Forecasting Epidemiological and Evolutionary Dynamics of Infectious Diseases
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Keywords:
Evolutionary Dynamics
Disease Transmission
Representation
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Dynamics
Epidemic disease
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An infectious disease is still a menace to our health even in high-technogical and advanced information society. A prevention of prevalence of the infectious disease is one of important problems in epidemiology. In such a problem, the mathematical model which describes the spread of the infectious disease has a very important role in the prediction and the analysis of prevalence of the infectious disease. In this paper, we study the modeling of the infectious disease in populations consisting of four populations: susceptible, infective, recovered and vaccinated ones. Noting that the real infectious disease contains some kinds of random fluctuations caused by changes in the environment and the weather, we propose the stochastic infectious model. By using the proposed stochastic model, we analyze the influence of the random fluctuation and vaccination on the spread of the infectious disease by numerical simulations.
Stochastic modelling
Emerging infectious disease
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OBJECTIVE To describe the importance of mathematical models in the understanding of infectious disease transmission dynamics, as well as in the design of effective strategies for control. MATERIAL AND METHODS International literature was reviewed on the subject through digital means. Around 60 papers about the subject were identified; nevertheless, this study is based on only 27 of these, due to the fact that they were directly related to the subject. RESULTS This work presents a brief explanation of the antecedents, importance and classification of mathematical models for infectious diseases. In addition, a detailed description of some classical models is discussed as well as other more recent models used in the modeling of infectious disease. CONCLUSIONS The use of mathematical models for infectious diseases has grown significantly in the last few years and has proven to be of great help in designing efficient strategies for control and eradication of infectious diseases.
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Delay differential equation
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Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as "economic epidemiology" or "epidemiological economics," the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
Animal ecology
Health Economics
Entomology
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Incubation period
Epidemic model
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Evolution of a laboratory based system for investigating outbreaks of infectious intestinal disease.
In 1995 Preston Public Health Laboratory introduced an incident logging system intended to improve the investigation of suspected outbreaks of infectious intestinal disease. A unique incident log (Ilog) number assigned and issued to the reporting individual and other interested parties when the laboratory is informed of a potential outbreak is used to identify all associated specimens submitted to the laboratory and is quoted in all communications about the incident. The results are reviewed formally each month. Between January 1995 and December 1998, 349 potential outbreaks of infectious intestinal disease were investigated, 325 of which were considered to be general outbreaks. Small round structured viruses were identified in 45% of these outbreaks, salmonellas in 8%, and no pathogens in 35%. Data from the national surveillance scheme for general outbreaks of infectious intestinal disease included 104 general outbreaks in 1996 and 1997 for the entire North West region, but our laboratory alone reported 184 general outbreaks during that period. The Ilog system is a simple and effective means for reviewing data from outbreaks, and helps to coordinate their investigation.
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