This document provides an overview and analysis of COVID-19 cases and projections globally and in several locations. It summarizes data sources and models used in the analysis. Updates are typically provided daily, with some delays possible due to the author's clinical responsibilities. Charts and figures with daily case, death, and testing data are analyzed to identify trends and project trajectories. Partisan lean is included as a metric to help understand outbreaks.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
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Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
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Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
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5th edition of the Diagnostic and Statistical Manual of Mental Disorders
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disorder called alcohol use disorder (AUD), with mild, moderate,
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In the DSM-5, all types of substance abuse and dependence have been
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New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
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The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Surgical Site Infections, pathophysiology, and prevention.pptx
COVID-19 Update (Summary): September 22, 2020
1. Caveats and Comments
1
Overview:
This is my analysis, not Stanford’s. My goal is to understand the trajectory of COVID. It is not confidential and can be freely shared. The R program code is
available at https://github.com/StevenLShafer/COVID19/. The daily analysis are available at https://1drv.ms/u/s!AuOyHP_aTIy7rowrt2AjGpWm_frnEQ?e=KBcNbh.
You are welcome to use the R code on GitHub for any purpose.
I am attempting to keep the analysis and commentary apolitical. I am now including partisan lean as a metric to help understand the epidemic. I occasionally point
out misrepresentations by government officials. I occasionally point out where government recommendations have placed Americans at increasing risk.
I try to provide a daily update in the morning, except Sundays. My analysis my be delayed by my clinical responsibilities as a Stanford anesthesiologist.
There is a lot of information on the figures. If something isn’t clear, please see the explanation on slide 2.
Data sources:
• USA Case Data: https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv
• USA Death Data: https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv
• USA Testing and Hospitalization Data: https://raw.githubusercontent.com/COVID19Tracking/covid-tracking-data/master/data/states_daily_4pm_et.csv
• Global Case Data: https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv
• Global Death Data: https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv
• Global Testing Data: https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv
• Mobility Data: https://www.gstatic.com/covid19/mobility/Global_Mobility_Report.csv
• Partisan Lean: MIT Election Data and Science Lab: https://doi.org/10.7910/DVN/VOQCHQ/HEIJCQ
• Ensemble Model: https://github.com/reichlab/covid19-forecast-hub/raw/master/data-processed/COVIDhub-ensemble/2020-xx-xx-COVIDhub-ensemble.csv
Models:
1. Future projections of case numbers are based on the Gompertz function (https://en.wikipedia.org/wiki/Gompertz_function): log 𝑐𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑐𝑎𝑠𝑒𝑠 =
𝑐𝑢𝑟𝑟𝑒𝑛𝑡 𝑐𝑎𝑠𝑒𝑠 + 𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑐𝑎𝑠𝑒𝑠 − 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 𝑐𝑎𝑠𝑒𝑠 1 − 𝑒−𝑘 𝑡 . This is a naïve asymptotic model. k is the rate constant, such that log(2) / k = time to 50%
rise. t is the number of days. Wikipedia The Gompertz function is estimated from the last 3 weeks of data for cumulative cases (red dots in the figures).
Deaths are predicted from a log linear regression of deaths over the past 21 days. For the US, and individual states, I am also including the 98% prediction
interval from the COVID-19 Forecast Hub (https://covid19forecasthub.org/).
2. The rate of change in daily cases and deaths is the slope of delta cases / day over the last 14 days, divided by the average number of cases.
Locations
The locations for the modeling are where Pamela and I have family and friends, locations of interest to friends and colleagues, or countries in the news (e.g.,
China, South Korea, Sweden, Brazil) or with significant economic impact on the United States (e.g., Japan, Canada, Mexico). Locations are easy to add.
Stay safe, well, resilient, and kind.
Steve Shafer
steven.shafer@Stanford.edu
2. 2,586,092
152,804
1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
100,000,000
Actual(points)/Predicted(line)
Phase
Pre-Model
Modeled
Deaths
Tests
USA projection as of 2020-05-27
0
10,000
20,000
30,000
0
2,000
4,000
6,000
Cases/Day
Deaths/Day
Cases: 1,662,302 (32,123) -- Deaths: 98,220 (829) -- Case Mortality: 5.9% -- Daily Change in Cases: -0.5%
Explanation of the Figures
2
Brown dots:
cumulative tests
Red dots: cumulative cases
used to estimate Gompertz
function, presently set to last
3 weeks
Red line: predicted cumulative
cases based on the Gompertz
function estimated from the red
dots
Red number: total cases
on June 30th, based on
the Gompertz function
estimated from the red
dots
Black number: total
Deaths on July 31th,
based on log-linear
regression of the past
21 days
Black line: predicted
cumulative deaths, based
on a log linear regression
of deaths over past 21
days.
Axis for deaths / day, usually
1/10th of the axis for cases /
day on the left side of the
figure.
Green line: linear regression
over 8 days, used to calculate
percent increase / decrease
(see below)
Daily change in cases,
calculated as the slope of the
green line (above left) /
number of new cases
yesterday.
Case mortality:
cumulative deaths
/ cumulative cases.
Cases / day calculated
from cumulative cases
used to estimate the
Gompertz function
Cases / day calculated
from cumulative cases
not used to estimate the
Gompertz function
Deaths / day,
axis is on the left
Blue line: today
Blue dots: cumulative cases not
used to estimate Gompertz
function
Cumulative cases
(yesterday’s cases)
and cumulative deaths
(yesterday’s deaths)
Axis for cases / day.
Axis for deaths / day
appears to the right.
Geographic
location
Date of analysis,
also shown as
blue vertical line
below
Purple wedge: 98% ensemble
prediction interval from COVID-19
Forecast Hub (USA and US
States only)
7. Comparison of COVID-19 Cases & Deaths
between US & Europe
Cases
Deaths
52,070
71,516
356
302
3
10
30
100
300
1,000
3,000
10,000
30,000
100,000
Date
DailyCasesandDeaths
Location
USA (318MM)
Western Europe (344MM)
Log plot of 7 day average
Comparison of COVID-19 Cases & Deaths between US & Europe
The numbers on the right are yesterday's figures, and will differ a bit from the plotted rolling mean
2020-09-22 Summary: 7
10. Average new cases over past 7 days
Israel
Spain
Argentina
Peru
France
CzechRepublic
Colombia
Brazil
USA
Iraq
Libya
Paraguay
Belgium
Netherlands
Chile
Austria
Hungary
Denmark
India
Ecuador
Honduras
Ukraine
DominicanRepublic
UnitedKingdom
Portugal
Morocco
Romania
Tunisia
Bolivia
Switzerland
Nepal
Iran
Russia
Philippines
Mexico
Guatemala
Jordan
Canada
Venezuela
SouthAfrica
Slovakia
Greece
Italy
Sweden
Belarus
Turkey
Uzbekistan
Germany
SaudiArabia
Bulgaria
Poland
Indonesia
ElSalvador
Azerbaijan
Kyrgyzstan
Finland
Bangladesh
Mozambique
Serbia
Myanmar
Ethiopia
Angola
Zambia
Algeria
Uganda
USA
None
1 in 10,000
1 in 5,000
1 in 3,333
1 in 2,500
1 in 2,000
1 in 1,667
1 in 1,429
1 6 11 16 21 26 31 36 41 46 51 56 61 66
Rank
Averagecases/day
Average new cases over past 7 days
Excludes countries with population < 5,000,000
2020-09-22 Summary: 10
13. Average daily deaths over past 7 days
Argentina
Colombia
Bolivia
Peru
Brazil
Mexico
Spain
Paraguay
Israel
Chile
Iran
Iraq
USA
Honduras
Libya
Romania
Ecuador
Guatemala
SouthAfrica
Ukraine
DominicanRepublic
SaudiArabia
Morocco
India
France
Turkey
CzechRepublic
Russia
Philippines
Bulgaria
Tunisia
Portugal
Hungary
Indonesia
Switzerland
ElSalvador
Greece
Belarus
Nepal
Poland
UnitedKingdom
Venezuela
Kazakhstan
Belgium
Sweden
Netherlands
Italy
Algeria
Australia
Canada
Uzbekistan
Azerbaijan
Egypt
Denmark
Zambia
Myanmar
Bangladesh
Angola
Serbia
Austria
Jordan
Ethiopia
Syria
Afghanistan
Finland
USA
None
1 in 500,000
1 in 250,000
1 in 166,667
1 in 125,000
1 6 11 16 21 26 31 36 41 46 51 56 61 66
Rank
Averagedeaths/day
Average daily deaths over past 7 days
Excludes countries with population < 5,000,000
2020-09-22 Summary: 13
15. Change in New Cases per Day
New cases are:
Increasing > +3%
Increasing between +1% and +3%
No Change (-1% to +1%)
Decreasing between -1% and -3%
Decreasing > -3%
New cases by state as of 2020-09-22
2020-09-22 Summary: 15
16. Cases as a Percent of Peak Cases
HI TX FL
OK LA MS AL GA
AZ NM KS AR TN NC SC DC
CA UT CO NE MO KY WV VA MD DE
OR NV WY SD IA IN OH PA NJ CT RI
WA ID MT ND MN IL MI NY MA
WI VT NH
AK ME
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
PercentofPeak
Daily Cases as a Percent of Peak Cases
2020-09-22 Summary: 16
17. Change in New Deaths per Day
New deaths are:
Increasing > +0.5%
Increasing between +0.1% and +0.5%
No Change (-0.1% to +0.1%)
Decreasing between -0.1% and -0.5%
Decreasing > -0.5%
New deaths by state as of 2020-09-22
2020-09-22 Summary: 17
18. Deaths as a Percent of Peak Deaths
HI TX FL
OK LA MS AL GA
AZ NM KS AR TN NC SC DC
CA UT CO NE MO KY WV VA MD DE
OR NV WY SD IA IN OH PA NJ CT RI
WA ID MT ND MN IL MI NY MA
WI VT NH
AK ME
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100
PercentofPeak
Daily Deaths as a Percent of Peak Deaths
2020-09-22 Summary: 18
19. Change in cases vs. change in deaths over
last 14 days
AL
AK
AZAR
CA
CO
CT
DE
FLGA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MI
MN
MO
MT
NE
NH
NJ
NM
NY
ND
OK
OR
PA
RI
SC
SD
TX
UT
WI
WY
-6
-3
0
3
6
-6 -3 0 3 6
Change in cases (%/day)
Changeindeaths(%/day)
Change in cases vs. change in deaths over last 14 days as of 2020-09-22
Size is proportional total cases per capita
2020-09-22 Summary: 19
20. Total US COVID-19 Cases
California
Texas
Florida
NewYork
Georgia
Illinois
Arizona
NewJersey
NorthCarolina
Tennessee
Louisiana
Pennsylvania
Alabama
Ohio
Virginia
SouthCarolina
Michigan
Massachusetts
Maryland
Missouri
Indiana
Wisconsin
Mississippi
Minnesota
Washington
Iowa
Oklahoma
Arkansas
Nevada
Colorado
Utah
Kentucky
Connecticut
Kansas
Nebraska
Idaho
Oregon
NewMexico
RhodeIsland
Delaware
SouthDakota
NorthDakota
DistrictofColumbia
WestVirginia
Hawaii
Montana
NewHampshire
Alaska
Maine
Wyoming
Vermont
0
250,000
500,000
750,000
1 6 11 16 21 26 31 36 41 46 51
Rank
Totalcases
Masks
No
Yes
Governor
aa
Democratic
Republican
Total US COVID-19 Cases
p masks as of July 20, 2020: 0.49, p governor: 0.82. NB: association != causation.
2020-09-22 Summary: 20
21. Total US COVID-19 Cases
Louisiana
Florida
Mississippi
Alabama
Arizona
Georgia
Tennessee
SouthCarolina
Iowa
Texas
Arkansas
Nevada
NorthDakota
NewYork
RhodeIsland
NewJersey
Illinois
Nebraska
SouthDakota
DistrictofColumbia
Idaho
Delaware
Utah
California
Maryland
Oklahoma
Missouri
NorthCarolina
Kansas
Massachusetts
Wisconsin
Indiana
Virginia
Minnesota
Connecticut
Kentucky
NewMexico
Michigan
Ohio
Pennsylvania
Colorado
Washington
Montana
Alaska
Wyoming
Hawaii
WestVirginia
Oregon
NewHampshire
Maine
Vermont
None
1 in 100
1 in 50
1 in 33
1 in 25
1 6 11 16 21 26 31 36 41 46 51
Rank
TotalCases
Masks
No
Yes
Governor
aa
Democratic
Republican
Total US COVID-19 Cases
p masks as of July 20, 2020: 0.22, p governor: 0.03. NB: association != causation.
2020-09-22 Summary: 21
22. Average US COVID-19 cases over the past
7 days
NorthDakota
SouthDakota
Wisconsin
Oklahoma
Arkansas
Utah
Iowa
Missouri
Tennessee
Texas
Kansas
Nebraska
Idaho
Alabama
Montana
Mississippi
Georgia
SouthCarolina
Minnesota
Illinois
Kentucky
Wyoming
Florida
RhodeIsland
Indiana
NorthCarolina
Louisiana
Alaska
Virginia
Delaware
WestVirginia
Nevada
Arizona
Maryland
California
Colorado
Ohio
Michigan
DistrictofColumbia
Hawaii
Pennsylvania
Connecticut
NewMexico
Massachusetts
NewJersey
Oregon
Washington
NewYork
NewHampshire
Maine
Vermont
None
1 in 10,000
1 in 5,000
1 in 3,333
1 in 2,500
1 in 2,000
1 6 11 16 21 26 31 36 41 46 51
Rank
NewCases/Day
Masks
No
Yes
Governor
aa
Democratic
Republican
Average US COVID-19 cases over the past 7 days
p masks as of July 20, 2020: 0.00055, p governor: 0.0012. NB: association != causation.
2020-09-22 Summary: 22
23. Total US COVID-19 Deaths
NewYork
NewJersey
Texas
California
Florida
Massachusetts
Illinois
Pennsylvania
Michigan
Georgia
Arizona
Louisiana
Ohio
Connecticut
Maryland
Indiana
NorthCarolina
SouthCarolina
Virginia
Mississippi
Alabama
Tennessee
Washington
Minnesota
Colorado
Missouri
Nevada
Iowa
Wisconsin
Arkansas
Kentucky
RhodeIsland
Oklahoma
NewMexico
Delaware
DistrictofColumbia
Kansas
Oregon
Nebraska
Idaho
Utah
NewHampshire
WestVirginia
SouthDakota
NorthDakota
Montana
Maine
Hawaii
Vermont
Wyoming
Alaska
0
10,000
20,000
30,000
1 6 11 16 21 26 31 36 41 46 51
Rank
TotalDeaths
Masks
No
Yes
Governor
aa
Democratic
Republican
Total US COVID-19 Deaths
p masks as of July 20, 2020: 0.066, p governor: 0.28. NB: association != causation.
2020-09-22 Summary: 23
24. Total US COVID-19 Deaths
NewJersey
NewYork
Massachusetts
Connecticut
Louisiana
RhodeIsland
Mississippi
DistrictofColumbia
Arizona
Michigan
Illinois
Delaware
Maryland
SouthCarolina
Pennsylvania
Georgia
Florida
Texas
Indiana
Alabama
Nevada
Iowa
NewMexico
Arkansas
Ohio
California
Minnesota
Virginia
Colorado
Tennessee
NewHampshire
NorthCarolina
Missouri
Washington
NorthDakota
Idaho
Kentucky
Oklahoma
Nebraska
SouthDakota
Wisconsin
Kansas
WestVirginia
Montana
Utah
Oregon
Maine
Vermont
Wyoming
Hawaii
Alaska
None
1 in 2,000
1 in 1,000
1 in 667
1 in 500
1 6 11 16 21 26 31 36 41 46 51
Rank
TotalDeaths
Masks
No
Yes
Governor
aa
Democratic
Republican
Total US COVID-19 Deaths
p masks as of July 20, 2020: 0.029, p governor: 0.35. NB: association != causation.
2020-09-22 Summary: 24
25. Average US COVID-19 deaths over the past
7 days
Arkansas
Mississippi
Virginia
Florida
NorthDakota
Louisiana
SouthCarolina
WestVirginia
Nevada
Georgia
Kansas
Texas
RhodeIsland
Montana
Tennessee
Arizona
SouthDakota
Iowa
NorthCarolina
Alabama
Ohio
Missouri
California
Massachusetts
Idaho
Hawaii
Wyoming
NewMexico
Delaware
Pennsylvania
Illinois
Kentucky
Indiana
Oklahoma
Minnesota
Nebraska
Washington
Maryland
DistrictofColumbia
Michigan
Wisconsin
Colorado
Oregon
NewJersey
Connecticut
NewYork
Maine
Utah
NewHampshire
Alaska
Vermont
None
1 in 500,000
1 in 250,000
1 in 166,667
1 in 125,000
1 in 100,000
1 6 11 16 21 26 31 36 41 46 51
Rank
Deaths/Day
Masks
No
Yes
Governor
aa
Democratic
Republican
Average US COVID-19 deaths over the past 7 days
p masks as of July 20, 2020: 0.58, p governor: 0.15. NB: association != causation.
2020-09-22 Summary: 25
26. Daily testing trends
HI TX FL
OK LA MS AL GA
AZ NM KS AR TN NC SC DC
CA UT CO NE MO KY WV VA MD DE
OR NV WY SD IA IN OH PA NJ CT RI
WA ID MT ND MN IL MI NY MA
WI VT NH
AK ME
min
max
min
max
min
max
min
max
min
max
min
max
min
max
min
max
Dailytestingfrommintomax
Daily testing trends from min to max
Line = Friedman's supersmoother
2020-09-22 Summary: 26
27. Change in daily tests over past 14 days
California
WestVirginia
Minnesota
NewMexico
Idaho
NorthCarolina
Colorado
Florida
Ohio
Hawaii
Illinois
Wyoming
Michigan
Montana
Connecticut
Kentucky
Utah
Oklahoma
Missouri
SouthCarolina
Arkansas
Tennessee
Washington
Maine
Texas
Virginia
NewYork
Kansas
Wisconsin
Mississippi
Indiana
Nebraska
Arizona
NorthDakota
NewJersey
Massachusetts
DistrictofColumbia
Iowa
SouthDakota
NewHampshire
Delaware
Pennsylvania
Maryland
Georgia
Louisiana
Alaska
RhodeIsland
Oregon
Nevada
Vermont
Alabama
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
1 6 11 16 21 26 31 36 41 46 51
Rank
Changeindailytests(%/day)
Masks
No
Yes
Governor
aa
Democratic
Republican
Change in daily tests over past 14 days
p masks as of July 20, 2020: 0.55, p governor: 0.22. NB: association != causation.
2020-09-22 Summary: 27
29. Percent of Positive COVID Tests
Arizona
Alabama
Florida
Mississippi
Idaho
Texas
SouthCarolina
Nevada
Kansas
Georgia
Iowa
SouthDakota
Nebraska
Missouri
Indiana
Arkansas
Utah
NorthDakota
Pennsylvania
Maryland
Colorado
Wisconsin
RhodeIsland
Louisiana
Virginia
Oklahoma
Delaware
Minnesota
NorthCarolina
Tennessee
Massachusetts
NewJersey
Kentucky
California
Illinois
Wyoming
Ohio
Oregon
Washington
NewYork
DistrictofColumbia
Hawaii
Michigan
Connecticut
Montana
NewHampshire
NewMexico
WestVirginia
Alaska
Maine
Vermont
0.0
5.0
10.0
15.0
1 6 11 16 21 26 31 36 41 46 51
Rank
PercentofPositiveTests
Masks
No
Yes
Governor
aa
Democratic
Republican
Percent of Positive COVID Tests
p masks as of July 20, 2020: 0.0091, p governor: 0.0023. NB: association != causation.
2020-09-22 Summary: 29
30. Positive fraction trends
HI TX FL
OK LA MS AL GA
AZ NM KS AR TN NC SC DC
CA UT CO NE MO KY WV VA MD DE
OR NV WY SD IA IN OH PA NJ CT RI
WA ID MT ND MN IL MI NY MA
WI VT NH
AK ME
min
max
min
max
min
max
min
max
min
max
min
max
min
max
min
max
Fractionpositivefrommintomax
Positive fraction trends from min to max
2020-09-22 Summary: 30
31. Change in positive tests over past 14 days
NorthDakota
Wisconsin
WestVirginia
Montana
SouthDakota
Wyoming
Utah
Alaska
Texas
Missouri
Kansas
Iowa
Oklahoma
Idaho
Nebraska
Minnesota
Oregon
Alabama
Arkansas
Delaware
Florida
Colorado
Nevada
Pennsylvania
SouthCarolina
NewHampshire
Maryland
Georgia
RhodeIsland
Virginia
Tennessee
Vermont
NewMexico
Indiana
Washington
Michigan
Hawaii
NorthCarolina
Illinois
California
Louisiana
Ohio
Arizona
NewJersey
Massachusetts
Mississippi
Kentucky
DistrictofColumbia
Connecticut
NewYork
Maine
-1.0
0.0
1.0
1 6 11 16 21 26 31 36 41 46 51
Rank
Changeinpositivetests(%/day)
Masks
No
Yes
Governor
aa
Democratic
Republican
Change in positive tests over past 14 days
p masks as of July 20, 2020: 0.0072, p governor: 0.0037. NB: association != causation.
2020-09-22 Summary: 31
32. Change in tests vs. change in positive tests
over last 14 days
AL
AK
AZ
AR
CA
CO
CT
DE
DC
GA
HI
ID
IL
IN
IA KS
LA
ME
MA
MI
MN
MT
NE
NV NH
NJ
NM
NY
NC
ND
OH
OR
SC
SD
TX
UT
VT
WV
WI
WY
-1
0
1
-5.0 -2.5 0.0 2.5 5.0
Change in tests (%/day)
Changeinpositivetests(%/day)
Change in tests vs. change in positive tests over last 14 days as of 2020-09-22
Size is proportional daily deaths per capita over the past 7 days
2020-09-22 Summary: 32
33. Current hospitalizations as a percent of peak
since FebruaryMissouri
NorthDakota
SouthDakota
WestVirginia
Wyoming
Alaska
Nebraska
Oklahoma
Kentucky
NorthCarolina
Arkansas
Kansas
Utah
Hawaii
Iowa
Idaho
Montana
Wisconsin
Virginia
Georgia
Tennessee
Oregon
Ohio
Indiana
Mississippi
Alabama
SouthCarolina
Washington
Minnesota
California
Nevada
Louisiana
NewMexico
Illinois
Texas
Maine
RhodeIsland
Florida
Colorado
DistrictofColumbia
Delaware
Maryland
Pennsylvania
Michigan
Arizona
Massachusetts
NewHampshire
Vermont
NewJersey
Connecticut
NewYork
0
30
60
90
1 6 11 16 21 26 31 36 41 46 51
Rank
Hospitalizations(%ofpeak)
Masks
No
Yes
Governor
aa
Democratic
Republican
Current hospitalizations as a percent of peak since February
p masks as of July 20, 2020: 0.0044, p governor: 0.03. NB: association != causation.
2020-09-22 Summary: 33
34. Hospitalizations trends
HI TX FL
OK LA MS AL GA
AZ NM KS AR TN NC SC DC
CA UT CO NE MO KY WV VA MD DE
OR NV WY SD IA IN OH PA NJ CT RI
WA ID MT ND MN IL MI NY MA
WI VT NH
AK ME
min
max
min
max
min
max
min
max
min
max
min
max
min
max
min
max
Hospitalizationsfrommintomax
Hospitalizations trends from min to max
2020-09-22 Summary: 34
35. Change in hospitalizations over past 14
days
SouthDakota
Maine
Connecticut
Wyoming
Wisconsin
NorthDakota
NewHampshire
Utah
Massachusetts
WestVirginia
Missouri
NewYork
Alaska
DistrictofColumbia
Oklahoma
Nebraska
Oregon
NorthCarolina
RhodeIsland
Delaware
Arkansas
Illinois
Idaho
Kansas
Indiana
NewMexico
SouthCarolina
Kentucky
Colorado
Minnesota
Virginia
Pennsylvania
NewJersey
Alabama
Iowa
Michigan
Georgia
Mississippi
Washington
Maryland
Ohio
Tennessee
Texas
Vermont
California
Nevada
Louisiana
Arizona
Hawaii
Florida
Montana
-2.0
0.0
2.0
4.0
1 6 11 16 21 26 31 36 41 46 51
Rank
Changeinhospitalizations(%/day)
Masks
No
Yes
Governor
aa
Democratic
Republican
Change in hospitalizations over past 14 days
p masks as of July 20, 2020: 0.33, p governor: 0.43. NB: association != causation.
2020-09-22 Summary: 35
36. Change in New Cases per Day
Direction
Increasing > +2%
Increasing between +0.5% and +2%
No Change (-0.5% to +0.5%)
Decreasing between -0.5% and -2%
Decreasing > -2%
NA
Trends by county as of 2020-09-22
NA = Inadequate data
2020-09-22 Summary: 36