PANDA’s Open Letter to Professor Pulliam – as SACEMA distances itself from the models used to justify lockdown

Press Release: PANDA’s Open Letter to Professor Pulliam – as SACEMA distances itself from the models used to justify lockdown 

 

Release: Immediate

Prof. Juliet Pulliam

SACEMA

Dear Professor Pulliam,

We refer to your letter of 5 June 2020 in reply to our letter of 1 June 2020.

At the outset, we note that you have not responded to any of the observations that we made regarding the parameters used in your models and that you refuse to respond thereto.

Tucking the models away in obscure parts of the Internet, does not, in our view, constitute making the models “publicly available”. No links to the models appear on SACEMA’s website or in any public documents that we are aware of.

Given the lack of public information about your models and others relied on by the State, it is no surprise that we appear to have “conflated” your models with the “National COVID Epi Model”. You seem in your letter to be refusing to provide us with details of the National COVID Epi Model on the basis that SACEMA did not develop it alone but is part of a “consortium” that developed it. In law, a “consortium” describes separate legal entities working together on a project. Any information that a member of the consortium has in relation to the project ordinarily belongs to that member. As such, it is our reading of the Promotion of Access to Information Act (“PAIA“) that any member of the consortium can be approached to provide information about the “Epi model” and SACEMA should therefore treat our PAIA request as a request for any information that SACEMA holds in relation to the National COVID Epi Model. We look forward to receiving such information. To be clear, we do not accept that we need to approach the NICD for this information.

You say in your letter that the earlier models that you reference in your letter are no longer in use. This is hardly the point. Given the lack of sophistication of your models and the results they produced, it is hardly surprising that SACEMA has turned its back on these models and had to be forced to endure the embarrassment of public disclosure. The fact of the matter is that the models you now so readily abandoned were in use at the time that government took a decision to implement a lockdown that has had a devastating impact on lives and livelihoods.

You also say that “to the best of our knowledge, they have not directly informed government policy.” On 19 March 2020 and subsequently, it was widely reported in the press that “terrifying coronavirus predictions” pushed government into lockdown. Those “terrifying projections” were directly attributed to SACEMA.[1] SACEMA has never denied the reports that the lockdown decision was based on SACEMA’s estimate of up to 351,000 deaths (at a 40% infection rate). All of the information summarised in the graphic that was printed in News24 on 19 March 2020 can now be verified using the models that you referred us to.

A cursory glance at the Internet reveals that the SACEMA model was widely described as the trigger for Lockdown, the above being just one example of many. We fail to find any refutation of the model by SACEMA on any public platform. This is extraordinary given your current stance in relation to this model.

If, as you say, the tools that you developed were “tools to improve situational awareness”, what did you do when you discovered that government had relied on them to take the decision to lock down the country, thereby removing hard won freedoms of South Africans and causing enormous societal damage? Are you perhaps suggesting that government misused your data and if so, what did you do to bring this injustice to the attention of the public and the authorities?

You say that these models were “created with information available at the time of their creation” but this is demonstrably untrue. SACEMA was selective in choosing which information to use. For your mortality input you relied on two studies utilising data emanating from China, a country that is not known for open and frank disclosure of data at the best of times and that had already been criticised for manipulating data relating to coronavirus for political purposes. The first of those studies, which you refer to as “Riou”, in reference to one of its authors, was published on 30 January 2020. The second which you refer to as “Russell”, after one of its co-authors, was published on 19 March 2020.

The more recent of the two studies you reference, the “Russell” study, consistently produces lower numbers in your model.  Whereas the newer “Russell” data returned a figure of 20,300 deaths at a 10% infection rate and 81,300 at a 40% infection rate, the press reports suggest that you only presented the higher Riou numbers to government – numbers that were 4 times higher than the Russell numbers your model was generating.

What is truly remarkable about the data sources you chose is that SACEMA ignored the best data that existed at the time. On 8 March 2020, prior to the Russel study, a study[2] was published based on information that emanated from what has been described as a coronavirus “petri dish” – the Diamond Princess cruise ship. The Diamond Princess offered a unique and precious opportunity to jumpstart our understanding of the dynamics of the epidemic. Without it, it would be many months before those dynamics could be teased out of emerging population-level data. The study laid out what had happened on the ship – who had been infected, who had died and at what ages and as such was the most valuable data point the world had in early March 2020.[3]

SACEMA not only failed to reference this work in its models, but failed to take into account the findings that emerged from the “coronavirus petri dish”. For example, in a closed system like the cruise ship, 80% of those infected presented asymptomatically. South Africa not being a cruise ship, it would have been evident that the real-life situation would never be as dire as on the ship. Consequently, in the first week of March 2020, it was already known that no more than 20% of the population waslikely to present symptomatic outcomes.  This data would further have adjusted your hospitalisation rates had it been acknowledged. And yet, despite the fact that this was known to be unrealistic, the SACEMA figures that grabbed government’s attention came from the presumptions that 100% of the population was susceptible and that up to 40% of the population could be infected.

The Diamond Princess study also showed that there were massive differences in case fatality ratios based on age. On board the ship, there were no fatalities in the population under 69. This finding was also being reflected in the data coming out of European countries at the time your model was presented – older populations were much more susceptible than young populations. And yet the SACEMA models appear to take no account of age, susceptibility despite age differentials appearing in your data-set, assuming that all ages are equally susceptible. This is extraordinary.

The disclaimer SACEMA presents on their website is telling, we ask quite simply, if you tacitly acknowledged the inaccuracy of the models, why were you not more strident in making the Public and the Government aware of your reservations in this regard. In turning your back on your models, you offer no explanation for why they were so wrong. SACEMA seems to treat this as some kind of academic hypothetical where errors have no consequence and where under-estimating fatalities is the only error that must be avoided. Nearly 80 days into a lockdown that was justified using the models you no longer support; you now claim to be part of a team working on another model that is in progress. A glance at the Ministry of Health slide decks indicates quite clearly that your consortium is still relying on Chinese data emanating in March 2020.

There are no references to current worldwide data and datasets, freely available, nor to the deluge of scientific papers that have been published since March. A layman (which we clearly claim to be) is easily able to refute the predictions in even the most recent of the “National COVID Epi Model”.  Quite frankly, we find it staggering, given the course of events to date, that SACEMA is still involved in modelling exercises that government might rely on. We find that almost as staggering as the news that the replacement government model is still “under development”.

Thank you for giving us access to your original model and the scripts used in your predictions. They will indeed prove valuable when the outcomes of this event are debated in a wider platform in time to come.

Yours sincerely

Nick Hudson

Pandemics ~ Data & Analytics

Panda

ENDS.


[1] https://www.news24.com/news24/southafrica/news/exclusive-the-terrifying-coronavirus-projections-that-pushed-government-into-lockdown-action-20200319

[2] https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.10.2000180

[3] See our article on the importance of this study at https://www.biznews.com/inside-covid-19/2020/05/21/government-covid-19-data-panda.

_______________________________________

Issued on behalf of PANDA by Stratagem Consultants.

For media enquiries, contact:

Jessica Shelver – 076 175 0663 – [email protected]

Colin Wardle – 073 326 0834 – colin@stratagemconsultants.co.za

About Pandemics ~ Data  & Analysis (PANDA): 

Pandemics ~ Data & Analysis (PANDA) is a multidisciplinary initiative seeking to inform policy. Panda’s technical team brings to bear knowledge from the fields of actuarial mathematics, economics and medicine and is continually recruiting. Membership is voluntary and independent of any institutions or political parties.

We have sought to make our models “as simple as possible, but no more so”, rejecting refinements that do not affect the ultimate answer. We aim to disclose everything that a skilled reader might require to understand and reproduce our results.

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Publisher’s note: The opinions and findings expressed in articles, reports and interviews on this website are not necessarily the opinions of PANDA, its directors or associates.

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