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1.  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. 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.
Electronic supplementary material
The online version of this article (doi:10.1007/s11524-011-9603-4) contains supplementary material, which is available to authorized users.
doi:10.1007/s11524-011-9603-4
PMCID: PMC3191213  PMID: 21826584
Computer simulation; Infectious disease transmission; Human influenza; Subway travel; Agent-based model; Pandemic
2.  Intercenter Differences in Bronchopulmonary Dysplasia or Death Among Very Low Birth Weight Infants 
Pediatrics  2010;127(1):e106-e116.
OBJECTIVES:
To determine (1) the magnitude of clustering of bronchopulmonary dysplasia (36 weeks) or death (the outcome) across centers of the Eunice Kennedy Shriver National Institute of Child and Human Development National Research Network, (2) the infant-level variables associated with the outcome and estimate their clustering, and (3) the center-specific practices associated with the differences and build predictive models.
METHODS:
Data on neonates with a birth weight of <1250 g from the cluster-randomized benchmarking trial were used to determine the magnitude of clustering of the outcome according to alternating logistic regression by using pairwise odds ratio and predictive modeling. Clinical variables associated with the outcome were identified by using multivariate analysis. The magnitude of clustering was then evaluated after correction for infant-level variables. Predictive models were developed by using center-specific and infant-level variables for data from 2001 2004 and projected to 2006.
RESULTS:
In 2001–2004, clustering of bronchopulmonary dysplasia/death was significant (pairwise odds ratio: 1.3; P < .001) and increased in 2006 (pairwise odds ratio: 1.6; overall incidence: 52%; range across centers: 32%–74%); center rates were relatively stable over time. Variables that varied according to center and were associated with increased risk of outcome included lower body temperature at NICU admission, use of prophylactic indomethacin, specific drug therapy on day 1, and lack of endotracheal intubation. Center differences remained significant even after correction for clustered variables.
CONCLUSION:
Bronchopulmonary dysplasia/death rates demonstrated moderate clustering according to center. Clinical variables associated with the outcome were also clustered. Center differences after correction of clustered variables indicate presence of as-yet unmeasured center variables.
doi:10.1542/peds.2010-0648
PMCID: PMC3010091  PMID: 21149431
logistic models; infant; premature; predictive value of tests; clustering
3.  Mass Commuting and Influenza Vaccination Prevalence in New York City: Protection in a Mixing Environment 
Epidemics  2010;2(4):183-188.
Objective
Assess influenza vaccination among commuters using mass transit in New York City (NYC).
Methods
We used the 2006 NYC Community Health Survey (CHS) to analyze the prevalence of influenza immunization by commuting behaviors and to understand what socioeconomic and geographic factors may explain any differences found.
Results
Vaccination prevalence is significantly lower for New Yorkers who commute on public transportation compared to other New Yorkers. This difference is largely attenuated after adjusting for socio-demographic characteristics and neighborhood of residence.
Conclusions
The analysis identified a low prevalence of immunization among commuters, and given the transmissibility in that setting, targeting commuters for vaccination campaigns may impede influenza spread.
doi:10.1016/j.epidem.2010.07.002
PMCID: PMC3014620  PMID: 21218159

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