Temporal shifts in 24 notifiable infectious diseases in China before and during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic, along with the implementation of public health and social measures (PHSMs), have markedly reshaped infectious disease transmission dynamics. We analysed the impact of PHSMs on 24 notifiable infectious diseases (NIDs) in the Chinese mainland, using time series models to forecast transmission trends without PHSMs or pandemic. Our findings revealed distinct seasonal patterns in NID incidence, with respiratory diseases showing the greatest response to PHSMs, while bloodborne and sexually transmitted diseases responded more moderately. 8 NIDs were identified as susceptible to PHSMs, including hand, foot, and mouth disease, dengue fever, rubella, scarlet fever, pertussis, mumps, malaria, and Japanese encephalitis. The termination of PHSMs did not cause NIDs resurgence immediately, except for pertussis, which experienced its highest peak in December 2023 since January 2008. Our findings highlight the varied impact of PHSMs on different NIDs and the importance of sustainable, long-term strategies, like vaccine development.

MODELS: a six-step framework for developing an infectious disease model

Since the COVID-19 pandemic began, a plethora of modeling studies related to COVID-19 have been released. While some models stand out due to their innovative approaches, others are flawed in their methodology. To assist novices, frontline healthcare workers, and public health policymakers in navigating the complex landscape of these models, we introduced a structured framework named MODELS. This framework is designed to detail the essential steps and considerations for creating a dependable epidemic model, offering direction to researchers engaged in epidemic modeling endeavors.

Epidemiological characteristics and transmissibility of HPV infection: A long-term retrospective study in Hokkien Golden Triangle, China, 2013-2021

OBJECTIVE

Multiple human papillomavirus (HPV)-associated diseases have put a significant disease burden on the world. Therefore, we conducted a study to explore the epidemiological characteristics of HPV and the transmissibility of its genotypes.

METHODS

HPV testing data was collected from Hospital. A transmission dynamics model of HPV was constructed to simulate and compare the transmissibility of different HPV genotypes, which was quantitatively described by the basic reproduction number (R0).

RESULTS

The collected HPV subjects were mainly from Xiamen City, Zhangzhou City and Quanzhou City, together, they are known as the Hokkien golden triangle. There were variations in the distribution of HPV infections by age groups. Among all HPV genotypes, 13 of them had R0 > 1, with 10 of them being high-risk types. The top five were HPV56, 18, 58, 52 and 53, among which, HPV56, 18, 58 and 42 were of high risk, whereas HPV53 was not, and the R0 values for the five were 3.35 (CI: 0.00-9.99), 3.20 (CI: 0.00-6.46), 3.19 (CI: 1.27-6.94), 3.19 (CI: 1.01-8.42) and 2.99 (CI: 0.00-9.39), respectively. In addition, HPV52 had R0 > 1 for about 51 months, which had the longest duration.

CONCLUSION

Most high-risk HPV types in the Hokkien golden triangle could transmit among the population. Therefore, there is a need of further optimization for developing HPV vaccines and better detection methods in the region.

Assessment of transmissibility and measures effectiveness of SARS in 8 regions, China, 2002-2003

Background

Severe acute respiratory syndrome (SARS) is a form of atypical pneumonia which took hundreds of lives when it swept the world two decades ago. The pathogen of SARS was identified as SARS-coronavirus (SARS-CoV) and it was mainly transmitted in China during the SARS epidemic in 2002-2003. SARS-CoV and SARS-CoV-2 have emerged from the SARS metapopulation of viruses. However, they gave rise to two different disease dynamics, a limited epidemic, and an uncontrolled pandemic, respectively. The characteristics of its spread in China are particularly noteworthy. In this paper, the unique characteristics of time, space, population distribution and transmissibility of SARS for the epidemic were discussed in detail.

Methods

We adopted sliding average method to process the number of reported cases per day. An SEIAR transmission dynamics model, which was the first to take asymptomatic group into consideration and applied indicators of R 0, Reff, Rt to evaluate the transmissibility of SARS, and further illustrated the control effectiveness of interventions for SARS in 8 Chinese cities.

Results

The R 0 for SARS in descending order was: Tianjin city (R 0 = 8.249), Inner Mongolia Autonomous Region, Shanxi Province, Hebei Province, Beijing City, Guangdong Province, Taiwan Province, and Hong Kong. R 0 of the SARS epidemic was generally higher in Mainland China than in Hong Kong and Taiwan Province (Mainland China: R 0 = 6.058 ± 1.703, Hong Kong: R 0 = 2.159, Taiwan: R 0 = 3.223). All cities included in this study controlled the epidemic successfully (Reff<1) with differences in duration. Rt in all regions showed a downward trend, but there were significant fluctuations in Guangdong Province, Hong Kong and Taiwan Province compared to other areas.

Conclusion

The SARS epidemic in China showed a trend of spreading from south to north, i.e., Guangdong Province and Beijing City being the central regions, respectively, and from there to the surrounding areas. In contrast, the SARS epidemic in the central region did not stir a large-scale transmission. There were also significant differences in transmissibility among eight regions, with R0 significantly higher in the northern region than that in the southern region. Different regions were able to control the outbreak successfully in differences time.

Possibility of mpox viral transmission and control from high-risk to the general population: a modeling study

BACKGROUND

Mpox is an emerging infectious disease that is now a global hazard. The strategies for preventing and controlling mpox should be further investigated in terms of transmission characteristics, infection risk among different populations, and ideal therapeutic approaches.

METHODS

A multi-group dynamic model was used to quantify the transmissibility of mpox. We further analyzed the transmission risk from men who have sex with men (MSM) to non-MSM and evaluated the effects of three intervention measures, including community-based prevention, early detection, and vaccination.

RESULTS

The median value of effective reproduction number (R_eff) and probability of contact via a single contact (q) among MSM worldwide is 3.11 (interquartile range [IQR]: 2.82-5.57) and 2.15% (IQR: 1.95-3.84%). We found that the cumulative incidence rate of non-MSM is much lower than that of MSM (< 1/2048) when the possibility of infection (including the percentage of high-risk behaviors of contact degree [C] and q) was lowered to less than 1 in 100,000. When comparing the three intervention measures, if we want to control the cumulative incidence rate to 5.96 × 10^-8 we need to increase the vaccine coverage to 81% or reduce the transmission rate factor (Cq) to 70% or shorten the transmission period to 74%.

CONCLUSIONS

Mpox has high transmissibility in MSM, which required minimize the risk of infection and exposure to high-risk populations. Community prevention and control is the top priority of interventions to contain the spread of mpox.

A comparative study on the three calculation methods for reproduction numbers of COVID-19

Objective

This study uses four COVID-19 outbreaks as examples to calculate and compare merits and demerits, as well as applicational scenarios, of three methods for calculating reproduction numbers.

Method

The epidemiological characteristics of the COVID-19 outbreaks are described. Through the definition method, the next-generation matrix-based method, and the epidemic curve and serial interval (SI)-based method, corresponding reproduction numbers were obtained and compared.

Results

Reproduction numbers (R eff ), obtained by the definition method of the four regions, are 1.20, 1.14, 1.66, and 1.12. Through the next generation matrix method, in region H R eff = 4.30, 0.44; region P R eff = 6.5, 1.39, 0; region X R eff = 6.82, 1.39, 0; and region Z R eff = 2.99, 0.65. Time-varying reproduction numbers (R t ), which are attained by SI of onset dates, are decreasing with time. Region H reached its highest R t = 2.8 on July 29 and decreased to R t < 1 after August 4; region P reached its highest R t = 5.8 on September 9 and dropped to R t < 1 by September 14; region X had a fluctuation in the R t and R t < 1 after September 22; R t in region Z reached a maximum of 1.8 on September 15 and decreased continuously to R t < 1 on September 19.

Conclusion

The reproduction number obtained by the definition method is optimal in the early stage of epidemics with a small number of cases that have clear transmission chains to predict the trend of epidemics accurately. The effective reproduction number R eff , calculated by the next generation matrix, could assess the scale of the epidemic and be used to evaluate the effectiveness of prevention and control measures used in epidemics with a large number of cases. Time-varying reproduction number R t , obtained via epidemic curve and SI, can give a clear picture of the change in transmissibility over time, but the conditions of use are more rigorous, requiring a greater sample size and clear transmission chains to perform the calculation. The rational use of the three methods for reproduction numbers plays a role in the further study of the transmissibility of COVID-19.

Evaluation of the transmissibility of norovirus and the effectiveness of prevention and control measures for schools in Jiangsu Province

OBJECTIVE

This study aims to estimate the transmissibility of norovirus outbreaks in schools by different transmission routes, and to evaluate the effects of isolation, school-closure and disinfection measures under different intervention intensities, finally, scientific prevention and control suggestions are proposed.

METHOD

23 outbreaks of norovirus infectious diarrhea occurring in Jiangsu Province's school from 2012-2018 were selected and fitted to the model. The data includes various types of school places and pathogen genotype. A 'SEIAQRW' model with two transmission routes was established. The transmissibility of each outbreak was assessed using effective reproduction number, the efficacy of different intervention measures and intensities were evaluated by calculating the total attack rate and peak incidence.

RESULTS

The mean effective reproduction number of noroviruses was estimated to be 8.92 for the human-to-human route of transmission and 2.19 for the water or food-to-human route of transmission. When all symptomatic cases were isolated, the median peak incidence for both transmission routes both being less than 1.8%. There was a smaller reduction in total attack rate compared to peak incidence, the median total attack rate for the two transmission routes decreased by 17.59% and 42.09%, respectively. When the effect of school-closure or disinfection is more than 90%, the total attack rate and peak incidence in the human-to-human route are reduced by more than 90% compared to no intervention, and the peak incidence in the water or food-to-human routes can be reduced to less than 1.4%, but the reduction in the total attack rate is only 50% or so.

CONCLUSION

Norovirus outbreaks have a high rate of transmission in schools. In the case of norovirus outbreaks, isolation should be complemented by other interventions, and the implementation of high-intensity school closures or disinfection of the external environment can be effective in reducing the spread of the virus.

Transmissibility of tuberculosis among students and non-students: an occupational-specific mathematical modelling

BACKGROUND

Recently, despite the steady decline in the tuberculosis (TB) epidemic globally, school TB outbreaks have been frequently reported in China. This study aimed to quantify the transmissibility of Mycobacterium tuberculosis (MTB) among students and non-students using a mathematical model to determine characteristics of TB transmission.

METHODS

We constructed a dataset of reported TB cases from four regions (Jilin Province, Xiamen City, Chuxiong Prefecture, and Wuhan City) in China from 2005 to 2019. We classified the population and the reported cases under student and non-student groups, and developed two mathematical models [nonseasonal model (Model A) and seasonal model (Model B)] based on the natural history and transmission features of TB. The effective reproduction number (R_eff) of TB between groups were calculated using the collected data.

RESULTS

During the study period, data on 456,423 TB cases were collected from four regions: students accounted for 6.1% of cases. The goodness-of-fit analysis showed that Model A had a better fitting effect (P < 0.001). The average R_eff of TB estimated from Model A was 1.68 [interquartile range (IQR): 1.20-1.96] in Chuxiong Prefecture, 1.67 (IQR: 1.40-1.93) in Xiamen City, 1.75 (IQR: 1.37-2.02) in Jilin Province, and 1.79 (IQR: 1.56-2.02) in Wuhan City. The average R_eff of TB in the non-student population was 23.30 times (1.65/0.07) higher than that in the student population.

CONCLUSIONS

The transmissibility of MTB remains high in the non-student population of the areas studied, which is still dominant in the spread of TB. TB transmissibility from the non-student-to-student-population had a strong influence on students. Specific interventions, such as TB screening, should be applied rigorously to control and to prevent TB transmission among students.

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models

BACKGROUND

There is a raising concern of a higher infectious Omicron BA.2 variant and the latest BA.4, BA.5 variant, made it more difficult in the mitigation process against COVID-19 pandemic. Our study aimed to find optimal control strategies by transmission of dynamic model from novel invasion theory.

METHODS

Based on the public data sources from January 31 to May 31, 2022, in four cities (Nanjing, Shanghai, Shenzhen and Suzhou) of China. We segmented the theoretical curves into five phases based on the concept of biological invasion. Then, a spatial autocorrelation analysis was carried out by detecting the clustering of the studied areas. After that, we choose a mathematical model of COVID-19 based on system dynamics methodology to simulate numerous intervention measures scenarios. Finally, we have used publicly available migration data to calculate spillover risk.

RESULTS

Epidemics in Shanghai and Shenzhen has gone through the entire invasion phases, whereas Nanjing and Suzhou were all ended in the establishment phase. The results indicated that Rt value and public health and social measures (PHSM)-index of the epidemics were a negative correlation in all cities, except Shenzhen. The intervention has come into effect in different phases of invasion in all studied cities. Until the May 31, most of the spillover risk in Shanghai remained above the spillover risk threshold (18.81-303.84) and the actual number of the spillovers (0.94-74.98) was also increasing along with the time. Shenzhen reported Omicron cases that was only above the spillover risk threshold (17.92) at the phase of outbreak, consistent with an actual partial spillover. In Nanjing and Suzhou, the actual number of reported cases did not exceed the spillover alert value.

CONCLUSIONS

Biological invasion is positioned to contribute substantively to understanding the drivers and mechanisms of the COVID-19 spread and outbreaks. After evaluating the spillover risk of cities at each invasion phase, we found the dynamic zero-COVID strategy implemented in four cities successfully curb the disease epidemic peak of the Omicron variant, which was highly correlated to the way to perform public health and social measures in the early phases right after the invasion of the virus.

Application of logistic differential equation models for early warning of infectious diseases in Jilin Province

Background

There is still a relatively serious disease burden of infectious diseases and the warning time for different infectious diseases before implementation of interventions is important. The logistic differential equation models can be used for predicting early warning of infectious diseases. The aim of this study is to compare the disease fitting effects of the logistic differential equation (LDE) model and the generalized logistic differential equation (GLDE) model for the first time using data on multiple infectious diseases in Jilin Province and to calculate the early warning signals for different types of infectious diseases using these two models in Jilin Province to solve the disease early warning schedule for Jilin Province throughout the year.

Methods

Collecting the incidence of 22 infectious diseases in Jilin Province, China. The LDE and GLDE models were used to calculate the recommended warning week (RWW), the epidemic acceleration week (EAW) and warning removed week (WRW) for acute infectious diseases with seasonality, respectively.

Results

Five diseases were selected for analysis based on screening principles: hemorrhagic fever with renal syndrome (HFRS), shigellosis, mumps, Hand, foot and mouth disease (HFMD), and scarlet fever. The GLDE model fitted the above diseases better (0.80 ≤ R2 ≤ 0.94, P <  0. 005) than the LDE model. The estimated warning durations (per year) of the LDE model for the above diseases were: weeks 12–23 and 40–50; weeks 20–36; weeks 15–24 and 43–52; weeks 26–34; and weeks 16–25 and 41–50. While the durations of early warning (per year) estimated by the GLDE model were: weeks 7–24 and 36–51; weeks 13–37; weeks 11–26 and 39–54; weeks 23–35; and weeks 12–26 and 40–50.

Conclusions

Compared to the LDE model, the GLDE model provides a better fit to the actual disease incidence data. The RWW appeared to be earlier when estimated with the GLDE model than the LDE model. In addition, the WRW estimated with the GLDE model were more lagged and had a longer warning time.

Mathematical Models Supporting Control of COVID-19

Mathematical models have played an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic. The aim of this review is to describe the use of COVID-19 mathematical models, their classification, and the advantages and disadvantages of different types of models. We conducted subject heading searches of PubMed and China National Knowledge Infrastructure with the terms "COVID-19," "Mathematical Statistical Model," "Model," "Modeling," "Agent-based Model," and "Ordinary Differential Equation Model" and classified and analyzed the scientific literature retrieved in the search. We categorized the models as data-driven or mechanism-driven. Data-driven models are mainly used for predicting epidemics, and have the advantage of rapid assessment of disease instances. However, their ability to determine transmission mechanisms is limited. Mechanism-driven models include ordinary differential equation (ODE) and agent-based models. ODE models are used to estimate transmissibility and evaluate impact of interventions. Although ODE models are good at determining pathogen transmission characteristics, they are less suitable for simulation of early epidemic stages and rely heavily on availability of first-hand field data. Agent-based models consider influences of individual differences, but they require large amounts of data and can take a long time to develop fully. Many COVID-19 mathematical modeling studies have been conducted, and these have been used for predicting trends, evaluating interventions, and calculating pathogen transmissibility. Successful infectious disease modeling requires comprehensive considerations of data, applications, and purposes.

Study on the interaction between different pathogens of Hand, foot and mouth disease in five regions of China

Objectives

This study aims to explore the interaction of different pathogens in Hand, foot and mouth disease (HFMD) by using a mathematical epidemiological model and the reported data in five regions of China.

Methods

A cross-regional dataset of reported HFMD cases was built from four provinces (Fujian Province, Jiangsu province, Hunan Province, and Jilin Province) and one municipality (Chongqing Municipality) in China. The subtypes of the pathogens of HFMD, including Coxsackievirus A16 (CV-A16), enteroviruses A71 (EV-A71), and other enteroviruses (Others), were included in the data. A mathematical model was developed to fit the data. The effective reproduction number (R _eff ) was calculated to quantify the transmissibility of the pathogens.

Results

In total, 3,336,482 HFMD cases were collected in the five regions. In Fujian Province, the R _eff between CV-A16 and EV-A71&CV-A16, and between CV-A16 and CV-A16&Others showed statistically significant differences (P < 0.05). In Jiangsu Province, there was a significant difference in R _eff (P < 0.05) between the CV-A16 and Total. In Hunan Province, the R _eff between CV-A16 and EV-A71&CV-A16, between CV-A16 and Total were significant (P < 0.05). In Chongqing Municipality, we found significant differences of the R _eff (P < 0.05) between CV-A16 and CV-A16&Others, and between Others and CV-A16&Others. In Jilin Province, significant differences of the R _eff (P < 0.05) were found between EV-A71 and Total, and between Others and Total.

Conclusion

The major pathogens of HFMD have changed annually, and the incidence of HFMD caused by others and CV-A16 has surpassed that of EV-A71 in recent years. Cross-regional differences were observed in the interactions between the pathogens.

Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022

Background

The epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control.

Methods

COVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (R _eff), time-dependent reproduction number (R _t), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (D _ID )/reported date (D _IR ) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P < 0.05 indicated that the difference was statistically significant.

Results

Mainland China has maintained a "dynamic zero-out strategy" since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum R _eff value of Omicron variant outbreaks was highest (median: 6.7; ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%; [IQR]: 87.30-94.27%), and the differences were statistically significant. The D _ID and D _IR for all strains was mostly in a range of 0-2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant.

Conclusion

With the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. R _eff is more suitable than R _t for assessing the transmissibility of the disease during an epidemic outbreak.

Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018

Background: With the progress of urbanization, the mobility of people has gradually increased, which has led to the further spread of dengue fever. This study evaluated the transmissibility of dengue fever within districts and between different districts in Zhanjiang City to provide corresponding advice for cross-regional prevention and control. Methods: A mathematical model of transmission dynamics was developed to explore the transmissibility of the disease and to compare that between different regions. Results: A total of 467 DF cases (6.38 per 100,000 people) were reported in Zhanjiang City in 2018. In the model, without any intervention, the number of simulated cases in this epidemic reached about 950. The dengue fever transmissions between districts varied within and between regions. When the spread of dengue fever from Chikan Districts to other districts was cut off, the number of cases in other districts dropped significantly or even to zero. When the density of mosquitoes in Xiashan District was controlled, the dengue fever epidemic in Xiashan District was found to be significantly alleviated. Conclusions: When there is a dengue outbreak, timely measures can effectively control it from developing into an epidemic. Different prevention and control measures in different districts could efficiently reduce the risk of disease transmission.

[Progress in research of 2019-nCoV infection in children and adolescents]

As 2019-nCoV vaccine is widely used in the adult population, children and adolescents have gradually become an important susceptible population to 2019-nCoV due to their low coverage of the vaccine and high contact degree. Understanding the characteristics of 2019-nCoV infection in minors is vital. This paper summarized the progress in the research of 2019-nCoV in minors by using the data from the retrieval of recently published literature. Furthermore, the key characteristics of 2019-nCoV infection in minors, including the susceptibility, transmissibility, prognosis and immune response were analyzed and the progress in child and adolescent vaccine development was introduced.

Assessing the Impacts of Meteorological Factors on COVID-19 Pandemic Using Generalized Estimating Equations

Background

Meteorological factors have been proven to affect pathogens; both the transmission routes and other intermediate. Many studies have worked on assessing how those meteorological factors would influence the transmissibility of COVID-19. In this study, we used generalized estimating equations to evaluate the impact of meteorological factors on Coronavirus disease 2019 (COVID-19) by using three outcome variables, which are transmissibility, incidence rate, and the number of reported cases.

Methods

In this study, the data on the daily number of new cases and deaths of COVID-19 in 30 provinces and cities nationwide were obtained from the provincial and municipal health committees, while the data from 682 conventional weather stations in the selected provinces and cities were obtained from the website of the China Meteorological Administration. We built a Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model to fit the data, then we calculated the transmissibility of COVID-19 using an indicator of the effective reproduction number (Reff ). To quantify the different impacts of meteorological factors on several outcome variables including transmissibility, incidence rate, and the number of reported cases of COVID-19, we collected panel data and used generalized estimating equations. We also explored whether there is a lag effect and the different times of meteorological factors on the three outcome variables.

Results

Precipitation and wind speed had a negative effect on transmissibility, incidence rate, and the number of reported cases, while humidity had a positive effect on them. The higher the temperature, the lower the transmissibility. The temperature had a lag effect on the incidence rate, while the remaining five meteorological factors had immediate and lag effects on the incidence rate and the number of reported cases.

Conclusion

Meteorological factors had similar effects on incidence rate and number of reported cases, but different effects on transmissibility. Temperature, relative humidity, precipitation, sunshine hours, and wind speed had immediate and lag effects on transmissibility, but with different lag times. An increase in temperature may first cause a decrease in virus transmissibility and then lead to a decrease in incidence rate. Also, the mechanism of the role of meteorological factors in the process of transmissibility to incidence rate needs to be further explored.

Meteorological factors and tick density affect the dynamics of SFTS in jiangsu province, China

Background

This study aimed to explore whether the transmission routes of severe fever with thrombocytopenia syndrome (SFTS) will be affected by tick density and meteorological factors, and to explore the factors that affect the transmission of SFTS. We used the transmission dynamics model to calculate the transmission rate coefficients of different transmission routes of SFTS, and used the generalized additive model to uncover how meteorological factors and tick density affect the spread of SFTS.

Methods

In this study, the time-varying infection rate coefficients of different transmission routes of SFTS in Jiangsu Province from 2017 to 2020 were calculated based on the previous multi-population multi-route dynamic model (MMDM) of SFTS. The changes in transmission routes were summarized by collecting questionnaires from 537 SFTS cases in 2018–2020 in Jiangsu Province. The incidence rate of SFTS and the infection rate coefficients of different transmission routes were dependent variables, and month, meteorological factors and tick density were independent variables to establish a generalized additive model (GAM). The optimal GAM was selected using the generalized cross-validation score (GCV), and the model was validated by the 2016 data of Zhejiang Province and 2020 data of Jiangsu Province. The validated GAMs were used to predict the incidence and infection rate coefficients of SFTS in Jiangsu province in 2021, and also to predict the effect of extreme weather on SFTS.

Results

The number and proportion of infections by different transmission routes for each year and found that tick-to-human and human-to-human infections decreased yearly, but infections through animal and environmental transmission were gradually increasing. MMDM fitted well with the three-year SFTS incidence data (P<0.05). The best intervention to reduce the incidence of SFTS is to reduce the effective exposure of the population to the surroundings. Based on correlation tests, tick density was positively correlated with air temperature, wind speed, and sunshine duration. The best GAM was a model with tick transmissibility to humans as the dependent variable, without considering lagged effects (GCV = 5.9247E-22, R² = 96%). Reported incidence increased when sunshine duration was higher than 11 h per day and decreased when temperatures were too high (>28°C). Sunshine duration and temperature had the greatest effect on transmission from host animals to humans. The effect of extreme weather conditions on SFTS was short-term, but there was no effect on SFTS after high temperature and sunshine hours.

Conclusions

Different factors affect the infection rate coefficients of different transmission routes. Sunshine duration, relative humidity, temperature and tick density are important factors affecting the occurrence of SFTS. Hurricanes reduce the incidence of SFTS in the short term, but have little effect in the long term. The most effective intervention to reduce the incidence of SFTS is to reduce population exposure to high-risk environments.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging vector-borne disease caused by SFTS virus. After the first case was detected in China in 2009, SFTS endemic areas have gradually increased, with more than 23 provinces and cities reporting SFTS cases. In order to explore the transmission mechanism of SFTS and explain the impact of meteorological factors and tick density on the transmission routes of SFTS, this study collected SFTS cases data, meteorological data and tick surveillance data in Jiangsu Province from 2017 to 2019 to investigate the study question. The multi-population and multi-route dynamic model established in the previous study was used to calculate the infection rate coefficients of various transmission routes of SFTS in Jiangsu Province, and the generalized additive model was established to further elaborate the influence of SFTS transmission mechanism.

Analysis of HFMD Transmissibility Among the Whole Population and Age Groups in a Large City of China

Background

Hand-Foot-and-Mouth-Disease (HFMD) has been widely spread in Asia, and has result in a high disease burden for children in many countries. However, the dissemination characteristics intergroup and between different age groups are still not clear. In this study, we aim to analyze the differences in the transmissibility of HFMD, in the whole population and among age groups in Shenzhen city, by utilizing mathematical models.

Methods

A database that reports HFMD cases in Shenzhen city from January 2010 to December 2017 was collected. In the first stage, a Susceptive-Infected-Recovered (SIR) model was built to fit data of Shenzhen city and its districts, and R_eff was used to assess transmissibility in each district. In the second stage, a cross-age groups SIR model was constructed to calculate the difference in transmissibility of reported cases among three age groups of EV71 virus: 0–3 years, 3–5 years, and over 5 years which was denoted as age group 1, 2, and 3, respectively.

Results

From 2010 to 2017, 345,807 cases of HFMD were reported in Shenzhen city, with peak incidence in spring and autumn in Shenzhen city and most of its districts each year. Analysis of the EV71 incidence data by age group revealed that age Group 1 have the highest incidence (3.13 ×10⁻⁷–2.31 ×10⁻⁴) while age group 3 had the lowest incidence (0–3.54 ×10⁻⁵). The differences in weekly incidence of EV71 between age groups were statistically significant (t₁₂ = 7.563, P < 0.0001; t₂₃ = 12.420, P < 0.0001; t₁₃ = 16.996, P < 0.0001). The R² of the SIR model Shenzhen city population-wide HFMD fit for each region was >0.5, and P < 0.001. R_eff values were >1 for the vast majority of time and regions, indicating that the HFMD virus has the ability to spread in Shenzhen city over the long-term. Differences in R_eff values between regions were judged by using analysis of variance (ANOVA) (F = 0.541, P = 0.744). S_iI_iR_i-S_jI_jR_j models between age groups had R² over 0.7 for all age groups and P <0.001. The R_eff values between groups show that the 0–2 years old group had the strongest transmissibility (median: 2.881, range: 0.017–9.897), followed by the over 5 years old group (median: 1.758, range: 1.005–5.279), while the 3–5 years old group (median: 1.300, range: 0.005–1.005) had the weakest transmissibility of the three groups. Intra-group transmissibility was strongest in the 0–2 years age group (median: 1.787, range: 0–9.146), followed by Group 1 to Group 2 (median: 0.287, range: 0–1.988) and finally Group 1 to Group 3 (median: 0.287, range: 0–1.988).

Conclusion

The incidence rate of HFMD is high in Shenzhen city. In the data on the incidence of EV71 in each age group, the highest incidence was in the 0–2 years age group, and the lowest incidence was in the over 5 years age group. The differences in weekly incidence rate of EV71 among age groups were statistically significant. Children with the age of 0–2 years had the highest transmissibility.

Epidemiological Characteristics and Transmissibility of Human Immunodeficiency Virus in Nanning City, China, 2001-2020

Background: Human immunodeficiency virus (HIV) is a single-stranded RNA virus that can weaken the body's cellular and humoral immunity and is a serious disease without specific drug management and vaccine. This study aimed to evaluate the epidemiologic characteristics and transmissibility of HIV.

Methods: Data on HIV follow-up were collected in Nanning City, Guangxi Zhuang Autonomous, China. An HIV transmission dynamics model was built to simulate the transmission of HIV and estimate its transmissibility by comparing the effective reproduction number (R_eff) at different stages: the rapid growth period from January 2001 to March 2005, slow growth period from April 2005 to April 2011, and the plateau from May 2011 to December 2019 of HIV in Nanning City.

Results: High-risk areas of HIV prevalence in Nanning City were mainly concentrated in suburbs. Furthermore, high-risk groups were those of older age, with lower income, and lower education levels. The R_eff in each stage (rapid growth, slow growth, and plateau) were 2.74, 1.62, and 1.15, respectively, which suggests the transmissibility of HIV in Nanning City has declined and prevention and control measures have achieved significant results.

Conclusion: Over the past 20 years, the HIV incidence in Nanning has remained at a relatively high level, but its development trend has been curbed. Transmissibility was reduced from 2.74 to 1.15. Therefore, the prevention and treatment measures in Nanning City have achieved significant improvement.

Correlation between mumps and meteorological factors in Xiamen City, China: A modelling study

Objective

Mumps is a seasonal infectious disease, always occurring in winter and spring. In this study, we aim to analyze its epidemiological characteristics, transmissibility, and its correlation with meteorological variables.

Method

A seasonal Susceptible–Exposed–Infectious/Asymptomatic–Recovered model and a next-generation matrix method were applied to estimate the time-dependent reproduction number (R_t).

Results

The seasonal double peak of annual incidence was mainly in May to July and November to December. There was high transmission at the median of R_t = 1.091 (ranged: 0 to 4.393). R_t was seasonally distributed mainly from February to April and from September to November. Correlations were found between temperature (Pearson correlation coefficient [r] ranged: from 0.101 to 0.115), average relative humidity (r = 0.070), average local pressure (r = -0.066), and the number of new cases. In addition, average local pressure (r = 0.188), average wind speed (r = 0.111), air temperature (r ranged: -0.128 to -0.150), average relative humidity (r = -0.203) and sunshine duration (r = -0.075) were all correlated with R_t.

Conclusion

A relatively high level of transmissibility has been found in Xiamen City, leading to a continuous epidemic of mumps. Meteorological factors, especially air temperature and relative humidity, may be more closely associated with mumps than other factors.

An Easy-to-Use Public Health-Driven Method (the Generalized Logistic Differential Equation Model) Accurately Simulated COVID-19 Epidemic in Wuhan and Correctly Determined the Early Warning Time

Introduction

Modeling on infectious diseases is significant to facilitate public health policymaking. There are two main mathematical methods that can be used for the simulation of the epidemic and prediction of optimal early warning timing: the logistic differential equation (LDE) model and the more complex generalized logistic differential equation (GLDE) model. This study aimed to compare and analyze these two models.

Methods

We collected data on (coronavirus disease 2019) COVID-19 and four other infectious diseases and classified the data into four categories: different transmission routes, different epidemic intensities, different time scales, and different regions, using R2 to compare and analyze the goodness-of-fit of LDE and GLDE models.

Results

Both models fitted the epidemic curves well, and all results were statistically significant. The R2 test value of COVID-19 was 0.924 (p &lt; 0.001) fitted by the GLDE model and 0.916 (p &lt; 0.001) fitted by the LDE model. The R2 test value varied between 0.793 and 0.966 fitted by the GLDE model and varied between 0.594 and 0.922 fitted by the LDE model for diseases with different transmission routes. The R2 test values varied between 0.853 and 0.939 fitted by the GLDE model and varied from 0.687 to 0.769 fitted by the LDE model for diseases with different prevalence intensities. The R2 test value varied between 0.706 and 0.917 fitted by the GLDE model and varied between 0.410 and 0.898 fitted by the LDE model for diseases with different time scales. The GLDE model also performed better with nation-level data with the R2 test values between 0.897 and 0.970 vs. 0.731 and 0.953 that fitted by the LDE model. Both models could characterize the patterns of the epidemics well and calculate the acceleration weeks.

Conclusion

The GLDE model provides more accurate goodness-of-fit to the data than the LDE model. The GLDE model is able to handle asymmetric data by introducing shape parameters that allow it to fit data with various distributions. The LDE model provides an earlier epidemic acceleration week than the GLDE model. We conclude that the GLDE model is more advantageous in asymmetric infectious disease data simulation.

Surveillance, Epidemiology and Impact of EV-A71 Vaccination on Hand, Foot, and Mouth Disease in Nanchang, China, 2010-2019

After the first national-scale outbreak of Hand, foot, and mouth disease (HFMD) in China, a national surveillance network was established. Here we described the epidemiology and pathogenic profile of HFMD and the impact of EV-A71 vaccination on pathogen spectrum of enteroviruses in the southeastern Chinese city of Nanchang during 2010–2019. A total of 7,951 HFMD cases from sentinel hospitals were included, of which 4,800 EV-positive cases (60.4%) were identified by real-time RT-PCR. During 2010–2012, enterovirus 71 (EV-A71) was the main causative agent of HFMD, causing 63.1% of cases, followed by 19.3% cases associated with coxsackievirus A16 (CV-A16). Since 2013, the proportion of other enteroviruses has increased dramatically, with the sub genotype D3 strain of Coxsackievirus A6 (CV-A6) replacing the dominance of EV-A71. These genetically diverse native strains of CV-A6 have co-transmitted and co-evolved in Nanchang. Unlike EV-A71 and CV-A16, most CV-A6 infections were concentrated in autumn and winter. The incidence of EV-A71 infection negatively correlated with EV-A71 vaccination (r = −0.990, p = 0.01). And severe cases sharply declined as the promotion of EV-A71 vaccines. After 2-year implementation of EV-A71 vaccination, EV-A71 is no longer detected from the reported HFMD cases in Nanchang. In conclusion, EV-A71 vaccination changed the pattern of HFMD epidemic, and CV-A6 replaced the dominance of EV-A71 over time.

Study of Risk Factors for Total Attack Rate and Transmission Dynamics of Norovirus Outbreaks, Jiangsu Province, China, From 2012 to 2018

Objective: To describe the epidemiological characteristics of norovirus outbreaks in Jiangsu Province, utilize the total attack rate (TAR) and transmissibility (R_unc) as the measurement indicators of the outbreak, and a statistical difference in risk factors associated with TAR and transmissibility was compared. Ultimately, this study aimed to provide scientific suggestions to develop the most appropriate prevention and control measures.

Method: We collected epidemiological data from investigation reports of all norovirus outbreaks in Jiangsu Province from 2012 to 2018 and performed epidemiological descriptions, sequenced the genes of the positive specimens collected that were eligible for sequencing, created a database and calculated the TAR, constructed SEIAR and SEIARW transmission dynamic models to calculate R_unc, and performed statistical analyses of risk factors associated with the TAR and R_unc.

Results: We collected a total of 206 reported outbreaks, of which 145 could be used to calculate transmissibility. The mean TAR in was 2.6% and the mean R_unc was 12.2. The epidemiological characteristics of norovirus outbreaks showed an overall increasing trend in the number of norovirus outbreaks from 2012 to 2018; more outbreaks in southern Jiangsu than northern Jiangsu; more outbreaks in urban areas than in rural areas; outbreaks occurred mostly in autumn and winter. Most of the sites where outbreaks occurred were schools, especially primary schools. Interpersonal transmission accounted for the majority. Analysis of the genotypes of noroviruses revealed that the major genotypes of the viruses changed every 3 years, with the GII.2 [P16] type of norovirus dominating from 2016 to 2018. Statistical analysis of TAR associated with risk factors found statistical differences in all risk factors, including time (year, month, season), location (geographic location, type of settlement, type of premises), population (total number of susceptible people at the outbreak site), transmission route, and genotype (P < 0.05). Statistical analysis of transmissibility associated with risk factors revealed that only transmissibility was statistically different between sites.

Conclusions: The number of norovirus outbreaks in Jiangsu Province continues to increase during the follow-up period. Our findings highlight the impact of different factors on norovirus outbreaks and identify the key points of prevention and control in Jiangsu Province.

Epidemiological Characteristics and Transmissibility for SARS-CoV-2 of Population Level and Cluster Level in a Chinese City

Background

To date, there is a lack of sufficient evidence on the type of clusters in which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is most likely to spread. Notably, the differences between cluster-level and population-level outbreaks in epidemiological characteristics and transmissibility remain unclear. Identifying the characteristics of these two levels, including epidemiology and transmission dynamics, allows us to develop better surveillance and control strategies following the current removal of suppression measures in China.

Methods

We described the epidemiological characteristics of SARS-CoV-2 and calculated its transmissibility by taking a Chinese city as an example. We used descriptive analysis to characterize epidemiological features for coronavirus disease 2019 (COVID-19) incidence database from 1 Jan 2020 to 2 March 2020 in Chaoyang District, Beijing City, China. The susceptible-exposed-infected-asymptomatic-recovered (SEIAR) model was fitted with the dataset, and the effective reproduction number (R_eff) was calculated as the transmissibility of a single population. Also, the basic reproduction number (R₀) was calculated by definition for three clusters, such as household, factory and community, as the transmissibility of subgroups.

Results

The epidemic curve in Chaoyang District was divided into three stages. We included nine clusters (subgroups), which comprised of seven household-level and one factory-level and one community-level cluster, with sizes ranging from 2 to 17 cases. For the nine clusters, the median incubation period was 17.0 days [Interquartile range (IQR): 8.4–24.0 days (d)], and the average interval between date of onset (report date) and diagnosis date was 1.9 d (IQR: 1.7 to 6.4 d). At the population level, the transmissibility of the virus was high in the early stage of the epidemic (R_eff = 4.81). The transmissibility was higher in factory-level clusters (R₀ = 16) than in community-level clusters (R₀ = 3), and household-level clusters (R₀ = 1).

Conclusions

In Chaoyang District, the epidemiological features of SARS-CoV-2 showed multi-stage pattern. Many clusters were reported to occur indoors, mostly from households and factories, and few from the community. The risk of transmission varies by setting, with indoor settings being more severe than outdoor settings. Reported household clusters were the predominant type, but the population size of the different types of clusters limited transmission. The transmissibility of SARS-CoV-2 was different between a single population and its subgroups, with cluster-level transmissibility higher than population-level transmissibility.

The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China

Background

Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China.

Methods

We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (R_eff) was used to estimate the transmission interaction in different age groups.

Results

A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (R_eff = 4.28), followed by group 2 to 3 (R_eff = 2.61), and group 2 to 4 (R_eff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45–64 years old.

Conclusions

Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15–64 years should first be vaccinated to prevent transmission in China.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00922-4.

Feasibility of Booster Vaccination in High-Risk Populations for Controlling Coronavirus Variants - China, 2021

Introduction

Vaccination booster shots are completely necessary for controlling breakthrough infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China. The study aims to estimate effectiveness of booster vaccines for high-risk populations (HRPs).

Methods

A vaccinated Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model was developed to simulate scenarios of effective reproduction number (R_eff) from 4 to 6. Total number of infectious and asymptomatic cases were used to evaluated vaccination effectiveness.

Results

Our model showed that we could not prevent outbreaks when covering 80% of HRPs with booster unless R_eff=4.0 or the booster vaccine had efficacy against infectivity and susceptibility of more than 90%. The results were consistent when the outcome index was confirmed cases or asymptomatic cases.

Conclusions

An ideal coronavirus disease 2019 (COVID-19) booster vaccination strategy for HRPs would be expected to reach the initial goal to control the transmission of the Delta variant in China. Accordingly, the recommendation for the COVID-19 booster vaccine should be implemented in HRPs who are already vaccinated and could prevent transmission to other groups.

Investigation and analysis on an outbreak of norovirus infection in a health school in Guangdong Province, China

Our objective was to describe the epidemiological features of an outbreak of norovirus infection in a health school in Guangdong province, China, to identify the cause of such a large scale outbreak of norovirus among older students, to simulate the transmission dynamics, and to evaluate the effect of intervention measures of GII.17 [P17] genotype norovirus infection. We identified all cases during the outbreak. Descriptive epidemiological, analytical epidemiological and hygiene survey methods were used to described the outbreak epidemic course and identify the cause of the outbreak of norovirus infection. We also used dynamical model to simulate the transmission dynamics of norovirus infection and evaluate the effect of intervention measures. Norovirus genotyping was assigned to the newly obtained strains, with a maximum likelihood phylogenetic analysis conducted. There were 360 cases of 42 classes in five grades with a 12.99% attack rate. Proportionally, more students were in contact with sick students and vomit in the suspected case group than the control group (χ² = 5.535, P = 0.019 and χ² = 5.549, P = 0.019, respectively). The basic reproduction number was 8.32 before and 0.49 after the intervention. Dynamical modeling showed that if the isolation rate was higher or case isolation began earlier, the total attack rate would decrease. Molecular characterization identified the GII.17 [P17] genotype in all stains obtained from the health school, which were clustered with high support in the phylogenetic tree. This was an outbreak of norovirus infection caused by contact transmission. The main reasons for the spread of the epidemic were the later control time, irregular treatment of vomit and no case isolation. The transmission dynamics of contact transmission was high, more efficient control measures should be employed.

Estimating the transmissibility of hepatitis C: A modelling study in Yichang City, China

Yichang is a city in central China in the Hubei Province. This study aimed to estimate the dynamics of the transmissibility of hepatitis C using a mathematical model and predict the transmissibility of hepatitis C in 2030. Data of hepatitis C cases from 13 counties or districts (cities) in Yichang from 2008 to 2016 were collected. A susceptible-infectious-chronic-recovered (SICR) model was developed to fit the data. The transmissibility of hepatitis C at the counties or districts was calculated based on new infections (including infected or chronically infected cases) reported monthly in the city caused by one infectious individual (MNI). The trend of the MNI was fitted and predicted using 11 models, with the coefficient of determination (R² ) was being used to test the goodness of fit of these models. A total of 3065 cases of hepatitis C were reported in Yichang from 2008 to 2016. The median MNI of Yichang was 0.0768. According to the fitting results and analysis, the trend of transmissibility of hepatitis C in Yichang City conforms with the logarithmic (R²  = 0.918, p < 0.001):MNI = 0.265-0.108 log(t) and exponential (R²  = 0.939, p < 0.001): MNI = 0.344e^(-0.278t) models. Hence, the transmission of hepatitis C virus at the county level has a downward trend. In conclusion, the transmissibility of hepatitis C in Yichang has a downward trend. With the current preventive and control measures in place, the spread of hepatitis C can be controlled.

Capturing the Trajectory of Psychological Status and Analyzing Online Public Reactions During the Coronavirus Disease 2019 Pandemic Through Weibo Posts in China

When a major, sudden infectious disease occurs, people tend to react emotionally and display reactions such as tension, anxiety, fear, depression, and somatization symptoms. Social media played a substantial awareness role in developing countries during the outbreak of coronavirus disease 2019 (COVID-19). This study aimed to analyze public opinion regarding COVID-19 and to explore the trajectory of psychological status and online public reactions to the COVID-19 pandemic by examining online content from Weibo in China. This study consisted of three steps: first, Weibo posts created during the pandemic were collected and preprocessed on a large scale; second, public sentiment orientation was classified as "optimistic/pessimistic/neutral" orientation via natural language processing and manual determination procedures; and third, qualitative and quantitative analyses were conducted to reveal the trajectory of public psychological status and online public reactions during the COVID-19 pandemic. Public psychological status differed in different periods of the pandemic (from December 2019 to May 2020). The newly confirmed cases had an almost 1-month lagged effect on public psychological status. Among the 15 events with high impact indexes or related to government decisions, there were 10 optimism orientation > pessimism orientation (OP) events (2/3) and 5 pessimism orientation > optimism orientation (PO) events (1/3). Among the top two OP events, the high-frequency words were "race against time" and "support," while in the top two PO events, the high-frequency words were "irrationally purchase" and "pass away." We proposed a hypothesis that people developed negative self-perception when they received PO events, but their cognition was developed by how these external stimuli were processed and evaluated. These results offer implications for public health policymakers on understanding public psychological status from social media. This study demonstrates the benefits of promoting psychological healthcare and hygiene activity in the early period and improving risk perception for the public based on public opinion and the coping abilities of people. Health managers should focus on disseminating socially oriented strategies to improve the policy literacy of Internet users, thereby facilitating the disease prevention work for the COVID-19 pandemic and other major public events.

Hepatitis E in 24 Chinese Cities, 2008-2018: A New Analysis Method for the Disease's Occupational Characteristics

Background: The disease burden of hepatitis E remains high. We used a new method (richness, diversity, evenness, and similarity analyses) to classify cities according to the occupational classification of hepatitis E patients across regions in China and compared the results of cluster analysis. Methods: Data on reported hepatitis E cases from 2008 to 2018 were collected from 24 cities (9 in Jilin Province, 13 in Jiangsu Province, Xiamen City, and Chuxiong Yi Autonomous Prefecture). Traditional statistical methods were used to describe the epidemiological characteristics of hepatitis E patients, while the new method and cluster analysis were used to classify the cities by analyzing the occupational composition across regions. Results: The prevalence of hepatitis E in eastern China (Jiangsu Province) was similar to that in the south (Xiamen City) and southwest of China (Chuxiong Yi Autonomous Prefecture), but higher than that in the north (Jilin Province). The age of hepatitis E patients was concentrated between 41 and 60 years, and the sex ratio ranged from 1:1.6 to 1:3.4. Farming was the most highly prevalent occupation; other sub-prevalent occupations included retirement, housework and unemployment. The incidence of occupations among migrant workers, medical staff, teachers, and students was moderate. There were several occupational types with few or no records, such as catering industry, caregivers and babysitters, diaspora children, childcare, herders, and fishing (boat) people. The occupational similarity of hepatitis E was high among economically developed cities, such as Nanjing, Wuxi, Baicheng, and Xiamen, while the similarity was small among cities with large economic disparities, such as Nanjing and Chuxiong Yi Autonomous Prefecture. A comparison of the classification results revealed more similarities and some differences when using these two methods. Conclusion: In China, the factors with the greatest influence on the prevalence of hepatitis E are living in the south, farming as an occupation, being middle-aged or elderly, and being male. The 24 cities we studied were highly diverse and moderately similar in terms of the occupational distribution of patients with hepatitis E. We confirmed the validity of the new method on in classifying cities according to their occupational composition by comparing it with the clustering method.

Impact of interventions on the incidence of natural focal diseases during the outbreak of COVID-19 in Jiangsu Province, China

BACKGROUND

During the period of the coronavirus disease 2019 (COVID-19) outbreak, strong intervention measures, such as lockdown, travel restriction, and suspension of work and production, may have curbed the spread of other infectious diseases, including natural focal diseases. In this study, we aimed to study the impact of COVID-19 prevention and control measures on the reported incidence of natural focal diseases (brucellosis, malaria, hemorrhagic fever with renal syndrome [HFRS], dengue, severe fever with thrombocytopenia syndrome [SFTS], rabies, tsutsugamushi and Japanese encephalitis [JE]).

METHODS

The data on daily COVID-19 confirmed cases and natural focal disease cases were collected from Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial CDC). We described and compared the difference between the incidence in 2020 and the incidence in 2015-2019 in four aspects: trend in reported incidence, age, sex, and urban and rural distribution. An autoregressive integrated moving average (ARIMA) (p, d, q) × (P, D, Q)_s model was adopted for natural focal diseases, malaria and severe fever with thrombocytopenia syndrome (SFTS), and an ARIMA (p, d, q) model was adopted for dengue. Nonparametric tests were used to compare the reported and the predicted incidence in 2020, the incidence in 2020 and the previous 4 years, and the difference between the duration from illness onset date to diagnosed date (DID) in 2020 and in the previous 4 years. The determination coefficient (R²) was used to evaluate the goodness of fit of the model simulation.

RESULTS

Natural focal diseases in Jiangsu Province showed a long-term seasonal trend. The reported incidence of natural focal diseases, malaria and dengue in 2020 was lower than the predicted incidence, and the difference was statistically significant (P < 0.05). The reported incidence of brucellosis in July, August, October and November 2020, and SFTS in May to November 2020 was higher than that in the same period in the previous 4 years (P < 0.05). The reported incidence of malaria in April to December 2020, HFRS in March, May and December 2020, and dengue in July to November 2020 was lower than that in the same period in the previous 4 years (P < 0.05). In males, the reported incidence of malaria in 2020 was lower than that in the previous 4 years, and the reported incidence of dengue in 2020 was lower than that in 2017-2019. The reported incidence of malaria in the 20-60-year age group was lower than that in the previous 4 years; the reported incidence of dengue in the 40-60-year age group was lower than that in 2016-2018. The reported cases of malaria in both urban and rural areas were lower than in the previous 4 years. The DID of brucellosis and SFTS in 2020 was shorter than that in 2015-2018; the DID of tsutsugamushi in 2020 was shorter than that in the previous 4 years.

CONCLUSIONS

Interventions for COVID-19 may help control the epidemics of natural focal diseases in Jiangsu Province. The reported incidence of natural focal diseases, especially malaria and dengue, decreased during the outbreak of COVID-19 in 2020. COVID-19 prevention and control measures had the greatest impact on the reported incidence of natural focal diseases in males and people in the 20-60-year age group.

Modelling the Emerging COVID-19 Epidemic and Estimating Intervention Effectiveness - Taiwan, China, 2021

INTRODUCTION

The coronavirus disease 2019 (COVID-19) pandemic recently affected Taiwan, China. This study aimed to calculate the transmissibility of COVID-19 to predict trends and evaluate the effects of interventions.

METHODS

The data of reported COVID-19 cases was collected from April 20 to May 26, 2021, which included daily reported data (Scenario I) and reported data after adjustment (Scenario II). A susceptible-exposed-symptomatic-asymptomatic-recovered model was developed to fit the data. The effective reproductive number (Reff ) was used to estimate the transmissibility of COVID-19.

RESULTS

A total of 4,854 cases were collected for the modelling. In Scenario I, the intervention has already taken some effects from May 17 to May 26 (the Reff reduced to 2.1). When the Reff was set as 0.1, the epidemic was projected to end on July 4, and a total of 1,997 cases and 855 asymptomatic individuals would have been reported. In Scenario II, the interventions were projected as having been effective from May 24 to May 26 (the Reff reduced to 0.4). When the Reff was set as 0.1, the epidemic was projected to end on July 1, and a total of 1,482 cases and 635 asymptomatic individuals would have been reported.

CONCLUSION

The epidemic of COVID-19 was projected to end after at least one month, even if the most effective interventions were applied in Taiwan, China. Although there were some positive effects of intervention in Taiwan, China.

Containing the Transmission of COVID-19: A Modeling Study in 160 Countries

Background: It is much valuable to evaluate the comparative effectiveness of the coronavirus disease 2019 (COVID-19) prevention and control in the non-pharmacological intervention phase of the pandemic across countries and identify useful experiences that could be generalized worldwide. Methods: In this study, we developed a susceptible-exposure-infectious-asymptomatic-removed (SEIAR) model to fit the daily reported COVID-19 cases in 160 countries. The time-varying reproduction number (R t ) that was estimated through fitting the mathematical model was adopted to quantify the transmissibility. We defined a synthetic index (I AC ) based on the value of R t to reflect the national capability to control COVID-19. Results: The goodness-of-fit tests showed that the SEIAR model fitted the data of the 160 countries well. At the beginning of the epidemic, the values of R t of countries in the European region were generally higher than those in other regions. Among the 160 countries included in the study, all European countries had the ability to control the COVID-19 epidemic. The Western Pacific Region did best in continuous control of the epidemic, with a total of 73.76% of countries that can continuously control the COVID-19 epidemic, while only 43.63% of the countries in the European Region continuously controlled the epidemic, followed by the Region of Americas with 52.53% of countries, the Southeast Asian Region with 48% of countries, the African Region with 46.81% of countries, and the Eastern Mediterranean Region with 40.48% of countries. Conclusion: Large variations in controlling the COVID-19 epidemic existed across countries. The world could benefit from the experience of some countries that demonstrated the highest containment capabilities.

Estimating the Transmissibility of Mumps: A Modelling Study in Wuhan City, China

Despite the adoption of a national immunization program in China, the incidence of mumps remains high. This study aimed to describe the epidemiological characteristics, including the time, region, occupation, and age, of mumps in Wuhan from 2005 to 2018 and to evaluate its transmissibility. In this study, the susceptible-exposed-infectious-asymptomatic-recovered (SEIAR) model fitted the actual incidence data of mumps. The effective reproduction number (R t ) was used to evaluate and compare the transmission capacity in different areas. From 2005 to 2018, there were 36,415 cases. The incidence of mumps was highest among people aged 5-10 years (460.02 per 100,000). The SEIAR model fitted the reported mumps data well (P < 0.01). The median transmissibility (R t ) was 1.04 (range = 0-2.50). There were two peak spreads every year (from March to May and from October to December). The R t peak always appeared in the first 2 months of the peak incidence rate. The peak time of the epidemic spread of mumps was 1-2 months earlier than the peak incidence rate. The prevention and control measures of vaccination for children aged 5-10 years should be taken before the peak transmission capacity each year, 2 months before the peak of the outbreak, to reduce the spread of mumps.

Feasibility of controlling hepatitis E in Jiangsu Province, China: a modelling study

BACKGROUND

Hepatitis E, an acute zoonotic disease caused by the hepatitis E virus (HEV), has a relatively high burden in developing countries. The current research model on hepatitis E mainly uses experimental animal models (such as pigs, chickens, and rabbits) to explain the transmission of HEV. Few studies have developed a multi-host and multi-route transmission dynamic model (MHMRTDM) to explore the transmission feature of HEV. Hence, this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province.

METHODS

We developed a dataset comprising all reported HEV cases in Jiangsu Province from 2005 to 2018. The MHMRTDM was developed according to the natural history of HEV cases among humans and pigs and the multi-transmission routes such as person-to-person, pig-to-person, and environment-to-person. We estimated the key parameter of the transmission using the principle of least root mean square to fit the curve of the MHMRTDM to the reported data. We developed models with single or combined countermeasures to assess the effectiveness of interventions, which include vaccination, shortening the infectious period, and cutting transmission routes. The indicator, total attack rate (TAR), was adopted to assess the effectiveness.

RESULTS

From 2005 to 2018, 44 923 hepatitis E cases were reported in Jiangsu Province. The model fits the data well (R2 = 0.655, P < 0.001). The incidence of the disease in Jiangsu Province and its cities peaks are around March; however, transmissibility of the disease peaks in December and January. The model showed that the most effective intervention was interrupting the pig-to-person route during the incidence trough of September, thereby reducing the TAR by 98.11%, followed by vaccination (reducing the TAR by 76.25% when the vaccination coefficient is 100%) and shortening the infectious period (reducing the TAR by 50.05% when the infectious period is shortened to 15 days).

CONCLUSIONS

HEV could be controlled by interrupting the pig-to-person route, shortening the infectious period, and vaccination. Among these interventions, the most effective was interrupting the pig-to-person route.

Relative transmissibility of shigellosis among different age groups: A modeling study in Hubei Province, China

Shigellosis is a heavy disease burden in China especially in children aged under 5 years. However, the age-related factors involved in transmission of shigellosis are unclear. An age-specific Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model was applied to shigellosis surveillance data maintained by Hubei Province Centers for Disease Control and Prevention from 2005 to 2017. The individuals were divided into four age groups (≤ 5 years, 6-24 years, 25-59 years, and ≥ 60 years). The effective reproduction number (Reff), including infectivity (RI) and susceptibility (RS) was calculated to assess the transmissibility of different age groups. From 2005 to 2017, 130,768 shigellosis cases were reported in Hubei Province. The SEIAR model fitted well with the reported data (P < 0.001). The highest transmissibility (Reff) was from ≤ 5 years to the 25-59 years (mean: 0.76, 95% confidence interval [CI]: 0.34-1.17), followed by from the 6-24 years to the 25-59 years (mean: 0.69, 95% CI: 0.35-1.02), from the ≥ 60 years to the 25-59 years (mean: 0.58, 95% CI: 0.29-0.86), and from the 25-59 years to 25-59 years (mean: 0.50, 95% CI: 0.21-0.78). The highest infectivity was in ≤ 5 years (RI = 1.71), and was most commonly transmitted to the 25-59 years (45.11%). The highest susceptibility was in the 25-59 years (RS = 2.51), and their most common source was the ≤ 5 years (30.15%). Furthermore, "knock out" simulation predicted the greatest reduction in the number of cases occurred by when cutting off transmission routes among ≤ 5 years and from 25-59 years to ≤ 5 years. Transmission in ≤ 5 years occurred mainly within the group, but infections were most commonly introduced by individuals in the 25-59 years. Infectivity was highest in the ≤ 5 years and susceptibility was highest in the 25-59 years. Interventions to stop transmission should be directed at these age groups.

Modelling the transmission dynamics of severe fever with thrombocytopenia syndrome in Jiangsu Province, China

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that is regionally distributed in Asia, with high fatality. Constructing the transmission model of SFTS could help provide clues for disease control and fill the gap in research on SFTS models.

METHODS

We built an SFTS transmission dynamics model based on the susceptible-exposed-infectious-asymptomatic-recovered (SEIAR) model and the epidemiological characteristics of SFTS in Jiangsu Province. This model was used to evaluate the effect by cutting off different transmission routes and taking different interventions into account, to offer clues for disease prevention and control.

RESULTS

The transmission model fits the reported data well with a minimum R2 value of 0.29 and a maximum value of 0.80, P < 0.05. Meanwhile, cutting off the environmental transmission route had the greatest effect on the prevention and control of SFTS, while isolation and shortening the course of the disease did not have much effect.

CONCLUSIONS

The model we have built can be used to simulate the transmission of SFTS to help inform disease control. It is noteworthy that cutting off the environment-to-humans transmission route in the model had the greatest effect on SFTS prevention and control.

The epidemiological characteristics and effectiveness of countermeasures to contain coronavirus disease 2019 in Ningbo City, Zhejiang Province, China

A novel coronavirus (SARS-CoV-2) has spread worldwide and led to high disease burden around the world. This study aimed to explore the key parameters of SARS-CoV-2 infection and to assess the effectiveness of interventions to control the coronavirus disease 2019 (COVID-19). A susceptible-exposed-infectious-asymptomatic-recovered (SEIAR) model was developed for the assessment. The information of each confirmed case and asymptomatic infection was collected from Ningbo Center for Disease Control and Prevention (CDC) to calculate the key parameters of the model in Ningbo City, China. A total of 157 confirmed COVID-19 cases (including 51 imported cases and 106 secondary cases) and 30 asymptomatic infections were reported in Ningbo City. The proportion of asymptomatic infections had an increasing trend. The proportion of elder people in the asymptomatic infections was lower than younger people, and the difference was statistically significant (Fisher's Exact Test, P = 0.034). There were 22 clusters associated with 167 SARS-CoV-2 infections, among which 29 cases were asymptomatic infections, accounting for 17.37%. We found that the secondary attack rate (SAR) of asymptomatic infections was almost the same as that of symptomatic cases, and no statistical significance was observed (χ2 = 0.052, P = 0.819) by Kruskal-Wallis test. The effective reproduction number (Reff) was 1.43, which revealed that the transmissibility of SARS-CoV-2 was moderate. If the interventions had not been strengthened, the duration of the outbreak would have lasted about 16 months with a simulated attack rate of 44.15%. The total attack rate (TAR) and duration of the outbreak would increase along with the increasing delay of intervention. SARS-CoV-2 had moderate transmissibility in Ningbo City, China. The proportion of asymptomatic infections had an increase trend. Asymptomatic infections had the same transmissibility as symptomatic infections. The integrated interventions were implemented at different stages during the outbreak, which turned out to be exceedingly effective in China.

Effectiveness of potential antiviral treatments in COVID-19 transmission control: a modelling study

BACKGROUND

Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy.

METHODS

We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f).

RESULTS

Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%).

CONCLUSIONS

Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.

Early warning of hand, foot, and mouth disease transmission: A modeling study in mainland, China

BACKGROUND

Hand, foot, and mouth disease (HFMD) is a global infectious disease; particularly, it has a high disease burden in China. This study was aimed to explore the temporal and spatial distribution of the disease by analyzing its epidemiological characteristics, and to calculate the early warning signals of HFMD by using a logistic differential equation (LDE) model.

METHODS

This study included datasets of HFMD cases reported in seven regions in Mainland China. The early warning time (week) was calculated using the LDE model with the key parameters estimated by fitting with the data. Two key time points, "epidemic acceleration week (EAW)" and "recommended warning week (RWW)", were calculated to show the early warning time.

RESULTS

The mean annual incidence of HFMD cases per 100,000 per year was 218, 360, 223, 124, and 359 in Hunan Province, Shenzhen City, Xiamen City, Chuxiong Prefecture, Yunxiao County across the southern regions, respectively and 60 and 34 in Jilin Province and Longde County across the northern regions, respectively. The LDE model fitted well with the reported data (R2 > 0.65, P < 0.001). Distinct temporal patterns were found across geographical regions: two early warning signals emerged in spring and autumn every year across southern regions while one early warning signals in summer every year across northern regions.

CONCLUSIONS

The disease burden of HFMD in China is still high, with more cases occurring in the southern regions. The early warning of HFMD across the seven regions is heterogeneous. In the northern regions, it has a high incidence during summer and peaks in June every year; in the southern regions, it has two waves every year with the first wave during spring spreading faster than the second wave during autumn. Our findings can help predict and prepare for active periods of HFMD.

Meteorological Factors and the Transmissibility of Hand, Foot, and Mouth Disease in Xiamen City, China

Background: As an emerging infectious disease, the prevention and control of hand, foot, and mouth disease (HFMD) poses a significant challenge to the development of public health in China. In this study, we aimed to explore the mechanism of the seasonal transmission characteristics of HFMD and to reveal the correlation and potential path between key meteorological factors and the transmissibility of HFMD. Methods: Combined with daily meteorological data such as average temperature, average relative humidity, average wind velocity, amount of precipitation, average air pressure, evaporation capacity, and sunshine duration, a database of HFMD incidence and meteorological factors was established. Spearman rank correlation was used to calculate the correlation between the various meteorological factors and the incidence of HFMD. The effective reproduction number (R eff ) of HFMD was used as an intermediate variable to further quantify the dynamic relationship between the average temperature and R eff . Results: A total of 43,659 cases of HFMD were reported in Xiamen from 2014 to 2018. There was a significantly positive correlation between the average temperature and the incidence of HFMD (r = 0.596, p < 0.001), and a significantly negative correlation between the average air pressure and the incidence of HFMD (r = -0.511, p < 0.001). There was no correlation between the average wind velocity (r = 0.045, p > 0.05) or amount of precipitation (r = 0.043, p > 0.05) and incidence. There was a temperature threshold for HFMD's transmissibility. Owing to the seasonal transmission characteristics of HFMD in Xiamen, the temperature threshold of HFMD's transmissibility was 13.4-18.4°C and 14.5-29.3°C in spring and summer and in autumn and winter, respectively. Conclusions: HFMD's transmissibility may be affected by the average temperature; the temperature threshold range of transmissibility in autumn and winter is slightly wider than that in spring and summer. Based on our findings, we suggest that the relevant epidemic prevention departments should pay close attention to temperature changes in Xiamen to formulate timely prevention strategies before the arrival of the high-risk period.

Dengue fever transmission between a construction site and its surrounding communities in China

BACKGROUND

Due to an increase in mosquito habitats and the lack facilities to carry out basic mosquito control, construction sites in China are more likely to experience secondary dengue fever infection after importation of an initial infection, which may then increase the number of infections in the neighboring communities and the chance of community transmission. The aim of this study was to investigate how to effectively reduce the transmission of dengue fever at construction sites and the neighboring communities.

METHODS

The Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model of human and SEI model of mosquitoes were developed to estimate the transmission of dengue virus between humans and mosquitoes within the construction site and within a neighboring community, as well between each of these. With the calibrated model, we further estimated the effectiveness of different intervention scenarios targeting at reducing the transmissibility at different locations (i.e. construction sites and community) with the total attack rate (TAR) and the duration of the outbreak (DO).

RESULTS

A total of 102 construction site-related and 131 community-related cases of dengue fever were reported in our area of study. Without intervention, the number of cases related to the construction site and the community rose to 156 (TAR: 31.25%) and 10,796 (TAR: 21.59%), respectively. When the transmission route from mosquitoes to humans in the community was cut off, the number of community cases decreased to a minimum of 33 compared with other simulated scenarios (TAR: 0.068%, DO: 60 days). If the transmission route from infectious mosquitoes in the community and that from the construction site to susceptible people on the site were cut off at the same time, the number of cases on the construction site dropped to a minimum of 74 (TAR: 14.88%, DO: 66 days).

CONCLUSIONS

To control the outbreak of dengue fever effectively on both the construction site and in the community, interventions needed to be made both within the community and from the community to the construction site. If interventions only took place within the construction site, the number of cases on the construction site would not be reduced. Also, interventions implemented only within the construction site or between the construction site and the community would not lead to a reduction in the number of cases in the community.

Epidemiology of tsutsugamushi disease and its relationship with meteorological factors in Xiamen city, China

Tsutsugamushi disease (TD) is an acute infectious disease caused by Orientia tsutsugamushi. This study aimed to analyze the epidemiological features of TD, investigate chigger mites and their hosts, and investigate the meteorological factors affecting TD incidence and the host of O. tsutsugamushi in Xiamen city, China. Data on reported TD cases were collected from 2006 to 2018. Spearman’s correlation test were used for identifying the relationship between meteorological factors and TD incidence and whether meteorological factors affect the host of O. tsutsugamushi. The incidence of reported TD increased gradually from 2006, reached a peak of 4.59 per 100,000 persons in 2014, and then decreased gradually. The TD incidence was seasonal, with epidemic periods occurred mainly in summer and autumn. Patients aged 40–60 years had the highest proportion of cases, accounting for 44.44% of the total cases. Farmers had the largest number of cases among all occupational groups. Rattus Norvegicus was the most common host, accounting for the largest proportion of rats (73.00%), and the highest rat density was observed in March and October every year. There were significant positive correlations between the number of reported cases and average temperature, sunshine duration, and rainfall as well as between rat density and average temperature. On phylogenetic analysis, 7 sequences of hosts and human TD cases obtained from health records demonstrated the highest similarities to the Kato, Karp, and Gilliam strains. No correlations were observed between rat density, and sunshine duration and rainfall. The transmission of TD in Xiamen city, China, was seasonal, and its incidence was affected by several meteorological factors including average temperature, sunshine duration, and rainfall. However, the host of O. tsutsugamushi was only affected by average temperature.

Tsutsugamushi disease (TD) is a natural focal disease caused by Orientia tsutsugamushi, which is widespread in some areas. The incidence of TD is greatly influenced by meteorological factors. Therefore, it is essential to analyze the epidemiological features of TD, investigate chigger mites and their hosts, and explore the relationship between meteorological factors and TD incidence and whether meteorological factors affect the host of O. tsutsugamushi in Xiamen city, China. The results showed significant positive correlations between the number of reported cases and average temperature, sunshine duration, and rainfall. A positive correlation between rat density and average temperature. No correlations were observed between the rat density and sunshine duration and rainfall. We believe our findings may provide scientific basis for studies or health strategies conducted in areas that are meteorologically similar in characteristics with Xiamen city, China.

Transmission of SARS-CoV-2 in Public Transportation Vehicles: A Case Study in Hunan Province, China

Here we report a case study of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak event during bus trips of an index patient in Hunan Province, China. This retrospective investigation suggests potential airborne transmission of SARS-CoV-2 and the possibility of superspreading events in certain close contact and closed space settings, which should be taken into account when control strategies are planned.

Protective equipment and health education program could benefit students from dust pollution

In recent years, children living in the downstream of the Choshui River in Taiwan have been exposed to violent dust episodes. For the sake of the health of these children, we aimed to investigate the effectiveness of protective equipment (sand-proof plastic cover and air purifier) installed outside/inside the classrooms on students' pulmonary function and evaluate the health education program for preventing the adverse consequences of exposure to river-dust episodes. Public elementary school students in Yunlin County, which was severely affected by river-dust, were selected as the participants. Study 1 consisted of three-wave follow-up data (801 person-times) in high-/low-dust exposure regions to examine pulmonary function. Study 2 used 147 and 73 students in the high-/low-dust exposure regions, respectively, to establish our health education intervention. Paired t tests, repeated measures ANOVA, and generalized estimating equation were used to analyze the short- and long-term effects. The results showed that the students' pulmonary function in schools that installed protective equipment was improved. The health education (such as the usage of correct masks and our designed PM_2.5 full-cover sand-proof clothing) improved the students' cognition and behaviors related to river-dust episodes and yielded both short- and long-term effects. Therefore, we suggest more schools with high-dust exposure to adopt protective equipment and health education program. Our designed PM_2.5 full-cover sand-proof clothing can prevent from not only haze but also droplet transmission by infectious diseases such as COVID-19.

Feasibility of containing shigellosis in Hubei Province, China: a modelling study

Background

The transmission features and the feasibility of containing shigellosis remain unclear among a population-based study in China.

Methods

A population–based Susceptible – Exposed – Infectious / Asymptomatic – Recovered (SEIAR) model was built including decreasing the infectious period (DIP) or isolation of shigellosis cases. We analyzed the distribution of the reported shigellosis cases in Hubei Province, China from January 2005 to December 2017, and divided the time series into several stages according to the heterogeneity of reported incidence during the period. In each stage, an epidemic season was selected for the modelling and assessing the effectiveness of DIP and case isolation.

Results

A total of 130,770 shigellosis cases were reported in Hubei Province. The median of R_eff was 1.13 (range: 0.86–1.21), 1.10 (range: 0.91–1.13), 1.09 (range: 0.92–1.92), and 1.03 (range: 0.94–1.22) in 2005–2006 season, 2010–2011 season, 2013–2014 season, and 2016–2017 season, respectively. The reported incidence decreased significantly (trend χ² = 8260.41, P <  0.001) among four stages. The incidence of shigellosis decreased sharply when DIP implemented in three scenarios (γ = 0.1, 0.1429, 0.3333) and when proportion of case isolation increased.

Conclusions

Year heterogeneity of reported shigellosis incidence exists in Hubei Province. It is feasible to contain the transmission by implementing DIP and case isolation.

A five-compartment model of age-specific transmissibility of SARS-CoV-2

BACKGROUND

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model.

METHODS

An epidemiological model with five compartments (susceptible-exposed-symptomatic-asymptomatic-recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model.

RESULTS

The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: β43 = 7.71 × 10- 9; SAR43 = 3.86 × 10- 8), followed by group 3 to 4 (median: β34 = 3.07 × 10- 9; SAR34 = 1.53 × 10- 8), group 2 to 2 (median: β22 = 1.24 × 10- 9; SAR22 = 6.21 × 10- 9), and group 3 to 1 (median: β31 = 4.10 × 10- 10; SAR31 = 2.08 × 10- 9). The lowest transmissibility was from age group 3 to 3 (median: β33 = 1.64 × 10- 19; SAR33 = 8.19 × 10- 19), followed by group 4 to 4 (median: β44 = 3.66 × 10- 17; SAR44 = 1.83 × 10- 16), group 3 to 2 (median: β32 = 1.21 × 10- 16; SAR32 = 6.06 × 10- 16), and group 1 to 4 (median: β14 = 7.20 × 10- 14; SAR14 = 3.60 × 10- 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: β43 = 4.27 × 10- 8; SAR43 = 2.13 × 10- 7), followed by group 3 to 4 (median: β34 = 1.81 × 10- 8; SAR34 = 9.03 × 10- 8).

CONCLUSIONS

SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.

Effectiveness of Interventions to Control Transmission of Reemergent Cases of COVID-19 - Jilin Province, China, 2020

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?

COVID-19 has a high transmissibility calculated by mathematical model. The dynamics of the disease and the effectiveness of intervention to control the transmission remain unclear in Jilin Province, China.

WHAT IS ADDED BY THIS REPORT?

This is the first study to report the dynamic characteristics and to quantify the effectiveness of interventions implemented in the second outbreak of COVID-19 in Jilin Province, China. The effective reproduction number of the disease before and after May 10 was 4.00 and p<0.01, respectively. The combined interventions reduced the transmissibility of COVID-19 by 99% and the number of cases by 98.36%.

WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?

The findings of this study would add data on the transmission of COVID-19 and provide evidence to prepare the second outbreak transmission of the disease in other areas of China even in many other countries.

Adjuvant chemoradiotherapy vs. radiotherapy alone in early-stage high-risk endometrial cancer: a systematic review and meta-analysis

OBJECTIVE

The benefits of adjuvant chemoradiotherapy (CRT) in patients with International Federation of Gynecology and Obstetrics (FIGO) stages I-II high-risk endometrial cancer remain controversial. We undertook a systematic review and meta-analysis to assess the efficacy of CRT over radiotherapy (RT) in patients with early-stage high-risk endometrial cancer.

PATIENTS AND METHODS

We searched MEDLINE (from 1946 to May 2018), EMBASE (from 1966 to May 2018), and the Cochrane Library database for randomized controlled trials (RCTs) conducted for endometrial cancer comparing CRT to RT alone. The outcomes were overall survival (OS), failure-free survival (FFS), local recurrence rates (LRR) and the distant metastasis rate (DMR).

RESULTS

Three eligible studies with 1120 participants were included in the meta-analysis. All studies were published from 1990 to 2018. The OS rates were 82.5% for the patients in the CRT group and 84.4% for patients in the RT group. The included three RCTs showed no significant difference of OS between the CRT and RT groups (odd ratio 0.98, 95% CI 0.93 to 1.02, p=0.35) with no heterogeneity (I2=0%, p=0.47). Two studies reported 382 FFS events in 469 patients with CRT treatment (81.4%) and 376 events of the 470 patients with RT treatment (80.0%). Overall, CRT group didn't provide any benefit over RT alone (1.02, 0.95 to 1.08, p=0.62; I2 = 0%, p=0.55) in FFS. 39 patients in CRT group (10.2%) vs. 16 patients in RT group (4.3%) were diagnosed with local recurrence. LRR was significantly more common in patients receiving adjuvant chemoradiotherapy compared with adjuvant radiotherapy (2.29, 1.31 to 3.98, p=0.004; I²=0%, p=0.33). The distant metastasis occurred in 20 patients (5.2%) treated with CRT and 26 patients (7.0%) treated with RT. The effect of reducing DMR was equivocal between the CRT group and the RT group, with an OR of 0.74 (0.43-1.27, p=0.28; I²=0%, p=0.87).

CONCLUSIONS

This study demonstrates that adjuvant chemoradiotherapy has no advantage over radiotherapy alone for overall survival and failure-free survival in high-risk patients with FIGO stages I-II endometrial cancer. In addition, CRT is associated with a high risk of local recurrences.