Impact of media reports on the early spread of COVID-19 epidemic

Using a novel 'difference-in-differences' method and syndromic surveillance to estimate the change in local healthcare utilisation during periods of media reporting in the early stages of the COVID-19 pandemic in England

OBJECTIVES

Syndromic surveillance supplements traditional laboratory reporting for infectious diseases monitoring. Prior to widespread COVID-19 community surveillance, syndromic surveillance was one of several systems providing real-time information on changes in healthcare-seeking behaviour. The study objective was to identify changes in healthcare utilisation during periods of high local media reporting in England using 'difference-in-differences' (DiD).

STUDY DESIGN

A retrospective observational study was conducted using five media events in January-February 2020 in England on four routinely monitored syndromic surveillance indicators.

METHODS

Dates 'exposed' to a media event were estimated using Google Trends internet search intensity data (terms = 'coronavirus' and local authority [LA]). We constructed a negative-binomial regression model for each indicator and event time period to estimate a direct effect.

RESULTS

We estimated a four-fold increase in telehealth 'cough' calls and a 1.4-fold increase in emergency department (ED) attendances for acute respiratory illness in Brighton and Hove, when a so-called 'superspreading event' in this location was reported in local and national media. Significant decreases were observed in the Buxton (telehealth and ED attendance) and Wirral (ED attendance) areas during media reports of a returnee from an outbreak abroad and a quarantine site opening in the area respectively.

CONCLUSIONS

We used a novel approach to directly estimate changes in syndromic surveillance reporting during the early phase of the COVID-19 pandemic in England, providing contextual information on the interpretation of changes in health indicators. With careful consideration of event timings, DiD is useful in producing real-time estimates on specific indicators for informing public health action.

The impact of Public Health Emergency (PHE) on the news dissemination strength: Evidence from Chinese-Speaking Vloggers on YouTube

News dissemination plays a vital role in supporting people to incorporate beneficial actions during public health emergencies, thereby significantly reducing the adverse influences of events. Based on big data from YouTube, this research study takes the declaration of COVID-19 National Public Health Emergency (PHE) as the event impact and employs a DiD model to investigate the effect of PHE on the news dissemination strength of relevant videos. The study findings indicate that the views, comments, and likes on relevant videos significantly increased during the COVID-19 public health emergency. Moreover, the public's response to PHE has been rapid, with the highest growth in comments and views on videos observed within the first week of the public health emergency, followed by a gradual decline and returning to normal levels within four weeks. In addition, during the COVID-19 public health emergency, in the context of different types of media, lifestyle bloggers, local media, and institutional media demonstrated higher growth in the news dissemination strength of relevant videos as compared to news & political bloggers, foreign media, and personal media, respectively. Further, the audience attracted by related news tends to display a certain level of stickiness, therefore this audience may subscribe to these channels during public health emergencies, which confirms the incentive mechanisms of social media platforms to foster relevant news dissemination during public health emergencies. The proposed findings provide essential insights into effective news dissemination in potential future public health events.

Information dissemination during public health emergencies: analysing the international flow of COVID-19-related news

A large-scale exchange of information between media across national borders is frequently observed when a worldwide public health emergency occurs. This study investigated the global news citation network in the early stage of the COVID-19 pandemic by analysing the network structure at different levels to identify important nodes and the relationships among news organisations. The results show that COVID-19-related international news flow had a complex and unequal pattern, with a few countries and media outlets occupying a prominent place in the network and three media groups played key but different roles in disseminating the news. It was jointly influenced by national traits, the relatedness between countries, and the pandemic emergency with public health risks. From a global perspective, the media of the United States, mainland China, and the United Kingdom played the most important parts in collaboration within the world media system in the early stage of the COVID-19 pandemic.

An improved method of global dynamics: Analyzing the COVID-19 model with time delays and exposed infection

Considering the transmission characteristics of the coronavirus disease 2019 (COVID-19), there are certain time delays in the transition from susceptible individuals to exposed individuals after contact with exposed, symptomatically infected, and asymptomatically infected individuals. A COVID-19 model with time delays and exposed infection is developed and then the global dynamics of this model is investigated by an improved method; moreover, the numerical simulations are carried out. It is shown that the COVID-19-free equilibrium T0 is globally asymptotically stable (GAS) if and only if the control reproduction number Rc≤1, while T0 is unstable and the COVID-19 equilibrium T∗ is GAS if and only if Rc>1. The numerical results reveal that strengthening quarantine measures is helpful to control the COVID-19 epidemic in India. Furthermore, when Rc<1, the numbers of symptomatically infected, asymptomatically infected, and quarantined individuals eventually tend to the zero equilibrium state, and with the increase in the time delay, the three kinds of variables change faster and their peaks become larger; when Rc>1, the three kinds of variables eventually tend to the positive equilibrium state, which are oscillatory and the amplitudes of the oscillation enlarge as the value of time delay increases. The numerical results show that when Rc<1, the smaller the value of time delay, the smaller the final epidemic size. In short, the longer it takes time for susceptible individuals to transform exposed individuals, the harder COVID-19 will be controlled.

Modeling COVID-19 transmission dynamics incorporating media coverage and vaccination

The COVID-19 pandemic has caused widespread concern around the world. In order to study the impact of media coverage and vaccination on the spread of COVID-19, we establish an SVEAIQR infectious disease model, and fit the important parameters such as transmission rate, isolation rate and vaccine efficiency based on the data from Shanghai Municipal Health Commission and the National Health Commission of the People's Republic of China. Meanwhile, the control reproduction number and the final size are derived. Moreover, through sensitivity analysis by PRCC (partial rank correlation coefficient), we discuss the effects of both the behavior change constant $ k $ according to media coverage and the vaccine efficiency $ \varepsilon $ on the transmission of COVID-19. Numerical explorations of the model suggest that during the outbreak of the epidemic, media coverage can reduce the final size by about 0.26 times. Besides that, comparing with $ 50\% $ vaccine efficiency, when the vaccine efficiency reaches $ 90\% $, the peak value of infected people decreases by about 0.07 times. In addition, we simulate the impact of media coverage on the number of infected people in the case of vaccination or non-vaccination. Accordingly, the management departments should pay attention to the impact of vaccination and media coverage.

Mathematical analysis of the impact of the media coverage in mitigating the outbreak of COVID-19

In this paper, a mathematical model with a standard incidence rate is proposed to assess the role of media such as facebook, television, radio and tweeter in the mitigation of the outbreak of COVID-19. The basic reproduction number R 0 which is the threshold dynamics parameter between the disappearance and the persistence of the disease has been calculated. And, it is obvious to see that it varies directly to the number of hospitalized people, asymptomatic, symptomatic carriers and the impact of media coverage. The local and the global stabilities of the model have also been investigated by using the Routh-Hurwitz criterion and the Lyapunov's functional technique, respectively. Furthermore, we have performed a local sensitivity analysis to assess the impact of any variation in each one of the model parameter on the threshold R 0 and the course of the disease accordingly. We have also computed the approximative rate at which herd immunity will occur when any control measure is implemented. To finish, we have presented some numerical simulation results by using some available data from the literature to corroborate our theoretical findings.

Irish Media Coverage of COVID-19 Evidence-Based Research Reports From One National Agency

BACKGROUND

How research findings are presented through domestic news can influence behaviour and risk perceptions, particularly during emergencies such as the coronavirus disease 2019 (COVID-19) pandemic. Monitoring media communications to track misinformation and find information gaps is an important component of emergency risk communication. Therefore, this study investigated the traditional media coverage of nine selected COVID-19 evidence-based research reports and associated press releases (PRs) published during the initial phases of the pandemic (April to July 2020) by one national agency.

METHODS

NVivo was used for summative content analysis. 'Key messages' from each research report were proposed and 488 broadcast, print, and online media sources were coded at the phrase level. Manifest content was coded and counted to locate patterns in the data (what and how many) while latent content was analysed to further investigate these patterns (why and how). This included the coding of the presence of political and public health actors in coverage.

RESULTS

Coverage largely did not misrepresent the results of the reports, however, selective reporting and the variability in the use of quotes from governmental and public health stakeholders changed and contextualised results in different manners than perhaps originally intended in the PR. Reports received varying levels of media attention. Coverage focused on more 'human-interest' stories (eg, spread of COVID-19 by children and excess mortality) as opposed to more technical reports (eg, focusing on viral load, antibodies, testing, etc).

CONCLUSION

Our findings provide a case-study of European media coverage of evidence reports produced by a national agency. Results highlighted several strengths and weaknesses of current communication efforts.

Determinants of panic buying during COVID-19: causes and consequences

Purpose

Despite the abundant literature on panic buying during COVID-19 pandemic, the several causes and consequences of panic buying have been enormously ignored. The purpose of this study is to emphasize the consumer’s behavior during the COVID-19 pandemic and illustrate the comprehensive theoretical model of consumers’ panic buying to investigate its causes and consequences in a developing country empirically to uncover this gap.

Design/methodology/approach

The authors collected data from 419 households of all socioeconomic classes of Bangladesh. A hierarchical regression model analyzed the data.

Findings

This study finds that internal and external factors such as rumors, government strategies, fear and anxiety and health security significantly affect consumers’ panic buying behaviors. This finding supports some theories of human behavior. This study also finds that panic buying has internal and external consequences such as price hike, shortage of supply of products, dissatisfaction of consumers and increase in utility (benefit) of the products but not on consumer’s budget. This finding supports as well as contradicts some established theories of human and consumer behavior.

Originality/value

This study proves that panic buying cannot help the consumers and they are the ultimate sufferers of this. The findings of this study will help the government, media, suppliers and consumers to interact properly to maintain panic buying during a pandemic crisis. Giving a holistic explanation of the causes and consequences of panic buying by introducing some novel variables is a momentous strength of this study.

Factors underlying denial of and disbelief in COVID-19

Objective: To investigate factors that influence or promote disbelief and negative attitudes toward COVID-19. Methods: This was cross-sectional study involving 544 males and females = 18 years of age in Greece between December of 2020 and January of 2021. All participants were informed about the purpose of the study, protection of anonymity, and volunteer participation. Participants completed an online anonymous 40-item questionnaire. Analysis of data included the identification of correlations and use of t-tests and ANOVA. Results: The level of knowledge regarding COVID-19 transmission routes, manifestations, and prevention was high in our sample. Women appeared to have a more positive attitude toward COVID-19 prevention and management than did men (p = 0.032 and p = 0.018, respectively). Younger people (18-30 years of age) seemed to deny the validity of scientific data and mass media reports about ways to deal with the pandemic more commonly than did those > 30 years of age (p = 0.003 and p = 0.001, respectively). People who resided in cities more commonly believed in scientific announcements than did those living in villages (p = 0.029). Conclusions: In order to minimize cases of denial of and disbelief in COVID-19 and to promote vaccination, a series of actions are required. Governments should implement a series of measures to contain the disease, taking into consideration the psychological and social aspects of those policies.

Preventive control strategy on second wave of Covid-19 pandemic model incorporating lock-down effect

This study presents an optimal control strategy through a mathematical model of the Covid-19 outbreak without lock-down. The pandemic model analyses the lock-down effect without control strategy based on the current scenario of second wave data to control the rapid spread of the virus. The pandemic model has been discussed with respect to the basic reproduction number and stability analysis of disease-free and endemic equilibrium. A new optimal control problem with treatment is framed to minimize the vulnerable situation of the second wave. This system is applied to study the effects of vaccines and treatment controls. Numerical solutions and the graphical presentation of the results predict the fate of India’s second wave situation on account of the control strategy. Lastly, a comparative study with control and without control has been analysed for the exposed phase, infective phase, and recovery phase to understand the effectiveness of the controls. This model is used to estimate the total number of infected and active cases, deaths, and recoveries in order to control the disease using this system and studying the effects of vaccines and treatment controls.

Risk Communication in the Alert Phase of the COVID-19 Pandemic: Analysis of News Flow at National and Global Levels

This study examined the global media citation network of COVID-19-related news at two stages of the pandemic alert phase, i.e., the national level alert stage and the global level alert stage. The findings reveal that the small-world pattern and scale-free property of media citation networks contributed to the rapid spread of COVID-19-related news around the world. Within the networks, a small number of media outlets from a few countries formed the backbone of the network to control the risk communication; meanwhile, many media of geographical and cultural similarities formed cross-border collaborative cliques in the periphery of the network. When the alert phase escalated from the national level to the global level, the network demonstrated a number of changes. The findings contribute to the understanding of risk communication for international public health emergencies by taking into account the network perspective and evolutionary nature of public health emergencies in analysis.

Asymptotic behavior of the solutions for a stochastic SIRS model with information intervention

In this paper, a stochastic SIRS epidemic model with information intervention is considered. By constructing an appropriate Lyapunov function, the asymptotic behavior of the solutions for the proposed model around the equilibria of the deterministic model is investigated. We show the average in time of the second moment of the solutions of the stochastic system is bounded for a relatively small noise. Furthermore, we find that information interaction response rate plays an active role in disease control, and as the intensity of the response increases, the number of infected population decreases, which is beneficial for disease control.

It Takes Two to Tango: How the COVID-19 Vaccination Campaign in Israel Was Framed by the Health Ministry vs. the Television News

Background

The internet has become a major resource in information transfer during COVID-19, and traditional means of communication are digitized and accessible online to the public at large.

Objectives

This study seeks to examine how Israel's two main television news channels (Channel 12 and Channel 13) covered the Covid-19 vaccination campaign, compared to how the Ministry of Health ran the campaign.

Methods

A qualitative study based on triangulation of online content analyses from three different sources: advertising campaigns, social media posts and reports on television news channels. The research sample included 252 reports from the newsrooms of Channel 13 (n = 151) and Channel N12 (n = 101), Israel's two leading news channels, all broadcast between December 1, 2020 and November 30, 2021. The sample also included posts from Israel Ministry of Health Facebook page and advertising campaigns from the Facebook page of the Israel Government Advertising Agency (LAPAM), which constructs advertising campaigns for the MOH (113 items).

Results

The research findings reveal congruence between the way the MOH framed its vaccination campaign and news coverage of the vaccination issue. The vaccination campaign used three primary framing strategies: (1) positive framing (emphasizing the vaccine's advantages and stressing that the vaccine is safe and effective based on cost-benefit calculations and public health perspectives); (2) fear appeal strategy (conveying persuasive messages that seek to arouse fear through threats of impending danger or harm); (3) attribution of responsibility strategy (blaming the unvaccinated and targeting all those who criticized Israel's generic vaccination policy).

Conclusion

As the watchdog of democracy, the news should function as a professional and objective source that criticizes government systems if necessary and strives to uncover the truth throughout the crisis. Public trust, which is so essential during such a crisis, can be achieved only if the news channels provide reports and meaningful journalistic investigations that challenge the system. By doing so, they can help fight conflicts of interest that divert management of the crisis from the professional health field to the political-economic arena.

Transmission dynamics model and the coronavirus disease 2019 epidemic: applications and challenges

Since late 2019, the beginning of coronavirus disease 2019 (COVID-19) pandemic, transmission dynamics models have achieved great development and were widely used in predicting and policy making. Here, we provided an introduction to the history of disease transmission, summarized transmission dynamics models into three main types: compartment extension, parameter extension and population-stratified extension models, highlight the key contribution of transmission dynamics models in COVID-19 pandemic: estimating epidemiological parameters, predicting the future trend, evaluating the effectiveness of control measures and exploring different possibilities/scenarios. Finally, we pointed out the limitations and challenges lie ahead of transmission dynamics models.

Assessment of the Risk of Depression in Residents Staying at Long-Term Care Institutions in Poland During the COVID-19 Pandemic Depending on the Quality of Cognitive Functioning

Background: The development of the COVID-19 pandemic has prompted the implementation of many procedures to safeguard against further increases in illness. Unfortunately, this has drastically reduced residents' contact with their families, which has increased feelings of loneliness and isolation. This is particularly difficult in long-term care facilities, where the risk of developing depression is higher than in the general population. Objectives: The aim of the study was to assess the risk of depression among the residents of long-term care institutions in Poland during the COVID-19 pandemic and to determine the relationship between the risk of depression and the occurrence of cognitive impairment in the study group. Methods: The study included 273 residents from long-term care institutions in Poland. The risk of depression was determined based on an originally designed questionnaire. The cognitive state of the subjects was assessed using the screening test Mini-Mental State Examination (MMSE). Both the depression risk assessment and the MMSE test were conducted twice: in March and December 2020. Results: In March, severe dementia was present in 28.2% of the residents and normal MMSE scores were observed in 16.1% of the subjects; in December, the prevalence of severe dementia increased to 31.1% and that of normal scores decreased to 10.3%. In March, no participant was found to be at high risk of depression and moderate risk was observed in 14.3% of the subjects; in December, 2.6% of the residents had a high risk score and 45.4% had a moderate risk score. Statistical analysis revealed that higher MMSE scores correspond with a higher risk of depression. Conclusion: A higher risk of depression was observed with the development of the pandemic. Residents with cognitive impairment were characterised by a lower risk of depression compared to individuals with normal MMSE scores. During the study, progression of cognitive impairment was observed in the residents.

Analysis of a COVID-19 Epidemic Model with Seasonality

The statistics of COVID-19 cases exhibits seasonal fluctuations in many countries. In this paper, we propose a COVID-19 epidemic model with seasonality and define the basic reproduction number [Formula: see text] for the disease transmission. It is proved that the disease-free equilibrium is globally asymptotically stable when [Formula: see text], while the disease is uniformly persistent and there exists at least one positive periodic solution when [Formula: see text]. Numerically, we observe that there is a globally asymptotically stable positive periodic solution in the case of [Formula: see text]. Further, we conduct a case study of the COVID-19 transmission in the USA by using statistical data.

Discrete epidemic modelling of COVID-19 transmission in Shaanxi Province with media reporting and imported cases

The large-scale infection of COVID-19 has led to a significant impact on lives and economies around the world and has had considerable impact on global public health. Social distancing, mask wearing and contact tracing have contributed to containing or at least mitigating the outbreak, but how public awareness influences the effectiveness and efficiency of such approaches remains unclear. In this study, we developed a discrete compartment dynamic model to mimic and explore how media reporting and the strengthening containment strategies can help curb the spread of COVID-19 using Shaanxi Province, China, as a case study. The targeted model is parameterized based on multi-source data, including the cumulative number of confirmed cases, recovered individuals, the daily number of media-reporting items and the imported cases from the rest of China outside Shaanxi from January 23 to April 11, 2020. We carried out a sensitivity analysis to investigate the effect of media reporting and imported cases on transmission. The results revealed that reducing the intensity of media reporting, which would result in a significant increasing of the contact rate and a sizable decreasing of the contact-tracing rate, could aggravate the outbreak severity by increasing the cumulative number of confirmed cases. It also demonstrated that diminishing the imported cases could alleviate the outbreak severity by reducing the length of the epidemic and the final size of the confirmed cases; conversely, delaying implementation of lockdown strategies could prolong the length of the epidemic and magnify the final size. These findings suggest that strengthening media coverage and timely implementing of lockdown measures can significantly reduce infection.

Influence of COVID-19 Pandemic Uncertainty in Negative Emotional States and Resilience as Mediators against Suicide Ideation, Drug Addiction and Alcoholism

This research uses structural equation modeling to determine the influence of uncertainty due to the COVID-19 pandemic as an independent variable in the negative emotional states and resilience (as mediating variables) vs. drug addiction, alcoholism, and suicide ideation as dependent variables in 5557 students from a public state university in Northern Mexico. The five variables are related through eight hypotheses and tested using partial least squares. We used an adapted questionnaire sent by email in May 2020. Findings show that uncertainty facing the COVID-19 pandemic had a direct and significant influence on negative emotional states and a significant inverse effect on resilience; in the trajectory, drug addiction and alcoholism, and suicide ideation are explained.

What shapes people's willingness to wear a face mask at the beginning of a public health disaster? A qualitative study based on COVID-19 in China

COVID-19 should not be the world's last public health disaster, so there is an urgent need to learn from COVID-19 to prepare better for the next public health disaster. This study aims to understand the factors that make people wear a face mask at the beginning of an outbreak of public health disaster. Semi-structured interviews were conducted during April 2020 in China, one month after the COVID-19 was declared a pandemic. The respondents were members of the public living in China, covering two age groups: young adults and older adults. They were recruited using a convenient sample and snowball sampling strategy. The results were analysed using content analysis. Seventeen subjects were recruited, among which nine were young adults (average age = 26.4; SD = 10.5), and eight were older adults (average age = 60.4; SD = 12.1). This study found that environmental factors, personal factors, factors concerning wearing masks, specific circumstances, and development of the pandemic were the common factors considered by both young adults and older adults. This study should help the authority formulate prevention policies better to reduce the risk of an outbreak if there is a new virus outbreak in the future, unfortunately.

Overall and COVID-19-specific citation impact of highly visible COVID-19 media experts: bibliometric analysis

OBJECTIVE

To evaluate whether the COVID-19 experts who appear most frequently in media have high citation impact for their research overall, and for their COVID-19 peer-reviewed publications in particular and to examine the representation of women among such experts.

DESIGN

Cross-linking of data sets of most highly visible COVID-19 media experts with citation data on the impact of their published work (career-long publication record and COVID-19-specific work).

SETTING

Cable news appearance in prime-time programming or overall media appearances.

PARTICIPANTS

Most highly visible COVID-19 media experts in the USA, Switzerland, Greece and Denmark.

INTERVENTIONS

None.

OUTCOME MEASURES

Citation data from Scopus along with discipline-specific ranks of overall career-long and COVID-19-specific impact based on a previously validated composite citation indicator.

RESULTS

We assessed 76 COVID-19 experts who were highly visible in US prime-time cable news, and 50, 12 and 2 highly visible experts in media in Denmark, Greece and Switzerland, respectively. Of those, 23/76, 10/50, 2/12 and 0/2 were among the top 2% of overall citation impact among scientists in the same discipline worldwide. Moreover, 37/76, 15/50, 7/12 and 2/2 had published anything on COVID-19 that was indexed in Scopus as of 30 August 2021. Only 18/76, 6/50, 2/12 and 0/2 of the highly visible COVID-19 media experts were women. 55 scientists in the USA, 5 in Denmark, 64 in Greece and 56 in Switzerland had a higher citation impact for their COVID-19 work than any of the evaluated highly visible media COVID-19 experts in the respective country; 10/55, 2/5, 22/64 and 14/56 of them were women.

CONCLUSIONS

Despite notable exceptions, there is a worrisome disconnect between COVID-19 claimed media expertise and scholarship. Highly cited women COVID-19 experts are rarely included among highly visible media experts.

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travel bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.

Dynamical analysis of a reaction–diffusion SEI epidemic model with nonlinear incidence rate

In this paper, a reaction–diffusion SEI epidemic model with nonlinear incidence rate is proposed. The well-posedness of solutions is studied, including the existence of positive and unique classical solution and the existence and the ultimate boundedness of global solutions. The basic reproduction numbers are given in both heterogeneous and homogeneous environments. For spatially heterogeneous environment, by the comparison principle of the diffusion system, the infection-free steady state is proved to be globally asymptotically stable if [Formula: see text] if [Formula: see text], the system will be persistent and admit at least one positive steady state. For spatially homogenous environment, by constructing a Lyapunov function, the infection-free steady state is proved to be globally asymptotically stable if [Formula: see text] and then the unique positive steady state is achieved and is proved to be globally asymptotically stable if [Formula: see text]. Finally, two examples are given via numerical simulations, and then some control strategies are also presented by the sensitive analysis.

Modeling the effects of prosocial awareness on COVID-19 dynamics: Case studies on Colombia and India

The ongoing COVID-19 pandemic has affected most of the countries on Earth. It has become a pandemic outbreak with more than 50 million confirmed infections and above 1 million deaths worldwide. In this study, we consider a mathematical model on COVID-19 transmission with the prosocial awareness effect. The proposed model can have four equilibrium states based on different parametric conditions. The local and global stability conditions for awareness-free, disease-free equilibrium are studied. Using Lyapunov function theory and LaSalle invariance principle, the disease-free equilibrium is shown globally asymptotically stable under some parametric constraints. The existence of unique awareness-free, endemic equilibrium and unique endemic equilibrium is presented. We calibrate our proposed model parameters to fit daily cases and deaths from Colombia and India. Sensitivity analysis indicates that the transmission rate and the learning factor related to awareness of susceptibles are very crucial for reduction in disease-related deaths. Finally, we assess the impact of prosocial awareness during the outbreak and compare this strategy with popular control measures. Results indicate that prosocial awareness has competitive potential to flatten the COVID-19 prevalence curve.

The information impact of network media, the psychological reaction to the COVID-19 pandemic, and online knowledge acquisition: Evidence from Chinese college students

This study focuses on whether network media information about the COVID-19 pandemic has had a significant impact on the online knowledge acquisition of college students. This research is of great significance, as it can have a profound impact on the way we think about knowledge acquisition in the future. Yet, a recent literature review finds that the academic community has not paid attention to this important topic. In the present work, which is based on a survey of 5000 Chinese college students during the COVID-19 pandemic period, we find that COVID-19 information from mainstream Chinese media and overseas media as well as social media has had a significant promoting effect on the online knowledge acquisition of college students. At the same time, the psychological response to the pandemic situation is shown to have had a significant mediating effect on the relationship between the information impact from mainstream Chinese and overseas media and the online knowledge acquisition of college students. Our findings have shown that the more positive college students are in responding to the pandemic, the stronger their willingness is to acquire knowledge through online means, and the better effect this will have on them acquiring knowledge. The results of this paper have important implications for the optimization and improvement of college students’ education and knowledge acquisition methods in the context of the long-term COVID-19 pandemic.