Optimal Channel Networks

Generate and analyze Optimal Channel Networks (OCNs): oriented spanning trees reproducing all scaling features characteristic of real, natural river networks. As such, they can be used in a variety of numerical experiments in the fields of hydrology, ecology and epidemiology. See Carraro et al. (2020) for a presentation of the package; Rinaldo et al. (2014) for a theoretical overview on the OCN concept; Furrer and Sain (2010) for the construct used.

Functions to Interact with the 'FAIR Data Pipeline'

R implementation of the 'FAIR Data Pipeline API'. The 'FAIR Data Pipeline' is intended to enable tracking of provenance of FAIR (findable, accessible and interoperable) data used in epidemiological modelling.

Prepare, Analyze, and Visualize Covid-19 Wastewater Data

Intended to make the process of analyzing epidemiological wastewater data easier and more insightful. Includes tools for preparing, analyzing, and visualizing data. It additionally includes Wisconsin's Covid19 data.

Combining Different Spatial Datasets in Cancer Risk Estimation

We propose a novel two-step procedure to combine epidemiological data obtained from diverse sources with the aim to quantify risk factors affecting the probability that an individual develops certain disease such as cancer. See Hui Huang, Xiaomei Ma, Rasmus Waagepetersen, Theodore R. Holford, Rong Wang, Harvey Risch, Lloyd Mueller & Yongtao Guan (2014) A New Estimation Approach for Combining Epidemiological Data From Multiple Sources, Journal of the American Statistical Association, 109:505, 11-23, .

A 'shiny' Wrapper of the R Package 'epiworldR'

R 'shiny' web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR' (Meyer et al., 2023) . Some of the main features of the package include the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.

Multi Calculator to Compute Scores of Adherence to Mediterranean Diet

Multi Calculator of different scores to measure adherence to Mediterranean Diet, to compute them in nutriepidemiological data. Additionally, a sample dataset of this kind of data is provided, and some other minor tools useful in epidemiological studies.

SEER and Atomic Bomb Survivor Data Analysis Tools

Creates SEER (Surveillance, Epidemiology and End Results) and A-bomb data binaries from ASCII sources and provides tools for estimating SEER second cancer risks. Methods are described in .

Analysis of High-Dimensional Categorical Data Such as SNP Data

Tools for the analysis of high-dimensional data developed/implemented at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME). Main focus is on SNP data. But most of the functions can also be applied to other types of categorical data.

Fast Agent-Based Epi Models

A flexible framework for Agent-Based Models (ABM), the 'epiworldR' package provides methods for prototyping disease outbreaks and transmission models using a 'C++' backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents' features, providing great complexity for the model dynamics. Furthermore, 'epiworldR' is ideal for simulation studies featuring large populations.

Performing Continuous-Time Microsimulation

This toolkit allows performing continuous-time microsimulation for a wide range of life science (demography, social sciences, epidemiology) applications. Individual life-courses are specified by a continuous-time multi-state model as described in Zinn (2014) .