Characteristics of measles epidemics in China (1951-2004) and implications for elimination: A case study of three key locations

Abstract

Measles is a highly infectious, severe viral disease. The disease is targeted for global eradication; however, this result has proven challenging. In China, where countrywide vaccination coverage for the last decade has been above 95% (the threshold for measles elimination), measles continues to cause large epidemics. To diagnose factors contributing to the persistency of measles, here we develop a model-inference system to infer measles transmission dynamics in China. The model-inference system uses demographic and vaccination data for each year as model inputs to directly account for changing population dynamics (including births, deaths, migrations, and vaccination). In addition, it simultaneously estimates unobserved model variables and parameters based on incidence data. When fitted to yearly incidence data for the entire population, it is able to accurately estimate independent, out-of-sample age-specific incidence. Using this validated model-inference system, we are thus able to estimate epidemiological and demographical characteristics key to measles transmission during 1951–2004 for three key locations in China, including its capital Beijing. These characteristics include age-specific population susceptibility and incidence rates, the basic reproductive number ( R 0 ), reporting rate, population mixing intensity, and amplitude of seasonality. Key differences among the three sites reveal population and epidemiological characteristics crucial for understanding the current persistence of measles epidemics in China. We also discuss the implications our findings have for future elimination strategies.

Mathematical analysis of a measles transmission dynamics model in Bangladesh with double dose vaccination

“…In recent decades, the research relating to measles in epidemiology has been one of the most important research fields to researchers. Many researchers have already proposed their ideas and accomplished their research mathematically, theoretically or experimentally, using different deterministic or compartmental models, to find the comparatively best ways for measles control and prevention, focusing on different areas of the world, for example, London 17 , Afghanistan 18 , Kenya 19 , Madagascar 20 , Ontario 21 , Cape Coast 22 , Italy 23 , Senegal 23 , Taiwan 24 and China 25 , 26 . Moreover, Momoh et al 27 studied an SEIR deterministic epidemic model to investigate the impact of asymptomatic individuals at the latent period on measles dynamics.…”

Early Waning of Maternal Measles Antibodies in Infants in Zhejiang Province, China: A Comparison of Two Cross-Sectional Serosurveys

“…Despite all the efforts to achieve universal MV coverage, China failed to achieve its goal of eliminating measles by 2012, most likely due to the change in epidemiology of measles infection [3,4,5,6]. One of the changes was that children aged <8 months, who were expected to be protected by maternal antibodies before receiving the first dose of MV (MV1), became the age group with the greatest risk of infection in recent years.…”

Phylogenetic and Epidemiological Analysis of Measles Viruses in Shenzhen, China from January 2015 to July 2019

“…However, the measles season was delayed in some cities. Guangzhou had a delayed outbreak from 1985 to 2001, in which the incidence began to increase in April and peaked in May [15]. There were 1890 cases reported in Shenzhen, and the disease appeared more frequently between June and July from 2010 to 2016 [9].…”