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Complex Systems and Complexity Science >

2020 , Vol. 17 >Issue 1: 87 - 94

DOI: https://doi.org/10.13306/j.1672-3813.2020.01.011

Measles Transmission Dynamics in China Based on Age-Structure Model

  • WANG Xufeng ,
  • WANG Yanfen ,
  • ZHAO Jijun ,
  • WANG Xufeng ,
  • WANG Yanfen ,
  • ZHAO Jijun
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  • Institute of Complex Science, Qingdao 266071, China

Received date: 2019-07-31

  Online published: 2020-04-29

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Abstract

This paper aims to analyze the force of infection of measles and the seasonality of measles transmission rate at different age groups in China, and to analyze the effect of seasonal children’s contact rate and seasonal population’s contacts on the seasonality of measles transmission rate. Base on the age-stratified reported cases of measles in China from 2013 to 2016, we used the force of infection analysis model to estimate the age-specific force of infection; we established an age-structured time series susceptible-infected-recovered (TSIR) model and analyzed the transmission dynamics of measles in China. The model contains two different driving factors for the measles seasonal transmission: the periodic contact rate among children, and the periodic contact rate of the overall population. Our results show that: 1) the force of infection of measles in China varied across ages with the highest for infants less than one years old (24%-44%) and the second highest for people aged 50-65 years;2) Seasonal contact rates that due to both school terms and Spring Festival travel rush will lead to seasonal transmission rate of measles in China; 3) school terms can increase transmission rate by 31%, and seasonal population contact rate caused by Spring Festival travel rush can increase the transmission rate by 23%.

Key words： measles; force of infection; transmission rate seasonality; school terms; Spring Festival travel rush; contact rate

Cite this article

WANG Xufeng , WANG Yanfen , ZHAO Jijun , WANG Xufeng , WANG Yanfen , ZHAO Jijun . Measles Transmission Dynamics in China Based on Age-Structure Model[J]. Complex Systems and Complexity Science, 2020 , 17(1) : 87 -94 . DOI: 10.13306/j.1672-3813.2020.01.011

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