Tracking COVID-19 in the Silicon valley and SF Bay Area

So we are in the middle of a pandemic. Or rather in the beginning according to some projections. And every new day we spend indoors working from home with two little kids, makes me a little more motivated to follow of trends of the new cases data in our area. I hope this will help you stay informed.

Silicon valley traditionally included only South Bay, but nowadays it really refers to everything between San Francisco to San Jose and spans three different counties – Santa Clara, the largest county, San Mateo and San Francisco. Longitudinal data for all of these counties is not easily available because the official websites report either all the numbers or the fatalities numbers only for the current day. To trace our trajectory, I collect daily data from the official websites, corroborate it with other news outlets and update the cases chart.

Updated on 04/20 [note San Mateo data reports lag one day, so all data here lags one day] This chart is showing the cases in the three counties. The number of cases went up today by 98 cases with a total of 4039. The growth in the last week has been fairly stable, between 100 and 200, per day. Two new deaths were reported. The count is at 125 deaths (3% mortality rate, although see the discussion of new research findings below).

Two new fatalities were reported in Santa Clara county with a total of 77. With 1903 total cases, it makes for a 4% death rate. Good news is that the death growth in Santa Clara continues to be linear – the dashed grey curve on the graph is a linear fit with a slope of 2, which means 2 new fatalities per day on average. The line for the valley is closer to 4 fatalities per day. According to new data from the county, San Jose accounts for ~70% of the COVID-19 cases in Santa Clara county.

New research, randomly testing a sample of the population for presence of COVID-19 antibodies, from Stanford found that the real number of cases in early April should be between 48,000 and 81,000, 50-85-fold more than the number of confirmed cases (~1K in the first week of April). It that is the case, the true mortality rate in our county is closer to 0.1%.

More good news come from the new data on hospitalizations. It seems like what we are doing is working. The hospitals are not overrun. Currently about 1/3 of the ICU beds in Santa Clara county are available (99 beds) and 77% of the ventilators are not in use and available (609 ventilators).

On March 26th, the San Jose Deputy City Manager Kip Harkness said that “Even in the best-case scenario, we were looking at the order — in the next 12 weeks — of 2,000 potential deaths directly from COVID-19” in Santa Clara county. The article reported that “officials have not explained publicly how they devised those estimates” . At the time, I investigated this using the available data I’ve been tracking. I projected a polynomial growth curve, that fits the cases data the best, 12 weeks from March 26th and got 53.5K cases. The mortality rate in the last weeks has been dancing around 4%. If we apply this rate to the number of cases, we, sadly, get 2.1K.

However, the death growth in Santa Clara county has been linear with a slope of 2. So if we project this curve to June, we only get ~150 fatalities. Much better than what we expected based on the data in March.

Data sources:

8 thoughts on “Tracking COVID-19 in the Silicon valley and SF Bay Area

  1. I’ve noticed that the sum of ‘community’, ‘travel’, and ‘contact’ numbers (from the SCC Health website) rarely matches the number of cases. So I suspect that the percentage of community transmission is much higher, they just haven’t done the detective work to determine the most likely source.


    1. I think you’re right, as of right now they accounted only for ~60% of the cases. I don’t know how much investigation they are doing anymore. Likely more was done with the first cases and less now that their hands are full.


  2. I think the curves should be done also as an exponential curve to show if the number of cases has exponentially grown. After all, it is the reason why we have a shelter in place to dampen exponential growth of cases.


    1. I played around with various exponentials and none were a good fit for Santa Clara. It’s a seemingly good thing, but cases data is limited by testing and there is no data source as far as I know that shows the number of tests performed for our area.


  3. I’d be very interested in seeing these plots, but with death rates (and hospitalization rates, which were posted by SCC, if you tracked those). As you note, the active cases are limited by tests, but these other numbers are not (yet, while we still have beds).

    Using the data of other countries who are farther ahead then the US in terms of the spread, we can try to extrapolate the potential active cases from these other numbers (3-5% death rate for the US, but other numbers could be used – see analysis in section 2 of this post:

    But, more importantly, seeing the trend lines of those confirmed numbers will help tell if the actions being take now are ‘flattening the curve’. Do you have the time and data to plot these?


    1. @Karen Agreed, these can be more informative. Today SCC switched to a dashboard based reporting and stopped reporting hospitalizations. So unfortunately this data is not available anymore. I am tracking the death and can plot them, so far it’s been 3-4% of the positive cases for the last week.


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