COVID-19 Study Review – Outbreak including COVID-19 Vaccine Breakthrough Infection – Delta Variant

COVID Massachusetts

How current was the study?

The study was published on August 6, 2021 as an MMWR Early Release. MMWR is the Morbidity and Mortality Weekly Report from the CDC.

Is there a source?

This study was conducted in late July or early August, 2021. This article is straight from the CDC and contains the details of the study.


Brown CM, Vostok J, Johnson H, et al. Outbreak of SARS-CoV-2 Infections, Including COVID-19 Vaccine Breakthrough Infections, Associated with Large Public Gatherings — Barnstable County, Massachusetts, July 2021. MMWR Morb Mortal Wkly Rep 2021;70:1059-1062. DOI: icon.

Primary or Secondary Dataset?

This study was based on two Secondary Datasets, specifically the Massachusetts state immunization registry, and travel history data from the state’s COVID-19 surveillance system.

How was the sample collected?

Let’s talk a little bit about what a sample is, and then I’ll share more about the sample for this study.

What is a sample?

Remember from my previous review, that the sample is intended to represent a larger group – or put differently, it’s intended to be a part that represents some whole.

If our sample, for example were made up of 50 pregnant women, the population those 50 pregnant women represent likely would be limited to the female population, more specifically, pregnant females.

But what if the fact that the women were pregnant had nothing to do with the study? To better understand the population that is represented, you have to know more about the sample and about the study. Perhaps pregnant women were easier to survey for the researcher, and perhaps the pregnant women are all Hispanic. We would infer based on that additional information that the represented population could be all Hispanic females.

You have to understand the sample, the biases that influenced the sample, and the nature of the study to understand what population that sample represents. As we look at COVID research, or any research for that matter, the sample matters, and is almost always overlooked by the media.

Hispanic pregnant women have nothing to do with this study, but I think it’s important for you to understand what a sample is, and how to really think about the population that sample represents.

Back to this study sample

The sample was collected by the MA Department of Public Health. They looked at the state’s COVID-19 surveillance system data, queried/identified a group of residents that clustered together geographically, and then matched that up with the state’s immunization registry.

The reason the MA DPH looked into the data in this manner was because on July 3rd, 2021, the 14-day average COVID-19 incidence of zero cases per 100,000 persons per day in residents of a town in Barnstable County jumped up to 177 cases per 100,000 persons per day by the 17th. In other words, a lot changed in 2 weeks – 0 cases per day to 177 cases per day for a single town. According to the US Census Bureau, Barnstable Town, MA has a population of about 44,477 in 2019. So .4% of the population were testing positive for SARS-CoV-2 each day.

The criteria they used to identify a cluster case was as follows:

  • A positive SARS-CoV-2 test (nucleic acid amplification or antigen)
  • 14 days or less after traveling to or living in the town in Barnstable County since July 3rd.

Breakthrough cases are defined as fully vaccinated Massachusetts residents (those documented within the state immunization registry of completion of COVID-19 vaccination 14 or more days prior to exposure. Unlike the previous study I reviewed, the MA DPH used whole genome sequencing through the MA State Public Health Laboratory or the Broad Instituted of MIT and Harvard University. They obtained 211 specimens for testing and then on July 15th the MA DPH issued two notifications to identify additional cases.

By July 26th, 469 COVID-19 cases were identified with positive specimen collections between July 6th and July 25th.

In short, the MA Department of Health noticed a significant uptick in positive COVID testing for a specific town, and then looked at recent events and geographies to identify people who came into contact with one another. These are the 469 people included in this study.

What were the findings?

Below is a figure that shows days a specimen was collected for testing across the bottom, with the height of the bars representing the number of cases. The Stacked Bar chart shows fully vaccinated individuals as light blue, and unvaccinated or not fully vaccinated as blue bars.

You can tell by the graphic that the number of cases rose quickly, and that the number of vaccinated individuals significantly outnumber the unvaccinated individuals.

So now for some stats.

  • 399 (85%) were males, 70 (15%) were Female
  • Median Age was 40 years – for those unfamiliar with Median, that means the very middle age of all 469 people was 40. Not sure why they didn’t include the mean (average). Seems odd to me that they would use median. Perhaps the ages were all over the place and the mean wasn’t useful. The age range for the 469 people was <1-76.
  • 199 (42%) live in Barnstable County. I’d infer that the rest lived outside and somehow came into contact with these 199.
  • 346 (74%) reported that they had symptoms similar to COVID-19.
  • 5 were hospitalized, and as of July 27th, there were no deaths.
  • They did not do genomic sequencing for all 469. For the initial 133 people that they found first, they did do genomic sequencing and 89% of those had the Delta variant.

Here’s where things get interesting.

  • 346 (74%) of the 469 cases were fully vaccinated individuals.
  • 301 (87%) were male
  • Median age of 42 years
  • 159 (46%) had the Pfizer-BioNTech Vaccine
  • 131 (38%) had the Moderna Vaccine
  • 56 (16%) had the Janssen (Johnson & Johnson) Vaccine
  • The study included the general population’s vaccination coverage as well:
    • 56% of fully vaccinated people in Massachusetts had received the Pfizer-BioNTech Vaccine
    • 38% had received the Moderna Vaccine
    • 7% had received the Johnson & Johnson Vaccine
    • The study didn’t indicate what percent of the overall population was vaccinated.
  • 274 (79%) of the 469 fully vaccinated people reported symptoms of COVID-19 including cough, headache, sore throat, myalgia and fever.
  • These fully vaccinated individuals had received the final dose of the vaccine 20-198 days prior to this study, with the median or middle number of days being 86.

Now, let’s talk about the 5 people that were hospitalized

  • 4 were fully vaccinated.
    • Ages ranged from 20-70 years old
    • Two had underlying medical conditions (comorbidities)
    • Two did not have underlying medical conditions.
  • 1 was not vaccinated
    • Age was between 50-59
    • Had multiple underlying medical conditions.

In short, more vaccinated people were impacted by this outbreak than unvaccinated, and 4 of the 5 hospitalized were vaccinated. If you look closely at the details about the 4 people hospitalized, you’ll note that at least one of them was in their 20s and two of them had no underlying medical conditions.

What were the limitations?

The study listed 4 limitations.

  • “The data from the report are insufficient to draw conclusions about the effectiveness of COVID-19 vaccines against SARS-CoV-2 including the delta variant during this outbreak.” – Meaning, readers shouldn’t take this study as a knock against the vaccine.
  • “asymptomatic breakthrough infections might be underrepresented because of detection bias” – Meaning, there may have been more fully vaccinated individuals who were re-infected, but not included in the study because they didn’t show symptoms.
  • “demographics of cases likely reflect those of attendees at the public gatherings, as events were marketed to adult male participants” – Meaning, the sample is mostly males because of a mostly male attended event. The study doesn’t indicate what the event was.
  • The tests (NAAT) that were done “provide a crude correlation to the amount of virus present in a sample. , and can be affected by factors other than viral load.” meaning – the tests that were done don’t give the researchers precise information about how impactful the virus was to each person. “This might mean that the viral load (how much of the virus a person has in their body) of vaccinated and unvaccinated persons … is similar”. In other words, it’s possible vaccination didn’t reduce the impact of the virus.

What you should consider

  • Did they cite a source and can you navigate to it? 9/10. I would give a 10/10 if I could actually get my hands on the dataset itself.
  • Did the source clearly describe how the data was acquired. 5/10. They could have done a much better job defining their data sources and the criteria by which they pulled and merged the datasets together. Much was left for inference.
  • Did the source cite potential biases or limitations to the study? 7/10. They provided 4 potential limitations which I described above. They did not describe the validity or reliability of their research.
  • Is the source reputable? 9/10. The CDC has long been a reputable source for human research studies. There are potential biases, given the source of CDC funding, executive and media biases along with public opinion, etc. The researchers conducting the research are really the sources for the study, and without further investigation into each one specifically, professionally I would not suspect intentional researcher bias.
  • We’re there enough participants in the sample? 8/10. The sample size has an N > 32, which is often the threshold to meet statistical significance. In this case there were almost 500 people included in their sample. Keep in mind the sample was 85% male, and the ages were all over the place. Also, it would be interesting to see what the event was that brought all of these people together. That might provide additional information into their lifestyles, health etc. If it was an overweight biker convention, for example, I wouldn’t consider the sample representative of the majority of males. Also, race/ethnicity, and other demographics were completely unmentioned.
  • Did the study or news article focus on one finding and not talk about other findings that are obviously visible in the study? 7/10. I feel like this is an underrepresented study in the news, for obvious reasons. One thing that was not mentioned was the size or category of the event that led to the outbreak. If the event had 50,000 people, and this small group of people were the only ones infected, that would be very different than an event of 600 people.
  • Are all the variables included that you think are necessary to arrive at the same conclusion, or at least identified as limitations? 3/10. I think this study tells us a lot about the efficacy of the vaccine in males in MA that attended this event. It did not really describe a conclusion, and I haven’t seen news articles bringing this study up. There are a lot more demographics and other variables that would have added a lot to the value and the representative population of the study.
  • Is the study clearly described to the point that it could be reproduced by someone else given the same data and research background? 4/10. In my opinion, they did a terrible job describing the process they went through. It could be that the full study and write-up just aren’t complete yet, but they could have been much more specific.

My Conclusion

I think this is a great example where the media focuses on headlines that match their agenda. I think a lot of people who have strong opinions about requiring people to be vaccinated, have totally missed and/or completely dismissed studies like this.

Longitudinal health research (or in other words, health research that requires time to pass) for COVID is severely limited. The pandemic started a little over a year ago, and the vaccine has only been out for about 8 months. That’s a very short amount of time to study the impacts of the virus, and the efficacy and effectiveness of a trial vaccine. It’s certainly not enough time to understand the long-term impact of the vaccine.

As a middle-aged male, this study gives me pause for obvious reasons. If you are vaccinated, is there an increased risk? Or were there just not many unvaccinated people at the event? If you are unvaccinated, does this study make a case for getting vaccinated?

Additionally, I want to point out that this is a delta variant. Another study I’ve seen lately is about the enhanced immunity of vaccinated individuals over the natural immunity of those who have had COVID – specifically enhanced immunity for other strains of the virus. This study doesn’t seem to indicate an enhanced immunity against variants for vaccinated individuals. To the contrary, it indicated that the viral load seemed to be the same. Keep in mind though, that we don’t know the extent of symptoms, and the study didn’t really compare the symptomatic severity of cases.

Also, there really wasn’t a difference between the types of vaccine. It wasn’t like one of them was way better than the other two. I haven’t seen claims to one being better than another, but it would have been interesting if that were the case. The percentage differences I listed above are really just informative of who had which vaccine.

Lastly, I’d really like to know more about the men included in the sample. If you know what events were tied to this study, please comment below. If I find out, I’ll come back and edit this for future readers. I think those details would help us better understand whether this study applies or could be representative of you and me.