This dashboard tracks the San Diego COVID experience: new cases, tests, and positivity rates at the county-level as well as new cases for each of the county’s ZIP Codes.

On this first-year anniversary of these daily postings, we thought we would look back at this roller coaster year.

And, although our dashboard does not include US data, we thought that comparing the San Diego COVID experience with the national average would be insightful.

San Diego COVID experience vs the nation

The following figure shows the 7-day moving average of daily new cases per 100,000, for both San Diego County and the entire US.[1]

As shown in the above figure, as a nation we have been through 3 waves with it being too soon to tell if the 4^th wave has crested. San Diego County’s experience was generally similar except for the 4^th wave.

Wave #1

The initial rise in daily new cases crested at a 7-day average of 10 per 100,000 for the US on April 12, 2020. San Diego’s first wave crested about a week earlier on April 4^th at about 4 per 100,000.

The US new case 7-day average fell to 6 per 100,000 by mid-June. San Diego’s briefly fell a bit but then rose back up to a daily rate of 3 to 4 per 100,000 till mid-June.

So, San Diego did not really experience the same recovery from the first wave as the US.

Wave #2

For both the US and San Diego, the second, much larger wave began in mid-June 2020. The US new case rate increased from a 7-day average of about 6 per 100,000 to a peak of 21 per 100,000 on July 23^rd. San Diego’s rate increased from about 4 per 100,000 to a peak of 16 per 100,000 on July 2^nd.

Both the US and San Diego new case rates declined through the end of the summer. The US new case rate bottomed at a 7-day average of 13 per 100,000 on September 13^th. San Diego’s bottomed at the end of August at about 8 per 100,000 and stayed essentially flat till mid-October.

Wave #3

The US third wave began in mid-September – a full month before San Diego was hit. Rising from a 7-day average low of about 11 per 100,000, the US new case rate increased throughout the fall and early winter, peaking at 76 cases per 100,000 on January 11, 2021.

San Diego’s third wave began in mid-October. From a 7-day average low of about 8 new cases per 100,000 on October 20, the new case rate peaked at a high of 109 per 100,000 on the same day that this third wave peaked for the country.

As the figure shows, San Diego (as well as Los Angeles) suffered much higher new case rates than the national average.

But daily new cases started to decline just as steeply as they increased. San Diego’s 7-day average new case rate fell from this high of 109 to around 7 per 100,000 by April 20, 2021.

The US new case rate fell as well, from a 7-day average of 76 to about 16 by March 19, 2021.

Wave #4

Until this point, San Diego’s experience, though different in severity, matched the general pattern of the country. However, a 4^th US wave began in mid-March 2021, driven by new outbreaks in Michigan and New Jersey. It is too soon to tell if this 4^th wave has crested but the most recent peak is a 7-day average of 21 new cases per 100,000 on April 13^th.

San Diego has been fortunate to escape this 4^th wave (so far).

Fingers crossed…

[1] San Diego new case data are from the San Diego County Health Department. US new case data are from the CDC.  The 7-day moving average is the average of the current and preceding 6 days. 2019 population is used to normalize case counts so we can compare San Diego with the nation.

The post San Diego and COVID-19 … A Very Challenging Year appeared first on KDD Analytics.

But oh, if we call the whole thing off
Then we must part
And oh, if we ever part
then that might break my heart

—Ira Gershwin

The eye-popping efficacy rates reported for the Moderna (94%), Pfizer (95%) and, to a lesser extent, the Johnson & Johnson (66%) COVID-19 vaccines have undoubtedly not escaped your attention.

But what is vaccine efficacy and how is it calculated? And how does it differ from vaccine effectiveness?

Moderna vaccine efficacy

First, consider efficacy. Using Moderna’s reported clinical trial results as an example, we see that it is a straightforward calculation.

Moderna reported results from it’s COVID-19 vaccine trial in November 2020. The results are shown below in a 2×2 “contingency” or “cross-tabulation” table. The columns show the number of subjects who were infected (or not); the rows show the number who received the vaccine (or the placebo). And the cells show the intersection of those two events.

Relative risk

The strength of the association, or the effect size, between receiving the vaccine and not getting infected is measured by the relative risk.

The probability or risk of a vaccinated subject being infected is 0.08%. That is, (11 / 14,134) or the expected number of events / sum of events and non-events. For a subject receiving the placebo, the probability of infection is higher at 1.31% (i.e., 185 / 14,073).

So, using the placebo group as the reference group, the relative risk is (11 / 14,134) / (185 / 14,073) or 0.059.[1]

In other words, the risk of a vaccinated person being infected is 94.1% lower compared to a subject who received the placebo (i.e., (1 – 0.059) * 100)).

It is this calculation of 94.1% that was reported by Moderna as the vaccine’s efficacy rate.[2]

Vaccine effectiveness

So, what about vaccine effectiveness? The term effectiveness refers to how the vaccine performs in the real world.  Efficacy refers to how the vaccine performs under “optimal” conditions of a clinical trial.

Clinical trials are based on a sample of subjects who may not be fully representative of the general population (e.g., all comorbidities are not controlled for). In addition, the COVID strain that existed in the population during the clinical trial period may not be the same that occurs when the vaccine is released. Also, vaccine transportation, storage and delivery may differ from the more controlled environment of the clinical trial. Thus, the effectiveness of the vaccine may be different from what was found during the clinical trial.

Studies on COVID vaccine effectiveness

So, do we have any data yet on the real-world effectiveness of the COVID vaccines? It takes time to collect data, but we do have some indication that vaccine effectiveness is very high.

An early study appeared February 24, 2021 in the New England Journal of Medicine.  The study examined the Pfizer vaccine performance in Israel. The sample was matched data from over 1 million people, half who were vaccinated between December 2020 to February 2021 and half who were not. The results of the study suggest a symptomatic infection effectiveness rate of 94% 7+ days after the second dose.

A more recent study released by the CDC on April 2 examined both the Pfizer and Moderna vaccines.  This study used US data from December 2020 to March 2021. The sample consisted of 3,950 health care personnel, first responders, and other front-line workers.  The study found that the vaccines were 90% effective against COVID infection 14+ days after the second dose. Even 14+ days after the first dose the vaccines were 80% effective.

As a point of comparison, according to the CDC, effectiveness of the annual flu vaccination ranges between 40 and 60%.[3]

So, the effectiveness rate, after 2 doses of the Pfizer and Moderna vaccines, appears to be very close in magnitude to the efficacy rate.

Very good news indeed!

Tomato, tomahto?

[1] A relative risk ratio of 1.0 would mean no difference in effect between the treatment types.

[2] A summary of efficacy rates across the range of current COVID vaccines can be found here.

[3] One reason for the range is that the flu strain that is in circulation can differ from what was predicted when the annual flu vaccine was developed earlier in the year.

The post Efficacy vs Effectiveness of the COVID Vaccines…”tomato, tomahto”? appeared first on KDD Analytics.