Predicting Impacts of Infectious Disease on Structure and Dynamics of Populations

预测传染病对人口结构和动态的影响

基本信息

批准号：
8288877
负责人：
SAMUEL J CLARK
金额：
$ 12.63万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-06-15 至 2013-09-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8288877
关键词：
AIDS/HIV problem Accounting Acquired Immunodeficiency Syndrome Address Adult Affect Africa Africa South of the Sahara African Age Algorithms Area Behavior Biological Process Budgets Cessation of life Chronic Collaborations Communicable Diseases Communities Complex Computer Simulation Computer software Data Demographer Disease Ecology Epidemic Epidemiology Future Geography Goals HIV Individual Infection Intervention Investigation Knowledge Life Measurement Measures Methods Modeling Modems Nomads Outcome Output Phase Play Politics Population Population Dynamics Population Projection Population Study Prevalence Probability Procedures Process Role Sexually Transmitted Diseases Simulate Site Social Network Societies South Africa Structure Symptoms System Time Training Activity Uncertainty Work abstracting base career development cohort computer program design experience heuristics improved insight intervention effect migration pandemic disease sexual relationship skills social statistics theories transmission process

项目摘要

Africa is experiencing a dramatic epidemiological transition driven in opposite directions by continuing improvements in the management of traditional infectious diseases, concurrent exploding sexually transmitted infection and TB epidemics, and swift increases in the prevalence of chronic non-communicable diseases. With the following specific aims, this career development application fits into my long-term goal to contribute to understanding and eventually controlling pandemic sexually transmitted infections inAfrica. (1) To measure and understand the important component systems of a population affected by sexually transmitted infections through empirical investigation of hypotheses that relate core groups, concurrency in sexual relationships and migration to the transmission and spread of sexually transmitted infections. (2) To modify, enhance and build mathematical/computational models to represent and investigate populations affected by sexually transmitted infections by: 1) continuing to adapt Bayesian melding methods that account for uncertainty in model inputs and outputs to work with UNAIDS's non-age-specific estimation and projections package (EPP) model; 2) to adapt and implement similar methods to work with a sexually transmitted infection-enabled age-specific cohort component projection model; 3) to improve my existing sexually transmitted infection-enabled microsimulator by: a) adding new modules to handle social, sexual and migrant networks, b) adding new procedures based on Bayesian melding to i) account for uncertainty, ii) put reasonable limits on outputs, iii)produce predictive distributions for outputs, and iv) provide a standard, reproducible method to calibrate the simulator. (3) To simulate populations affected by sexually transmitted infections to understand and predict the overall effects of interventions. There are three proximate determinants of an infectious disease epidemic, the transmission probability/?, the contact structurec, and the duration of infectiousnessdsuggested by the relationship R0 = f3¿ c ¿d for the number of secondary cases produced by a case. The simulator will be used to explore the relationships between these and the dynamics of sexually transmitted infection epidemics. Insight gained through this process will be used to simulate and prioritize possible real interventions. I have experience with this type of investigation and some of the skills necessary to address these specific aims. The career development component of this application is designed to expand my minimal knowledge and skills in three specific areas that are necessary to address these aims: 1) social network theory and modeling methods, 2) mathematical statistics and Bayesian statistics in particular, and 3) modem up-to-date software algorithm design and computer programming skills.

非洲正在经历通过继续以相反方向驱动的戏剧性流行病学转变改善传统传染病的管理，并发性爆炸传播感染和结核病流行病，以及慢性非传染性患病率的迅速增加疾病。以以下特定目标，此职业发展应用程序符合我的长期目标有助于理解，有时控制大流行性传播感染的疾病。（1）测量和理解受性影响的人群的重要组成系统通过对核心群体相关的假设的实证研究，同时发生的假设，传播感染性关系以及向性传播感染传播和传播的性关系。（2）修改，增强和构建数学/计算模型以表示和调查受性传播感染影响的种群通过：1）继续适应贝叶斯融合方法该解释了模型输入和输出的不确定性，以与UNAID的非时代特定估计一起使用和项目软件包（EPP）模型； 2）适应和实施类似的方法以与传播具有感染的年龄特异性队列组件投影模型； 3）改善我现有的性传播感染的微型模拟器：a）添加新模块来处理社交，性爱 b）添加基于贝叶斯融合的新程序i）不确定性，ii）对产出的合理限制，iii）为输出产生预测分布，iv）提供标准，可再现的方法来校准模拟器。（3）模拟受性传播感染影响的种群，以了解和预测总体干预的影响。传染病流行的三个近端决定者，传输概率/？，联系结构，以及由关系R0 =f3¿d对于案例产生的次要病例的数量。模拟器将使用探索这些与性传播感染发作的动态之间的关系。通过此过程获得的洞察力将用于模拟和确定可能的实际干预措施。我有这种投资的经验以及解决这些特定的一些技能目标。该应用程序的职业发展组成部分旨在扩大我最少的知识以及解决这些目标所需的三个特定领域的技能：1）社交网络理论和建模方法，2）数学统计和贝叶斯统计，3）调制解调器最新软件算法设计和计算机编程技能。

项目成果

期刊论文数量（2）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Improving public health training and research capacity in Africa: a replicable model for linking training to health and socio-demographic surveillance data.

提高非洲的公共卫生培训和研究能力：将培训与健康和社会人口监测数据联系起来的可复制模型。

DOI：
10.3402/gha.v3i0.5287
发表时间：
2010
期刊：
Global health action
影响因子：
2.6
作者：
Williams,JillR;Schatz,EnidJ;Clark,BenjaminD;Collinson,MarkA;Clark,SamuelJ;Menken,Jane;Kahn,Kathleen;Tollman,StephenM
通讯作者：
Tollman,StephenM

Probabilistic Cause-of-death Assignment using Verbal Autopsies.