Predicting Impacts of Infectious Disease on Structure and Dynamics of Populations

描述（由申请人提供）：由于传统传染病管理的不断改进、性传播感染和结核病同时爆发以及慢性非传染性疾病的流行迅速增加，非洲正在经历一场由相反方向推动的戏剧性流行病学转变。有了以下具体目标，这个职业发展应用程序符合我的长期目标，即有助于了解并最终控制非洲的性传播传染病。(1)通过对核心群体、性关系的并发性行为和人口迁移与性传播感染的传播和传播相关的假设进行实证调查，衡量和了解受性传播感染影响的人群的重要组成系统。(2)修改、增强和建立数学/计算模型，以表示和调查受性传播感染影响的人群，方法如下：1)继续采用贝叶斯融合方法，该方法考虑了模型输入和输出的不确定性，以配合联合国艾滋病规划署的非年龄估计和预测包（EPP）模型；2)调整和实施类似的方法，用于支持性传播感染的特定年龄队列成分预测模型；3)通过以下方式改进我现有的性传播感染微模拟器：a)添加新模块来处理社会、性和移民网络；b)添加基于贝叶斯融合的新程序，以i)考虑不确定性；ii)对输出设置合理限制；iii)生成输出的预测分布；iv)提供标准的、可重复的方法来校准模拟器。(3)模拟受性传播感染影响的人群，了解和预测干预措施的总体效果。传染病流行有三个近似决定因素，即传播概率、接触结构和传染性持续时间，这一关系由病例产生的继发病例数R0 = f3 c d表示。模拟器将用于探索这些与性传播感染流行动态之间的关系。通过这一过程获得的见解将用于模拟和优先考虑可能的实际干预措施。我有这类调查的经验，也有处理这些具体目标所需的一些技能。这个申请的职业发展部分旨在扩展我在三个特定领域的最低限度的知识和技能，这是实现这些目标所必需的：1)社会网络理论和建模方法，2)数理统计和贝叶斯统计，以及3)现代最新的软件算法设计和计算机编程技能。

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.