COVID-19 Case-Cluster-Study

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This article was considered for deletion at Wikipedia on April 18 2020. This is a backup of Wikipedia:COVID-19_Case-Cluster-Study. All of its AfDs can be found at Wikipedia:Special:PrefixIndex/Wikipedia:Articles_for_deletion/COVID-19_Case-Cluster-Study, the first at Wikipedia:Wikipedia:Articles_for_deletion/COVID-19_Case-Cluster-Study. Purge

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Hendrik Streeck, principal investigator

The so-called COVID-19 Case-Cluster-Study – colloquially, Heinsberg study, marketed as Heinsbergprotokoll and HEINSBERG PROTOKOLL. – is an unfinished and unpublished study about the COVID-19 pandemic in Gangelt.

The study was commissioned and is co-financed by the government of Northrhine-Westfalia and is led by Hendrik Streeck. In the public sphere, the marketing agency StoryMachine advocates its results on Facebook and Twitter. Private enterprises also co-financed the study. First results of the study garnered cross-national media attention.[1]

The study aims to determine lethality of, and immunity to SARS-CoV-2; it also estimates the number of unrecorded cases.[2]

Despite the fact that sample size does not determine the representativeness of a study,[3] principle investigator Streeck claims, they examined more persons than recommonended by the World Health Organization, the study would "thus be statistically absolutely representative".[4][5]

References

  1. Sydney, Philip Oltermann Helen Davidson in; Orleans, Oliver Laughland in New; Bangkok, Rebecca Ratcliffe in; Paris, Joanna Walters in New York Kim Willsher in; Palermo, Lorenzo Tondo in (2020-04-09). "The cluster effect: how social gatherings were rocket fuel for coronavirus". The Guardian. ISSN 0261-3077. https://www.theguardian.com/world/2020/apr/09/the-cluster-effect-how-social-gatherings-were-rocket-fuel-for-coronavirus. Retrieved 2020-04-15. 
  2. Burger, Reiner (2020-03-27). "Ergebnisse ab nächster Woche: Am Beispiel von Heinsberg die Pandemie verstehen". Frankfurter Allgemeine Zeitung. ISSN 0174-4909. https://www.faz.net/1.6699780. Retrieved 2020-04-16. 
  3. Kaplan, Robert M.; Chambers, David A.; Glasgow, Russell E. (August 2014). "Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias". Clinical and Translational Science 7 (4): 342–346. Template:Citation error. ISSN 1752-8054. PMC 5439816. PMID 25043853. //www.ncbi.nlm.nih.gov/pmc/articles/PMC5439816/. 
  4. Streeck, Hendrik; Jauch, Matthias (2020-04-12). "Die Veröffentlichung zu Heinsberg war nicht leichtfertig" (Tagesspiegel). https://www.tagesspiegel.de/wissen/virologe-streeck-zur-coronavirus-studie-die-veroeffentlichung-zu-heinsberg-war-nicht-leichtfertig/25735672.html. Retrieved 2020-04-16.  original text: "also statistisch absolut repräsentativ"
  5. Schneider, Paula (2020-04-15). "Unwissenschaftlich: Statistikerin zerlegt Heinsberg-Studie, auf die sich Laschet stützt". Focus. https://www.focus.de/gesundheit/news/hoffe-dass-wir-daraus-nur-wenig-ueber-corona-lernen-statistikerin-zerlegt-heinsberg-studie-keine-transparenz-kein-wissenschaftlicher-standard_id_11881853.html. Retrieved 2020-04-18. 


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