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Category Archives: SARS-CoV-2
“Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions”
J. Dehning et al., Science 369, eabb9789 (2020). DOI: 10.1126/science.abb9789 Source code and data. Note: This is not a classical approach to assessing strength of interventions using either counterfactuals or other kinds of causal inference. Accordingly, the argument for the … Continue reading
Posted in American Association for the Advancement of Science, American Statistical Association, Bayesian, Bayesian computational methods, causal inference, causation, changepoint detection, coronavirus, counterfactuals, COVID-19, epidemiology, SARS-CoV-2, state-space models, statistical series, time series
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COVID-19 statistics, a caveat : Sources of data matter
There are a number of sources of COVID-19-related demographics, cases, deaths, numbers testing positive, numbers recovered, and numbers testing negative available. Many of these are not consistent with one another. One could hope at least rates would be consistent, but … Continue reading
First substantial mechanism for long term immunity from SARS-CoV-2 : T-cells
M. Leslie, “T cells found in COVID-19 patients ‘bode well’ for long-term immunity“, Science, doi:10.1126/science.abc8120. A. Grifoni, et al, “Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals“, Cell, 14th May 2020. J. … Continue reading
Dissection of the Dr Judy Mikovits’ claims in AAAS Science
https://www.sciencemag.org/news/2020/05/fact-checking-judy-mikovits-controversial-virologist-attacking-anthony-fauci-viral h/t Dr Katharine Hayhoe @LinkedIn The Chronic Fatigue Syndrome retraction notice. Excerpt: Science asked Mikovits for an interview for this article. She responded by sending an empty email with, as attachments, a copy of her new book and a … Continue reading
“Seasonality of COVID-19, Other Coronaviruses, and Influenza” (from Radford Neal’s blog)
Thorough review with documentation and technical criticism of claims of COVID-19 seasonality or its lack. Whichever way this comes down, the links are well worth the visit! Will the incidence of COVID-19 decrease in the summer? There is reason to … Continue reading
Phase plane plots of COVID-19 deaths
There are many ways of presenting analytical summaries of new series data for which the underlying mechanisms are incompletely understood. With respect to series describing the COVID-19 pandemic, Tamino has used piecewise linear models. I have mentioned how I prefered … Continue reading
Machiavelli
It’s right out of Machiavelli’s The Prince. #covid_19 #coronavirus Even for the Trump administration, it is odd they are pushing #Hydroxychloroquine and #Azithromycin so hard, against medical advice and evidence. I’ve thought about this and, given the growing animosity between … Continue reading
New COVID-19 incidence in the United States as AR(1) processes
There are several sources of information regarding Covid-19 incidence now available. This post uses data from a single source: the COVID Tracking Project. In particular I restrict attention to cumulative daily case counts for the United States, the UK, and … Continue reading
Posted in coronavirus, COVID-19, epidemiology, pandemic, regression, SARS-CoV-2
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