400 level, Enugu state university of science and technology, Enugu, Nigeria.
The need to control infectious diseases
Infectious diseases have really contributed to high death rate experienced today in Nigeria. These diseases can be controlled by the measures describe in my research work.
Abstract: It is well established in the epidemiological literature that individual behaviors have a significant effect on the spread of infectious diseases. Agent-based models are increasingly being recognized as the next generation of epidemiological models. In this research, we use the ability of agent-based models to incorporate behavior into simulations by examining the relative importance of vaccination and social distancing, two common measures for controlling the spread of infectious diseases, with respect to seasonal influenza. We modeled health behaviour using the result of a Health Belief Model study focused on influenza. We considered a control and a treatment group to explore the effect of education on people's health-related behaviors patterns. The control group reflects the behavioral patterns of students based on their general knowledge of influenza and its interventions while the treatment group illustrates the level of behavioral changes after individuals have been educated by a health care expert. The results of this study indicate that self-initiated behaviors are successful in controlling an outbreak in a high contact rate location such as a university. Self-initiated behaviors resulted in a population attack rate decrease of 17% and a 25% reduction in the peak number of cases. The simulation also provides significant evidence for the effect of an HBM theory-based educational program to increase the rate of applying the target interventions (vaccination by 22% percent and social distancing by 41%) and consequently to control the outbreak.
Pub.: 13 Jan '15, Pinned: 13 Sep '17
Abstract: In the face of serious infectious diseases, governments endeavour to implement containment measures such as public vaccination at a macroscopic level. Meanwhile, individuals tend to protect themselves by avoiding contacts with infections at a microscopic level. However, a comprehensive understanding of how such combined strategy influences epidemic dynamics is still lacking. We study a susceptible-infected-susceptible epidemic model with imperfect vaccination on dynamic contact networks, where the macroscopic intervention is represented by random vaccination of the population and the microscopic protection is characterised by susceptible individuals rewiring contacts from infective neighbours. In particular, the model is formulated both in populations without and then with demographic effects (births, deaths, and migration). Using the pairwise approximation and the probability generating function approach, we investigate both dynamics of the epidemic and the underlying network. For populations without demography, the emerging degree correlations, bistable states, and oscillations demonstrate the combined effects of the public vaccination program and individual protective behavior. Compared to either strategy in isolation, the combination of public vaccination and individual protection is more effective in preventing and controlling the spread of infectious diseases by increasing both the invasion threshold and the persistence threshold. For populations with additional demographic factors, we investigate temporal evolution of infected individuals and infectious contacts, as well as degree distributions of nodes in each class. It is found that the disease spreads faster but is more restricted in scale-free networks than in the Erdös-Rényi ones. The integration between vaccination intervention and individual rewiring may promote epidemic spreading due to the birth effect. Moreover, the degree distributions of both networks in the steady state is closely related to the degree distribution of newborns, which leads to uncorrelated connectivity. All the results demonstrate the importance of both local protection and global intervention, as well as the demographic effects. Our work thus offers a more comprehensive description of disease containment.
Pub.: 17 Apr '16, Pinned: 13 Sep '17
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