Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017 - 2018 winter influenza season

Shing Hei Ho (Lead / Corresponding author), Daihai He, Raluca Eftimie

Research output: Contribution to journalArticle

2 Citations (Scopus)
25 Downloads (Pure)

Abstract

Two mathematical models described by simple ordinary differential equations are developed to investigate the Hong Kong influenza epidemic during 2017–2018 winter, based on overall epidemic dynamics and different influenza subtypes. The first model, describing the overall epidemic dynamics, provides the starting data for the second model which different influenza subtypes, and whose dynamics is further investigated. Weekly data from December 2017 to May 2018 are obtained from the data base of the Centre of Health Protection in Hong Kong, and used to parametrise the models. With the help of these models, we investigate the impact of different vaccination strategies and determine the corresponding critical vaccination coverage for different vaccine efficacies. The results suggest that at least 72% of Hong Kong population should have been vaccinated during 2017–2018 winter to prevent the seasonal epidemic by herd immunity (while data showed that only a maximum of 11.6% of the population were vaccinated). Our results also show that the critical vaccination coverage decreases with increasing vaccine efficacy, and the increase in one influenza subtype vaccine efficacy may lead to an increase in infections caused by a different subtype.

Original languageEnglish
Pages (from-to)74-94
Number of pages21
JournalJournal of Theoretical Biology
Volume476
Early online date23 May 2019
DOIs
Publication statusPublished - 7 Sep 2019

Keywords

  • Influenza
  • SVIR model
  • Vaccination coverage
  • Vaccine efficacy

Fingerprint Dive into the research topics of 'Mathematical models of transmission dynamics and vaccine strategies in Hong Kong during the 2017 - 2018 winter influenza season'. Together they form a unique fingerprint.

  • Cite this