CA County by County Covid-19 Key Metrics: Rate of CV-19 Spread over Time and Hospitalizations as % of Total Care Capacity

Kante

GOLD
Here's a solid tool posted from state of CA to status on a county by county basis. https://calcat.covid19.ca.gov/cacovidmodels/

Can look up status on the bug on a county by county basis - i.e. is the spread accelerating, stable or decelerating - as well as current # of hospitalizations as % of total available beds which is a key early indicator where mortality rates are going.

For example, at some point, a county's max care capacity for CV-19 is used up and mortality rates hit a tipping point and start to disproportionately accelerate, which is what happened in Italy, Spain, France and, closer to home, NYC. Even more close to home, Imperial County looks like it got close to this tipping point.

The powers that be are likely looking hard at these numbers when making their decisions about what happens/open when, so, if nothing else, the model provides insight into how/why decisions are being made on a county by county basis.

Below is a consolidated SoCal summary of the numbers. Covid 19 spread is measured in the tool by the R-effective value: Per CA gov, Rf = .9 to 1.1 is stable ... the range allows for a margin of error; Rf >1.1 = accelerating; Rf <.9= decelerating). Looking at SoCal counties but being liberal of definition of SoCal as Kern/SLO and points south.
__________

As of 6/23/20:

Spread Accelerating in the following counties (i.e. increase in new case numbers in these counties is - in part - due to Covid-19 infections increasing as % of population)

1. San Diego: Rf ~1.27
note: significant increase since June 2 when Rf = .95

2. San Luis Obispo: Rf ~1.22
note: significant increase since eom May when Rf = 1

3. Ventura: Rf ~1.2
note: Ventura Rf was down at 1.08 as recently as June 3rd but has been on slowbut steady since.

3. Orange: Rf ~1.19
note: Orange County has been Rf >1 pretty consistently, but Rf has slowly but steadily increased up since June 4th

4. Santa Barbara: Rf ~1.16
note: Santa Barbara County had solid progress w/ Rf dropping to .86 on May 26th but has seen a steady increase in Rf since.

Spread Stable (i.e. increase in new case numbers primarily due to increase in testing)
1. Kern County: Rf ~1.08
note: Kern County hit 1.16 on June 4th but has seen a slow but steady decline in Rf since

2. Riverside County: Rf ~1.05
note: Riverside County has been pretty steady w/ their Rf ~1.05 since the end of April

3. San Bernadino: Rf ~1.03
note: San Bernadino County looks like they spiked up to Rf=1.24 on June 15th but seems to have corralled their Rf value back down to a more manageable 1.03

4. Los Angeles: Rf ~.9
note: LA County looks like there was a brief Rf spike on May 24th, but things look like they're back under control. LA's increase in new case numbers has been driving a lot of "sky is falling" headlines but those headlines should be taken with a grain of salt.

Spread Decelerating (i.e. any increase new case numbers is due entirely to increase in testing)
1. Imperial County: Rf ~.8
note: Imperial County had been in a no joke/serious meltdown with Rf pretty consistently btw 1.2 and 1.35 up until about June 7th, when the Rf started a steady and sharp decline to .8 as of June 21st.

__________

CV-19 Hospitalizations as % of total hospital beds county by county as of 6/23/20:

1. Imperial County: 35% (93 CV-19 vs 268 total beds)
2. Riverside County: 9% (315 CV-19 vs 3,623 total)
3. Kern County: 8% (118 CV-19 vs 1,510 total)
4. San Bernadino County: 8% (311 CV-19 vs 4,003 total)
5. Los Angeles County: 8% (1,633 CV-19 vs 21,693 total)
6. Orange County: 7% (406 CV-19 vs 6,034 total)
7. Santa Barbara County: 6% (53 CV-19 vs 848 total)
8. San Diego County: 5% (312 CV-19 vs 6,509 total)
9. Ventura County: 4% (54 CV-19 vs 1,353 total)
10. San Luis Obispo County: 1% (5 CV-19 vs 449 total)
 

Copa9

GOLD
Here's a solid tool posted from state of CA to status on a county by county basis. https://calcat.covid19.ca.gov/cacovidmodels/

Can look up status on the bug on a county by county basis - i.e. is the spread accelerating, stable or decelerating - as well as current # of hospitalizations as % of total available beds which is a key early indicator where mortality rates are going.

For example, at some point, a county's max care capacity for CV-19 is used up and mortality rates hit a tipping point and start to disproportionately accelerate, which is what happened in Italy, Spain, France and, closer to home, NYC. Even more close to home, Imperial County looks like it got close to this tipping point.

The powers that be are likely looking hard at these numbers when making their decisions about what happens/open when, so, if nothing else, the model provides insight into how/why decisions are being made on a county by county basis.

Below is a consolidated SoCal summary of the numbers. Covid 19 spread is measured in the tool by the R-effective value: Per CA gov, Rf = .9 to 1.1 is stable ... the range allows for a margin of error; Rf >1.1 = accelerating; Rf <.9= decelerating). Looking at SoCal counties but being liberal of definition of SoCal as Kern/SLO and points south.
__________

As of 6/23/20:

Spread Accelerating in the following counties (i.e. increase in new case numbers in these counties is - in part - due to Covid-19 infections increasing as % of population)

1. San Diego: Rf ~1.27
note: significant increase since June 2 when Rf = .95

2. San Luis Obispo: Rf ~1.22
note: significant increase since eom May when Rf = 1

3. Ventura: Rf ~1.2
note: Ventura Rf was down at 1.08 as recently as June 3rd but has been on slowbut steady since.

3. Orange: Rf ~1.19
note: Orange County has been Rf >1 pretty consistently, but Rf has slowly but steadily increased up since June 4th

4. Santa Barbara: Rf ~1.16
note: Santa Barbara County had solid progress w/ Rf dropping to .86 on May 26th but has seen a steady increase in Rf since.

Spread Stable (i.e. increase in new case numbers primarily due to increase in testing)
1. Kern County: Rf ~1.08
note: Kern County hit 1.16 on June 4th but has seen a slow but steady decline in Rf since

2. Riverside County: Rf ~1.05
note: Riverside County has been pretty steady w/ their Rf ~1.05 since the end of April

3. San Bernadino: Rf ~1.03
note: San Bernadino County looks like they spiked up to Rf=1.24 on June 15th but seems to have corralled their Rf value back down to a more manageable 1.03

4. Los Angeles: Rf ~.9
note: LA County looks like there was a brief Rf spike on May 24th, but things look like they're back under control. LA's increase in new case numbers has been driving a lot of "sky is falling" headlines but those headlines should be taken with a grain of salt.

Spread Decelerating (i.e. any increase new case numbers is due entirely to increase in testing)
1. Imperial County: Rf ~.8
note: Imperial County had been in a no joke/serious meltdown with Rf pretty consistently btw 1.2 and 1.35 up until about June 7th, when the Rf started a steady and sharp decline to .8 as of June 21st.

__________

CV-19 Hospitalizations as % of total hospital beds county by county as of 6/23/20:

1. Imperial County: 35% (93 CV-19 vs 268 total beds)
2. Riverside County: 9% (315 CV-19 vs 3,623 total)
3. Kern County: 8% (118 CV-19 vs 1,510 total)
4. San Bernadino County: 8% (311 CV-19 vs 4,003 total)
5. Los Angeles County: 8% (1,633 CV-19 vs 21,693 total)
6. Orange County: 7% (406 CV-19 vs 6,034 total)
7. Santa Barbara County: 6% (53 CV-19 vs 848 total)
8. San Diego County: 5% (312 CV-19 vs 6,509 total)
9. Ventura County: 4% (54 CV-19 vs 1,353 total)
10. San Luis Obispo County: 1% (5 CV-19 vs 449 total)
I just posted something in the wrong forum spot. For south Orange County friends, info only, 7 Tesoro High School football players have just tested positive for covid. Something else to think about.
 
Here's a solid tool posted from state of CA to status on a county by county basis. https://calcat.covid19.ca.gov/cacovidmodels/

Can look up status on the bug on a county by county basis - i.e. is the spread accelerating, stable or decelerating - as well as current # of hospitalizations as % of total available beds which is a key early indicator where mortality rates are going.

For example, at some point, a county's max care capacity for CV-19 is used up and mortality rates hit a tipping point and start to disproportionately accelerate, which is what happened in Italy, Spain, France and, closer to home, NYC. Even more close to home, Imperial County looks like it got close to this tipping point.

The powers that be are likely looking hard at these numbers when making their decisions about what happens/open when, so, if nothing else, the model provides insight into how/why decisions are being made on a county by county basis.

Below is a consolidated SoCal summary of the numbers. Covid 19 spread is measured in the tool by the R-effective value: Per CA gov, Rf = .9 to 1.1 is stable ... the range allows for a margin of error; Rf >1.1 = accelerating; Rf <.9= decelerating). Looking at SoCal counties but being liberal of definition of SoCal as Kern/SLO and points south.
__________

As of 6/23/20:

Spread Accelerating in the following counties (i.e. increase in new case numbers in these counties is - in part - due to Covid-19 infections increasing as % of population)

1. San Diego: Rf ~1.27
note: significant increase since June 2 when Rf = .95

2. San Luis Obispo: Rf ~1.22
note: significant increase since eom May when Rf = 1

3. Ventura: Rf ~1.2
note: Ventura Rf was down at 1.08 as recently as June 3rd but has been on slowbut steady since.

3. Orange: Rf ~1.19
note: Orange County has been Rf >1 pretty consistently, but Rf has slowly but steadily increased up since June 4th

4. Santa Barbara: Rf ~1.16
note: Santa Barbara County had solid progress w/ Rf dropping to .86 on May 26th but has seen a steady increase in Rf since.

Spread Stable (i.e. increase in new case numbers primarily due to increase in testing)
1. Kern County: Rf ~1.08
note: Kern County hit 1.16 on June 4th but has seen a slow but steady decline in Rf since

2. Riverside County: Rf ~1.05
note: Riverside County has been pretty steady w/ their Rf ~1.05 since the end of April

3. San Bernadino: Rf ~1.03
note: San Bernadino County looks like they spiked up to Rf=1.24 on June 15th but seems to have corralled their Rf value back down to a more manageable 1.03

4. Los Angeles: Rf ~.9
note: LA County looks like there was a brief Rf spike on May 24th, but things look like they're back under control. LA's increase in new case numbers has been driving a lot of "sky is falling" headlines but those headlines should be taken with a grain of salt.

Spread Decelerating (i.e. any increase new case numbers is due entirely to increase in testing)
1. Imperial County: Rf ~.8
note: Imperial County had been in a no joke/serious meltdown with Rf pretty consistently btw 1.2 and 1.35 up until about June 7th, when the Rf started a steady and sharp decline to .8 as of June 21st.

__________

CV-19 Hospitalizations as % of total hospital beds county by county as of 6/23/20:

1. Imperial County: 35% (93 CV-19 vs 268 total beds)
2. Riverside County: 9% (315 CV-19 vs 3,623 total)
3. Kern County: 8% (118 CV-19 vs 1,510 total)
4. San Bernadino County: 8% (311 CV-19 vs 4,003 total)
5. Los Angeles County: 8% (1,633 CV-19 vs 21,693 total)
6. Orange County: 7% (406 CV-19 vs 6,034 total)
7. Santa Barbara County: 6% (53 CV-19 vs 848 total)
8. San Diego County: 5% (312 CV-19 vs 6,509 total)
9. Ventura County: 4% (54 CV-19 vs 1,353 total)
10. San Luis Obispo County: 1% (5 CV-19 vs 449 total)
Imperial looks like it's in solid shape now, but Newsome is calling for them to lockdown again. What am I missing?

"In a Friday update, Newsom urged Imperial County leaders to reimpose restrictions to combat the spread of the virus."
 

dad4

PREMIER
Imperial looks like it's in solid shape now, but Newsome is calling for them to lockdown again. What am I missing?

"In a Friday update, Newsom urged Imperial County leaders to reimpose restrictions to combat the spread of the virus."
Their ICU rate doesn't show the 500 patients airlifted to LA, SD, and SF.

And their mortuary is out of freezer space.
 
Their ICU rate doesn't show the 500 patients airlifted to LA, SD, and SF.

And their mortuary is out of freezer space.
Thanks. So, is the calculation based on patient count and the count is artificially low due to moving patients elsewhere? If so, I don't know why they are producing a result for Imperial County.
 

Speed

SILVER ELITE
I just posted something in the wrong forum spot. For south Orange County friends, info only, 7 Tesoro High School football players have just tested positive for covid. Something else to think about.
that's our school are you part of the football program?
 
And what has the football program been doing? Soccer nada.
I was thinking the same thing. Someone obviously was super political before Corona and the GDA league was the most political league I ever witnessed in my life. Cope dd got her deal so she is super happy she got what she demanded and now she wants her Joe to be President. Again, soccer is being used for all the wrong reasons and Copa won;t leave this place until Nov 3rd. I wouldnt share anything on here about your High School. She is out and about looking for corona virus cases and who got the virus all over OC. She knows her news too.
 
Here's a solid tool posted from state of CA to status on a county by county basis. https://calcat.covid19.ca.gov/cacovidmodels/

Can look up status on the bug on a county by county basis - i.e. is the spread accelerating, stable or decelerating - as well as current # of hospitalizations as % of total available beds which is a key early indicator where mortality rates are going.

For example, at some point, a county's max care capacity for CV-19 is used up and mortality rates hit a tipping point and start to disproportionately accelerate, which is what happened in Italy, Spain, France and, closer to home, NYC. Even more close to home, Imperial County looks like it got close to this tipping point.

The powers that be are likely looking hard at these numbers when making their decisions about what happens/open when, so, if nothing else, the model provides insight into how/why decisions are being made on a county by county basis.

Below is a consolidated SoCal summary of the numbers. Covid 19 spread is measured in the tool by the R-effective value: Per CA gov, Rf = .9 to 1.1 is stable ... the range allows for a margin of error; Rf >1.1 = accelerating; Rf <.9= decelerating). Looking at SoCal counties but being liberal of definition of SoCal as Kern/SLO and points south.
__________

As of 6/23/20:

Spread Accelerating in the following counties (i.e. increase in new case numbers in these counties is - in part - due to Covid-19 infections increasing as % of population)

1. San Diego: Rf ~1.27
note: significant increase since June 2 when Rf = .95

2. San Luis Obispo: Rf ~1.22
note: significant increase since eom May when Rf = 1

3. Ventura: Rf ~1.2
note: Ventura Rf was down at 1.08 as recently as June 3rd but has been on slowbut steady since.

3. Orange: Rf ~1.19
note: Orange County has been Rf >1 pretty consistently, but Rf has slowly but steadily increased up since June 4th

4. Santa Barbara: Rf ~1.16
note: Santa Barbara County had solid progress w/ Rf dropping to .86 on May 26th but has seen a steady increase in Rf since.

Spread Stable (i.e. increase in new case numbers primarily due to increase in testing)
1. Kern County: Rf ~1.08
note: Kern County hit 1.16 on June 4th but has seen a slow but steady decline in Rf since

2. Riverside County: Rf ~1.05
note: Riverside County has been pretty steady w/ their Rf ~1.05 since the end of April

3. San Bernadino: Rf ~1.03
note: San Bernadino County looks like they spiked up to Rf=1.24 on June 15th but seems to have corralled their Rf value back down to a more manageable 1.03

4. Los Angeles: Rf ~.9
note: LA County looks like there was a brief Rf spike on May 24th, but things look like they're back under control. LA's increase in new case numbers has been driving a lot of "sky is falling" headlines but those headlines should be taken with a grain of salt.

Spread Decelerating (i.e. any increase new case numbers is due entirely to increase in testing)
1. Imperial County: Rf ~.8
note: Imperial County had been in a no joke/serious meltdown with Rf pretty consistently btw 1.2 and 1.35 up until about June 7th, when the Rf started a steady and sharp decline to .8 as of June 21st.

__________

CV-19 Hospitalizations as % of total hospital beds county by county as of 6/23/20:

1. Imperial County: 35% (93 CV-19 vs 268 total beds)
2. Riverside County: 9% (315 CV-19 vs 3,623 total)
3. Kern County: 8% (118 CV-19 vs 1,510 total)
4. San Bernadino County: 8% (311 CV-19 vs 4,003 total)
5. Los Angeles County: 8% (1,633 CV-19 vs 21,693 total)
6. Orange County: 7% (406 CV-19 vs 6,034 total)
7. Santa Barbara County: 6% (53 CV-19 vs 848 total)
8. San Diego County: 5% (312 CV-19 vs 6,509 total)
9. Ventura County: 4% (54 CV-19 vs 1,353 total)
10. San Luis Obispo County: 1% (5 CV-19 vs 449 total)
You do realize that you still need to add the suspected CV patients in the numbers related to hospitalizations because even if they are not COVID positive, they are still in a hospital bed.
 
Here's a solid tool posted from state of CA to status on a county by county basis. https://calcat.covid19.ca.gov/cacovidmodels/

Can look up status on the bug on a county by county basis - i.e. is the spread accelerating, stable or decelerating - as well as current # of hospitalizations as % of total available beds which is a key early indicator where mortality rates are going.

For example, at some point, a county's max care capacity for CV-19 is used up and mortality rates hit a tipping point and start to disproportionately accelerate, which is what happened in Italy, Spain, France and, closer to home, NYC. Even more close to home, Imperial County looks like it got close to this tipping point.

The powers that be are likely looking hard at these numbers when making their decisions about what happens/open when, so, if nothing else, the model provides insight into how/why decisions are being made on a county by county basis.

Below is a consolidated SoCal summary of the numbers. Covid 19 spread is measured in the tool by the R-effective value: Per CA gov, Rf = .9 to 1.1 is stable ... the range allows for a margin of error; Rf >1.1 = accelerating; Rf <.9= decelerating). Looking at SoCal counties but being liberal of definition of SoCal as Kern/SLO and points south.
__________

As of 6/23/20:

Spread Accelerating in the following counties (i.e. increase in new case numbers in these counties is - in part - due to Covid-19 infections increasing as % of population)

1. San Diego: Rf ~1.27
note: significant increase since June 2 when Rf = .95

2. San Luis Obispo: Rf ~1.22
note: significant increase since eom May when Rf = 1

3. Ventura: Rf ~1.2
note: Ventura Rf was down at 1.08 as recently as June 3rd but has been on slowbut steady since.

3. Orange: Rf ~1.19
note: Orange County has been Rf >1 pretty consistently, but Rf has slowly but steadily increased up since June 4th

4. Santa Barbara: Rf ~1.16
note: Santa Barbara County had solid progress w/ Rf dropping to .86 on May 26th but has seen a steady increase in Rf since.

Spread Stable (i.e. increase in new case numbers primarily due to increase in testing)
1. Kern County: Rf ~1.08
note: Kern County hit 1.16 on June 4th but has seen a slow but steady decline in Rf since

2. Riverside County: Rf ~1.05
note: Riverside County has been pretty steady w/ their Rf ~1.05 since the end of April

3. San Bernadino: Rf ~1.03
note: San Bernadino County looks like they spiked up to Rf=1.24 on June 15th but seems to have corralled their Rf value back down to a more manageable 1.03

4. Los Angeles: Rf ~.9
note: LA County looks like there was a brief Rf spike on May 24th, but things look like they're back under control. LA's increase in new case numbers has been driving a lot of "sky is falling" headlines but those headlines should be taken with a grain of salt.

Spread Decelerating (i.e. any increase new case numbers is due entirely to increase in testing)
1. Imperial County: Rf ~.8
note: Imperial County had been in a no joke/serious meltdown with Rf pretty consistently btw 1.2 and 1.35 up until about June 7th, when the Rf started a steady and sharp decline to .8 as of June 21st.

__________

CV-19 Hospitalizations as % of total hospital beds county by county as of 6/23/20:

1. Imperial County: 35% (93 CV-19 vs 268 total beds)
2. Riverside County: 9% (315 CV-19 vs 3,623 total)
3. Kern County: 8% (118 CV-19 vs 1,510 total)
4. San Bernadino County: 8% (311 CV-19 vs 4,003 total)
5. Los Angeles County: 8% (1,633 CV-19 vs 21,693 total)
6. Orange County: 7% (406 CV-19 vs 6,034 total)
7. Santa Barbara County: 6% (53 CV-19 vs 848 total)
8. San Diego County: 5% (312 CV-19 vs 6,509 total)
9. Ventura County: 4% (54 CV-19 vs 1,353 total)
10. San Luis Obispo County: 1% (5 CV-19 vs 449 total)
If we keep increasing at 18.5% every 3 days like we have the last 3 days in OC, we will be at 6,379 patients in 45 days.
 
If we keep increasing at 18.5% every 3 days like we have the last 3 days in OC, we will be at 6,379 patients in 45 days.
I understand what you are saying, but 45 days is a long time to try to predict with this virus. Consider that in 45 days we went from, "What's this Chinese virus?" (March 15) to past the peak (April 11) for deaths above normal.

1593361059116.png
 
I understand what you are saying, but 45 days is a long time to try to predict with this virus. Consider that in 45 days we went from, "What's this Chinese virus?" (March 15) to past the peak (April 11) for deaths above normal.

View attachment 7972
Your chart is pretty outdated and is looking at the period of time we were in shut down. I don't see anything changing that will decrease the daily average increase rate and the calculation is based on the latest increase. I only see it increasing because of the no mask believers that are only looking at their own risk, and all of the additional opening of businesses in the last couple of weeks. Here in OC we increased occupied ICU beds for COVID (confirmed and suspected) by 34% last week. We have 200 people in the ICU right now related to COVID (confirmed and suspected) and we have 673 licensed ICU beds What about people in ICU for other reasons? If we keep increasing at the rate we did last week, we have a problem in approximately 3 weeks.
 

Copa9

GOLD
Your chart is pretty outdated and is looking at the period of time we were in shut down. I don't see anything changing that will decrease the daily average increase rate and the calculation is based on the latest increase. I only see it increasing because of the no mask believers that are only looking at their own risk, and all of the additional opening of businesses in the last couple of weeks. Here in OC we increased occupied ICU beds for COVID (confirmed and suspected) by 34% last week. We have 200 people in the ICU right now related to COVID (confirmed and suspected) and we have 673 licensed ICU beds What about people in ICU for other reasons? If we keep increasing at the rate we did last week, we have a problem in approximately 3 weeks.
So many people forget the consequences of being sick with this virus beyond the death rate. The financial burden could be huge if you get it and are hospitalized.
 
So many people forget the consequences of being sick with this virus beyond the death rate. The financial burden could be huge if you get it and are hospitalized.
And if God forbid you or your loved one has some issue like a heart attack, stroke, traffic accident or a complication from cancer etc. that requires you to be in the ICU or regular hospital bed then there will be a problem if our hospital system is overwhelmed by COVID patients.
 

tjinaz

SILVER ELITE
Curious about the new numbers. Is there an actual increase in the numbers of infected or is it we are now testing more and actually finding them? More testing means more detected cases not necessarily more cases. They may have been there all along but asymptomatic. So is the rise due to more testing or more infections? Haven't found any graph or article that shows a clear differentiation.
 
Curious about the new numbers. Is there an actual increase in the numbers of infected or is it we are now testing more and actually finding them? More testing means more detected cases not necessarily more cases. They may have been there all along but asymptomatic. So is the rise due to more testing or more infections? Haven't found any graph or article that shows a clear differentiation.
I have always looked at it this way....I look at hospitalizations because that will tell us pretty clearly what is going on with the spread because there aren't other variables like you pointed out....more testing equates to more cases and not necessarily indicative of the spread of the illness. There are some nuances in the changing hospital rates but that number in my opinion is a cleaner number to look at to know what is going on with the spread because it has less variables that can change conclusions.

I saw Dr. Birx report that our rate of infection is decreasing but the reality is, we just opened up testing recently to people that weren't symptomatic so of course our rate of infection to testing will decrease from the testing that was restricted to symptomatic people. We will know more in a few more weeks as it relates to infection to testing rates but that still isn't a real clear picture.
 
Your chart is pretty outdated and is looking at the period of time we were in shut down.
No, it's up to date. The link is below. If you use the link, you can hover over the graph and see the week associated with each line. My point was that 45 days is way too long to project any kind of trend.

Also this chart just looks at deaths and a projected line where we wouldn't expect the number of deaths to be over more than 1 in 20 weeks. The best thing about it is it simply counts deaths - regardless of category. There's no worry of over count or under count due to COVID. It shows the obvious impact of the virus and is now definitely trending down. We'll see if it continues that way.

I agree that the ICU hospital count is a big deal. I also believe in, and practice, wearing a mask and social distancing. Unfortunately, there is no "solution". People will die due to mental health issues caused by financial burdens and loss of contact with people. This all must be considered. Yes, Copa, hospital costs can be a burden, but so is unemployment and counseling associated with mental health issues brought on by unemployment and isolation. Again, this all needs to be considered.

 
Curious about the new numbers. Is there an actual increase in the numbers of infected or is it we are now testing more and actually finding them? More testing means more detected cases not necessarily more cases. They may have been there all along but asymptomatic. So is the rise due to more testing or more infections? Haven't found any graph or article that shows a clear differentiation.
It's definitely both, but the fact that we are seeing ICU hospitalization rates rise in certain areas unequivocally indicates new infections associated with opening up. I don't see any other reasonable explanation.
 
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