The disproportionate excess mortality risk of COVID-19 in younger people with diabetes warrants vaccination prioritisation.
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ABSTRACT:
SUBMITTER: McGovern AP
PROVIDER: S-EPMC7885981 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Latino people in the US are experiencing higher excess deaths during the COVID-19 pandemic than any other racial/ethnic group, but it is unclear which sociodemographic subgroups within this diverse population are most affected. Such information is necessary to target policies that prevent further excess mortality and reduce inequities. Using death certificate data for January 1, 2016 through February 29, 2020 and time-series models, we estimated the expected weekly deaths among Latino people in California from March 1 through October 3, 2020. We quantified excess mortality as observed minus expected deaths and risk ratios (RR) as the ratio of observed to expected deaths. We considered subgroups categorized by age, sex, nativity, country of birth, educational attainment, occupation, and combinations of these factors. Our results indicate that during the first seven months of the pandemic, Latino deaths in California exceeded expected deaths by 10,316, a 31% increase. Excess death rates were greatest for individuals born in Mexico (RR 1.44; 95% PI, 1.41, 1.48) or a Central American country (RR 1.49; 95% PI, 1.37, 1.64), with less than a high school degree (RR 1.41; 95% PI, 1.35, 1.46), or in food-and-agriculture (RR 1.60; 95% PI, 1.48, 1.74) or manufacturing occupations (RR 1.59; 95% PI, 1.50, 1.69). Immigrant disadvantages in excess death were magnified among working-age Latinos in essential occupations. In sum, the COVID-19 pandemic has disproportionately impacted mortality among Latino immigrants, especially those in unprotected essential jobs. Interventions to reduce these inequities should include targeted vaccination, workplace safety enforcement, and expanded access to medical care and economic support.
| S-EPMC8283318 | biostudies-literature
Project description:PURPOSE:Our aim was to quantify the mortality from COVID-19 and identify any interactions with frailty and other demographic factors. METHODS:Hospitalised patients aged???70 were included, comparing COVID-19 cases with non-COVID-19 controls admitted over the same period. Frailty was prospectively measured and mortality ascertained through linkage with national and local statutory reports. RESULTS:In 217 COVID-19 cases and 160 controls, older age and South Asian ethnicity, though not socioeconomic position, were associated with higher mortality. For frailty, differences in effect size were evident between cases (HR 1.02, 95% CI 0.93-1.12) and controls (HR 1.99, 95% CI 1.46-2.72), with an interaction term (HR 0.51, 95% CI 0.37-0.71) in multivariable models. CONCLUSIONS:Our findings suggest that (1) frailty is not a good discriminator of prognosis in COVID-19 and (2) pathways to mortality may differ in fitter compared with frailer older patients.
| S-EPMC7368630 | biostudies-literature
Project description: Not available
| S-EPMC8239314 | biostudies-literature
Project description:ObjectivesThe first wave of the SARS-CoV-2 pandemic in Germany lasted from week 10 to 23 in 2020. The aim is to provide estimates of excess mortality in Germany during this time.MethodsWe analyzed age-specific numbers of deaths per week from 2016 to week 26 in 2020. We used weekly mean numbers of deaths of 2016-2019 to estimate expected weekly numbers for 2020. We estimated standardized mortality ratios (SMR) and 95% confidence intervals.ResultsDuring the first wave observed numbers of deaths were higher than expected for age groups 60-69, 80-89, and 90+. The age group 70-79 years did not show excess mortality. The net excess number of deaths for weeks 10-23 was +8,071. The overall SMR was 1•03 (95%CI 1•03-1•04). The largest increase occurred among people aged 80-89 and 90+ (SMR=1•08 and SMR=1•09). A sensitivity analysis that accounts for demographic changes revealed an overall SMR of 0•98 (95%CI 0•98-0•99) and a deficit of 4,926 deaths for week 10-23, 2020.ConclusionsThe excess mortality existed for two months. The favorable course of the first wave may be explained by a younger age at infection at the beginning of the pandemic, lower contact rates, and a more efficient pandemic management.
| S-EPMC7501062 | biostudies-literature
Project description:We compare the expected all-cause mortality with the observed one for different age classes during the pandemic in Lombardy, which was the epicenter of the epidemic in Italy. The first case in Italy was found in Lombardy in early 2020, and the first wave was mainly centered in Lombardy. The other three waves, in Autumn 2020, March 2021 and Summer 2021 are also characterized by a high number of cases in absolute terms. A generalized linear mixed model is introduced to model weekly mortality from 2011 to 2019, taking into account seasonal patterns and year-specific trends. Based on the 2019 year-specific conditional best linear unbiased predictions, a significant excess of mortality is estimated in 2020, leading to approximately 35000 more deaths than expected, mainly arising during the first wave. In 2021, instead, the excess mortality is not significantly different from zero, for the 85+ and 15-64 age classes, and significant reductions with respect to the 2020 estimated excess mortality are estimated for other age classes.
| S-EPMC8743436 | biostudies-literature
Project description: Not available
| S-EPMC8032917 | biostudies-literature
Project description:BackgroundWhile morbidity attributable to podoconiosis is relatively well studied, its pattern of mortality has not been established.MethodsWe compared the age-standardised mortality ratios (SMRs) of two datasets from northern Ethiopia: podoconiosis patients enrolled in a 1-y trial and a Health and Demographic Surveillance System cohort.ResultsThe annual crude mortality rate per 1000 population for podoconiosis patients was 28.7 (95% confidence interval [CI] 17.3 to 44.8; n=663) while that of the general population was 2.8 (95% CI 2.3 to 3.4; n=44 095). The overall SMR for the study period was 6.0 (95% CI 3.6 to 9.4).ConclusionsPodoconiosis patients experience elevated mortality compared with the general population and further research is required to understand the reasons.
| S-EPMC7738655 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic has produced vastly disproportionate deaths for communities of color in the United States. Minnesota seemingly stands out as an exception to this national pattern, with white Minnesotans accounting for 80 percent of the population and 82 percent of COVID-19 deaths. The authors examine confirmed COVID-19 mortality alongside deaths indirectly attributable to the pandemic-"excess mortality"-in Minnesota. This analysis reveals profound racial disparities: age-adjusted excess mortality rates for whites are exceeded by a factor of 2.8 to 5.3 for all other racial groups, with the highest rates among Black, Latino, and Native Minnesotans. The seemingly small disparities in COVID-19 deaths in Minnesota reflect the interaction of three factors: the natural history of the disease, whose early toll was heavily concentrated in nursing homes; an exceptionally divergent age distribution in the state; and a greatly different proportion of excess mortality captured in confirmed COVID-19 rates for white Minnesotans compared with most other groups.
| S-EPMC7780067 | biostudies-literature
Project description:Mortality due to massive events like the COVID-19 pandemic is underestimated because of several reasons, among which the impossibility to track all positive cases and the inadequacy of coding systems are presumably the most relevant. Therefore, the most affordable method to estimate COVID-19-related mortality is excess mortality (EM). Very often, though, EM is calculated on large spatial units that may entail different EM patterns and without stratifying deaths by age or sex, while, especially in the case of epidemics, it is important to identify the areas that suffered a higher death toll or that were spared. We developed the Stata COVID19_EM.ado procedure that estimates EM within municipalities in six subgroups defined by sex and age class using official data provided by ISTAT (Italian National Statistics Bureau) on deaths occurred from 2015 to 2020. Using simple linear regression models, we estimated the mortality trend in each age-and-sex subgroup and obtained the expected deaths of 2020 by extrapolating the linear trend. The results are then displayed using choropleth maps. Subsequently, local autocorrelation maps, which allow to appreciate the presence of local clusters of high or low EM, may be obtained using an R procedure that we developed.•We focused on estimating excess mortality in small-scale spatial units (municipalities) and in population strata defined by age and sex.•This method gives a deeper insight on excess mortality than summary figures at regional or national level, enabling to identify the local areas that suffered the most and the high-risk population subgroups within them.•This type of analysis could be replicated on different time frames, which might correspond to successive epidemic waves, as well as to periods in which containment measures were enforced and for different age classes; moreover, it could be applied in every instance of mortality crisis within a region or a country.
| S-EPMC8105045 | biostudies-literature
Project description:Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the expected mortality, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no global, frequently-updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 94 countries and territories, openly available as the regularly-updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in several worst-affected countries (Peru, Ecuador, Bolivia, Mexico) the excess mortality was above 50% of the expected annual mortality. At the same time, in several other countries (Australia, New Zealand) mortality during the pandemic was below the usual level, presumably due to social distancing measures decreasing the non-COVID infectious mortality. Furthermore, we found that while many countries have been reporting the COVID-19 deaths very accurately, some countries have been substantially underreporting their COVID-19 deaths (e.g. Nicaragua, Russia, Uzbekistan), sometimes by two orders of magnitude (Tajikistan). Our results highlight the importance of open and rapid all-cause mortality reporting for pandemic monitoring.
| S-EPMC7852240 | biostudies-literature