In the first-stage logistic regressions, we obtained logits of district-specific prevalence of wheeze, asthma, bronchitis, hospitalization for respiratory diseases, persistent cough, and persistent phlegm, adjusted for covariates representing personal, household, and family parameters.
By assuming uncertainties in different households' parameters (e.g. width, length and building materials) to closely simulate real-life conditions, Monte Carlo simulation is performed by repeated sampling of stochastic parameters to generate heterogeneous operating scenarios.
Finally, the likely practical benefits of estimating household transmission parameters in an emerging epidemic need to be clearly established and communicated, and the most effective ways to enhance data collection protocols to allow their rapid estimation need to be identified.
From the French influenza study [10], I obtain maximum likelihood estimates of the within household transmission parameter of ρn = 1.35/n1.0 (which is consistent with the best fit to the Tecumseh data [8] of ρn = 1.27/n0.97).
A wide range of definitions of physical activity have been used in these studies, and none has systematically measured all types (i.e., occupational, household, recreational) and parameters (i.e., duration, frequency, and intensity) of physical activity performed throughout life.
Overall, limited correlation was observed between the socio-economic data and ecological measures of stream health, with the highest being a negative correlation of 0.18 between HBI and the social parameter household size.
First, influenza transmission is known to be concentrated within the household, and thus parameter estimates which ignore this heterogeneity are likely to be frail.
