Temperature-mortality association during and before the COVID-19 pandemic in Italy: A nationwide time-stratified case-crossover study.
TL;DR: In this article, the authors investigated the relationship of temperature with all-cause and non-COVID-19 mortality in the pandemic year 2020 compared to its counterpart period in 2015-2019 in Italy.
Abstract: Objectives To identify the associations of temperature with non-COVID-19 mortality and all-cause mortality in the pandemic 2020 in comparison with the non-COVID-19 period in Italy. Methods The data on 3,189,790 all-cause deaths (including 3,134,137 non-COVID-19 deaths) and meteorological conditions in 107 Italian provinces between February 1st and November 30th in each year of 2015–2020 were collected. We employed a time-stratified case-crossover study design combined with the distributed lag non-linear model to investigate the relationships of temperature with all-cause and non-COVID-19 mortality in the pandemic and non-pandemic periods. Results Cold temperature exposure contributed higher risks for both all-cause and non-COVID-19 mortality in the pandemic period in 2020 than in 2015–2019. However, no different change was found for the impacts of heat. The relative risk (RR) of non-COVID-19 deaths and all-cause mortality at extremely cold (2 °C) in comparison with the estimated minimum mortality temperature (19 °C) in 2020 were 1.63 (95% CI: 1.55–1.72) and 1.45 (95%CI: 1.31–1.61) respectively, which were higher than all-cause mortality risk in 2015–2019 with RR of 1.19 (95%CI: 1.17–1.21). Conclusion Cold exposure indicated stronger impacts than high temperatures on all-cause and non-COVID-19 mortality in the pandemic year 2020 compared to its counterpart period in 2015–2019 in Italy.
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TL;DR: In this article , the effects brought by climate change and the pandemic upon worker health and wellbeing are varied and necessitate the identification and implementation of improved strategic interventions, such as identifying and implementing improved strategic intervention.
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TL;DR: In this paper , a two-stage time-series framework was applied to estimate the association between daily maximum eight-hour average ozone and mortality as well as economic loss in Italy.
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TL;DR: In this article , the authors proposed a new method to decompose temperature variability into interday TV and intraday TV through algebra derivation and performed an illustrative analysis using data on daily mortality and temperature in France in 2019-2021.
Abstract: Temperature variability (TV) is associated with increased mortality risks. However, the independent impacts of interday and intraday are still unknown.We proposed a new method to decompose TV into interday TV and intraday TV through algebra derivation. Intraday TV was defined as the weighted average standard deviation (SD) of minimum temperature and maximum temperature on each day. Interday TV was defined as the weighted SD of daily mean temperatures during the exposure period. We then performed an illustrative analysis using data on daily mortality and temperature in France in 2019-2021.The novel interday and intraday TV indices were good proxies for existing indicators, inlcluding diurnal temperature range (DTR) and temperature change between neighbouring days (TCN). In the illustrative analyses, interday and intraday TVs showed differentiated mortality risks. Mortality burden related to TV was mainly explained by the intraday component, accounting for an attributable fraction (AF) of 1.81% (95% CI: 0.64%, 2.97%) of total mortality, more than twice the AF of interday TV (0.86%, 95% CI: 0.47%, 1.24%).This study proposed a novel method for identifying and isolating the different components of temperature variability and offered a comprehensive way to investigate their health impacts.
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TL;DR: The Covid-19 pandemic and the public health response to it will undoubtedly contribute to widespread emotional distress and increased risk of mental health problems.
Abstract: Mental Health and the Covid-19 Pandemic Many aspects of the Covid-19 pandemic and the public health response to it will undoubtedly contribute to widespread emotional distress and increased risk fo...
2,970 citations
TL;DR: Analysis of the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Italy might help political leaders and health authorities to allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks.
2,470 citations
TL;DR: Allocating Scarce Medical Resources for Covid-19 The Covd-19 pandemic has already stressed health care systems throughout the world, requiring rationing of medical equipment and care.
Abstract: Allocating Scarce Medical Resources for Covid-19 The Covid-19 pandemic has already stressed health care systems throughout the world, requiring rationing of medical equipment and care. The authors ...
2,286 citations
TL;DR: In this paper, the effects of physical distancing measures on the progression of the COVID-19 epidemic in Wuhan, China were investigated using synthetic location-specific contact patterns.
Abstract: BACKGROUND: In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world. METHODS: To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April). FINDINGS: Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66-97) and 24% (13-90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic. INTERPRETATION: Restrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R0 and the duration of infectiousness. FUNDING: Bill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.
1,775 citations
University of London1, University of Queensland2, Nagasaki University3, RMIT University4, Harvard University5, Spanish National Research Council6, Queensland University of Technology7, Umeå University8, Yale University9, National Taiwan University10, Fudan University11, Seoul National University12, University of São Paulo13, University of Tsukuba14
TL;DR: Most of the temperature-related mortality burden was attributable to the contribution of cold, and the effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather.
1,569 citations