COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies.

BACKGROUND: Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. OBJECTIVE: Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. METHODS: We proposed an age-structured mathematical model and estimated the unknown parameters based on the method of Markov Chain Monte Carlo (MCMC). We also calibrated our model by using three different types of reported COVID-19 data in NYC. Moreover, we evaluated the reduced cumulative number of deaths and new infections with different vaccine allocation strategies. RESULTS: Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75-100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals. If we gradually increased the vaccination coverage rate for two age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 65-100 age group would be reduced the most, about 36 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-44 age group would be reduced the most, about 17,515 fewer new infections per increased 100,000 vaccinated individuals. In addition, if we had an additional 100,000 doses of vaccine for 0-17 and 75-100 age groups as of June 1, 2021, then the allocation of 80% to the 0-17 age group and 20% to the 75-100 age group would reduce the maximum numbers of new infections and deaths simultaneously in NYC. CONCLUSIONS: The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections.

Evaluating the independent influence of sexual transmission on HBV infection in China: a modeling study.

BACKGROUND: The long-term impact of sexual transmission on the hepatitis B virus (HBV) infection in China remains unclear. This study aims to estimate the independent influence of sexual transmission on HBV infection. METHODS: Based on the natural history of HBV infection and three national serosurvey data of hepatitis B in China, we developed an age- and sex-specific discrete model to describe the transmission dynamics of HBV. The initial conditions of the model were determined according to the age- and sex-specific national serosurvey data in 1992. Based on the national survey data of hepatitis B in 1992 and 2006, by using the Markov Chain Monte Carlo (MCMC) method, we estimated the age- and sex-specific seroclearance rates of hepatitis B surface antigen (HBsAg) and the horizontal transmission rates as well as their 95% confidence intervals (CI). Then we used the age- and sex-specific national serosurvey data of hepatitis B in 2014 to test the accuracy of our model-based estimation. Finally, we evaluated the independent impact of sexual transmission on HBV infection and discussed the long-term effect of promotion of condom use in China. RESULTS: We estimated that the annual rates of HBsAg seroclearance for males and females aged 1-59 years were respectively 1.04% (95% CI, 0.49-1.59%) and 1.92% (95% CI, 1.11-2.73%). Due to sexual transmission, in 2014, the total number of chronic HBV infections in people aged 0-100 years increased 292,581, of which males increased 189,200 and females increased 103,381. In 2006, the acute HBV infections due to sexual transmission accounted for 24.76% (male: 31.33%, female: 17.94%) and in 2014, which accounted for 34.59% (male: 42.93%, female: 25.73%). However, if the condom usage rate was increased by 10% annually starting in 2019, then compared with current practice, the total number of acute HBV infections from 2019 to 2035 would be reduced by 16.68% (male: 21.49%, female: 11.93%). The HBsAg prevalence in people aged 1-59 years in 2035 would be reduced to 2.01% (male: 2.40%, female: 1.58%). CONCLUSIONS: Sexual transmission has become the predominant route of acute HBV infection in China, especially for men. The promotion of condom use plays a significant role in reducing the cases of acute HBV infection.

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures-such as face mask use and social distancing-may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely. STUDY DESIGN: This was a mathematical modeling study. METHODS: We developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic. RESULTS: The model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge. CONCLUSIONS: Adherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study.

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently. Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19. Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method. Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0-17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0-17 and 18-44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

Transmission patterns of COVID-19 in the mainland of China and the efficacy of different control strategies: a data- and model-driven study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak has seriously endangered the health and lives of Chinese people. In this study, we predicted the COVID-19 epidemic trend and estimated the efficacy of several intervention strategies in the mainland of China. METHODS: According to the COVID-19 epidemic status, we constructed a compartmental model. Based on reported data from the National Health Commission of People's Republic of China during January 10-February 17, 2020, we estimated the model parameters. We then predicted the epidemic trend and transmission risk of COVID-19. Using a sensitivity analysis method, we estimated the efficacy of several intervention strategies. RESULTS: The cumulative number of confirmed cases in the mainland of China will be 86 763 (95% CI: 86 067-87 460) on May 2, 2020. Up until March 15, 2020, the case fatality rate increased to 6.42% (95% CI: 6.16-6.68%). On February 23, 2020, the existing confirmed cases reached its peak, with 60 890 cases (95% CI: 60 350-61 431). On January 23, 2020, the effective reproduction number was 2.620 (95% CI: 2.567-2.676) and had dropped below 1.0 since February 5, 2020. Due to governmental intervention, the total number of confirmed cases was reduced by 99.85% on May 2, 2020. Had the isolation been relaxed from February 24, 2020, there might have been a second peak of infection. However, relaxing the isolation after March 16, 2020 greatly reduced the number of existing confirmed cases and deaths. The total number of confirmed cases and deaths would increase by 8.72 and 9.44%, respectively, due to a 1-day delayed diagnosis in non-isolated infected patients. Moreover, if the coverage of close contact tracing was increased to 100%, the cumulative number of confirmed cases would be decreased by 88.26% on May 2, 2020. CONCLUSIONS: The quarantine measures adopted by the Chinese government since January 23, 2020 were necessary and effective. Postponing the relaxation of isolation, early diagnosis, patient isolation, broad close-contact tracing, and strict monitoring of infected persons could effectively control the COVID-19 epidemic. April 1, 2020 would be a reasonable date to lift quarantine in Hubei and Wuhan.

The review of differential equation models of HBV infection dynamics.

Understanding the infection and pathogenesis mechanism of hepatitis B virus (HBV) is very important for the prevention and treatment of hepatitis B. Mathematical models contribute to illuminate the dynamic process of HBV replication in vivo. Therefore, in this paper we review the viral dynamics in HBV infection, which may help us further understand the dynamic mechanism of HBV infection and efficacy of antiviral treatment. Firstly, we introduce a family of deterministic models by considering different biological mechanisms, such as, antiviral therapy, CTL immune response, multi-types of infected hepatocytes, time delay and spatial diffusion. Particularly, we briefly describe the stochastic models of HBV infection. Secondly, we introduce the commonly used parameter estimation methods for HBV viral dynamic models and briefly discuss how to use these methods to estimate unknown parameters (such as drug efficacy) through two specific examples. We also discuss the idea and method of model identification and use a specific example to illustrate its application. Finally, we propose three new research programs, namely, considering HBV drug-resistant strain, coupling within-host and between-host dynamics in HBV infection and linking population dynamics with evolutionary dynamics of HBV diversity.

Estimating the impact of test-and-treat strategies on hepatitis B virus infection in China by using an age-structured mathematical model.

The potential impact of increasing test-and-treat coverage on hepatitis B virus (HBV) infection remains unclear in China. The objective of this study was to develop a dynamic compartmental model at a population level to estimate the long-term effect of this strategy.Based on the natural history of HBV infection and 3 serosurvey data of hepatitis B in China, we proposed an age- and time-dependent discrete model to predict the number of new HBV infection, the number of chronic HBV infection, and the number of HBV-related deaths for the time from 2018 to 2050 under 5 different test-and-treat coverage and compared them with current intervention policy.Compared with current policy, if the test-and-treat coverage was increased to 100% since 2018, the numbers of chronic HBV infection, new HBV infection, and HBV-related deaths in 2035 would be reduced by 26.60%, 24.88%, 26.55%, respectively, and in 2050 it would be reduced by 44.93%, 43.29%, 43.67%, respectively. In contrast, if the test-and-treat coverage was increased by 10% every year since 2018, then the numbers of chronic HBV infection, new HBV infection, and HBV-related deaths in 2035 would be reduced by 21.81%, 20.10%, 21.40%, respectively, and in 2050 it would be reduced by 41.53%, 39.89%, 40.32%, respectively. In particular, if the test-and-treat coverage was increased to 75% since 2018, then the annual number of HBV-related deaths would begin to decrease from 2018. If the test-and-treat coverage was increased to above 25% since 2018, then the hepatitis B surface antigen (HBsAg) prevalence for population aged 1 to 59 years in China would be reduced to below 2% in 2035. Our model also showed that in 2035, the numbers of chronic HBV infection and HBV-related deaths in 65 to 69 age group would be reduced the most (about 1.6 million and 13 thousand, respectively).Increasing test-and-treat coverage would significantly reduce HBV infection in China, especially in the middle-aged people and older people. The earlier the treatment and the longer the time, the more significant the reduction. Implementation of test-and-treat strategy is highly effective in controlling hepatitis B in China.