Analyses of the Duration and Dynamics of the COVID-19 Epidemic in 11 Severely Affected Countries.
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ABSTRACT:
SUBMITTER: Chen C
PROVIDER: S-EPMC8485420 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:AimThe lockdown of sports infrastructure due to the COVID-19 pandemic has substantially shifted people's physical activity towards public green spaces. With Germany's lockdown as one of the more severe governmentally imposed epidemic-control-decisions, we tested to what extent the frequency of outdoor cycling activities changed from March to June 2020.MethodsUser behaviour and frequency in 15 urban and 7 rural German public green spaces was quantified using cycling data from the fitness application Strava. Changes in cycling activities were analysed with four different generalised linear models, correcting for factors like weather conditions and temporal changes in the user base of the fitness application.ResultsWe found a clear increase in outdoor cycling sport activities in urban public green spaces in response to epidemic-control decisions (e.g. increase by 81% in April relative to the expected value (95% CI [48%, 110%])). In contrast, biking in rural areas showed no significant change with epidemic-control-decisions in place.ConclusionFitness App data, e.g. from Strava, can be used to monitor visitor behaviour and frequency. The increase in outdoor cycling activities during epidemic control decisions likely reflects a shift of sport activities from indoor and team sports to outdoor and individual sports. This highlights the importance of accessible green space for maintaining physical fitness and health. Beyond this shift, it is likely that outdoor activities may be of particularly importance for stress relief in times of crisis such as the current COVID-19 pandemic.
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Project description:[Figure: see text].
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Project description:BackgroundThe ongoing coronavirus disease 2019 (COVID-19) pandemic has caused a tremendous health burden and impact on the world economy. The UK Government implemented the biggest lockdown of society during peacetime in British history at the end of March 2020, aiming to contain the rapid spread of the virus. The UK lockdown was maintained for 7 weeks, but the effectiveness of the control measures in suppressing disease transmission remains incompletely understood.MethodsA Bayesian SEIR (susceptible-exposed-infected-removed) epidemiological model was used to rebuild the local transmission dynamics of the spread of COVID-19 in nine regions of England.ResultsThe basic reproduction number (R0) in England was found to be relatively high compared with China. The estimate of the temporally varying effective reproduction number (Rt) suggests that the control measures, especially the forced lockdown, were effective to reduce transmissibility and curb the COVID-19 epidemic. Although the overall incidence rate in the UK has declined, forecasting highlights the possibility of a second epidemic wave in several regions.ConclusionThis study enhances understanding of the current outbreak and the effectiveness of control measures in the UK.
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Project description:COVID-19 or SARS-Cov-2, affecting 6 million people and more than 300,000 deaths, the global pandemic has engulfed more than 90% countries of the world. The virus started from a single organism and is escalating at a rate of 3% to 5% daily and seems to be a never ending process. Understanding the basic dynamics and presenting new predictions models for evaluating the potential effect of the virus is highly crucial. In present work, an evolutionary data analytics method called as Genetic programming (GP) is used to mathematically model the potential effect of coronavirus in 15 most affected countries of the world. Two datasets namely confirmed cases (CC) and death cases (DC) were taken into consideration to estimate, how transmission varied in these countries between January 2020 and May 2020. Further, a percentage rise in the number of daily cases is also shown till 8 June 2020 and it is expected that Brazil will have the maximum rise in CC and USA have the most DC. Also, prediction of number of new CC and DC cases for every one million people in each of these countries is presented. The proposed model predicted that the transmission of COVID-19 in China is declining since late March 2020; in Singapore, France, Italy, Germany and Spain the curve has stagnated; in case of Canada, South Africa, Iran and Turkey the number of cases are rising slowly; whereas for USA, UK, Brazil, Russia and Mexico the rate of increase is very high and control measures need to be taken to stop the chains of transmission. Apart from that, the proposed prediction models are simple mathematical equations and future predictions can be drawn from these general equations. From the experimental results and statistical validation, it can be said that the proposed models use simple linkage functions and provide highly reliable results for time series prediction of COVID-19 in these countries.
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Project description:Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, guidance ("Japanese Guide") has been published by a working group of several academic societies and announced by the Ministry of Health, Labour, and Welfare. Steroids as a candidate treatment for COVID-19 were noted in the Japanese Guide. However, the prescription details for steroids, and whether the Japanese Guide changed its clinical practice, were unclear. This study aimed to examine the impact of the Japanese Guide on the trends in the prescription of steroids for COVID-19 inpatients in Japan. We selected our study population using Diagnostic Procedure Combination (DPC) data from hospitals participating in the Quality Indicator/Improvement Project (QIP). The inclusion criteria were patients discharged from hospital between January 2020 and December 2020, who had been diagnosed with COVID-19, and were aged 18 years or older. The epidemiological characteristics of cases and the proportion of steroid prescriptions were described on a weekly basis. The same analysis was performed for subgroups classified by disease severity. The study population comprised 8603 cases (410 severe cases, 2231 moderate II cases, and 5962 moderate I/mild cases). The maximum proportion of cases prescribed with dexamethasone increased remarkably from 2.5 to 35.2% in the study population before and after week 29 (July 2020), when dexamethasone was included in the guidance. These increases were 7.7% to 58.7% in severe cases, 5.0% to 57.2% in moderate II cases, and 1.1% to 19.2% in moderate I/mild cases. Although the proportion of cases prescribed prednisolone and methylprednisolone decreased in moderate II and moderate I/mild cases, it remained high in severe cases. We showed the trends of steroid prescriptions in COVID-19 inpatients. The results showed that guidance can influence drug treatment provided during an emerging infectious disease pandemic.
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Project description:Detection and isolation of infected people are believed to play an important role in the control of the COVID-19 pandemic. Some countries conduct large-scale screenings for testing, whereas others test mainly people with high prior probability of infection such as showing severe symptoms and/or having an epidemiological link with a known or suspected case or cluster of cases. However, what a good testing strategy is and whether the difference in testing strategy shows a meaningful, measurable impact on the COVID-19 epidemic remain unknown. Here, we showed that patterns of association between effective reproduction number (Rt) and test positivity rate can illuminate differences in testing situation among different areas, using global and local data from Japan. This association can also evaluate the adequacy of current testing systems and what information is captured in COVID-19 surveillance. The differences in testing systems alone cannot predict the results of epidemic containment efforts. Furthermore, monitoring test positivity rates and severe case proportions among the nonelderly can predict imminent case count increases. Monitoring test positivity rates in conjunction with the concurrent Rt could be useful to assess and strengthen public health management and testing systems and deepen understanding of COVID-19 epidemic dynamics.
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Project description:BackgroundIn Ireland and across the European Union the COVID-19 epidemic waves, driven mainly by the emergence of new variants of the SARS-CoV-2 have continued their course, despite various interventions from governments. Public health interventions continue in their attempts to control the spread as they wait for the planned significant effect of vaccination.MethodsTo tackle this challenge and the observed non-stationary aspect of the epidemic we used a modified SEIR stochastic model with time-varying parameters, following Brownian process. This enabled us to reconstruct the temporal evolution of the transmission rate of COVID-19 with the non-specific hypothesis that it follows a basic stochastic process constrained by the available data. This model is coupled with Bayesian inference (particle Markov Chain Monte Carlo method) for parameter estimation and utilized mainly well-documented Irish hospital data.ResultsIn Ireland, mitigation measures provided a 78-86% reduction in transmission during the first wave between March and May 2020. For the second wave in October 2020, our reduction estimation was around 20% while it was 70% for the third wave in January 2021. This third wave was partly due to the UK variant appearing in Ireland. In June 2020 we estimated that sero-prevalence was 2.0% (95% CI: 1.2-3.5%) in complete accordance with a sero-prevalence survey. By the end of April 2021, the sero-prevalence was greater than 17% due in part to the vaccination campaign. Finally we demonstrate that the available observed confirmed cases are not reliable for analysis owing to the fact that their reporting rate has as expected greatly evolved.ConclusionWe provide the first estimations of the dynamics of the COVID-19 epidemic in Ireland and its key parameters. We also quantify the effects of mitigation measures on the virus transmission during and after mitigation for the three waves. Our results demonstrate that Ireland has significantly reduced transmission by employing mitigation measures, physical distancing and lockdown. This has to date avoided the saturation of healthcare infrastructures, flattened the epidemic curve and likely reduced mortality. However, as we await for a full roll out of a vaccination programme and as new variants potentially more transmissible and/or more infectious could continue to emerge and mitigation measures change silent transmission, challenges remain.
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Project description:The role of meteorological factors in the transmission of the COVID-19 still needs to be determined. In this study, the daily new cases of the eight severely affected regions in four countries of South America and their corresponding meteorological data (average temperature, maximum temperature, minimum temperature, average wind speed, visibility, absolute humidity) were collected. Daily number of confirmed and incubative cases, as well as time-dependent reproductive number (Rt) was calculated to indicate the transmission of the diseases in the population. Spearman's correlation coefficients were assessed to show the correlation between meteorological factors and daily confirmed cases, daily incubative cases, as well as Rt. In particular, the results showed that there was a highly significant correlation between daily incubative cases and absolute humidity throughout the selected regions. Multiple linear regression model further confirmed the negative correlation between absolute humidity and incubative cases. The absolute humidity is predicted to show a decreasing trend in the coming months from the meteorological data of recent three years. Our results suggest the necessity of continuous controlling policy in these areas and some other complementary strategies to mitigate the contagious rate of the COVID-19.
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Project description:During the so-called "second wave of the pandemic" in Europe, the authors conducted a cross-sectional online survey that aimed to examine changes in dietary habits and associated practices, as well as physical activity during the COVID-19 pandemic and before the onset of lockdowns in three European countries: Poland, Austria and the United Kingdom. The online observational study, both prospective and retrospective, conducted with the use of social media for the distribution of an anonymous online questionnaire, was completed from 1 October to 30 October 2020, during the second wave of the pandemic in Europe. The study encompassed a total of 1071 adults from Poland (n = 407), Austria (n = 353) and the United Kingdom (n = 311). The results of this study indicate that the COVID-19 confinement period influenced eating behavior and the level of physical activity in a group of adult residents of Poland, Austria and the United Kingdom. The general shopping frequency decreased, regardless of the place and manner. However, there was an increased interest in online grocery shopping. The resulting data revealed an increased frequency of the daily consumption of food products such as dairy, grains, fats, vegetables and sweets (p < 0.05). A rise in the frequency of purchasing frozen goods and food with long shelf life has also been observed. The changed workplace and working conditions or unemployment probably affected a perceptible rise in alcohol consumption (p = 0.02). In turn, physical activity levels markedly decreased, which reflected the body mass changes. The dietary habits in the studied countries have changed as a result of the pandemic situation. They contribute to the aggravation of the problem of excess body weight and its health consequences.
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