We therefore ask how individual labor market experiences are related to the development of mental health complaints in the spring of 2020. As clinical data collection was compromised during the lockdowns, standardized surveys of the European labor force provide an opportunity to observe mental health complaints as the crisis unfolded. Data are representative of active members of the labor force of six European nations that contained varying levels of COVID-19 burdens in terms of mortality and lockdown measures. We document a steep occupational prestige level gradient on the probability of facing economic hardship during the lockdowns-looming job loss, income loss, and workload decline-which evidently exacerbate socioeconomic inequalities. Analyses indicate a striking positive relationship between instantaneous economic hardships during the COVID-19 lockdown and expressing feelings of depression and health anxiety. Importantly, the magnitude of the association between such hardships and indicators of mental health deterioration is highly dependent on workers' occupational standing, revealing a second layer of exacerbating inequality.
| S-EPMC7959574 | biostudies-literature
Project description:This study examines the prevalence of several types of hardship (e.g., bill paying and housing hardships) among immigrants by race and ethnicity in the United States using data from the 2008 and 2014 panels of the Survey of Income and Program Participation and logistic regressions. I find that Blacks, and to some extent Hispanics, are more likely to report hardships than Whites and Asians, who are about equally likely to report hardships. Exploring results by nativity and citizenship status, I find that immigrants who became U.S. citizens are less likely than the native-born population to report some kinds of hardship. Undocumented immigrants, however, are more likely to report some kinds of hardships, particularly in the 2008 panel conducted at the time of the Great Recession, which hit immigrants especially hard; this relationship, however, is explained by the lower incomes of undocumented immigrant households in the 2008 panel. Results within racial and ethnic groups are generally in the same direction but are less frequently statistically significant. Overall, these findings suggest that immigrants are not particularly prone to hardship, especially when other characteristics are controlled for. In fact, the lower likelihood of some hardships among foreign-born citizens suggests that they are positively selected: they may have unobserved characteristics that are protective, such as better health, stronger social networks, or money management skills. Because the foreign-born are less likely to be disadvantaged vis-à-vis the native-born when hardship rather than the official income poverty measure is used, this study highlights the importance of using multiple measures when assessing the well-being of immigrants.
| S-EPMC8932239 | biostudies-literature
Project description:The devastating trail of Covid-19 is characterized by one of the highest mortality-to-infected ratio for a pandemic. Restricted therapeutic and early-stage vaccination still renders social exclusion through lockdown as the key containment mode.To understand the dynamics, we propose PHIRVD, a mechanistic infection propagation model that Machine Learns (Bayesian Markov Chain Monte Carlo) the evolution of six infection stages, namely healthy susceptible (H), predisposed comorbid susceptible (P), infected (I), recovered (R), herd immunized (V) and mortality (D), providing a highly reliable mortality prediction profile for 18 countries at varying stages of lockdown. Training data between 10 February to 29 June 2020, PHIRVD can accurately predict mortality profile up to November 2020, including the second wave kinetics. The model also suggests mortality-to-infection ratio as a more dynamic pandemic descriptor, substituting reproduction number. PHIRVD establishes the importance of early and prolonged but strategic lockdown to contain future relapse, complementing futuristic vaccine impact.
| S-EPMC8173017 | biostudies-literature
Project description:I compare the extent of food hardships in the United States among adults and seniors before and during the COVID-19 pandemic. Food insufficiency increased threefold compared to 2019, and more than doubled relative to the Great Recession. Food insufficiency among seniors increased 75% during the COVID period, but more than doubled when including reduced intake of food varieties. Receipt of charitable foods among disadvantaged adults spiked 50% in the COVID period, but the initial response among seniors was a sharp reduction, before rising. These patterns are consistent with strong social distancing measures enacted in response to the pandemic.
| S-EPMC7537182 | biostudies-literature
Project description:BackgroundWe hypothesize that comprehensive surveillance of COVID-19 in Singapore has facilitated early case detection and prompt contact tracing and, with community-based measures, contained spread. We assessed the effectiveness of containment measures by estimating transmissibility (effective reproduction number, (Equation is included in full-text article.)) over the course of the outbreak.MethodsWe used a Bayesian data augmentation framework to allocate infectors to infectees with no known infectors and determine serial interval distribution parameters via Markov chain Monte Carlo sampling. We fitted a smoothing spline to the number of secondary cases generated by each infector by respective onset dates to estimate (Equation is included in full-text article.)and evaluated increase in mean number of secondary cases per individual for each day's delay in starting isolation or quarantine.ResultsAs of April 1, 2020, 1000 COVID-19 cases were reported in Singapore. We estimated a mean serial interval of 4.6 days [95% credible interval (CI) = 4.2, 5.1] with a SD of 3.5 days (95% CI = 3.1, 4.0). The posterior mean (Equation is included in full-text article.)was below one for most of the time, peaking at 1.1 (95% CI = 1.0, 1.3) on week 9 of 2020 due to a spreading event in one of the clusters. Eight hundred twenty-seven (82.7%) of cases infected less than one person on average. Over an interval of 7 days, the incremental mean number of cases generated per individual for each day's delay in starting isolation or quarantine was 0.03 cases (95% CI = 0.02, 0.05).ConclusionsWe estimate that robust surveillance, active case detection, prompt contact tracing, and quarantine of close contacts kept (Equation is included in full-text article.)below one.
| S-EPMC7707159 | biostudies-literature
Project description:ImportanceLittle is known about the association of severe COVID-19 and post-COVID-19 conditions with household finances.ObjectiveTo examine associations between COVID-19 outcomes, pandemic-related economic hardship, and prepandemic socioeconomic status among families in the US.Design, setting, and participantsThis cohort study used data from the Panel Study of Income Dynamics (PSID), a nationally representative, longitudinal study. Data included 6932 families active in the PSID in both 2019 and 2021.ExposuresOrdinal exposure categories were defined based on whether the reference person or spouse or partner reported a positive COVID-19 diagnosis and (1) persistent COVID-19 symptoms, (2) previous severe COVID-19, or (3) previous moderate, mild, or asymptomatic COVID-19. Families with no history of COVID-19 served as the reference group.Main outcomes and measuresOutcomes included whether a resident family member was laid off or furloughed, lost earnings, or had any financial difficulties due to the COVID-19 pandemic.ResultsIn this cohort study of 6932 families (772 Hispanic families [weighted, 13.5%; 95% CI, 12.4%-14.6%], 2725 non-Hispanic Black families [weighted, 13.1%; 95% CI, 12.3%-14.1%], and 3242 non-Hispanic White families [weighted, 66.8%; 95% CI, 65.2%-68.3%]), close to 1 in 4 (2222 [weighted, 27.0%; 95% CI, 25.6%-28.6%]) reported income below 200% of the US Census Bureau poverty threshold. In survey-weighted regression models adjusted for prepandemic sociodemographic characteristics and experiences of economic hardship, the odds of reporting pandemic-related economic hardship were 2.0 to 3.7 times higher among families headed by an adult with persistent COVID-19 symptoms (laid off or furloughed: adjusted odds ratio [AOR], 1.98 [95% CI, 1.37-2.85]; lost earnings: AOR, 2.86 [95% CI, 2.06-3.97]; financial difficulties: AOR, 3.72 [95% CI, 2.62-5.27]) and 1.7 to 2.0 times higher among families headed by an adult with previous severe COVID-19 (laid off or furloughed: AOR, 1.69 [95% CI, 1.13-2.53]; lost earnings: AOR, 1.99 [95% CI, 1.37-2.90]; financial difficulties: AOR, 1.87 [95% CI, 1.25-2.80]) compared with families with no history of COVID-19. Families headed by an adult with persistent COVID-19 symptoms had increased odds of reporting financial difficulties due to the pandemic regardless of prepandemic socioeconomic status (families with lower income: AOR, 3.71 [95% CI, 1.94-7.10]; families with higher income: AOR, 3.74 [95% CI, 2.48-5.63]). Previous severe COVID-19 was significantly associated with financial difficulties among families with lower income (AOR, 2.59 [95% CI, 1.26-5.31]) but was not significantly associated with financial difficulties among those with high income (OR, 1.56 [95% CI, 0.95-2.56]).Conclusions and relevanceThis cohort study suggests that persistent COVID-19 symptoms and, to a lesser extent, previous severe COVID-19 were associated with increased odds of pandemic-related economic hardship in a cohort of US families. The economic consequences of COVID-19 varied according to socioeconomic status; families with lower income before the pandemic were more vulnerable to employment disruptions and earnings losses associated with an adult family member's COVID-19 illness.
| S-EPMC10716716 | biostudies-literature
Project description:Responses to the COVID-19 outbreak resulted in one of the largest short-term decreases in anthropogenic emissions in modern history. To date, there has been no comprehensive assessment of the impact of lockdowns on air quality and human health. Using global satellite observations and ground measurements from 36 countries in Europe, North America, and East Asia, we find that lockdowns led to reductions in NO2 concentrations globally, resulting in ~32,000 avoided premature mortalities, including ~21,000 in China. However, we do not find corresponding reductions in PM2.5 and ozone globally. Using satellite measurements, we show that the disconnect between NO2 and ozone changes stems from local chemical regimes. The COVID-related lockdowns demonstrate the need for targeted air quality policies to reduce the global burden of air pollution, especially related to secondary pollutants.
| S-EPMC8139585 | biostudies-literature
Project description:Across three experiments (N = 1565), we investigated how forecasts about the spread of COVID 19 are impacted by data trends, and whether patterns of misestimation predict adherence to social-distancing guidelines. We also investigated how mode of data presentation influences forecasting of future cases by showing participants data on the number of COVID-19 cases from a 5-week period in either graphical, tabular, or text-only form. We consistently found that people shown tables produced more accurate forecasts compared to people shown line-graphs of the same data; yet people shown line-graphs were more confident in their estimates. These findings suggest that graphs engender false-confidence in the accuracy of forecasts, that people's forecasts of future cases have important implications for their attitudes concerning social distancing, and that tables may be better than graphs for informing the public about the trajectory of COVID-19.
| S-EPMC8960688 | biostudies-literature