Omicron spread in Hungary much faster than authorities estimated

Portfolio
Gergely Röst, mathematician and Head of COVID-19 Epidemiological Analysis and Modelling Response Team, and his team have come up with a new epidemiological calculation, which once again confirms the strong suspicion that the Omicron variant of coronavirus began to spread, became dominant and caused a surge in the number of cases long before the domestic epidemiological authorities could follow.
koronavírus omikron szupervariáns

A new entry has been added to the Facebook page of the MASZK - Hungarian Data Provider Questionnaire (national coronavirus survey). The research group led by Gergely Röst, Professor of Mathematics at the University of Szeged, has shared a mathematically estimated course of the spread of Omicron (B.1.1.529) on its Facebook page.

As they wrote: "Mathematical methods can be used to estimate the proportion of Omicron cases among new infections. To do this, one simply fits a mixed exponential model to the reported case numbers and does a bit more arithmetic to get the figure below."

This is how the Omicron variant has become the dominant strain in Hungary, based on mathematical calculations

omikron dominancia
Source: MASZK/Facebook.

The calculation shows that

the omicron variant appeared in hungary in early december 2021 and is currently responsible for nearly 100% of new infections.

An epidemiologist told Portfolio on 6 January that local authorities "have learned nothing from the previous four waves of the pandemic. The variants should be tracked to get to know the situation." The source said domestic epidemiological authorites never intended to detect Omicron or to test how quickly it would crowd out the previously dominant Delta strain.

Private laboratory Neumann Labs was the first to detect Omicron in two samples in Hungary. The National Public Health Centre (NNK) estimated that 11% of the new infections were caused by Omicron, while physicist and epidemic modeller Gábor Vattay estimated that Omicron was behind 40% of cases nationwide and 70% in Budapest. At that time, 80% of the positive tests performed at Neumann Labs were linked to Omicron.

Up until 4 January, the NNK provided no information on the share of Omicron cases.

The latest estimate by Röst and his team confirms that by then Omicron was the dominant variant in the country.

Chief Medical Officer Cecília Müller said on 13 January said NNK data did not confirm the dominance of Omicron, adding that 29% of their samples were linked to this new variant of concern.

This Tuesday (18 January), the CMO said 87% of the infections were caused by Omicron.

Get it? The share of the Omicron variant in all analysed sequences leaped to 87% from 29% between 13 January and 18 January.

Based on the surge in new cases this appears to be a not so realistic scenario to say the least. And it does not explain what had happened before 13 January. Was it a new wave caused by the Delta variant? No way. Hospitalisations, the number of ventilated Covid patients and deaths would be totally different in that case.

The explanation is simple. It's Omicron. And the NNK not being on top of its game. Again.  

for the time When the CMO talked about 29% of infections being linked to Omicron, the model conceived by Röst and his team showed a close to 100% share.

The conclusion is the same as so many times before. The NNK either has no clue about the spread of the Omicron variant (or any previous variant for that matter), or it conceals this piece of information, as it does with hospital data, such as the number of Covid patients in ICUs (no data whatsoever), Covid patients on ventilator (reporting only those that are intubated after a controversial and obfuscating mandate for hospitals to change their reporting method), the vaccination status of Covid patients in hospital, on ventilator and the deceased.

The right-hand graph helps you see how the situation in health care has been changing and when it has begun to worsen.

220121hosp03b

On these two charts the 0% line is important. When the curves are under 0% there’s a decline, when they go over 0% it’s an increase.

More importantly, when a value is north of 0% but the curve descends, it means an increase at a slowing rate, rather than a decrease. If the curve is above 0% and ascending, it is an increase at an accelerating rate. When we are under 0% and the curve goes lower, it translates into an accelerating decrease, and when it goes up it marks a decelerating decrease. As you can see, we are witnessing the latter here, and there was a turnaround in the improvement around 27-29 December. The number of active cases started to go up at an increasing rate at that time and the pace has only picked up. The changes in terms of hospitalisations and mechanical ventilation have been showing a similar start but then a different and mixed pattern. We need data for a couple of more days to see if the trend is changing for the worse or not, but an improvement would be surprising. The ascent of orange curve has already been tracked by the blue one. The yellow circle shows the days when the deterioration started.

Cover photo: Getty Images.

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