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. Each person resides in one of the five boroughs of NYC and has a set of socio-demographic characteristics and daily behaviors that include age, sex, employment status, income, occupation, and household location and membership. The model simulates the interactions of subway riders with their workplaces, schools, households, and community activities. It was calibrated using historical data from the 1957-1958 influenza pandemics and from NYC travel surveys. The surveys were necessary to enable inclusion of subway riders into the model. The model results estimate that if influenza did occur in NYC with the characteristics of the 1957-1958 pandemic, 4% of transmissions would occur on the subway. This suggests that interventions targeted at subway riders would be relatively ineffective in containing the epidemic. A number of hypothetical examples demonstrate this feature. This information could prove useful to public health officials planning responses to epidemics.

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. RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants. For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models. Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.

Objectives: To examine whether audio computer assisted survey interviewing (ACASI) influenced responses to sensitive HIV risk behaviour questions, relative to interviewer administration of those questions (IAQ), among patients attending a sexually transmitted infection (STI) clinic and whether the impact of interview mode on reporting of risk behaviours was homogeneous across subgroups of patients (defined by age, sex, and previous STI clinic experience). Methods: 1350 clinic patients were assigned to complete a detailed behavioural survey on sexual risk practices, previous STIs and symptoms, condom use, and drug and alcohol use using either ACASI or IAQ. Results: Respondents assigned to ACASI were more likely to report recent risk behaviours such as sex without a condom in the past 24 hours (adjusted OR = 1.9), anal sex (adjusted OR = 2.0), and one or more new partners in the past 6 months (adjusted OR = 1.5) compared to those interviewed by IAQ. The impact of ACASI varied by sex but, contrary to expectations, not by whether the patient had previously visited an STI clinic. Mode of survey administration made little difference within this population in reports of STI knowledge, previous STIs, STI symptoms, or illicit drug use. Conclusion: ACASI provides a useful tool for improving the quality of behavioural data in clinical environments.

Please cite this paper as: Cooley et al. (2010) Protecting health care workers: a pandemic simulation based on Allegheny County. Influenza and Other Respiratory Viruses 4(2), 61–72. 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. Findings  Our simulation runs found the secondary attack rate among unprotected HCWs to be approximately 60% higher (54·3%) as that of all adults (34·1%), which would result in substantial absenteeism and additional risk to HCW families. Understanding how a pandemic may affect HCWs, who must be available to treat infected patients as well as patients with other medical conditions, is crucial to policy makers’ and hospital administrators’ preparedness planning.

A substantial proportion of positive NAAT results for chlamydial infection may be of lower transmissibility and may not persist after a short follow-up. The long-term health effects of some positive NAAT are uncertain.