LA County Recovery Model

[08/12/20 Update: This analysis from May assumed a gradual and measured return to normal per the CDC guidelines.  The rapid June return to high connectivity that caused the summer surge was not anticipated.  As a result, the winter surge shown below has moved to summer.  LAC is currently nearing 5000 deaths.  It is likely that the ultimate conclusion of the 50% asymptomatic case below is much the same in terms of total deaths once the infection dies down.]

Los Angeles County, like the rest of the west coast, has had a fairly low initial death rate compared to New York, Italy and Spain. The death rate in this current wave is comparable to deaths for a typical flu season (Pneumonia and Flu). Since a small percentage of the overall population has been exposed to the virus, and the reproductive rate has been pushed well below 1, we can begin to return to normal.

Our LA County recovery model illustrates that recovery measures can be implemented now with minimal risk, buying time for the development of therapeutic measures. The model assigns two months for each phase of the White House/CDC plan for recovery. We allow for mild summer reduction in the transmission rate and mortality rate. Our analysis of the simulation input parameters is here.

The model shows that the a second wave of the virus does not appear until the transition to full recovery (return to normal). But the decision to transition to full recovery can be deferred and mitigation strategies adjusted to protect those who are vulnerable, or to respond to high infection rate opportunities (like large events).

We present two separate cases. The first case assumes that 50% of cases are asymptomatic (which results in an initial death rate of 0.5%). The second case assumes 80% of the cases are asymptomatic (which results in an initial death rate of 0.2%). Recent testing by USC and the LA County Department of Health [USC Release] are in line with the assumption that 80% of cases are asymptomatic.

If we assume 50% asymptomatic, the daily death rate in the simulated second wave is about the same as the first wave at the peak, but is spread out over greater time, resulting in twice as many deaths as the first wave. General herd immunity can be established in early 2021 assuming that a long-term 20% reduction in social contacts is achieved (sustained moderate social distancing). Note that once a return to normal occurs the number of infections increases sharply and the number of infections at the peak is greater than the initial number of infections which was controlled by the lockdown.

If we assume 80% asymptomatic, the daily death rate in the second wave is much lower than the first wave, but since the infection is spread out over time it results in about the same number of deaths as the first wave.

Deaths Versus Time [50% Asymptomatic]
Deaths Versus Time [80% Asymptomatic]
Below are the cumulative numbers from this simulation. The number of infected people in the general population is fairly low, and as such, Los Angeles County is vulnerable to a second wave as our analysis shows, but will reach herd immunity once >35% of the population is exposed if the contact rate is held to 80% of the initial baseline.

Since we are protecting the vulnerable, most of the deaths are within the general population. For the 50% asymptomatic case, the death rate is pretty low in this scenario: 6300 deaths divided by a population of 2.9 Million (dead+recovered+infected) infected is a death rate close to 0.22%. In the 80% asymptomatic case, the death rate is even lower, about 0.12%.

With 50% asymptomatic, hospital demand in the second wave is about the same as the first for the critical care beds and three times for standard hospital care. With 80% asymptomatic the second wave has the critical care demand one third of the first wave and standard hospital demand is about the same as the first wave.

Cum Versus Time [50% Asymptomatic]

Hospital Load [50% Asymptomatic]

Cum Versus Time [80% Asymptomatic]

Hospital Load [80% Asymptomatic]

The plot of the R(t), the reproduction factor over time shows Phase 1 and Phase 2 mitigation strategies keep the outbreak in check.  Phase 3 and beyond show a slow regrowth over time.  R(t) is a measure of the number of people infected by each infected person over time.  The average time of infectiousness (T Ave) is assumed to be 9 days.

R(t) [50% Asymptomatic]

R(t) [80% Asymptomatic]




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