• Statistical Society of Australia webinar on COVID-19 by by Nicholas Fisher and Dennis Trewin “Learning about the knowns and unknowns: The essential role of statisticians” is on the SSAI Youtube channel: https://youtu.be/naQZlpuWdbE

About this webinar:

Understanding and controlling the spread of COVID-19 is critically dependent on the availability of high-quality data to inform modelling and forecasting, and to monitor the efficacy of government actions.  However, the currently available data are largely observational or, if planned, focused on very specific groups in the population.  It is appropriate to ask:  What about the data we need to inform decision-making but haven’t got – the known unknowns?  There are several categories:  people who haven’t had the virus, those who have the virus but are asymptomatic, those who have symptoms but have not been tested, those who are actually ill, those who have had the virus and recovered, and potentially those who have recovered and then lapsed.

Fortunately, there is a long-established and cost-effective statistical approach to acquiring reliable data for such purposes, and it is relatively straightforward to implement.  It involves selecting people – men, women, and children – at random and testing them to identify which categories they fall into.  Professional statisticians need to be involved at the highest level of decision-making in relation to how a suitable program is designed and deployed.  There is a real opportunity for the statistical profession to give a prominent demonstration of the important contribution it makes to national affairs.

The Government needs to act on this now.  The welfare of all Australians is at stake.  Every day’s delay in implementing this program will be costly.

 

About the presenters

Nicholas Fisher PhD DSc

After three decades as a research statistician in CSIRO, Nick left his position as Chief Research Scientist in 2001 to found ValueMetrics Australia, an R&D consultancy that carries out R&D in Performance Measurement, in which area he has consulted to a  wide variety of business, industry and Government clients in Australia and overseas. He is also originator and leader of the International Data Science in Schools Project (www.idssp.org). He holds an honorary position as Visiting Professor of Statistics at the University of Sydney, and is professionally accredited by the Statistical Society of Australia and by the American Statistical Association.

Dennis Trewin AO FASSA

Mr Trewin was trained as a Statistician but has had 40 years of executive management experience in official statistics in Australia and New Zealand. He was the 2000 – 2007 Australian Statistician. He has also been an Electoral Commissioner and an Associate Commissioner at the Productivity Commission. He has chaired and been a member of Boards/Councils in the superannuation and university sectors. He is the current Chair of the Australian Mathematics Trust. He has also chaired several NGO Boards associated with international statistical activities.  He is professionally accredited by the Statistical Society of Australia.

 

  • COVID-19 Modelling reports

https://www.health.govt.nz/publication/covid-19-modelling-reports

 

  • CWML Announces Public Collection of COVID-19 Citations

https://library.medicine.yale.edu/blog/cwml-announces-public-collection-covid-19-citations?fbclid=IwAR2bbkWTGGQpWjcQs0YV1Jr0BlvF4GjgzCmBS2EHZKzWFpoBXP-iXsTUcjA

 

  • Pandemics History and Prevention

https://nutritionfacts.org/video/pandemics-history-prevention/

 

  • The maths and ethics of minimising COVID-19 deaths in NZ – Prof Tony Blakely, Prof Michael Baker, and Prof Nick Wilson

https://sciblogs.co.nz/public-health-expert/2020/03/23/the-maths-and-ethics-of-minimising-covid-19-deaths-in-nz/

 

The numbers get updated regularly, and one can sort the rows in the By Countries table by “per million of popn”, etc, etc.

 

  • Sean Hendy on Checkpoint Thursday 26 March 2020

https://www.rnz.co.nz/national/programmes/checkpoint/audio/2018740325/covid-19-four-week-lockdown-buys-nz-time-is-it-enough

 

  • Sean Hendy’s spinoff “Covid-19: The maths that explains why we’re locking down”

https://thespinoff.co.nz/science/26-03-2020/covid-19-the-maths-that-explains-why-were-locking-down/

“there is a detailed summary of our work here and further details available on our website

 

 

Covid19ita – Italy:

Covid19ita is developed by the Unit of Biostatistics, Epidemiology, and Public Health of the Department of Cardiac, Thoracic and Vascular Sciences and Public Health at Università degli Studi di Padova , in partnership with the Department of Clinical and Biological Sciences at Università degli Studi di Torino , and the Department of Translational Medicine at Università del Piemonte Orientale.

 

 

From International Statistical Institute:  https://isi-web.org/index.php/covid-19

COVID-19

This page contains some current resources for statisticians interested in the COVID-19 pandemic.

We give links to some data sources, talks and preprints.

The ISI Committee on the Public Voice of Statistics has prepared this page, but neither the Committee nor the ISI have evaluated or are endorsing the analyses.

 

GENERAL INFORMATION:

 

DATA:

  • World Health Organization daily updates. These are the official counts from each country reporting, starting at January 21, 2020.
  • Johns Hopkins University outbreak map and data.

 

MODELS:

  • Tom Britton explains the susceptible-infected-removed (SIR) epidemic model and how social distancing can affect the epidemic curve (36 minutes).

 

  • talk by Xihong Lin, Harvard Biostat, presenting lessons learned from Wuhan about limiting the spread of COVID-19. The main model is a latent SIR model, taking into account that we do not observe the actual cases but only the identified ones (56 minutes; talk starts at 1:10). The preprint is also available.

 

  • preprint by Agosto and Giudici on a Poisson autoregressive model on COVID-19 contagion dynamics, applied to data from China, South Korea and Italy.

 

  • preprint by Riou et al. an age-adjusted fatality of COVID-19 in China Jan-Feb 2020, taking into account under-reporting. Data and Stan code are available.