COVID-19 Account for 60% of Latino Neighborhoods

In early April, Latino communities in Chicago experienced a fast growing number of COVIS-10 Cases.

As of 4/14/20, the Top Fastest growing Illinois Zip Codes reporting new COVID-19 cases shifted disproportionately to Latino populations based on the ethnic racial makeup of those Zip Codes. The CDC needs to immediately begin releasing detailed data on actual confirmed Coronavirus positive cases and deaths by Zip Code to help effectively target emerging hot pockets. There remains no available data reporting death’s by zip code impacting the Latino community.

Of the 710,648 people that live in the top 10 Zip Codes (2014 Census estimates from https://zipdatamaps.com/), the racial break down of these combined communities is as follows:

Racial Group2014 Population% of Population
White159,87022%
Black or African American76,32311%
Hispanic / Latino428,16960%
All Others46,2867%
All Groups Top 10 Zip Codes710,648
Source data Illinois Department of Public Health compiled daily by Enigma Forensics to report 2 day trailing growth rates of the virus.

This new data suggests that Mayor Lightfoot’s campaign targeting African American and other communities has been highly effective at slowing growth rates in many majority African American and other neighborhoods where English is broadly spoken. The growth rates in majority Latino neighborhoods suggests similar outreach efforts and analysis is needed targeting Latino neighborhoods where the virus is growing at the highest rates across Illinois.

Yesterday, a coalition of Latino leaders issued a press release calling on such a well needed outreach campaign to address the unique cultural and language needs of the Latino communities.

Other observed trends from yesterday’s data is the emergence of University Village into the top position for fastest growing Zip Code statewide at an alarming rate of 27% daily growth over the most recent 2 day period. We speculate that this may be a result of UIC and possibly the increase in availability of rapid testing in that zip code.

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Top 10 Coronavirus Confirmed Positive Growth Zip Codes in Illinois

The following data was compiled using the Illinois Department of Public Health’s daily statistics showing Coronavirus / COVID-19 Confirmed Positive Statistics taken from each of the last three day reports. The ranking is based on the 2 day average daily growth rate. Demographic data has been added from the website illinois-demographics.com to help better understand the communities impacted. The data shows statistics reported as of April 10th, 2020.

Yesterday I spent time driving into some of the Zip Codes that were experiencing the greatest growth rates that reported 100 or more Coronavirus confirmed positive tests. I observed a lack of social distancing with many young African American men not practicing social distancing or wearing protective masks or gloves congregating outside various essential businesses like retail stores and liquor stores. I observed an instance amongst young male Latinos as well. I observed problems at shopping centers with essential staff not having protective clothing or enforcing social distancing at the entrances or inside their stores. Customers entering stores generally are not wearing protective wraps around their faces.

It appears that these locations are economically disadvantaged largely. The residents of these zip codes need help in being educated on prevention measures to curtail the expanding growth rates of the Coronavirus. Businesses operating may need government inspectors to enforce social distancing recommendations through outreach. Ticketing of individuals willfully disregarding social distancing measures in larger groups may be necessary. The State of Illinois should prioritize deployment of the new Rapid 5 minute test equipment to suspected Coronavirus patients in these zip codes to more effectively curtail the growth of the virus to the general surrounding population. Essential service workers need to be wearing protective covering of some sort to help minimize and slow the virus transmission. A ban on shopping to customers not wearing protective coverings may need to be considered in the highest growth areas to protect those residents.

Click the Excel button below to copy the data above into a sortable spreadsheet.

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View all Illinois Zip Codes with 100 or more Coronavirus Confirmed Positive Cases ranked from fastest growing to slowest growing.

Latino Communities Taking the Lead in COVID-19 Rate of Growth

Fastest Growing Zip Codes with more than 100 confirmed Coronavirus cases

The fastest growing zip code with more than 100 confirmed positive diagnosis for COVID-19 is 60632. Brighton Park is the Chicago Community just East of Chicago Midway Airport. 88% of the population in this Zip Code is Latino. The runner up, 60608 which includes the Pilsen neighborhood and has just over 50% of the population identified as Hispanic or Latino. In third place is 60804 which is Cicero’s Zip Code. 60804 is 85% Hispanic of Latino.

State RankingZip Code4/8/204/9/20Net Change
160632, (East of Midway) Chicago, IL9211019.6%
260608, (Pilsen) Chicago, IL15818718.4%
360804 Cicero, IL12014218.3%
4600168610016.3%
56062316318815.3%
6606169210615.2%
76062415117113.2%
86061411412913.2%
96061215617612.8%
106065115717712.7%

See the latest rankings for all of Illinois

Top 10 Illinois Zip Codes with Largest Confirmed Corona Positive Cases

The Illinois Department of Public Health has begun publishing zip code level Coronavirus / COVID-19 Confirmed Positive cases. This data was captured as of 4/8/2020 4:15PM from http://www.dph.illinois.gov/covid19/covid19-statistics

The top 10 Zip Codes in Illinois reporting the highest number of Coronavirus / COVID-19 Confirmed Positive Cases

Top Cook County Locations Where Coronavirus / COVID-19 Confirmed Cases have been reported.
Zip CodePositive CasesCity – Neighborhood – CountyPeople per sq mile% of Population in Zip Code Black
60645272Chicago – West Ridge – (Cook)20,05514%
60620269Chicago – Auburn Gresham – (Cook)10,19198%
60619238Chicago – Chatham – (Cook)10,60197%
60628229Chicago – Roseland – (Cook)6,61295%
60617209South Chicago – (Cook)6,07056%
60644184Chicago – Austin – (Cook)13,88594%
60085178Waukegan – (Lake)4,79119%
60643178Beverly – (Cook)6,80075%
60623163Chicago – South Lawndale (Cook)17,19633%
60629162Chicago – Chicago Lawn (Cook)16,72623%
Six out of the top ten zip codes in Illinois with the highest total confirmed Coronavirus confirmed positive cases are majority black / African American population centers. Income, population, density and race appear to be factors in test positive rates. Incarceration rates by zip code we plan to look into as well to see if there appears to be a correlation. African Americans make up a disproportionate part of the prison population. This seems to be impacting them at a much higher rate.

Waukegan may be higher due to it being home to Abbott Laboratories which recently reported availability of Coronavirus rapid 5 minute test units.

Social Distancing Photos in Hot Zones

60644 Chicago Austin Photo Taken @ 4/9/20 9:30AM

60628 Chicago 100 W. 95th @ 4/9/20 10:30AM

60620, Family Dollar, 7927 S Ashland Ave, Chicago, IL 60620 @ 4/9:20 10:30AM

60620 Home Depot taking appropriate measures 200-232 W 87th St Chicago, IL 60620

State Ranking Coronavirus / COVID-19 Zip Codes reporting more than 5 Confirmed Positives as of 4/9/20

State RankingZip Code4/8/204/9/20Net Change
1606202692928.6%
2606452722854.8%
36061923826511.3%
4606282292383.9%
5606172092268.1%
66064418420410.9%
76008517819610.1%
8606431781927.9%
96062316318815.3%
106060815818718.4%
116062916218111.7%
126065115717712.7%
136061215617612.8%
146062415117113.2%
15604111581686.3%
166063914616211.0%
176064914716210.2%
18606341361499.6%
19606181351425.2%
206080412014218.3%
21606371241369.7%
22606591321341.5%
23606251281333.9%
246063611713011.1%
256061411412913.2%
26606571201243.3%
27604021151237.0%
286062211012311.8%
296046611012210.9%
30606521161214.3%
316065310811910.2%
326060910311410.7%
33606131071146.5%
34604431011119.9%
35606329211019.6%
36606151091090.0%
3760638991089.1%
38606401011075.9%
39606169210615.2%
40604099410410.6%
4160076961026.3%
4260435981024.1%
4360025971014.1%
4460104921019.8%
45600168610016.3%
4660901921008.7%
476062694984.3%
486045388969.1%
4960621849614.3%
5060473839413.3%
516064788935.7%
526052786904.7%
536007781888.6%
5460440788610.3%
556082782864.9%
566041978859.0%
576063080845.0%
586064176816.6%
596061078802.6%
606020177770.0%
6160655667716.7%
626003576760.0%
6360153657616.9%
646070774762.7%
656007374751.4%
666060770757.1%
6760426657413.8%
686047868748.8%
6960099637112.7%
706043866717.6%
716009369701.4%
726006862689.7%
736066063664.8%
7460087536522.6%
7560101546316.7%
76604296563-3.1%
7760586556314.5%
786006258615.2%
7960506526117.3%
806009160600.0%
816020258603.4%
8260446495920.4%
836061158591.7%
846063155597.3%
856047155585.5%
866004556571.8%
876006456571.8%
886043054575.6%
896071452567.7%
9060148495512.2%
9160406505510.0%
926015451545.9%
936044151545.9%
946001552531.9%
9560302465213.0%
9660462425121.4%
976005649502.0%
986064648504.2%
996018847494.3%
1006042345498.9%
1016042845498.9%
10260656424916.7%
1036060546484.3%
1046009045474.4%
1056016044464.5%
1066005343454.7%
1076045542457.1%
1086008941447.3%
10960431404410.0%
1106049042444.8%
11160026394310.3%
1126003142432.4%
11360133374316.2%
11460459384313.2%
11560525364319.4%
11660805384313.2%
1176001840425.0%
1186043341422.4%
1196010639415.1%
1206012037408.1%
1216012338405.3%
1226012637408.1%
1236013937408.1%
1246018540400.0%
1256040339402.6%
1266065439402.6%
12760107333918.2%
1286013036398.3%
1296013137395.4%
1306018138392.6%
13160477353911.4%
1326042536385.6%
1336045235388.6%
13460565303826.7%
1356071237382.7%
13660505293727.6%
13760164283628.6%
1386019335362.9%
13960484313616.1%
14060706313616.1%
1416004633356.1%
1426007432359.4%
1436042232359.4%
1446056132359.4%
1456041731349.7%
1466049131349.7%
1476051732346.3%
14860004303310.0%
14960048303310.0%
15060463283317.9%
15160467293313.8%
1526056432333.1%
15360007293210.3%
15460098273218.5%
15560432283110.7%
15660475283110.7%
1576006028307.1%
1586054329303.4%
1596060128307.1%
16060047262911.5%
16160439242920.8%
1626013728280.0%
1636045126287.7%
1646050427283.7%
16560516232821.7%
16660544252812.0%
1676055927283.7%
16860563252812.0%
1696044525278.0%
1706046525278.0%
1716048725278.0%
1726001424268.3%
1736016225264.0%
1746040425264.0%
1756041524268.3%
1766064225264.0%
1776170125264.0%
17860061222513.6%
1796010223258.7%
1806010324254.2%
1816051325250.0%
1826124423258.7%
18360044212414.3%
1846015523244.3%
18560436212414.3%
18660448212414.3%
1876063322249.1%
18860803212414.3%
1896003022234.5%
1906017222234.5%
1916046123230.0%
19260585202315.0%
1936001321224.8%
19460084192215.8%
1956054622220.0%
1966091422220.0%
197628010222200.0%
19860005172123.5%
19960010192110.5%
20060108192110.5%
2016018920215.0%
20261265172123.5%
20360050162025.0%
2046017119205.3%
20560194182011.1%
2066052119205.3%
2076256820200.0%
20862901162025.0%
2096017519190.0%
2106040118195.6%
2116044918195.6%
2126045719190.0%
21360515171911.8%
21460540171911.8%
21562040171911.8%
21660008161812.5%
2176043417185.9%
21860472161812.5%
2196051417185.9%
2206182217185.9%
22162226141828.6%
22262233141828.6%
22362236718157.1%
2246005116176.3%
2256006717170.0%
226601691817-5.6%
2276030416176.3%
2286052317170.0%
2296120117170.0%
2306011516160.0%
23160418141614.3%
23260502131623.1%
2336053216160.0%
2346066116160.0%
2356176116160.0%
2366222116160.0%
23762269141614.3%
2386000214157.1%
23960156131515.4%
2406044214157.1%
2416229814157.1%
2426008313147.7%
24360110101440.0%
2446017414140.0%
24561704121416.7%
24662002121416.7%
24762223111427.3%
2486002213130.0%
2496013413130.0%
250601421413-7.1%
2516017613130.0%
252602031413-7.1%
2536052612138.3%
2546004312120.0%
2556016581250.0%
25660458101220.0%
25760501101220.0%
2586056012120.0%
2596108112120.0%
2606202511129.1%
2616220811129.1%
26260012101110.0%
2636006911110.0%
26460081101110.0%
2656012411110.0%
2666054291122.2%
2676060611110.0%
2686002010100.0%
2696014010100.0%
2706017710100.0%
2716030591011.1%
2726046491011.1%
2736048281025.0%
2746050310100.0%
2756053871042.9%
2766095081025.0%
2776110271042.9%
2786180110100.0%
2796182110100.0%
2806220691011.1%
281622341110-9.1%
2826270281025.0%
28360070990.0%
28460118990.0%
28560163990.0%
286604698912.5%
287605347928.6%
28860558990.0%
28961802990.0%
290626508912.5%
29160136880.0%
292601737814.3%
29360178880.0%
29460301880.0%
29560410880.0%
296604507814.3%
29762278880.0%
2986230508800.0%
29960042770.0%
30060191770.0%
30160192770.0%
30260468770.0%
30360510770.0%
30460545770.0%
30560554770.0%
306609646716.7%
307611096716.7%
30861241770.0%
3096176407700.0%
31062220770.0%
31162258770.0%
31262265770.0%
3136230107700.0%
31462711770.0%
3156011906600.0%
31660143660.0%
31760187660.0%
31860551660.0%
31960555660.0%
3206103206600.0%
3216110306600.0%
32261114660.0%
32361282660.0%
32461853660.0%
32561910660.0%
3266203406600.0%
32762035660.0%
32862959660.0%
329600416 -100.0%
330620956 -100.0%

Top Locations in U.S. Where Corona Deaths Are Ramping

These are locations that report 3 or more Corona Related Deaths. Only 1 of these 28 locations has their Daily Growth rate under 30%. Medical supplies are desperately needed at these locations.

Average Daily Growth Rate= ((3/27 Confirmed Cases – 3/23 Confirmed Cases)/(3/23 Confirmed Cases))/Days Elapsed

Estimated Confirmed Positive Cases One Week Out = 3/27 Confirmed Cases * (1 + Average Daily Growth Rate)* (1 + Average Daily Growth Rate)* (1 + Average Daily Growth Rate)* (1 + Average Daily Growth Rate)* (1 + Average Daily Growth Rate)* (1 + Average Daily Growth Rate)* (1 + Average Daily Growth Rate)

Note: The average daily growth rate will slow before exceeding the max population. E.G. IN-Marion will not continue at the experienced average 245% daily growth rate.

The Transcript of the Video Follows:

Kitty Kurth (KK): Good morning! Today we’re here with Lee Neubecker from Enigma Forensics. A renowned data analyst, computer forensics expert, and inquisitive mind. Lee’s been thinking about the corona virus and looking into data. The data that’s out there in the world and taking it in, and looking at how we can analyze this data and what we can learn from it. Lee, tell us about what you’ve been doing.

Lee Neubecker (LN): Yes well, like everyone else I’ve been holed up at home in my basement and I’ve been wanting to think about, what can I do to help impact positive change, and what can my team do. And we decided we wanted to use our time to help minimize the spread of the virus and to help minimize death, so that’s my new mission that gives me something to wake up for and do, because certainly in the short term most client work is on hold because the courts are closed.

KK: So what, yesterday you released some data, can you tell us about where you got the data, what it was, and what it means. What you did with it, what it means.

LN: Yes, well like everyone else, I’ve been looking at the John Hopkins data map and they have a really nice visualization tool that lets you see the data as it’s updated. And I was examining their site and I discovered they had a GitHub repository where they’re uploading every day around 7pm central time. And as I looked at the data, I thought, you know there’s some interesting things that probably could be done that aren’t happening yet, such as looking at the penetration rate. If the county data just became available of the reporting, I looked out at the census and found some data from the census that included the population by county. So I started mapping out the population by county so that I could come up with something that I’m calling penetration rate. Which is essentially, what percent of the population has tested positive for the virus. And that information’s useful because it can give us some idea of, you know, how saturated will things be. Unfortunately though, the testing kits aren’t widely available so, it’s difficult to know for certain what’s happening as it relates to testing. More telling though is the data relating to deaths of corona virus, and that’s something that I was looking at this morning. And it has some, you know, really interesting things to talk about.

KK: What did you find when you were looking at that data? And the data you released yesterday, didn’t it show that there are 10 counties that are particularly in dire straits, or will be in dire straits, where the county officials should telling everybody to stay home.

LN: Yeah here’s my data model, are you able to see that? On screen, great. So, what I did is I thought, let’s look at locations that have 10 or more positive tests, and have, what are top 10 locations with 10 or more positive tests, that have the greatest rate of daily growth. And those are areas that no one’s talking about right now but I thought it was important to talk about that because they may think they’re safe. They may not know that someone’s begun passing the virus in the community. And so, you know, I identified places like Jackson, Michigan, which isn’t too far from where my family members are. They may not know there that they have a problem. They may not have public health professionals like Cook County has, dedicated to looking at the data. So, I thought it was important that we get the word out to some of these communities, that they’re emerging very fast with their growth of corona positive tests.

KK: There were some new data that you looked at last night, and some new things that you found, what did you find today?

LN: I wanted to look at where are people actually having deaths reported. So I looked at, where are there three or more deaths in the US. And because the tests are less reliable, you know, the confirmed test because there aren’t enough tests out there. But the places where people are actually starting to die, those are the places that are going to need a lot of medical supplies and help. And so today I published a new list of 29 locations. Let me resort this here by death rate. And death rate is a calculation, you know, how many deaths relative to the population. So for instance, in Dougherty, Georgia. They have the highest death rate, which may mean they’re in dire need of medical supplies. But they’re a very low population area.

KK: Georgia is one of the places that nobody’s been talking about at all. LN: Yeah and you can see there that, their population’s 87,000 roughly. They’ve had six deaths, but in terms of death rate, they’re at the top of it. So, you know, the public needs to look at what’s going on there. Are they keeping their kids at home? Are schools still open? Now those are important questions. Are people cavalier about it? You know, what’s the characteristic of the people who passed away? Are they all in a nursing home? There’s a lot of other things that can be looked into here. KK: Is there a cluster, are they all in one place? Or are they people that are out circulating in the community?

LN: Exactly.

KK: Is one of them the letter carrier? And then Louisiana has a high death rate and we heard about the fact that there are numerous cases there. Washington State it looks like is also high. New York, New Jersey. Connecticut is really growing it looks like. But then Colorado, no one has talked about that this one county in Colorado, El Paso County seems to have a really high rate. And Milwaukee, Wisconsin. People aren’t really talking about that either.

LN: If you look at Cook County, Illinois. What this is showing in my opinion is that despite the fact that we have a lot of cases, our health care system is keeping up, and keeping people from dying. So, you know, looking at how LA’s performing, what’s LA getting in terms of resources, and what’s the quality of their health care versus Dougherty, Georgia, or King, Washington, or some of these other places. You know, it’s very disheartening for instance to see Dougherty, Georgia, they’re at a 71% increase in testing over just a few days. That’s a average daily increase. They’ve actually, you know, more than almost tripled in just a few days.

KK: And again, that’s something that at least in the national media, no one is addressing Georgia. So, you know, we don’t know. I hope Georgia realizes they have a problem but no one else has talked about the fact that Georgia has a problem.

LN: The White House did say yesterday, that they wanted to try to address the counties where the hotspots are. So these are the hotspots. Some would say we should be doing this at the state level, and not focusing just on the county. But these counties definitely need attention.

KK: These counties need attention but what I heard the White House also say was, “we’re going to let counties be free if they’re not affected, then they can open up for business again.” And I don’t know about other states but here in Illinois, people go across the Cook County, Lake County, Cook County, DuPage County, Cook County, Will County borders pretty frequently. And sometimes several times in a day. So I don’t see how a plan to let places quote open up for business on a county by county basis could be helpful.

LN: Yeah but, you know, one of the things that I’ll be looking at as I update data. We’ll be looking at what’s going on in these counties. Are they sending alert out to people? If people aren’t aware that they’re having a daily increase of 128%, like Marion, Indiana. Their increase rate is alarming, 128%.

KK: And I don’t know about today, but historically Marion has been a place with a lot of manufacturing, and if people are working side by side in factories, that could be a huge problem. Thank you very much, and we’ll put up another post tomorrow and the next day as more data becomes available. Thank you Lee Neubecker and Enigma Forensics.

LN: Thank you.

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