flumodelr: Introduction

Kevin W. McConeghy

2019-06-06

Source: vignettes/01-introduction.Rmd

Welcome to flumodelr! This program was written as a companion to academic work performed by researchers at Brown University in collaboration with Sanofi-Pasteur. The primary objective was to streamline and formalize published work on estimating attributable influenza cases. We drew from many sources which are acknowledged and cited throughout in the development of this package.

Introduction

This vignette is a short introduction to the package for interested readers. In following vignettes describe in detail:

  1. Publicly available data used to develop and test this software.
    Data

  2. Simple modeling approach: Risk Difference
    Risk Difference

  3. Explanation of original Serfling Model.
    Serfling Background

  4. Explanation of modern implementation of Serfling Model in a Generalized linear model.
    Modern Serfling Applications

  5. Estimating attributable mortality using ARIMA models. ARIMA models

  6. Estimating attributable mortality using Generalized Additive Models. GAM models

  7. Estimating attributable mortality using Dynamic Bayesian Models. Bayesian models

Contacting authors

The primary author of the package was Kevin W. McConeghy. Several other researchers including Andrew Zullo, Rob van Aalst, Vincent Mor, Stefan Gravenstein provided statistical consultation, clinical insight and institutional support.