There is significant current interest in the application of media/psychosocial effects to problems in epidemiology. News reporting has the potential to reach and to modify the knowledge, attitudes, and behavior of a large proportion of the community. A susceptible-infected-hospitalized-recovered model with vital dynamics, where media coverage of disease incidence and disease prevalence can influence people to reduce their contact rates is formulated. The media function is incorporated into the model using an exponentially decreasing function. Qualitative analysis of the model reveals that the disease-free equilibrium is locally asymptotically stable when a certain threshold is less than unity. Numerical results show the potential short-term beneficial effect of media coverage. 1. Introduction Populations worldwide have incurred significant losses from infectious disease outbreaks since the second century, both in terms of morbidity and mortality as well as social and economic costs [1]. As a result, a wide range of tools, including mass media, have been deployed in the effort to control and eliminate epidemic diseases. This study is motivated by the fact that information spreading in a population even though complex, has a great number of applications. Mass media (television, radio, newspapers, billboards, and booklets) have been used as a way of delivering preventive health messages as they have the potential to influence people’s behavior [2], and deter them from risky behavior or from taking precautionary measures in relation to a disease outbreak, as concurrent presentation of objective information about the diseases can mitigate its severity [3]. There is a causal relationship between the mass media health education campaign and the increase in the demand for health services during a disease outbreak. However, there is a dearth of research documenting this, at least from the mathematical standpoint. It has been posited that mass media can enable people to demand direct TB smear tests and increase case finding [4]. Grilli et al. [5] noted that those engaged in promoting a better uptake of research information in clinical practice should consider mass media as one of the tools that may encourage the use of effective services and discourage those of unproved effectiveness. The responsibilities of the media are to disseminate health information [6] and to frequently cover health-related topics and, as such, the media are the leading source of information about important health issues for many individuals. Media coverage of health-related events has
References
[1]
P. Bonanni, “Demographic impact of vaccination: a review,” Vaccine, vol. 17, supplement 3, pp. S120–S125, 1999.
[2]
M. P. Brinn, K. V. Carson, A. J. Esterman, A. B. Chang, and B. J. Smith, “Mass media interventions for preventing smoking in young people,” Cochrane Database of Systematic Reviews, vol. 11, Article ID CD001006, 2010.
[3]
M. E. Young, G. R. Norman, and K. R. Humphreys, “Medicine in the popular press: the influence of the media on perceptions of disease,” PLoS One, vol. 3, no. 10, Article ID e3552, 2008.
[4]
E. Jaramillo, “The impact of media-based health education on tuberculosis diagnosis in Cali, Colombia,” Health Policy and Planning, vol. 16, no. 1, pp. 68–73, 2001.
[5]
R. Grilli, C. Ramsay, and S. Minozzi, “Mass media interventions: effects on health services utilisation,” Cochrane Database of Systematic Reviews, no. 1, Article ID CD000389, 2002.
[6]
G. Schwitzer, G. Mudur, D. Henry et al., “What are the roles and responsibilities of the media in disseminating health information?” PLoS Medicine, vol. 2, no. 7, article e215, 2005.
[7]
J. S. Brownstein, C. C. Freifeld, and L. C. Madoff, “Influenza A (H1N1) virus, 2009—online monitoring,” The New England journal of medicine, vol. 360, no. 21, p. 2156, 2009.
[8]
E. Mykhalovskiy and L. Weir, “The global public health intelligence network and early warning outbreak detection: a Canadian contribution to Global Public Health,” Canadian Journal of Public Health, vol. 97, no. 1, pp. 42–44, 2006.
[9]
A. Bauman, B. J. Smith, E. W. Maibach, and B. Reger-Nash, “Evaluation of mass media campaigns for physical activity,” Evaluation and Program Planning, vol. 29, no. 3, pp. 312–322, 2006.
[10]
N. T. Brewer, N. D. Weinstein, C. L. Cuite, and J. E. Herrington, “Risk perceptions and their relation to risk behavior,” Annals of Behavioral Medicine, vol. 27, no. 2, pp. 125–130, 2004.
[11]
N. T. Brewer and W. K. Hallman, “Subjective and objective risk as predictors of influenza vaccination during the vaccine shortage of 2004-2005,” Clinical Infectious Diseases, vol. 43, no. 11, pp. 1379–1386, 2006.
[12]
M. Bala, L. Strzeszynski, and K. Cahill, “Mass media interventions for smoking cessation in adults,” Cochrane Database of Systematic Reviews, no. 1, Article ID CD004704, 2008.
[13]
R. Jepson, F. Harris, and N. Rowa-Dewar, “A review of the effectiveness of mass media interventions which both encourage quit attempts and reinforce current and recent attempts to quit smoking (Report),” SC4-1, 2006.
[14]
US Department of Health and Human Services, “Preventing tobacco use among young people: a report of the Surgeon General,” US Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, Atlanta, Ga, USA, 1994.
[15]
M. S. Rahman and M. L. Rahman, “Media and education play a tremendous role in mounting AIDS awareness among married couples in Bangladesh,” AIDS Research and Therapy, vol. 4, article no. 10, 2007.
[16]
V. Ramalingaswami, “Psychosocial effects of the 1994 plague outbreak in Surat, India,” Military Medicine, vol. 166, no. 12, pp. 29–30, 2001.
[17]
A. D'Onofrio, P. Manfredi, and P. Manfredi, “Bifurcation thresholds in an SIR model with information-dependent vaccination,” Mathematical Modelling of Natural Phenomena, vol. 2, no. 1, pp. 26–43, 2007.
[18]
Z. Mukandavire and W. Garira, “Effects of public health educational campaigns and the role of sex workers on the spread of HIV/AIDS among heterosexuals,” Theoretical Population Biology, vol. 72, no. 3, pp. 346–365, 2007.
[19]
Z. Mukandavire, W. Garira, and J. M. Tchuenche, “Modelling effects of public health educational campaigns on HIV/AIDS transmission dynamics,” Applied Mathematical Modelling, vol. 33, no. 4, pp. 2084–2095, 2009.
[20]
S. Redman, E. A. Spencer, and R. W. Sanson-Fisher, “The role of mass media in changing health-related behaviour: a critical appraisal of two models,” Health Promotion International, vol. 5, no. 1, pp. 85–101, 1990.
[21]
F. H. Chen, “Modeling the effect of information quality on risk behavior change and the transmission of infectious diseases,” Mathematical Biosciences, vol. 217, no. 2, pp. 125–133, 2009.
[22]
V. Capasso and G. Serio, “A generalization of the Kermack-McKendrick deterministic epidemic model,” Mathematical Biosciences, vol. 42, no. 1-2, pp. 43–61, 1978.
[23]
R. Liu, J. Wu, and H. Zhu, “Media/psychological impact on multiple outbreaks of emerging infectious diseases,” Computational and Mathematical Methods in Medicine, vol. 8, no. 3, pp. 153–164, 2007.
[24]
Y. Liu and J. Cui, “The impact of media coverage on the dynamics of infectious disease,” International Journal of Biomathematics, vol. 1, no. 1, pp. 65–74, 2008.
[25]
L. M. Cai and X. Z. Li, “Analysis of a SEIV epidemic model with a nonlinear incidence rate,” Applied Mathematical Modelling, vol. 33, no. 7, pp. 2919–2926, 2009.
[26]
J. A. Cui, X. Tao, and H. Zhu, “An SIS infection model incorporating media coverage,” Rocky Mountain Journal of Mathematics, vol. 38, no. 5, pp. 1323–1334, 2008.
[27]
C. Sun, W. Yang, J. Arino, and K. Khan, “Effect of media-induced social distancing on disease transmission in a two patch setting,” Mathematical Biosciences, vol. 230, no. 2, pp. 87–95, 2011.
[28]
J. Cui, Y. Sun, and H. Zhu, “The impact of media on the control of infectious diseases,” Journal of Dynamics and Differential Equations, vol. 20, no. 1, pp. 31–53, 2008.
[29]
Y. Li and J. Cui, “The effect of constant and pulse vaccination on SIS epidemic models incorporating media coverage,” Communications in Nonlinear Science and Numerical Simulation, vol. 14, no. 5, pp. 2353–2365, 2009.
[30]
H. Joshi, S. Lenhart, K. Albright, and K. Gipson, “Modeling the effect of information campaigns on the hiv epidemic in uganda,” Mathematical Biosciences and Engineering, vol. 5, no. 4, pp. 757–770, 2008.
[31]
A. Mummert and H. Weiss, “Get the news out loudly and quickly: Modeling the influence of the media on limiting infectious disease outbreaks,” 2010, http://arxiv.org/pdf/1006.5028v2.pdf.
[32]
J. M. Tchuenche, N. Dube, C. P. Bhunu, R. J. Smith, and C. T. Bauch, “The impact of media coverage on the transmission dynamics of human influenza,” BMC Public Health, vol. 11, supplement 2, article S5, 2011.
[33]
G. Y. Perlman, “The influence of an event in the Israeli media on the compliance of patients with influenza vaccinations in the winter of 2006-2007,” Harefuah, vol. 148, no. 12, pp. 811–856, 2009.
[34]
B. K. Yoo, M. L. Holland, J. Bhattacharya, C. E. Phelps, and P. G. Szilagyi, “Effects of mass media coverage on timing and annual receipt of influenza vaccination among medicare elderly,” Health Services Research, vol. 45, no. 5, pp. 1287–1309, 2010.
[35]
R. M. Anderson and R. M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, 1992.
[36]
G. J. Rubin, H. W. W. Potts, and S. Michie, “The impact of communications about swine flu (influenza A HINIv) on public responses to the outbreak: results from 36 national telephone surveys in the UK,” Health Technology Assessment, vol. 14, no. 34, pp. 183–266, 2010.
[37]
S. Funk, E. Gilad, C. Watkins, and V. A. A. Jansen, “The spread of awareness and its impact on epidemic outbreaks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 16, pp. 6872–6877, 2009.
[38]
A. Banaszuk, “On the existence and uniqueness of solutions for implicit linear systems on finite interval,” Circuits, Systems, and Signal Processing, vol. 12, no. 3, pp. 375–390, 1993.
[39]
Z. Zhang, Y. Suo, J. Peng, and W. Lin, “Singular perturbation approach to stability of a SIRS epidemic system,” Nonlinear Analysis: Real World Applications, vol. 10, no. 5, pp. 2688–2699, 2009.
[40]
P. Van Den Driessche and J. Watmough, “Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission,” Mathematical Biosciences, vol. 180, pp. 29–48, 2002.
[41]
Z. Feng, W. Huang, and C. Castillo-Chavez, “On the role of variable latent periods in mathematical models for tuberculosis,” Journal of Dynamics and Differential Equations, vol. 13, no. 2, pp. 425–452, 2001.
[42]
Y. H. Fan and W. T. Li, “Permanence in delayed ratio-dependent predator-prey models with monotonic functional responses,” Nonlinear Analysis: Real World Applications, vol. 8, no. 2, pp. 424–434, 2007.
[43]
A. Korobeinikov and P. K. Maini, “A Lyapunov function and global properties for SIR and SEIR epidemiological models with nonlinear incidence,” Mathematical Bioscience and Engineering, vol. 1, no. 1, pp. 57–60, 2004.
[44]
I. Barbalat, “Système d'équation différentielle d'Oscillation Nonlinéaires,” Revue Roumaine de Mathématique Pures et Appliquées, vol. 4, pp. 267–270, 1959.
[45]
T. Jefferson, “Real or perceived adverse effects of vaccines and the media—a tale of our times,” Journal of Epidemiology and Community Health, vol. 54, no. 6, pp. 402–403, 2000.
[46]
F. Brauer, “A simple model for behaviour change in epidemics,” BMC Public Health, vol. 11, supplement 2, article S3, 2011.
[47]
D. T. N. Evensen and C. Clarke, “Efficacy information in media coverage of infectious disease risks: an ill predicament?” 2009, http://www.aejmc.com/home/2011/03/sci-2009-abstracts/.
[48]
W. Goffman and V. A. Newill, “Generalization of epidemic theory: an application to the transmission of ideas,” Nature, vol. 204, no. 4955, pp. 225–228, 1964.
[49]
E. Agliari, R. Burioni, D. Cassi, and F. M. Neri, “Efficiency of information spreading in a population of diffusing agents,” Physical Review E, vol. 73, no. 4, Article ID 046138, 2006.
[50]
N. Ferguson, “Capturing human behaviour,” Nature, vol. 446, no. 7137, p. 733, 2007.
[51]
M. Nekovee, Y. Moreno, G. Bianconi, and M. Marsili, “Theory of rumour spreading in complex social networks,” Physica A, vol. 374, no. 1, pp. 457–470, 2007.
[52]
A. Lynch, “Thoaught contagion as abstract evolution,” Journal of Ideas, vol. 2, pp. 3–10, 1991.
