Transmissibility of acute haemorrhagic conjunctivitis in small-scale outbreaks in Hunan Province, China

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.

Apollo Rising: Acute Conjunctivitis Outbreak in India, 2022

Purpose

To identify pathogens associated with the 2022 conjunctivitis outbreak in Tamil Nadu, India.

Methods

This prospective study was conducted in November of 2022. Patients with presumed acute infectious conjunctivitis presenting to the Aravind Eye Clinic in Madurai, India were eligible. Anterior nares and conjunctival samples from participants were obtained and processed for metagenomic RNA deep sequencing (RNA-seq).

Results

Samples from 29 patients were sequenced. A pathogen was identified in 28/29 (97%) patients. Coxsackievirus A24v, a highly infectious RNA virus, was the predominant pathogen and detected in 23/29 patients. Human adenovirus D (HAdV-D), a DNA virus commonly associated with conjunctivitis outbreaks, was detected in the remaining patients (5/29). Hemorrhagic conjunctiva was documented in both HAdV-D and coxsackievirus A24v affected patients but was not the predominant clinical presentation. Phylogenetic analysis of coxsackievirus A24v revealed a recent divergence from the 2015 outbreak.

Conclusions

Coxsackievirus A24v and HAdV-D were co-circulating during the 2022 conjunctivitis outbreak in Tamil Nadu, India. Clinical findings were similar between patients with HAD-V and coxsackievirus A24v associated conjunctivitis. As high-throughput technologies become more readily accessible and cost-effective, unbiased pathogen surveillance may prove useful for outbreak surveillance and control.

Viral Conjunctivitis

Viruses account for 80% of all cases of acute conjunctivitis and adenovirus; enterovirus and herpes virus are the common causative agents. In general, viral conjunctivitis spreads easily. Therefore, to control the spread, it is crucial to quickly diagnose illnesses, strictly implement hand washing laws, and sanitize surfaces. Swelling of the lid margin and ciliary injection are subjective symptoms, and eye discharge is frequently serofibrinous. Preauricular lymph node swelling can occasionally occur. Approximately 80% of cases of viral conjunctivitis are caused by adenoviruses. Adenoviral conjunctivitis may become a big global concern and may cause a pandemic. Diagnosis of herpes simplex viral conjunctivitis is crucial for using corticosteroid eye solution as a treatment for adenovirus conjunctivitis. Although specific treatments are not always accessible, early diagnosis of viral conjunctivitis may help to alleviate short-term symptoms and avoid long-term consequences.

Oscillatory properties of class C notifiable infectious diseases in China from 2009 to 2021

Background

Epidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government.

Method

In this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis.

Results

We found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009-2015) and the next 6 years (2015-2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter.

Conclusion

Our results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.

Shigellosis seasonality and transmission characteristics in different areas of China: A modelling study

Objective

In China, the burden of shigellosis is unevenly distributed, notably across various ages and geographical areas. Shigellosis temporal trends appear to be seasonal. We should clarify seasonal warnings and regional transmission patterns.

Method

This study adopted a Logistic model to assess the seasonality and a dynamics model to compare the transmission in different areas. The next-generation matrix was used to calculate the effective reproduction number (R eff) to quantify the transmissibility.

Results

In China, the rate of shigellosis fell from 35.12 cases per 100,000 people in 2005 to 7.85 cases per 100,000 people in 2017, peaking in June and August. After simulation by the Logistic model, the 'peak time' is mainly concentrated from mid-June to mid-July. China's 'early warning time' is primarily focused on from April to May. We predict the 'peak time' of shigellosis is the 6.30th month and the 'early warning time' is 3.87th month in 2021. According to the dynamics model results, the water/food transfer pathway has been mostly blocked off. The transmissibility of different regions varies greatly, such as the mean R eff of Longde County (3.76) is higher than Xiamen City (3.15), higher than Chuxiong City (2.52), and higher than Yichang City (1.70).

Conclusion

The 'early warning time' for shigellosis in China is from April to May every year, and it may continue to advance in the future, such as the early warning time in 2021 is in mid-March. Furthermore, we should focus on preventing and controlling the person-to-person route of shigellosis and stratified deploy prevention and control measures according to the regional transmission.

Epidemiological Investigation and Risk Factor Analysis of Acute Hemorrhagic Conjunctivitis in Huangshi Port District, Huangshi City

Objective

This study is aimed at investigating the epidemiology and risk factors of acute hemorrhagic conjunctivitis (pinkeye) in Huangshi Port District of Huangshi City.

Methods

A total of 593 cases of acute hemorrhagic conjunctivitis from January 2019 to December 2021 were selected as the observation group. The epidemiological characteristics (age of onset, season, occupation, clinical manifestations, and etiological characteristics) were analyzed. A total of 425 healthy subjects (nonacute hemorrhagic conjunctivitis) were selected as the control group. The general data of the two groups were compared, and the risk factors affecting the occurrence of acute hemorrhagic conjunctivitis were analyzed by logistic regression.

Results

The onset age of acute hemorrhagic conjunctivitis was mainly concentrated in 0-20-year-old and 60-year-old age groups, and the onset season was mainly concentrated in April to August, with the highest incidence in May. The proportions of middle school students and workers in patients with acute hemorrhagic conjunctivitis were higher than those of other occupations (both P < 0.05). Ocular conjunctival congestion, tingling, and foreign body sensation were the main clinical manifestations of patients with acute hemorrhagic conjunctivitis. Among the 593 conjunctival swab samples collected in this study, the positive rates of HEV70 and CVA24v were higher than those of adenovirus nucleic acid (both P < 0.05). The proportion of people aged ≤40 years old, male, working outdoors, using potable water equipment, contact history of patients with acute conjunctivitis, history of chemical substances entering eyes, combined with immune system diseases, and public toilet utilization rate ≥ 1 times/d in the observation group was higher than that in the control group (all P < 0.05), and the proportion of people washing hands before eating and after toilet was lower than that in the control group (P < 0.05). Multiple logistic regression analysis showed that working place outdoors, use of potable water equipment, contact history of patients with acute conjunctivitis (all P < 0.05), and use of public toilets ≥ once a day were risk factors for the occurrence of acute hemorrhagic conjunctivitis, and washing hands before eating and after toilet was a protective factor (P < 0.05).

Conclusion

The onset age of acute hemorrhagic conjunctivitis was mainly concentrated in 0-20-year-old and 60-year-old age; the onset season was mainly concentrated in summer and autumn; adenovirus is the main pathogenic bacteria; ocular conjunctivitis congestion, tingling, and foreign body sensation were the main clinical manifestations; working place outdoors, use of potable water equipment, contact history of patients with acute conjunctivitis (all P < 0.05), and use of public toilets ≥ once a day were risk factors for the occurrence of acute hemorrhagic conjunctivitis, while washing hands before eating and after toilet was a protective factor.

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.

Epidemiological trends and sociodemographic factors associated with acute hemorrhagic conjunctivitis in mainland China from 2004 to 2018

BACKGROUND

Acute hemorrhagic conjunctivitis (AHC) is classified as a class C notifiable infectious disease in China and poses a great threat to public health. This study aimed to investigate the epidemiological trends and hotspots of AHC in mainland China. Sociodemographic factors that could contribute to early warning of AHC were further explored.

METHODS

Yearly and monthly incidences of acute hemorrhagic conjunctivitis by date and region from 2004 to 2018 were extracted from the Data Center of China Public Health Science. Joinpoint regression and spatial autocorrelation analysis were performed to explore the epidemiological trends and hotspots of AHC. A generalized linear model was then applied to explore the relationship between sociodemographic factors and AHC incidence.

RESULTS

The average annual AHC incidence was 3.58/100,000 in mainland China. The first-level spatial and temporal aggregation areas were distributed in Guangxi, Hainan, Guangdong, Guizhou, Hunan, Jiangxi, Fujian, Chongqing, Hubei, Anhui, and Zhejiang, with gathering times from 2010/1/1 to 2010/12/31 (RR = 20.13, LLR = 474,522.89, P < 0.01). After 2010, the AHC incidence was stable (APC = - 8.37, 95% CI: - 23.02-9.06). However, it was significantly increased in low- and middle-income provinces (AAPC = 10.65, 95% CI: 0.62-21.68, AAPC = 11.94, 95% CI: 0.62-24.53). The peak of AHC occurred during the August to October period. Children who age 0-3 years are identified as high-risk group with AHC incidence significantly increased (APC = 31.54, 95% CI: 0.27-72.56). Birth rate, population ages 0-14 (% of total population), passenger traffic, and urban population (% of total population) were positively associated with the AHC incidence, while per capita gross domestic product was negatively associated with the AHC incidence.

CONCLUSION

Overall, the AHC incidence was stable after 2010 in China, but it was significantly increased in low- and middle-income provinces. Regions with a high birth rate, population ages 0-14 (% of the total population), passenger traffic, urban population (% of the total population) and low per capita gross domestic product are at high risk of incidences of AHC. In the future, public health policy and resource priority for AHC in regions with these characteristics are necessary.

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 (Reff ) 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 (Reff = 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.

Long-term effects of weather condition and air pollution on acute hemorrhagic conjunctivitis in China: A nationalwide surveillance study in China

BACKGROUND

Global climate change could have potential impact on enterovirus (EV)-induced infectious diseases. However, the environmental factors promoting acute hemorrhagic conjunctivitis (AHC) circulation remain inconclusive. This study aimed to quantify the relationship between the environment and AHC.

METHODS

We retrieved the monthly counts and incidence of AHC, meteorological variables and air quality in mainland China between 2013 and 2018. Exposure risks were evaluated by multivariate distributed lag nonlinear models.

RESULTS

A total of 219,599 AHC cases were reported in 31 provinces of China, predominantly in southern and central China, seasonally increased in summer. AHC incidence increased by 7% between 2013 and 2018, from 2.6873 to 2.7570 per 100,000 people. A moderate positive correlation was seen between AHC and monthly mean temperature, relative humidity (RH) and precipitation. Each unit increment was associated with a relative risk for AHC of 1.058 at 17°-32 °C at lag 0 months, 1.017 at 65-71% RH at lag 1.4 months, and 1.039 at 400-569 mm at lag 2.4 months. By contrast, a negative correlation was seen between monthly ambient NO₂ and AHC.

CONCLUSION

Long-term exposure to higher mean temperature, RH and precipitation were associated with an increased risk of AHC. The general public, especially susceptible populations, should pay close attention to weather changes and take protective measures in advance to any AHC outbreak as the above situations occur.

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.

Using caputo-fabrizio derivative for the transmission of mathematical model epidemic Corona Virus

Just in a week a rapidly spreading corona virus which was originated in Wuhan, city of China, infected more than 20,000 people and also killed at least 427 people in that week worldwide. Corona virus is transmissible and spreading from person to person, while the Chinese commanded authorities are scrambling to treat a flood of new patients in Chines successfully. The said Corona virus has been spread from an initial outbreak in Wuhan, city of China, and invade 25 other worldwide countries. In this article, we considered the mathematical model (Chen et al. Infect Dis Poverty, https://doi.org/10.1186/s40249-020-00640-3) in which Bats-Hosts-Reservoir-People and their transmission was taken, while we introduced the population of susceptible Bats and visitors to Wuhan city or any country in same mathematical model. Now we studying two types of populations first Bats-Hosts-Reservoir-People (Chen et al. Infect Dis Poverty, https://doi.org/10.1186/s40249-020-00640-3, also introducing susceptible Bats and second visitors to Wuhan city, china or any country in the same model. We used Caputo-Fabrizio derivative with provided result that the addition of susceptible Bats and visitors are not responsible in spread of infection. The numerical result also supported our model.

Methylene Blue Inhibits Acute Hemorrhagic Conjunctivitis Virus Production and Induction of Caspase-3 Mediated Human Corneal Cell Cytopathy

Background

Acute hemorrhagic conjunctivitis (AHC) is a highly contagious eye disease caused by enterovirus type 70 (E70) and Coxsackievirus A24 variant (CA24v) with no clinically approved treatment. The antiviral activity of methylene blue (MB; a WHO essential medicine) against AHC viruses was investigated using human corneal epithelial cells (HCEC).

Methods

Time and concentration-dependent MB accumulation by HCEC was determined colorimetrically and MB inhibition of virus production of 5 E70 and 3 CA24v AHC epidemic isolates in HCEC was determined by micro-plaque assay. AHC virus cytopathy inhibition by MB was detected by reductions in virus-induced caspase-3 activity and polymeric DNA fragments.

Results

MB uptake by HCEC was rapid and concentration dependent. MB inhibition of E70 and CA24v production was concentration dependent. AHC virus yields were significantly lower (50 to >10,000 fold) in HCEC pre-treated with 0.25–1% MB than in placebo controls (p’s ≤ 0.01). MB pre-treatment significantly inhibited virus-induced caspase-3 activation and DNA fragmentation (p’s<0.01). Virus-infected cells accumulate oxidized MB and MB application up to 6 h after infection inhibited virus production and virus-induced HCEC cytopathy.

Conclusion

The results suggest MB treatment prior to and shortly after infection can inhibit AHC virus production and caspase-mediated HCEC cytopathy. The results support the therapeutic potential of ophthalmic solutions containing MB against AHC virus infection during epidemics.

The transmissibility of hepatitis C virus: a modelling study in Xiamen City, China

This study aimed at estimating the transmissibility of hepatitis C. The data for hepatitis C cases were collected in six districts in Xiamen City, China from 2004 to 2018. A population-mixed susceptible-infectious-chronic-recovered (SICR) model was used to fit the data and the parameters of the model were calculated. The basic reproduction number (R0) and the number of newly transmitted cases by a primary case per month (MNI) were adopted to quantitatively assess the transmissibility of hepatitis C virus (HCV). Eleven curve estimation models were employed to predict the trends of R0 and MNI in the city. The SICR model fits the reported HCV data well (P < 0.01). The median R0 of each district in Xiamen is 0.4059. R0 follows the cubic model curve, the compound curve and the power function curve. The median MNI of each district in Xiamen is 0.0020. MNI follows the cubic model curve, the compound curve and the power function curve. The transmissibility of HCV follows a decreasing trend, which reveals that under the current policy for prevention and control, there would be a high feasibility to eliminate the transmission of HCV in the city.

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.

Relative transmissibility of shigellosis among male and female individuals: a modeling study in Hubei Province, China

BACKGROUND

Developing countries exhibit a high disease burden from shigellosis. Owing to the different incidences in males and females, this study aims to analyze the features involved in the transmission of shigellosis among male (subscript m) and female (subscript f) individuals using a newly developed sex-based model.

METHODS

The data of reported shigellosis cases were collected from the China Information System for Disease Control and Prevention in Hubei Province from 2005 to 2017. A sex-based Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model was applied to explore the dataset, and a sex-age-based SEIAR model was applied in 2010 to explore the sex- and age-specific transmissions.

RESULTS

From 2005 to 2017, 130 770 shigellosis cases (including 73 981 male and 56 789 female cases) were reported in Hubei Province. The SEIAR model exhibited a significant fitting effect with the shigellosis data (P <  0.001). The median values of the shigellosis transmission were 2.3225 × 10⁸ for SAR_mm (secondary attack rate from male to male), 2.5729 × 10⁸ for SAR_mf, 2.7630 × 10^-8 for SAR_fm, and 2.1061 × 10^-8 for SAR_ff. The top five mean values of the transmission relative rate in 2010 (where the subscript 1 was defined as male and age ≤ 5 years, 2 was male and age 6 to 59 years, 3 was male and age ≥ 60 years, 4 was female and age ≤ 5 years, 5 was female and age 6 to 59 years, and 6 was male and age ≥ 60 years) were 5.76 × 10^-8 for β₆₁, 5.32 × 10^-8 for β₃₁, 4.01 × 10^-8 for β₃₄, 7.52 × 10^-9 for β₆₂, and 6.04 × 10^-9 for β₆₄.

CONCLUSIONS

The transmissibility of shigellosis differed among male and female individuals. The transmissibility between the genders was higher than that within the genders, particularly female-to-male transmission. The most important route in children (age ≤ 5 years) was transmission from the elderly (age ≥ 60 years). Therefore, the greatest interventions should be applied in females and the elderly.

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

BACKGROUND

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus.

METHODS

In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R0) from the RP model to assess the transmissibility of the SARS-CoV-2.

RESULTS

The value of R0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58.

CONCLUSIONS

Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

BACKGROUND

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus.

METHODS

In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R₀) from the RP model to assess the transmissibility of the SARS-CoV-2.

RESULTS

The value of R₀ was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58.

CONCLUSIONS

Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.