Time : 1:30-4:00 pm , Oct 24, (Tuesday)
Venue: Room 300, SIBS Main Building, Yueyang Road 320
Host：Prof. Zefeng Wang
CAS-MPG Partner Institute for Computational Biology
1.Speaker： Dr. Yingqing Chen, Phd
Affiliate Professor, Fred Hutchinson Cancer Research Center.
Title： Design for a Scientific Breakthrough Study in HIV/AIDS Research
Abstract:
The HIV Prevention Trial Network (HPTN) 052 Study is a Phase III, controlled, randomized clinical trial to assess the effectiveness of antiretroviral therapy strategies in preventing sexual transmission of HIV-1 (Cohen, et al., 2011). The “Science” Magazine named it as the Scientific Breakthrough of the Year for 2011 (Alberts, 2011). In this talk, we will focus on the design and methods that underlie this successful study in HIV Treatment-as-Prevention, and discuss the lessons that we have learned for future research.
References:
Alberts, B (2011) Science breakthroughs, Science, 334: 1604
Cohen, MS, Chen, YQ, McCauley, M, et al. (2011) Prevention of HIV-1 infection with early antiretroviral therapy, New England Journal of Medicine, 365: 493-505
2.Speaker：Dr , Sayan Dasgupta, PhD
Staff Scientist,Fred Hutchinson Cancer Research Center.
Title：Assessment of complex epidemiological models
Abstract:
Complex, dynamic models of infectious diseases can be used to understand the transmission dynamics of the disease, project the course of an epidemic, predict the effect of interventions and/or provide information for power calculations of community level intervention studies. However, there have been relatively few opportunities to rigorously evaluate the predictions of such models. Indeed, while there is a large literature on calibration (fitting model parameters) and validation (comparing model outputs to data) of complex models, the lack of substantial high quality, population-level disease incidence data has led to fairly simple procedures for calibration and validation of models of infectious diseases. Recently, several community level randomized trials of combination HIV intervention have been planned and/or initiated. In each case, significant epidemic modeling efforts were conducted during trial planning and were integral to the design of these trials. The existence of these models that have been designed to predict trial results in a specific setting, and the (anticipated) availability of results from those trials, provide a unique opportunity to evaluate those models and their usefulness in trial design. In this project, we outline a framework for evaluating the predictions of complex epidemiological models and describe experiments that can be used to test this framework prior to the completion of the ongoing trials, such as the HPTN 071 (PopART) Study.
3.Speaker：Dr.Yifan Zhu, PhD
Staff Scientist,Fred Hutchinson Cancer Research Center.
Title：Data challenges in mobile health - a motivating example from Wisepill drug monitoring in HIV prevention trials
Abstract:
With rapid advancement in hardware and software technologies, a vast amount of multi-channel, real-time high-resolution data are being generated from wearable devices and mobile phones. The comprehensive coverage of individual-level physiological and behavioral monitoring, combined with traditional approaches, could make significant public health impact on risk-assessment, disease monitoring, and prevention intervention. The mobile device R01 project focuses on the common data features and challenges that are produced by various devices, such as wearable accelerometers, electrocardiogram (ECG) patch monitors, electrical drug monitoring and GPS/cellular phone location tracking. We aim for novel statistical methods alongside the analytic workflow for these data, namely sensors to markers, markers to predictions and predictions to interventions in mobile health. An example of analyzing drug adherence monitoring from Wisepill drug dispenser for HIV pre-exposure prophylaxis (PrEP) trial HPTN 069 is given to illustrate the analytic steps, and how these steps promote precision public health.
All are welcome！
官方微信
