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Abstract: The objective of this study was to reconstruct the type A influenza epidemic that occurred in the Research Triangle Park (RTP) region of North Carolina during the 2003–04 flu season. We describe an agent-based influenza transmission model that uses Influenza-like Illness (ILI) data gathered from state agencies to estimate model parameters. The design of the model is similar to models represented in the literature that have been used to predict the impact of pandemic avian influenza in Southeast Asia and in the continental United States and to assess containment strategies. The focus of this model is to reconstruct a historical epidemic that left traces of its impact in the form of an ILI epidemic curve. In this context, the work assumes aspects of a curve fitting exercise. [Copyright &y& Elsevier]

Aim To assess the impact of telephone audio computer-assisted self-interviewing (T-ACASI) on reporting of alcohol use, alcohol problems and illicit drug use in telephone surveys of the general population. Prior research suggests that illicit drug use is underreported in traditional, interviewer-administered, telephone surveys. Design Randomized experiment embedded in telephone survey of probability samples of populations of USA and Baltimore, MD. Survey respondents were randomly assigned to be interviewed either by human telephone interviewers or by T-ACASI after household screening, recruitment, and informed consent procedures were completed. Setting Respondents were interviewed by telephone in their homes. Participants Probability samples of 1543 English-speaking adults ages 18–45 residing in telephone-accessible households in USA and 744 similarly defined adults residing in Baltimore, MD, USA. Measurements Nine questions on alcohol, marijuana, cocaine, and injection drug use adapted from 1994 NHSDA and four CAGE questions on alcohol problems. Crude odds ratios and odds ratios controlling for demographic factors calculated to test for differences between responses obtained by T-ACASI and human interviewers. Findings T-ACASI had mixed effects on reporting of alcohol use, but it did increase reporting of one of four CAGE alcohol problems: feeling guilty about drinking (23.0% in T-ACASI vs. 17.6% in T-IAQ, OR = 1.4, P < 0.01). T-ACASI also obtained significantly more frequent reporting of marijuana, cocaine, and injection drug use. The impact of T-ACASI was most pronounced for reporting of recent use of ‘harder’ drugs. Thus T-ACASI respondents were more likely to report marijuana use in the past month (10.0% vs. 5.7%, crude OR = 1.9, P < 0.001), cocaine use in the past month (2.1% vs. 0.7%, crude 3.2, P < 0.001) and injection drug use in the past five years (1.6% vs. 0.3%, crude OR = 4.8, P < 0.01). Conclusions Telephone survey respondents were more likely to report illicit drug use and one alcohol problem when interviewed by T-ACASI rather than by human telephone interviews. [ABSTRACT FROM AUTHOR]

The National Institute of Diabetes and Digestive Disease (NIDDK) Central Data Repository (CDR) is a web-enabled resource available to researchers and the general public. The CDR warehouses clinical data and study documentation from NIDDK funded research, including such landmark studies as The Diabetes Control and Complications Trial (DCCT, 1983-93) and the Epidemiology of Diabetes Interventions and Complications (EDIC, 1994-present) follow-up study which has been ongoing for more than 20 years. The CDR also houses data from over 7 million biospecimens representing 2 million subjects. To help users explore the vast amount of data stored in the NIDDK CDR, we developed a suite of search mechanisms called the public query tools (PQTs). Five individual tools are available to search data from multiple perspectives: study search, basic search, ontology search, variable summary and sample by condition. PQT enables users to search for information across studies. Users can search for data such as number of subjects, types of biospecimens and disease outcome variables without prior knowledge of the individual studies. This suite of tools will increase the use and maximize the value of the NIDDK data and biospecimen repositories as important resources for the research community. Database URL: https://www.niddkrepository.org/niddk/home.do.

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository makes data and biospecimens from NIDDK-funded research available to the broader scientific community. It thereby facilitates: the testing of new hypotheses without new data or biospecimen collection; pooling data across several studies to increase statistical power; and informative genetic analyses using the Repository's well-curated phenotypic data. This article describes the initial database plan for the Repository and its revision using a simpler model. Among the lessons learned were the trade-offs between the complexity of a database design and the costs in time and money of implementation; the importance of integrating consent documents into the basic design; the crucial need for linkage files that associate biospecimen IDs with the masked subject IDs used in deposited data sets; and the importance of standardized procedures to test the integrity data sets prior to distribution. The Repository is currently tracking 111 ongoing NIDDK-funded studies many of which include genotype data, and it houses over 5 million biospecimens of more than 25 types including serum, plasma, stool, urine, DNA, red blood cells, buffy coat and tissue. Repository resources have supported a range of biochemical, clinical, statistical and genetic research (188 external requests for clinical data and 31 for biospecimens have been approved or are pending). Genetic research has included GWAS, validation studies, development of methods to improve statistical power of GWAS and testing of new statistical methods for genetic research. We anticipate that the future impact of the Repository's resources on biomedical research will be enhanced by (i) cross-listing of Repository biospecimens in additional searchable databases and biobank catalogs; (ii) ongoing deployment of new applications for querying the contents of the Repository; and (iii) increased harmonization of procedures, data collection strategies, questionnaires etc. across both research studies and within the vocabularies used by different repositories.