Media coverage and hospital notifications: Correlation analysis and optimal media impact duration to manage a pandemic

Effect of avian influenza scare on transmission of zoonotic avian influenza: A case study of influenza A (H7N9)

Avian influenza scare is a human psychological factor that asserts both positive and negative effects on the transmission of zoonotic avian influenza. In order to study the dichotomous effect of avian influenza scare on disease transmission, taking H7N9 avian influenza as a typical case, a two-patch epidemic model is proposed. The global dynamics and the threshold criteria are established by LaSalle invariant principle and the theory of asymptotic autonomous system. To mitigate the negative effects and curb illegal poultry trade, a game-theoretic model is adopted to explore the optimal policy of culling subsidies to reasonably compensate stakeholders for their economic losses resulting from the scare. The optimal policy of culling subsidy is found to heavily depend on the penalty of illegal poultry trade, the stakeholders' income, the intensity of control measures, and the prevalence level of the disease. The negative effect of avian influenza scare on disease transmission is considerably more significant than the positive effect. In order to avoid a widespread outbreak of zoonotic avian influenza across the region, a comprehensive national global control strategy is essential and effective, even in the presence of the negative effect of the avian influenza scare.

How news reporting exacerbated the monkeypox pandemic in Spain and the US: A corpus-based news values analysis

Media reporting greatly influences the civilians' mentality, which further exacerbates or mitigates outbreaks of infectious diseases, prolongs or shortens the pandemic process. Adopting corpus linguistic methods and Discursive news values analysis (DNVA) framework, this study examined the news values through key words, naming strategies and photographs in monkeypox-themed news reporting in Spanish and the US media, to analyse how they constructed the monkeypox pandemic in their news reporting, sold it to the public and exacerbated the pandemic in the two societies. The results show that the Spanish media constructed the monkeypox pandemic predominantly as an international medical event, distancing the monkeypox pandemic from the Spanish indigenous context and depriving the domestic audiences from the sense of urgency to take prevention actions. On the other hand, the US media mainly packaged the monkeypox pandemic as a political event which isolated this public health crisis from the life of the common people and hindered the US citizens' understanding of the requisite medical information about the monkeypox virus. It is concluded that the lack of indigenous focus of the Spanish media, and the excessively politicised focus of the US media are important factors that lead to the exacerbation of the monkeypox epidemic.

Did text-based news-media coverage about the COVID-19 pandemic increase vaccine uptake? A population-based study in Alaska

COVID-19 vaccinations protect against severe infection, hospitalisation, and death. News media can be an important source of information for the public during a health crisis. This study explores the extent to which local or statewide text-based news coverage of the pandemic was related to the uptake of initial doses of COVID-19 vaccines among adults in Alaska. Multilevel modelling was employed to explore the association between news media intensity and vaccine uptake rates across boroughs and census areas, while controlling for relevant covariates. Results suggest that the intensity of news media did not significantly influence vaccine uptake during the majority of this time period and had a negative affect during the Delta-surge in the fall of 2021. However, the political lean and median age of boroughs or census areas were significantly associated with vaccine uptake. Race, poverty, or education were not significant determinants of vaccine uptake suggesting there are unique differences in Alaska compared to the U.S., particularly amongst Alaska Native people. The political environment in Alaska surrounding the pandemic was polarized. Future research in communications and channels that can cut through this polarized and politicized environment, and reach younger adults is needed.

Keeping up with COVID-19 information: Capacity issues and knowledge uncertainty early in the pandemic

This article examines the relationship between information consumption and mental health during the early stages of the COVID-19 pandemic. Adopting a qualitative approach, we interviewed 39 people in British Columbia, Canada between October and December 2020. Interestingly, half of the participants did not want to seek out new information on COVID-19, making their early insights and initial confusion salient. While some individuals did desire up-to-date information on outbreaks and new risks, many expressed confusion over what was perceived to be an evolving landscape of public health policy and practice. Overall, our research found that capacity issues, information overload/fatigue, politics, distrust, and competing sources of news all contributed to a culture of confusion towards public health information. As a consequence, this confusion resulted in knowledge uncertainty about the virus, vaccinations, and the pandemic itself. Our findings highlight the need for a host of future projects that examine how citizens experience disempowerment and limited agency towards compliance with health and safety initiatives.

Renewal equations for delayed population behaviour adaptation coupled with disease transmission dynamics: A mechanism for multiple waves of emerging infections

There are many plausible reasons for recurrent outbreaks of emerging infectious diseases. In this paper, we develop a mathematical model to illustrate how population behavioural adaption and adaptation implementation delay, in response to the perceived infection risk, can lead to recurrent outbreak patterns. We consider the early phase of an infection outbreak when herd immunity is not reached, pathogen mutation is not considered, and seasonality is ruled out as a major contributor. We derive a transmission dynamics model coupled with the renewal equation for the disease transmission effective contacts (contact rate per unit time multiplied by the transmission probability per contact). The model incorporates two critical parameters: the population behavioural adaptation flexibility index and the behavioural change implementation delay. We show that when the behavioural change implementation delay reaches a critical value, the number of infections starts to oscillate in an equilibrium that is determined by the population behavioural adaptation flexibility. We also show that the numbers of infections at the subsequent peaks can exceed that of the first peak. This was an oblique observation globally during the early phase of the COVID-19 pandemic before variants of concern emerged, and it was an observed phenomena with the Omicron variant induced wave in areas where early interventions were successful in preventing the large outbreaks. Our model and analyses can provide partially explanation for these observations.

Global Hopf bifurcation of a cholera model with media coverage

We propose a model for cholera under the impact of delayed mass media, including human-to-human and environment-to-human transmission routes. First, we establish the extinction and uniform persistence of the disease with respect to the basic reproduction number. Then, we conduct a local and global Hopf bifurcation analysis by treating the delay as a bifurcation parameter. Finally, we carry out numerical simulations to demonstrate theoretical results. The impact of the media with the time delay is found to not influence the threshold dynamics of the model, but is a factor that induces periodic oscillations of the disease.

Dynamics of an SEIR model with media coverage mediated nonlinear infectious force

Media coverage can greatly impact the spread of infectious diseases. Taking into consideration the impacts of media coverage, we propose an SEIR model with a media coverage mediated nonlinear infection force. For this novel disease model, we identify the basic reproduction number using the next generation matrix method and establish the global threshold results: If the basic reproduction number $ \mathcal{R}_{0} < 1 $, then the disease-free equilibrium $ P_{0} $ is stable, and the disease dies out. If $ \mathcal{R}_{0} > 1 $, then the endemic equilibrium $ P^{*} $ is stable, and the disease persists. Sensitivity analysis indicates that the basic reproduction number $ \mathcal{R}_{0} $ is most sensitive to the population recruitment rate $ \Lambda $ and the disease transmission rate $ \beta _{1} $.

A COVID-19 Infection Model Considering the Factors of Environmental Vectors and Re-Positives and Its Application to Data Fitting in Japan and Italy

COVID-19, which broke out globally in 2019, is an infectious disease caused by a novel strain of coronavirus, and its spread is highly contagious and concealed. Environmental vectors play an important role in viral infection and transmission, which brings new difficulties and challenges to disease prevention and control. In this paper, a type of differential equation model is constructed according to the spreading functions and characteristics of exposed individuals and environmental vectors during the virus infection process. In the proposed model, five compartments were considered, namely, susceptible individuals, exposed individuals, infected individuals, recovered individuals, and environmental vectors (contaminated with free virus particles). In particular, the re-positive factor was taken into account (i.e., recovered individuals who have lost sufficient immune protection may still return to the exposed class). With the basic reproduction number R0 of the model, the global stability of the disease-free equilibrium and uniform persistence of the model were completely analyzed. Furthermore, sufficient conditions for the global stability of the endemic equilibrium of the model were also given. Finally, the effective predictability of the model was tested by fitting COVID-19 data from Japan and Italy.

Stability analysis of the COVID-19 model with age structure under media effect

The spread and control of infectious diseases are inevitably influenced by the age structure of the population and media effect. In this paper, we propose a susceptible-exposure-infection-recovery type age-structured COVID-19 model with media effect. First, the existence and uniqueness of the solution are obtained using semigroup theory and the positive operator method. The basic regeneration number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{0}$$\end{document} R 0 is computed next and the globally asymptotical stability of the disease-free steady state, as well as the locally asymptotical stability of endemic steady state is studied without any extra conditions. The influence of media effect and age structure of the population on disease transmission are also verified by numerical simulations. Our result show that additional intensity of media broadcasts not only reduces the peak of disease outbreak but also shortens the duration of the epidemic. Further more, the proportion of infected adolescents is lower, and adults should pay more attention to self-protection.

Coupling an individual adaptive-decision model with a SIRV model of influenza vaccination reveals new insights for epidemic control

Past seasonal influenza epidemics and vaccination experience may affect individuals' decisions on whether to be vaccinated or not, decisions that may be constantly reassessed in relation to recent influenza related experience. To understand the potentially complex interaction between experience and decisions and whether the vaccination rate is likely to reach a critical coverage level or not, we construct an adaptive-decision model. This model is then coupled with an influenza vaccination dynamics (SIRV) model to explore the interaction between individuals' decision-making and an influenza epidemic. Nonlinear least squares estimation is used to obtain the best-fit parameter values in the SIRV model based on data on new influenza-like illness (ILI) cases in Texas. Uncertainty and sensitivity analyses are then carried out to determine the impact of key parameters of the adaptive decision-making model on the ILI epidemic. The results showed that the necessary critical coverage rate of ILI vaccination could not be reached by voluntary vaccination. However, it could be reached in the fourth year if mass media reports improved individuals' memory of past vaccination experience. Individuals' memory of past vaccination experience, the proportion with histories of past vaccinations and the perceived cost of vaccination are important factors determining whether an ILI epidemic can be effectively controlled or not. Therefore, health authorities should guide people to improve their memory of past vaccination experience through media reports, publish timely data on annual vaccination proportions and adjust relevant measures to appropriately reduce vaccination perceived cost, in order to effectively control an ILI epidemic.

Dynamic analysis and optimal control of a class of SISP respiratory diseases

In this paper, the actual background of the susceptible population being directly patients after inhaling a certain amount of PM2.5 is taken into account. The concentration response function of PM2.5 is introduced, and the SISP respiratory disease model is proposed. Qualitative theoretical analysis proves that the existence, local stability and global stability of the equilibria are all related to the daily emission P0 of PM2.5 and PM2.5 pathogenic threshold K. Based on the sensitivity factor analysis and time-varying sensitivity analysis of parameters on the number of patients, it is found that the conversion rate β and the inhalation rate η has the largest positive correlation. The cure rate γ of infected persons has the greatest negative correlation on the number of patients. The control strategy formulated by the analysis results of optimal control theory is as follows: The first step is to improve the clearance rate of PM2.5 by reducing the PM2.5 emissions and increasing the intensity of dust removal. Moreover, such removal work must be maintained for a long time. The second step is to improve the cure rate of patients by being treated in time. After that, people should be reminded to wear masks and go out less so as to reduce the conversion rate of susceptible people becoming patients.

Influenza surveillance systems using traditional and alternative sources of data: A scoping review

OBJECTIVE

While the World Health Organization's recommendation of syndromic sentinel surveillance for influenza is an efficient method to collect high-quality data, limitations exist. Aligned with the Research Recommendation 1.1.2 of the WHO Public Health Research Agenda for Influenza-to identify reliable complementary influenza surveillance systems which provide real-time estimates of influenza activity-we performed a scoping review to map the extent and nature of published literature on the use of non-traditional sources of syndromic surveillance data for influenza.

METHODS

We searched three electronic databases (PubMed, Web of Science, and Scopus) for articles in English, French, and Spanish, published between January 1 2007 and January 28 2022. Studies were included if they directly compared at least one non-traditional with a traditional influenza surveillance system in terms of correlation in activity or timeliness.

FINDINGS

We retrieved 823 articles of which 57 were included for analysis. Fifteen articles considered electronic health records (EHR), 11 participatory surveillance, 10 online searches and webpage traffic, seven Twitter, five absenteeism, four telephone health lines, three medication sales, two media reporting, and five looked at other miscellaneous sources of data. Several articles considered more than one non-traditional surveillance method.

CONCLUSION

We identified eight categories and a miscellaneous group of non-traditional influenza surveillance systems with varying levels of evidence on timeliness and correlation to traditional surveillance systems. Analyses of EHR and participatory surveillance systems appeared to have the most agreement on timeliness and correlation to traditional systems. Studies suggested non-traditional surveillance systems as complements rather than replacements to traditional systems.

Analysis of a diffusive epidemic system with spatial heterogeneity and lag effect of media impact

We considered an SIS functional partial differential model cooperated with spatial heterogeneity and lag effect of media impact. The wellposedness including existence and uniqueness of the solution was proved. We defined the basic reproduction number and investigated the threshold dynamics of the model, and discussed the asymptotic behavior and monotonicity of the basic reproduction number associated with the diffusion rate. The local and global Hopf bifurcation at the endemic steady state was investigated theoretically and numerically. There exists numerical cases showing that the larger the number of basic reproduction number, the smaller the final epidemic size. The meaningful conclusion generalizes the previous conclusion of ordinary differential equation.

Complex dynamics of an epidemic model with saturated media coverage and recovery

During the outbreak of emerging infectious diseases, media coverage and medical resource play important roles in affecting the disease transmission. To investigate the effects of the saturation of media coverage and limited medical resources, we proposed a mathematical model with extra compartment of media coverage and two nonlinear functions. We theoretically and numerically investigate the dynamics of the proposed model. Given great difficulties caused by high nonlinearity in theoretical analysis, we separately considered subsystems with only nonlinear recovery or with only saturated media impact. For the model with only nonlinear recovery, we theoretically showed that backward bifurcation can occur and multiple equilibria may coexist under certain conditions in this case. Numerical simulations reveal the rich dynamic behaviors, including forward-backward bifurcation, Hopf bifurcation, saddle-node bifurcation, homoclinic bifurcation and unstable limit cycle. So the limitation of medical resources induces rich dynamics and causes much difficulties in eliminating the infectious diseases. We then investigated the dynamics of the system with only saturated media impact and concluded that saturated media impact hardly induces the complicated dynamics. Further, we parameterized the proposed model on the basis of the COVID-19 case data in mainland China and data related to news items, and estimated the basic reproduction number to be 2.86. Sensitivity analyses were carried out to quantify the relative importance of parameters in determining the cumulative number of infected individuals at the end of the first month of the outbreak. Combining with numerical analyses, we suggested that providing adequate medical resources and improving media response to infection or individuals' response to mass media may reduce the cumulative number of the infected individuals, which mitigates the transmission dynamics during the early stage of the COVID-19 pandemic.

Factor Structures of Patient Health Questionnaire-9 Instruments in Exploring Depressive Symptoms of Suburban Population

BACKGROUND

This study aims to examine the psychometric properties of the nine-item Patient Health Questionnaire (PHQ-9) and assess the relationship between the PHQ-9 domain and demographics and health behaviors in Vietnamese people.

MATERIALS AND METHODS

The PHQ9 was administered to 899 participants. Exploratory factor and reliability analyses were performed. Tobit regression and Ordered logistic regression were further performed to determine factors associated with the PHQ-9 score and characteristics of depression.

RESULTS

The 2-factor model of PHQ-9, including factor 1 "Somatic" and factor 2 "Cognitive/Affective," showed good psychometric properties. The Cronbach's alpha value showed high internal consistency in two factors (0.84 and 0.80, respectively). Gender, health behavior exercising, drinking, and health status had associations with both factors of the PHQ-9 model.

CONCLUSION

The PHQ-9 scale is a valid and reliable instrument to assess depression in the Vietnam population. This scale can be a useful screening tool for depression; however, further validation studies in other populations are required.

Evaluating the impacts of non-pharmaceutical interventions on the transmission dynamics of COVID-19 in Canada based on mobile network

The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada's provinces since it was first reported more than a year ago. During the COVID-19 epidemic, Canadian provinces have implemented many Non-Pharmaceutical Interventions (NPIs). However, the spread of the COVID-19 epidemic continues due to the complex dynamics of human mobility. We develop a meta-population network model to study the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies in different provinces of Canada, such as the timing of implementing NPIs, the human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences due to work and recreation. To determine which activity is most closely related to the dynamics of COVID-19, we use the cross-correlation analysis to find that the positive correlation is the highest between the mobility data of parks and the weekly number of confirmed COVID-19 from February 15 to December 13, 2020. The average effective reproduction numbers in nine Canadian provinces are all greater than one during the time period, and NPIs have little impact on the dynamics of COVID-19 epidemics in Ontario and Saskatchewan. After November 20, 2020, the average infection probability in Alberta became the highest since the start of the COVID-19 epidemic in Canada. We also observe that human activities around residences do not contribute much to the spread of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human mobility is effective in mitigating COVID-19 transmission in Canada. Our findings can provide guidance for public health authorities in projecting the effectiveness of future NPIs.

The effect of public health awareness and behaviors on the transmission dynamics of syphilis in Northwest China, 2006-2018, based on a multiple-stages mathematical model

Syphilis, a sexually transmitted infectious disease caused by the bacterium treponema pallidum, has re-emerged as a global public health issue with an estimated 12 million people infected each year. Understanding the impacts of health awareness and behaviors on transmission dynamics of syphilis can help to establish optimal control strategy in different regions. In this paper, we develop a multiple-stage SIRS epidemic model taking into account the public health awareness and behaviors of syphilis. First, the basic reproduction number R0 is obtained, which determines the global dynamics behaviors of the model. We derive the necessary conditions for implementing optimal control and the corresponding optimal solution for mitigation syphilis by using Pontryagin's Maximum Principle. Based on the data of syphilis in Ningxia from 2006 to 2018, the parameterizations and model calibration are carried out. The fitting results are in good agreement with the data. Moreover, sensitivity analysis shows that the public awareness induced protective behaviors C_e, compliance of condom-induced preventability ε and treatment for the primary syphilis m₁ play an important role in mitigating the risk of syphilis outbreaks. These results can help us gain insights into the epidemiology of syphilis and provide guidance for the public health authorities to implement health education programs.

Media bias exposure and the incidence of COVID-19 in the USA

The role of the media as a source of reliable health information during the COVID-19 pandemic has come under intense scrutiny, with claims of misinformation and partisanship coming from all sides of the political divide. This paper seeks to understand the relationship between exposure to biased media outlets and the likelihood of testing positive for COVID-19 in the USA. I use detailed household data extracted from the 2020 American National Election Study in order to gauge media consumption patterns, coupled with data on media bias scores for different outlets and programmes. I combine these variables to compute media bias exposure values for each respondent, and relate these to the likelihood of a positive COVID-19 test within each respondent’s household, controlling for a variety of other factors including partisanship, social media use, trust in the media and several socioeconomic and demographic variables. The results indicate that media bias exposure is significantly related to COVID-19 incidence, and in particular the coefficients show that a 1% increase in exposure to left-wing media is associated with a 0.2% decrease in the probability of a positive COVID-19 test. Conversely, I find no significant relationship between right-wing media exposure and COVID-19 infection rates. I also find a significantly higher likelihood of contracting COVID-19 among low socioeconomic status households, suggesting a disproportionate impact of the pandemic on such cohorts. These findings are robust to a number of tests, and emphasise the importance of aligning media messages with those advocated by leading medical experts during public health crises.

Mental Health Issues in the COVID-19 Pandemic and Responses in Bangladesh: View Point of Media Reporting

Background: The negative impact of COVID-19 on mental health has been reported by media throughout the world, although this role is not well-understood in low-and middle-income countries (LMIC). We examined the reporting of mental health issues during the COVID-19 pandemic in Bangladesh and initiatives undertaken to support mental health reported from the viewpoint of media. Methods: We reviewed articles published in 10 local newspapers, including seven Bangla and three English newspapers, during the first year of the COVID-19 pandemic. News topics were identified through discussions among the team members, with searches across online newspapers and portals. Data extrapolated from newspapers were documented in an Excel spreadsheet. A mixed-method approach was used following a framework analysis for analyzing data. Recurring issues and commonly emerging topics were generated from the data. Descriptive statistics were applied for analyzing quantitative data. Results: Between March 2020 and March 2021, we have identified 201 reports on mental health issues including 45 reports (22.4%) focused on stress due to the associated financial crisis, unemployment and loneliness, 50 reports (24.9%) of 80 apparent suicides linked to family issues, disharmony in conjugal relationships, harassment, sexual violence, emotional breakdown, financial crisis, and stigma due to COVID-19.There were 77 reports (38.3%) concerning domestic violence during the pandemic. Twenty-nine reports (14.4%) referenced actions taken by different organizations to address mental health issues in response to the pandemic in Bangladesh. Conclusion: News coverage has the scope to highlight important issues that can emerge as a consequence of the COVID-pandemic, such as mental health, in a low resource setting. Capacity building of the media on the way to report mental health issues during emergency situations could be a useful strategy for more credible reporting on mental health issues during the COVID-19 pandemic for raising awareness of the public and policymakers about the negative consequences on mental health of the COVID-19 pandemic in Bangladesh. Adopting policies to support essential mental health care and promoting the local organizations to take timely public health measures will be imperative for averting the negative consequences of mental health due to the COVID-19 pandemic in Bangladesh.

Symbolic annihilation of Syrian refugees by Turkish news media during the COVID-19 pandemic

BACKGROUND

This article presents a discussion about the representation of Syrian refugees in Turkish news media during the COVID-19 pandemic. Media play a critical role during pandemics by affecting values, opinions, public knowledge about stigmatized groups. When media ignore and stereotypically represent a social group, the social value of the group decreases, and their problems are trivialized.

METHOD

I analyzed data provided by Media Monitoring Center which is an independent media company in Turkey. Sample was selected to reveal news representation of Syrian refugees between March 11, 2020 (the first confirmed case of COVID-19 in Turkey) and August 20, 2020 (the time of this research). Mostly watched television evening (prime) news, the most widely circulated newspapers, and the most visited online news platforms were analyzed. By using content analysis method, the news stories about Syrian refugees were examined.

RESULTS

It has been revealed that Turkish news media overwhelmingly acclaimed for Turkey's polices on Syrian refugees and the criticized the European Union policies towards refugees in the news stories. Even though almost 4 million Syrian refugees live in Turkey, with the largest refugee population in the world, Turkish news media ignored the plight of Syrian refugees.

CONCLUSION

Results of the study demonstrate that Syrian refugees were symbolically annihilated by Turkish news media during the COVID-19 pandemic. The concealment of information and symbolic annihilation of disadvantaged groups could potentially cause health disparities and irreparable harm to public health. Moreover, inequities exacerbate when predicaments of stigmatized groups are ignored in the news media. Further studies are needed to reveal the impact of the media on health disparities among stigmatized groups during the pandemics.

Linking the disease transmission to information dissemination dynamics: An insight from a multi-scale model study

During the outbreak of emerging infectious diseases, information dissemination dynamics significantly affects the individuals’ psychological and behavioral changes, and consequently influences on the disease transmission. To investigate the interaction of disease transmission and information dissemination dynamics, we proposed a multi-scale model which explicitly models both the disease transmission with saturated recovery rate and information transmission to evaluate the effect of information transmission on dynamic behaviors. Considering time variation between information dissemination, epidemiological and demographic processes, we obtained a slow-fast system by reasonably introducing a sufficiently small quantity. We carefully examined the dynamics of proposed system, including existence and stability of possible equilibria and existence of backward bifurcation, by using the fast-slow theory and directly investigating the full system. We then compared the dynamics of the proposed system and the essential thresholds based on two methods, and obtained the similarity between the basic dynamical behaviors of the slow system and that of the full system. Finally, we parameterized the proposed model on the basis of the COVID-19 case data in mainland China and data related to news items, and estimated the basic reproduction number to be 3.25. Numerical analysis suggested that information transmission about COVID-19 pandemic caused by media coverage can reduce the peak size, which mitigates the transmission dynamics during the early stage of the COVID-19 pandemic.

Stochastic analysis of COVID-19 by a SEIR model with Lévy noise

We propose a Lévy noise-driven susceptible-exposed-infected-recovered model incorporating media coverage to analyze the outbreak of COVID-19. We conduct a theoretical analysis of the stochastic model by the suitable Lyapunov function, including the existence and uniqueness of the positive solution, the dynamic properties around the disease-free equilibrium and the endemic equilibrium; we deduce a stochastic basic reproduction number R₀ ^s for the extinction of disease, that is, if R₀ ^s≤1, the disease will go to extinction. Particularly, we fit the data from Brazil to predict the trend of the epidemic. Our main findings include the following: (i) stochastic perturbation may affect the dynamic behavior of the disease, and larger noise will be more beneficial to control its spread; (ii) strengthening social isolation, increasing the cure rate and media coverage can effectively control the spread of disease. Our results support the feasible ways of containing the outbreak of the epidemic.

Associations between COVID-19 related media consumption and symptoms of anxiety, depression and COVID-19 related fear in the general population in Germany

In context of the current COVID-19 pandemic the consumption of pandemic-related media coverage may be an important factor that is associated with anxiety and psychological distress. Aim of the study was to examine those associations in the general population in Germany. 6233 participants took part in an online-survey (March 27th-April 6th, 2020), which included demographic information and media exploitation in terms of duration, frequency and types of media. Symptoms of depression, unspecific anxiety and COVID-19 related anxiety were ascertained with standardized questionnaires. Frequency, duration and diversity of media exposure were positively associated with more symptoms of depression and unspecific and COVID-19 specific anxiety. We obtained the critical threshold of seven times per day and 2.5 h of media exposure to mark the difference between mild and moderate symptoms of (un)specific anxiety and depression. Particularly the usage of social media was associated with more pronounced psychological strain. Participants with pre-existing fears seem to be particularly vulnerable for mental distress related to more immoderate media consumption. Our findings provide some evidence for problematical associations of COVID-19 related media exposure with psychological strain and could serve as an orientation for recommendations-especially with regard to the thresholds of critical media usage.

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

Media reports can modify people's knowledge of emerging infectious diseases, and thus changing the public attitudes and behaviors. However, how the media reports affect the development of COVID-19 epidemic is a key public health issue. Here the Pearson correlation and cross-correlation analyses are conducted to find the statistically significant correlations between the number of new hospital notifications for COVID-19 and the number of daily news items for twelve major websites in China from January 11th to February 6th 2020. To examine the implication for transmission dynamics of these correlations, we proposed a novel model, which embeds the function of individual behaviour change (media impact) into the intensity of infection. The nonlinear least squares estimation is used to identify the best-fit parameter values in the model from the observed data. To determine impact of key parameters with media impact and control measures for the later outcome of the outbreak, we also carried out the uncertainty and sensitivity analyses. These findings confirm the importance of the responses of individuals to the media reports, and the crucial role of experts and governments in promoting the public under self-quarantine. Therefore, for mitigating epidemic COVID-19, the media publicity should be focused on how to guide people's behavioral changes by experts, and the management departments and designated hospitals of the COVID-19 should take effective quarantined measures, which are critical for the control of the disease.

Role of Mass Media and Public Health Communications in the COVID-19 Pandemic

In Dec 2019, a novel pathogen emerged, and within weeks, led to the emergence of the biggest global health crises seen to date. The virus called 'SARS-CoV-2', causes coronavirus disease which was named 'COVID-19' by the World Health Organization (WHO). The speedy spread of this infection globally became a source of public worry and several unknowns regarding this new pathogen created a state of panic. Mass media became the major source of information about the novel coronavirus. Much like the previous pandemics of SARS (2003), H1N1 (2009), and MERS (2012), the media significantly contributed to the COVID-19 infodemics. In this review, we analyze the role of mass media and public health communications from December 31, 2019 to July 15, 2020, and make scientific inferences. The COVID-19 pandemic highlights multiple social, cultural, and economic issues arising from the media's arguable role. The racial prejudices linked to the origin of the virus prevented collaborations among scientists to find a solution. Media coverage of coronavirus news during geographical lockdowns, extended quarantines, and financial and social hardships induced fear and caused psychological stress. Domestic and elderly abuse upsurged. The unscientific cures and unverified medicines endorsed by the politicians and fake doctors proved harmful. The media played a worldwide role in coronavirus disease tracking and updates through live updates dashboard. The media allowed for timely interventions by the Center For Disease Control And Prevention (CDC) and the World Health Organization (WHO), enabling a rapid and widespread reach of public health communications. We saw an upward trend for the promotion of health and hygiene practices worldwide by adaption of safe health practices such as increased hand washing, use of face coverings, and social distancing. Media reinforced illness-preventing guidelines daily, and people were encouraged to use telehealth to meet their healthcare needs. Mass media has an imperative role in today's world and it can provide a unified platform for all public health communications, comprehensive healthcare education guidelines, and robust social distancing strategies while still maintaining social connections. It can enable equal access to healthcare, end discrimination, and social stigmatization. The role of media and public health communications must be understood and explored further as they will be an essential tool for combating COVID-19 and future outbreaks.

The Association of Media and Environmental Variables with Transit Ridership

Transportation systems are central to all cities, and city planners and policy makers take special interest in assuring these systems are efficient, functional, sustainable, and, increasingly, that they have a positive impact on human health. In addition, vehicular emissions are increasingly costly to cities due to congestion and its impact on public health. This study aims to show the associations between the media and environmental variables and associated transit ridership. By tracking media influence, we illustrated how media coverage and attention to an issue over time may impact public opinion and ridership outcomes, especially at the local level where the issues are most salient. The relationship between air quality and transit ridership shown can be generally explained through a combination of infrastructure and human behavior. The media key terms examined in this analysis show that ridership is associated with favorable weather conditions and air quality, suggesting that ridership volume may be influenced by an overall sense of comfort and safety. Based on this analysis, we illustrated the role of media attention in both increased and decreased transit ridership and how such effects are compounded by air quality conditions (e.g., green, yellow, orange, and red air quality days).

The impact of media on the spatiotemporal pattern dynamics of a reaction-diffusion epidemic model

In this paper, a reaction-diffusion SI epidemic model with media impact is considered. The boundedness of system and the existence of the state are given. The local stabilities of the endemic states are analyzed. Sufficient conditions of the occurrence of the Turing pattern are obtained by the center manifold theorem and normal form method. Some numerical simulations are given to check in the theoretical results. We find that the influence of media not only inhibits the spread of infectious diseases, but also effects the spatial steady-state of model.

Coverage of Health Information by Different Sources in Communities: Implication for COVID-19 Epidemic Response

Health personnel and community workers are at the front line of the COVID-19 emergency response and need to be equipped with adequate knowledge related to epidemics for an effective response. This study aimed to identify the coverage of COVID-19 health information via different sources accessed by health workers and community workers in Vietnam. A cross-sectional study using a web-based survey was carried out from January to February 2020 in Vietnam. Respondent-driven sampling (RDS) was used for recruiting participants. We utilized the exploratory factor analysis (EFA) to examine the construct validity of the questionnaire. A higher percentage of participants knew about "Clinical and pathogen characteristics of COVID-19", compared to "Regulations and policies related to COVID-19". The percentage of participants accessing the information on "Guidelines and policies on prevention and control of COVID-19" was the lowest, especially among medical students. "Mass media and peer-educators" channels had a higher score of accessing COVID-19 information, compared to "Organizations/ agencies/ associations" sources. Participants consumed most of their COVID-19 information via "Internet, online newspapers, social networks". Our findings indicate an urgency to re-design training programs and communication activities for a more effective dissemination of information related to the COVID-19 epidemic or epidemics in general.

Dynamic modelling of the impact of public health education on the control of emerging infectious disease

Public health education, including mass and interpersonal communication, has been recognized as an effective control of infectious disease. Compared to the well-studied mass communication by dynamic modelling, not much mathematical study has been done on the effect of interpersonal communication. Here, we build a model, to study the overall impact of mass communication and interpersonal communication on disease spread and disease control during the transmission process. By analysing the dynamic behaviour of our model, we find two threshold parameters on which the disease persistence and extinction condition depend. We further prove that the endemic equilibrium, whenever existing, is locally asymptotically stable. Its global stability is also verified. And the impact of public health education on the behaviours of the model is considered by numerical simulation. Our study confirms the value of various education activities and shows that public health education may affect the epidemic threshold.

The fertility-inhibiting effect of mosquitoes: Socio-economic differences in response to the Zika crisis in Colombia

We estimated the impact of the Zika virus outbreak on birth rates and demand for health care services in Colombia. Our analysis exploits the variation in the level of natural protection against mosquito-transmitted diseases across the country. This characteristic induced exogenous variation in Zika incidence, which allows us to construct a control group of municipalities with similar historical fertility trends but with differential exposure to the Zika crisis. We implemented a difference-in-differences model after matching, as well as synthetic control. We found a decrease in birth rates of approx. 10% in the last two quarters of 2019. The impact of the virus was similar irrespective of the women's education level, and we found no discernible impact on teenage pregnancy.

Just Google it! Impact of media coverage of an outbreak of high-level azithromycin-resistant Neisseria gonorrhoeae on online searches, and attendances, testing and diagnoses at sexual health clinics in England between 2015 and 2016: an interrupted time series analysis using surveillance data

OBJECTIVES

To determine if media coverage of an outbreak of high-level azithromycin-resistant Neisseria gonorrhoeae (HL-AziR) impacted online search interest or was temporally associated with health-seeking behaviours in several English cities.

METHODS

A descriptive analysis of outbreak-related online media articles and relative search interest (RSI) using Google and an interrupted time series analysis using routine surveillance data from sexual health clinics (SHCs) in England (GUMCAD STI surveillance system). The main outcomes were adjusted incidence rate ratios (IRRs) of weekly attendances, gonorrhoea tests and diagnoses of gonorrhoea or 'any STI' in selected cities after media coverage of the outbreak in 2015 and 2016.

RESULTS

RSI for outbreak-related terms peaked during media coverage in September 2015 with smaller peaks coinciding with subsequent coverage. The greatest increase in RSI was in Leeds, which coincided with a 63% rise (n=1932; IRR 1.26, 95% CI 1.12 to 1.43) in SHC attendances by women. There was only a 7% (n=1358; IRR 1.01, 95% CI 0.91 to 1.11) increase in attendances by men. Modest increases in outcomes occurred in four other cities with a high RSI. There was no evidence of increases in outcomes in cities, other than Leeds, after subsequent media coverage of the outbreak.

CONCLUSIONS

National and local media coverage of the HL-AziR outbreak coincided with peak RSI for related terms, and a transient increase in attendances, gonorrhoea tests and diagnoses of gonorrhoea or 'any STI' in some cities with a high RSI. Our analysis demonstrates the potential for media coverage to influence health-seeking behaviours during high-profile STI outbreaks.

Optimal media reporting intensity on mitigating spread of an emerging infectious disease

Mass media reports can induce individual behaviour change during a disease outbreak, which has been found to be useful as it reduces the force of infection. We propose a compartmental model by including a new compartment of the intensity of the media reports, which extends existing models by considering a novel media function, which is dependent both on the number of infected individuals and on the intensity of mass media. The existence and stability of the equilibria are analyzed and an optimal control problem of minimizing the total number of cases and total cost is considered, using reduction or enhancement in the media reporting rate as the control. With the help of Pontryagin's Maximum Principle, we obtain the optimal media reporting intensity. Through parameterization of the model with the 2009 A/H1N1 influenza outbreak data in the 8th Hospital of Xi'an in Shaanxi Province of China, we obtain the basic reproduction number for the formulated model with two particular media functions. The optimal media reporting intensity obtained here indicates that during the early stage of an epidemic we should quickly enhance media reporting intensity, and keep it at a maximum level until it can finally weaken when epidemic cases have decreased significantly. Numerical simulations show that media impact reduces the number of cases during an epidemic, but that the number of cases is further mitigated under the optimal reporting intensity. Sensitivity analysis implies that the outbreak severity is more sensitive to the weight α1 (weight of media effect sensitive to infected individuals) than weight α2 (weight of media effect sensitive to media items).

Analysis of an Epidemic System with Two Response Delays in Media Impact Function

A functional differential model of SEIS-M type with two time delays, representing the response time for mass media to cover the current infection and for individuals' behavior changes to media coverage, was proposed to examine the delayed media impact on the transmission dynamics of emergent infectious diseases. The threshold dynamics were established in terms of the basic reproduction number [Formula: see text]. When there are no time delays, we showed that if the media impact is low, the endemic equilibrium is globally asymptotically stable for [Formula: see text], while the endemic equilibrium may become unstable and Hopf bifurcation occurs for some appropriate conditions by taking the level of media impact as bifurcation parameter. With two time delays, we comprehensively investigated the local and global bifurcation by considering the summation of delays as a bifurcation parameter, and theoretically and numerically examined the onset and termination of Hopf bifurcations from the endemic equilibrium. Main results show that either the media described feedback cycle, from infection to the level of mass media and back to disease incidence, or time delays can induce Hopf bifurcation and result in periodic oscillations. The findings indicate that the delayed media impact leads to a richer dynamics that may significantly affect the disease infections.

The effect of media coverage on threshold dynamics for a stochastic SIS epidemic model

Media coverage is one of the important measures for controlling infectious diseases, but the effect of media coverage on diseases spreading in a stochastic environment still needs to be further investigated. Here, we present a stochastic susceptible-infected-susceptible (SIS) epidemic model incorporating media coverage and environmental fluctuations. By using Feller's test and stochastic comparison principle, we establish the stochastic basic reproduction number R 0 s , which completely determines whether the disease is persistent or not in the population. If R 0 s ≤ 1 , the disease will go to extinction; if R 0 s = 1 , the disease will also go to extinction in probability, which has not been reported in the known literatures; and if R 0 s > 1 , the disease will be stochastically persistent. In addition, the existence of the stationary distribution of the model and its ergodicity are obtained. Numerical simulations based on real examples support the theoretical results. The interesting findings are that (i) the environmental fluctuation may significantly affect the threshold dynamical behavior of the disease and the fluctuations in different size scale population, and (ii) the media coverage plays an important role in affecting the stationary distribution of disease under a low intensity noise environment.

A Filippov model describing the effects of media coverage and quarantine on the spread of human influenza

Mass-media reports on an epidemic or pandemic have the potential to modify human behaviour and affect social attitudes. Here we construct a Filippov model to evaluate the effects of media coverage and quarantine on the transmission dynamics of influenza. We first choose a piecewise smooth incidence rate to represent media reports being triggered once the number of infected individuals exceeds a certain critical level [Formula: see text] . Further, if the number of infected cases increases and exceeds another larger threshold value [Formula: see text] ( [Formula: see text] ), we consider that the incidence rate tends to a saturation level due to the protection measures taken by individuals; meanwhile, we begin to quarantine susceptible individuals when the number of susceptible individuals is larger than a threshold value S_c. Then, for each susceptible threshold value S_c, the global properties of the Filippov model with regard to the existence and stability of all possible equilibria and sliding-mode dynamics are examined, as we vary the infected threshold values [Formula: see text] and [Formula: see text] . We show generically that the Filippov system stabilizes at either the endemic equilibrium of the subsystem or the pseudoequilibrium on the switching surface or the endemic equilibrium [Formula: see text] depending on the choice of the threshold values. The findings suggest that proper combinations of infected and susceptible threshold values can maintain the number of infected individuals either below a certain threshold level or at a previously given level.

Impact of individual behaviour change on the spread of emerging infectious diseases

Human behaviour plays an important role in the spread of emerging infectious diseases, and understanding the influence of behaviour changes on epidemics can be key to improving control efforts. However, how the dynamics of individual behaviour changes affects the development of emerging infectious disease is a key public health issue. To develop different formula for individual behaviour change and introduce how to embed it into a dynamic model of infectious diseases, we choose A/H1N1 and Ebola as typical examples, combined with the epidemic reported cases and media related news reports. Thus, the logistic model with the health belief model is used to determine behaviour decisions through the health belief model constructs. Furthermore, we propose 4 candidate infectious disease models without and with individual behaviour change and use approximate Bayesian computation based on sequential Monte Carlo method for model selection. The main results indicate that the classical compartment model without behaviour change and the model with average rate of behaviour change depicted by an exponential function could fit the observed data best. The results provide a new way on how to choose an infectious disease model to predict the disease prevalence trend or to evaluate the influence of intervention measures on disease control. However, sensitivity analyses indicate that the accumulated number of hospital notifications and deaths could be largely reduced as the rate of behaviour change increases. Therefore, in terms of mitigating emerging infectious diseases, both media publicity focused on how to guide people's behaviour change and positive responses of individuals are critical.

Global hopf bifurcation of a delayed equation describing the lag effect of media impact on the spread of infectious disease

We proposed a delay differential model, associated with the response time for individuals to the current infection, to examine the media impact on the transmission dynamics of infectious diseases. We investigated the global bifurcation by considering the delay as a bifurcation parameter and examined the onset and termination of Hopf bifurcations from a positive equilibrium. Numerical studies to identify ranges of parameters for coexisting multiple periodic solutions are guided by the bifurcation analysis and the Matlab package DDE-BIFTOOL developed by Engelborghs et al. Further, we parameterized the proposed model on the basis of the 2009 A/H1N1 pandemic influenza data in Shaanxi province, China, and estimated the basic reproduction number to be 1.79 [95% CI (1.77-1.80)] and the time delay to be 2.94 days [95% CI (2.56-3.24)]. Our main results indicated that media impact with time delay significantly influenced the transmission dynamics of infectious diseases.