Sentence examples for pandemic diffusion from inspiring English sources

A multivariate sensitivity analysis showed that the transmission rate and proportion of susceptibles have a strong impact on the pandemic diffusion.

Using a well-documented metapopulation model incorporating air travel between 52 major world cities, we identified potential influenza pandemic diffusion profiles and examined how the impact of interventions might be affected by this heterogeneity.

So, although we can learn from past experience, current response plans need to consider the possibility that the eventual pandemic diffusion profile may differ substantially geographically and temporally from previous pandemics.

In the present study, we evaluated the diffusion of pandemic influenza in Italy and the impact of various control measures, coupling a global SEIR model with an individual based model.

In the present study, we evaluated the diffusion of pandemic influenza in Italy and the impact of various control measures, coupling a global SEIR model for importation of cases with an individual based model (IBM) describing the Italian epidemic.

To explore the spatial and temporal diffusion trend of pandemic influenza in mainland China, a map of pandemic influenza spread was developed using trend surface analysis, which is a spatial smoothing method that uses polynomials with geographic coordinates, as defined by the central point of each county (12– 12).

A multivariate sensitivity analysis was applied to these 1000 simulations to identify which input parameters had the greatest influence on the temporal and geographical diffusion of the pandemic in the absence of any control measures.

In an early attempt to characterize the spread of the pandemic, Pyle [ 12] presented diffusion patterns of the disease alongside those of other influenza epidemics of the 20th century.

A trend surface on these durations was created in ArcGIS 9.2 (ESRI Inc., Redlands, California) using a second-order trend surface model with a local polynomial method to explore the diffusion patterns of pandemic influenza over time.

Although strategies to contain influenza pandemics are well studied, the characterization and the implications of different geographical and temporal diffusion patterns of the pandemic have been given less attention.

Analyzing diffusion patterns of pandemics is difficult, as it depends upon various factors including place-specific public health responses, social interactions among people, travel patterns within cities and across countries, the natural and built environments, and characteristics of the pathogens themselves [ 5, 23, 24].