New York

Alaska: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

California: Never reported negatives directly, but did report in Total tests (people) until April 21, 2020. Removing time series from present to April 22, 2020.

Values Removed: Changes.txt

Washington DC: Never reported negatives directly, and has always reported encounters, removing total time series

Values Removed: Changes.txt

Georgia: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

Kentucky: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

New York: Never reported negatives directly and always reported in encounters, removing total time series

Values Removed: Changes.txt

Ohio: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

Oregon: Never reported negatives directly, but did report in Total tests (people) until December 1, 2020. Removing time series from present to December 2, 2020.

Values Removed: Changes.txt

Texas: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

Virginia: Never reported negatives directly and always reported in encounters, removing total time series

Values Removed: Changes.txt

Washington: Negatives were backfilled with values calculated from total tests (encounters)-confirmed cases in August 2020. Removing total time series.

Values Removed: Changes.txt

Alaska: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

California: Never reported negatives directly, but did report in Total tests (people) until April 21, 2020. Removing time series from present to April 22, 2020.

Values Removed: Changes.txt

Washington DC: Never reported negatives directly, and has always reported encounters, removing total time series

Values Removed: Changes.txt

Georgia: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

Kentucky: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

New York: Never reported negatives directly and always reported in encounters, removing total time series

Values Removed: Changes.txt

Ohio: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

Oregon: Never reported negatives directly, but did report in Total tests (people) until December 1, 2020. Removing time series from present to December 2, 2020.

Values Removed: Changes.txt

Texas: Never reported negatives directly and always reported in specimens, removing total time series

Values Removed: Changes.txt

Virginia: Never reported negatives directly and always reported in encounters, removing total time series

Values Removed: Changes.txt

Washington: Negatives were backfilled with values calculated from total tests (encounters)-confirmed cases in August 2020. Removing total time series.

Values Removed: Changes.txt

Rows edited: 1 NY 2021-01-04 lastUpdateTime: 2021-01-03 19:00:00+00:00 (was 2021-01-04 19:00:00+00:00)

Rows edited: 1 NY 2021-01-04 lastUpdateTime: 2021-01-03 19:00:00+00:00 (was 2021-01-04 19:00:00+00:00)

Changes (2).txt

Multi-edit tool-PRODUCTION - NY-REB-20201123.csv.txt Multi-edit tool-PRODUCTION - NY-REB-20201123_post.csv.txt

BEFORE:

AFTER:

Before

After

NY's timestamp for 8/1 was changed to 7/31 23:59 per existing guidance.

Before:

After:

I confirmed the provided numbers matched the NY dashboard and then made six patches for current hospitalization:

Before:

After:

Before:

After:

Before:

After:

Before:

After:

Before:

After:

Before:

After:

Note I didn't change the fact we are a day behind, just corrected the values at the day-later offset from the official data.

I pulled the data for the ICU backfill, will finish later tonight

Here's what we had for NY ICU until now:

Here's the official numbers I pulled from the dashboard linked in the issue description:

There were a few days before and after the gap which got straightened out as part of this process. Spreadsheet with the analysis, the original states daily column, and the new one: https://docs.google.com/spreadsheets/d/1K4YnfdMCCI4QX40DgPnxKPdMw_QGM47vmYHT9RWFlDM/edit#gid=0

Also, for the ICU updates, as with the hospitalization updates, I didn't "fix" the fact we are a day behind the official numbers (since we'd just immediately fall behind again)

Amazing, Matt, Thanks so much! The graphs here are really helpful too.

Everything matches up. Thanks so much for your work here.

Just adding my thanks!

On Sat, Jul 4, 2020 at 6:48 PM Gerald Schifman notifications@github.com wrote:

Everything matches up. Thanks so much for your work here.

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Updated tooltip and added process note.

States Daily

BEFORE

AFTER

DC'd by SNW

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Yes, see this tweet and the attached story: https://twitter.com/COVID19Tracking/status/1258503564785156101?s=20

On Fri, May 8, 2020 at 6:02 PM nrodrigo notifications@github.com wrote:

Not sure if this is the right forum for data validation but I wasn't sure if the number of deaths on 5/7 i NY is correct:

20200508 NY 217 20200507 NY 951 20200506 NY 232

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Hi @caspiegel

Thanks for writing Please see this issue for the explanation: https://github.com/COVID19Tracking/issues/issues/331

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Hi @buh2003 Thanks for writing.We are now calculating the hospitalizations based on the numbers given in the daily briefings.

Please note that there is a state wide call to provide this information in a more straightforward way, as many other states already do. https://reinventalbany.org/2020/04/watchdogs-urge-governor-to-publish-covid-19-data-as-open-data/

Hi @platham1

We are now calculating the NYS hospitalizations based on the 3 day rolling average numbers given in the governor's daily press briefings. Thanks for you note.

Hi @thelola,

Thanks for writing. We are now calculating the hospitalizations based on the numbers given in the daily briefings.

Please note that there is a state wide call to provide this information in a more straightforward way, as many other states already do. https://reinventalbany.org/2020/04/watchdogs-urge-governor-to-publish-covid-19-data-as-open-data/

Still potentially a big problem with the under reporting deaths in NY state. On 4/26 you reported 49153 whereas Worldometer reported 55413 (+6260!). Also a smaller discrepancy for PA, 1550 vs.1823 for Worldometer. This is affecting the US total which is over 55,000 at Worldometer and only 49153 on your table.

Here's the explanation: https://twitter.com/COVID19Tracking/status/1254161668671541248?s=20

Pennsylvania recently restated their numbers, which I don't think Worldometer has reflected.

Thanks,

Alexis

On Mon, Apr 27, 2020 at 9:41 AM MadDr33 notifications@github.com wrote:

Still potentially a big problem with the under reporting deaths in NY state. On 4/26 you reported 49153 whereas Worldometer reported 55413 (+6260!). Also a smaller discrepancy for PA, 1550 vs.1823 for Worldometer. This is affecting the US total which is over 55,000 at Worldometer and only 49153 on your table.

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Tweet is vague. It implies(to me) that the discrepancy is due to the difference between deaths attributed to COVID but not confirmed by test...but this interpretation requires an assumption.

There is a HUGE difference between worldometers total fatalities in the U.S. and the total here (as of this moment, this site lists a net 61,688 deaths. Worldometers lists 68,609. This is nearly a 10%(!) difference.

What is the cause of the difference, and please post this cause in a text box in your google docs worksheets and on the web pages.

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Thanks for writing @Josh0883123

Please see this response https://github.com/COVID19Tracking/issues/issues/331#issuecomment-621381956

We're working on separate accounting of lab-confirmed and probable deaths for all states where we can do so.

This is related to COVID19Tracking/covid-tracking-data#26

Thanks @xaminmo! Forwarding to our data team

Also, Indiana just showed up missing cumulative ICU.

Duplicate of #132 and you can find the resolution process on that issue

Hello, We did go back and clean up some of our historical hospitalization data due to a modification of our process. Check out #132 for reference.

Here is what I see now:

• 4/2 US Daily: "hospitalizedIncrease":4141 -4/2 NY Dail: "hospitalizedIncrease":2449

Good catch! negatives should be =260520-102863=157657

Data before:

Data after:

You are correct - all pf NY data is for the end of the day prior to our report. We are considering adding a timestamp to our data to help clarify this issue.

Another way to look at this is: we cannot report on all of data from 4/2 until 4/3

Not sure why there is a variance between what the report and their repo. That could be a great resource though - thanks for the link!

States daily before

States daily after

Checks before

Checks after

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Uploading a spreadsheet of all decreases (more than documented previously), current as of today: covidtracking_problemdates.xlsx

States affected: AK, AL, AZ, CO, DC, DE, FL, HI, IA, KS, MA, MD, MI, NJ, NM, NV, NY, OH, OK, PR, RI, SC, WI

This is my R code to calculate new cases and pull records that decreased from the prior day (any variable) AND the prior day's row for comparison:

library(tidyverse)
covidtracking %>% 
    arrange(state, date) %>% 
    group_by(state) %>% 
    mutate_at(vars(c("positive", "death", "total")), 
              list(new = ~ coalesce(. - lag(.), .))) %>%
    filter_at(vars(ends_with("new")), any_vars(. < 0 | lead(.) < 0)) %>% 
    ungroup()

I wonder if the problem is an error in the data source in which corrections for prior day results are included as adjustments on the day the error was discovered. This is common in the banking world because of the value of keeping past transactions immutable. It's poor practice for scientific data, however, because the test counts on a given day matter.

If the problem is deferred adjustment, the idea solution is to inform the data sources and ask for better quality data. Short of that, an corrective approach is to reverse the error to the best extent that the data allows: Where a daily result is negative, set that day to zero, and decrease the count of the previous day by the corresponding amount.

Such a correction would not be perfect since (a) you don't know for sure whether the error was from the previous day versus earlier and (b) it doesn't correct any of the cases where adjustments didn't cause negative result. Still, it leads to better data quality than making no correction and avoids the confusion of negative daily counts.

Hello, and thank you for helping us clean our data. Please see the following:

New York:

• [ ] 3/7 to 3/8 the total changed due to pending tests no longer being reported.
• [ ] 3/10 to 3/11 should be correct

Oklahoma

• [ ] 3/20 to 3/21 the variance in totals is tied to the unreliable Pending category. It may be that the data point was phased out and our data was affected by this transition;

Ohio

• [ ] 3/16 to 3/17 variation in data is due to Pending data no longer being published.

New Jersey

• [ ] 3/16 is infact incorrect:
• [ ] corrected

Hawaii

• [ ] Pending for 3/19 decrease per the state

Michigan stopped reporting pending data as of 3/17

Kansas stopped reporting pending data as of 3/11

Iowa stopped reporting pending data as of 3/14 Deleware stopped reporting pending data as of 3/17 DC has fluctuating pending data

Thank you for these clarifications, @careeningspace, and for working on providing these data so accessibly! In terms of cleaning up these records for use:

1. Has the NJ correction been applied to the live data?
2. Given the inconsistencies with pending data, do you foresee any problems with subtracting pending cases from the totals?

The NJ correction should be in the live feed. Going forward, our API will no longer be focusing on including Pending in our "Total". You can find more detail on our API Page

• [ ] totalTestResults - Calculated value (positive + negative) of total test results.
• [ ] total - DEPRECATED Will be removed in the future. (positive + negative + pending). Pending has been an unstable value and should not count in any totals.

As for subtracting historical "Pending" data - if you want a clean Total, you can sum Positive and Negative.

Great, thanks. That fixes problems in many states and leaves only AK, DC, HI, ID, KY, MI, NV, and SC with negative "increases": covidtracking_problemdates.xlsx

covidtracking %>% arrange(state, date) %>% group_by(state) %>% filter_at(vars(ends_with("Increase")), any_vars(. < 0 | lead(.) < 0)) %>% ungroup()

-[ ] Alaska has a period of data flux that needs more research 3/17 - 3/19: Data Log:

Daily Report:

State Data from 3/17 14:09 ET:

State Data from 3/17 18:00 ET:

State Data from 3/18:

Updated Daily after correction:

District of Columbia 3/10 - 3/11

• [ ] We do not have screen grabs from this time period
• [ ] It looks like DC changed how they were reporting data. I am going to make both days match

DC Before update:

DC after update:

• [ ] ID has an issue with a change in data from 3/18 to 3/19

• [ ] Screen cap of State Data from 3/18 14:04:

• [ ] Screencap of State Data from 3/19 14:04:

• [ ] The positives increase, while the total tests reported did not. Our methodology is to leave the negatives unchanged in this case. Fixed data below:

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Thank you - will get to this later today

Great thanks!

Thank you - will get to this later today

Great thanks!

I looked at our historical for NY and we have something completely different - I will need to dig further.

I wasn't helping track back in those early days so I don't know how/what NY was reporting. But to my knowledge, that screenshot I sent was the first time they gave solid retrospective testing data, so I imagine it would be different from whatever they disclosed piecemeal before perhaps? Thanks for taking a look.

Jordan

On Fri, Mar 27, 2020 at 12:10 AM Elliott Klug notifications@github.com wrote:

I looked at our historical for NY and we have something completely different - I will need to dig further. [image: Screen Shot 2020-03-27 at 12 09 31 AM] <../../assets/github/images/43073915/77720777-45e08480-6fbf-11ea-8714-38533d065acd.png>

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There's communication - perhaps the site could note somewhere how much coordination if any is happening with other major sites.

NYT using our data: https://www.nytimes.com/interactive/2020/03/17/us/coronavirus-testing-data.html.

Asked about making their map data open, they said no.

There's communication - perhaps the site could note somewhere how much coordination if any is happening with other major sites.

NYT using our data: https://www.nytimes.com/interactive/2020/03/17/us/coronavirus-testing-data.html.

Asked about making their map data open, they said no.