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

• 批准号: 7862494
• 负责人: SAMUEL J CLARK
• 金额: $ 12.59万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-15 至 2013-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7862494
• 关键词: AIDS/HIV problem; Accounting; Acquired Immunodeficiency Syndrome; Address; Adult; Affect; Africa; Africa South of the Sahara; African; Age; Algorithms; Area; Behavior; Binding; 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; numb protein; pandemic disease; sexual relationship; skills; social; statistics; theories; transmission process

DESCRIPTION (provided by applicant): 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 in Africa. (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 structure, and the duration of infectiousness suggested 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.

描述（由申请人提供）：非洲正在经历通过持续改善传统传统疾病的管理，同时爆炸性传播感染和结核病流行病，并迅速增加了慢性非传染性疾病的患病率。以以下特定目标，这一职业发展应用程序符合我的长期目标，可以为理解并最终控制非洲的大流行性传播感染。 （1）通过实证研究核心群体，性关系的并发以及迁移与性传播感染的传播和传播，测量和理解受性传播感染影响的人群的重要组成系统。 （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人群：1）继续适应贝叶斯式融合方法，这些方法可以说明模型输入和输出中的不确定性，以与INAIDS的非年龄特异性估计和预测软件包（EPP）模型一起使用； 2）适应和实施类似的方法来使用具有性传播感染的年龄特异性队列组件投影模型； 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）模拟受性传播感染影响的种群，以了解和预测干预措施的总体影响。传染病流行，传播概率，接触结构以及关系R0 = F3 C D的传染性持续时间，对于由病例产生的次要病例的数量，有三个近端决定因素。模拟器将用于探索这些与性传播感染流行病的动态之间的关系。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。我有这种调查的经验以及解决这些特定目标所需的一些技能。该应用程序的职业发展组成部分旨在扩大我在解决这些目标所需的三个特定领域的最低知识和技能：1）社交网络理论和建模方法，2）数学统计和拜访的统计数据，尤其是3）调制解调器最新软件算法算法设计和计算机编程技能。