Besides the weather, check the current Covid situation? A new app based on the same technology as weather apps should make it possible. US scientists are currently working on a prediction technology that should effectively contain the infection process.
Check the new Covid situation in the morning – maybe together with the weather? The vision of two American scientists predicts just that. With the help of a so-called Covid-19 forecast, which is based on the same technology as that used by weather apps, it should be possible to prevent extensive lockdowns in the future.
Sounds unusual at first, but could soon become reality. Because: The scientific couple, consisting of Tapio Schneider, professor of environmental sciences at the California Institute of Technology and senior scientist at NASA’s Jet Propulsion Laboratory (JPL), and his wife Chiara Daraio, professor at the California Institute of Technology and mechanical engineer, are working on the implementation of their vision now together with an international team.
The potential of the method for how society deals with the corona virus is still being examined, but the results so far, which have been published in the journal “PLOS Computational Biology”, are already promising – this is what the medical online platform “MedScape” writes in one go Report on the new procedure.
The idea of the Covid-19 prediction was born during the lockdown itself. The scientific couple were stuck at home, along with two young children who were not going to school. “We hid at home like everyone else and talked about how lockdowns could be avoided,” says Schneider.
Even then, it was clear to the couple that lockdowns, as they have been carried out up to now, cannot help: “Even at the peak of the pandemic, only 1 to 2 percent of the population were actually contagious,” emphasizes Schneider. “98 percent, on the other hand, did not have to be isolated.” The key is therefore to find out which people are infectious at all – and therefore have to be isolated.
A prediction app is now supposed to solve the problem. It is just as effective as a lockdown, with the difference that “only a small part of the population would have to isolate itself at the same time, around 10 percent,” says Schneider. “Most people could go on with their lives normally.”
The climate scientist’s idea: To use the technology of weather apps, which is mainly based on regular analyzes using algorithms. Like the corona infection situation, the weather calculation is extremely complex and consists of an enormous amount of data that is regularly imported and can increase the accuracy of the forecast:
The weather data is based on the analysis of global observation stations that constantly record different weather data – including wind speed, temperature or amount of precipitation and humidity. In principle, an analysis is performed every twelve hours, with the current data being synchronized with the forecast from twelve hours ago and inserted into a model – an algorithm then determines what the conditions may be in the next twelve hours.
The envisioned Covid-19 app should also work according to the principle of constant data evaluation. Infection data is inserted into a disease tracking model to chart the path from exposure through infection to recovery. The files refer to:
In addition, the data from the Covid-19 tests should ideally be combined with devices for measuring body temperature – so-called body temperature sensors – in order to predict the individual risk of infection. “The important thing is that this is personal data,” says Schneider. Ultimately, this data should be sent to an app so that every user can see their personal risk directly using their smartphone.
Here’s how the app could:
The mathematical modeling described for infectious diseases was already used during the H1N1 pandemic (swine flu) and the Zika virus in order to curb the spread of the virus at the time and to better understand the connections between possible secondary diseases. Studies also show the usefulness of mathematical modelling.
As part of the previous investigations into the potential of the app, the research team created a simulation city that resembles New York in the early stages of the pandemic. The data network comprised several thousand intersecting points, each representing a person – and thus also recorded the number of interactions of each person.
The conclusion: With a high diagnostic rate, the pandemic can be fought so effectively. “We have a technology here with which we can get epidemics under control and even contain them completely if it is widespread enough and combined with tests,” predicts Schneider. However, there are also some challenges:
It is not yet clear whether and when such an app will actually be developed and implemented.
