As the plaintiffs’ expert medical witness in the active Southwell vs. McKee litigation, the most shocking—and depressing—revelation has been the ongoing willful, hubristic covid-19 published data ignorance of the Rhode Island Department of Health (RIDOH) “experts,” and the defendants attorneys from both RIDOH, and the Rhode Island Attorney General’s Office.
The state defendants’ attorneys chose to send interrogatories to all the plaintiffs, ostensibly as part of the state’s “discovery” process. I selected two of them, and wrote my own responses. Those evidence-based ripostes highlight the hubristic ignorance of the defendants.
Interrogatory 9. “Do you agree or disagree that in mid-August 2021, the State of Rhode Island experienced an increase in cases and hospitalizations related to COVID-19? Please provide all facts and information to support your answer.”
Yes, there was a modest increase in persons testing positive for SARS-CoV-2, as well as those hospitalized who also tested positive for SARS-CoV-2, in the latter half of August, 2021. However, RI Care New England data from an 8/25/21 conference call (1) demonstrated that total hospital discharges decreased during the covid-19 pandemic period from October 2020, through June 2021, vs. a comparable, if partial non-covid-19 nine month period from 2019-20, by -1%, and even more vs. the same 9-month periods in non-covid-19, 2018-19, by -7.6%, and non- covid-19, 2017-18, by -9.8% (2a). The 8/25/21 Care New England conference call also featured a campaign of continued encouragement to “Bring Patients Back,” and “return [hospitalization] volume to pre-covid levels,” further debunking the covid-19 pandemic-caused hospital bed over-utilization narrative (2a). Consistent data were reported by the state’s largest hospital system, Lifespan (2b). Lifespan hospital discharges averaged 62,531 for the 2018-19 pre-pandemic years, and 56,603 for the 2021 pandemic year, i.e., -9,5% lower (2b).
The August-early October, 2021 change in covid-19 hospitalizations for children, specifically, was trivial as these data reveal: corrected, conservatively, for hospitalizations among children testing SARS-CoV-2 positive, but hospitalized for non-covid reasons, the average pediatric hospital bed census for RI, 8/1/21 through 10/3/21, was well under 1 per day (1). These corrected hospitalization data likely overestimate true covid-19 hospitalizations (for both children, and adults), based upon RIDOH’s own current methods which reveal consistently <40% (or even <30%) of those testing positive are primary covid-19 admissions (3). For example RIDOH’s own age-stratified data, obtained per APRA request (4), reveal that during the 16-week period from February 13, 2022 through June 4, 2022 there were a total of only 15 primary covid-19 pediatric hospitalizations (for ages 0 to 17 years-old), out of 39 “total covid-19 hospitalizations,” (i.e., 38.4%) as determined by Rhode Island Department of Health (RIDOH) criteria. For adults 18 years of age and older only 322/1209 “total covid-19 hospitalizations,” or 26.6%, were true covid-19 hospitalizations (4).
Interrogatory 10. “Do you agree or disagree that COVID-19 (and its variants) is/are a contagious illness spread through respiratory droplets, which contain the COVID-19 virus? Please provide all facts and information to support your answer.”
Yes, SARS-CoV-2 infection causes the contagious illness dubbed “covid-19,” but it is spread by respiratory micro-aerosols in the ~250nm particle size range, not much larger respiratory “droplets” (5,6). Lednicky et al determined that particles in the 250 nm range, i.e., micro-aerosols, alone, not droplets, carried “viable (SARS-CoV-2) virus” (5). Moreover, even during a well-controlled laboratory simulation of perfectly fitted N95 masks on mannequins, Stahl et al showed that under these optimal conditions such high quality masks were only 54% “effective” at filtering a (slightly larger) particle size of 350nm (6). Unsurprisingly, in light of these data, a seminal March, 2022 analysis in the preeminent materials journal Physics of Fluids, revealed that even the tightest ply fabric masks were a mere 2.5% to 10.0% “effective” at filtering out much larger particles of 1500nm in diameter! (7).
These laboratory-based studies of mask barrier performance are validated by 15 uniformly negative, gold-standard randomized controlled trials (RCTs) testing the real-world efficacy of masks (primarily standard medical-surgical masks, but also cloth masks, and even N95s) in both community (8,9,10,11,12,13, 13a,13b), and healthcare settings (14), since 2008.
Twelve negative RCTs of community masking for influenza prevention [influenza being a respiratory virus with a comparable ~100 to 140nm particle diameter to SARS-CoV-2, and also spread by micro-aerosols (15)], have been reported (8,9,10). Ten of these negative studies, focusing primarily on influenza, 2008 to 2016, were “meta-analyzed” [their data “pooled”], confirming the individual negative results (9). Independently confirming these pooled findings are the results from a single large randomized controlled trial of masking among a cohort of Hajj pilgrims whose enrollment [n=6338] equaled the sum enrollment of all the 10 studies in the May, 2020 “meta-analysis.” Published online in mid-October, 2020, this “cluster randomized” (i.e., by tent) controlled trial confirmed mask usage did not reduce the incidence of clinically defined, or laboratory-confirmed respiratory viral infections, primarily influenza and/or rhinovirus. Indeed, there was a suggestion masking increased laboratory-confirmed infections by 40%, although this trend was not “statistically significant” (10).
Subsequently, Danish investigators published the results during mid-November, 2020 of a randomized, controlled study conducted in 4862 persons which found that masking did not reduce SARS-CoV-2 (covid-19) infection rates to a statistically significant, or clinically relevant extent. Covid-19 infections (detected by laboratory testing or hospital diagnosis) occurred among 1.8% of those assigned masks, versus 2.1% in control participants. Moreover, a secondary analysis including only participants who reported wearing face masks “exactly as instructed,” revealed a further narrowing of this non-significant, clinically meaningless infection rate “difference” to 0.1%, i.e., 2.0% in mask wearers versus 2.1% in controls (11). A vast (n=342,000) Bangladesh randomized trial of community masking, found that cloth masks did not prevent SARS-CoV-2 infections. Odd, contradictory findings were described regarding surgical masks: they conferred a minimal, clinically irrelevant overall absolute risk reduction of 0.09%, which was somehow selectively limited only to those over 50 years old (12). However, a re-analysis of the raw data using appropriate statistical methods, found no evidence of benefit of paper masks either, in any subgroup (13,13a). Indeed, UC-Berkeley mathematician and computer scientist Professor Ben Recht’s re-examination of the Bengladesh mask trial’s own raw data, citing findings from the study that the authors didn’t include in their write-up or tables, revealed that, based on the study’s invalid method of analysis, “cloth purple masks did nothing, but the red masks ‘work.’” (13a) Moreover Chikina et al (13b) re-analyzed the raw Bengladesh mask trial data [provided by the study authors (12)] and found additional systematic, invalidating biases, noting, “Even for the serology endpoint, which may appear unbiased at first glance, subjects were only eligible for a blood draw if they had reported symptoms.” They (13b) concluded, “Thus, all endpoints are subject to behavioral biases. Our analysis of the population size shows that behavioral biases can produce a highly significant 9% difference between the control and intervention arm in the absence of any causal link with the intervention. It is thus also premature to conclude a similarly sized causal effect on any other variable that is subject to behavior bias, including the trial endpoints.”
Finally, an RCT of healthcare workers (n~2400) conducted in U.S. hospital outpatient settings demonstrated that fit-tested N95 respirator masks afforded no greater protection against laboratory-confirmed influenza than simple medical-surgical paper masks (14).
5) Lednicky JA, Lauzardo M, Alam MM, Elbadry MA, Stephenson CJ, Gibson JC, Morris JG Jr. Isolation of SARS-CoV-2 from the air in a car driven by a COVID patient with mild illness. Int J Infect Dis. 2021 Jul;108:212-216. doi: 10.1016/j.ijid.2021.04.063. Epub 2021 Apr 24. PMID: 33901650; PMCID: PMC8064821.
6) Stahl C, Frederick K, Chaudhary S, Morton CJ, Loy D, Muralidharan K, Sorooshian A and Parthasarathy S (2021) Comparison of the Filtration Efficiency of Different Face Masks Against Aerosols. Front. Med. 8:654317. doi: 10.3389/fmed.2021.654317
7) Rios de Anda I, Wilkins JW, Robinson JF, Royall CP, Sear RP. Modeling the filtration efficiency of a woven fabric: The role of multiple length scales. Phys Fluids. 2022 Mar;34(3):033301. doi: 10.1063/5.0074229. Epub 2022 Mar 1. PMID: 35342280; PMCID: PMC8939465.
8) Canini L, Andréoletti L, Ferrari P, D’Angelo R, Blanchon T, Lemaitre M, Filleul L, Ferry JP, Desmaizieres M, Smadja S, Valleron AJ, Carrat F. Surgical mask to prevent influenza transmission in households: a cluster randomized trial. PLoS One. 2010 Nov 17;5(11):e13998. doi: 10.1371/journal.pone.0013998. PMID: 21103330; PMCID: PMC2984432.
9) Xiao J, Shiu EYC, Gao H, Wong JY, Fong MW, Ryu S, Cowling BJ. Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings-Personal Protective and Environmental Measures. Emerg Infect Dis. 2020 May;26(5):967-975. doi: 10.3201/eid2605.190994. Epub 2020 May 17. PMID: 32027586; PMCID: PMC7181938.
10) Alfelali M, Haworth EA, Barasheed O, Badahdah AM, Bokhary H, Tashani M, Azeem MI, Kok J, Taylor J, Barnes EH, El Bashir H, Khandaker G, Holmes EC, Dwyer DE, Heron LG, Wilson GJ, Booy R, Rashid H; Hajj Research Team. Facemask against viral respiratory infections among Hajj pilgrims: A challenging cluster-randomized trial. PLoS One. 2020 Oct 13;15(10):e0240287. doi: 10.1371/journal.pone.0240287. PMID: 33048964; PMCID: PMC7553311.
11) Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, von Buchwald C, Todsen T, Norsk JB, Pries-Heje MM, Vissing CR, Nielsen PB, Winsløw UC, Fogh K, Hasselbalch R, Kristensen JH, Ringgaard A, Porsborg Andersen M, Goecke NB, Trebbien R, Skovgaard K, Benfield T, Ullum H, Torp-Pedersen C, Iversen K. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers : A Randomized Controlled Trial. Ann Intern Med. 2021 Mar;174(3):335-343. doi: 10.7326/M20-6817. Epub 2020 Nov 18. PMID: 33205991; PMCID: PMC7707213.
12) Abaluck J, Kwong LH, Styczynski A, Haque A, Kabir MA, Bates-Jefferys E, Crawford E, Benjamin-Chung J, Raihan S, Rahman S, Benhachmi S, Bintee NZ, Winch PJ, Hossain M, Reza HM, Jaber AA, Momen SG, Rahman A, Banti FL, Huq TS, Luby SP, Mobarak AM. Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh. Science. 2022 Jan 14;375(6577):eabi9069. doi: 10.1126/science.abi9069. Epub 2022 Jan 14. PMID: 34855513; PMCID: PMC9036942.
13) Chikina M, Pegden w, Recht B. “A note on sampling biases in the Bangladesh mask trial.” https://arxiv.org/pdf/2112.01296.pdf
13a) Recht B. Revisiting the Bengladesh mask RCT. https://www.argmin.net/2021/11/23/mask-rct-revisited/
13b) Chikina, M., Pegden, W. & Recht, B. Re-analysis on the statistical sampling biases of a mask promotion trial in Bangladesh: a statistical replication. Trials 23, 786 (2022). https://doi.org/10.1186/s13063-022-06704-z
14) Radonovich LJ Jr, Simberkoff MS, Bessesen MT, Brown AC, Cummings DAT, Gaydos CA, Los JG, Krosche AE, Gibert CL, Gorse GJ, Nyquist AC, Reich NG, Rodriguez-Barradas MC, Price CS, Perl TM; ResPECT investigators. N95 Respirators vs Medical Masks for Preventing Influenza Among Health Care Personnel: A Randomized Clinical Trial. JAMA. 2019 Sep 3;322(9):824-833. doi: 10.1001/jama.2019.11645. PMID: 31479137; PMCID: PMC6724169. https://jamanetwork.com/journals/jama/fullarticle/2749214
15) de Gabory L, Alharbi A, Kérimian M, Lafon ME. The influenza virus, SARS-CoV-2, and the airways: Clarification for the otorhinolaryngologist. Eur Ann Otorhinolaryngol Head Neck Dis. 2020 Sep;137(4):291-296. doi: 10.1016/j.anorl.2020.05.015. Epub 2020 May 31. PMID: 32507410; PMCID: PMC7261469.