I am interested in how my area and my friends and family’s area are doing during this crisis, so I made a script that will extract that data for me.

John Hopskins University collects data regarding the sick and diseased from COVID-19, you can get an up-to-date overview from the link above.

The underlying data is available on github, you can find them here github.com/CSSEGISandData/COVID-19

The script will download the data for a given day, and produce an output like this one

rank provins                 sick    died died/sick population died/population  04-01-2020.csv
  0  Total                 932605   46809    5.0 %   7775.0     6 deaths/mill
  1  Italy                 110574   13155   11.9 %     60.5   218 deaths/mill
  2  Spain                 104118    9387    9.0 %     46.8   201 deaths/mill
  3  US                    213372    4757    2.2 %    331.0    14 deaths/mill
  4  France                 56989    4032    7.1 %     65.3    62 deaths/mill
  5  China                  82361    3316    4.0 %   1439.3     2 deaths/mill
  6  Iran                   47593    3036    6.4 %     84.0    36 deaths/mill
  7  United_Kingdom         29474    2352    8.0 %     67.9    35 deaths/mill
  8  New_York-US            83948    1941    2.3 %     19.5   100 deaths/mill
  9  Netherlands            13614    1173    8.6 %     17.1    68 deaths/mill
 10  Germany                77872     920    1.2 %     83.8    11 deaths/mill
 11  Belgium                13964     828    5.9 %     11.6    71 deaths/mill
 12  Switzerland            17768     488    2.7 %      8.7    56 deaths/mill
 13  New_Jersey-US          22255     355    1.6 %      8.9    40 deaths/mill
 14  Michigan-US             9315     335    3.6 %     10.0    34 deaths/mill
 15  Turkey                 15679     277    1.8 %     84.3     3 deaths/mill
 16  Louisiana-US            6424     273    4.2 %      4.6    59 deaths/mill
 17  Brazil                  6836     240    3.5 %    212.6     1 deaths/mill
 18  Sweden                  4947     239    4.8 %     10.1    24 deaths/mill
 19  Washington-US           5608     234    4.2 %      7.6    31 deaths/mill
 20  California-US           9399     199    2.1 %     39.5     5 deaths/mill
 27  Massachusetts-US        7738     122    1.6 %      6.9    18 deaths/mill
 28  Denmark                 3107     104    3.3 %      5.8    18 deaths/mill
 88  Norfolk-Massachusetts    829      15    1.8 %      0.7    21 deaths/mill

The script is below, you are welcome to adapt it to your own needs:

#!/bin/sh
# (C) Beerware by Storepeter 2020
# based on data from https://github.com/CSSEGISandData/COVID-19
#
usage()
{
    if [ $# != 0 ]; then
	echo ERROR:$*
    fi
    echo USAGE: top20.sh 04-01-2020.csv
    echo download and extract top 20 corona virus for at a given day
    exit
}

NTOP=20

URL_DIR=https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports
# FILE=03-21-2020.csv

# got two format:

# until 2020-03-22
# Province/State,Country/Region,Last Update,Confirmed,Deaths,Recovered,Latitude,Longitude
# Hubei,China,2020-03-13T11:09:03,67786,3062,51553,30.9756,112.2707

# from 2020-03-23
# FIPS,Admin2,Province_State,Country_Region,Last_Update,Lat,Long_,Confirmed,Deaths,Recovered,Active,Combined_Key
# 21001,Adair,Kentucky,US,2020-03-23 23:19:34,37.10459774,-85.28129668,0,0,0,0,"Adair, Kentucky, US"

# create a simplified record
# deaths : sick : provins_state : date
simplify()
{
if [ ! -f "$1" ]; then
    usage
fi
sed -e 's/\"\([a-zA-Z]*\), \(.*\)\",/\1_\2,/' $1 \
-e 's/,/|/g' \
-e 's/ /_/g' \
-e 's/...:..:..//' \
| awk -F\| '
{
    if (NF < 10) {
	provins_id=1
	land_id=2
	sick_id=4
	died_id=5
	date=$3
    } else {
	provins_id=3
	land_id=4
	sick_id=8
	died_id=9
	date=$5
	if (($2=="Norfolk") && ($3=="Massachusetts")) {
	    name = "Norfolk-" $provins_id
	    sick[name] += $sick_id
	    died[name] += $died_id
	}
    }
    if ($land_id == "US") {
	name = $land_id
	sick[name] += $sick_id
	died[name] += $died_id
    }
    if (($land_id == "Mainland_China") || ($land_id == "China")) {
	name = "China"
    } else if (($provins_id == $land_id) || ($provins_id == "")) {
	name = $land_id
    } else {
	name = $provins_id "-" $land_id
    }
    sick[name] += $sick_id
    died[name] += $died_id
    sick["Total"] += $sick_id
    died["Total"] += $died_id
}
END {
    for (n in sick) {
	printf "%d:%d:%s:%s\n", died[n], sick[n], n, date
    }
}' | sort -rn -t: > $2
}


do_stat()
{
if [ ! -f $1 ]; then
    wget $URL_DIR/$1
    if [ $? != 0 ]; then
	if [ ! -f $1.simple ]; then
		usage $1 not available
	fi
    else
	simplify $1 $1.simple;
    fi
fi

cat $1.simple | awk -F: ' BEGIN {
# https://en.wikipedia.org/wiki/List_of_states_and_territories_of_the_United_States_by_population
# from https://www.worldometers.info/world-population/population-by-country/
    population["Total"] = 7775040500
    population["China"] = 1439323776
    population["US"] = 331002651
    population["Indonesia"] = 273523615
    population["Brazil"] = 212559417
    population["Japan"] = 126476461
    population["Philippines"] = 109581078
    population["Turkey"] = 84339067
    population["Iran"] = 83992949
    population["Germany"] = 83783942
    population["United_Kingdom"] = 67886011
    population["France"] = 65273511
    population["Italy"] = 60461826
    population["Korea_South"] = 51269185
    population["Spain"] = 46754778
    population["Iraq"] = 40222493
    population["California-US"] = 39512223
    population["New_York-US"] = 19453561
    population["Netherlands"] = 17134872
    population["Belgium"] = 11589623
    population["Sweden"] = 10099265
    population["Michigan-US"] = 9986857
    population["New_Jersey-US"] = 8882190
    population["Switzerland"] = 8654622
    population["Washington-US"] = 7614893
    population["Massachusetts-US"] = 6949503
    population["Denmark"] = 5792202
    population["Louisiana-US"] = 4648794
    population["Norfolk-Massachusetts"] = 705388
    population["San_Marino"] = 33931
    n=0
    print "rank provins                 sick    died died/sick population died/population  '$1'"
}
{
    died = $1
    sick = $2
    name = $3
    if ((n <= '$NTOP') || (name == "Denmark") || (name ~ /Massachusetts/)) {
	printf "%3d  %-21s %7d %7d", n, name, sick, died
	if (sick== 0)  {
	    printf "        "
	} else {
	    printf "  %5.1f %", 100 * died / sick
	}
	if (name in population) {
	    printf "   %6.1f  %5d deaths/million", population[name]/1000000, died * 1000000/ population[name] 
	}
	printf "\n"
    }
    n++
}'
}

if [ $# = 0 ]; then
    i=$(date -d "1 day ago" +%m-%d-%Y).csv
    rm -f $i
    do_stat $i;
else
    for i in $*;do
	do_stat $i;
    done
fi

The script started out as a oneliner, but have evolved a bit,

• John Hopskins changed the format of the file between March 22 and March 23, hence I added the simplify() function to give me an intermediate format
• added the population of the regions

My conclusion of these numbers are: We are lucky to live a in an area that has taken the same precautions as my birth-country, and that we are seeing the same results. which could be far worse.