Literature DB >> 7606144

A core group model for disease transmission.

K P Hadeler1, C Castillo-Chavez.   

Abstract

Models for sexually transmitted diseases generally assume that the size of the core group is fixed. Publicly available information on disease prevalence may influence the recruitment of new susceptibles into highly sexually active populations. It is assumed that the recruitment rate into the core population is low while disease prevalence is high, core group members mix only with each other, disease levels outside the core are negligible, and some core group members reduce their risk through the use of a partially effective vaccine or prophylactics. A demographic-epidemic model is formulated in which the combined size of the core and non-core population is constant. A simpler version models the epidemic in an isolated core population of constant size under the influence of educational programs and measures that reduce susceptibility. The threshold condition for an endemic infection is determined. Backward bifurcations, multiple infective stationary states, and hysteresis phenomena can be observed even in the simplified version. Abrupt changes in disease prevalence levels may result from small changes in the disease management parameters and do not occur in the absence of such a program. The general conclusion is that partially effective vaccination or education programs may increase the total number of cases while decreasing the relative frequency of cases in the core group. The study throws some new light on the role of the reproduction number in connection with elimination attempts. It shows that although the reproduction number defines the threshold for the spread of the disease in a susceptible population, it is of limited value when elimination of an existing epidemic is planned.

Mesh:

Year:  1995        PMID: 7606144     DOI: 10.1016/0025-5564(94)00066-9

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  27 in total

1.  Frequency-dependent incidence in models of sexually transmitted diseases: portrayal of pair-based transmission and effects of illness on contact behaviour.

Authors:  James O Lloyd-Smith; Wayne M Getz; Hans V Westerhoff
Journal:  Proc Biol Sci       Date:  2004-03-22       Impact factor: 5.349

2.  SIR DYNAMICS WITH ECONOMICALLY DRIVEN CONTACT RATES.

Authors:  Benjamin R Morin; Eli P Fenichel; Carlos Castillo-Chavez
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3.  The minimum effort required to eradicate infections in models with backward bifurcation.

Authors:  Muntaser Safan; Hans Heesterbeek; Klaus Dietz
Journal:  J Math Biol       Date:  2006-08-05       Impact factor: 2.259

Review 4.  Vaccine-induced pathogen strain replacement: what are the mechanisms?

Authors:  Maia Martcheva; Benjamin M Bolker; Robert D Holt
Journal:  J R Soc Interface       Date:  2008-01-06       Impact factor: 4.118

5.  Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.

Authors:  John E Franke; Abdul-Aziz Yakubu
Journal:  J Math Biol       Date:  2008-07-15       Impact factor: 2.259

6.  Vaccination based control of infections in SIRS models with reinfection: special reference to pertussis.

Authors:  Muntaser Safan; Mirjam Kretzschmar; Karl P Hadeler
Journal:  J Math Biol       Date:  2012-09-05       Impact factor: 2.259

7.  SIS and SIR Epidemic Models Under Virtual Dispersal.

Authors:  Derdei Bichara; Yun Kang; Carlos Castillo-Chavez; Richard Horan; Charles Perrings
Journal:  Bull Math Biol       Date:  2015-10-21       Impact factor: 1.758

8.  Perspectives on the role of mobility, behavior, and time scales in the spread of diseases.

Authors:  Carlos Castillo-Chavez; Derdei Bichara; Benjamin R Morin
Journal:  Proc Natl Acad Sci U S A       Date:  2016-12-13       Impact factor: 11.205

9.  A simple epidemiological model for populations in the wild with Allee effects and disease-modified fitness.

Authors:  Yun Kang; Carlos Castillo-Chavez
Journal:  Discrete Continuous Dyn Syst Ser B       Date:  2014-01       Impact factor: 1.327

10.  Mathematical epidemiology is not an oxymoron.

Authors:  Fred Brauer
Journal:  BMC Public Health       Date:  2009-11-18       Impact factor: 3.295

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