Literature DB >> 32027879

Influence of demographically-realistic mortality schedules on vaccination strategies in age-structured models.

Zhilan Feng1, Yejuan Feng2, John W Glasser3.   

Abstract

Because demographic realism complicates analysis, mathematical modelers either ignore demography or make simplifying assumptions (e.g., births and deaths equal). But human populations differ demographically, perhaps most notably in their mortality schedules. We developed an age-stratified population model with births, deaths, aging and mixing between age groups. The model includes types I and II mortality as special cases. We used the gradient approach (Feng et al., 2015, 2017) to explore the impact of mortality patterns on optimal strategies for mitigating vaccine-preventable diseases such as measles and rubella, which the international community has targeted for eradication. Identification of optimal vaccine allocations to reduce the effective reproduction number Rv under various scenarios is presented. Numerical simulations of the model with various types of mortality are carried out to ascertain the long-term effects of vaccination on disease incidence. We conclude that both optimal vaccination strategies and long-term effects of vaccination may depend on demographic assumptions. Published by Elsevier Inc.

Entities:  

Keywords:  Age-structured epidemiological model; Non-random mixing; Optimal vaccination strategies; Realistic demographics

Mesh:

Year:  2020        PMID: 32027879      PMCID: PMC9271362          DOI: 10.1016/j.tpb.2020.01.005

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.514


  8 in total

1.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission.

Authors:  P van den Driessche; James Watmough
Journal:  Math Biosci       Date:  2002 Nov-Dec       Impact factor: 2.144

2.  Global stability of an age-structure model for TB and its applications to optimal vaccination strategies.

Authors:  C Castillo-Chavez; Z Feng
Journal:  Math Biosci       Date:  1998-08-01       Impact factor: 2.144

3.  Evaluating vaccination policies to accelerate measles elimination in China: a meta-population modelling study.

Authors:  Lixin Hao; John W Glasser; Qiru Su; Chao Ma; Zhilan Feng; Zundong Yin; James L Goodson; Ning Wen; Chunxiang Fan; Hong Yang; Lance E Rodewald; Zijian Feng; Huaqing Wang
Journal:  Int J Epidemiol       Date:  2019-08-01       Impact factor: 7.196

4.  An elaboration of theory about preventing outbreaks in homogeneous populations to include heterogeneity or preferential mixing.

Authors:  Zhilan Feng; Andrew N Hill; Philip J Smith; John W Glasser
Journal:  J Theor Biol       Date:  2015-09-14       Impact factor: 2.691

5.  Constrained minimization problems for the reproduction number in meta-population models.

Authors:  Gayane Poghotanyan; Zhilan Feng; John W Glasser; Andrew N Hill
Journal:  J Math Biol       Date:  2018-02-14       Impact factor: 2.259

6.  The effect of heterogeneity in uptake of the measles, mumps, and rubella vaccine on the potential for outbreaks of measles: a modelling study.

Authors:  John W Glasser; Zhilan Feng; Saad B Omer; Philip J Smith; Lance E Rodewald
Journal:  Lancet Infect Dis       Date:  2016-02-05       Impact factor: 25.071

7.  Evaluating targeted interventions via meta-population models with multi-level mixing.

Authors:  Zhilan Feng; Andrew N Hill; Aaron T Curns; John W Glasser
Journal:  Math Biosci       Date:  2016-09-23       Impact factor: 2.144

8.  Measles virus infection diminishes preexisting antibodies that offer protection from other pathogens.

Authors:  Michael J Mina; Tomasz Kula; Yumei Leng; Mamie Li; Rory D de Vries; Mikael Knip; Heli Siljander; Marian Rewers; David F Choy; Mark S Wilson; H Benjamin Larman; Ashley N Nelson; Diane E Griffin; Rik L de Swart; Stephen J Elledge
Journal:  Science       Date:  2019-11-01       Impact factor: 47.728

  8 in total
  6 in total

1.  The Impact of Rubella Vaccine Introduction on Rubella Infection and Congenital Rubella Syndrome: A Systematic Review of Mathematical Modelling Studies.

Authors:  Nkengafac Villyen Motaze; Zinhle E Mthombothi; Olatunji Adetokunboh; C Marijn Hazelbag; Enrique M Saldarriaga; Lawrence Mbuagbaw; Charles Shey Wiysonge
Journal:  Vaccines (Basel)       Date:  2021-01-25

2.  Assessing the burden of congenital rubella syndrome in China and evaluating mitigation strategies: a metapopulation modelling study.

Authors:  Qiru Su; Zhilan Feng; Lixin Hao; Chao Ma; José E Hagan; Gavin B Grant; Ning Wen; Chunxiang Fan; Hong Yang; Lance E Rodewald; Huaqing Wang; John W Glasser
Journal:  Lancet Infect Dis       Date:  2021-01-27       Impact factor: 71.421

3.  Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of Columbia.

Authors:  Daniel K Sewell; Aaron Miller
Journal:  PLoS One       Date:  2020-11-10       Impact factor: 3.240

4.  The heterogeneous mixing model of COVID-19 with interventions.

Authors:  Moran Duan; Zhen Jin
Journal:  J Theor Biol       Date:  2022-08-28       Impact factor: 2.405

5.  Analysis of Serological Surveys of Antibodies to SARS-CoV-2 in the United States to Estimate Parameters Needed for Transmission Modeling and to Evaluate and Improve the Accuracy of Predictions.

Authors:  John W Glasser; Zhilan Feng; MyVan Vo; Jefferson N Jones; Kristie E N Clarke
Journal:  J Theor Biol       Date:  2022-10-05       Impact factor: 2.405

6.  COVID-19 Seroprevalence in Canada Modelling Waning and Boosting COVID-19 Immunity in Canada a Canadian Immunization Research Network Study.

Authors:  David W Dick; Lauren Childs; Zhilan Feng; Jing Li; Gergely Röst; David L Buckeridge; Nick H Ogden; Jane M Heffernan
Journal:  Vaccines (Basel)       Date:  2021-12-23
  6 in total

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