This working group will focus on statistical issues related to public health surveillance. There will be special emphasis placed on biosurveillance and monitoring for bioterrorist attacks. Talks will be accessible to students, as well as researchers and other officials outside of the biostatistics department.

Till Baernighausen, Ph.D., M.D., Sc.D.
Assistant Professor of Global Health, Department of Global Health and Population, Harvard School of Public Health

"Adding Interventions and Information to HIV Surveillance: Studies in South Africa"

ABSTRACT: None Given

Martin Kulldorff, Ph.D.
Professor, and Biostatistician, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute

"Drug and Vaccine Safety Data Mining"

ABSTRACT: When a new pharmaceutical drug enters the market, there are always questions about its effectiveness and safety profile in comparison with other related drugs. Post-marketing drug safety surveillance is important in order to detect serious adverse events that are too rare to be detected during phase three clinical trials. Such surveillance has traditionally been based on spontaneous adverse event reporting systems but electronic health records from health insurance plans are now increasingly being used instead.

We use the tree-based scan statistic data mining method to search for unexpected acute drug adverse events, using a 4.5 million patient electronic health records database from three health insurance plans: Harvard Pilgrim Health Care, Kaiser Permanente Northern California and Kaiser Permanente Colorado. We are assessing the safety of the majority of commonly used pharmaceutical drugs. Any signals detected will be evaluated through temporal scan statistics that looks at the temporal distribution of the time between drug initiation and the adverse event.

Miguel Marino, Ph.D.
Research Fellow, Department of Biostatistics, Harvard School of Public Health

"On the Gender Difference in HIV Prevalence Estimates From sub-Saharan Demographic and Health Surveys"

ABSTRACT: Accurate national HIV prevalence estimates are necessary for monitoring the epidemic, developing policy formulation, planning resource allocation, and evaluating treatment interventions. One of the largest national population-based surveys designed to estimate HIV prevalence in sub-Saharan Africa is the Demographics and Health Survey (DHS). Because of the survey's ability to characterize subgroups, several studies have been carried out on DHS contrasting the HIV prevalence between males and females in sub-Saharan Africa. These studies suggest that women have a higher prevalence of HIV than males in most sub-Saharan African countries. Prevailing explanations for this observed HIV prevalence gender gap in sub-Saharan Africa mainly involve biological and social factors.

We explore the possibility that survey nonresponse explains some of the gender gap in HIV prevalence. It is very common for surveys to experience some amount of nonresponse. Are women simply more likely to consent to HIV testing than males, and could this have an impact on the observed gender gap? The aim of this study is to evaluate the impact of differential survey nonresponse rates between males and females on the gender differences in HIV prevalence estimates in 29 DHS sub-Saharan surveys from 2001 to 2010. We introduce the concept of plausible range intervals that account for nonresponse without any modeling assumptions. Finally, we provide heuristic formulations of the true prevalence ratio between genders as a function of the observed prevalence ratio and gender-specific nonresponse rates.