3 ms·

> the transmission rate dropped again, to the point where any single case led to less than one more. Once that happens, an epidemic dies. Unless, you know, it'

> the transmission rate dropped again, to the point where any single case led to less than one more. Once that happens, an epidemic dies. Unless, you know, it's as contagious as corona. Then it only takes one person to infect an office or grocery store or hospital (as happened with SARS-1 in S. Korea.) I wish people would start using facts, instead of hope.

lutorm 7y ago
What do you mean? That statement is manifestly true. IF any single case leads to <1 additional case, then the numbers will decline. That's math. One person being able to infect an entire office just means it will be harder to get to that point.
- SpicyLemonZest 7y ago
  The epidemic isn't "dead", in the author's words, until we stop having to take emergency measures to fight it. A plan that doesn't finish with "then we reopen sports stadiums and stop all social distancing" isn't a plan to end the epidemic, and social distancing is one of the author's five prongs.
- KMag 7y ago
  More succintly: In the SIR (Susceptible, Infected, Resolved) epidimic model, r0 is the ratio of dI/dt / dR/dt. r0 < 1 means people are recovering at a rate faster than new people are getting sick. If each new case, on average results in less than one new case, and all cases eventually resolve (recovery or death), then it's a mathematical truth that the number of active cases must go down over time. The decrease isn't necessarily monotonic, but over a long enough time frame it's inevitable. The bursty nature of super-spreading will produce variance, but as long as these super-spreaders are accounted for in the observed r0, the variance itself doesn't change the long-term outcome. Now, the estimated/measured r0 is just a sample/estimate of the (unknowable) "true" r0, and r0 isn't constant, but those are separate issues.

3 ms·

> the transmission rate dropped again, to the point where any single case led to less than one more. Once that happens, an epidemic dies. Unless, you know, it'

by redis_mlc 7y ago

lutorm 7y ago
What do you mean? That statement is manifestly true. IF any single case leads to <1 additional case, then the numbers will decline. That's math. One person being able to infect an entire office just means it will be harder to get to that point.
- SpicyLemonZest 7y ago
  The epidemic isn't "dead", in the author's words, until we stop having to take emergency measures to fight it. A plan that doesn't finish with "then we reopen sports stadiums and stop all social distancing" isn't a plan to end the epidemic, and social distancing is one of the author's five prongs.
- KMag 7y ago
  More succintly: In the SIR (Susceptible, Infected, Resolved) epidimic model, r0 is the ratio of dI/dt / dR/dt. r0 < 1 means people are recovering at a rate faster than new people are getting sick. If each new case, on average results in less than one new case, and all cases eventually resolve (recovery or death), then it's a mathematical truth that the number of active cases must go down over time. The decrease isn't necessarily monotonic, but over a long enough time frame it's inevitable. The bursty nature of super-spreading will produce variance, but as long as these super-spreaders are accounted for in the observed r0, the variance itself doesn't change the long-term outcome. Now, the estimated/measured r0 is just a sample/estimate of the (unknowable) "true" r0, and r0 isn't constant, but those are separate issues.