During the early phase of the coronavirus disease epidemic in Hong Kong, 1,715 survey respondents reported high levels of perceived risk, mild anxiety, and adoption of personal-hygiene, ...travel-avoidance, and social-distancing measures. Widely adopted individual precautionary measures, coupled with early government actions, might slow transmission early in the outbreak.
This paper looks into the impact of the recent COVID-19 epidemic on the daily mobility of people. Existing research into the epidemic travel patterns points at transport as a channel for disease ...spreading with especially long-distance travel in the centre of interest. We adopt a different approach looking into the effects that epidemic has on the transport system and specifically in relation to short-distance daily mobility activities. We go beyond simple travel avoidance behaviours and look into factors influencing change in travel times and in modal split under epidemic. This leads to the research problems we posit in this paper. We look into the overall reduction of daily travel and into the factors impacting peoples' decisions to refrain from daily traveling. This paper focuses on modes affected and explores differences between various societal groups.
We use a CATI survey with a representative sample size of 1069 respondents from Poland. The survey was carried out between March, 24th and April, 6th2020, with a start date one week after the Polish government introduced administrative measures aimed at slowing down the COVID-19 epidemic. For data analysis, we propose using the GLM (general linear model), allowing us to include all the qualitative and quantitative variables which depict our sample.
We observe significant drops in travel times under epidemic conditions. Those drops are similar regardless of the age group and gender. The time decrease depended on the purpose of travels, means of transport, traveller's household size, fear of coronavirus, main occupation, and change in it caused by the epidemic. The more the respondent was afraid of coronavirus, the more she or he shortened the travel time.
•CATI survey reveals significant drops in daily travel times during epidemic.•The research confirms the effectiveness of mobility restrictions.•Travel time drops are similar regardless of the age group and gender.•Main occupation is the key factor affecting travel time change.•The more one was afraid of coronavirus, the bigger the travel time reduction was.
We propose a mathematical model for the transmission dynamics of SARS-CoV-2 in a homogeneously mixing non constant population, and generalize it to a model where the parameters are given by piecewise ...constant functions. This allows us to model the human behavior and the impact of public health policies on the dynamics of the curve of active infected individuals during a COVID-19 epidemic outbreak. After proving the existence and global asymptotic stability of the disease-free and endemic equilibrium points of the model with constant parameters, we consider a family of Cauchy problems, with piecewise constant parameters, and prove the existence of pseudo-oscillations between a neighborhood of the disease-free equilibrium and a neighborhood of the endemic equilibrium, in a biologically feasible region. In the context of the COVID-19 pandemic, this pseudo-periodic solutions are related to the emergence of epidemic waves. Then, to capture the impact of mobility in the dynamics of COVID-19 epidemics, we propose a complex network with six distinct regions based on COVID-19 real data from Portugal. We perform numerical simulations for the complex network model, where the objective is to determine a topology that minimizes the level of active infected individuals and the existence of topologies that are likely to worsen the level of infection. We claim that this methodology is a tool with enormous potential in the current pandemic context, and can be applied in the management of outbreaks (in regional terms) but also to manage the opening/closing of borders.
•Existence of pseudo-periodic solutions and epidemic waves in COVID-19 pandemic.•Complex network model for COVID-19 with piecewise constant parameters.•Impact of mobility in the transmission dynamics of SARS-CoV-2.•Optimal topologies for the minimization of active infected individuals.•Management of epidemic outbreaks and human mobility.
With the global outbreak of COVID-19, people are facing great physical and mental stress, and mental health problems are becoming increasingly prominent. Some theories emphasize the role of family in ...people's mental health, but the association between family functioning and mental health and the mediating and moderating mechanisms underlying this relation have not been extensively researched. This study examined whether loneliness mediates the relation between family functioning and mental health and, if so, whether this mediating effect is moderated by hope. A total of 5783 Chinese secondary vocational students completed measures of family adaptability and cohesion, loneliness, mental health, and hope. The results indicated that family functioning had a significant and positive predictive effect on the mental health of the students and that this relationship was partially mediated by loneliness. Further, hope moderated the relationship between family functioning and loneliness. Specifically, the relationship between family functioning and loneliness was significant for students with both high and low levels of hope. The current study contributes to a better understanding of the influence of family functioning on mental health, especially during trying times such as the COVID-19 epidemic.
•The family functioning was positively associated with mental health.•Loneliness mediated the relationship between family functioning and mental health.•Hope moderated the relationship between family functioning and loneliness.
Since the COVID-19 outbreak in Wuhan City in December of 2019, numerous model predictions on the COVID-19 epidemics in Wuhan and other parts of China have been reported. These model predictions have ...shown a wide range of variations. In our study, we demonstrate that nonidentifiability in model calibrations using the confirmed-case data is the main reason for such wide variations. Using the Akaike Information Criterion (AIC) for model selection, we show that an SIR model performs much better than an SEIR model in representing the information contained in the confirmed-case data. This indicates that predictions using more complex models may not be more reliable compared to using a simpler model. We present our model predictions for the COVID-19 epidemic in Wuhan after the lockdown and quarantine of the city on January 23, 2020. We also report our results of modeling the impacts of the strict quarantine measures undertaken in the city after February 7 on the time course of the epidemic, and modeling the potential of a second outbreak after the return-to-work in the city.
The most important features to assess the severity of an epidemic are its size and its timescale. We discuss these features in a systematic way in the context of SIR and SIR-type models. We ...investigate in detail how the size and timescale of the epidemic can be changed by acting on the parameters characterizing the model. Using these results and having as guideline the COVID-19 epidemic in Italy, we compare the efficiency of different containment strategies for contrasting an epidemic diffusion such as social distancing, lockdown, tracing, early detection and isolation.
•We discuss the expected outcome of different COVID-19 contrasting strategies.•Special attention is devoted to how long a total or partial lockdown should be.•Limiting the action to social distancing can lead to a dramatically long time scale.•Tracking of contacts allows to shorten the epidemic time-scale.
People with disabilities during the COVID-19 epidemic were particularly vulnerable to information exclusion, e.g. press conferences were not translated into PJM, there was no information in plain ...language, etc. In addition, restrictions were introduced on social contacts and the possibility of carrying out previous activities and using the support of volunteers or assistants. This made social media an important tool during the COVID-19 pandemic for people with disabilities as it often provided a way to connect with a wider community, maintain social relationships, and obtain information about the epidemic and the restrictions being imposed. The aim of the article is to demonstrate the significance of social media during the COVID-19 pandemic in Poland from 2020 to 2021 for people with disabilities. This will be facilitated by netnographic research, which will be based on the analysis of content published in 10 Facebook groups for people with disabilities between March–April 2020 and December–February 2021.
The results of the research indicate that social media played an important role for people with disabilities during the crisis situation of the pandemic. Analysis of the content of social media group profiles showed that they provide a space for seeking and exchanging information, sharing concerns, seeking support, and fighting for their rights by people with disabilities.
In this paper, we analyze a stochastic coronavirus (COVID-19) epidemic model which is perturbed by both white noise and telegraph noise incorporating general incidence rate. Firstly, we investigate ...the existence and uniqueness of a global positive solution. Then, we establish the stochastic threshold for the extinction and the persistence of the disease. The data from Indian states, are used to confirm the results established along this paper.
The outbreaks of Coronavirus (COVID-19) epidemic have increased the pressure on healthcare and medical systems worldwide. The timely diagnosis of infected patients is a critical step to limit the ...spread of the COVID-19 epidemic. The chest radiography imaging has shown to be an effective screening technique in diagnosing the COVID-19 epidemic. To reduce the pressure on radiologists and control of the epidemic, fast and accurate a hybrid deep learning framework for diagnosing COVID-19 virus in chest X-ray images is developed and termed as the COVID-CheXNet system. First, the contrast of the X-ray image was enhanced and the noise level was reduced using the contrast-limited adaptive histogram equalization and Butterworth bandpass filter, respectively. This was followed by fusing the results obtained from two different pre-trained deep learning models based on the incorporation of a ResNet34 and high-resolution network model trained using a large-scale dataset. Herein, the parallel architecture was considered, which provides radiologists with a high degree of confidence to discriminate between the healthy and COVID-19 infected people. The proposed COVID-CheXNet system has managed to correctly and accurately diagnose the COVID-19 patients with a detection accuracy rate of 99.99%, sensitivity of 99.98%, specificity of 100%, precision of 100%, F1-score of 99.99%, MSE of 0.011%, and RMSE of 0.012% using the weighted sum rule at the score-level. The efficiency and usefulness of the proposed COVID-CheXNet system are established along with the possibility of using it in real clinical centers for fast diagnosis and treatment supplement, with less than 2 s per image to get the prediction result.
The COVID-19 epidemic made the most countries to take strict lockdown measures, what has seriously caused an unprecedented impact in the shipping industries, whereas these measures have also played a ...significant impact to control carbon emissions from international shipping. Here, we try to use the threshold generalized autoregressive conditional heteroscedasticity and the exponential generalized autoregressive heteroscedasticity to investigate whether the fluctuations of the control variable on carbon emissions from international shipping are asymmetric or not. On this basis, the GARCH-MIDAS model is introduced to discuss whether the newly confirmed cases are independent of control variables and have an impact on the fluctuation of carbon emissions. From the results, we find that the information contained in the newly confirmed cases cannot be covered when adding the other control variables. In addition, the newly confirmed cases have a negative impact on the volatility of carbon emissions, while the other control variables significantly increase carbon emissions. This study provides a quantitative research method for the analysis of the volatility and impact factors on international shipping carbon emissions, which helps to formulate more reasonable emission reduction measures and promote the low-carbon transformations of the global shipping industry.
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•Explore the impact of the COVID-19 epidemic on carbon emissions from international shipping•Build GARCH-MIDAS model by adding control variables about the COVID-19 epidemic•Analyze the effectiveness of the COVID-19 epidemic on the fluctuation of carbon emissions from international shipping•The COVID-19 epidemic has obviously reduced the fluctuation of carbon emissions from international shipping.
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