Internal migration networks and mortality in home communities: Evidence from Italy during the Covid-19 pandemic.
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ABSTRACT:
SUBMITTER: Valsecchi M
PROVIDER: S-EPMC8475185 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundObservational studies have suggested that the risks of non-communicable diseases in voluntary migrants become similar to those in the host population after one or more generations, supporting the hypothesis that these diseases have a predominantly environmental (rather than inherited) origin. However, no study has been conducted thus far to identify alterations at the molecular level that might mediate these changes in disease risk after migration.MethodsUsing genome-wide DNA methylation profiles from more than 1000 Italian participants, we conducted an epigenome-wide association study (EWAS) to identify differences between south-to-north migrants and their origin (southern natives) and host (north-western natives) populations.ResultsWe identified several differentially methylated CpG loci, in particular when comparing south-to-north migrants with north-western natives. We hypothesise that these alterations may underlie an adaptive response to exposure differentials that exist between origin and host populations.ConclusionsOur study is the first large agnostic investigation of DNA methylation changes linked to migratory processes, and shows the potential of EWAS to investigate their biological effects.
| S-EPMC4588856 | biostudies-literature
Project description:Estimates of the real death toll of the COVID-19 pandemic have proven to be problematic in many countries, Italy being no exception. Mortality estimates at the local level are even more uncertain as they require stringent conditions, such as granularity and accuracy of the data at hand, which are rarely met. The "official" approach adopted by public institutions to estimate the "excess mortality" during the pandemic draws on a comparison between observed all-cause mortality data for 2020 and averages of mortality figures in the past years for the same period. In this paper, we apply the recently developed machine learning control method to build a more realistic counterfactual scenario of mortality in the absence of COVID-19. We demonstrate that supervised machine learning techniques outperform the official method by substantially improving the prediction accuracy of the local mortality in "ordinary" years, especially in small- and medium-sized municipalities. We then apply the best-performing algorithms to derive estimates of local excess mortality for the period between February and September 2020. Such estimates allow us to provide insights about the demographic evolution of the first wave of the pandemic throughout the country. To help improve diagnostic and monitoring efforts, our dataset is freely available to the research community.Supplementary informationThe online version contains supplementary material available at 10.1007/s00148-021-00857-y.
| S-EPMC8214048 | biostudies-literature
Project description:This study examines the productivity of working from home (WFH) practices during the COVID-19 pandemic. The results reveal that the mean WFH productivity relative to working at the usual workplace was about 60%-70%, and it was lower for employees and firms that started WFH practice only after the spread of the COVID-19 pandemic. However, there was a large dispersion of WFH productivity, both by individual and firm characteristics. Highly educated and high-wage employees tended to exhibit a small reduction in WFH productivity. The results obtained from the employee and employer surveys were generally consistent with each other.
| S-EPMC9011721 | biostudies-literature
Project description:Since the beginning of the COVID-19 pandemic, data have been accumulated to examine excess mortality in the first half of 2020. Mortality in the preceding year or years is used to calculate the expected number of deaths, which is then compared with the actual number of deaths in 2020. We calculated weekly age- and sex-specific mortality rates for 93.1% of the Italian municipalities for the years 2015-2019 and for the first 26 weeks in 2020. We assumed the mortality experience during 2015-2019 as the reference period to calculate standardised mortality ratios. Furthermore, in order to compare the mortality experience of males and females, we calculated sex- and age- specific weekly direct standardised mortality rates and differences between the observed and expected number of deaths. We observed considerable changes in the demographics in the Italian population between the years 2015 and 2020, particularly among people 60 years and older and among males. The population is aging and the proportion of elderly males has increased, which was not reflected adequately in previous estimates of excess mortality. Standardized excess mortality results show that in Italy between the 8th and 26th weeks in 2020, there were 33,035 excess deaths, which is only 643 fewer deaths than the official COVID-19 death toll for this time period. A comparative increase in the mortality rates was observed in March among both sexes, but particularly for males. Comparisons with recently published data show considerably higher excess deaths, but these data were either not covering the complete country or did not account for age and sex. Neglecting the demographic changes in a region, even over a short time span, can result in biased estimates.
| S-EPMC7832414 | biostudies-literature
Project description:In this study we present the first comprehensive analysis of the spatio-temporal differences in excess mortality during the COVID-19 pandemic in Italy. We used a population-based design on all-cause mortality data, for the 7,904 Italian municipalities. We estimated sex-specific weekly mortality rates for each municipality, based on the first four months of 2016-2019, while adjusting for age, localised temporal trends and the effect of temperature. Then, we predicted all-cause weekly deaths and mortality rates at municipality level for the same period in 2020, based on the modelled spatio-temporal trends. Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed one week lag, with higher mortality from the beginning of March and 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. We observed marked geographical differences also at municipality level. For males, the city of Bergamo (Lombardia) showed the largest percent excess, 88.9% (81.9% to 95.2%), at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for males in the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. We provided a fully probabilistic analysis of excess mortality during the COVID-19 pandemic at sub-national level, suggesting a differential direct and indirect effect in space and time. Our model can be used to help policy-makers target measures locally to contain the burden on the health-care system as well as reducing social and economic consequences. Additionally, this framework can be used for real-time mortality surveillance, continuous monitoring of local temporal trends and to flag where and when mortality rates deviate from the expected range, which might suggest a second wave of the pandemic.
| S-EPMC7546500 | biostudies-literature
Project description:This paper explores the relationship between the spatial distribution of excess deaths and the presence of care home facilities during the first wave of the COVID-19 outbreak in Italy. Using registry-based mortality data for Lombardy, one of the areas most severely hit by the pandemic we show that the presence of a care home in a municipality is associated with significantly higher excess death rates in the population. This effect appears to be driven by excess mortality in the elderly population of 70 years old and older. Our results are robust to controlling for the number of residents in each care home, suggesting that the presence of such facilities may have acted as one of factors contributing to the diffusion of COVID-19 at the local level.
| S-EPMC8250368 | biostudies-literature
Project description:ObjectivesIt is important to quantify the true burden of coronavirus disease 2019 (COVID-19) in different countries, to enable informed decisions about imposing and relaxing control measures. COVID-19 surveillance data fails in this respect, as it is influenced by different definitions, control policies and capacities. This article aims to quantify excess mortality and estimate the distribution between COVID-19 and non-COVID-19 causes of death.Study designObservational study and mathematical modelling.MethodsPublicly available data from multiple institutional sources were used and an in-depth analysis was carried out of deaths from all causes between 2015 and 2020 in Italy at the national, regional and local level. Excess mortality over time and space was first explored, followed by an assessment of how this related to COVID-19 surveillance and, ultimately, assuming a fixed male:female ratio, a model was developed and applied to estimate the proportions of COVID-19 and non-COVID-19 excess mortality in 2020.ResultsIn Italy, the mortality rate doubled in March and April 2020 compared with data from 2015 to 2019 (+109%, when considering municipalites with >10.000 inhabitants), with excess mortality reaching >600% in large municipalities in northern areas. Notified COVID-19 deaths accounted for only 43.5% (regional range: 43-62%) of excess mortality. It is estimated that more than two-thirds of excess deaths that were not captured by surveillance are non-COVID-19 deaths, which could be a result of the excess burden on the health systems, in addition to reduced demand and supply of other non-COVID healthcare services.ConclusionsThe impact of COVID-19 during the early stages of the pandemic is much larger than official figures have reported. Monitoring excess mortality helps to capture the full effect of the COVID-19 pandemic, which differs between regions in Italy and which might have resulted in significant indirect effects on the well-being of the population. In addition, the COVID-19 pandemic has also resulted in significant indirect effects on the well-being of the population.
| S-EPMC7703200 | biostudies-literature
Project description:Background and aimPatients with interstitial lung diseases, including asbestosis, showed high susceptibility to the SARS-CoV-2 virus and a high risk of severe COVID-19 symptoms. Italy, highly impacted by asbestos-related diseases, in 2020 was among the European countries with the highest number of COVID-19 cases. The mortality related to malignant mesotheliomas and asbestosis in 2020 and its relationship with COVID-19 in Italy are investigated.MethodsAll death certificates involving malignant mesotheliomas or asbestosis in 2010-2020 and those involving COVID-19 in 2020 were retrieved from the National Registry of Causes of Death. Annual mortality rates and rate ratios (RRs) of 2020 and 2010-2014 compared to 2015-2019 were calculated. The association between malignant pleural mesothelioma (MPM) and asbestosis with COVID-19 in deceased adults ≥80 years old was evaluated through a logistic regression analysis (odds ratios: ORs), using MPM and asbestosis deaths COVID-19-free as the reference group. The hospitalization for asbestosis in 2010-2020, based on National Hospital Discharge Database, was analyzed.ResultsIn 2020, 746,343 people died; out of them, 1,348 involved MPM and 286 involved asbestosis. Compared to the period 2015-2019, the mortality involving the two diseases decreased in age groups below 80 years; meanwhile, an increasing trend was observed in subjects aged 80 years and older, with a relative mortality risks of 1.10 for MPM and 1.17 for asbestosis. In subjects aged ≥80 years, deaths with COVID-19 were less likely to have MPM in both genders (men: OR = 0.22; women: OR = 0.44), while no departure was observed for asbestosis. A decrease in hospitalization in 2020 with respect to those in 2010-2019 in all age groups, both considering asbestosis as the primary or secondary diagnosis, was observed.ConclusionsThe increasing mortality involving asbestosis and, even if of slight entity, MPM, observed in people aged over 80 years during the 1st year of the COVID-19 pandemic, aligned in part with the previous temporal trend, could be due to several factors. Although no positive association with COVID-19 mortality was observed, the decrease in hospitalizations for asbestosis among individuals aged over 80 years, coupled with the increase in deaths, highlights the importance of enhancing home-based assistance during the pandemic periods for vulnerable patients with asbestos-related conditions.
| S-EPMC10824953 | biostudies-literature
Project description:The Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as Covid-19-related has increased compared to what would have been expected in the absence of the pandemic. Reasons behind this might include Covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown. I used weekly ONS data on the number of deaths in England and Wales that did not officially involve Covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a difference-in-differences econometric approach to study whether there was a relative increase in deaths not registered as Covid-19-related during the pandemic, compared to a control. Results suggest that there were an additional 968 weekly deaths that officially did not involve Covid-19, compared to what would have otherwise been expected. It is possible that some people are dying from Covid-19 without being diagnosed, and/or that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.
| S-EPMC7836531 | biostudies-literature
Project description:Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in US nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, WA, to other skilled nursing facilities. The full extent of staff connections between nursing homes-and the role these connections serve in spreading a highly contagious respiratory infection-is currently unknown given the lack of centralized data on cross-facility employment. We perform a large-scale analysis of nursing home connections via shared staff and contractors using device-level geolocation data from 50 million smartphones, and find that 5.1% of smartphone users who visited a nursing home for at least 1 h also visited another facility during our 11-wk study period-even after visitor restrictions were imposed. We construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7.1 other facilities. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Controlling for demographic and other factors, a home's staff network connections and its centrality within the greater network strongly predict COVID-19 cases.
| S-EPMC7817179 | biostudies-literature