🦠 COVID-19 | Follow or find the science?

I am a scientist by education, banker at JPMorgan for a few years, then mature PhD student in Chemical Biology at Oxford under the supervision of Christofer Schofield (FRS) and Peter Ratcliffe (Nobel laureate in medicine in 2019). Founder and tech investor focusing on media and education. I care about science, learning and Democracy which are good bedfellows.

📊 Daily Data Brief: 

3,212,850 (+84,462cumulative cases 

Active cases: 1,987,063 (+26,570 (this is the number of currently infected patients)

Total Deaths:  227,780  (+10,763)

Serious/Critical Cases: 59,960 (+3,418)

Recovered:   998,007 (+37,129)

Source: Worldometers

Death curves (updated daily as ECDC releases). Major update with per country graphs now available (Link) (USUKFranceGermanySweden) (👈NEW❗️)

A hopeful day, as drug discovery and vaccine research both seem on an accelerating path to strengthen our toolbox to contain this pandemic. Some positive news about Gilead’s remdesivir and Pfizer’s accelerated timetable for its vaccine candidate. On this front, hope welcomes and follows these scientific breakthrough.

On the other hand and as superbly narrated by Ed Yong in his long read of the day, uncertainty and knowledge gaps drive pre-print as well as political opportunism. Re-opening and school opening policy trends, are seriously challenged by two important papers. More precisely, politicians who appear more eager to bow to public pressure and find the science that fits their narrative, rather than follow the science to communicate to their public, are challenged by a joint statement from the presidents four leading scientific institutions in Germany as well as a pre-print on viral load comparisons amongst age groups from Christian Drosten’s lab.

It will be interesting to see whether politicians and their public heed the warning. Whether they decide to follow the science or find the ‘science’ will determine the course of this pandemic and its severity.

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The Long Read: Ed Yong writes “Why the Coronavirus Is So Confusing” for the Atlantic. (Link)

Every time Yong writes an article, it is very likely to make it as a long read of the day. This one is no exception. It mainly focuses on the protagonists in this pandemic starting with the virus, going through the academics, the data and the communication between public, experts and policy makers. The article is split in the following eight sections:

I. The Virus
II. The Disease
III. The Research
IV. The Experts
V. The Messaging
VI. The Information
VII. The Numbers
VIII. The Narrative

Yong aims to show how the radical uncertainty brought by the pandemic, the urge to close the scientific gaps in an open sphere (mainly Twitter), creates a myriad of confusing narratives which get politicised and twisted.

All of the protagonists end up transformed during a pandemic including the society they are part of. A dizzying article conveying the sheer amount of information (and disinformation) and uncertainty which everyone grapples with during their respective lockdown.

Video of the day: Scott Gottlieb’s (former Food and Drug Administration Commissioner) take on positive preliminary analysis release on Gilead remdesivir and drug discovery ore generally.

🦠 Terry C. Jones​ et al. published a pre-print: “An analysis of SARS-CoV-2 viral load by patient age”. This is a publication from Christian Drosten’s lab whose portrait article was published in the Corona Daily yesterday.

Even though, as Kai Kupferschmidt points out “same viral load doesn’t mean same role in spreading disease” in the tweet below,

he does agree that things did not get easier with this publication. The authors rightly warn about school re-opening in light of this findings in the opening summary of their paper.

"Based on these results, we have to caution against an unlimited re-opening of schools and kindergartens in the present situation. Children may be as infectious as adults"

It would be great to hear leaders in Denmark who have already re-opened schools, and leaders in France planning re-open them on May 11, to see how a scientific paper affects their decision or thinking. (Link)

💊 Hannah Kuchler and Donato Paolo Mancini write “Fauci praises remdesivir after data show it speeds recovery” in the Financial Times. The comments by Anthony Fauci reported in the article followed the announcement by the US National Institute for Allergy and Infectious Diseases of the positive result of the drug study:

Most experts agreed on what the study results means from Carlos del Rio (Executive Associate Dean for Emory at Grady and co-Director of the Emory Center for AIDS Research (CFAR)),

to Kai Kupferschmidt’s “cautiously hopeful” but “not a miracle cure”:

The sense was that it was a first positive result, and that there will be many more which will increasingly strengthen the toolbox at doctors’ disposal to treat patients. (Link)

💉 Jared S. Hopkins and Jonathan D. Rockoff write “Race for Coronavirus Vaccine Accelerates as Pfizer Says U.S. Testing to Begin Next Week”. Pfizer’s announcement comes on the heels of the Oxford Group led by Adrian Hill announcing that they are on track to get a few million doses by September if all goes well, and following equally optimistic timetables from Moderna Therapeutics and Johnson&Johnson’s efforts. The race between these groups has always been on in the lab. It is now also on in the press. (Link)

🇩🇪 The presidents of four large science institutions in Germany (Max Planck Society, Fraunhofer Presse, Helmholtz-Gemeinschaft, and Leibniz-Gemeinschaf) have published a paper (in German) titled “Strategies to contain the COVID-19 pandemic” (via Google translate). In their opening joint statement they write:

The situation is not stable, even a small increase in the number of reproductions would lead us back to a phase of exponential growth. The number of reproductions must therefore be kept below 1 until a vaccine is available. The new R-value close to 1 reported by the RKI on April 28, 2020 shows that consistent contact restrictions are still required in this phase.” (via Google Translate; my emphasis)

Interestingly, in their opening summary they also comment on the timeline for achieving herd immunity without a vaccine and its consequence:

“According to the data available to date, achieving “herd immunity” would require a period of a few years if the health system is not to be overloaded. Such a strategy would have to maintain restrictive measures over the entire period.”

In taking this public step, the four presidents echo and strengthen the views of Christian Drosten which we reported in yesterday’s Corona Daily: to be cautious about re-opening and not jeopardise Germany’s great achievements thus far.

Kai Kupferschmidt has written an excellent thread about his interpretation of this joint-statement and paper. It will be interesting to see over the coming days whether it shifts the debate in Germany or at the very least modify the behaviours of citizens. The scientists are increasingly worried about the political decisions taken at the Lander levels regarding reopening. (Twitter thread)

🦠  Jayson S. Jia et al. published “Population flow drives spatio-temporal distribution of COVID-19 in China” in Nature. The authors have used mobile phone data in China to model the spread of COVID19 in the country and built a model to assess “community transmission risk over time for different locations”. There will be huge policy interest in such analysis as the authors point out at the end of the abstract:

“This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan allocation of limited resources ahead of ongoing outbreaks.”

Nicholas A Christakis (Sterling Professor of Social & Natural Science at Yale) also wrote a detailed thread on the finding and significance of his lab paper, incidentally commenting on the possible obfuscation of COVID19 data in China. In the thread he cites a paper from Neil Ferguson from 2006 in Nature looking at the effectiveness of travel restrictions in containing an influenza outbreak at a late stage of the epidemic:

NA Christakis also makes sure that even thought the authors used data provided by telecommunications operators, it had respected the privacy of the phone users:

It is a timely made point, as epidemiologists in Europe are advising (or maybe just informing) governments on the data they would like to retrieve from contact-tracing apps, in order to help devise better policies to contain the epidemic. (Paper and Twitter thread)

🎬 Another happy animal video: (Link)

📊 A picture is worth a thousand words:  Global (🌎) and local (with relevant flag) visualisation and forecasting tool

  1. 🌎 The Financial Times (NEW❗️visualisation) has a data tracking page which is in front of the paywall, looking at cases and fatality curves for selective countries and metropolitan areas/region. It is not as extensive as the Madlag link below, where you can see static as well as animated images for a greater number of individual countries. (Link)

  2. 🇺🇸  The John Hopkins University resource center was the first one I used back in January they have now made available in their latest iteration a county by county dashboard in the US including information about health capacity, insurance coverage, ethnicity and age breakdown of the population (New York example below) (Link)

  1. 💊 The "Map of Hope" provides a geographical overview of planned, ongoing and completed clinical trials. It is put together with data from WHO Clinical Trials Search Portal by the Heidelberg Institute for Geoinformation technology. (Link)

  2. 🌍 MRC Centre for Global Infectious Disease Analysis started to publish weekly death estimates for countries (Link)

  3. 🇺🇸 The US Center for Disease Control and Surveillance (CDC) publishes “A Weekly Surveillance Summary of U.S. COVID-19 Activity” (Link)

  4. Google has published a new website to “See how your community is moving around differently due to COVID-19”. They have a lot of data to do so… (Link)

  5. 🇺🇸Another valuable resource by Unacast ( a data company providing human mobility insights). Their “Social distancing scoreboard looks and compares (State by State and County by County), the change in mobility to prior to COVID19 (Link)

  6. 🌎 Country by Country Curves: This is a GitHub made by my friend Francois Lagunas. He has written a script to scrape deaths and number of cases in order to visualise the rate of growth on a logarithmic scale.  Great resource (Link)

  7. CityMapper has started to produce City Mobility Index to show how much a City is moving. This is a very good indicator of how well lockdowns are respected around the world: Barcelona (4% of city moving) at one end and St Petersburg at the other end (68% of city moving) for yesterday (Link)

  8. 🌎A great resource put together by Ben Kuhn and Yuri Vishnevsky.  At a time when we need solidarity and cooperation, I prefer their subtitle “We need stronger measures, much faster” than their title. It’s a simulator on what case growth looks like depending on your community’s measures. Fantastic resource to stir communities and governments to action (Link)

  9. 🇩🇪 The COVID19 dashboard for Germany is one of the best around. (Link)

  10. 🌎A helpful guide by VOX of the “9 coronavirus pandemic charts everyone should see” (Link)

  11. 🌎Data and chart regularly updated by the  Centre for the Mathematical Modelling of Infectious Diseases at the London School of Hygiene & Tropical Medicine. It maps the effective reproduction number (also known as R0) of COVID19. You want to get it below 1 as fast as possible to contain an epidemic. (Link to see charts and more data about your country)

  12. 🌎This is a great COVID19 Dashboard prepared by Andrzej Leszkiewicz. Andrzej has also written an introductory and explanatory blog for it (“Coronavirus disease (COVID-19) fatality rate: WHO and media vs logic and mathematics”). I particularly like the country comparison tab, which allows you to track and benchmark the curve of the epidemic (number of cases and deaths) in your country with that of another. Very well done and informative. (Link)

  13. Going Critical” by Kevin Simler is a detailed interacting essay talking about complex systems, the importance of understanding networks, modelling and how this applies to: memes, infectious diseases, herd immunity, wildfire, neutrons and culture. Must read (Link

🏛  Notable tracking projects 

  1. 💊 “COVID-19 treatment and vaccine tracker”.  This tracker contains an aggregation of publicly-available information from validated sourcesby the Milken Institute (Link)

  2. 🏛Tariq Krim has started a COVID19 website tracking data about each government policy response to the pandemic (Link)

  3. 🏛Oxford COVID-19 Government Response Tracker (OxCGRT) was launched yesterday. Data is collected from public sources by a team of dozens of Oxford University students and staff from every part of the world. It also looks at stringency of the measures and plots stringency with case curves. A great initiative and resource (Link)

  4. 👩‍💻Mike Butcher (Editor at Large Techcrunch and founder of TechforUK), had refocused TechforUK on the fight against COVID19. It is a very effective hands-on team of volunteer. Do reach out to them. He has also teamed up with We are now working closely with the volunteers behind the “Coronavirus Tech Handbook”. (They are ‘cousins’ of ours who originally created the Electiontechhandbook). Volunteer collaboration at its best! (Link)

📰 Cronycle resource:

Cronycle has made available a number of open-access feeds on its website which I extensively use for the Corona Daily. The four first feeds are:

1.  COVID-19 General (Link

2.  COVID-19 x Resilience (Link)  

3.  COVID-19 x HCQ/CQ (Link)  (HydroxyChloroquine and Chloroquine)

4. Gig Economy x COVID-19 (Link) 5. Supply Chain x COVID-19 (Link)

5. Supply Chain x COVID-19 (Link)

  1. Human Rights x COVID-19 (Link)