Antibodies Children GA Innovative Solutions National changes Social Distancing


Buckle up. In true 2020 fashion, several scientific developments popped up while I was on vacation…

1. Teachers’ and parents’ risk for severe COVID19

• 2.95 million teachers (50.6%) have risk factors for severe COVID19. This is mostly driven by obesity or heart conditions

• 37.7 million adults living with school-aged children (54%) have risk factors for severe COVID19. This is mostly driven by age, heart problems, or diabetes

• Risk is the same for those living with younger children compared to older children.

• So… what? “Without adequate safeguards, reopening schools could put millions of vulnerable adults at risk for severe COVID-19 illness”.

2. First global case of COVID19 re-infection

• In March, a 33-year-old man in Hong Kong was infected with COVID19. He had mild symptoms.

• Last week, he was infected with a different COVID19 strain and tested positive upon his arrival to Hong Kong from Spain. He is asymptomatic.


• After the first infection, he had no antibodies. But we already know that not everyone gets antibodies (especially mild symptoms; see my previous posts)

• After the second infection, he did produce antibodies. This is consistent with the immune system building stronger with each exposure to a pathogen, so second and third exposures may increase the chances to develop antibodies.

• In the words of immunologist Dr. Akiko Iwasaki, “This is no cause for alarm – this is a textbook example of how immunity should work.”

• Vaccination (and social distancing and masking) needs to be considered among people that have already been infected with COVID19

3. Wearing masks works (I feel like this is no duh, but in case you needed more ammunition)

• US states with high mask wearing compliance were more likely to have a R(t) less than 1 (control of community transmission)

• Mask wearing was higher among women, elderly, non-white or Hispanic, lower income people

• Mask wearing is highest along the coasts, southern border, and urban areas (see Figure)

• Mask wearing is even more important when (or if) social distancing is relaxed

4. Super-spreaders played a key role in MERS and Ebola. Their role in COVID19 was just revealed in Georgia:

• 2% of the population is responsible for 20% of infections• Super-spreaders likely explain major outbreaks in rural areas • Younger people are more likely to be super-spreaders

Love, YLE





Children GA

GA summer camp

Attack rate among kids at an overnight camp in Georgia. A case analysis. 

What happened?
June 17–20: Orientation for 138 trainees and 120 staff members
June 21: 138 trainees left. 363 campers and three senior staff members joined staff
June 23: Teenage staff member left camp because of symptoms
June 24: Teenage staff member tested and reported a positive COVID19 test 
June 24: Officials began sending campers home
June 27: Camp closed 

Interestingly, this camp did adhere (to the most part) of state requirements. All trainees, staff members, and campers were required to provide documentation of a negative viral SARS-CoV-2 test ≤12 days before arriving. Staff members also were required to wear cloth masks (if they actually did, we don’t know).

However, some measures were not implemented:
• Kids didn’t wear cloth masks
• Windows and doors were not opened to increase ventilation 
• A variety of activities were indoor and outdoor, including daily vigorous singing and cheering.

Figure shows attack rate: high across all ages. CDC concluded: “This investigation adds to the body of evidence demonstrating that children of all ages are susceptible to SARS-CoV-2 infection and, contrary to early reports, might play an important role in transmission”.

Love, your local epidemiologist

Data source
Szablewski CM, Chang KT, Brown MM, et al. SARS-CoV-2 Transmission and Infection Among Attendees of an Overnight Camp — Georgia, June 2020. MMWR Morb Mortal Wkly Rep. ePub: 31 July 2020. 

AZ California Deaths FL GA Texas update

Case Fatality Rates

On July 7, I posted five reasons as to why CFR may be decreasing while cases are increasing. One of which was lag time.

In other words, deaths today aren’t indicative of spread today, but rather a reflection of case severity 20-30 days ago. It’s been 27ish days since exponential growth started across several states. We should start seeing an uptick in CFR if this hypothesis is correct.

And we are. This is obvious in TX and CA. Doesn’t look like there is change in FL, AZ, or GA (yet). Given the spread among the younger population, this lag time may be even more than 30 days.

It’s still too early to see the impact of this recent uptick in TX and CA on cumulative CFR (Figure 2).

So, what’s causing this increase in TX and CA? Either we have reached hospital capacity (which we haven’t). OR COVID19’s reach is so wide it’s starting to reach vulnerable populations. OR we are increasingly testing those that are more sick (indicative of a high test positive rate). It’s likely a combination of the latter two. CFR is a difficult measurement because it’s highly dependent on the number cases we catch. For example, if we are only testing high risk populations (like nursing homes), the CFR will be high. It’s typically missing asymptomatic or mild cases that just never get tested.

Because of this, public health decision makers are starting to use Infection Fatality Rate (IFR). IFR estimates the fatality rate among those infected (detected AND undetected cases).

In the US, the CDC’s best IFR estimate is 0.65%. So, on average, 6.5 people of 1000 infected will die of COVID19. A recent publication pooled global IFR; IFR ranged between 0.53% and 0.82%. IFR is a more direct measure of disease severity, although highly dependent on place.

Understanding the true fatality rate has implications for public health planning. Unfortunately, if you thought the CFR was “low”, you are really not going to worry about 0.65% IFR. Given the reach of COVID19, this is still very much a leading cause of death in the US. The morbidity of COVID19 should still be of great concern too.

Love, your local epidemiologist

Data source: COVID19 tracking project. Graphs by yours truly.
Pooled IRC:…/10.1101/2020.05.03.20089854v4
CDC report:…/…/hcp/planning-scenarios.html