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      Influence of population density, temperature, and absolute humidity on spread and decay durations of COVID-19: A comparative study of scenarios in China, England, Germany, and Japan

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          Abstract

          In this study, we analyzed the spread and decay durations of the COVID-19 pandemic in several cities of China, England, Germany, and Japan, where the first wave has undergone decay. Differences in medical and health insurance systems, as well as in regional policies incommoded the comparison of the spread and decay in different cities and countries. The spread and decay durations in the cities of the four studied countries were reordered and calculated based on an asymmetric bell-shaped model. We acquired the values of the ambient temperature, absolute humidity, and population density to perform multivariable analysis. We found a significant correlation ( p < 0.05) of the spread and decay durations with population density in the four analyzed countries. Specifically, spread duration showed a high correlation with population density and absolute humidity ( p < 0.05), whereas decay duration demonstrated the highest correlation with population density, absolute humidity, and maximum temperature ( p < 0.05). The effect of population density was almost nonexistent in China because of the implemented strict lockdown. Our findings will be useful in policy setting and governmental actions in the next pandemic, as well as in the next waves of COVID-19.

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          Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

          Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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            Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

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              Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy

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                Author and article information

                Contributors
                Journal
                One Health
                One Health
                One Health
                Elsevier
                2352-7714
                11 December 2020
                June 2021
                11 December 2020
                : 12
                : 100203
                Affiliations
                [a ]Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan
                [b ]Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Nagoya 466-8555, Japan
                [c ]Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt
                Author notes
                [* ]Corresponding author at: Center of Biomedical Physics and Information Technology, Nagoya Institute of Technology, Gokiso-cho, Showaku, Nagoya 466-8555, Japan. ahirata@ 123456nitech.ac.jp
                Article
                S2352-7714(20)30304-9 100203
                10.1016/j.onehlt.2020.100203
                7736723
                33344745
                20d6c75a-5091-42a0-b2c0-3b8d2cd5ab53
                © 2020 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 23 September 2020
                : 4 December 2020
                : 7 December 2020
                Categories
                Research Paper

                covid-19,temperature,absolute humidity,population density,multivariable analysis

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