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      Changes in Physical Activity and Sedentary Behavior Amid Confinement: The BKSQ-COVID-19 Project


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          Coronavirus disease 19 (COVID-19) has compelled implementing confinement measure across the globe. These measures can potentially lead to many changes in lifestyle. However, no studies examined the effect of COVID-19-induced confinement on physical activity (PA) and sedentary behavior (SB).


          During April and May of 2020, the current study surveyed changes in PA and SB induced by COVID-19 confinement.


          The participants of the study were 1844. Among the participants who were regularly involved in PA, the majority (41.8–42.2%) of the participants reported a “decrease” ( p<0.05) in walking, jogging, and sports while the majority (46.3–53.1%) reported a “no change” ( p<0.05) in swimming, cycling, and weight lifting. With regard to the SB, most of the participants reported an “increase” in watching TV (72.3%), using electronics (82.7%), and logging to social media (81.9%). Additionally, gender, job type, obesity, and being worried to contract the disease were associated ( p<0.05) with changes in PA. On the other hand, age, gender, obesity, job type and income were related ( p<0.05) to changes in SB.


          Results of the current study might enhance knowledge about the impact of COVID-19 on lifestyle, particularly PA and SB. Subsequently, it can also be used to establish strategies to enhance engagement in activities during the current and future pandemics.

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          Most cited references42

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          The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak

          Coronavirus disease (COVID-19) is caused by SARS-COV2 and represents the causative agent of a potentially fatal disease that is of great global public health concern. Based on the large number of infected people that were exposed to the wet animal market in Wuhan City, China, it is suggested that this is likely the zoonotic origin of COVID-19. Person-to-person transmission of COVID-19 infection led to the isolation of patients that were subsequently administered a variety of treatments. Extensive measures to reduce person-to-person transmission of COVID-19 have been implemented to control the current outbreak. Special attention and efforts to protect or reduce transmission should be applied in susceptible populations including children, health care providers, and elderly people. In this review, we highlights the symptoms, epidemiology, transmission, pathogenesis, phylogenetic analysis and future directions to control the spread of this fatal disease.
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            Presumed Asymptomatic Carrier Transmission of COVID-19

            This study describes possible transmission of novel coronavirus disease 2019 (COVID-19) from an asymptomatic Wuhan resident to 5 family members in Anyang, a Chinese city in the neighboring province of Hubei.
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              Estimates of the severity of coronavirus disease 2019: a model-based analysis

              Summary Background In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. Methods We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. Findings Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9–19·2) and to hospital discharge to be 24·7 days (22·9–28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56–3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23–1·53), with substantially higher ratios in older age groups (0·32% [0·27–0·38] in those aged <60 years vs 6·4% [5·7–7·2] in those aged ≥60 years), up to 13·4% (11·2–15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4–3·5] in those aged <60 years [n=360] and 4·5% [1·8–11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39–1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0–7·6) in those aged 80 years or older. Interpretation These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death. Funding UK Medical Research Council.

                Author and article information

                Risk Manag Healthc Policy
                Risk Management and Healthcare Policy
                25 September 2020
                : 13
                : 1757-1764
                [1 ]Department of Physical Education, Qatar University , Doha, Qatar
                [2 ]Department of Medical Laboratory Sciences, Jordan University of Science and Technology , Irbid, Jordan
                [3 ]Department of Clinical Pharmacy, Jordan University of Science and Technology , Irbid, Jordan
                Author notes
                Correspondence: Mahmoud A Alomari Department of Physical Education, Qatar University , Doha, Qatar Email malomari@qu.edu.qa
                Author information
                © 2020 Alomari et al.

                This work is published by Dove Medical Press Limited, and licensed under a Creative Commons Attribution License. The full terms of the License are available at http://creativecommons.org/licenses/by/4.0/. The license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                : 18 June 2020
                : 14 August 2020
                Page count
                Figures: 0, Tables: 6, References: 46, Pages: 8
                Original Research

                Social policy & Welfare
                physical activity,sedentary behavior,confinement,covid-19,pandemic
                Social policy & Welfare
                physical activity, sedentary behavior, confinement, covid-19, pandemic


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