Background At the end of 2022,China adjusted its coronavirus disease 2019(COVID-19)prevention and control strategy.How this adjustment affected the cumulative infection rate is debated,and how second booster dose vacc...Background At the end of 2022,China adjusted its coronavirus disease 2019(COVID-19)prevention and control strategy.How this adjustment affected the cumulative infection rate is debated,and how second booster dose vaccination affected the pandemic remains unclear.Methods We collected COVID-19 case data for China's mainland from December 7,2022,to January 7,2023,reported by the World Health Organization.We also collected cumulative infection rate data from five large-scale population-based surveys.Next,we developed a dynamic transmission compartment model to characterize the COVID-19 pandemic and to estimate the cumulative infection rate.In addition,we estimated the impact of second booster vaccination on the pandemic by examining nine scenarios with different vaccination coverages(0%,20%,and 40%)and vaccine effectiveness(30%,50%,and 70%).Results By January 7,2023,when COVID-19 was classified as a Class B infectious disease,the cumulative infection rate of the Omicron variant nationwide had reached 84.11%(95%confidence interval[CI]:78.13%–90.08%).We estimated that the cumulative infection rates reached 50.50%(95%CI:39.58%–61.43%),56.15%(95%CI:49.05%–67.22%),73.82%(95%CI:64.63%–83.02%),75.76%(95%CI:67.02%–84.50%),and 84.99%(95%CI:79.45%–90.53%)on December 19,20,25,and 26,2022,and on January 15,2023,respectively.These results are similar to those of the population survey conducted on the corresponding dates,that is 46.93%,61%,63.52%,74%,and 84.7%,respectively.In addition,we estimated that by January 7,2023,the cumulative infection rate decreased to 29.55%(64.25%)if vaccination coverage and the effectiveness of second booster vaccination were 40%(20%)and 70%(30%),respectively.Conclusion We estimate that,in late 2022,the cumulative infection rate was approximately 84%and that second booster vaccination before the policy adjustment was effective in reducing this rate.展开更多
Background The World Health Organization(WHO)targets a 65%reduction in hepatitis B-related deaths by 2030 compared to 2015 to eliminate viral hepatitis as a major public health threat.It is unknown whether and how Chi...Background The World Health Organization(WHO)targets a 65%reduction in hepatitis B-related deaths by 2030 compared to 2015 to eliminate viral hepatitis as a major public health threat.It is unknown whether and how China can achieve this target despite significant intervention achievements.We aimed to predict the hepatitis B-related deaths in China and identify key developments needed to achieve the target.Methods An age-and time-dependent dynamic hepatitis B virus(HBV)transmission compartmental model was developed to predict the trend of hepatitis B-related deaths under base-case and subsequent scenarios from 2015 to 2040.In base-case scenario,we assumed the diagnosis and treatment(D&T)rate would reach 72%in 2030,as proposed by WHO.Subsequent scenarios were set based on the results of base-case and one-way sensitivity analysis.Results Compared with 2015,hepatitis B-related deaths would be reduced by 23.89%in 2030 and 51.79%in 2040,respectively,and the WHO's impact target of 65%reduction would not be achieved until 2038 at the earliest under base-case scenario.HBV clearance rate and current treatment effectiveness were the most sensitive parameters that significantly influenced the decline of hepatitis B-related deaths from 2015 to 2040.In the subsequent scenario,when D&T rate improving to 90%by 2030,with the current treatment effectiveness and HBV clearance rate being optimized from 2016,the WHO's impact target would be achieved in 2038.Increasing the clearance rate further from 2%to 2.8%during 2016–2030 linearly,the impact target would be achieved on time.Conclusions It is difficult for China to achieve the WHO's impact target of 65%reduction in hepatitis B-related deaths by 2030 even we assumed the D&T rate would reach 72%in 2030 and beyond.A comprehensive scale-up of available strategies,especially innovative drugs and technologies will ensure that China achieves the target on schedule.展开更多
The global pandemic of 2019 coronavirus disease(COVID-19)is a great assault to public health.Presymptomatic transmission cannot be controlled with measures designed for symptomatic persons,such as isolation.This study...The global pandemic of 2019 coronavirus disease(COVID-19)is a great assault to public health.Presymptomatic transmission cannot be controlled with measures designed for symptomatic persons,such as isolation.This study aimed to estimate the interval of the transmission generation(TG)and the presymptomatic period of COVID-19,and compare the ftting effects of TG and serial interval(S)based on the SEIHR model incorporating the surveillance data of 3453 cases in 31 provinces.These data were allocated into three distributions and the value of AIC presented that the Weibull distribution fitted well.The mean of TG was 5.2 days(95%C:4.6-5.8).The mean of the presymptomatic period was 2.4 days(95%CI:1.5-3.2).The dynamic model using TG as the generation time performed well.Eight provinces exhibited a basic reproduction number from 2.16 to 3.14.Measures should be taken to control presymptomatic transmission in the COVID-19 pandemic.展开更多
A new coronavirus disease(COVID-19)with infection by a novel coronavirus named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has spread globally since December 2019.By 22th September 2020,more than 200 co...A new coronavirus disease(COVID-19)with infection by a novel coronavirus named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has spread globally since December 2019.By 22th September 2020,more than 200 countries worldwide have reported about 30 million confirmed cases and more than 950,000 deaths.1 China has reported a total of 85,307(including 2,758 imported)cases and 4,634 deaths.展开更多
Mass testing is an intervention strategy for COVID-19 control in the general population regardless of the presentation of symptoms.It involves collecting nasal or pharyngeal swabs for DNA testing,often using the polym...Mass testing is an intervention strategy for COVID-19 control in the general population regardless of the presentation of symptoms.It involves collecting nasal or pharyngeal swabs for DNA testing,often using the polymerase chain reaction method.Countries that have used mass testing consider it to be a viable strategy to control the COVID-19 pandemic as the strategy can potentially identify and isolate asymptomatic cases in the early stages of infection and reduce the risk of virus transmission.Since the reopening of Wuhan,China,in early April 2020,China has conducted mass testings in three megacities with populations of over 10 million,including Beijing and Qingdao1 at the beginning of their local outbreaks,and Wuhan immediately after the reopening.展开更多
Introduction:Minimizing the importation and exportation risks of coronavirus disease 2019(COVID-19)is a primary concern for sustaining the“Dynamic COVID-zero”strategy in China.Risk estimation is essential for cities...Introduction:Minimizing the importation and exportation risks of coronavirus disease 2019(COVID-19)is a primary concern for sustaining the“Dynamic COVID-zero”strategy in China.Risk estimation is essential for cities to conduct before relaxing border control measures.Methods:Informed by the daily number of passengers traveling between 367 prefectures(cities)in China,this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.Results:Under the transmission scenario(R0=5.49),this study estimated the cumulative case incidence of Changchun City,Jilin Province as 3,233(95%confidence interval:1,480,4,986)before a lockdown on March 14,2022,which is close to the 3,168 cases reported in real life by March 16,2022.In a total of 367 prefectures(cities),127(35%)had high exportation risks according to the simulation and could transmit the disease to 50%of all other regions within a period from 17 to 94 days.The average time until a new infection arrives in a location in 1 of the 367 prefectures(cities)ranged from 26 to 101 days.Conclusions:Estimating COVID-19 importation and exportation risks is necessary for preparedness,prevention,and control measures of COVID-19—especially when new variants emerge.展开更多
BACKGROUND The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus COVID-19.Lifting of this quarantine is imminent.We modelled the e...BACKGROUND The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus COVID-19.Lifting of this quarantine is imminent.We modelled the effects of two key health interventions on the epidemic when the quarantine is lifted.展开更多
基金supported by the National Natural Science Foundation of China(82320108018,12171387)National Key R&D Program of China(2023YFC2306004,2022YFC2304000,2022YFC2505100).
文摘Background At the end of 2022,China adjusted its coronavirus disease 2019(COVID-19)prevention and control strategy.How this adjustment affected the cumulative infection rate is debated,and how second booster dose vaccination affected the pandemic remains unclear.Methods We collected COVID-19 case data for China's mainland from December 7,2022,to January 7,2023,reported by the World Health Organization.We also collected cumulative infection rate data from five large-scale population-based surveys.Next,we developed a dynamic transmission compartment model to characterize the COVID-19 pandemic and to estimate the cumulative infection rate.In addition,we estimated the impact of second booster vaccination on the pandemic by examining nine scenarios with different vaccination coverages(0%,20%,and 40%)and vaccine effectiveness(30%,50%,and 70%).Results By January 7,2023,when COVID-19 was classified as a Class B infectious disease,the cumulative infection rate of the Omicron variant nationwide had reached 84.11%(95%confidence interval[CI]:78.13%–90.08%).We estimated that the cumulative infection rates reached 50.50%(95%CI:39.58%–61.43%),56.15%(95%CI:49.05%–67.22%),73.82%(95%CI:64.63%–83.02%),75.76%(95%CI:67.02%–84.50%),and 84.99%(95%CI:79.45%–90.53%)on December 19,20,25,and 26,2022,and on January 15,2023,respectively.These results are similar to those of the population survey conducted on the corresponding dates,that is 46.93%,61%,63.52%,74%,and 84.7%,respectively.In addition,we estimated that by January 7,2023,the cumulative infection rate decreased to 29.55%(64.25%)if vaccination coverage and the effectiveness of second booster vaccination were 40%(20%)and 70%(30%),respectively.Conclusion We estimate that,in late 2022,the cumulative infection rate was approximately 84%and that second booster vaccination before the policy adjustment was effective in reducing this rate.
基金supported by the National Science and Technology Key Project of the Ministry of Science and Technology of the People’s Republic of China(No.2018ZX10721202).
文摘Background The World Health Organization(WHO)targets a 65%reduction in hepatitis B-related deaths by 2030 compared to 2015 to eliminate viral hepatitis as a major public health threat.It is unknown whether and how China can achieve this target despite significant intervention achievements.We aimed to predict the hepatitis B-related deaths in China and identify key developments needed to achieve the target.Methods An age-and time-dependent dynamic hepatitis B virus(HBV)transmission compartmental model was developed to predict the trend of hepatitis B-related deaths under base-case and subsequent scenarios from 2015 to 2040.In base-case scenario,we assumed the diagnosis and treatment(D&T)rate would reach 72%in 2030,as proposed by WHO.Subsequent scenarios were set based on the results of base-case and one-way sensitivity analysis.Results Compared with 2015,hepatitis B-related deaths would be reduced by 23.89%in 2030 and 51.79%in 2040,respectively,and the WHO's impact target of 65%reduction would not be achieved until 2038 at the earliest under base-case scenario.HBV clearance rate and current treatment effectiveness were the most sensitive parameters that significantly influenced the decline of hepatitis B-related deaths from 2015 to 2040.In the subsequent scenario,when D&T rate improving to 90%by 2030,with the current treatment effectiveness and HBV clearance rate being optimized from 2016,the WHO's impact target would be achieved in 2038.Increasing the clearance rate further from 2%to 2.8%during 2016–2030 linearly,the impact target would be achieved on time.Conclusions It is difficult for China to achieve the WHO's impact target of 65%reduction in hepatitis B-related deaths by 2030 even we assumed the D&T rate would reach 72%in 2030 and beyond.A comprehensive scale-up of available strategies,especially innovative drugs and technologies will ensure that China achieves the target on schedule.
基金the National Natural Science Foundation of China(82041026,81673275,11961071,91846302)the Huai'an Key Laboratory for Infectious Diseases Control and Prevention(HAP201704).
文摘The global pandemic of 2019 coronavirus disease(COVID-19)is a great assault to public health.Presymptomatic transmission cannot be controlled with measures designed for symptomatic persons,such as isolation.This study aimed to estimate the interval of the transmission generation(TG)and the presymptomatic period of COVID-19,and compare the ftting effects of TG and serial interval(S)based on the SEIHR model incorporating the surveillance data of 3453 cases in 31 provinces.These data were allocated into three distributions and the value of AIC presented that the Weibull distribution fitted well.The mean of TG was 5.2 days(95%C:4.6-5.8).The mean of the presymptomatic period was 2.4 days(95%CI:1.5-3.2).The dynamic model using TG as the generation time performed well.Eight provinces exhibited a basic reproduction number from 2.16 to 3.14.Measures should be taken to control presymptomatic transmission in the COVID-19 pandemic.
基金supported by the National Natural Science Foundation of China(81950410639[L.Z.],11801435[M.S.],11631012[Y.X.],81673275[Z.P.],91846302[Z.P.])Outstanding Young Scholars Support Program(3111500001[L.Z.])+9 种基金Xi'an Jiaotong University Basic Research and Profession Grant(xtr022019003[L.Z.],xzy032020032[L.Z.])Xi'an Jiaotong University Young Scholar Support Grant(YX6J004[L.Z.])the Bill&Melinda Gates Foundation(20200344[L.Z.])China Postdoctoral Science Foundation(2018M631134,2020T130095ZX)the Fundamental Research Funds for the Central Universities(xjh012019055,xzy032020026)Natural Science Basic Research Program of Shaanxi Province(2019JQ-187)Xi'an Special Science and Technology Projects on Prevention and Treatment of Novel Coronavirus Penumonia Emergency(20200005YX005)Zhejiang University special scientific research fund for COVID-19 prevention and control(2020XGZX056)the National S&T Major Project Foundation of China(2018ZX10715002-004,2018ZX10713001-001)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘A new coronavirus disease(COVID-19)with infection by a novel coronavirus named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has spread globally since December 2019.By 22th September 2020,more than 200 countries worldwide have reported about 30 million confirmed cases and more than 950,000 deaths.1 China has reported a total of 85,307(including 2,758 imported)cases and 4,634 deaths.
基金This work was supported by the National Natural Science Foundation of China(11801435 to M.S.,8191101420 to L.Z.,11631012 to Y.X.)the China Postdoctoral Science Foundation(2018M631134,2020T130095ZX)+7 种基金the Fundamental Research Funds for the Central Universities(xjh012019055,xzy032020026)the Natural Science Basic Research Program of Shaanxi Province(2019JQ-187)the Bill&Melinda Gates FoundationOutstanding Young Scholars Funding(3111500001to L.Z.)Xi’an Jiaotong University Basic Research and Profession Grant(xtr022019003 and xzy032020032 to L.Z.),and Xi’an Jiaotong University Young Talent Support Grant(YX6J004 to L.Z.)Xi’an Special Science and Technology Projects on Prevention and Treatment of Novel Coronavirus Penumonia Emergency(20200005YX005)Science Foundation for COVID-19 of Xi’an Jiaotong University Health Science Center and Qinnong Bank(2008124)Zhejiang University special scientific research fund for COVID-19 prevention and control(2020XGZX056).
文摘Mass testing is an intervention strategy for COVID-19 control in the general population regardless of the presentation of symptoms.It involves collecting nasal or pharyngeal swabs for DNA testing,often using the polymerase chain reaction method.Countries that have used mass testing consider it to be a viable strategy to control the COVID-19 pandemic as the strategy can potentially identify and isolate asymptomatic cases in the early stages of infection and reduce the risk of virus transmission.Since the reopening of Wuhan,China,in early April 2020,China has conducted mass testings in three megacities with populations of over 10 million,including Beijing and Qingdao1 at the beginning of their local outbreaks,and Wuhan immediately after the reopening.
基金Supported by AIR@InnoHK programme from The Innovation and Technology Commission of the Hong Kong Special Administrative Region,National Natural Science Foundation of China(72104208)JSPS KAKENHI(JP21H04595)National Nature Science Foundation of China(72025405,91846301,72088101,and 71790615).
文摘Introduction:Minimizing the importation and exportation risks of coronavirus disease 2019(COVID-19)is a primary concern for sustaining the“Dynamic COVID-zero”strategy in China.Risk estimation is essential for cities to conduct before relaxing border control measures.Methods:Informed by the daily number of passengers traveling between 367 prefectures(cities)in China,this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.Results:Under the transmission scenario(R0=5.49),this study estimated the cumulative case incidence of Changchun City,Jilin Province as 3,233(95%confidence interval:1,480,4,986)before a lockdown on March 14,2022,which is close to the 3,168 cases reported in real life by March 16,2022.In a total of 367 prefectures(cities),127(35%)had high exportation risks according to the simulation and could transmit the disease to 50%of all other regions within a period from 17 to 94 days.The average time until a new infection arrives in a location in 1 of the 367 prefectures(cities)ranged from 26 to 101 days.Conclusions:Estimating COVID-19 importation and exportation risks is necessary for preparedness,prevention,and control measures of COVID-19—especially when new variants emerge.
基金This work is supported by a research grant from the Bill&Melinda Gates Foundation.L.Z.is supported by the National Natural Science Foundation of China(8191101420)Outstanding Young Scholars Funding,China(Grant number:3111500001)+4 种基金Xi’an Jiaotong University Young Talent Support ProgramXi'an Jiaotong University Basic Research and Profession Grant(xtr022019003).M.S.was supported by the National Natural Science Foundation of China(grant no.11801435),China Postdoctoral Science Foundation(grant no.2018M631134)the Fundamental Research Funds for the Central Universities(grant no.xjh012019055,xzy032020026)Natural Science Basic Research Program of Shaanxi Province(grant no.2019JQ-187)and Xi'an Special Science and Technology Projects on Prevention and Treatment of Novel Coronavirus Penumonia Emergency(grant no.20200005YX005).
文摘BACKGROUND The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus COVID-19.Lifting of this quarantine is imminent.We modelled the effects of two key health interventions on the epidemic when the quarantine is lifted.
