检索结果-南通市图书馆

Infectious Disease Modelling 2017年第3期2卷 379-398页

作者： gerardo chowell Division of Epidemiology&Biostatistics School of Public HealthGeorgia State UniversityAtlantaGAUSA Division of International Epidemiology and Population Studies Fogarty International CenterNational Institutes of HealthBethesdaMDUSA

Mathematical models provide a quantitative framework with which scientists can assess hypotheses on the potential underlying mechanisms that explain patterns in observed data at different spatial and temporal scales,generate estimates of key kinetic parameters,assess the impact of interventions,optimize the impact of control strategies,and generate *** review and illustrate a simple data assimilation framework for calibrating mathematical models based on ordinary differential equation models using time series data describing the temporal progression of case counts relating,for instance,to population growth or infectious disease transmission *** contrast to Bayesian estimation approaches that always raise the question of how to set priors for the parameters,this frequentist approach relies on modeling the error structure in the *** discuss issues related to parameter identifiability,uncertainty quantification and propagation as well as model performance and forecasts along examples based on phenomenological and mechanistic models parameterized using simulated and real datasets.

关键词： Parameter estimation Uncertainty quantification Bootstrap Parameter identifiability Model performance Forecasts Uncertainty propagation

Is it growing exponentially fast? -Impact of assuming exponential growth for characterizing and forecasting epidemics with initial near-exponential growth dynamics

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2016年第1期1卷 71-78页

作者： gerardo chowell Cecile Viboud School of Public Health Georgia State UniversityAtlantaGAUSA Division of International Epidemiology and Population Studies Fogarty International CenterNational Institutes of HealthBethesdaMDUSA

The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing models that capture the baseline transmission characteristics in order to generate reliable epidemic *** models for epidemic forecasting could be achieved by identifying signature features of epidemic growth,which could inform the design of models of disease spread and reveal important characteristics of the transmission *** particular,it is often taken for granted that the early growth phase of different growth processes in nature follow early exponential growth *** the context of infectious disease spread,this assumption is often convenient to describe a transmission process with mass action kinetics using differential equations and generate analytic expressions and estimates of the reproduction *** this article,we carry out a simulation study to illustrate the impact of incorrectly assuming an exponential-growth model to characterize the early phase(e.g.,3e5 disease generation intervals)of an infectious disease outbreak that follows near-exponential growth ***,we assess the impact on:1)goodness of fit,2)bias on the growth parameter,and 3)the impact on short-term epidemic *** findings indicate that devising transmission models and statistical approaches that more flexibly capture the profile of epidemic growth could lead to enhanced model fit,improved estimates of key transmission parameters,and more realistic epidemic forecasts.

关键词： dynamics. process. exponential

A primer on stable parameter estimation and forecasting in epidemiology by a problem-oriented regularized least squares algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2017年第2期2卷 268-275页

作者： Alexandra Smirnova gerardo chowell Department of Mathematics and Statistics Georgia State UniversityAtlantaUSA School of Public Health Georgia State UniversityAtlantaUSA Division of International Epidemiology and Population Studies Fogarty International CenterNational Institutes of HealthBethesdaMDUSA

Public health officials are increasingly recognizing the need to develop disease-forecasting systems to respond to epidemic and pandemic *** instance,simple epidemic models relying on a small number of parameters can play an important role in characterizing epidemic growth and generating short-term epidemic *** the absence of reliable information about transmission mechanisms of emerging infectious diseases,phenomenological models are useful to characterize epidemic growth patterns without the need to explicitly model transmission mechanisms and the natural history of the *** this article,our goal is to discuss and illustrate the role of regularization methods for estimating parameters and generating disease forecasts using the generalized Richards model in the context of the 2014e15 Ebola epidemic in West Africa.

关键词： Generalized Richards model Parameter estimation Regularization methods Epidemic forecasting Ebola

Transmission potential of the novel coronavirus (COVID-19) onboard the diamond Princess Cruises Ship, 2020

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2020年第1期5卷 264-270页

作者： Kenji Mizumoto gerardo chowell Graduate School of Advanced Integrated Studies in Human Survivability Kyoto University Yoshida-Nakaadachi-choSakyo-kuKyotoJapan Hakubi Center for Advanced Research Kyoto UniversityYoshidahonmachiSakyo-kuKyotoJapan Department of Population Health Sciences School of Public HealthGeorgia State UniversityAtlantaGeorgiaUSA Division of International Epidemiology and Population Studies Fogarty International CenterNational Institutes of HealthBethesdaUSA

An outbreak of COVID-19 developed aboard the Princess Cruises Ship during January eFebruary *** mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members,we characterize how the transmission potential varied over the course of the *** estimate of the mean reproduction number in the confined setting reached values as high as^11,which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore(approximate range:1.1e7).Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine *** recent estimates of Rt reached values largely below the epidemic threshold,indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

关键词： Corona Epidemic Confined settings Cruise Next generation matrix

Systematic comparison of epidemic growth patterns using two different estimation approaches

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2021年第1期6卷 5-14页

作者： Yiseul Lee Kimberlyn Roosa gerardo chowell Department of Population Health Sciences School of Public HealthGeorgia State UniversityAtlantaGA30303USA Division of International Epidemiology and Population Studies Fogarty International CenterNational Institute of HealthBethesdaMD20892USA UT One Health Initiative University of TennesseeKnoxvilleTN37996USA

Background:Different estimation approaches are frequently used to calibrate mathematical models to epidemiological data,particularly for analyzing infectious disease ***,we use two common methods to estimate parameters that characterize growth patterns using the generalized growth model(GGM)calibrated to real outbreak *** and methods:Data from 31 outbreaks are used to fit the GGM to the ascending phase of each outbreak and estimate the parameters using both least squares(LSQ)and maximum likelihood estimation(MLE)*** utilize parametric bootstrapping to construct confidence intervals for parameter *** compare the results including RMSE,Anscombe residual,and 95%prediction interval *** also evaluate the correlation between the estimates from both ***:Comparing LSQ and MLE estimates,most outbreaks have similar parameter estimates,RMSE,Anscombe,and 95%prediction interval *** estimates do not differ across methods when the model yields a good fit to the early growth ***,for two outbreaks,there are systematic deviations in model fit to the data that explain differences in parameter estimates(e.g.,residuals represent random error rather than systematic deviation).Conclusion:Our findings indicate that utilizing LSQ and MLE methods produce similar results in the context of characterizing epidemic growth patterns with the GGM,provided that the model yields a good fit to the data.

关键词： Parameter estimation Generalized growth model Least squares estimation Maximum likelihood estimation Epidemiological models

COVID-19 case fatality risk by age and gender in a high testing setting in Latin America: Chile, March-August 2020

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Diseases of Poverty 2021年第1期10卷 99-99页

作者： Eduardo A.Undurraga gerardo chowell Kenji Mizumoto Escuela de Gobierno Pontificia Universidad Catolica de ChileVicuna Mackenna 4860MaculCP 7820436 SantiagoRegion MetropolitanaChile 不详

Background:Early severity estimates of coronavirus disease 2019(COVID-19)are critically needed to assess the potential impact of the on going pandemic in differe nt demographic *** we estimate the real-time delayadjusted case fatality rate across nine age groups by gender in Chile,the country with the highest testing rate for COVID-19 in Latin ***:We used a publicly available real-time daily series of age-stratified COVID-19 cases and deaths reported by the Ministry of Health in Chile from the beginning of the epidemic in March through August 31,*** used a robust likelihood function and a delay distribution to estimate real-time delay-adjusted case-fatality risk and estimate model parameters using a Monte Carlo Markov Chain in a Bayesian framework.

关键词： COVID-19 Chile Death risk by age group Time-delay adjusted case fatality rate Latin America

Urban structure and the risk of influenza A(H1N1) outbreaks in municipal districts

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Science Bulletin 2014年第5期59卷 554-562页

作者： Hong Xiao Xiaoling Lin gerardo chowell Cunrui Huang Lidong Gao Biyun Chen Zheng Wang Liang Zhou Xinguang He Haining Liu Xixing Zhang Huisuo Yang College of Resources and Environment Science Hunan Normal University Mathematical Computational and Modeling Sciences CenterSchool of Human Evolution and Social Change Arizona State University Division of International Epidemiology and Population Studies Fogarty International Center National Institutes of Health Centre for Environment and Population Health School of Environment Griffith University Hunan Provincial Center for Disease Control and Prevention Department of Respiratory and Critical Care Medicine Beijing Institute of Respiratory Medicine Beijing Chaoyang Hospital Affiliated to Capital Medical University Changsha Municipal Center for Disease Prevention and Control Center for Disease Control and Prevention of Beijing Military Region

Changsha was one of the most affected areas during the 2009 A(H1N1)influenza pandemic in ***,we analyze the spatial–temporal dynamics of the 2009 pandemic across Changsha municipal districts,evaluate the relationship between case incidence and the local urban spatial structure and predict high-risk areas of influenza A(H1N1).We obtained epidemiological data on all cases of influenza A(H1N1)reported across municipal districts in Changsha during period May 2009–December 2010 and data on population density and basic geographic characteristics for 239 primary schools,97 middle schools,347 universities,96 malls and markets,674 business districts and 121 ***–temporal K functions,proximity models and logistic regression were used to analyze the spatial distribution pattern of influenza A(H1N1)incidence and the association between influenza A(H1N1)cases and spatial risk factors and predict the infection *** found that the 2009 influenza A(H1N1)was driven by a transmission wave from the center of the study area to surrounding areas and reported cases increased significantly after September *** also found that the distribution of influenza A(H1N1)cases was associated with population density and the presence of nearest public places,especially universities(OR=10.166).The final predictive risk map based on the multivariate logistic analysis showed high-risk areas concentrated in the center areas of the study area associated with high population *** findings support the identification of spatial risk factors and highrisk areas to guide the prioritization of preventive and mitigation efforts against future influenza pandemics.

关键词：风险图流感甲型城市结构 Logistic回归分析 logistic回归城市空间结构爆发

Early transmission dynamics of COVID-19 in a southern hemisphere setting:Lima-Peru:February 29^(th)-March 30^(th),2020

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Infectious Disease Modelling 2020年第1期5卷 338-345页

作者： César V.Munayco Amna Tariq Richard Rothenberg Gabriela G.Soto-Cabezas Mary F.Reyes Andree Valle Leonardo Rojas-Mezarina César Cabezas Manuel Loayza gerardo chowell 无 Centro Nacional de Epidemiología Prevencion y Control de EnfermedadesPeruvian Ministry of HealthLimaPeru Department of Population Health Sciences School of Public HealthGeorgia State UniversityAtlantaGAUSA Instituto Nacional de Salud Peruvian Ministry of HealthLimaPeru Peru COVID-19 working group

The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four *** daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th,*** Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th,2020,the daily number of new COVID-19 cases continues to accumulate in this *** assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima,*** estimated the reproduction number,R,during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th,*** also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in *** to the implementation of the social distancing measures in Lima,the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter,p,estimated at 0.96(95%CI:0.87,1.0)and the reproduction number at 2.3(95%CI:2.0,2.5).Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus,with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the *** the interventions appear to have slowed the transmission rate in Lima,the number of new COVID-19 cases continue to accumulate,highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

关键词： COVID-19 SARS-CoV-2 Transmission potential Short-term forecast Reproduction number Generalized growth model