Modeling Respiratory Syncytial Virus Adult Vaccination in the United States With a Dynamic Transmission Model.

BACKGROUND: Respiratory syncytial virus (RSV) is shown to cause substantial morbidity, hospitalization, and mortality in infants and older adults. Population-level modeling of RSV allows to estimate the full burden of disease and the potential epidemiological impact of novel prophylactics. METHODS: We modeled the RSV epidemiology in the United States across all ages using a deterministic compartmental transmission model. Population-level symptomatic RSV acute respiratory tract infection (ARI) cases were projected across different natural history scenarios with and without vaccination of adults aged ≥60 years. The impact of vaccine efficacy against ARIs, infectiousness and vaccine coverage on ARI incidence were assessed. The impact on medical attendance, hospitalization, complications, death, and other outcomes was also derived. RESULTS: Without a vaccine, we project 17.5-22.6 million symptomatic RSV ARI cases annually in adults aged ≥18 years in the US, with 3.6-4.8 million/year occurring in adults aged ≥60 years. Modeling indicates that up to 2.0 million symptomatic RSV-ARI cases could be prevented annually in ≥60-year-olds with a hypothetical vaccine (70% vaccine efficacy against symptomatic ARI and 60% vaccine coverage) and that up to 0.69 million/year could be prevented in the nonvaccinated population, assuming 50% vaccine impact on infectiousness. CONCLUSIONS: The model provides estimated burden of RSV in the US across all age groups, with substantial burden projected specifically in older adults. Vaccination of adults aged ≥60 years could significantly reduce the burden of disease in this population, with additional indirect effect in adults aged <60 years due to reduced transmissibility.

A basic dynamic transmission model of Staphylococcus aureus in the US population--ERRATUM.

doi: http://dx.doi.org/10.1017/S0950268813001106. Published online: 23 May 2013. In the above-mentioned article [1] the y axis in Figure 3a is incorrect. The correct version is given below. US pop. growth (estimated) (×108)

A basic dynamic transmission model of Staphylococcus aureus in the US population.

We present a basic mathematical model of Staphylococcus aureus transmission in the USA based on natural history of infection and nationally representative data. We employed a Susceptible-Colonized-Infected-Recovered-Susceptible compartmental modelling framework with two different phenotypes of S. aureus: methicillin-susceptible (MSSA) and methicillin-resistant (MRSA). The model is dynamic and accounts for the US population growth. For model calibration/validation, we used published 1999-2005 S. aureus infection data in conjunction with the 2001-2004 National Health and Nutrition Examination Survey colonization data. Baseline model projections illustrated how MRSA might continue to expand and gradually replace MSSA over time, in the absence of intervention, if there is strong competition for colonization. The model-based estimate of the basic reproduction number (R0) highlights the need for infection control. We illustrate the potential population-level impact of intervention with a hypothetical S. aureus vaccination component.

A mathematical model of the indirect effects of rotavirus vaccination.

Rotavirus (RV) infections progressively confer natural immunity against subsequent infection. Similarly to natural infection, vaccination with a live attenuated vaccine potentially reduces RV transmission and induces herd protection. A mathematical transmission model was developed to project the impact of a vaccination programme on the incidence of RV infection and disease for five countries in the European Union. With vaccination coverage rates of 70%, 90% and 95% the model predicted that, in addition to the direct effect of vaccination, herd protection induced a reduction in RV-related gastroenteritis (GE) incidence of 25%, 22% and 20%, respectively, for RV-GE of any severity, and of 19%, 15%, and 13%, respectively, for moderate-to-severe RV-GE, 5 years after implementation of a vaccination programme.

Aspect graphs for visual recognition of three-dimensional objects.

Visual representation of three-dimensional (3-D) objects in our environment is a crucial question, for human as well as for machine vision. Some basics are reviewed of a viewer-centred model of 3-D objects, aspect graphs, which represents a 3-D object by all its topologically stable visible image contours (its aspects) and by the transitions between stable image contours (the visual events). This representation takes only geometrical information about discontinuities in depth and in surface orientation into account, and other clues, such as shadows, markings, texture, etc, are disregarded. Mathematical results give some insight into the relationships between the geometry of a 3-D object and the aspect of its image contours, the techniques used to compute an aspect graph effectively, and the state of the art of this type of model in computer vision. Current research is reviewed on viewer-centred representation in cognitive science that seems to indicate that aspect graphs could also have some relevance for human vision.