Preparation of highly efficient antibacterial non-woven by facile plasma-induced graft polymerizing of DADMAC

The development of surface modification technology for temperature sensitive fibers has been a huge challenge.In this work,a novel technique based on cold plasma treatment was developed for the preparation of anti-bacterial polypropylene(PP)fibers.The results showed that plasma treatment introduced a rough surface and polar groups,which acted as the anchor point and initiators for diallyldimethyl ammonium chloride(DADMAC)graft-polymerization.The fabricated PP membranes presented a high bacterial sterilization rate,as well as excellent adhesion force and washing durability.After ultrasonic treatment for 30 min,the physical coating sample had lost anti-bacterial effect,while the plasma grafted sample still showed a sterilization rate of 91.67%.This work provided a clean and novel DADMAC grafting method and it is also applicable for anti-bacterial material fabrication.

Simulating potential outbreaks of Delta and Omicron variants based on contact-tracing data:A modelling study in Fujian Province,China

Although studies have compared the relative severity of Omicron and Delta variants by assessing the relative risks,there are still gaps in the knowledge of the potential COVID-19 burden these variations may cause.And the contact patterns in Fujian Province,China,have not been described.We identified 8969 transmission pairs in Fujian,China,by analyzing a contact-tracing database that recorded a SARS-CoV-2 outbreak in September 2021.We estimated the waning vaccine effectiveness against Delta variant infection,contact patterns,and epidemiology distributions,then simulated potential outbreaks of Delta and Omicron variants using a multi-group mathematical model.For instance,in the contact setting without stringent lockdowns,we estimated that in a potential Omicron wave,only 4.7%of infections would occur in Fujian Province among individuals aged>60 years.In comparison,58.75%of the death toll would occur in unvaccinated individuals aged>60 years.Compared with no strict lockdowns,combining school or factory closure alone reduced cumulative deaths of Delta and Omicron by 28.5%and 6.1%,respectively.In conclusion,this study validates the need for continuous mass immunization,especially among elderly aged over 60 years old.And it confirms that the effect of lockdowns alone in reducing infections or deaths is minimal.However,these measurements will still contribute to lowering peak daily incidence and delaying the epidemic,easing the healthcare system's burden.

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 susceptibleexposed-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.

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(Reff)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 Reff 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 personto-person route of shigellosis and stratified deploy prevention and control measures according to the regional transmission.

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(Reff)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 Reff=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.

Computing R_(0) of dynamic models by a definition-based method

Objectives:Computing the basic reproduction number(R0)in deterministic dynamical models is a hot topic and is frequently demanded by researchers in public health.The nextgeneration methods(NGM)are widely used for such computation,however,the results of NGM are usually not to be the true R0 but only a threshold quantity with little interpretation.In this paper,a definition-based method(DBM)is proposed to solve such a problem.Methods:Start with the definition of R0,consider different states that one infected individual may develop into,and take expectations.A comparison with NGM has proceeded.Numerical verification is performed using parameters fitted by data of COVID-19 in Hunan Province.Results:DBM and NGM give identical expressions for single-host models with single-group and interactive Rij of single-host models with multi-groups,while difference arises for models partitioned into subgroups.Numerical verification showed the consistencies and differences between DBM and NGM,which supports the conclusion that R0 derived by DBM with true epidemiological interpretations are better.Conclusions:DBM is more suitable for single-host models,especially for models partitioned into subgroups.However,for multi-host dynamic models where the true R0 is failed to define,we may turn to the NGM for the threshold R0.