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Nino Cartabellotta has been studying the data of the pandemic since day one and has accompanied all these months with the weekly reports from the Gimbe Foundation, which have provided a snapshot of the evolution of the infection in Italy. His voice is also joined by organizations and scientists who ask the Higher Institute of Health and the Government to make more essential information available to science on the coronavirus pandemic in Italy, because basing decisions on the Rt index is inappropriate. “
What do your analyzes say based on data from the last seven days?
Over the last week we have heard various terms – slowing down, cooling down, braking – that some have interpreted as a flattening of the contagion curve. In reality, there is only a slower speed with which the curve rises, or a reduction in the percentage increase of new daily cases: from 5% on October 30 to 2.7% on November 17. An effect certainly attributable to the measures introduced, but also to a lower capacity to perform swabs, given that the ratio of positives / cases analyzed continues to grow (from 23.9% in the week October 28 – November 3 to 28.4% in the week 11 -17 of November). The “slowdown” is manifested, to a lesser extent, in the growth rate of hospitalizations and intensive care. However, ignoring the entrances and exits of patients, even these data can be influenced by the saturation effect of the beds. In fact, the employment thresholds of 40% (medical area) and 30% (intensive care) have been exceeded with a national average of 51% and 42% respectively as of November 17 and much higher values in some Regions, where Los Hospital services are now at the end, as documented by the narratives of those who work on the front lines.
Professor Giorgio Parisi defined the Rt index as “unreliable”. The Gimbe Foundation in Parliament called it “inappropriate.” Why?
The Rt index was initially only one of the 21 monitoring indicators of the epidemic, but after the Dpcm came into force on November 3, 2020, it assumed a preponderant role, “weighing” more than 50% in the final decision on the allocation of “colors” to Regions. All this, against the limits widely reported in the international literature. in a article published in Nature Last July the researchers openly declared the fear of “having created a monster”, since “Rt does not tell us what we need to know to handle this situation. The RT processing has a delay of at least 3 weeks and is not useful as a real-time decision-making tool ”.
But, in practice, what are the real limits of the Rt index?
First, it is inappropriate for reporting quick decisions because it is estimated at infections from a couple of weeks ago; secondly, the fact that it is calculated only on symptomatic cases underestimates the real circulation of the virus because symptomatic infected today are around 1/3 of all cases; it is also based on the symptom onset date, an indicator that many Regions do not report for all cases, resulting in a further underestimation of the Rt index; finally, if the point value is correctly quoted in public communication, the lower margin of the confidence limit (the so-called “fork”) is used as a decision parameter, which represents the most optimistic view of this index. In addition, two “official” estimates of RT continue to circulate. The first is that communicated by the ISS weekly integrated surveillance report and communicated to the media: the calculation method is explicit, it is estimated in symptomatic cases at 14 days. The second is indicator 3.2. of the Ministerial Decree of April 30, 2020, used to assign the scenario according to the dpcm of November 3, 2020: the calculation method is unknown, but we know that it is estimated in the last 7 days on symptomatic cases and hospitalizations.
You have requested a review of the tracking system. How?
The system of 21 indicators is an epidemiological monitoring tool built in the phase of descent of the curve, but it is not a predictive tool to be applied in a phase of exponential growth of infections. As a result, it photographs a previous contagion situation, returning an image that is all the more blurred the faster the curve grows. Today we need a system capable of rapidly measuring the evolution of the epidemic, the overload of hospital services and, above all, indicators with a predictive function at least 1-2 weeks, to anticipate the race of the virus.
Like the Lincei, the president of the Institute of Nuclear Physics Antonio Zoccoli also requested that the data be made available to the scientific community. Agree?
I fully agree, so much so that as Fundación Gimbe we launched the campaign together with other organizations #DatiBeneComune signed so far by more than 30,000 people. In Parliament we emphasized the need to make public access to all pandemic data: from greater granularity of the data in the daily bulletin to access to the integrated national surveillance database, to the availability of all the reports from the Control Room.
Is the data provided useful to understand the evolution of the epidemic or do we need other data?
Many others are needed: from the number of infections by municipality to all the details by provinces and municipalities (subjects in home isolation, hospitalized with symptoms, intensive care, recovered, deceased, tampons, tested cases, etc.) to the flows related to the clinical evolution of positive subjects. The most striking thing is that today we know, both for hospitalized patients with symptoms and for those in intensive care, only the daily “balance” of occupied beds, but not the patients admitted and discharged. For example, +100 intensive therapies compared to yesterday only informs us that we have 100 more occupied places: but the admitted patients could be 400 because 200 have improved and have returned to ordinary hospitalization and 100 have died.
What data is needed to anticipate the movements of the virus and not chase it, since, as many have said, it is being done now?
All disaggregated data can be consulted in real time, in open format and machine readable , or in an interoperable format that allows the different databases to “communicate”. The decision to rely solely on researchers who handle data at the institutional level is highly warranted for policy, but it prevents all other researchers from identifying different interpretations of the data and proposing different strategies. A sensational own goal for the whole country.
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