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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# promedr
<!-- badges: start -->
[![Travis build status](https://travis-ci.org/sangeetabhatia03/promedr.svg?branch=master)](https://travis-ci.org/sangeetabhatia03/promedr)
[![Codecov test coverage](https://codecov.io/gh/sangeetabhatia03/promedr/branch/master/graph/badge.svg)](https://codecov.io/gh/sangeetabhatia03/promedr?branch=master)
<!-- badges: end -->
The goal of promedr is to pre-process data from ProMED and HealthMap
and produce a clean incidence time series that can be used in
analysis downstream.
ProMED/HealthMap data are made available as a CSV with the following
columns:
+ Location
+ Country
+ Region/City
+ Disease
+ Species
+ Feed Language
+ HM Alert ID
+ Headline
+ URL
+ Issue Date
+ Alert Tag
+ New SC
+ New SD
+ New CC
+ New CS
+ Cumulative SC
+ Cumulative SD
+ Cumulative CC
+ RO
+ Feed Name
+ Report Source - Primary
+ Secondary Report Source
Processing this data consists of the following steps:
+ Extract the total cumulative case count as a sum of desired case
categories (Confirmed, Suspected, or both)
+ If there are any duplicate alerts for a given day, merge them
according to pre-specified set of rules.
+ Any inconsistent data points at the end of the time series i.e.,
those that make the cumulative case count non-increasing, are moved
using Chebyshev's inequality.
+ Any points in the middle of the time series that cause the cumulative
case count to be decreasing, are removed using pre-specified rules.
+ Finally, missing data are imputed.
## Installation
You can install the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("sangeetabhatia03/promedr")
```