A dynamic model for elevator operation-induced spread of a respiratory infectious disease in an apartment building.

Residents have to use elevators to leave and enter their high-rise apartments frequently. An elevator car can easily spread respiratory infectious diseases, as it has a confined and small space. Therefore, studying how elevator operations promote epidemic transmission is of importance to public health. We developed an infectious disease dynamics model. First, we used homemade codes to simulate the operating state of an elevator and the dynamic process of infectious disease transmission in an apartment building due to elevator operations. Second, we analysed the temporal distribution patterns of infected individuals and patients. Finally, we validated the reliability of the model by performing continuous-time sensitivity analysis on important model parameters. We found that elevator operations can cause rapid spread of infectious diseases within an apartment building. Therefore, it is necessary to enhance elevator ventilation and disinfection mechanisms to prevent the outbreak of respiratory infections. Moreover, residents should reduce elevator use and wear masks.

Dynamic model of respiratory infectious disease transmission in urban public transportation systems.

During the epidemics of respiratory infectious diseases, the use of public transportation increases the risk of disease transmission. Therefore, we established a dynamic model to provide an in-depth understanding of the mechanism of epidemic spread via this route. We designed a computer program to model a rail transit system including four transit lines in a small town in which assumed 70% of the residents commute via these trams in weekdays and the remaining residents take the tram at random. The model could identify the best travel route for each passenger and the specific passengers onboard when the tram passed through each station, and simulate the dynamic spread of a respiratory pathogen as the passengers used the rail transit system. Based on the program operating, we estimated that all residents in the town were ultimately infected, including 86.6% who were infected due to the public transportation system. The remaining individuals were infected at home. As the infection rate increased, the number of infected individuals increased more rapidly. Reducing the frequency of trams, driving private cars or riding bicycles, showing nucleic acid certificates and wearing masks for passengers, etc., are effective measures for the prevention of the spread of epidemic diseases.

Dynamic model of respiratory infectious disease transmission by population mobility based on city network.

In modern societies, newly emerging infectious diseases spread rapidly between regions owing to frequent contact between people, causing considerable social and economic impacts. In this study, first, a scale-free city network was established, and then the shortest path between any two nodes was determined. Second, the movement path of tourists was designed based on the shortest path. Subsequently, every infected person's information, such as the city, infection time, onset and hospitalization, was confirmed based on their movement path. Third, the features of the transmission path and time distribution of the epidemic were characterized after summarizing the information. Finally, the reliability of the model was verified. The number of citizens and tourists in every city remained stable during this time. The results indicated that a larger basic reproduction number (R 0) and population outflow rate signify a faster growth rate of infected people in each city in the network. Compared with small and medium-sized cities, the epidemic spread faster in central cities. Population mobility was the decisive factor causing the spread of the epidemic to other areas. Therefore, the rapid spread of epidemics can be prevented by swiftly reducing the flow of people between cities.

Investigation of the baseline tetanus antibody level and its persistence in a military unit.

OBJECTIVES: To determine tetanus antibody levels in army recruits and evaluate the persistence of immunity following tetanus booster immunization in adults. METHODS: A total of 680 recruits were selected for observation of their tetanus antibody levels. From 2005 to 2015, 691 peacekeepers with tetanus vaccination were included in the questionnaire-based and serological survey based on cluster stratification. The tetanus antibody-positive rate, geometric mean concentration (GMC), and their respective changes over time were analyzed in different age groups, regions, and years after tetanus booster immunization. RESULTS: The positivity rates of tetanus antibodies in the recruits and peacekeepers were 74.85% and 99.86%, respectively (χ2 = 193.00, P < 0.05) and the antibody GMCs were 0.05 and 0.70 IU/mL (t = 15.73, P < 0.05). The antibody positivity rates of recruits from 12 provinces ranged from 47.62% (Hubei) to 100% (Inner Mongolia) (χ2 = 37.24, P < 0.05) and the antibody GMCs ranged from 0.02 (Hubei) to 0.09 IU/mL (Heilongjiang) (F = 5.19, P < 0.01). Among the 691 peacekeepers, no statistically significant difference in antibody positivity rate was detected between men and women. After administration of one booster dose of the tetanus vaccine, a protective antibody level was calculated to persist up to 22 years; a significant difference in antibody levels was observed within 10 years between one and two or more booster doses. CONCLUSION: The rate at which recruits tested positive for tetanus antibodies was low. Thus, it is necessary to screen for tetanus antibodies during military recruitment and implement a precision-based booster immunization protocol for tetanus vaccine. Moreover, one dose of the tetanus vaccine booster has been calculated to maintain a protective antibody level up to 22 years, without the need for repeated reinforcements during this period.

Epidemiological analysis of asymptomatic SARS-CoV-2 transmission in the community: an individual-based model.

We established an individual-based computer model to simulate the occurrence, infection, discovery, quarantine, and quarantine release (recovery) of asymptomatic SARS-CoV-2 infected individuals or patients within the community. The model was used to explore the effects of control measures, such as active tracing, laboratory testing, active treatment, and home quarantine on the epidemic. Considering the condition that R0 = 1.2, when a case of an imported asymptomatic infected individual (AII) was reported in the community, the implementation of control measures reduced the number of AIIs and patients by 62.2% and 62.4%, respectively. The number of undetected AIIs and patients peaked at 302 days of the epidemic, reaching 53 and 20 individuals, respectively. The implementation of sustained active tracing, laboratory testing, active treatment, and home quarantine can significantly reduce the probability of disease outbreaks and block the spread of the COVID-19 epidemic caused by AIIs in the community.

Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model.

We established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82-5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982-2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

Epidemiological analysis of an outbreak of an adenovirus type 7 infection in a boot camp in China.

BACKGROUND: An outbreak of respiratory disease associated with adenovirus type 7 occurred in a boot camp in China and was characterized by many cases, severe symptoms, and intrapulmonary infection in many patients. METHODS: We implemented a series of comprehensive preventive and control measures. We analyzed the incubation period and generation time by using the maximum likelihood method, assessed the symptom period and hospitalization duration using the Kaplan-Meier method, and estimated the basic reproductive number and dormitory transmission rate by using established methods. RESULTS: The epidemic lasted for 30 days, and 375 individuals were affected. Overall, 109 patients were hospitalized, and 266 individuals were isolated and treated. The median incubation period was 5.2 days (95% confidence interval [CI]: 5.0 to 5.4 days). The median generation time was 7.3 days (95% CI: 7.1 to 7.6 days). The median symptom period was 6 days (95% CI: 6 to 7 days). The median hospitalization duration was 9 days (95% CI: 9 to 11 days). The basic reproductive number was 5.1 (95% CI: 4.6 to 5.6), and the dormitory transmission rate was 0.15 (95% CI: 0.12 to 0.18). CONCLUSION: Patients in the early stage of the epidemic were treated as having a regular cold and were not isolated; therefore, the virus continued to be transmitted to other susceptible individuals.

Early warning of some notifiable infectious diseases in China by the artificial neural network.

In order to accurately grasp the timing for the prevention and control of diseases, we established an artificial neural network model to issue early warning signals. The real-time recurrent learning (RTRL) and extended Kalman filter (EKF) methods were performed to analyse four types of respiratory infectious diseases and four types of digestive tract infectious diseases in China to comprehensively determine the epidemic intensities and whether to issue early warning signals. The numbers of new confirmed cases per month between January 2004 and December 2017 were used as the training set; the data from 2018 were used as the test set. The results of RTRL showed that the number of new confirmed cases of respiratory infectious diseases in September 2018 increased abnormally. The results of the EKF showed that the number of new confirmed cases of respiratory infectious diseases increased abnormally in January and February of 2018. The results of these two algorithms showed that the number of new confirmed cases of digestive tract infectious diseases in the test set did not have any abnormal increases. The neural network and machine learning can further enrich and develop the early warning theory.

An artificially simulated outbreak of a respiratory infectious disease.

BACKGROUND: Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a stochastic model to simulate an outbreak of a respiratory infectious disease at a military camp. This model fits the general pattern of disease transmission and further enriches theories on the transmission dynamics of infectious diseases. METHODS: We established an enclosed system of 500 people exposed to adenovirus type 7 (ADV 7) in a military camp. During the infection period, the patients transmitted the virus randomly to susceptible people. The spread of the epidemic under militarized management mode was simulated using a computer model named "the random collision model", and the effects of factors such as the basic reproductive number (R0), time of isolation of the patients (TOI), interval between onset and isolation (IOI), and immunization rates (IR) on the developmental trend of the epidemic were quantitatively analysed. RESULTS: Once the R0 exceeded 1.5, the median attack rate increased sharply; when R0 = 3, with a delay in the TOI, the attack rate increased gradually and eventually remained stable. When the IOI exceeded 2.3 days, the median attack rate also increased dramatically. When the IR exceeded 0.5, the median attack rate approached zero. The median generation time was 8.26 days, (95% confidence interval [CI]: 7.84-8.69 days). The partial rank correlation coefficients between the attack rate of the epidemic and R0, TOI, IOI, and IR were 0.61, 0.17, 0.45, and - 0.27, respectively. CONCLUSIONS: The random collision model not only simulates how an epidemic spreads with superior precision but also allows greater flexibility in setting the activities of the exposure population and different types of infectious diseases, which is conducive to furthering exploration of the epidemiological characteristics of epidemic outbreaks.

Analysis and forecast of the HIV/AIDS epidemic in Mainland China, 1985-2016.

BACKGROUND: We aimed to forecast the number of unidentified and newly acquired HIV-infected individuals each year and to estimate the effectiveness of government prevention and control programs in China. METHODS: Dynamic and stochastic models were established based on officially published data regarding the four main modes of transmission: male homosexual sexual behavior, heterosexual sexual behavior, injection drug use (IDU) and plasma donation. Finally, we performed sensitivity analyses on model parameters. RESULTS: Nationally, by December 2016, approximately 280 790 individuals were estimated to have an unidentified HIV infection, with transmission via male homosexual sexual behavior (n = 100 710), heterosexual sexual behavior (n = 174 310), IDU (n = 5 620) and plasma donation (n = 150). Moreover, 196 970 newly acquired HIV-infected individuals were expected in 2016, via male homosexual sexual behavior (n = 78 610), heterosexual sexual behavior (n = 116,540), IDU (n = 1820), and plasma donation (n < 2). CONCLUSIONS: Our results show that HIV transmission via IDU and plasma donation has been effectively controlled; transmission via heterosexual sexual contact is being somewhat controlled; however, transmission via male homosexual sexual contact is not controlled. Hence, China should strengthen efforts aimed at control of unsafe sexual behaviors.

Epidemiological characteristics of pulmonary tuberculosis in mainland China from 2004 to 2015: a model-based analysis.

BACKGROUND: We used data released by the government to analyze the epidemiological distribution of pulmonary tuberculosis in mainland China from 2004 to 2015, in order to provide a deeper understanding of trends in the epidemiology of pulmonary tuberculosis in China and a theoretical basis to assess the effectiveness of government interventions and develop more targeted prevention and control strategies. METHODS: A discrete dynamic model was designed based on the epidemiological characteristics of pulmonary tuberculosis and fitted to data published by the government to estimate changes in indicators such as adequate contact rate, prevalence of non-treated pulmonary tuberculosis (abbreviated as prevalence), and infection rate. Finally, we performed sensitivity analyses of the effects of parameters on the population infection rate. RESULTS: The epidemiological features of pulmonary tuberculosis in China include a pattern of seasonal fluctuations, with the highest rates of infection in autumn and winter. The adequate contact rate has increased slightly from an average of 0.12/month in 2010 to an average of 0.21/month in 2015. The prevalence in the population has continued to decrease from 3.4% in early 2004 to 1.7% in late 2015. The Mycobacterium tuberculosis (M. tuberculosis) infection rate in the population decreased gradually from 42.3% at the beginning of 2004 to 36.7% at the end of 2015. The actual number of new infections gradually decreased from 1,300,000/year in 2010 to 1,100,000/year in 2015. The actual number of new patients each year has been relatively stable since 2010 and remains at approximately 2,600,000/year. CONCLUSIONS: The population prevalence and the M. tuberculosis infection rate have decreased year by year since 2004, indicating that the tuberculosis epidemic in China has been effectively controlled. However, pulmonary tuberculosis has become increasingly contagious since 2010. China should focus on the prevention and control of pulmonary tuberculosis during autumn and winter.

The temporal distribution of new H7N9 avian influenza infections based on laboratory-confirmed cases in Mainland China, 2013-2017.

In this study, estimates of the growth rate of new infections, based on the growth rate of new laboratory-confirmed cases, were used to provide a statistical basis for in-depth research into the epidemiological patterns of H7N9 epidemics. The incubation period, interval from onset to laboratory confirmation, and confirmation time for all laboratory-confirmed cases of H7N9 avian influenza in Mainland China, occurring between January 2013 and June 2017, were used as the statistical data. Stochastic processes theory and maximum likelihood were used to calculate the growth rate of new infections. Time-series analysis was then performed to assess correlations between the time series of new infections and new laboratory-confirmed cases. The rate of new infections showed significant seasonal fluctuation. Laboratory confirmation was delayed by a period of time longer than that of the infection (average delay, 13 days; standard deviation, 6.8 days). At the lags of -7.5 and -15 days, respectively, the time-series of new infections and new confirmed cases were significantly correlated; the cross correlation coefficients (CCFs) were 0.61 and 0.16, respectively. The temporal distribution characteristics of new infections and new laboratory-confirmed cases were similar and strongly correlated.

Predicting and Evaluating the Epidemic Trend of Ebola Virus Disease in the 2014-2015 Outbreak and the Effects of Intervention Measures.

We constructed dynamic Ebola virus disease (EVD) transmission models to predict epidemic trends and evaluate intervention measure efficacy following the 2014 EVD epidemic in West Africa. We estimated the effective vaccination rate for the population, with basic reproduction number (R0) as the intermediate variable. Periodic EVD fluctuation was analyzed by solving a Jacobian matrix of differential equations based on a SIR (susceptible, infective, and removed) model. A comprehensive compartment model was constructed to fit and predict EVD transmission patterns, and to evaluate the effects of control and prevention measures. Effective EVD vaccination rates were estimated to be 42% (31-50%), 45% (42-48%), and 51% (44-56%) among susceptible individuals in Guinea, Liberia and Sierra Leone, respectively. In the absence of control measures, there would be rapid mortality in these three countries, and an EVD epidemic would be likely recur in 2035, and then again 8~9 years later. Oscillation intervals would shorten and outbreak severity would decrease until the periodicity reached ~5.3 years. Measures that reduced the spread of EVD included: early diagnosis, treatment in isolation, isolating/monitoring close contacts, timely corpse removal, post-recovery condom use, and preventing or quarantining imported cases. EVD may re-emerge within two decades without control and prevention measures. Mass vaccination campaigns and control and prevention measures should be instituted to prevent future EVD epidemics.