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• An age-structured mathematical model on mumps outbreaks in Jiangsu, China is proposed and analyzed. • Three different stages of no vaccine, effectively controlled and resurgence stages are considered. • Patterns of mumps dynamics are simulated and compared based on data in Jiangsu from January 2005 to May 2019. • The time average basic reproduction number may be lower or over estimated the real one. • Changes in seasonal transmission patterns and demographic structures may be reasons of mumpsre-emerging. Measles, mumps and rubella (MMR) vaccine program was introduced in Jiangsu province of China in May 2008 and has been greatly contributed to decreasing of mumps cases. However, mumps has been resurging since May 2015. A number of studies have put forward that the resurgence of mumps is due to vaccine failure. In this paper, we investigated the other reasons for the resurging of mumps, such as the changes in seasonal transmission patterns and demographic structures, by using an age-structured mathematical model. We divided the history (January 2005 to May 2019) of mumps epidemics of Jiangsu province into three different stages: No vaccine stage (January 2005 to December 2008), effectively controlled stage (January 2009 to December 2014) and resurgence stage (January 2015 to May 2019). The features of mumps epidemics in three stages are compared under different demographic structures with same physical contact rate. The mumps transmission rate was increased in summer and dropped in November in stage III compared with that in stage I. The changes in demographic structures give a good explanation why the mumps outbreaked among children around 10 years old in stage I and around 5 years old in stage III. We have a conclusion that the vaccine failure, changes in seasonality and demographic structures were associated with the mumps outbreaks in recent years in Jiangsu province, China. We give the patterns of mumps dynamics considering age, vaccine, seasonality and demographic structures, which can help health program planners to implement more preventive interventions in mumps control during the period of higher risk of infection. [ABSTRACT FROM AUTHOR]

• We study the impact of supplementary immunization activities (SIAs) on the measles transmission dynamics and its implications for measles elimination goals in China. • The model takes into account population demographics, age-specific contact patterns, seasonality, routine vaccination, SIAs, and the waning vaccine-induced immunity. • SIAs have greatly reduced the measles incidence and the fraction of susceptibles, but the benefit may wane over time. Additional SIAs may accelerate the measles elimination. • The outbreak risk may be greater than 70% once the monthly imported measles cases exceed ten. Measles has re-emerged globally due to the accumulation of susceptible individuals and immunity gap, which causes challenges in eliminating measles. Routine vaccination and supplementary immunization activities (SIAs) have greatly improved measles control, but the impact of SIAs on the measles transmission dynamics remains unclear as the vaccine-induced immunity wanes. We developed a comprehensive measles transmission dynamics model by taking into account population demographics, age-specific contact patterns, seasonality, routine vaccination, SIAs, and the waning vaccine-induced immunity. The model was calibrated by the monthly age-specific cases data from 2005 to 2018 in Jiangsu Province, China, and validated by the dynamic sero-prevalence data. We aimed to investigate the short-term and long-term impact of three-time SIAs during 2009–2012 (9.68 million and 4.25 million children aged 8 months-14 years in March 2009 and September 2010, respectively, and 140,000 children aged 8 months-6 years in March 2012) on the measles disease burden and explored whether additional SIAs could accelerate the measles elimination. We estimated that the cumulative numbers of measles cases from March 2009 to December 2012 (in the short run) and to December 2018 (in the long run) after three-time SIAs (base case) were 6,699 (95% confidence interval [CI]: 2,928–10,469), and 22,411 (15,146–29,675), which averted 45.0% (42.9%-47.0%) and 34.3% (30.7%-37.9%) of 12,226 (4,916–19,537) and 34,274 (21,350–47,199) cases without SIAs, respectively. The fraction of susceptibles for children aged 8–23 months and 2–14 years decreased from 8.3% and 10.8% in March 2009 to 5.8% and 5.8% in April 2012, respectively. However, the fraction of susceptibles aged 15–49 years and above 50 years increased gradually to about 15% in 2018 irrespective of SIAs due to the waning immunity. The measles elimination goal would be reached in 2028, and administrating additional one-off SIAs in September 2022 to children aged 8–23 months, or young adolescents aged 15–19 years could accelerate the elimination one year earlier. SIAs have greatly reduced the measles incidence and the fraction of susceptibles, but the benefit may wane over time. Under the current interventions, Jiangsu province would reach the measles elimination goal in 2028. Additional SIAs may accelerate the measles elimination one year earlier. [ABSTRACT FROM AUTHOR]

• A tuberculosis model incorporating contaminated environments is developed. • A threshold theorem of the model is established. • The annual average of the basic reproduction number is obtained. • TB in Jiangsu is an endemic disease and will persist for a long time. Tuberculosis (TB) is still an important public health issue in Jiangsu province, China. In this study, based on the TB transmission routes and the statistical data of TB cases, we formulate a novel TB epidemic model accounting for the effects of the contaminated environments on TB transmission dynamics. The value of this study lies in two aspects. Mathematically, we define the basic reproduction number, R 0 , and prove that R 0 can be used to govern the threshold dynamics of the model. Epidemiologically, we find that the annual average R 0 is 1.13 , > 1 and TB in Jiangsu is an endemic disease. Therefore, in order to control the TB in Jiangsu efficiently, we must decrease the virus shedding rate or increase the recovery rates, and increase the environmental clearance rate. [ABSTRACT FROM AUTHOR]