Transmissibility of the variant of concern for SARS-CoV-2 in six regions.

Introduction: Differences in transmissibility of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) in different districts are hard to assess. To address this, our study focused on calculating the Real-time reproduction number (R t ) for these variants in different regions. Methods: According to the criteria defined by the World Health Organization (WHO), the global landscape was categorized into six distinct regions. In each region, the predominant SARS-CoV-2 variant was first identified based on the proportion of variant sequencing analysis results. Then, using serial interval (SI) parameters, we calculated R t for the relevant Variant of Concern (VOC) in each region. This approach enabled us to compare the R t values of the same variant across different regions and analyze the transmissibility of each region's variant in relation to the overall situation in that region. Results: The progression of VOC for SARS-CoV-2 shows regional variations. However, a common sequence of evolution is observed: Wild-type → Alpha → Beta → Delta → Omicron. Moreover, an increasing trend is discerned within diverse regions where the shift in R t of distinct VOC corresponds with the overarching R t route of SARS-CoV-2 in specific regions. Conclusion: As the COVID-19 pandemic advances, regional epidemiological trends are aligning, likely due to similar virus mutations and shared public health strategies, suggesting opportunities for standardized global responses.

Theoretical Epidemiology Needs Urgent Attention in China.

The mathematical method to which theoretical epidemiology belongs is one of the three major methodologies in epidemiology. It is of great value in diagnosing infectious disease epidemic trends and evaluating the effectiveness of prevention and control measures. This paper aims to summarize the brief history of the development of theoretical epidemiology, common types of mathematical models, and key steps to develop a mathematical model. It also provides some thoughts and perspectives on the development and application of theoretical epidemiology in China.

An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere.

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

Relationship of various COVID-19 antibody titer with individual characteristics and prediction of future epidemic trend in Xiamen City, China.

Background: Reinfection of coronavirus disease 2019 (COVID-19) has raised concerns about how reliable immunity from infection and vaccination is. With mass testing for the virus halted, understanding the current prevalence of COVID-19 is crucial. This study investigated 1,191 public health workers at the Xiamen Center for Disease Control, focusing on changes in antibody titers and their relationship with individual characteristics. Methods: The study began by describing the epidemiological characteristics of the study participants. Multilinear regression (MLR) models were employed to explore the associations between individual attributes and antibody titers. Additionally, group-based trajectory models (GBTMs) were utilized to identify trajectories in antibody titer changes. To predict and simulate future epidemic trends and examine the correlation of antibody decay with epidemics, a high-dimensional transmission dynamics model was constructed. Results: Analysis of epidemiological characteristics revealed significant differences in vaccination status between infected and non-infected groups (χ2=376.706, P<0.05). However, the distribution of antibody titers among the infected and vaccinated populations was not significantly different. The MLR model identified age as a common factor affecting titers of immunoglobulin G (IgG), immunoglobulin M (IgM), and neutralizing antibody (NAb), while other factors showed varying impacts. History of pulmonary disease and hospitalization influenced IgG titer, and factors such as gender, smoking, family history of pulmonary diseases, and hospitalization impacted NAb titers. Age was the sole determinant of IgM titers in this study. GBTM analysis indicated a "gradual decline type" trajectory for IgG (95.65%), while IgM and NAb titers remained stable over the study period. The high-dimensional transmission dynamics model predicted and simulated peak epidemic periods in Xiamen City, which correlated with IgG decay. Age-group-specific simulations revealed a higher incidence and infection rate among individuals aged 30-39 years during both the second and third peaks, followed by those aged 40-49, 50-59, 18-29, and 70-79 years. Conclusions: Our study shows that antibody titer could be influenced by age, previous pulmonary diseases as well as smoking. Furthermore, the decline in IgG titers is consistent with epidemic trends. These findings emphasize the need for further exploration of these factors and the development of optimized self-protection countermeasures against reinfection.

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.

Tuberculosis Prevalence Trends from a Predictive Modelling Study - 10 High-Burden Countries, 1980-2035.

What is already known about this topic?: Given the challenges presented by drug-resistant strains of tuberculosis (TB) and the rising mobility of the population, achieving the objective of eradicating TB appears uncertain. What is added by this report?: The examination of TB incidence trends in 10 high-burden countries (HBCs) indicated a steady rise in cases, with India and China jointly accounting for nearly 70% of the burden. Projections for the future show diverse trajectories in these countries, with potential difficulties in reaching the TB elimination target, especially in Nigeria, Congo, and South Africa. What are the implications for public health practice?: The number of TB cases is on the rise. It is crucial to learn from successful strategies to improve TB prevention and control worldwide through collaborative efforts.

Trends in Respiratory Infectious Pathogens in Children Under the Age of 14 - Xiamen City, Fujian Province, China, 2017-2023.

What is already known about this topic?: Respiratory infections pose a significant burden on public health. Despite recent outbreaks occurring in various locations, there is limited information available on the prevalence trends of multiple common respiratory pathogens in China beyond 2022. What is added by this report?: A retrospective analysis was conducted on respiratory pathogen infections in a Xiamen hospital over a seven-year period. The analysis revealed fluctuating trends, with the number of infections for certain viruses initially decreasing after 2019, only to rebound to previous or higher levels. Recently, there has been an observed collective increase in positive cases for certain pathogens. What are the implications for public health practice?: The study improves understanding of respiratory pathogens, primarily in Xiamen, with potential implications for the improvement of strategies for the prevention and management of respiratory infectious diseases.

Comparative analysis and prediction of avian influenza in Shangrao city, China from 2016 to 2022.

The aim of this study was to investigate the effects of vaccination, COVID-19 pandemic and migration of migratory birds on the avian influenza positivity rate in Shangrao City and to predict the future avian influenza positivity rate. Real-time reverse transcription polymerase chain reaction (RT-PCR) was used to detect nucleic acids of avian influenza A viruses. 1795 samples were collected between 2016 and 2022, of which 1086 were positive. In addition, there were seven human cases of avian influenza. The results showed that the positivity rate of H9 subtype in Shangrao City was higher than usual during the COVID-19 pandemic and migratory birds. Predictions suggest that the H9 subtype positivity rate in Shangrao City will be on the rise in the future. In recent years, the H5 positivity rate has gradually increased. Migratory birds and the COVID-19 pandemic have led to an increase in H9 subtype positivity. Therefore, the prevention and control of them should be strengthened.

Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China.

Introduction: Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding sites as an effect modifier. Methods: In this study, we addressed this research gap by considering the impact of prior water availability for the first time. We measured prior water availability as the cumulative precipitation over the preceding 8 weeks and utilized a distributed lag non-linear model stratified by the level of prior water availability to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China. Results: Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24-55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 [95% credible interval (CI): 1.02-1.83] occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43-0.79), occurring at a lag of 45 days. Discussion: These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.

Nowcasting and Forecasting Seasonal Influenza Epidemics - China, 2022-2023.

Background: Seasonal influenza resurged in China in February 2023, causing a large number of hospitalizations. While influenza epidemics occurred across China during the coronavirus disease 2019 (COVID-19) pandemic, the relaxation of COVID-19 containment measures in December 2022 may have contributed to the spread of acute respiratory infections in winter 2022/2023. Methods: Using a mathematical model incorporating influenza activity as measured by influenza-like illness (ILI) data for northern and southern regions of China, we reconstructed the seasonal influenza incidence from October 2015 to September 2019 before the COVID-19 pandemic. Using this trained model, we predicted influenza activities in northern and southern China from March to September 2023. Results: We estimated the effective reproduction number R e as 1.08 [95% confidence interval ( CI): 0.51, 1.65] in northern China and 1.10 (95% CI: 0.55, 1.67) in southern China at the start of the 2022-2023 influenza season. We estimated the infection attack rate of this influenza wave as 18.51% (95% CI: 0.00%, 37.78%) in northern China and 28.30% (95% CI: 14.77%, 41.82%) in southern China. Conclusions: The 2023 spring wave of seasonal influenza in China spread until July 2023 and infected a substantial number of people.

Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China.

Background: Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions. Methods: In this study, we use a distributed lag non-linear model to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China, stratified by prior water availability. Results: Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24-55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 (95% credible interval (CI): 1.02-1.83) occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43-0.79), occurring at a lag of 45 days. Conclusions: These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.

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.

Analysis of the effect of PCR testing and antigen testing on controlling the transmission for Omicron based on different scenarios.

After the policy adjustment, China no longer carries out COVID-19 PCR testing for all people, and antigen testing has become the main way to detect and manage infectious sources. We developed a dynamic model to evaluate and compare the effects between PCR and antigen testing for controlling the pandemic. Due to the increase of contact degree, the peak reduction effect of PCR testing in population is lower than that of antigen testing. Even if it was only 20% of people isolated at home after antigen testing, the peak of the epidemic could be reduced by 9.46%. If the proportion of antigen testing is further increased to 80%, the peak of the pandemic can be reduced by 31.41%. Antigen testing performed better effects in school (reduction proportion 29.27%) and community (29.34%) than in workplace (27.75%). Therefore, we recommend that antigen testing in the population should be encouraged during the pandemic, and home isolation of infected persons should be advocated, especially in crowded places. To improve the availability of antigen, the testing proportion should be further enhanced.

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.

Response Strategies for Emerging Infectious Diseases: More Efforts Are Needed.

In recent years, emerging infectious disease outbreaks have placed significant health and socioeconomic burdens upon the population [...].

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.

Trends in disease burden of hepatitis B infection in Jiangsu Province, China, 1990-2021.

Background: The incidence of hepatitis B virus (HBV) has decreased year by year in China after the expansion of vaccination, but there is still a high disease burden in Jiangsu Province of China. Methods: The year-by-year incidence data of HBV in Jiangsu Province from 1990 to 2021 were collected. The incidence rates of males and females age groups were clustered by systematic clustering, and the incidence rates of each age group were analyzed and studied by using Joinpoint regression model and age-period-cohort effect model (APC). Results: Joinpoint regression model and APC model showed a general decrease in HBV prevalence in both males and females. In addition, the results of the APC model showed that the age, period, and cohort effects of patients all affected the incidence of HBV, and the incidence was higher in males than in females. The incidence is highest in the population between the ages of 15 and 30 years (mean: 21.76/100,000), especially in males (mean: 31.53/100,000) than in females (mean:11.67/100,000). Another high-risk group is those over 60 years of age (mean: 21.40/100,000), especially males (mean: 31.17/100,000) than females (mean: 11.63/100,000). The period effect of the APC model suggests that HBV vaccination is effective in reducing the incidence of HBV in the population. Conclusions: The incidence of HBV in Jiangsu Province showed a gradual downward trend, but the disease burden in males was higher than that in females. The incidence is higher and increasing rapidly in the population between the ages of 15 and 30 years and people over 60 years of age. More targeted prevention and control measures should be implemented for males and the elderly.