Introduction:Since November 2023,influenza has ranked first in reported cases of infectious diseases in China,with the outbreak in both northern and southern provinces exceeding the levels observed during the same per...Introduction:Since November 2023,influenza has ranked first in reported cases of infectious diseases in China,with the outbreak in both northern and southern provinces exceeding the levels observed during the same period in 2022.This poses a serious health risk to the population.Therefore,short to medium-term influenza predictions are beneficial for epidemic assessment and can reduce the disease burden.Methods:A transmission dynamics model considering population migration,encompassing susceptible-exposed-infectious-asymptomatic-recovered(SEIAR)was used to predict the dynamics of influenza before the Spring Festival travel rush.Results:The overall epidemic shows a declining trend,with the peak expected to occur from week 47 in 2023 to week 1 in 2024.The number of cases of A(H3N2)is greater than that of influenza B,and the influenza situation is more severe in the southern provinces compared to the northern ones.Conclusion:Our method is applicable for short-term and medium-term influenza predictions.As the spring festival travel rush approaches.Therefore,it is advisable to advocate for nonpharmaceutical interventions(NPIs),influenza vaccination,and other measures to reduce healthcare and public health burden.展开更多
Since late 2019,the beginning of coronavirus disease 2019(COVID-19)pandemic,transmission dynamics models have achieved great development and were widely used in predicting and policymaking.Here,we provided an introduc...Since late 2019,the beginning of coronavirus disease 2019(COVID-19)pandemic,transmission dynamics models have achieved great development and were widely used in predicting and policymaking.Here,we provided an introduction to the history of disease transmission,summarized transmission dynamics models into three main types:compartment extension,parameter extension and population-stratified extension models,highlight the key contribution of transmission dynamics models in COVID-19 pandemic:estimating epidemiological parameters,predicting the future trend,evaluating the effectiveness of control measures and exploring different possibilities/scenarios.Finally,we pointed out the limitations and challenges lie ahead of transmission dynamics models.展开更多
The coronavirus disease 2019(COVID-19)pandemic is a global crisis,and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and seve...The coronavirus disease 2019(COVID-19)pandemic is a global crisis,and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and severe illnesses.This study aimed to assess COVID-19-related essential clinical resource demands in China,based on different scenarios involving COVID-19 spreads and interventions.We used a susceptible–exposed–infectious–hospitalized/isolated–removed(SEIHR)transmission dynamics model to estimate the number of COVID-19 infections and hospitalizations with corresponding essential healthcare resources needed.We found that,under strict non-pharmaceutical interventions(NPIs)or mass vaccination of the population,China would be able to contain community transmission and local outbreaks rapidly.However,under scenarios involving a low intensity of implemented NPIs and a small proportion of the population vaccinated,the use of a peacetime–wartime transition model would be needed for medical source stockpiles and preparations to ensure a normal functioning healthcare system.The implementation of COVID-19 vaccines and NPIs in different periods can influence the transmission of COVID-19 and subsequently affect the demand for clinical diagnosis and treatment.An increased proportion of asymptomatic infections in simulations will not reduce the demand for medical resources;however,attention must be paid to the increasing difficulty in containing COVID-19 transmission due to asymptomatic cases.This study provides evidence for emergency preparations and the adjustment of prevention and control strategies during the COVID-19 pandemic.It also provides guidance for essential healthcare investment and resource allocation.展开更多
Surveillance is an essential work on infectious diseases prevention and control.When the pandemic occurred,the inadequacy of traditional surveillance was exposed,but it also provided a valuable opportunity to explore ...Surveillance is an essential work on infectious diseases prevention and control.When the pandemic occurred,the inadequacy of traditional surveillance was exposed,but it also provided a valuable opportunity to explore new surveillance methods.This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness(ILI)surveillance.A novel hybrid model(multiattention bidirectional gated recurrent unit(MABG)-susceptible-exposed-infected-removed(SEIR))was developed,which leveraged a deep learning algorithm(MABG)to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever,pyrexia,cough,sore throat,anti-fever medicine,and runny nose.By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019(COVID-19)cases,a transmission dynamics model(SEIR)was formulated to estimate the transmission dynamics and epidemic curve of SARS-Co V-2.During the COVID-19 pandemic,when conventional surveillance measures have been suspended temporarily,cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19.In the specific case of Beijing,it has been ascertained that cumulative infection attack rate surpass 80.25%(95%confidence interval(95%CI):77.51%-82.99%)since December 17,2022,with the apex of the outbreak projected to transpire on December 12.The culmination of existing patients is expected to occur three days subsequent to this peak.Effective reproduction number(Rt)represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic,remained below 1 since December 17,2022.The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support.Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks.Syndrome surveillance on COVID-19 should be established to following on the epidemic,clinical severity,and medical resource demand.展开更多
Cervical cancer is a common malignancy in women,with persistent human papillomavirus(HPV)infection as its primary cause.Understanding the progression from HPV infection to cervical cancer is crucial.Mathematical model...Cervical cancer is a common malignancy in women,with persistent human papillomavirus(HPV)infection as its primary cause.Understanding the progression from HPV infection to cervical cancer is crucial.Mathematical models play a key role in converting clinical trial data into long-term health forecasts,helping decision-makers tackle challenges posed by limited data and uncertain outcomes.This paper reviews transmission dynamics models and advancements in simulating HPV transmission leading to cervical cancer.It evaluates preventive and control measures,focusing on the impact of HPV vaccination across different vaccine types,doses,age groups,and both genders.These model-based assessments aim to provide insights for developing effective strategies to prevent and control HPV-related cervical cancer.展开更多
Mathematical models are increasingly being used in the evaluation of control strategies for infectious disease such as the vaccination program for the Human PapiUomavirus （HPV）. Here, an ordinary differential equati...Mathematical models are increasingly being used in the evaluation of control strategies for infectious disease such as the vaccination program for the Human PapiUomavirus （HPV）. Here, an ordinary differential equation （ODE） transmission dynamic model for HPV is presented and analyzed. Parameter values for a gender and risk structured model are estimated by calibrating the model around the known prevalence of infection. The effect on gender and risk sub-group prevalence induced by varying the epidemiological parameters are investigated. Finally, the outcomes of this model are applied using a classical mathematical method for calculating R0 in a heterogeneous mixing population. Estimates for R0 under various gender and mixing scenarios are presented.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supported by the Key Research and Development Project in the Health Field of Chongqing(CSTC2021jscx-gksb-N0003)the Provincial Key Research and Development Programof Jiangxi,China(20232BBG70020)+1 种基金the Major Project of Guangzhou National Laboratory(GZNL2024A01004)the National Key Research and Development Program Project(2021YFC2301604).
文摘Introduction:Since November 2023,influenza has ranked first in reported cases of infectious diseases in China,with the outbreak in both northern and southern provinces exceeding the levels observed during the same period in 2022.This poses a serious health risk to the population.Therefore,short to medium-term influenza predictions are beneficial for epidemic assessment and can reduce the disease burden.Methods:A transmission dynamics model considering population migration,encompassing susceptible-exposed-infectious-asymptomatic-recovered(SEIAR)was used to predict the dynamics of influenza before the Spring Festival travel rush.Results:The overall epidemic shows a declining trend,with the peak expected to occur from week 47 in 2023 to week 1 in 2024.The number of cases of A(H3N2)is greater than that of influenza B,and the influenza situation is more severe in the southern provinces compared to the northern ones.Conclusion:Our method is applicable for short-term and medium-term influenza predictions.As the spring festival travel rush approaches.Therefore,it is advisable to advocate for nonpharmaceutical interventions(NPIs),influenza vaccination,and other measures to reduce healthcare and public health burden.
基金the National Natural Science Foundation of China(No.82041024 to F.C.,81973142 to Y.W.)the Bill&Melinda Gates Foundation(Investment ID:INV-006371).
文摘Since late 2019,the beginning of coronavirus disease 2019(COVID-19)pandemic,transmission dynamics models have achieved great development and were widely used in predicting and policymaking.Here,we provided an introduction to the history of disease transmission,summarized transmission dynamics models into three main types:compartment extension,parameter extension and population-stratified extension models,highlight the key contribution of transmission dynamics models in COVID-19 pandemic:estimating epidemiological parameters,predicting the future trend,evaluating the effectiveness of control measures and exploring different possibilities/scenarios.Finally,we pointed out the limitations and challenges lie ahead of transmission dynamics models.
基金supported by the following fundings:Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2020-I2M-1-001,2020-I2M-2-015,and 2016-I2M-1-014)National Social Science Fund of China(20&ZD201).
文摘The coronavirus disease 2019(COVID-19)pandemic is a global crisis,and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and severe illnesses.This study aimed to assess COVID-19-related essential clinical resource demands in China,based on different scenarios involving COVID-19 spreads and interventions.We used a susceptible–exposed–infectious–hospitalized/isolated–removed(SEIHR)transmission dynamics model to estimate the number of COVID-19 infections and hospitalizations with corresponding essential healthcare resources needed.We found that,under strict non-pharmaceutical interventions(NPIs)or mass vaccination of the population,China would be able to contain community transmission and local outbreaks rapidly.However,under scenarios involving a low intensity of implemented NPIs and a small proportion of the population vaccinated,the use of a peacetime–wartime transition model would be needed for medical source stockpiles and preparations to ensure a normal functioning healthcare system.The implementation of COVID-19 vaccines and NPIs in different periods can influence the transmission of COVID-19 and subsequently affect the demand for clinical diagnosis and treatment.An increased proportion of asymptomatic infections in simulations will not reduce the demand for medical resources;however,attention must be paid to the increasing difficulty in containing COVID-19 transmission due to asymptomatic cases.This study provides evidence for emergency preparations and the adjustment of prevention and control strategies during the COVID-19 pandemic.It also provides guidance for essential healthcare investment and resource allocation.
基金supported by grants from the Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2021I2M-1-044)。
文摘Surveillance is an essential work on infectious diseases prevention and control.When the pandemic occurred,the inadequacy of traditional surveillance was exposed,but it also provided a valuable opportunity to explore new surveillance methods.This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness(ILI)surveillance.A novel hybrid model(multiattention bidirectional gated recurrent unit(MABG)-susceptible-exposed-infected-removed(SEIR))was developed,which leveraged a deep learning algorithm(MABG)to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever,pyrexia,cough,sore throat,anti-fever medicine,and runny nose.By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019(COVID-19)cases,a transmission dynamics model(SEIR)was formulated to estimate the transmission dynamics and epidemic curve of SARS-Co V-2.During the COVID-19 pandemic,when conventional surveillance measures have been suspended temporarily,cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19.In the specific case of Beijing,it has been ascertained that cumulative infection attack rate surpass 80.25%(95%confidence interval(95%CI):77.51%-82.99%)since December 17,2022,with the apex of the outbreak projected to transpire on December 12.The culmination of existing patients is expected to occur three days subsequent to this peak.Effective reproduction number(Rt)represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic,remained below 1 since December 17,2022.The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support.Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks.Syndrome surveillance on COVID-19 should be established to following on the epidemic,clinical severity,and medical resource demand.
基金Supported by grants from The Department of Science and Technology of Hunan Province(No:2020SK1010)the National Health Commission of the Hunan Province(No:202212054651).
文摘Cervical cancer is a common malignancy in women,with persistent human papillomavirus(HPV)infection as its primary cause.Understanding the progression from HPV infection to cervical cancer is crucial.Mathematical models play a key role in converting clinical trial data into long-term health forecasts,helping decision-makers tackle challenges posed by limited data and uncertain outcomes.This paper reviews transmission dynamics models and advancements in simulating HPV transmission leading to cervical cancer.It evaluates preventive and control measures,focusing on the impact of HPV vaccination across different vaccine types,doses,age groups,and both genders.These model-based assessments aim to provide insights for developing effective strategies to prevent and control HPV-related cervical cancer.
文摘Mathematical models are increasingly being used in the evaluation of control strategies for infectious disease such as the vaccination program for the Human PapiUomavirus （HPV）. Here, an ordinary differential equation （ODE） transmission dynamic model for HPV is presented and analyzed. Parameter values for a gender and risk structured model are estimated by calibrating the model around the known prevalence of infection. The effect on gender and risk sub-group prevalence induced by varying the epidemiological parameters are investigated. Finally, the outcomes of this model are applied using a classical mathematical method for calculating R0 in a heterogeneous mixing population. Estimates for R0 under various gender and mixing scenarios are presented.
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.
