| Type: | Package |
| Title: | Quantitative Assessment of Zoonotic Disease Risk |
| Version: | 1.0.0 |
| Description: | Provides quantitative tools for assessing zoonotic disease risk across animal, human, environmental, and transmission interfaces. The package supports exposure and transmission risk estimation, spillover risk assessment, risk scoring, cross-species comparison, transmission-network analysis, Monte Carlo uncertainty simulation, and sensitivity analysis. The One Health framework underlying these assessments is described by World Health Organization, Food and Agriculture Organization of the United Nations, United Nations Environment Programme, and World Organisation for Animal Health (2022) <doi:10.4060/cc2289en>. |
| License: | MIT + file LICENSE |
| URL: | https://github.com/vinodhpmd/ZooRisk |
| BugReports: | https://github.com/vinodhpmd/ZooRisk/issues |
| Encoding: | UTF-8 |
| Suggests: | igraph, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| Config/roxygen2/version: | 8.1.0 |
| NeedsCompilation: | no |
| Packaged: | 2026-09-14 16:48:26 UTC; m |
| Author: | Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut] |
| Maintainer: | Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-09-24 13:50:18 UTC |
ZooRisk: Quantitative Assessment of Zoonotic Disease Risk
Description
Tools for quantitative assessment of zoonotic disease risk across animal, human, environmental, and transmission interfaces.
Author(s)
Maintainer: Vinodhkumar Obli Rajendran vinodhkumar.rajendran@gmail.com
Authors:
Vinodhkumar Obli Rajendran vinodhkumar.rajendran@gmail.com
Keerthi Aaradhana vkeerthi1817@gmail.com
See Also
Useful links:
Compare risk across host species
Description
Compare risk across host species
Usage
cross_species(species, risk)
Arguments
species |
Character species names. |
risk |
Numeric risk values between 0 and 1. |
Value
A ranked data frame.
Exposure risk
Description
Exposure risk
Usage
exposure_risk(prevalence, exposure)
Arguments
prevalence |
Probability or prevalence of pathogen occurrence. |
exposure |
Probability of exposure. |
Value
Numeric exposure-associated risk.
Calculate host-specific risk
Description
Calculate host-specific risk
Usage
host_risk(prevalence, exposure)
Arguments
prevalence |
Prevalence. |
exposure |
Exposure probability. |
Value
Numeric host risk.
Summarize Monte Carlo risk
Description
Summarizes the distribution of zoonotic risk obtained from
risk_simulate().
Usage
monte_carlo_risk(x, probs = c(0.025, 0.5, 0.975))
Arguments
x |
A data frame returned by |
probs |
Probability levels used to calculate the lower and upper quantiles. |
Value
A data frame containing the mean, median, lower, and upper risk estimates.
Examples
sim <- risk_simulate(
prevalence = c(0.1, 0.3),
exposure = c(0.2, 0.6),
transmission = c(0.3, 0.8),
n_sim = 100
)
monte_carlo_risk(sim)
Calculate transmission network centrality
Description
Calculates node-level centrality measures for a transmission network.
When the optional igraph package is available, degree,
betweenness, and closeness centrality are calculated. Otherwise,
degree is calculated from the network structure and the other
measures are returned as NA.
Usage
network_centrality(x)
Arguments
x |
A transmission network created by |
Value
A data frame containing node-level network centrality measures.
Summarize transmission network connectivity
Description
Calculates node-level connectivity in a transmission network using in-degree, out-degree, and total degree. Higher total degree indicates greater network connectivity and does not itself represent epidemiological risk or probability of transmission.
Usage
network_risk(x)
Arguments
x |
A transmission network created by |
Value
A data frame containing the node identifier, out-degree, in-degree, and total degree, ordered by decreasing total degree.
Summarize One Health risk components
Description
Summarize One Health risk components
Usage
onehealth_summary(animal, human, environment)
Arguments
animal, human, environment |
Numeric risk components between 0 and 1. |
Value
A data frame.
Plot a transmission network
Description
Plots a transmission network using igraph when available. Otherwise, a base R degree plot is produced.
Usage
plot_network(x, ...)
Arguments
x |
A transmission network created by |
... |
Graphical arguments passed to the plotting method. |
Value
Invisibly returns x.
Plot a zoonotic risk score
Description
Plot a zoonotic risk score
Usage
plot_risk(x, ...)
Arguments
x |
Numeric risk score or |
... |
Graphical arguments. |
Value
Invisibly returns x.
Plot a two-dimensional risk matrix
Description
Plot a two-dimensional risk matrix
Usage
plot_risk_matrix(x, y = NULL, ...)
Arguments
x |
Numeric risk values. |
y |
Optional second risk dimension. |
... |
Graphical arguments. |
Value
Invisibly returns x.
Print a ZooRisk result
Description
Prints a quantitative zoonotic risk result, including the overall multiplicative risk estimate and its component probabilities.
Usage
## S3 method for class 'zoorisk'
print(x, ...)
Arguments
x |
A |
... |
Ignored. |
Value
Invisibly returns the original zoorisk object of class
zoorisk. The object contains the overall risk estimate,
component probabilities, and the model specification.
Calculate component contributions
Description
Calculate component contributions
Usage
risk_contribution(probabilities, weights = NULL)
Arguments
probabilities |
Numeric component probabilities. |
weights |
Optional weights. |
Value
Data frame of normalized contributions.
Classify risk into qualitative categories
Description
Classify risk into qualitative categories
Usage
risk_matrix(x, breaks = c(0, 0.25, 0.5, 0.75, 1))
Arguments
x |
Numeric risk scores between 0 and 1. |
breaks |
Five increasing cut points from 0 to 1. |
Value
A factor of risk categories.
Rank zoonotic risks
Description
Rank zoonotic risks
Usage
risk_rank(x, decreasing = TRUE)
Arguments
x |
Numeric risk scores. |
decreasing |
Sort from highest to lowest when TRUE. |
Value
Integer ranks.
Calculate a weighted zoonotic risk score
Description
Calculate a weighted zoonotic risk score
Usage
risk_score(probabilities, weights = NULL)
Arguments
probabilities |
Numeric probabilities between 0 and 1. |
weights |
Optional non-negative weights. |
Value
A numeric risk score between 0 and 1.
Simulate zoonotic risk under uncertainty
Description
Generates random combinations of zoonotic risk components within user-specified bounds and calculates the resulting risk.
Usage
risk_simulate(
prevalence,
exposure,
transmission,
susceptibility = c(1, 1),
n_sim = 10000,
seed = NULL
)
Arguments
prevalence |
Numeric vector of length two giving the lower and upper bounds for prevalence. |
exposure |
Numeric vector of length two giving the lower and upper bounds for exposure. |
transmission |
Numeric vector of length two giving the lower and upper bounds for transmission. |
susceptibility |
Numeric vector of length two giving the lower and upper bounds for susceptibility. |
n_sim |
Number of simulations. |
seed |
Optional random seed. |
Value
A data frame containing simulated prevalence, exposure, transmission, susceptibility, and zoonotic risk values.
Examples
set.seed(123)
sim <- risk_simulate(
prevalence = c(0.1, 0.3),
exposure = c(0.2, 0.6),
transmission = c(0.3, 0.8),
susceptibility = c(0.5, 1),
n_sim = 100
)
head(sim)
One-at-a-time sensitivity analysis
Description
Evaluates the effect of fractional changes to each risk component while holding the other components at their baseline values.
Usage
sensitivity_risk(base, changes = c(-0.2, 0.2))
Arguments
base |
Named numeric vector of baseline risk components. Values must be between 0 and 1. |
changes |
Numeric vector of fractional changes applied to each component individually. |
Value
A data frame containing the component and simulated risk
values for each specified change. The baseline risk is returned
as the baseline_risk attribute.
Examples
base <- c(
prevalence = 0.2,
exposure = 0.5,
transmission = 0.6,
susceptibility = 0.8
)
sensitivity_risk(base)
Spillover risk
Description
Spillover risk
Usage
spillover_risk(prevalence, exposure, transmission, susceptibility = 1)
Arguments
prevalence |
Probability or prevalence in the reservoir. |
exposure |
Probability of relevant exposure. |
transmission |
Probability of transmission given exposure. |
susceptibility |
Probability of infection given transmission. |
Value
Numeric spillover risk.
Summarize a ZooRisk result
Description
Summarize a ZooRisk result
Usage
## S3 method for class 'zoorisk'
summary(object, ...)
Arguments
object |
A |
... |
Ignored. |
Value
A data frame.
Construct a transmission network
Description
Constructs an edge-list representation of a transmission network.
Usage
transmission_network(from, to, directed = TRUE)
Arguments
from |
Source node identifiers. |
to |
Destination node identifiers. |
directed |
Logical; whether edges are directed. |
Value
An edge-list data frame of class zoorisk_network.
Transmission risk
Description
Transmission risk
Usage
transmission_risk(exposure, transmission)
Arguments
exposure |
Probability of exposure. |
transmission |
Probability of transmission given exposure. |
Value
Numeric transmission-associated risk.
Quantitative zoonotic disease risk
Description
Calculates a transparent multiplicative risk estimate.
Usage
zoonotic_risk(prevalence, exposure, transmission, susceptibility)
Arguments
prevalence |
Probability or prevalence of pathogen occurrence. |
exposure |
Probability of relevant exposure. |
transmission |
Probability of transmission given exposure. |
susceptibility |
Probability of infection given transmission. |
Value
An object of class zoorisk.