@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
This is a thread discussing Pediatric COVID-19 vaccination. Contents: 1) Detailed review of Vaccine Adverse Events Reporting System (VAERS) for the 16yo-17yo age group https://wonder.cdc.gov/vaers.html 2) Examine Pediatric mortality estimates & compare to adverse event rate 1/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Contents (cont): 3) Review the # of patients required to assess efficacy & safety in the <18yo population 4) Review "# needed to treat" (NNT) & "# needed to harm" (NNH) 5) Extend discussion to "# needed to vaccinate" (NNV) & possible limitations of this concept 2/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
I downloaded the VAERS data for 6-17yo (so effectively just 16yo and 17yo) validated through 5/19/2021. I restricted analysis only "serious" events (returned 124 results). https://wonder.cdc.gov/vaers.html 3/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
As some have noted, some VAERS entries, even ones labeled "serious", are a bit silly. They are known side effects or clearly incidental (i.e., emotional reactions to the circumstances, mistakes on age). Not counted by me: vague reports, moderate allergic or other reactions 4/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
But there is already some signal in just this cohort: 9 Critical condition 3 Cardiac Arrests 1 Stroke while on anticoagulation 1 Guillan Barre Syndrome 6 anaphylaxis (1 counted in the PICU tally) 6 new onset or exacerbation of seizures 4 Myocarditis/Pericarditis 5/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Fully Vaccinated by 4/20/21: 3.10% (260400) Fully Vaccinated by 5/20/21: 19.90% (1671600) https://covid.cdc.gov/covid-data-tracker/#vaccination-demographics-trends Serious Adverse Events (AE) as of 5/19/21: 29 Reporting Lag: assumed @ ~1 month. A serious pediatric event I reported in mid-April was not in my download. 6/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Serious adverse event rate: 4/20/21 vax percentage: 0.00011 5/20/21 vax percentage: 0.000017 Download from VAERS Wonder was on 5/19/21 so it's likely that the 4/20/21 serious AE rate above is more accurate. 7/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
C19 mortality for kids is very low, but the exact number is difficult to pin down. Estimation method based upon CDC numbers with references providing low and high bounds. 8/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Consequently, roughly speaking, in the best case scenario, the AE rate essentially matches COVID-19 mortality in the <18yo group. When probabilities of harm from COVID-19 are so low, treatment trials should have sufficient power to detect rare adverse events. 9/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Since almost all treatment has the potential for adverse events, when examining treatments, we often look at the NNT (number needed to treat) and NNH (number needed to harm): https://www.cebm.ox.ac.uk/resources/ebm-tools/number-needed-to-treat-nnt Traditionally, when NNT > NNH, a treatment is justifiable (excluding cost) 10/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
But to accurately assess NNH, we need to know the underlying rate of adverse events with a treatment. In order to do so, the initial treatment trial must have "adequate power": they must have a sufficient number of patients in the trial to detect rare AEs. 11/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
If we want 95% certainty that we've detect at least *ONE* AE, required sample depends on the event rate. From Tweet 7: With AE with rate 0.00011 => need 30,000 patients With AE rate of 0.000017 => need 180,000 patients (calculate or use table: https://www.statstodo.com/SSizRareEvent_Exp.php) 12/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Using the observed AE rates, potentially how underpowered was the 12yo-15yo Pfizer trial to detect just *ONE* AE? AE rate of 0.00011 => 30,000/1133 = ~26 fold too small AE rate of 0.000017 => 180,000/1133 = ~159 fold too small 13/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Now, we are seeing emerging discussions about AEs from the mRNA vaccines in younger populations: https://cdc.gov/vaccines/acip/work-groups-vast/technical-report-2021-05-17.html https://www.nytimes.com/2021/05/22/health/cdc-heart-teens-vaccination.html Fortunately, myocarditis tends to have a benign course in most. In my download, the 4 reported cases appeared to do well. 14/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
But I am deeply concerned about how we went about the decision making for low risk Pediatric populations when the NNH > NNT. Even more than adults, there are clear risk factors that put a child at greater risk of severe COVID-19. Why not tailor guidance to at risk groups? 15/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
While there are always one-off exceptions, we know obesity plays a larger role for severe disease in younger populations (kids and younger adults): https://www.jpeds.com/article/S0022-3476(20)31393-7/fulltext https://www.cdc.gov/mmwr/volumes/70/wr/mm7010e4.htm#F2_down 16/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Some will argue that the NNT (NNV in this case) "goes to zero" because unvaccinated children can transmit to susceptible adults increasing the benefit to vaccinating children by breaking that chain of transmission: both primary infection and reinfection. 17/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
There are several problems with this hypothesis: 1) One has to establish that children drive the epidemic 2) Reinfection and infection post-vaccination results in severe COVID-19 18/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Do children drive the epidemic? @nberpubs took a recent look at this: https://www.medrxiv.org/content/10.1101/2021.02.20.21252131v1.full.pdf They attributed 5% +/- 2% of transmission to school openings (ergo, young adults and kids). I have some standing concerns with this study: 19/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
But let's take the respected @nberpubs's estimate 5% (+/- 2%) as given. It's also biologically plausible: https://www.pnas.org/content/118/8/e2021830118 We can now construct a simple quantitative thought exercise if NNT is significantly altered by Pediatric transmission concerns. 20/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
For the exercise, let's create an incredibly basic transmission model where either kids (K) or adults (A) are transmitting. Furthermore, we assume that K->A is the same as A->K. Both assumptions bias towards vaccinating the young to decrease transmission to at risk adults. 21/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
Referring to the attached, using a binomial expansion for the approximation and using the standard errors provided in the NBER paper, you can see that within 2 years, kids drive <1% of all transmission. Within 3 years, it's under 0.1%. Kids do/will not drive this pandemic. 22/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
As for the dangers of infection after vaccination or primary infection, we have abundant data that is reassuring in this regard. https://www.medrxiv.org/content/10.1101/2021.04.20.21255670v1.full.pdf Your vaccine/infection protects you. Rising vaccination will amplify natural processes in play (see images) 23/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
But we keep seeing "experts" like @DrLeanaWen pushing an innumerate narrative. Maybe she spends too much time with media to examine the data or have someone help her understand it. She has been repeatedly wrong and can't correct her ways. 24/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
I am not some "contrarian voice" in the hinterlands. We have a horribly dysfunctional policy conversation in this country driven by politicization and an incurious and innumerate media. Speak to your Pediatrician and do what makes you feel safe. https://t.co/Wx3p5cwdbI 25/n
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
@sdbaral @davidzweig @VPrasadMDMPH @ProfEmilyOster @WesPegden @TracyBethHoeg @MonicaGandhi9 @covidtweets @Hold2LLC @Humble_Analysis @interpolated @ebennett74 I look forward to questions and feedback
@contrarian4data - Newsom Myālgía MD, PhD (formerly Virál)
And how could I forget @districtai !