Systems biology for organotypic cell cultures.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue.

Quantifying the economic value and quality of life impact of earlier influenza vaccination.

Background: Influenza vaccination is administered throughout the influenza disease season, even as late as March. Given such timing, what is the value of vaccinating the population earlier than currently being practiced?

Methods: We used real data on when individuals were vaccinated in Allegheny County, Pennsylvania, and the following 2 models to determine the value of vaccinating individuals earlier (by the end of September, October, and November): Framework for Reconstructing Epidemiological Dynamics (FRED), an agent-based model (ABM), and FluEcon, our influenza economic model that translates cases from the ABM to outcomes and costs [health care and lost productivity costs and quality-adjusted life-years (QALYs)]. We varied the reproductive number (R0) from 1.

Sample and data sharing: observations from a central data repository.

Objectives: From 2003 to 2013, RTI International served as the data repository for the National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK). RTI worked closely with two sample repository partners to build and maintain the Central Repository (CR) that made data and samples available to approved requestors. In this paper, we recap aspects of establishing the mechanism; detail the challenges and limitations of data and sample sharing, and explore the future of resource sharing in light of the evolving environment of research funding.

'What's in the NIDDK CDR?'--public query tools for the NIDDK central data repository.

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.

The NIDDK Central Repository at 8 years--ambition, revision, use and impact.

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.

Including the Group Quarters Population in the US Synthesized Population Database.

In 2005, RTI International researchers developed methods to generate synthesized population data on US households for the US Synthesized Population Database. These data are used in agent-based modeling, which simulates large-scale social networks to test how changes in the behaviors of individuals affect the overall network. Group quarters are residences where individuals live in close proximity and interact frequently.

The role of subway travel in an influenza epidemic: a New York City simulation.

The interactions of people using public transportation in large metropolitan areas may help spread an influenza epidemic. An agent-based model computer simulation of New York City's (NYC's) five boroughs was developed that incorporated subway ridership into a Susceptible-Exposed-Infected-Recovered disease model framework. The model contains a total of 7,847,465 virtual people.

Sharing Research Models: Using Software Engineering Practices for Facilitation.

Increasingly, researchers are turning to computational models to understand the interplay of important variables on systems' behaviors. Although researchers may develop models that meet the needs of their investigation, application limitations-such as nonintuitive user interface features and data input specifications-may limit the sharing of these tools with other research groups. By removing these barriers, other research groups that perform related work can leverage these work products to expedite their own investigations.

The benefits to all of ensuring equal and timely access to influenza vaccines in poor communities.

When influenza vaccines are in short supply, allocating vaccines equitably among different jurisdictions can be challenging. But justice is not the only reason to ensure that poorer counties have the same access to influenza vaccines as do wealthier ones. Using a detailed computer simulation model of the Washington, D.

Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost?: a computational simulation of Pennsylvania.

Background: During the 2009 H1N1 influenza epidemic, policy makers debated over whether, when, and how long to close schools. While closing schools could have reduced influenza transmission thereby preventing cases, deaths, and health care costs, it may also have incurred substantial costs from increased childcare needs and lost productivity by teachers and other school employees.

Methods: A combination of agent-based and Monte Carlo economic simulation modeling was used to determine the cost-benefit of closing schools (vs.

Vaccination deep into a pandemic wave potential mechanisms for a "third wave" and the impact of vaccination.

Background: In December 2009, when the H1N1 influenza pandemic appeared to be subsiding, public health officials and unvaccinated individuals faced the question of whether continued H1N1 immunization was still worthwhile.

Purpose: To delineate what combinations of possible mechanisms could generate a third pandemic wave and then explore whether vaccinating the population at different rates and times would mitigate the wave.

Methods: As part of ongoing work with the Office of the Assistant Secretary for Preparedness and Response at the USDHHS during the H1N1 influenza pandemic, the University of Pittsburgh Models of Infectious Disease Agent Study team employed an agent-based computer simulation model of the Washington DC metropolitan region to delineate what mechanisms could generate a "third pandemic wave" and explored whether vaccinating the population at different rates and times would mitigate the wave.

Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling.

Communicable-disease transmission models are useful for the testing of prevention and intervention strategies. Agent-based models (ABMs) represent a new and important class of the many types of disease transmission models in use. Agent-based disease models benefit from their ability to assign disease transmission probabilities based on characteristics shared by individual agents.

Synthesized Population Databases: A US Geospatial Database for Agent-Based Models.

Agent-based models simulate large-scale social systems. They assign behaviors and activities to "agents" (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses.

Protecting health care workers: a pandemic simulation based on Allegheny County.

Background And Objectives: The Advisory Committee on Immunization Practices has identified health care workers (HCWs) as a priority group to receive influenza vaccine. Although the importance of HCW to the health care system is well understood, the potential role of HCW in transmission during an epidemic has not been clearly established.

Methods: Using a standard SIR (Susceptible-Infected-Recovered) framework similar to previously developed pandemic models, we developed an agent-based model (ABM) of Allegheny County, PA, that incorporates the key health care system features to simulate the spread of an influenza epidemic and its effect on hospital-based HCWs.

Using Influenza-Like Illness Data to Reconstruct an Influenza Outbreak.

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.

Modeling targeted layered containment of an influenza pandemic in the United States.

Planning a response to an outbreak of a pandemic strain of influenza is a high public health priority. Three research groups using different individual-based, stochastic simulation models have examined the consequences of intervention strategies chosen in consultation with U.S.

SAME-GENDER SEX IN THE UNITED STATES IMPACT OF T-ACASI ON PREVALENCE ESTIMATES.

Well-conducted telephone surveys provide an economical means of estimating the prevalence of sexual and reproductive behaviors in a population. There is, however, a nontrivial potential for bias since respondents must report sensitive information to a human interviewer. The National STD and Behavior Measurement Experiment (NSBME) evaluates a new survey technology-telephone audio computer-assisted self-interviewing (T-ACASI)-that eliminates this requirement.

Strategies for mitigating an influenza pandemic.

Development of strategies for mitigating the severity of a new influenza pandemic is now a top global public health priority. Influenza prevention and containment strategies can be considered under the broad categories of antiviral, vaccine and non-pharmaceutical (case isolation, household quarantine, school or workplace closure, restrictions on travel) measures. Mathematical models are powerful tools for exploring this complex landscape of intervention strategies and quantifying the potential costs and benefits of different options.

NIDDK data repository: a central collection of clinical trial data.

Background: The National Institute of Diabetes and Digestive and Kidney Diseases have established central repositories for the collection of DNA, biological samples, and clinical data to be catalogued at a single site. Here we present an overview of the site which stores the clinical data and links to biospecimens.

Description: The NIDDK Data repository is a web-enabled resource cataloguing clinical trial data and supporting information from NIDDK supported studies.

Using Touch Screen Audio-CASI to Obtain Data on Sensitive Topics.

This paper describes a new interview data collection system that uses a laptop personal computer equipped with a touch-sensitive video monitor. The touch-screen-based audio computer-assisted self-interviewing system, or touch screen audio-CASI, enhances the ease of use of conventional audio CASI systems while simultaneously providing the privacy of self-administered questionnaires. We describe touch screen audio-CASI design features and operational characteristics.