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

Author

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  • Feng, Zhilan
  • Feng, Yejuan
  • Glasser, John W.

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.

Suggested Citation

  • Feng, Zhilan & Feng, Yejuan & Glasser, John W., 2020. "Influence of demographically-realistic mortality schedules on vaccination strategies in age-structured models," Theoretical Population Biology, Elsevier, vol. 132(C), pages 24-32.
    • Handle: RePEc:eee:thpobi:v:132:y:2020:i:c:p:24-32
    DOI: 10.1016/j.tpb.2020.01.005
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    Cited by:

    1. Daniel K Sewell & Aaron Miller & for the CDC MInD-Healthcare Program, 2020. "Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of Columbia," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.

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