Predicting Impacts of Infectious Disease on Structure and Dynamics of Populations

描述(申请人提供)：非洲正在经历一场戏剧性的流行病学转变，其驱动因素是传统传染病管理的持续改善、性传播感染和结核病流行的同时爆炸性增长以及慢性非传染性疾病的流行迅速增加。有了以下具体目标，这份职业发展申请符合我的长期目标，即有助于了解并最终控制非洲流行的性传播感染。(1)通过对将核心群体、性关系的并存和移民与性传播感染的传播和传播联系起来的假设的实证调查，衡量和了解受性传播感染影响的人口的重要构成系统。(2)修改、加强和建立数学/计算模型，以代表和调查性传播感染影响的人群，办法是：1)继续采用贝叶斯融合方法，说明模型输入和输出中的不确定性，以便与联合国艾滋病规划署的非特定年龄估计和预测包(EPP)模型配合使用；2)调整和实施类似的方法，以使用支持性传播感染的特定年龄队列部分预测模型；3)为了改进我现有的性传播感染微型模拟器：a)增加新的模块来处理社会、性和移民网络，b)增加基于贝叶斯融合的新程序，以i)考虑不确定性，ii)对输出施加合理的限制，iii)产生输出的预测分布，以及iv)提供一种标准的、可重复的方法来校准模拟器。(3)模拟性传播感染人群，了解和预测干预措施的总体效果。传染病流行有三个直接决定因素：传播概率、接触结构和传染病持续时间，由一个病例产生的继发性病例数的关系式r0=f3cd得出。该模拟器将被用来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洞察力将被用来模拟和确定可能的实际干预措施的优先顺序。我有这类调查的经验，也有解决这些具体目标所需的一些技能。该应用程序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，这些领域是实现这些目标所必需的：1)社会网络理论和建模方法，2)特别是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.