Package: anovir 0.1.0

anovir: Analysis of Virulence

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>.

Authors:Philip Agnew [aut, cre], Jimmy Lopez [aut]

anovir_0.1.0.tar.gz
anovir_0.1.0.zip(r-4.7)anovir_0.1.0.zip(r-4.6)anovir_0.1.0.zip(r-4.5)
anovir_0.1.0.tgz(r-4.6-any)anovir_0.1.0.tgz(r-4.5-any)
anovir_0.1.0.tar.gz(r-4.7-any)anovir_0.1.0.tar.gz(r-4.6-any)
anovir_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
anovir/json (API)

# Install 'anovir' in R:
install.packages('anovir', repos = c('https://philipagnew.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.53 score 31 scripts 248 downloads 20 exports 7 dependencies

Last updated from:80ffca0c6b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK211
linux-release-x86_64OK151
macos-release-arm64OK131
macos-oldrel-arm64OK155
windows-develOK126
windows-releaseOK113
windows-oldrelOK100
wasm-releaseOK98

Exports:av_long_infectedav_long_uninfectedcheck_dataconf_ints_virulenceetd_infectedetd_uninfectednll_basicnll_basic_logscalenll_controlsnll_exposed_infectednll_frailtynll_frailty_correlatednll_frailty_logscalenll_frailty_sharednll_proportional_virulencenll_recoverynll_recovery_IInll_two_inf_subpops_obsnll_two_inf_subpops_unobssim_data_nll_basic

Dependencies:bbmlebdsmatrixlatticeMASSMatrixmvtnormnumDeriv

Confidence intervals
The delta method | Setting confidence interval bounds | Worked example: 1 random variable | Worked example: 2 random variables | Part I: estimate parameter variables | Part II: calculate confidence intervals | Part III: compare results with those of conf_ints_virulence | Worked example: 3 random variables | Confidence intervals back-calculated from nll_basic_logscale | References
Rendered fromconfidence_intervals.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Data format
Introduction | General format required | Specific formats | nll_two_inf_subpops_obs | nll_recovery | nll_recovery_II
Rendered fromdata_format.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Introduction
Population dynamics | Empirical setting | Survival functions | Relative survival | Relative survival and virulence | References
Rendered fromIntroduction.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Likelihood functions described
Introduction | Log-likelihood expressions: no censoring | Log-likelihood expressions: with censoring | Log-likelihood expressions: relative survival, with censoring | Likelihood functions in this package | The functions: | nll_basic | nll_basic_logscale | nll_controls | nll_exposed_infected | nll_frailty | nll_frailty_correlated | nll_frailty_logscale | nll_frailty_shared | nll_proportional_virulence | nll_recovery | nll_recovery_II | nll_two_inf_subpops_obs | nll_two_inf_subpops_unobs | Back to top | References
Rendered fromnll_functions.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Modifying nll functions
Introduction | Modifying nll_basic | Default: 4 variables to estimate | Modified: 5 variables to estimate | References
Rendered fromnll_functions_modifying.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Probability distribution functions
Parameters | Weibull distribution | Gumbel distribution | Fréchet distribution | Exponential distribution | back to top | Notes | Linear transformations of cumulative survival
Rendered fromprobability_distributions.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Starting values
Introduction | Linear regression of transformed cumulative survival data | Non-linear regression of cumulative survival data | Limitations to regression of cumulative survival data | Example | Linear regressions | Non-linear regressions | Maximum likelihood estimation | Compare models | References
Rendered fromstarting_values.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

The exponential distribution
Introduction | Example: background rate of mortality constant | References
Rendered fromthe_exponential_distribution.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Using nll functions
Introduciton | Two-step preparation | Step #1 | Step #2 | References
Rendered fromnll_functions_using.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Worked examples I
Introduction | S06. Analysis of Blanford et al. data (i) | S08. Analysis of the Lorenz & Koella data | S10. Analysis of Blanford et al. data (ii) | S11. Analysis of Parker et al. data | S12. Exposed-but-uninfected hosts model | S14. Lorenz & Koella pooled data | S15. Shared and correlated frailty models | References
Rendered fromworked_examples_I.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Worked examples II
Extending nll_proportional_virulence to multiple treatments | Modifying nll_basic_logscale | References
Rendered fromworked_examples_II.Rmdusingknitr::rmarkdown

Last update: 2020-10-24
Started: 2020-10-24

Readme and manuals

Help Manual

Help pageTopics
anovir: Analysis of Virulenceanovir-package anovir
Average longevity: estimate for infected hostsav_long_infected
Average longevity: estimate for uninfected hostsav_long_uninfected
Checks data are correctly described for modelscheck_data
Approximate 95% confidence intervals for virulenceconf_ints_virulence
Full data from Blanford et al (2012)data_blanford
A subset of data from Lorenz & Koella (2011)data_lorenz
Full data from Parker et al (2014)data_parker
Expected time of death: infected hostsetd_infected
Expected time of death: uninfected hostsetd_uninfected
Negative log-likelihood function: basic modelnll_basic
Negative log-likelihood function: basic model on logscalenll_basic_logscale
Negative log-likelihood function: control data onlynll_controls
Negative log-likelihood function: exposed-infectednll_exposed_infected
Negative log-likelihood function: frailtynll_frailty
Negative log-likelihood function: correlated frailty modelnll_frailty_correlated
Negative log-likelihood function: frailty variables on logscalenll_frailty_logscale
Negative log-likelihood function: frailty sharednll_frailty_shared
Negative log-likelihood function: nll proportional virulencenll_proportional_virulence
Negative log-likelihood function: recovery modelnll_recovery
Negative log-likelihood function: recovery model, no background mortalitynll_recovery_II
Negative log-likelihood function: two observed subpopulations of infected hostsnll_two_inf_subpops_obs
Negative log-likelihood function: two unobserved subpopulations of infected hostsnll_two_inf_subpops_unobs
Simulated recovery datarecovery_data
Simulated recovery data, with no background mortalityrecovery_data_II
Function simulating survival data for nll_basicsim_data_nll_basic