Covid Behaviors Python Library
From the CORGIS Dataset Project
By Sam Donald Version 1.0.0, created 9/23/2022 Tags: Covid-19, social response, healthcare
Overview
Behavioral analysis of how populations are responding to the pandemic - based on a monthly survey where respondents note counts of various activities along with a 0-100 score related to how much they agree with a given statement
https://github.com/YouGov-Data/covid-19-tracker
Explore Structure
Each row represents covid-report .
Explore covid behaviors data
Index Type Example Value
0
dict
{
1 dict (same structure)
2 dict (same structure)
... ... ...
Key Type Example Value Description
"Country"
str
"Australia"
Nameof country
"Days since outbreak"
int
85
Count of days passed since Covid-19 outbreak began
"Counts"
dict
{
"Scores"
dict
{
Key Type Example Value Description
"Household contacts"
float
2.0
Number of household contacts for the previous day (averaged by country)
"Total contacts"
float
8.2
Total number of contacts for the previous day (averaged by country)
"Times left home"
float
1.0
Number of times the respondent left the house on the previous day (averaged by country)
"Handwashes"
float
11.5
Number of times the respondent washed their hands on the previous day (averaged by country)
Key Type Example Value Description
"Isolate"
dict
{
"Masks"
dict
{
"Avoidance"
dict
{
"Precautions"
dict
{
"Outlooks"
dict
{
Key Type Example Value Description
"Willingness if symptoms"
float
85.8
Score (0-100) related to how much the respondent would be willing to isolate if syptomatic (100 = very willing)
"Willingness if advised"
float
14.3
Score (0-100) related to how much the respondent would be willing to isolate if advised (100 = very willing)
"Difficulty"
float
91.9
Score (0-100) related to how difficult isolating would be (100 = very difficult)
Key Type Example Value Description
"Outside home"
float
23.9
Score (0-100) related to how often the respondent wears a mask outside (100 = all the time)
"Grocery store"
float
0.0
Score (0-100) related to how often the respondent wears a mask while at a grocery store (100 = all the time)
"Clothing store"
float
0.0
Score (0-100) related to how often the respondent wears a mask while at a clothing store (100 = all the time)
"Work"
float
0.0
Score (0-100) related to how often the respondent wears a mask while at work (100 = all the time)
"Public transport"
float
0.0
Score (0-100) related to how often the respondent wears a mask while on public transport (100 = all the time)
Key Type Example Value Description
"Symptomatic people"
float
86.6
Score (0-100) related to how much effort the respondent takes to avoid symptomatic people (100 = maximum effort)
"Going out"
float
77.6
Score (0-100) related to how much effort the respondent takes to avoid going out (100 = maximum effort)
"Healthcare settings"
float
72.9
Score (0-100) related to how much effort the respondent takes to avoid healthcare settings people (100 = maximum effort)
"Public transport"
float
83.3
Score (0-100) related to how much effort the respondent takes to avoid public transport (100 = maximum effort)
"Working outside home"
float
59.4
Score (0-100) related to how much effort the respondent takes to avoid working outside the home (100 = maximum effort)
"Children going to school"
float
79.1
Score (0-100) related to how much effort the respondent and their children takes to avoid school (100 = maximum effort)
"Having guests"
float
87.2
Score (0-100) related to how much effort the respondent takes to avoid having guests (100 = maximum effort)
"Gatherings"
dict
{
"Crowded areas"
float
89.8
Score (0-100) related to how much effort the respondent takes to avoid crowded areas (100 = maximum effort)
"Shops"
float
60.2
Score (0-100) related to how much effort the respondent takes to avoid shops (100 = maximum effort)
Key Type Example Value Description
"Small"
float
85.7
Score (0-100) related to how much effort the respondent takes to avoid small gatherings (100 = maximum effort)
"Medium"
float
90.9
Score (0-100) related to how much effort the respondent takes to avoid medium gatherings (100 = maximum effort)
"Large"
float
92.7
Score (0-100) related to how much effort the respondent takes to avoid large gatherings (100 = maximum effort)
Key Type Example Value Description
"Cleaned surfaces"
float
64.4
Score (0-100) related to how much effort the respondent takes to clean surfaces (100 = maximum effort)
"Covered mouth sneeze"
float
91.8
Score (0-100) related to how much effort the respondent takes to cover their mouth while sneezing (100 = maximum effort)
"Used hand sanitiser"
float
72.9
Score (0-100) related to how much effort the respondent takes to use hand sanitiser (100 = maximum effort)
Key Type Example Value Description
"Covid is dangerous"
float
0.0
Score (0-100) related to how dangergerous the respondent thinks Covid is (100 = very dangerous)
"Likely to get covid"
float
0.0
Score (0-100) related to how likely the respondent thinks they are to contract Covid (100 = certain)
"Life greatly impacted"
float
0.0
Score (0-100) related to how much the respondents live is impacted (100 = maximum impact)
Downloads
Download all of the following files.
covid_behaviors.py covid_behaviors.data
Usage
import covid_behaviors
report = covid_behaviors . get_report ()
Documentation
get_report() Returns a list of dictionaries representing Report.
