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...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-HostsReservoir 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.展开更多
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...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≤14years old;group 2,those 15 to 44years old;group 3,those 45 to 64years 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.展开更多
Background:The China-Myanmar border region presents a great challenge in malaria elimination in China,and it is essential to understand the relationship between malaria vulnerability and population mobility in this re...Background:The China-Myanmar border region presents a great challenge in malaria elimination in China,and it is essential to understand the relationship between malaria vulnerability and population mobility in this region.Methods:A community-based,cross-sectional survey was performed in five villages of Yingjiang county during September 2016.Finger-prick blood samples were obtained to identify asymptomatic infections,and imported cases were identified in each village(between January 2013 and September 2016).A stochastic simulation model(SSM)was used to test the relationship between population mobility and malaria vulnerability,according to the mechanisms of malaria importation.Results:Thirty-two imported cases were identified in the five villages,with a 4-year average of 1 case/year(range:0-5 cases/year).No parasites were detected in the 353 blood samples from 2016.The median density of malaria vulnerability was 0.012(range:0.000-0.033).The average proportion of mobile members of the study population was 32.56%(range:28.38-71.95%).Most mobile individuals lived indoors at night with mosquito protection.The SSM model fit the investigated data(χ2=0.487,P=0.485).The average probability of infection in the members of the population that moved to Myanmar was 0.011(range:0.0048-0.1585).The values for simulated vulnerability increased with greater population mobility in each village.Conclusions:A high proportion of population mobility was associated with greater malaria vulnerability in the China-Myanmar border region.Mobile population-specific measures should be used to decrease the risk of malaria re-establishment in China.展开更多
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 contr...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.展开更多
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...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 2017,130770 shigellosis cases(including 73981 male and 56789 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 2.3225×10^8 for SARmm(secondary attack rate from male to male),2.5729×10^8 for SARmf 2.7630×10^8 for SARfm,and 2.1061×10^8 for SARff.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 forβ61;5.32×10^8 forβ31,4.01×10^8 forβ34,7.52×10^9 forβ62,and 6.04×10^9 for 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.展开更多
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 m...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.展开更多
Background:Hepatitis E,an acute zoonotic disease caused by the hepatitis E virus(HEV),has a relatively high burden in developing countries.The current research model on hepatitis E mainly uses experimental animal mode...Background:Hepatitis E,an acute zoonotic disease caused by the hepatitis E virus(HEV),has a relatively high burden in developing countries.The current research model on hepatitis E mainly uses experimental animal models(such as pigs,chickens,and rabbits)to explain the transmission of HEV.Few studies have developed a multi-host and multiroute transmission dynamic model(MHMRTDM)to explore the transmission feature of HEV.Hence,this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province.展开更多
基金This study was supported by Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program(No:3502Z2020YJ03).
文摘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-HostsReservoir 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.
基金This work was partly supported by the Open Research Fund of State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics(SKLVD2019KF005)the Bill&Melinda Gates Foundation(INV-005834)+3 种基金the Science and Technology Program of Fujian Province(No:2020Y0002)the Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program(No:3502Z2020YJ03)the Hunan Provincial Construction of Innovative Provinces Special Social Development Areas Key Research and Development Project(2020SK3012)the Chinese Academy of Medical Sciences Coronavirus Disease 2019 Science and Technology Research Project in 2020(2020HY320003).
文摘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≤14years old;group 2,those 15 to 44years old;group 3,those 45 to 64years 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.
基金This work was supported by Scientific Project of Shanghai Municipal Commission of Health and Family Planning(No.20164Y0047).
文摘Background:The China-Myanmar border region presents a great challenge in malaria elimination in China,and it is essential to understand the relationship between malaria vulnerability and population mobility in this region.Methods:A community-based,cross-sectional survey was performed in five villages of Yingjiang county during September 2016.Finger-prick blood samples were obtained to identify asymptomatic infections,and imported cases were identified in each village(between January 2013 and September 2016).A stochastic simulation model(SSM)was used to test the relationship between population mobility and malaria vulnerability,according to the mechanisms of malaria importation.Results:Thirty-two imported cases were identified in the five villages,with a 4-year average of 1 case/year(range:0-5 cases/year).No parasites were detected in the 353 blood samples from 2016.The median density of malaria vulnerability was 0.012(range:0.000-0.033).The average proportion of mobile members of the study population was 32.56%(range:28.38-71.95%).Most mobile individuals lived indoors at night with mosquito protection.The SSM model fit the investigated data(χ2=0.487,P=0.485).The average probability of infection in the members of the population that moved to Myanmar was 0.011(range:0.0048-0.1585).The values for simulated vulnerability increased with greater population mobility in each village.Conclusions:A high proportion of population mobility was associated with greater malaria vulnerability in the China-Myanmar border region.Mobile population-specific measures should be used to decrease the risk of malaria re-establishment in China.
基金the Bill&Melinda Gates Foundation(Grant INV-005834 to T.C.)the Science and Technology Program of Fujian Province(Grant 2020Y0002 to T.C.)NHC Key Laboratory of Echinococcosis Preven‑tion and Control(Grant 2020WZK2001 to T.C.)。
文摘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.
文摘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 2017,130770 shigellosis cases(including 73981 male and 56789 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 2.3225×10^8 for SARmm(secondary attack rate from male to male),2.5729×10^8 for SARmf 2.7630×10^8 for SARfm,and 2.1061×10^8 for SARff.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 forβ61;5.32×10^8 forβ31,4.01×10^8 forβ34,7.52×10^9 forβ62,and 6.04×10^9 for 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.
文摘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.
文摘Background:Hepatitis E,an acute zoonotic disease caused by the hepatitis E virus(HEV),has a relatively high burden in developing countries.The current research model on hepatitis E mainly uses experimental animal models(such as pigs,chickens,and rabbits)to explain the transmission of HEV.Few studies have developed a multi-host and multiroute transmission dynamic model(MHMRTDM)to explore the transmission feature of HEV.Hence,this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province.