Literature DB >> 1808755

Disease in changing populations: growth and disequilibrium.

S Tuljapurkar1, A M John.   

Abstract

This paper examines simple age-structured models of childhood disease epidemiology, focusing on nonstationary populations which characterize LDCs. An age-structured model of childhood disease epidemiology for nonstationary populations is formulated which incorporates explicit scaling assumptions with respect both to time and to population density. The static equilibrium properties and the dynamic local stability of the model are analyzed, as are the effects of random variability due to fluctuations in demographic structure. We determine the consequences of population growth rate for: the critical level of immunization needed to eradicate an endemic disease, the transient epidemic period, the return time which measures the stability of departures from epidemiological equilibrium, and the power spectrum of epidemiological fluctuations and combined demographic-epidemiological fluctuations. Growing populations are found to be significantly different from stationary ones in each of these characteristics. The policy implications of these findings are discussed.

Mesh:

Year:  1991        PMID: 1808755     DOI: 10.1016/0040-5809(91)90059-o

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  4 in total

1.  Age-structured homogeneous epidemic systems with application to the MSEIR epidemic model.

Authors:  Hisashi Inaba
Journal:  J Math Biol       Date:  2006-10-21       Impact factor: 2.259

2.  Structured models of infectious disease: inference with discrete data.

Authors:  C J E Metcalf; J Lessler; P Klepac; A Morice; B T Grenfell; O N Bjørnstad
Journal:  Theor Popul Biol       Date:  2011-12-09       Impact factor: 1.570

3.  Decreasing fertility rate correlates with the chronological increase and geographical variation in incidence of Kawasaki disease in Japan.

Authors:  Yoshiro Nagao
Journal:  PLoS One       Date:  2013-07-08       Impact factor: 3.240

4.  A 'post-honeymoon' measles epidemic in Burundi: mathematical model-based analysis and implications for vaccination timing.

Authors:  Katelyn C Corey; Andrew Noymer
Journal:  PeerJ       Date:  2016-09-15       Impact factor: 2.984

  4 in total

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