Analysis of Virulence
anovir: Analysis of Virulence
Average longevity: estimate for infected hosts
Average longevity: estimate for uninfected hosts
Checks data are correctly described for models
Approximate 95% confidence intervals for virulence
Expected time of death: infected hosts
Expected time of death: uninfected hosts
Negative log-likelihood function: basic model
Negative log-likelihood function: basic model on logscale
Negative log-likelihood function: control data only
Negative log-likelihood function: exposed-infected
Negative log-likelihood function: frailty
Negative log-likelihood function: correlated frailty model
Negative log-likelihood function: frailty variables on logscale
Negative log-likelihood function: frailty shared
Negative log-likelihood function: nll proportional virulence
Negative log-likelihood function: recovery model
Negative log-likelihood function: recovery model, no background mortal...
Negative log-likelihood function: two observed subpopulations of infec...
Negative log-likelihood function: two unobserved subpopulations of inf...
Function simulating survival data for nll_basic
Epidemiological population dynamics models traditionally define a pathogen's virulence as the increase in the per capita rate of mortality of infected hosts due to infection. This package provides functions allowing virulence to be estimated by maximum likelihood techniques. The approach is based on the analysis of relative survival comparing survival in matching cohorts of infected vs. uninfected hosts (Agnew 2019) <doi:10.1101/530709>.