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Dynamical Systems Approach to Infectious Disease Epidemiology (Ecology/Evolution)
Exploration of simulation models (apps) of various infectious disease transmission dynamics scenarios. The purpose of the package is to help individuals learn about infectious disease epidemiology (ecology/evolution) from a dynamical systems perspective. All apps include explanations of the underlying models and instructions on what to do with the models.
Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data
Bayesian reconstruction of disease outbreaks using epidemiological
and genetic information. Jombart T, Cori A, Didelot X, Cauchemez S, Fraser
C and Ferguson N. 2014.
Code Sharing at the Department of Epidemiological Research at Statens Serum Institut
This is a collection of assorted functions and examples collected from various projects. Currently we have functionalities for simplifying overlapping time intervals, Charlson comorbidity score constructors for Danish data, getting frequency for multiple variables, getting standardized output from logistic and log-linear regressions, sibling design linear regression functionalities a method for calculating the confidence intervals for functions of parameters from a GLM, Bayes equivalent for hypothesis testing with asymptotic Bayes factor, and several help functions for generalized random forest analysis using 'grf'.
Tables of Descriptive Statistics in HTML
Create HTML tables of descriptive statistics, as one would expect to see as the first table (i.e. "Table 1") in a medical/epidemiological journal article.
Process Based Epidemiological Model for Cercospora Leaf Spot of Sugar Beet
Estimates sugar beet canopy closure with remotely sensed leaf area index and estimates when action might be needed to protect the crop from a Leaf Spot epidemic with a negative prognosis model based on published models.
Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters
Estimates the time-varying reproduction number,
rate of spread, and doubling time using a range of open-source tools
(Abbott et al. (2020)
Characterise Tables of an OMOP Common Data Model Instance
Summarises key information in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Assess suitability to perform specific epidemiological studies and explore the different domains to obtain feasibility counts and trends.
Epimed Solutions Collection for Data Editing, Analysis, and Benchmark of Health Units
Collection of functions related to benchmark with prediction models for data analysis and editing of clinical and epidemiological data.
A Comprehensive Collection of Cancer Types and Cancer-Related Datasets
Offers a rich collection of data focused on cancer research, covering survival rates, genetic studies, biomarkers, and epidemiological insights. Designed for researchers, analysts, and bioinformatics practitioners, the package includes datasets on various cancer types such as melanoma, leukemia, breast, ovarian, and lung cancer, among others. It aims to facilitate advanced research, analysis, and understanding of cancer epidemiology, genetics, and treatment outcomes.
Data Wrangling and Automated Reports from 'SIVIGILA' Source
Data wrangling, pre-processing, and generating automated reports from Colombia's epidemiological surveillance system, 'SIVIGILA' < https://portalsivigila.ins.gov.co/>. It provides a customizable R Markdown template for analysis and automatic generation of epidemiological reports that can be adapted to local, regional, and national contexts. This tool offers a standardized and reproducible workflow that helps to reduce manual labor and potential errors in report generation, improving their efficiency and consistency.