April 3-4, 2020 summary: The big news today is that California has finally addressed its testing backlog, and its paucity of testing. So, big jump in new infections, but not necessarily bad news. After I adjust for jump in old test results, it seems pretty positive, though we’ll have to wait out 2-3 days to see the steady state. I’m more worried about other states that started late (in terms of infections, but particularly in taking measures to stop the spread).

April 1-2, 2020 summary: Continuing positive news - in the sense that #days to double the #infections has gone from 2-3 days to about 7 (i.e., daily growth rate fallen from ~ 30% to ~ 10%), indicating that lockdown measures are showing results (see my note below about 10-15 day lag). This is true nationally, and there’s some improvement in key states CA, WA, NY). But I’m a bit hesitant about California due to testing and reporting issues.

March 31, 2020 summary: A larger jump in new infections, both nationally and in California. California data remains a mess with still a huge number of pending results and inconsistent reporting from counties and private labs.

March 29-30, 2020 summary: Is a positive trend building up over the last few days?

March 28, 2020 summary: Continuation of the mildly positive trend from yesterday - in terms of the lack of increase in daily growth rate, especially in New York.

March 27, 2020 summary: Am I right in seeing some hopeful signs from national data. Based on the last 3 days, daily infection curve is linear rather than exponential (though still very high), leading to about a 20% “daily growth rate for cumulative infections” and doubling period of 4 days (rather than 2 or 3).

March 26, 2020 summary: There is a big jump in known infections (positive test results) relative to a day ago. Some due to increase in testing capacity, but it is disturbing that even the % of positive results is higher during the last 3 days. We are still in a danger zone of the cumulative number of known infections doubling about every 3 days.

March 25, 2020 summary: NY is mixed (% daily infections was higher, but growth over cumulative was lower); MA and FL an TX worse. CA and WA (west coast) - don’t have good data for the day yet. National numbers (daily growth) flat over yesteday, which is not good but not bad.

Corona Virus Crisis: Where is it Heading?

For a few weeks now my ears, eyes and thoughts have been consumed with corona virus issues - status, policy making, crisis management. Early in March, my co-chairs and I pulled the plug on our TEIS academic workshop (but had a very successful event over Zoom, instead of the original Newport Beach location). Next, I conducted my final class of the quarter over Zoom rather than in-person. And then, as the picture started looking bleaker, my friends and I began discussing broader community- and state-level actions that were needed to confront the impending crisis. We put out a blog (Needed: Bold Decisions to Stop Covid-19) and a change.org petition on March 12, calling for suspension of in-person activities at schools, universities and other places of gathering. Around this time, I started laying my hands on daily data about the spread of corona virus in the US.

This blog is based on looking at the data over the last few days, trying to get a sense of how bad things are, their trends, and whether institutional measures are having a mitigating effect. My analysis is based on daily data from https://covidtracking.com/; see the section on “Data Source” and “Data Limitations and Data Quality” for a discussion of data limitations and the need to interpret any analyses cautiously. The raw numbers are listed at the bottom of the blog.

Number Tested (Results) and Percentage Infected

For many weeks after this crisis hit the US, the main story was the growing number of infections and the lack of testing. During March, testing capacity has increased rapidly - from about 500 tests per day on March 2 to 50,000 tests per day on March 22, and now 100,000 on March 26 - although some states still aren’t testing much.

We see a huge growth in infections (> 15,000 in the US each of the last few days), and part of it is due to increased testing. But, is the new infections curve becoming linear rather than exponential? If so, that would be some good news. Still, before making any strong opinion on this, you might want to check the section “Data Limitations and Data Quality”.

Is the Lockdown Sensible?

The big question - apart from “what is happening” - is “what should we do about it?” We’ve seen several measures such as lockdowns at the state and federal level.

First, there is no question that significant restrictions - such as a lockdown - are needed. Despite some who argue that this is an overreaction, the reality is that the infection has spread undetected among the population, that many more people have the virus than we know, and these unknown asymptomatic individuals will keep propogating the spread. Slowing the spread down - which the restrictions do - will enable us to “flatten the curve” and make it less unmanageable for hospitals and other responders. There are even others who argue that current lockdown measures are too untargeted (and based on data which is highly unprecise) - and that a more precise targeting would still limit the spread but reduce the accompanying harm (see, e.g., https://www.dailywire.com/news/stanford-professor-data-indicates-were-overreacting-to-coronavirus). The criticism is that we’re using the big cannons to shoot a few ants. But that misses the point. Sure, if we could compute a precise targeting solution, we should. But we need good data for that, which is not available. Moreover, even if we could, what looks like a precise targeted multidimensional action plan to an expert will appear vague and ambiguous to the general public. A general lockdown, on the other hand, is more likely to be enforced and implemented.

Is the Lockdown Working, and How to Bend the Curve??

What do the numbers tell us about whether the situation is getting better or worse, and at what rate? Are the control measures working? There are many different measures to consider, each tells a different story. One metric everyone is interested in is “how quickly is the cumulative number of known infections growing each day?” For instance, if we had 100 known infections until yesterday, and then learnt about another 20 new infections in the last day, then the growth rate (over cumulative) is 20%. Is this growth rate slowing down? Let’s look at these numbers, but first note some important caveats.

  • Results will lag actions by about 10-15 days: the time before people get tested, the time for test results, and some extra days to account for people really changing their behavior.

Lesson: Don’t conclude that the measures are not working just because you don’t observe quick results.

  • Volume of past-infected people still in the population. If this number is high, then even if the spread slows down, the available mass of infected people will continue to produce more positive test results as they get tested. So, even longer time lag to see the effects of measures.

There’s some “slowdown in the growth rate”, with daily growth rate moving from about 40% to 20%. An important aspect of looking at the data is that “signals” (measured infections) lag the “event” (someone getting infected) by 10-15 days, so it is notable that signs of slowdown are emerging about 2 weeks after many states (and later the US) adopted restrictions.

From the growth rate r we can quickly estimate the number of days d(r) for infections to double. The relationship is (1+r)^d = 2. In other words, Log(2) = d*log(1+r), so that d = log(2)/log(1+r). (Note: log = with base e.) We’re seeing very rapid doubling in some countries, e.g., in Spain it is about 2 days to double.

At a 40% growth rate, the total number of infections doubles almost every 2 days. If we can reduce the rate of growth from 40% to 30% to 25%, the doubling-period goes up from about 2 days to 2.6 days to about 3.1 days. Then reducing again from 25% to 20% growth rate takes us from 3.1 days to 3.8 days, and then if we reduce again to 10% it goes up to over 7 days!

New Infections and Rate of Positive Results

Another metric to look at is the percentage of positive test results each day. This number is huge, but look for the change over time.

  • At one extreme it could be that a large-enough segment of the population was infected some days ago - and there are no new infections since then - but as we’re testing more people we’re catching more infected ones.

  • At the other extreme, it is that more people are getting infected each day - and we’re seeing exponentially more - and that is why they show up in the results when we test more people.

To visualize this, suppose that at some day, the mix of infected and non-infected people looked like the picture below. The red dots are infected individuals, the orange ones are not infected but otherwise indistinguishable from them, and the green ones are healthy. The left panel is the picture at some time, and the next panel a few days later.

Extreme Best Case: No spread in infection

Suppose that the red-orange-green status and mix remained constant. That is, many people are already infected - but no more new infections! Now imagine a circular net thrown into the left panel, representing people we picked up to test one day. The number of positive results for the day (new infections) will depend on the size of the net, the method for picking whom to test (we’ll ignore this for a moment), and the mix of red and orange (which remains constant). Therefore, if we didn’t change the method for picking whom to test, then the number of positive test results should be somewhat proportional to the size of the net. The more you test, the more show up infected - but the proportion or percentage of people who show up positive should remain the same regardless of the size of the net. (Recall this is the case where the red-orange status remains static.)

The third panel shows what percentage of daily test results are positive (again, with caveats - no change in the method for deciding whom to test, etc.). The percentage is up and down a bit, and increasing. This suggests we’re somewhere between the two extremes discussed. If there were no new infections the positive rate would have been nearly flat (again, assuming we aren’t picking more from the “more likely to be infected” group). Any uptick in “% infections” is of concern.

Any Conclusions?

A few things.

Next, we’ll want to look at state level data. We do this below - but with a huge caveat: state-level numbers are still too sketchy and finicky, so any insights are probably even more faulty.

State-Level Analysis

Growth Rates in States

States with Early Hits but Early Decisive Action

California

California experienced the earliest known covid19 cases in the US, starting in January-February, in both the Bay Area and in Davis/Sacramento. Early in March, Bay Area counties starting imposing movement restrictions, and California Governor Gavin Newsom displayed great leadership in taking stock of the situation quickly and taking decision action. Statewide lockdowns came into effect in mid-March, and many universities and schools had already announced suspension of normal activity before that.

The reported number of infections grew in the state during March, but both absolute numbers and growth rates have been below that of, say, New York. However, California hasn’t done well in terms of testing - too few, lengthy delays, and inconsistent reporting from counties and private labs. As of the end of March, only about 25,000 total test results have been reported since the start, and almost 60,000 tests are pending!

Finally, backlog clears on April 4, also resulting in a jump in new infections. But it is not too high (see the % positive results relative to total new results). Let’s wait a few days for steady state data.

The rate of positive test results each is also a problematic metric because of reporting problems (some days negative results are not reported at all) and all the pending tests. The daily growth rate has converged to around 15-20%, but the lack of data quality does raise concern about what the situation really is.

New York

New York has been the epicenter in the US, lots of infections (and deaths) - but the growth rate of infections is finally slowing down, and hopefully the death rate will too in about 10-15 days. New York has done well in testing.

Washington

Washington was an early state in terms of covid19 infections, especially in King County. But the state has seemed to done exceptionally well in managing the situation since then, not least because of early and decisive action and good testing.

Massachusetts

Massachusetts was also one of the early hit states, with the Biogen spread. Things have sort of been under control since then, but I’m still cautious about the situation here.

States with Less Decisive and Delayed Actions

AL

AZ

GA

Texas

Florida

Louisiana

Virginia

North Dakota

Some Other States

Illinois

Kentucky

Michigan

Data Source (US numbers)

The first question is where to get the data, whose data to believe? For instance, on March 18 morning, the New York Times’ updated number (March 18, 10 am, based on Johns Hopkins University) was 5,879, but the Johns Hopkins page itself showed 6,519 confirmed cases. The CDC puts out numbers daily (updated at 4pm ET) but this appears to be a substantial undercount relative to others: 4,226. This site shows a history of daily numbers (in US at 4pm EDT): https://covidtracking.com/, with a March 17 update of 5,723 cases.

I’ll use the covidtracking site in this analysis, mainly because it provides a running table of data vs. just current reports. Here’s a look at the data. n.states is the number of states with known infections (including Puerto Rico and other territories). The next 3 columns are about known test results (positive, negative, total) and pending results.

date n.states n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 56 491156 2028486 17444 48344 50559 12688 1174 5937 41 23322 18356 2519642
2020-04-09 56 458474 1916737 17631 46665 48344 12244 924 5794 39 21162 16424 2375211
2020-04-08 56 424391 1788294 17228 41095 47154 9927 1013 4131 216 19378 14547 2212685
2020-04-07 56 394210 1678891 16557 39677 45500 9875 889 4076 151 18477 12646 2073101
2020-04-06 56 363800 1561229 17292 32210 43198 6943 814 2961 147 16584 10720 1925029
2020-04-05 56 335069 1440733 17307 27909 40223 5499 760 652 147 14542 9554 1775802
2020-04-04 56 309097 1344104 15573 26374 37667 5209 554 656 147 12840 8379 1653201
2020-04-03 56 275542 1148372 61980 23825 33501 4811 486 605 147 10861 7026 1423914
2020-04-02 56 243462 1048251 62101 21135 30198 4410 456 574 140 8586 5835 1291713
2020-04-01 56 215381 954534 59669 19408 26057 3937 407 561 140 7084 4746 1169915
2020-03-31 56 190096 876287 59518 17353 22167 3487 236 507 NA 5666 3803 1066383
2020-03-30 56 165597 793614 65369 15216 18511 3087 187 451 NA 4560 2983 959211
2020-03-29 56 144391 696372 65545 13501 16263 2456 156 439 NA 4061 2467 840763
2020-03-28 56 124897 622779 65709 11872 13749 2174 140 390 NA 3148 2001 747676
2020-03-27 56 105474 534249 60091 10511 11542 1792 124 324 NA 2422 1574 639723
2020-03-26 56 86793 442281 60251 7387 9147 1299 91 258 NA 97 1208 529074
2020-03-25 56 69492 363191 51235 740 5436 NA 74 167 NA 147 931 432683
2020-03-24 56 52561 296585 14433 369 4091 NA NA NA NA NA 706 349146
2020-03-23 56 42596 240160 14571 67 3258 NA NA NA NA NA 509 282756
2020-03-22 56 32319 195106 2842 56 2498 NA NA NA NA NA 426 227425
2020-03-21 56 23670 157536 3468 NA 1964 NA NA NA NA NA 297 181206
2020-03-20 56 17422 118970 3330 NA NA NA NA NA NA NA 247 136392
2020-03-19 56 12070 88939 3016 NA NA NA NA NA NA NA 185 101009
2020-03-18 56 8098 67168 2526 NA NA NA NA NA NA NA 142 75266
2020-03-17 56 6031 48053 1687 NA NA NA NA NA NA NA 119 54084
2020-03-16 56 4298 36104 1691 NA NA NA NA NA NA NA 97 40402
2020-03-15 51 3452 22624 2242 NA NA NA NA NA NA NA 76 26076
2020-03-14 51 2672 17102 1236 NA NA NA NA NA NA NA 63 19774
2020-03-13 51 2164 13613 1130 NA NA NA NA NA NA NA 55 15777
2020-03-12 51 1519 8041 673 NA NA NA NA NA NA NA 51 9560
2020-03-11 51 1260 6106 563 NA NA NA NA NA NA NA 43 7366
2020-03-10 51 1005 3812 469 NA NA NA NA NA NA NA 37 4817
2020-03-09 51 793 3344 313 NA NA NA NA NA NA NA 35 4137
2020-03-08 51 562 2335 347 NA NA NA NA NA NA NA 31 2897
2020-03-07 51 421 1839 602 NA NA NA NA NA NA NA 27 2260
2020-03-06 37 296 1588 458 NA NA NA NA NA NA NA 26 1884
2020-03-05 25 204 970 197 NA NA NA NA NA NA NA 20 1174
2020-03-04 15 157 759 103 NA NA NA NA NA NA NA 16 916
2020-03-03 2 60 6 NA NA NA NA NA NA NA NA 14 66
2020-03-02 2 35 NA NA NA NA NA NA NA NA NA 11 NA
2020-03-01 2 31 NA NA NA NA NA NA NA NA NA 8 NA
2020-02-29 1 18 NA NA NA NA NA NA NA NA NA 5 NA
2020-02-28 1 9 NA NA NA NA NA NA NA NA NA 4 NA

Data Limitations and Data Quality

One could look at state-level data (as I do below, just as an exercise to see how a few specific states are doing), but the same occurs there because state data is just an aggregate of county-level reporting, and so on. I’d love to get a hold of every individual-level (or transactional) data.

Current data are very sketchy - data-driven analysis is still needed - but tread cautiously.

With that said, let’s see what we have, see what clues are contained in the data … but, at the end, interpret all results cautiously.

State-Level Numbers

date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 CA 19472 145391 13900 2897 NA 1145 NA NA NA NA 514 164863
2020-04-09 CA 18309 145191 14100 2825 NA 1132 NA NA NA NA 492 163500
2020-04-08 CA 16957 127307 14600 2714 NA 1154 NA NA NA NA 442 144264
2020-04-07 CA 15865 115364 14100 2611 NA 1108 NA NA NA NA 374 131229
2020-04-06 CA 14336 103095 15000 2509 NA 1085 NA NA NA NA 343 117431
2020-04-05 CA 13438 103095 15000 2398 NA 1040 NA NA NA NA 319 116533
2020-04-04 CA 12026 101674 13000 2300 NA 1008 NA NA NA NA 276 113700
2020-04-03 CA 10701 24599 59500 2188 NA 901 NA NA NA NA 237 35300
2020-04-02 CA 9191 23809 59500 1922 NA 816 NA NA NA NA 203 33000
2020-04-01 CA 8155 21772 57400 1855 NA 774 NA NA NA NA 171 29927
2020-03-31 CA 7482 21772 57400 1617 NA 657 NA NA NA NA 153 29254
2020-03-30 CA 6447 20549 64400 1432 NA 597 NA NA NA NA 133 26996
2020-03-29 CA 5708 20549 64400 1034 NA 410 NA NA NA NA 123 26257
2020-03-28 CA 4643 20549 64400 1034 NA 410 NA NA NA NA 101 25192
2020-03-27 CA 3879 17380 57400 746 NA 200 NA NA NA NA 78 21259
2020-03-26 CA 3006 17380 57400 NA NA NA NA NA NA NA 65 20386
2020-03-25 CA 2355 15921 48600 NA NA NA NA NA NA NA 53 18276
2020-03-24 CA 2102 13452 12100 NA NA NA NA NA NA NA 40 15554
2020-03-23 CA 1733 12567 12100 NA NA NA NA NA NA NA 27 14300
2020-03-22 CA 1536 11304 NA NA NA NA NA NA NA NA 27 12840
2020-03-21 CA 1279 11249 NA NA NA NA NA NA NA NA 24 12528
2020-03-20 CA 1063 10424 NA NA NA NA NA NA NA NA 20 11487
2020-03-19 CA 924 8787 NA NA NA NA NA NA NA NA 18 9711
2020-03-18 CA 611 7981 NA NA NA NA NA NA NA NA 13 8592
2020-03-17 CA 483 7981 NA NA NA NA NA NA NA NA 11 8464
2020-03-16 CA 335 7981 NA NA NA NA NA NA NA NA 6 8316
2020-03-15 CA 293 916 NA NA NA NA NA NA NA NA 5 1209
2020-03-14 CA 252 916 NA NA NA NA NA NA NA NA 5 1168
2020-03-13 CA 202 916 NA NA NA NA NA NA NA NA 4 1118
2020-03-12 CA 202 916 NA NA NA NA NA NA NA NA 4 1118
2020-03-11 CA 157 916 NA NA NA NA NA NA NA NA NA 1073
2020-03-10 CA 133 690 NA NA NA NA NA NA NA NA NA 823
2020-03-09 CA 114 690 NA NA NA NA NA NA NA NA NA 804
2020-03-08 CA 88 462 NA NA NA NA NA NA NA NA NA 550
2020-03-07 CA 69 462 NA NA NA NA NA NA NA NA NA 531
2020-03-06 CA 60 462 NA NA NA NA NA NA NA NA NA 522
2020-03-05 CA 53 462 NA NA NA NA NA NA NA NA NA 515
2020-03-04 CA 53 462 NA NA NA NA NA NA NA NA NA 515
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 MA 20974 81398 NA NA 1956 NA NA NA NA NA 599 102372
2020-04-09 MA 18941 76017 NA NA 1747 NA NA NA NA NA 503 94958
2020-04-08 MA 16790 70721 NA NA 1583 NA NA NA NA NA 433 87511
2020-04-07 MA 15202 66142 NA NA 1435 NA NA NA NA NA 356 81344
2020-04-06 MA 13837 62592 NA NA 1241 NA NA NA NA NA 260 76429
2020-04-05 MA 12500 59437 NA NA 1145 NA NA NA NA NA 231 71937
2020-04-04 MA 11736 57064 NA NA 1068 NA NA NA NA NA 216 68800
2020-04-03 MA 10402 52560 NA NA 966 NA NA NA NA NA 192 62962
2020-04-02 MA 8966 47642 NA NA 813 NA NA NA NA NA 154 56608
2020-04-01 MA 7738 44000 NA NA 682 NA NA NA NA NA 122 51738
2020-03-31 MA 6620 40315 NA NA 562 NA NA NA NA NA 89 46935
2020-03-30 MA 5752 37041 NA NA 453 NA NA NA NA NA 56 42793
2020-03-29 MA 4955 34111 NA NA 399 NA NA NA NA NA 48 39066
2020-03-28 MA 4257 30792 NA NA 350 NA NA NA NA NA 44 35049
2020-03-27 MA 3240 26131 NA NA 219 NA NA NA NA NA 35 29371
2020-03-26 MA 2417 21204 NA NA 219 NA NA NA NA NA 25 23621
2020-03-25 MA 1838 17956 NA NA 103 NA NA NA NA NA 15 19794
2020-03-24 MA 1159 12590 NA NA 94 NA NA NA NA NA 11 13749
2020-03-23 MA 777 8145 NA NA 79 NA NA NA NA NA 9 8922
2020-03-22 MA 646 5459 NA NA 71 NA NA NA NA NA 5 6105
2020-03-21 MA 525 4752 NA NA 61 NA NA NA NA NA 1 5277
2020-03-20 MA 413 3678 NA NA NA NA NA NA NA NA 1 4091
2020-03-19 MA 328 2804 NA NA NA NA NA NA NA NA NA 3132
2020-03-18 MA 256 2015 NA NA NA NA NA NA NA NA NA 2271
2020-03-17 MA 218 1541 NA NA NA NA NA NA NA NA NA 1759
2020-03-16 MA 164 352 NA NA NA NA NA NA NA NA NA 516
2020-03-15 MA 138 352 NA NA NA NA NA NA NA NA NA 490
2020-03-14 MA 138 352 NA NA NA NA NA NA NA NA NA 490
2020-03-13 MA 123 92 NA NA NA NA NA NA NA NA NA 215
2020-03-12 MA 95 NA NA NA NA NA NA NA NA NA NA NA
2020-03-11 MA 92 NA NA NA NA NA NA NA NA NA NA NA
2020-03-10 MA 92 NA NA NA NA NA NA NA NA NA NA NA
2020-03-09 MA 41 NA NA NA NA NA NA NA NA NA NA NA
2020-03-08 MA 13 NA NA NA NA NA NA NA NA NA NA NA
2020-03-07 MA 13 NA NA NA NA NA NA NA NA NA NA NA
2020-03-06 MA 8 NA NA NA NA NA NA NA NA NA NA NA
2020-03-05 MA 2 NA NA NA NA NA NA NA NA NA NA NA
2020-03-04 MA 2 NA NA NA NA NA NA NA NA NA NA NA
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 WA 9608 83391 NA 639 NA 181 NA NA NA NA 446 92999
2020-04-09 WA 9608 83391 NA 639 NA 181 NA NA NA NA 446 92999
2020-04-08 WA 9608 83391 NA 639 NA 181 NA NA NA NA 446 92999
2020-04-07 WA 9117 83391 NA 641 NA 190 NA NA NA NA 393 92508
2020-04-06 WA 8775 83391 NA 638 NA 191 NA NA NA NA 378 92166
2020-04-05 WA 8434 80327 NA NA NA NA NA NA NA NA 365 88761
2020-04-04 WA 8038 75633 NA NA NA NA NA NA NA NA 345 83671
2020-04-03 WA 7633 72833 NA NA NA NA NA NA NA NA 325 80466
2020-04-02 WA 7021 68814 NA NA NA NA NA NA NA NA 296 75835
2020-04-01 WA 6645 60566 NA NA NA NA NA NA NA NA 270 67211
2020-03-31 WA 6048 60566 NA NA NA NA NA NA NA NA 252 66614
2020-03-30 WA 5566 60566 NA NA NA NA NA NA NA NA 239 66132
2020-03-29 WA 5116 54896 NA NA NA NA NA NA NA NA 228 60012
2020-03-28 WA 4720 49015 NA NA NA NA NA NA NA NA 211 53735
2020-03-27 WA 4228 43173 NA NA NA NA NA NA NA NA 191 47401
2020-03-26 WA 3727 31712 NA NA NA NA NA NA NA NA 177 35439
2020-03-25 WA 3259 31712 NA NA NA NA NA NA NA NA 155 34971
2020-03-24 WA 2810 31712 NA NA NA NA NA NA NA NA 142 34522
2020-03-23 WA 2440 28879 NA NA NA NA NA NA NA NA 133 31319
2020-03-22 WA 2233 25328 NA NA NA NA NA NA NA NA 122 27561
2020-03-21 WA 1997 21719 NA NA NA NA NA NA NA NA 108 23716
2020-03-20 WA 1765 19336 NA NA NA NA NA NA NA NA 102 21101
2020-03-19 WA 1527 15918 NA NA NA NA NA NA NA NA 91 17445
2020-03-18 WA 1380 13117 NA NA NA NA NA NA NA NA 81 14497
2020-03-17 WA 1211 11582 NA NA NA NA NA NA NA NA 77 12793
2020-03-16 WA 1048 9451 NA NA NA NA NA NA NA NA 68 10499
2020-03-15 WA 921 7122 NA NA NA NA NA NA NA NA 56 8043
2020-03-14 WA 790 6001 NA NA NA NA NA NA NA NA 51 6791
2020-03-13 WA 691 4350 NA NA NA NA NA NA NA NA 47 5041
2020-03-12 WA 541 3037 NA NA NA NA NA NA NA NA 44 3578
2020-03-11 WA 472 2175 NA NA NA NA NA NA NA NA 40 2647
2020-03-10 WA 389 1110 NA NA NA NA NA NA NA NA 37 1499
2020-03-09 WA 342 1110 NA NA NA NA NA NA NA NA 35 1452
2020-03-08 WA 245 640 60 NA NA NA NA NA NA NA 31 885
2020-03-07 WA 180 370 66 NA NA NA NA NA NA NA 27 550
2020-03-06 WA 149 370 NA NA NA NA NA NA NA NA 26 519
2020-03-05 WA 96 NA NA NA NA NA NA NA NA NA 20 NA
2020-03-04 WA 76 NA NA NA NA NA NA NA NA NA 16 NA
2020-03-03 WA 58 NA NA NA NA NA NA NA NA NA 14 NA
2020-03-02 WA 34 NA NA NA NA NA NA NA NA NA 11 NA
2020-03-01 WA 30 NA NA NA NA NA NA NA NA NA 8 NA
2020-02-29 WA 18 NA NA NA NA NA NA NA NA NA 5 NA
2020-02-28 WA 9 NA NA NA NA NA NA NA NA NA 4 NA
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 NY 170512 247373 NA 18569 33159 4908 NA NA NA 14590 7844 417885
2020-04-09 NY 159937 231612 NA 18279 32869 4925 NA NA NA 14590 7067 391549
2020-04-08 NY 149316 215837 NA 18079 32669 4593 NA NA NA 14590 6268 365153
2020-04-07 NY 138863 201195 NA 17493 32083 4593 NA NA NA 14590 5489 340058
2020-04-06 NY 130689 190122 NA 16837 30203 4504 NA NA NA 13366 4758 320811
2020-04-05 NY 122031 180249 NA 16479 28092 4376 NA NA NA 12187 4159 302280
2020-04-04 NY 113704 169917 NA 15905 26383 4126 NA NA NA 10478 3565 283621
2020-04-03 NY 102863 157657 NA 14810 23696 3731 NA NA NA 8886 2935 260520
2020-04-02 NY 92381 146584 NA 13383 20817 3396 NA NA NA 7434 2373 238965
2020-04-01 NY 83712 137168 NA 12226 18368 3022 NA NA NA 6142 1941 220880
2020-03-31 NY 75795 129391 NA 10929 15904 2710 NA NA NA 4975 1550 205186
2020-03-30 NY 66497 119971 NA 9517 13721 2352 NA NA NA 4204 1218 186468
2020-03-29 NY 59513 112847 NA 8503 12075 2037 NA NA NA 3572 965 172360
2020-03-28 NY 52318 103616 NA 7328 10054 1755 NA NA NA 2726 728 155934
2020-03-27 NY 44635 101118 NA 6481 8526 1583 NA NA NA 2045 519 145753
2020-03-26 NY 37258 84846 NA 5327 6844 1290 NA NA NA NA 385 122104
2020-03-25 NY 30811 72668 NA NA 3805 NA NA NA NA NA 285 103479
2020-03-24 NY 25665 65605 NA NA 3234 NA NA NA NA NA 210 91270
2020-03-23 NY 20875 57414 NA NA 2635 NA NA NA NA NA 114 78289
2020-03-22 NY 15168 46233 NA NA 1974 NA NA NA NA NA 114 61401
2020-03-21 NY 10356 35081 NA NA 1603 NA NA NA NA NA 44 45437
2020-03-20 NY 7102 25325 NA NA NA NA NA NA NA NA 35 32427
2020-03-19 NY 4152 18132 NA NA NA NA NA NA NA NA 12 22284
2020-03-18 NY 2382 12215 NA NA NA NA NA NA NA NA 12 14597
2020-03-17 NY 1700 5506 NA NA NA NA NA NA NA NA 7 7206
2020-03-16 NY 950 4543 NA NA NA NA NA NA NA NA 7 5493
2020-03-15 NY 729 4543 NA NA NA NA NA NA NA NA 3 5272
2020-03-14 NY 524 2779 NA NA NA NA NA NA NA NA NA 3303
2020-03-13 NY 421 2779 NA NA NA NA NA NA NA NA NA 3200
2020-03-12 NY 216 92 NA NA NA NA NA NA NA NA NA 308
2020-03-11 NY 216 92 NA NA NA NA NA NA NA NA NA 308
2020-03-10 NY 173 92 NA NA NA NA NA NA NA NA NA 265
2020-03-09 NY 142 92 NA NA NA NA NA NA NA NA NA 234
2020-03-08 NY 105 92 NA NA NA NA NA NA NA NA NA 197
2020-03-07 NY 76 92 236 NA NA NA NA NA NA NA NA 168
2020-03-06 NY 33 92 236 NA NA NA NA NA NA NA NA 125
2020-03-05 NY 22 76 24 NA NA NA NA NA NA NA NA 98
2020-03-04 NY 6 48 24 NA NA NA NA NA NA NA NA 54
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 FL 17531 145299 1411 NA 2487 NA NA NA NA NA 390 162830
2020-04-09 FL 16364 136185 1395 NA 2268 NA NA NA NA NA 354 152549
2020-04-08 FL 15455 127679 1324 NA 2062 NA NA NA NA NA 309 143134
2020-04-07 FL 14747 123415 1407 NA 1999 NA NA NA NA NA 296 138162
2020-04-06 FL 13324 109950 1142 NA 1682 NA NA NA NA NA 236 123274
2020-04-05 FL 12151 101253 1129 NA 1572 NA NA NA NA NA 218 113404
2020-04-04 FL 11111 90956 1281 NA 1462 NA NA NA NA NA 191 102067
2020-04-03 FL 9585 82137 1225 NA 1287 NA NA NA NA NA 163 91722
2020-04-02 FL 8010 69286 1285 NA 1123 NA NA NA NA NA 128 77296
2020-04-01 FL 6955 59529 1235 NA 949 NA NA NA NA NA 87 66484
2020-03-31 FL 6338 54285 1163 NA 823 NA NA NA NA NA 77 60623
2020-03-30 FL 5473 48225 NA NA 652 NA NA NA NA NA 63 53698
2020-03-29 FL 4246 39070 NA NA 594 NA NA NA NA NA 56 43316
2020-03-28 FL 3763 35366 NA NA 526 NA NA NA NA NA 54 39129
2020-03-27 FL 2765 28186 1517 NA 456 NA NA NA NA NA 34 30951
2020-03-26 FL 2355 23741 1443 NA 406 NA NA NA NA NA 28 26096
2020-03-25 FL 1682 15374 1233 NA 316 NA NA NA NA NA 22 17056
2020-03-24 FL 1412 13127 1008 NA 259 NA NA NA NA NA 18 14539
2020-03-23 FL 1171 11063 860 NA 217 NA NA NA NA NA 14 12234
2020-03-22 FL 830 7990 963 NA 185 NA NA NA NA NA 13 8820
2020-03-21 FL 658 6579 1002 NA 158 NA NA NA NA NA 12 7237
2020-03-20 FL 520 1870 1026 NA NA NA NA NA NA NA 10 2390
2020-03-19 FL 390 1533 1019 NA NA NA NA NA NA NA 8 1923
2020-03-18 FL 314 1225 954 NA NA NA NA NA NA NA 7 1539
2020-03-17 FL 186 940 872 NA NA NA NA NA NA NA 6 1126
2020-03-16 FL 141 684 514 NA NA NA NA NA NA NA 4 825
2020-03-15 FL 116 678 454 NA NA NA NA NA NA NA 4 794
2020-03-14 FL 77 478 221 NA NA NA NA NA NA NA 3 555
2020-03-13 FL 50 478 221 NA NA NA NA NA NA NA 2 528
2020-03-12 FL 32 301 147 NA NA NA NA NA NA NA 2 333
2020-03-11 FL 28 301 147 NA NA NA NA NA NA NA 2 329
2020-03-10 FL 19 222 155 NA NA NA NA NA NA NA NA 241
2020-03-09 FL 18 140 115 NA NA NA NA NA NA NA NA 158
2020-03-08 FL 17 118 108 NA NA NA NA NA NA NA NA 135
2020-03-07 FL 14 100 88 NA NA NA NA NA NA NA NA 114
2020-03-06 FL 9 55 51 NA NA NA NA NA NA NA NA 64
2020-03-05 FL 9 31 69 NA NA NA NA NA NA NA NA 40
2020-03-04 FL 2 24 16 NA NA NA NA NA NA NA NA 26
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 IL 17887 69640 NA 3680 NA 1166 NA 821 NA NA 596 87527
2020-04-09 IL 16422 64435 NA 3680 NA 1166 NA 821 NA NA 528 80857
2020-04-08 IL 15078 59988 NA 3680 NA 1166 NA 821 NA NA 462 75066
2020-04-07 IL 13549 55183 NA 3680 NA 1166 NA 821 NA NA 380 68732
2020-04-06 IL 12262 50680 NA NA NA NA NA NA NA NA 307 62942
2020-04-05 IL 11256 47727 NA NA NA NA NA NA NA NA 274 58983
2020-04-04 IL 10357 43224 NA NA NA NA NA NA NA NA 243 53581
2020-04-03 IL 8904 39144 NA NA NA NA NA NA NA NA 210 48048
2020-04-02 IL 7695 35961 NA NA NA NA NA NA NA NA 157 43656
2020-04-01 IL 6980 33404 NA NA NA NA NA NA NA NA 141 40384
2020-03-31 IL 5994 29231 NA NA NA NA NA NA NA NA 99 35225
2020-03-30 IL 5057 25389 NA NA NA NA NA NA NA NA 73 30446
2020-03-29 IL 4596 23166 NA NA NA NA NA NA NA NA 65 27762
2020-03-28 IL 3491 22000 NA NA NA NA NA NA NA NA 47 25491
2020-03-27 IL 3026 18516 NA NA NA NA NA NA NA NA 34 21542
2020-03-26 IL 2538 14093 NA NA NA NA NA NA NA NA 26 16631
2020-03-25 IL 1865 12344 NA NA NA NA NA NA NA NA 19 14209
2020-03-24 IL 1535 9934 NA NA NA NA NA NA NA NA 16 11469
2020-03-23 IL 1273 8583 NA NA NA NA NA NA NA NA 12 9856
2020-03-22 IL 1049 7271 NA NA NA NA NA NA NA NA 9 8320
2020-03-21 IL 753 5488 NA NA NA NA NA NA NA NA 6 6241
2020-03-20 IL 585 3696 NA NA NA NA NA NA NA NA 5 4281
2020-03-19 IL 422 2725 NA NA NA NA NA NA NA NA 4 3147
2020-03-18 IL 288 1763 NA NA NA NA NA NA NA NA 1 2051
2020-03-17 IL 159 1340 NA NA NA NA NA NA NA NA 1 1499
2020-03-16 IL 93 932 NA NA NA NA NA NA NA NA NA 1025
2020-03-15 IL 64 449 195 NA NA NA NA NA NA NA NA 513
2020-03-14 IL 46 316 82 NA NA NA NA NA NA NA NA 362
2020-03-13 IL 32 294 92 NA NA NA NA NA NA NA NA 326
2020-03-12 IL 25 266 76 NA NA NA NA NA NA NA NA 291
2020-03-11 IL 19 244 63 NA NA NA NA NA NA NA NA 263
2020-03-10 IL 19 244 63 NA NA NA NA NA NA NA NA 263
2020-03-09 IL 7 191 44 NA NA NA NA NA NA NA NA 198
2020-03-08 IL 6 191 44 NA NA NA NA NA NA NA NA 197
2020-03-07 IL 6 191 44 NA NA NA NA NA NA NA NA 197
2020-03-06 IL 5 180 35 NA NA NA NA NA NA NA NA 185
2020-03-05 IL 5 165 27 NA NA NA NA NA NA NA NA 170
2020-03-04 IL 4 124 27 NA NA NA NA NA NA NA NA 128
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 VA 4509 30950 521 1238 772 457 NA 287 NA NA 121 35459
2020-04-09 VA 4042 28984 627 669 685 469 NA 285 NA NA 109 33026
2020-04-08 VA 3645 27000 NA NA 615 NA 145 NA 108 NA 75 30645
2020-04-07 VA 3333 25312 NA NA 563 NA 145 NA 108 NA 63 28645
2020-04-06 VA 2878 21643 NA NA 497 NA 145 NA 108 NA 54 24521
2020-04-05 VA 2637 21034 NA NA 431 NA 145 NA 108 NA 51 23671
2020-04-04 VA 2407 19145 NA NA 390 NA 145 NA 108 NA 52 21552
2020-04-03 VA 2012 16993 NA NA 312 NA 145 NA 108 NA 46 19005
2020-04-02 VA 1706 15883 NA 246 305 NA 145 NA 108 NA 41 17589
2020-04-01 VA 1484 13860 NA NA 305 NA 145 NA 108 NA 34 15344
2020-03-31 VA 1250 12151 NA NA 165 NA NA NA NA NA 27 13401
2020-03-30 VA 1020 11018 NA NA 136 NA NA NA NA NA 25 12038
2020-03-29 VA 890 9719 NA NA 112 NA NA NA NA NA 22 10609
2020-03-28 VA 739 8427 NA NA 99 NA NA NA NA NA 17 9166
2020-03-27 VA 604 6733 NA NA 83 NA NA NA NA NA 14 7337
2020-03-26 VA 460 5729 NA NA 65 NA NA NA NA NA 13 6189
2020-03-25 VA 391 4979 NA NA 59 NA NA NA NA NA 9 5370
2020-03-24 VA 290 4180 NA NA 45 NA NA NA NA NA 7 4470
2020-03-23 VA 254 3443 NA NA 38 NA NA NA NA NA 6 3697
2020-03-22 VA 219 3118 NA NA 32 NA NA NA NA NA 3 3337
2020-03-21 VA 152 2638 NA NA 25 NA NA NA NA NA 2 2790
2020-03-20 VA 114 2211 NA NA NA NA NA NA NA NA 2 2325
2020-03-19 VA 94 1829 NA NA NA NA NA NA NA NA 2 1923
2020-03-18 VA 77 1201 NA NA NA NA NA NA NA NA 1 1278
2020-03-17 VA 67 961 NA NA NA NA NA NA NA NA 1 1028
2020-03-16 VA 51 438 NA NA NA NA NA NA NA NA 1 489
2020-03-15 VA 45 363 NA NA NA NA NA NA NA NA 1 408
2020-03-14 VA 30 117 NA NA NA NA NA NA NA NA NA 147
2020-03-13 VA 30 117 NA NA NA NA NA NA NA NA NA 147
2020-03-12 VA 17 117 NA NA NA NA NA NA NA NA NA 134
2020-03-11 VA 9 60 NA NA NA NA NA NA NA NA NA 69
2020-03-10 VA 8 53 NA NA NA NA NA NA NA NA NA 61
2020-03-09 VA 3 38 9 NA NA NA NA NA NA NA NA 41
2020-03-08 VA 2 36 6 NA NA NA NA NA NA NA NA 38
2020-03-07 VA 0 31 7 NA NA NA NA NA NA NA NA 31
2020-03-06 VA 0 21 10 NA NA NA NA NA NA NA NA 21
2020-03-05 VA 0 18 3 NA NA NA NA NA NA NA NA 18
date state n.pos n.neg n.pend n.hosp n.hosp.tot n.ICU n.ICU.tot n.vent n.vent.tot n.recov n.death n.result
2020-04-10 LA 19253 73027 NA 2054 NA NA NA 479 NA NA 755 92280
2020-04-09 LA 18283 68636 NA 2014 NA NA NA 473 NA NA 702 86919
2020-04-08 LA 17030 64376 NA 1983 NA NA NA 490 NA NA 652 81406
2020-04-07 LA 16284 58371 NA 1996 NA NA NA 519 NA NA 582 74655
2020-04-06 LA 14867 54299 NA 1981 NA NA NA 552 NA NA 512 69166
2020-04-05 LA 13010 47315 NA 1803 NA NA NA 561 NA NA 477 60325
2020-04-04 LA 12496 46002 NA 1726 NA NA NA 571 NA NA 409 58498
2020-04-03 LA 10297 43348 NA 1707 NA NA NA 535 NA NA 370 53645
2020-04-02 LA 9150 41936 NA 1639 NA NA NA 507 NA NA 310 51086
2020-04-01 LA 6424 39352 NA 1498 NA NA NA 490 NA NA 273 45776
2020-03-31 LA 5237 33730 NA 1355 NA NA NA 438 NA NA 239 38967
2020-03-30 LA 4025 30008 NA 1185 NA NA NA 385 NA NA 185 34033
2020-03-29 LA 3540 24331 NA 1127 NA NA NA 380 NA NA 151 27871
2020-03-28 LA 3315 21846 NA 927 NA NA NA 336 NA NA 137 25161
2020-03-27 LA 2746 18613 NA 773 NA NA NA 270 NA NA 119 21359
2020-03-26 LA 2305 15724 NA 676 NA NA NA 239 NA NA 83 18029
2020-03-25 LA 1795 9656 NA 491 NA NA NA 163 NA NA 65 11451
2020-03-24 LA 1388 7215 NA 271 NA NA NA NA NA NA 46 8603
2020-03-23 LA 1172 4776 NA NA NA NA NA NA NA NA 34 5948
2020-03-22 LA 837 2661 NA NA NA NA NA NA NA NA 20 3498
2020-03-21 LA 585 2180 NA NA NA NA NA NA NA NA 16 2765
2020-03-20 LA 479 568 NA NA NA NA NA NA NA NA 12 1047
2020-03-19 LA 347 458 NA NA NA NA NA NA NA NA 8 805
2020-03-18 LA 240 335 NA NA NA NA NA NA NA NA 6 575
2020-03-17 LA 171 286 NA NA NA NA NA NA NA NA 4 457
2020-03-16 LA 114 188 NA NA NA NA NA NA NA NA 2 302
2020-03-15 LA 91 156 NA NA NA NA NA NA NA NA 2 247
2020-03-14 LA 69 109 NA NA NA NA NA NA NA NA NA 178
2020-03-13 LA 36 37 NA NA NA NA NA NA NA NA NA 73
2020-03-12 LA 14 37 NA NA NA NA NA NA NA NA NA 51
2020-03-11 LA 6 37 NA NA NA NA NA NA NA NA NA 43
2020-03-10 LA 1 11 NA NA NA NA NA NA NA NA NA 12
2020-03-09 LA 1 5 NA NA NA NA NA NA NA NA NA 6
2020-03-08 LA 0 5 NA NA NA NA NA NA NA NA NA 5
2020-03-07 LA 0 NA NA NA NA NA NA NA NA NA NA NA