20 research outputs found
Characterization of overall severity and individual base fits.
<p><b>a</b> Estimates of <i>R</i><sub>0</sub> versus <i>p</i><sub><i>C</i></sub> for top-50 military installations. The ten installations with the largest number of ILI cases are colored red, installations 11 through 20 are colored blue, and the remaining 30 bases are colored cyan. The grey box denotes the 40 installations with the smallest area in <i>p</i><sub><i>C</i></sub>-<i>R</i><sub>0</sub> space. The histograms along the top and right show the distribution of <i>p</i><sub><i>C</i></sub> and <i>R</i><sub>0</sub> values, respectively. <b>b-e</b> Incidence rates for four military installations (red line), with model fits overlaid (blue line), illustrating: <b>b</b> a two-peak profile; <b>c</b> a single-peak profile; <b>d</b> an anomalously high and narrow profile; and <b>e</b> a complex profile. The green line shows the value of the basic reproduction number and the horizontal dashed grey line marks the critical value of 1.0. The inset in each panel shows the cumulative attack rate for the same time period.</p
Transmissibility and severity of pandemic influenza.
<p><b>a</b> Relationship between the total number of individuals infected and the basic reproductive number <i>R</i><sub>0</sub>. Arrows show the non-linear effect of a 20% reduction in transmission: at lower reproductive numbers, the same intervention is much more effective. <b>b</b> Severity pyramid for infectious disease. The strength of symptoms and ability to detect cases increases with each level in the pyramid. <b>c</b> Conceptual two-dimensional classification of pandemics in terms of basic reproductive number (<i>R</i><sub>0</sub>) and severity (<i>p</i><sub><i>C</i></sub>), illustrating the likely impact of interventions, depending on where the outbreak falls in this parameter space (see main text).</p
Characterizing a model strain of pandemic influenza in real time for a single population.
<p><b>a-c</b> Three frames illustrating stochastic predictions for an outbreak based on parameters that give a typical two-peak profile (such as that of MPZ-92055), but increasing <i>p</i><sub><i>C</i></sub> by about an order of magnitude. The grey lines give individual simulation realizations while the green line shows the ensemble average. The data contributing to the realizations is marked in red. The insets show the evolution of computed <i>p</i><sub><i>C</i></sub>, <i>R</i><sub><i>A</i></sub>, and <i>R</i><sub><i>B</i></sub> as more simulated data are added to the predictions. The red line is our median estimate and the blue lines are the 95% confidence intervals. <b>d-f</b> Analogous frames for a typical single-peaked outbreak such as that of MPZ-23708, but again increasing <i>p</i><sub><i>c</i></sub> by about an order of magnitude.</p
ICD-9 Diagnosis Codes examined in this study.
<p>ICD-9 Diagnosis Codes examined in this study.</p
Percentage of individuals with a sexually transmitted infection by year of service.
<p>Percentage of individuals with a sexually transmitted infection by year of service.</p
Multivariate analysis of factors associated with STI diagnosis during military service.
<p>Multivariate analysis of factors associated with STI diagnosis during military service.</p
Multiple Estimates of Transmissibility for the 2009 Influenza Pandemic Based on Influenza-like-Illness Data from Small US Military Populations
<div><p>Rapidly characterizing the amplitude and variability in transmissibility of novel human influenza strains as they emerge is a key public health priority. However, comparison of early estimates of the basic reproduction number during the 2009 pandemic were challenging because of inconsistent data sources and methods. Here, we define and analyze influenza-like-illness (ILI) case data from 2009–2010 for the 50 largest spatially distinct US military installations (military population defined by zip code, MPZ). We used publicly available data from non-military sources to show that patterns of ILI incidence in many of these MPZs closely followed the pattern of their enclosing civilian population. After characterizing the broad patterns of incidence (e.g. single-peak, double-peak), we defined a parsimonious SIR-like model with two possible values for intrinsic transmissibility across three epochs. We fitted the parameters of this model to data from all 50 MPZs, finding them to be reasonably well clustered with a median (mean) value of 1.39 (1.57) and standard deviation of 0.41. An increasing temporal trend in transmissibility (, p-value: 0.013) during the period of our study was robust to the removal of high transmissibility outliers and to the removal of the smaller 20 MPZs. Our results demonstrate the utility of rapidly available – and consistent – data from multiple populations.</p></div
Incident rates (per 1,000 person-years) of sexually transmitted infections for women and men.
<p>Incident rates (per 1,000 person-years) of sexually transmitted infections for women and men.</p
Crude and Adjusted OR for Hospitalized and Non-hospitalized Cases and Controls.
<p>Note: OR = Odds Ratio.</p><p>*Adjusted for sex, age group, and number of prior vaccinations.</p
Baseline characteristics of participants and lifetime prevalence of at least one sexually transmitted infection.
<p>Baseline characteristics of participants and lifetime prevalence of at least one sexually transmitted infection.</p