5 ms·

Without social distancing or contact tracing. The Bay Area's r is probably around 0.8 at this point with Santa Clara even lower (EDITED - see notes below). Some

Without social distancing or contact tracing. The Bay Area's r is probably around 0.8 at this point with Santa Clara even lower (EDITED - see notes below). Some restrictions can be relaxed.

MrGando 7y ago
> The Bay Area's r is probably under 0.8 at this point Could you tell me where are you getting this magic number ballpark estimate from? (somewhere concrete, not just your gut and imagination)
- usaar333 7y ago
  Various data points. This is an upper bound, more calculated for Santa Clara county. International comparisons to lockdown level and case count changes. Assuming serial interval of 4 and > 10x non-detection rate on March 31 and 3x now gives you this. Knowing people were dying if the disease in early February implies very high lack of detection when SIP was in place. (Likely over 800 infections a day when Santa Clara activated SIP) Edit: More detailed explanation above.
killion 7y ago
Rt of .88 according to https://rt.live https://rt.live I agree some restrictions could be relaxed. Hospitals were a good first step. More of the outdoors could be a good next one.
- usaar333 7y ago
  Note that is CA as a whole. LA is skewing it upward. e.g. CA was around 1250 new cases 2nd week of April and maybe 1200 now (4% lower). With test capacity increasing, rt.live is giving 0.88, which on a 4 day serial interval implies a 33% actual reduction Bay Area went from about 200 to about 140 now (30% lower). Factoring the reduction from testing (if same for all of CA), we're actually at a 53% reduction. That's an R of 0.81. Santa Clara (which I admittedly originally mis-used for all Bay Area) went from 62 to 25. That's an crude R of 0.77 -- 0.7 factoring the test increases.
- mattkrause 7y ago
  0.88 doesn't buy you very much room. If it creeps up to 1.1, you still don't need many rounds of infection to completely overwhelm the system. 7 rounds of infection (~a month) would result in 10.4x more total patients.
  - usaar333 7y ago
    I'm not following your math. On a serial interval of 4, 7 rounds of infection does take a month, but that's only 1.1^7 = 2.
    - mattkrause 7y ago
      That's new cases though, isn't it? I was summing over the entire "tree" to get the total instead. If R0=2 (each person infects two more), you have 1 case at time zero, two after the first time step, and four after the next, but the total number of cases is 1+2+4=7, not 2^2. It's true that people are discharged from the hospital eventually (one way or another), so there's a little extra room from that, but not much.
      - usaar333 7y ago
        > It's true that people are discharged from the hospital eventually (one way or another), so there's a little extra room from that, but not much. No, you need to account for that. We're at steady-state to decreasing hospitalization already (that is at r=1, increase = decrease).
        mattkrause 7y ago
        California is somewhere near steady-state (R=1) right now, but that's not a "stable" point, in the dynamical systems sense. A small decrease below R=1 would lead to falling rates, but a small increase above R=1 can make them skyrocket. I'm not sure if there's good data on the length of hospital stays, but an early preprint from China reported a median stay of 19 days. That's not much help here: On day 20, the intake is 60% larger than the initial cohort--and only half of them (b/c median) will be discharged. People with more data and expertise!) have worked up full SIR and utilization models, but the general point is that exponential growth is manageable, even boring, until suddenly it suddenly isn't.

Without social distancing or contact tracing. The Bay Area's r is probably around 0.8 at this point with Santa Clara even lower (EDITED - see notes below). Some restrictions can be relaxed.

MrGando 7y ago

> The Bay Area's r is probably under 0.8 at this point Could you tell me where are you getting this magic number ballpark estimate from? (somewhere concrete, not just your gut and imagination)

usaar333 7y ago
Various data points. This is an upper bound, more calculated for Santa Clara county. International comparisons to lockdown level and case count changes. Assuming serial interval of 4 and > 10x non-detection rate on March 31 and 3x now gives you this. Knowing people were dying if the disease in early February implies very high lack of detection when SIP was in place. (Likely over 800 infections a day when Santa Clara activated SIP) Edit: More detailed explanation above.

killion 7y ago

Rt of .88 according to https://rt.live https://rt.live I agree some restrictions could be relaxed. Hospitals were a good first step. More of the outdoors could be a good next one.

usaar333 7y ago
Note that is CA as a whole. LA is skewing it upward. e.g. CA was around 1250 new cases 2nd week of April and maybe 1200 now (4% lower). With test capacity increasing, rt.live is giving 0.88, which on a 4 day serial interval implies a 33% actual reduction Bay Area went from about 200 to about 140 now (30% lower). Factoring the reduction from testing (if same for all of CA), we're actually at a 53% reduction. That's an R of 0.81. Santa Clara (which I admittedly originally mis-used for all Bay Area) went from 62 to 25. That's an crude R of 0.77 -- 0.7 factoring the test increases.
mattkrause 7y ago
0.88 doesn't buy you very much room. If it creeps up to 1.1, you still don't need many rounds of infection to completely overwhelm the system. 7 rounds of infection (~a month) would result in 10.4x more total patients.
- usaar333 7y ago
  I'm not following your math. On a serial interval of 4, 7 rounds of infection does take a month, but that's only 1.1^7 = 2.
  - mattkrause 7y ago
    That's new cases though, isn't it? I was summing over the entire "tree" to get the total instead. If R0=2 (each person infects two more), you have 1 case at time zero, two after the first time step, and four after the next, but the total number of cases is 1+2+4=7, not 2^2. It's true that people are discharged from the hospital eventually (one way or another), so there's a little extra room from that, but not much.
    - usaar333 7y ago
      > It's true that people are discharged from the hospital eventually (one way or another), so there's a little extra room from that, but not much. No, you need to account for that. We're at steady-state to decreasing hospitalization already (that is at r=1, increase = decrease).
      - mattkrause 7y ago
        California is somewhere near steady-state (R=1) right now, but that's not a "stable" point, in the dynamical systems sense. A small decrease below R=1 would lead to falling rates, but a small increase above R=1 can make them skyrocket. I'm not sure if there's good data on the length of hospital stays, but an early preprint from China reported a median stay of 19 days. That's not much help here: On day 20, the intake is 60% larger than the initial cohort--and only half of them (b/c median) will be discharged. People with more data and expertise!) have worked up full SIR and utilization models, but the general point is that exponential growth is manageable, even boring, until suddenly it suddenly isn't.