Estimating COVID-19 mortality in Italy early in the COVID-19 pandemic

Modi, Chirag; Böhm, Vanessa; Ferraro, Simone; Stein, George; Seljak, Uroš

doi:10.1038/s41467-021-22944-0

Cited by 72 publications

(56 citation statements)

References 11 publications

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“…Excess mortality has already been used to estimate the COVID-19 impact in different countries, both in academic literature (e.g. Kontis et al, 2020 ; Alicandro et al, 2020 ; Ghafari et al, 2021 ; Woolf et al, 2020a ; Woolf et al, 2020b ; Weinberger et al, 2020 ; Blangiardo et al, 2020 ; Kobak, 2021a ; Modi et al, 2021 ; Bradshaw et al, 2021 ; Islam et al, 2021 , among many others) and by major media outlets. It has also been used to compare COVID-19 impact to the impact of major influenza pandemics ( Faust et al, 2020 ; Petersen et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

Karlinsky

Kobak

2021

eLife

484

454

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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.

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Section: Introductionmentioning

confidence: 99%

Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

Karlinsky

Kobak

2021

eLife

484

454

View full text Add to dashboard Cite

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“…Estimates for SARS-CoV-2 are ranging anywhere from of 0.1–25% depending on the age group, the country and the stage of the pandemic, although this number could change substantially as more accurate information on the numbers of infections and deaths becomes available [ 5 , 6 ]. In contrast to SARS and MERS, COVID-19 has rapidly spread worldwide despite the severe restrictions imposed in many countries, and the official number of deaths now exceeds 5.0 million [ 7 ] (which is a well underestimated number as shown by excess mortality studies [ 8 ]).…”

Section: Introductionmentioning

confidence: 99%

Design, synthesis and in vitro evaluation of novel SARS-CoV-2 3CLpro covalent inhibitors

Stille

Tjutrins

Wang

et al. 2022

European Journal of Medicinal Chemistry

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Severe diseases such as the ongoing COVID-19 pandemic, as well as the previous SARS and MERS outbreaks, are the result of coronavirus infections and have demonstrated the urgent need for antiviral drugs to combat these deadly viruses. Due to its essential role in viral replication and function, 3CL pro (main coronaviruses cysteine-protease) has been identified as a promising target for the development of antiviral drugs. Previously reported SARS-CoV 3CL pro non-covalent inhibitors were used as a starting point for the development of covalent inhibitors of SARS-CoV-2 3CL pro . We report herein our efforts in the design and synthesis of submicromolar covalent inhibitors when the enzymatic activity of the viral protease was used as a screening platform.

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“…COVID-19 mortality varies across countries ranging 1.4–4.3%, but the number of deaths due to COVID-19 is higher than that due to other respiratory viral infections, such as seasonal influenza. 2 3 4 5 The individualized prediction of COVID-19-related mortality is important for prioritizing patients with a high risk of mortality in terms of the allocation of limited medical resources.…”

Section: Introductionmentioning

confidence: 99%

Prediction of COVID-19-related Mortality and 30-Day and 60-Day Survival Probabilities Using a Nomogram

et al. 2021

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Background Prediction of mortality in patients with coronavirus disease 2019 (COVID-19) is a key to improving the clinical outcomes, considering that the COVID-19 pandemic has led to the collapse of healthcare systems in many regions worldwide. This study aimed to identify the factors associated with COVID-19 mortality and to develop a nomogram for predicting mortality using clinical parameters and underlying diseases. Methods This study was performed in 5,626 patients with confirmed COVID-19 between February 1 and April 30, 2020 in South Korea. A Cox proportional hazards model and logistic regression model were used to construct a nomogram for predicting 30-day and 60-day survival probabilities and overall mortality, respectively in the train set. Calibration and discrimination were performed to validate the nomograms in the test set. Results Age ≥ 70 years, male, presence of fever and dyspnea at the time of COVID-19 diagnosis, and diabetes mellitus, cancer, or dementia as underling diseases were significantly related to 30-day and 60-day survival and mortality in COVID-19 patients. The nomogram showed good calibration for survival probabilities and mortality. In the train set, the areas under the curve (AUCs) for 30-day and 60-day survival was 0.914 and 0.954, respectively; the AUC for mortality of 0.959. In the test set, AUCs for 30-day and 60-day survival was 0.876 and 0.660, respectively, and that for mortality was 0.926. The online calculators can be found at https://koreastat.shinyapps.io/RiskofCOVID19/ . Conclusion The prediction model could accurately predict COVID-19-related mortality; thus, it would be helpful for identifying the risk of mortality and establishing medical policies during the pandemic to improve the clinical outcomes.

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Estimating COVID-19 mortality in Italy early in the COVID-19 pandemic

Cited by 72 publications

References 11 publications

Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

Design, synthesis and in vitro evaluation of novel SARS-CoV-2 3CLpro covalent inhibitors

Prediction of COVID-19-related Mortality and 30-Day and 60-Day Survival Probabilities Using a Nomogram

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