FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

BACKGROUND: Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels. RESULTS: FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations. CONCLUSIONS: State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

School closure as an influenza mitigation strategy: how variations in legal authority and plan criteria can alter the impact.

BACKGROUND: States' pandemic influenza plans and school closure statutes are intended to guide state and local officials, but most faced a great deal of uncertainty during the 2009 influenza H1N1 epidemic. Questions remained about whether, when, and for how long to close schools and about which agencies and officials had legal authority over school closures. METHODS: This study began with analysis of states' school-closure statutes and pandemic influenza plans to identify the variations among them. An agent-based model of one state was used to represent as constants a population's demographics, commuting patterns, work and school attendance, and community mixing patterns while repeated simulations explored the effects of variations in school closure authority, duration, closure thresholds, and reopening criteria. RESULTS: The results show no basis on which to justify statewide rather than school-specific or community-specific authority for school closures. Nor do these simulations offer evidence to require school closures promptly at the earliest stage of an epidemic. More important are criteria based on monitoring of local case incidence and on authority to sustain closure periods sufficiently to achieve epidemic mitigation. CONCLUSIONS: This agent-based simulation suggests several ways to improve statutes and influenza plans. First, school closure should remain available to state and local authorities as an influenza mitigation strategy. Second, influenza plans need not necessarily specify the threshold for school closures but should clearly define provisions for early and ongoing local monitoring. Finally, school closure authority may be exercised at the statewide or local level, so long as decisions are informed by monitoring incidence in local communities and schools.

Identification of quantitative trait loci underlying proteome variation in human lymphoblastoid cells.

Population-based variability in protein expression patterns, especially in humans, is often observed but poorly understood. Moreover, very little is known about how interindividual genetic variation contributes to protein expression patterns. To begin to address this, we describe elements of technical and biological variations contributing to expression of 544 proteins in a population of 24 individual human lymphoblastoid cell lines that have been extensively genotyped as part of the International HapMap Project. We determined that expression levels of 10% of the proteins were tightly correlated to cell doubling rates. Using the publicly available genotypes for these lymphoblastoid cell lines, we applied a genetic association approach to identify quantitative trait loci associated with protein expression variation. Results identified 24 protein forms corresponding to 15 proteins for which genetic elements were responsible for >50% of the expression variation. The genetic variation associated with protein expression levels were located in cis with the gene coding for the transcript of the protein for 19 of these protein forms. Four of the genetic elements identified were coding non-synonymous single nucleotide polymorphisms that resulted in migration pattern changes in the two-dimensional gel. This is the first description of large scale proteomics analysis demonstrating the direct relationship between genome and proteome variations in human cells.

Improving epidemiological surveys of sexual behaviour conducted by telephone.

BACKGROUND: This study assesses the impact of Telephone Audio Computer-Assisted Self-Interviewing (T-ACASI) on the reporting of sensitive (mainly heterosexual) behaviours. METHODS: A randomized experiment was embedded in a telephone survey that drew probability samples of the populations of the USA (N = 1543) and Baltimore city (N = 744). Respondents were randomly assigned to have questions asked either by a T-ACASI computer or by a human telephone interviewer. RESULTS: Compared with interviewer-administered telephone surveys, T-ACASI obtained more frequent reporting of a range of mainly heterosexual behaviours that were presumed to be sensitive, including recency of anal sex [adjusted odds ratio (A-OR) = 2.00, P < 0.001), sex during menstrual period (A-OR = 1.49, P < 0.001), giving oral sex (A-OR = 1.40, P = 0.001) and receiving oral sex (A-OR = 1.36, P = 0.002), and sexual difficulties for the respondent (A-OR = 1.45, P = 0.034) and their main sex partner (A-OR = 1.48, P = 0.0). T-ACASI also obtained less frequent reporting that respondent had a 'main sex partner' (A-OR = 0.56, P = 0.011) and discussed contraception prior to first sex with that sex partner (A-OR = 0.82, P = 0.094). For both males and females, T-ACASI obtained more frequent reports of first vaginal sex occurring at early ages (before ages 12 through 15). 'For males only', T-ACASI also elicited more frequent reports that first vaginal sex had 'not' occurred at later ages (i.e. by ages 20 through 24). CONCLUSION: T-ACASI increases the likelihood that survey respondents will report sensitive heterosexual behaviours.

The model repository of the models of infectious disease agent study.

The model repository (MREP) is a relational database management system (RDBMS) developed under the auspices of models of infectious disease agent study (MIDAS). The purpose of the MREP is to organize and catalog the models, results, and suggestions for using the MIDAS and to store them in a way to allow users to run models from an access-controlled disease MREP. The MREP contains source and object code of disease models developed by infectious disease modelers and tested in a production environment. Different versions of models used to describe various aspects of the same disease are housed in the repository. Models are linked to their developers and different versions of the codes are tied to Subversion, a version control tool. An additional element of the MREP will be to house, manage, and control access to a disease model results warehouse, which consists of output generated by the models contained in the MREP. The result tables and files are linked to the version of the model and the input parameters that collectively generated the results. The result tables are warehoused in a relational database that permits them to be easily identified, categorized, and downloaded.

T-ACASI reduces bias in STD measurements: the National STD and Behavior Measurement Experiment.

BACKGROUND: Although telephone surveys provide an economical method for assessing patterns of diagnosed sexually transmitted diseases (STDs) and STD-related behaviors in populations, the requirement that respondents report such information to human telephone interviewers introduces an opportunity for substantial reporting bias. Telephone computer-assisted self-interviewing (T-ACASI) surveys substitute a computer for human interviewers when asking sensitive questions. METHODS: A randomized experiment was embedded in a telephone survey that drew probability samples of the populations of the United States (N = 1543) and Baltimore city (N = 744). Respondents were randomly assigned to have sensitive questions asked either by a T-ACASI computer or by a human telephone interviewer. RESULTS: Respondents interviewed by a T-ACASI computer were more likely to report STD symptoms [dysuria, genital sores, genital discharge, and genital warts; adjusted odds ratios (ORs) = 1.5-2.8] and a diagnosis of gonococcal or chlamydial infection during the past year (adjusted ORs = 3.6 and 6.1). T-ACASI respondents with a main sex partner in the past year were more likely to report that their partner has had an STD (adjusted OR = 2.4). For some measurements, the impact of T-ACASI was strongest among younger and less-educated respondents. When sampling weights were applied to project National STD and Behavior Measurement Experiment results to the populations of the United States and Baltimore, we found that reliance on data obtained by human interviewers would underestimate the annual incidence of chlamydial and gonococcal infections in these populations by factors of 2.4 to 9.7. CONCLUSIONS: Compared with human telephone interviewers, T-ACASI surveys obtain increased reporting of STD symptoms, infections, and STD-related behaviors.

Untreated gonococcal and chlamydial infection in a probability sample of adults.

CONTEXT: The prevalence and distribution of gonococcal and chlamydial infections in the general population are poorly understood. Development of nucleic acid amplification tests, such as the ligase chain reaction assay, provides new opportunities to estimate the prevalence of untreated infections in the population. OBJECTIVE: To estimate the overall prevalence of untreated gonococcal and chlamydial infections and to describe patterns of infection within specific demographic subgroups of the young adult population in Baltimore, Md. DESIGN AND SETTING: Cross-sectional behavioral survey based on a probability sample of Baltimore households with collection of urine specimens between January 1997 and September 1998. PARTICIPANTS: A total of 728 adults aged 18 to 35 years completed the interview portion of the study, and 579 of these respondents also provided a urine specimen adequate for testing. MAIN OUTCOME MEASURE: Prevalence of untreated infection, as measured by the percentage of specimens testing positive for gonococcal and chlamydial infection by ligase chain reaction, weighted to reflect variations in probabilities of sample selection from the population. Alternate estimates of the prevalence of recent treated infection were derived from clinically diagnosed cases reported to the Baltimore City Health Department and by diagnoses reported by participants in the survey. RESULTS: An estimated 5.3% (SE, 1.4%) of the population aged 18 to 35 years has an untreated gonococcal infection, and 3.0% (SE, 0.8%) is estimated to have an untreated chlamydial infection. While 7.9% (SE, 1.6%) of the population is estimated to have either an untreated gonococcal or chlamydial infection, estimated prevalence is substantially higher among black women (15.0%; SE, 3.7%). Few participants with untreated infections reported dysuria or discharge during the 6 months preceding testing. The estimated number of untreated gonococcal infections in the population (9241; SE, 2441) substantially exceeds both the number of such infections diagnosed among Baltimore adults aged 18 to 35 years and reported to the Baltimore City Health Department during 1998 (4566), and the estimated number of diagnoses derived using participants' reports for the 12 months prior to the survey (4708 [SE, 1918] to 5231 [SE, 2092]). The estimated number of untreated chlamydial infections (5231; SE, 1395) is also greater than the number of cases reported to the health department in 1998 (3664) but is slightly less than the estimated number of diagnoses derived using participants' reports of chlamydial infections diagnosed during the 12 months prior to the survey (5580 [SE, 1918] to 6975 [SE, 2441]). CONCLUSION: In 1997-1998, the estimated number of undiagnosed gonococcal and chlamydial infections prevalent in the population of Baltimore adults aged 18 to 35 years approached or exceeded the number of infections that were diagnosed and treated annually.