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Biodemography and Social Biology, 1986
An epidemic model of suicides clustered in time and space is presented. In this model suicides are depicted as an infection that can be spread from person to person. The model is based on the assumption that spread of suicide ideation via various means of communication increases as the number of suicides increases.
B R, Davis, R J, Hardy
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An epidemic model of suicides clustered in time and space is presented. In this model suicides are depicted as an infection that can be spread from person to person. The model is based on the assumption that spread of suicide ideation via various means of communication increases as the number of suicides increases.
B R, Davis, R J, Hardy
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Differential susceptibility epidemic models
Journal of Mathematical Biology, 2004We formulate compartmental differential susceptibility (DS) susceptible-infective-removed (SIR) models by dividing the susceptible population into multiple subgroups according to the susceptibility of individuals in each group. We analyze the impact of disease-induced mortality in the situations where the number of contacts per individual is either ...
Hyman, James M., Li, Jia
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Journal of the Royal Statistical Society. Series A (Statistics in Society), 1994
"The problems of understanding and controlling disease raise a range of challenging mathematical and statistical research topics, from broad theoretical issues to specific practical ones. In particular, recent interest in acquired immune deficiency syndrome has stimulated much progress in diverse areas of epidemic modelling, particularly with regard ...
D, Mollison, V, Isham, B, Grenfell
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"The problems of understanding and controlling disease raise a range of challenging mathematical and statistical research topics, from broad theoretical issues to specific practical ones. In particular, recent interest in acquired immune deficiency syndrome has stimulated much progress in diverse areas of epidemic modelling, particularly with regard ...
D, Mollison, V, Isham, B, Grenfell
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Simplifying simple epidemic models
Nature, 1984Interest has recently revived in the use of simple models for epidemic diseases. In particular, Anderson et al. have introduced an improved simple differential equation model for diseases such as fox rabies which regulate the population density of their host. Here I describe how such apparently simple models can be dissected into their basic components.
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Avian–human influenza epidemic model
Mathematical Biosciences, 2007A mathematical model is proposed to interpret the spread of avian influenza from the bird world to the human world. Our mathematical model warns that two types of the outbreak of avian influenza may occur if the humans do not prevent the spread of avian influenza. Moreover, it suggests that we cannot feel relieved although the total infected humans are
Iwami, Shingo +2 more
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Dynamic population epidemic models
Mathematical Biosciences, 1991Most multipopulation epidemic models are of the contact distribution type, in which the locations of successive contacts are chosen independently from appropriate contact distributions. This paper is concerned with an alternative class of models, termed dynamic population epidemic models, in which infectives move among the populations and can infect ...
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Estimation for an Epidemic Model
Biometrics, 1976In many epidemic models the initial infection rate, suitably defined, plays a fundamental role in determining the probability of a major epidemic. An estimate for this rate is suggested on the basis of least squares and maximum likelihood methods. The model used to arrive at the estimate is a Galton-Watson process modified by letting the offspring ...
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1994
Abstract Even though AIDS incidence data are reliable enough to make useful short-term projections of AIDS incidence (Chapters 7 and 8), such data lag the course of infection by several years and give much less reliable information on underlying infection trends in HIV prevalence and incidence.
Ron Brookmeyer, Mitchell H Gail
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Abstract Even though AIDS incidence data are reliable enough to make useful short-term projections of AIDS incidence (Chapters 7 and 8), such data lag the course of infection by several years and give much less reliable information on underlying infection trends in HIV prevalence and incidence.
Ron Brookmeyer, Mitchell H Gail
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2006
One of the important areas of real-life applications of stochastic processes is in epidemiology, more specifically, in analyzing the spread of epidemics. Roughly speaking, the situation that we want to look at is as follows. There is a group of individuals, all mixing homogeneously together.
A. Goswami, B. V. Rao
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One of the important areas of real-life applications of stochastic processes is in epidemiology, more specifically, in analyzing the spread of epidemics. Roughly speaking, the situation that we want to look at is as follows. There is a group of individuals, all mixing homogeneously together.
A. Goswami, B. V. Rao
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