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

Final epidemic size and optimal control of socio-economic multi-group influenza model

Flu, a common respiratory disease is caused mainly by the influenza virus. The Avian influenza (H5N1) outbreaks, as well as the 2009 H1N1 pandemic, have heightened global concerns about the emergence of a lethal influenza virus capable of causing a catastrophic pandemic. During the early stages of an epidemic a favourable change in the behaviour of people can be of utmost importance. An economic status-based (higher and lower economic class) structured model is formulated to examine the behavioural effect in controlling influenza. Following that, we have introduced controls into the model to analyse the efficacy of antiviral treatment in restraining infections in both economic classes and examined an optimal control problem. We have obtained the reproduction number R 0 along with the final epidemic size for both the strata and the relation between reproduction number and epidemic size. Through numerical simulation and global sensitivity analysis, we have shown the importance of the parameters ϕ i , ϕ s , η 2 , β and θ on reproduction number. Our result shows that by increasing ϕ 1 , η 2 and by decreasing β , θ and ϕ s , we can reduce the infection in both the economic group. As a result of our analysis, we have found that the reduction of infections and their level of adversity is directly influenced by positive behavioural patterns or changes as without control susceptible population is increased by 23 % , the infective population is decreased by 48.54 % and the recovered population is increased by 23.23 % in the higher economic group who opted changed behaviour as compared to the lower the economic group (people living with normal behaviour). Thus normal behaviour contributes to the spread and growth of viruses and adds to the hassle. We also examined how antiviral drug control impacts both economic strata and found that in the higher economic strata, the susceptible population increased by 53.84 % , the infective population decreased by 33.6 % and the recovered population improved by 62.29 % as compared to the lower economic group, the susceptible population has increased by 19.04 % , the infective population is decreased by 17.29 % and the recovered population is improved by 47.82 % . Our results enlighten the role that how different behaviour in separate socio-economic class plays an important role in changing the dynamics of the system and also affects the basic reproduction number. The results of our study suggest that it is important to adopt a modified behaviour like social distancing, wearing masks accompanying the time-dependent controls in the form of an antiviral drug's effectiveness to combat infections and increasing the proportion of the susceptible population.

A case-crossover study of the effect of vaccination on SARS-CoV-2 transmission relevant behaviours during a period of national lockdown in England and Wales

BACKGROUND

Studies of COVID-19 vaccine effectiveness show increases in COVID-19 cases within 14 days of a first dose, potentially reflecting post-vaccination behaviour changes associated with SARS-CoV-2 transmission before vaccine protection. However, direct evidence for a relationship between vaccination and behaviour is lacking. We aimed to examine the association between vaccination status and self-reported non-household contacts and non-essential activities during a national lockdown in England and Wales.

METHODS

Participants (n = 1154) who had received the first dose of a COVID-19 vaccine reported non-household contacts and non-essential activities from February to March 2021 in monthly surveys during a national lockdown in England and Wales. We used a case-crossover study design and conditional logistic regression to examine the association between vaccination status (pre-vaccination vs 14 days post-vaccination) and self-reported contacts and activities within individuals. Stratified subgroup analyses examined potential effect heterogeneity by sociodemographic characteristics such as sex, household income or age group.

RESULTS

457/1154 (39.60 %) participants reported non-household contacts post-vaccination compared with 371/1154 (32.15 %) participants pre-vaccination. 100/1154 (8.67 %) participants reported use of non-essential shops or services post-vaccination compared with 74/1154 (6.41 %) participants pre-vaccination. Post-vaccination status was associated with increased odds of reporting non-household contacts (OR 1.65, 95 % CI 1.31-2.06, p < 0.001) and use of non-essential shops or services (OR 1.50, 95 % CI 1.03-2.17, p = 0.032). This effect varied between men and women and different age groups.

CONCLUSION

Participants had higher odds of reporting non-household contacts and use of non-essential shops or services within 14 days of their first COVID-19 vaccine compared to pre-vaccination. Public health emphasis on maintaining protective behaviours during this post-vaccination time period when individuals have yet to develop full protection from vaccination could reduce risk of SARS-CoV-2 infection.

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.

Knowledge, attitude, and practice of Bangladeshi urban slum dwellers towards COVID-19 transmission-prevention: A cross-sectional study

The first COVID-19 case in Bangladesh was detected on March 8, 2020. Since then, efforts are being made across the country to raise awareness among the population for preventing the spread of this virus. We aimed to examine the urban slum dwellers' knowledge, attitude, and practice (KAP) towards COVID-19 transmission-prevention. A phone-based cross-sectional survey was conducted in five slums of Dhaka City. Total 476 adult slum dwellers were interviewed between October 31 to December 1, 2020 using a pre-tested questionnaire. During an interview, information was collected on participants' demographic characteristics and KAP items towards COVID-19. We used quartiles for categorization of knowledge and practice score where the first quartile represents poor, the second and third quartiles represent average while the fourth quartile represents good. Attitude score was standardized using z-score and identified as positive and negative attitude. Multiple linear regression models were used separately to identify the socioeconomic predictors of the KAP scores. The results showed that 25% of the respondents had good knowledge and 25% had poor knowledge, 48% had a positive attitude and 52% had a negative attitude, and 21% maintained good practice and 33% maintained poor practice towards COVID-19 transmission-prevention. About 75% respondents relied on television for COVID-19 related information. Regression results showed that knowledge and attitude scores were significantly higher if respondents had primary or secondary and above level of education compared to the uneducated group. Female respondents maintained significantly good practice compared to their male counterparts (β = 6.841; p<0.01). This study has found that one third of the studied slum dwellers maintained poor practice and one fourth had poor knowledge towards COVID-19 transmission-prevention. As KAP domains are significantly correlated, efforts are needed to raise awareness of COVID-19 particularly targeting individuals with average and lower knowledge to improve attitude and practice for the prevention of COVID-19.

Risk Perception Measurement and Influencing Factors of COVID-19 in Medical College Students

Purpose: In China, the coronavirus disease 2019 (COVID-19) pandemic has been under control and entered the normal prevention and control stage. For medical college students, many studies have analyzed their knowledge, risk perception, and prevention behaviors of COVID-19, but only a few pieces of research explore the content structure of COVID-19 risk perception and the influencing factors. This study measured the students' risk perception of COVID-19 and its dimensions and analyzed the influencing factors of risk perception among them.

Methods: The online questionnaire survey was conducted at Hangzhou Medical College in Zhejiang Province among undergraduates and junior college students. A scale was formulated to precisely measure and analyze the COVID-19 risk perception among medical college students. The factors affecting the COVID-19 risk perception in medical college students were analyzed using the multivariate linear regression model.

Results: A total of 810 medical students participated in the survey. Results show that COVID-19 risk perception among medical college students was divided into four dimensions: perceived health threat, perceived severity, perceived controllability, and perceived infection possibility. The results showed that income, education, major, and COVID-19 knowledge were the important factors affecting the COVID-19 risk perception of medical college students. Related factors have different influences on the various dimensions of COVID-19 risk perception. COVID-19 knowledge was significantly related to all dimensions of risk perception.

Conclusion: This study evaluates the content structure of medical college students' risk perception of COVID-19 precisely and related influencing factors. It is necessary to grasp the risk perception, prevention, and control behaviors of medical college students of different backgrounds, education levels, and majors. Further knowledge training should be conducted for students majoring in clinical medicine, especially the pandemic prevention and control measure training to enhance their sense of security at work.

Internal and external drivers for compliance with the COVID-19 preventive measures in Slovenia: The view from general deterrence and protection motivation

The emergence of a pandemic is usually accompanied by different measures–economic, social, preventive, and (self)protective. In the case of the COVID-19, several preventive measures were formally enforced by state authorities in the majority of countries worldwide. Thus, during the COVID-19 pandemic, the intertwining of formal and informal social control could be observed. Hence, in this study a cross-sectional design was chosen to explore the issue in Slovenia. To the best of our knowledge, this research is the first in the current literature to empirically test the general deterrence theory in pandemic circumstances (as external factors predicting individuals’ compliance with the COVID-19 preventive measures). The results suggest an important role of informal punishment, with perceived informal severity being the only statistically significant factor from the general deterrence theory. In contrast to external factors, internal factors play a significantly greater role in promoting people’s self-protective behavior in pandemic circumstances. During the unknown, the uncertain and delicate situations with which people have no previous experience, both personal beliefs about the effectiveness of measures and perceived self-efficacy are more important than fear of formal sanctions.

Predictors of Changes in Travel Behavior during the COVID-19 Pandemic: The Role of Tourists' Personalities

This study investigates travel behavior and psychosocial factors that influence it during the COVID-19 pandemic. In a cross-sectional study, using an online survey, we examined changes in travel behavior and preferences after lifting travel restrictions, and how these changes were influenced by exposure to COVID-19, COVID-19 travel-related risk and severity, personality, fear of travel, coping, and self-efficacy appraisals in the Romanian population. Our results showed that participants traveled less in the pandemic year than the year before-especially group and foreign travel-yet more participants reported individual traveling in their home county during the pandemic period. Distinct types of exposure to COVID-19 risk, as well as cognitive and affective factors, were related to travel behavior and preferences. However, fun-seeking personality was the only major predictor of travel intention, while fear of travel was the only predictor of travel avoidance. Instead, people traveled more cautiously when they perceived more risk of infection at the destination, and had higher levels of fear of travel, but also a high sense of efficacy in controlling the infection and problem-solving capacity. The results suggest that specific information about COVID-19, coping mechanisms, fear of travel, and neuropsychological personality traits may affect travel behavior in the pandemic period.

Impact of COVID-19 pandemic on socio-economic, energy-environment and transport sector globally and sustainable development goal (SDG)

The United Nation's Sustainable Development Goals (SDGs) want to have a peaceful world where human life will be in a safe, healthy, sustainable environment without any inequalities. However, the year 2020 experienced a global pandemic due to COVID-19. This COVID-19 created an adverse impact on human life, economic, environment, and energy and transport sector compared to the pre-COVID-19 scenario. These above-mentioned sectors are interrelated and thus lockdown strategy and stay at home rules to reduce the COVID-19 transmission had a drastic effect on them. With lockdown, all industry and transport sectors were closed, energy demand reduced greatly but the time shift of energy demand had a critical impact on grid and energy generation. Decreased energy demand caused a silver lining with an improved environment. However, drowned economy creating a negative impact on the human mind and financial condition, which at times led to life-ending decisions. Transport sector which faced a financial dip last year trying to coming out from the losses which are not feasible without government aid and a new customer-friendly policy. Sustainable transport and the electric vehicle should take high gear. While people are staying at home or using work from home scheme, building indoor environment must specially be taken care of as a compromised indoor environment affects and increases the risk of many diseases. Also, the energy-efficient building will play a key role to abate the enhanced building energy demand and more generation from renewable sources should be in priority. It is still too early to predict any forecast about the regain period of all those sectors but with vaccination now being introduced and implemented but still, it can be considered as an ongoing process as its final results are yet to be seen. As of now, COVID-19 still continue to grow in certain areas causing anxiety and destruction. With all these causes, effects, and restoration plans, still SDGs will be suffered in great order to attain their target by 2030 and collaborative support from all countries can only help in this time.

Government and social trust vs. hotel response efficacy: A protection motivation perspective on hotel stay intention during the COVID-19 pandemic

Based on protection motivation theory (PMT), this study conceptualizes a research framework to explain and examine customer intentions regarding hotel stays during the COVID-19 pandemic. Data were collected from 700 U.S. consumers via a crowdsourcing website in July 2020. Structural equation modeling was used to analyze the collected data for testing proposed hypotheses. The analytical results showed that the level of threat perceived by customers significantly reduced their intention to stay at a hotel. On the contrary, individual customer response efficacy significantly enhanced their intention to stay at a hotel. Additionally, both government and social trust, as well as hotel response efficacy, were found to significantly increase hotel stay intention by mediating the effects of threat perception and individual response efficacy. To the best of our knowledge, this study is one of the first attempts to apply PMT to explain customer hotel stay intentions during the COVID-19 pandemic.

Effects of masks on the transmission of infectious diseases

In the present paper, based on the conditions that asymptomatic virus carriers are contagious and all symptomatic infected individuals wear masks, we study the impact of wearing masks in the susceptible and the asymptomatic virus carriers on the spread of infectious diseases by developing a differential equation model. At first, we give the existence, uniqueness, boundedness, and positivity of the solution as well as the basic reproduction number R 0 for the established model. Then, for two cases of wearing masks in the susceptible and the asymptomatic virus carriers where the proportion of wearing masks is fixed and the proportion of wearing masks changes with time, the results of the numerical simulation are shown in a series of pictures, and quantitative description of effects of the proportion of the population wearing masks, the protective effect of masks, and the time when they start wearing masks on the epidemic is given. Our results show that under the situation that the proportion of wearing masks is positively related to the confirmed new cases and new deaths, though the proportion will be close to 1 during the high incidence of patients, the effect on controlling the spread of such infectious diseases is far worse than the case of always maintaining a relatively higher proportion (≥0.66) of wearing masks.

COVID-19 early-alert signals using human behavior alternative data

Google searches create a window into population-wide thoughts and plans not just of individuals, but populations at large. Since the outbreak of COVID-19 and the non-pharmaceutical interventions introduced to contain it, searches for socially distanced activities have trended. We hypothesize that trends in the volume of search queries related to activities associated with COVID-19 transmission correlate with subsequent COVID-19 caseloads. We present a preliminary analytics framework that examines the relationship between Google search queries and the number of newly confirmed COVID-19 cases in the United States. We designed an experimental tool with search volume indices to track interest in queries related to two themes: isolation and mobility. Our goal was to capture the underlying social dynamics of an unprecedented pandemic using alternative data sources that are new to epidemiology. Our results indicate that the net movement index we defined correlates with COVID-19 weekly new case growth rate with a lag of between 10 and 14 days for the United States at-large, as well as at the state level for 42 out of 50 states with the exception of 8 states (DE, IA, KS, NE, ND, SD, WV, WY) from March to June 2020. In addition, an increasing caseload was seen over the summer in some southern US states. A sharp rise in mobility indices was followed by a sharp increase, respectively, in the case growth data, as seen in our case study of Arizona, California, Florida, and Texas. A sharp decline in mobility indices is often followed by a sharp decline, respectively, in the case growth data, as seen in our case study of Arizona, California, Florida, Texas, and New York. The digital epidemiology framework presented here aims to discover predictors of the pandemic's curve, which could supplement traditional predictive models and inform early warning systems and public health policies.

Role-playing: an Effective Method for Clinical Novitiate Teaching of Infectious Diseases

OBJECTIVE

This study aims to apply the role-play method of teaching to clinical novitiate teaching of infectious diseases and assess the student feedback and learning effect.

METHODS

The students were randomly divided into a role-playing group (taught using a role-playing method) and a standard group (taught using traditional method). Typical cases of hemorrhagic fever with renal syndrome (HFRS) with fever, hypertensive shock, and oliguria phase overlap as clinical manifestations were selected. Students in the role-playing group underwent pre-class preparation according to a well-designed script and performed the patient's consultation process of suspected HFRS in the classroom, followed by a discussion and questionnaire survey. The standard group underwent routine theory teaching. Teaching efficacy was evaluated by theoretical examination.

RESULTS

The test scores and case analysis ability were higher for students in the role-playing group than in the standard group (p < 0.05). Nearly 90% of the students in the role-playing group gave positive feedback on the role-playing pedagogy and were willing to participate in its classroom implementation.

CONCLUSION

Role-playing has positive effects on knowledge acquisition, skills upgrading, and attitudes related to medical teaching. Therefore, this method can be introduced in the teaching of other medical courses.

SUPPLEMENTARY INFORMATION

The online version of this article (10.1007/s40670-020-01031-x) contains supplementary material, which is available to authorized users.

Exploring the impacts of COVID-19 on travel behavior and mode preferences

Various measures were recommended or imposed by the governments to control the spread of COVID-19. Travel behaviors are significantly influenced due to such measures. However, people have various travel needs ranging from grocery shopping to work. This study examines the changes that occurred in travel behavior due to the COVID-19 pandemic. Data were collected through an online questionnaire survey that included questions on trip purpose, mode choice, distance traveled, and frequency of trips before and during COVID-19. 1203 responses were collected from various countries around the world. Results explained that trip purpose, mode choice, distance traveled, and frequency of trips for the primary travel were significantly different before and during the pandemic. Further, the majority of trips were made for shopping during the pandemic. There was a significant shift from public transport to private transport and non-motorized modes. People placed a higher priority on the pandemic related concerns while choosing a mode during the pandemic as compared to the general concerns. Gender, car ownership, employment status, travel distance, the primary purpose of traveling, and pandemic-related underlying factors during COVID-19 were found to be significant predictors of mode choice during the pandemic. Outcomes of this study could be useful in transport planning and policymaking during pandemics based on the travel needs of people. In particular, government authorities could utilize such knowledge for planning smart and partial lockdowns. Service providers, e.g., taxi companies and retailers, could use such information to better plan their services and operations.

COVID-19 spread and inter-county travel: Daily evidence from the U.S

Daily data at the U.S. county level suggest that coronavirus disease 2019 (COVID-19) cases and deaths are lower in counties where a higher share of people have stayed in the same county (or travelled less to other counties). This observation is tested formally by using a difference-in-difference design controlling for county-fixed effects and time-fixed effects, where weekly changes in COVID-19 cases or deaths are regressed on weekly changes in the share of people who have stayed in the same county during the previous 14 days. A counterfactual analysis based on the formal estimation results suggests that staying in the same county has the potential of reducing total weekly COVID-19 cases and deaths in the U.S. as much as by 139,503 and by 23,445, respectively.

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.

Implications of human activities for (re)emerging infectious diseases, including COVID-19

Since 1980, the world has been threatened by different waves of emerging disease epidemics. In the twenty-first century, these diseases have become an increasing global concern because of their health and economic impacts in both developed and resource-constrained countries. It is difficult to stop the occurrence of new pathogens in the future due to the interconnection among humans, animals, and the environment. However, it is possible to face a new disease or to reduce the risk of its spread by implementing better early warning systems and effective disease control and prevention, e.g., effective global surveillance, development of technology for better diagnostics, effective treatments, and vaccines, the global political will to respond to any threats and multidisciplinary collaboration involving all sectors in charge of good health maintenance. In this review, we generally describe some factors related to human activities and show how they can play a role in the transmission and spread of infectious diseases by using some diseases as examples. Additionally, we describe and discuss major factors that are facilitating the spread of the new pandemic known as COVID-19 worldwide.

Role of Transport during Outbreak of Infectious Diseases: Evidence from the Past

The outbreak of infectious diseases affects people’s lifestyles significantly, as they undertake fewer outdoor activities as a protective measure and to follow government orders of restricted movements. This paper reviewed the scientific literature related to transport and infectious diseases to gain insights into managing such circumstances. The outcomes indicate that the transport sector has a two-fold role during the outbreak of infectious diseases: controlling the spread of infection and assessing the impact of reduced outdoor activities on the transport sector. It was found that local and international travel restrictions, if applied at the initial stages, are effective in controlling the spread of infectious disease; at a later stage, behavioral changes become prominent in limiting the spread. Further, the outbreaks resulted in a significant reduction in mobility, altering traffic patterns with lower peaks and improving traffic safety. The public transport mode share reduced considerably and people preferred cars and active modes. These changes also showed positive impacts on air pollution and water pollution. Further, the air transport and tourism sector were noted to be the hardest hit and will recover slowly. The outcomes from the review will be useful for planners and administrators in managing future emergency conditions better.

Risk perception of coronavirus disease 2019 (COVID-19) and its related factors among college students in China during quarantine

Objective

At the end of 2019, the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan was a serious threat to public health. This study aimed to evaluate the risk perception of COVID-19 among college students in China during the quarantine, explore its related factors, and provide reference for future study.

Methods

This study invited college students from various provinces of China to participate in the survey through the Internet, and a total of 1,461 college students were included. T-test and analysis of variance were used to explore the relationship between demographic characteristics, social pressure, knowledge and risk perception. Multiple linear regression was used to identify factors associated with risk perception.

Results

This study shows that college students in China have high risk perception of COVID-19. Female college students (p<0.01), non-medical students (p<0.01), college students whose schools are located in Hubei (p = 0.01) and college students with higher knowledge level (p<0.01) have higher risk perception.

Conclusion

Due to the strong infectivity and occult nature of COVID-19, it is necessary to improve the risk perception of college students through health education in various ways, and attention should be paid to some college students with low risk perception.

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.