Hernán, M. A., Clayton, D., & Keiding, N. (2011). The Simpson’s paradox unraveled. International Journal of Epidemiology, 40(3), 780–785. https://doi.org/10.1093/ije/dyr041

Benjy Renton on Twitter: “For those who are wondering: There is a slight association (r = 0.34) between the percentage a county voted for Trump in 2020 and estimated hesitancy levels. As @JReinerMD mentioned, GOP state, county and local levels need to do their part to promote vaccination. Https://t.co/ZY2lUqHgLd” / Twitter. (n.d.). Retrieved April 28, 2021, from https://twitter.com/bhrenton/status/1382330404586274817

Indian expansion of Covid vaccine drive may further strain supplies | India | The Guardian. (n.d.). Retrieved April 19, 2021, from https://www.theguardian.com/world/2021/apr/19/indian-expansion-of-covid-vaccine-drive-may-further-strain-supplies

Fears frontline NHS staff are refusing to get Covid vaccine | Coronavirus | The Guardian. (n.d.). Retrieved April 19, 2021, from https://www.theguardian.com/world/2021/apr/17/fears-frontline-nhs-staff-are-refusing-to-get-covid-vaccine

ReconfigBehSci. ‘RT @kareem_carr: PSA: When You Say "there Were 6 Cases in 6.8 Million Doses Therefore We Can Expect about 1 in a Million Incidents Going Fo…’. Tweet. @SciBeh (blog), 15 April 2021. https://twitter.com/SciBeh/status/1382620714633732097.

The complement of an event \(A\) in a sample space \(S\), denoted \(A^c\), is the collection of all outcomes in \(S\) that are not elements of the set \(A\). It corresponds to negating any description in words of the event \(A\).

The complement of an event \(A\) consists of all outcomes of the experiment that do not result in event \(A\).

Complement formula:

$$P(A^c)=1-P(A)$$

Jeremy Faust MD MS (ER physician) on Twitter: “Let’s talk about the background risk of CVST (cerebral venous sinus thrombosis) versus in those who got J&J vaccine. We are going to focus in on women ages 20-50. We are going to compare the same time period and the same disease (CVST). DEEP DIVE🧵 KEY NUMBERS!” / Twitter. (n.d.). Retrieved April 15, 2021, from https://twitter.com/jeremyfaust/status/1382536833863651330

Covid: Red states vaccinating at lower rate than blue states—CNNPolitics. (n.d.). Retrieved April 12, 2021, from https://edition.cnn.com/2021/04/10/politics/vaccinations-state-analysis/

UK’s Covid vaccine programme on track despite AstraZeneca problems | Vaccines and immunisation | The Guardian. (n.d.). Retrieved April 12, 2021, from https://www.theguardian.com/society/2021/apr/11/uks-covid-vaccine-programme-on-track-despite-astrazeneca-problems

Dr Lea Merone MBChB (hons) MPH&TM MSc FAFPHM Ⓥ. ‘I’m an Introvert and Being Thrust into the Centre of This Controversy Has Been Quite Confronting. I’ve Had a Little Processing Time Right Now and I Have a Few Things to Say. I Won’t Repeat @GidMK and His Wonderful Thread but I Will Say 1 This Slander of Us Both Has Been 1/n’. Tweet. @LeaMerone (blog), 29 March 2021. https://twitter.com/LeaMerone/status/1376365651892166658.

BDI-pathogens/covid-19_instant_tracing. (n.d.). GitHub. Retrieved 13 February 2021, from https://github.com/BDI-pathogens/covid-19_instant_tracing

Undetected Covid Cases Change the True Shape of the Pandemic—Bloomberg. (n.d.). Retrieved March 1, 2021, from https://www.bloomberg.com/opinion/articles/2020-12-01/undetected-covid-cases-change-the-true-shape-of-the-pandemic

Ashish K. Jha, MD, MPH. (2020, December 12). Michigan vs. Ohio State Football today postponed due to COVID But a comparison of MI vs OH on COVID is useful Why? While vaccines are coming, we have 6-8 hard weeks ahead And the big question is—Can we do anything to save lives? Lets look at MI, OH for insights Thread [Tweet]. @ashishkjha. https://twitter.com/ashishkjha/status/1337786831065264128

Coenen, A., & Gureckis, T. (2021). The distorting effects of deciding to stop sampling information. PsyArXiv. https://doi.org/10.31234/osf.io/tbrea

Weber, Hannah Recht, Lauren. ‘As Vaccine Rollout Expands, Black Americans Still Left Behind’. Kaiser Health News (blog), 29 January 2021. https://khn.org/news/article/as-vaccine-rollout-expands-black-americans-still-left-behind/.

Freedman, D. A. (n.d.). Ecological Inference and the Ecological Fallacy. 7.

November 19: “Randomisation and control in the age of coronavirus?” (Stephen Senn). (2020, October 30). PhilStatWars. https://phil-stat-wars.com/2020/10/30/november-19-randomisation-and-control-in-the-age-of-coronavirus-stephen-senn/

ReconfigBehSci on Twitter: ‘RT @d_spiegel: Excellent new Covid RED dashboard from UCL https://t.co/wHMG8LzTUb Would be good to also know (a) how many contacts isolate…’ / Twitter. (n.d.). Retrieved 6 March 2021, from https://twitter.com/SciBeh/status/1323316018484305920

The COVID Tracking Project. (2020, November 19). Our daily update is published. States reported 1.5M tests, 164k cases, and 1,869 deaths. A record 79k people are currently hospitalized with COVID-19 in the US. Today’s death count is the highest since May 7. Https://t.co/8ps5itYiWr [Tweet]. @COVID19Tracking. https://twitter.com/COVID19Tracking/status/1329235190615474179

Stefan Simanowitz. (2020, November 14). “Sweden hoped herd immunity would curb #COVID19. Don’t do what we did” write 25 leading Swedish scientists “Sweden’s approach to COVID has led to death, grief & suffering. The only example we’re setting is how not to deal with a deadly infectious disease” https://t.co/azOg6AxSYH https://t.co/u2IqU5iwEn [Tweet]. @StefSimanowitz. https://twitter.com/StefSimanowitz/status/1327670787617198087

Sweden’s COVID death toll is unnerving due to herd immunity experiment. (n.d.). Retrieved March 4, 2021, from https://eu.usatoday.com/story/opinion/2020/07/21/coronavirus-swedish-herd-immunity-drove-up-death-toll-column/5472100002/

Armaos, K., Tapper, K., Ecker, U., Juanchich, M., Bruns, H., Gavaruzzi, T., Sah, S., Al-Rawi, A., Lewandowsky, S. (2020). Tips on countering conspiracy theories and disinformation. Available at sks.to/countertips

David Spiegelhalter. (2020, December 17). Wow, Our World in Data now showing both Sweden and Germany having a higher daily Covid death rate than the UK https://t.co/EKx7ntil6m https://t.co/YCy4a0DrqP [Tweet]. @d_spiegel. https://twitter.com/d_spiegel/status/1339493869394780160

Hyland, P., Vallières, F., Shevlin, M., Bentall, R. P., McKay, R., Hartman, T. K., McBride, O., & Murphy, J. (2021). Resistance to COVID-19 vaccination has increased in Ireland and the UK during the pandemic. PsyArXiv. https://doi.org/10.31234/osf.io/ry6n4

ReconfigBehSci on Twitter: ‘RT @PsyArXivBot: Resistance to COVID-19 vaccination has increased in Ireland and the UK during the pandemic https://t.co/AgKErDr7Yj’ / Twitter. (n.d.). Retrieved 2 March 2021, from https://twitter.com/SciBeh/status/1366707710151053312

ReconfigBehSci. (2020, October 27). RT @JASPStats: How to perform Robust Bayesian Meta-Analysis in JASP. To learn more, have a look at the tutorial video: Https://t.co/4fmkLEH… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1321387314887708672

Darren Dahly. (2019, September 4). It seems appropriate to do a thread on our recent session about the use of Twitter by statisticians. Https://t.co/eFwLDuXnOU [Tweet]. @statsepi. https://twitter.com/statsepi/status/1169313702715281408

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WABC. ‘Coronavirus: Glasses Wearers Less Likely to Get COVID, Study Says’. ABC7 New York, 24 February 2021. https://abc7ny.com/10365580/.

Witte, E. H., Stanciu, A., & Zenker, F. (2020, October 28). A simple measure for the empirical adequacy of a theoretical construct. https://doi.org/10.31234/osf.io/gdm

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Cousins, R. D. (2017). The Jeffreys–Lindley paradox and discovery criteria in high energy physics. Synthese, 194(2), 395–432. https://doi.org/10.1007/s11229-014-0525-z

Westreich, D., & Iliinsky, N. (2014). Epidemiology Visualized: The Prosecutor’s Fallacy. American Journal of Epidemiology, 179(9), 1125–1127. https://doi.org/10.1093/aje/kwu025

Mayo. (2019, August 2). S. Senn: Red herrings and the art of cause fishing: Lord’s Paradox revisited (Guest post). Error Statistics Philosophy. https://errorstatistics.com/2019/08/02/s-senn-red-herrings-and-the-art-of-cause-fishing-lords-paradox-revisited-guest-post/

Efron, B., & Morris, C. (1977). Stein’s Paradox in Statistics. Scientific American - SCI AMER, 236, 119–127. https://doi.org/10.1038/scientificamerican0577-119

Altman, D. G., & Bland, J. M. (1995). Statistics notes: Absence of evidence is not evidence of absence. BMJ, 311(7003), 485. https://doi.org/10.1136/bmj.311.7003.485

Lakens, D. (2019, November 18). The Value of Preregistration for Psychological Science: A Conceptual Analysis. https://doi.org/10.31234/osf.io/jbh4w

A fairly comprehensive list of problems and limitations that are often encountered with data as well as suggestions about who should be responsible for fixing them (from a journalistic perspective).

Here’s a graph they don’t want you to see. (2021, January 25). Sebastian Rushworth M.D. https://sebastianrushworth.com/2021/01/25/heres-a-graph-they-dont-want-you-to-see/

Statistics Guy [@Stat_O_Guy] (2020-01-26) When this is over, the 100,000 deaths wil be revised down, by tens of thousands. Twitter. Retrieved from: https://twitter.com/RejectBadSci/status/1354162277059092480

Spiegelhalter. D. (2020). David Spiegelhalter: How to be a coronavirus statistics sleuth. New Scientist. Retrieved from: https://www.newscientist.com/article/mg24732954-000-david-spiegelhalter-how-to-be-a-coronavirus-statistics-sleuth/?utm_term=Autofeed&utm_campaign=echobox&utm_medium=social&utm_source=Twitter#Echobox=1597271080

Stuaert Rtchie [@StuartJRitchie] (2020) This encapsulates the problem nicely. Sure, there’s a paper. But actually read it & what do you find? p-values mostly juuuust under .05 (a red flag) and a sample size that’s FAR less than “25m”. If you think this is in any way compelling evidence, you’ve totally been sold a pup. Twitter. Retrieved from:https://twitter.com/StuartJRitchie/status/1305963050302877697

Lakens. D. Etz.. A. J. (2020) Too True to be Bad: When Sets of Studies With Significant and Nonsignificant Findings Are Probably True. Pubmed. Retrieved from: https://pubmed.ncbi.nlm.nih.gov/29276574/

Descriptive statistics are used specifically to test hypotheses.

https://zenodo.org/record/4275864

Kunin, D. (n.d.). Seeing Theory. Retrieved October 27, 2020, from http://seeingtheory.io

David Spiegelhalter and False Positives. (2020, October 14). https://www.youtube.com/watch?v=XmiEzi54lBI&feature=youtu.be

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Dominique Heinke on Twitter. (n.d.). Twitter. Retrieved October 12, 2020, from https://twitter.com/Epi_D_Nique/status/1314753256556552192

McCrystal, J. M., Oona Goodin-Smith, Laura. (n.d.). 1 in 4 Philadelphians knows someone who has died of COVID-19, and nearly half have lost jobs or wages, Pew study says. Https://Www.Inquirer.Com. Retrieved October 9, 2020, from https://www.inquirer.com/news/coronavirus-covid-19-pandemic-philadelphia-protests-george-floyd-city-kenney-response-pew-survey-20201007.html

Take Away

Transmission of viable SARS-CoV-2 RNA can occur even from an infected but asymptomatic individual. Some people never become symptomatic. That group usually becomes non-infectious after 14 days from initial infection. For persons displaying symptoms , the SARS-CoV-2 RNA can be detected for 1 to 2 days prior to symptomatology. (1)

The Claim

Asymptomatic people who had SARS-CoV-2 contact should be tested.

The Evidence

Yes, this is a reversal of August 2020 advice. What is the importance of asymptomatic testing?

Studies show that asymptomatic individuals have infected others prior to displaying symptoms. (1)

According to the CDC’s September 10th 2020 update approximately 40% of infected Americans are asymptomatic at time of testing. Those persons are still contagious and are estimated to have already transmitted the virus to some of their close contacts. (2)

In a report appearing in the July 2020 Journal of Medical Virology, 15.6% of SARS-CoV-2 positive patients in China are asymptomatic at time of testing. (3)

Asymptomatic infection also varies by age group as older persons often have more comorbidities causing them to be susceptible to displaying symptoms earlier. A larger percentage of children remain asymptomatic but are still able to transmit the virus to their contacts. (1) (3)

Transmission modes

Droplet transmission is the primary proven mode of transmission of the SARS-CoV-2 virus, although it is believed that touching a contaminated surface then touching mucous membranes, for example, the mouth and nose can also serve to transmit the virus. (1)

It is still unclear how big or small a dose of exposure to viable viral particles is needed for transmission; more research is needed to elucidate this. (1)

Citations

(1) https://www.who.int/news- room/commentaries/detail/transmission-of-sars-cov-2- implications-for-infection-prevention-precautions

(2) https://www.cdc.gov/coronavirus/2019- ncov/hcp/planning-scenarios.html

(3) He J, Guo Y, Mao R, Zhang J. Proportion of asymptomatic coronavirus disease 2019: A systematic review and metaanalysis. J Med Virol. 2020;1– 11.https://doi.org/10.1002/jmv.26326

Take Away: The exact frequency of false positive test results for COVID-19 is unknown. Real world data on COVID-19 testing suggests that rigorous testing regimes likely produce fewer than 1 in 10,000 (<0.01%) false positives, orders of magnitude below the frequency proposed here.

The Claim: The reported numbers for new COVID-19 cases are overblown due to a false positive rate of 0.8%

The Evidence: In this opinion article, the author correctly conveys the concern that for large testing strategies, case rates could become inflated if there is (a) a high false positive rate for the test and (b) there is a very low prevalence of the virus within the population. The false positive rate proposed by the author is 0.8%, based on the "lowest value" for similar tests given by a briefing to the UK's Scientific Advisory Group for Emergencies (1).

In fact, the briefing states that, based on another analysis, among false positive rates for 43 external quality assessments, the interquartile range for false positive rate was 0.8-4.0%. The actual lowest value for false positive rate from this study was 0% (2).

An upper limit for false positive rate can also be estimated from the number of tests conducted per confirmed COVID-19 case. In countries with low infection rates that have conducted widespread testing, such as Vietnam and New Zealand, at multiple periods throughout the pandemic they have achieved over 10,000 tests per positive case (3). Even if every single positive was false, the false positive rate would be below 0.01%.

The prevalence of the virus within a population being tested can affect the positive predictive value of a test, which is the likelihood that a positive result is due to a true infection. The author here assumes the current prevalence of COVID-19 in the UK is 1 in 1,000 and the expected rate of positive results is 0.1%. Data from the University of Oxford and the Global Change Data Lab show that the current (Sept. 22, 2020) share of daily COVID-19 tests that are positive in the UK is around 1.7% (4). Therefore, based on real world data, the probability that a patient is positive for the test and does have the disease is 99.4%.

Sources: (1) https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/895843/S0519_Impact_of_false_positives_and_negatives.pdf

(2) https://www.medrxiv.org/content/10.1101/2020.04.26.20080911v3.full.pdf+html

(3) https://ourworldindata.org/coronavirus-data-explorer?yScale=log&zoomToSelection=true&country=USA~DEU~IND~ITA~AUS~VNM~FIN~NZL~GBR&region=World&testsPerCaseMetric=true&interval=smoothed&aligned=true&smoothing=7&pickerMetric=location&pickerSort=asc

(4) https://ourworldindata.org/coronavirus-data-explorer?zoomToSelection=true&country=USA~DEU~IND~ITA~AUS~VNM~FIN~NZL~GBR&region=World&positiveTestRate=true&interval=smoothed&aligned=true&smoothing=7&pickerMetric=location&pickerSort=asc

What? Why? Does he mean k-fold specifically?

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Facts v feelings: How to stop our emotions misleading us. (2020, September 10). The Guardian. http://www.theguardian.com/science/2020/sep/10/facts-v-feelings-how-to-stop-emotions-misleading-us

I'm sorry but this is kind of lazy from the author. Either write H0, \(H_0\) or H naught. H not sounds like you're saying H "not" (negation)

Susan Athey, July 22, 2020. (2020, August 2). https://www.youtube.com/watch?v=hqTOPrUxDzM

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