Making the DAEN information accessible.

Overview

AccessibleAdverseEventNotification

Making the DAEN information accessible.

The purpose of this repository is to make the information on Australian COVID-19 adverse events accessible. The Therapeutics Goods Administration (TGA) keeps a database of adverse reactions to medications including the COVID-19 vaccines. This Database of Adverse Event Notifications (DAEN) is available to the public via this awful web interface. The most recent two weeks is never available.

The DAEN website doesn't provide information in a format that might be useful for analysis. Instead you have to scrape the information by entering each individual day and collecting the results from two tables which might span multiple pages. I've already done that and the code is here (this code isn't great, but it is good enough to get the job done).

Please be aware that the numbers reported in DAEN are probably significantly less than the actual number of adverse events and deaths. As the DAEN website states:

Adverse event reports from consumers and health professionals to the TGA are voluntary, so there is under-reporting by these groups of adverse events related to therapeutic goods in Australia. This is the same around the world.

The scraped data is found in the data directory. These files are tab separated files which you can easily import in to a spreadsheet program. All of the files are only for COVID-19 vaccines.

  • DAEN_webscrape_simple.txt This file shows the date (twice for reasons that made sense at the time, but don't necessarily make sense anymore), the number of cases reported that day, the number of cases with a single suspected medicine for that day, and the number of deaths reported that day.
  • DAEN_webscrape_medsummary.txt This file gives a daily count of each adverse event category. Please note that if one patient had multiple adverse events, then each event would be counted in the appropriate category.
  • DAEN_webscrape_listofreports.txt This file provides the individual reports and includes sex and age (when recorded).

Figure 1 shows some of the basic information such as number of adverse events and deaths reported each day for the COVID-19 vaccines, myocarditis, pericarditis and the more general term cardiac disorder.

Figure 1 Figure 1.

Figure 2 shows a histogram of reported cases of myocarditis and pericarditis from the COVID-19 vaccine. Please note that the age group 10-19 is somewhat distorted as the age 10-11 should not receive the vaccine (although there are cases of 8 year olds getting the vaccine when that should not have occurred). This age group also has a significantly lower uptake than other age groups.

Figure 2 Figure 2.

Figures 3 and 4 plot the reports of myocarditis by age grouped by sex or manufacturer respectively. Figures 5 and 6 are the same for pericarditis. A '-' is used where an age was not given in the report.

Figure 3 Figure 3.

Figure 4 Figure 4.

Figure 5 Figure 5.

Figure 6 Figure 6.

Figure 7 shows how the histogram for myocarditis has progressed over time.

Figure 7
Figure 7.

Figure 8 shows the death rate of people in Australia who contracted COVID-19. Data taken from health.gov on 1/12/2021. Bottom graph is zoomed in to 1% to see what is happening with those under the age of 60.

Figure 8
Figure 8.

Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles

Correlation-Study-Climate-Change-EV-Adoption Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles I

Jonathan Feng 1 Jan 03, 2022
A set of procedures that can realize covid19 virus detection based on blood.

A set of procedures that can realize covid19 virus detection based on blood.

Nuyoah-xlh 3 Mar 07, 2022
A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

TennisBusinessIntelligenceProject - A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

carlo paladino 1 Jan 02, 2022
Employee Turnover Analysis

Employee Turnover Analysis Submission to the DataCamp competition "Can you help reduce employee turnover?"

Jannik Wiedenhaupt 1 Feb 13, 2022
Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required)

Binomial Option Pricing Calculator Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required) Background A derivative is a fi

sammuhrai 1 Nov 29, 2021
Tools for working with MARC data in Catalogue Bridge.

catbridge_tools Tools for working with MARC data in Catalogue Bridge. Borrows heavily from PyMarc

1 Nov 11, 2021
Automatic earthquake catalog building workflow: EQTransformer + Siamese EQTransformer + PickNet + REAL + HypoInverse

Automatic regional-scale earthquake catalog building workflow: EQTransformer + Siamese EQTransforme

Xiao Zhuowei 9 Nov 27, 2022
Port of dplyr and other related R packages in python, using pipda.

Unlike other similar packages in python that just mimic the piping syntax, datar follows the API designs from the original packages as much as possible, and is tested thoroughly with the cases from t

179 Dec 21, 2022
Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.

Stock Statistics/Indicators Calculation Helper VERSION: 0.3.2 Introduction Supply a wrapper StockDataFrame based on the pandas.DataFrame with inline s

Cedric Zhuang 1.1k Dec 28, 2022
Calculate multilateral price indices in Python (with Pandas and PySpark).

IndexNumCalc Calculate multilateral price indices using the GEKS-T (CCDI), Time Product Dummy (TPD), Time Dummy Hedonic (TDH), Geary-Khamis (GK) metho

Dr. Usman Kayani 3 Apr 27, 2022
Additional tools for particle accelerator data analysis and machine information

PyLHC Tools This package is a collection of useful scripts and tools for the Optics Measurements and Corrections group (OMC) at CERN. Documentation Au

PyLHC 3 Apr 13, 2022
Using Python to scrape some basic player information from www.premierleague.com and then use Pandas to analyse said data.

PremiershipPlayerAnalysis Using Python to scrape some basic player information from www.premierleague.com and then use Pandas to analyse said data. No

5 Sep 06, 2021
Includes all files needed to satisfy hw02 requirements

HW 02 Data Sets Mean Scale Score for Asian and Hispanic Students, Grades 3 - 8 This dataset provides insights into the New York City education system

7 Oct 28, 2021
Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine

Statistical Rethinking: A Bayesian Course Using CmdStanPy and Plotnine Intro This repo contains the python/stan version of the Statistical Rethinking

Andrés Suárez 3 Nov 08, 2022
statDistros is a Python library for dealing with various statistical distributions

StatisticalDistributions statDistros statDistros is a Python library for dealing with various statistical distributions. Now it provides various stati

1 Oct 03, 2021
Sample code for Harry's Airflow online trainng course

Sample code for Harry's Airflow online trainng course You can find the videos on youtube or bilibili. I am working on adding below things: the slide p

102 Dec 30, 2022
This repo contains a simple but effective tool made using python which can be used for quality control in statistical approach.

This repo contains a powerful tool made using python which is used to visualize, analyse and finally assess the quality of the product depending upon the given observations

SasiVatsal 8 Oct 18, 2022
Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code

Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code. Tuplex has similar Python APIs to Apache Spark or Dask, but rather

Tuplex 791 Jan 04, 2023
PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to

Derek Snow 527 Jan 02, 2023
Python library for creating data pipelines with chain functional programming

PyFunctional Features PyFunctional makes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do

Pedro Rodriguez 2.1k Jan 05, 2023