COVID-19 comes from a family of viruses associated with severe acute respiratory syndrome (SARS) and the common cold. Big data and predictive analysis, in combination with artificial intelligence and a variety of thermal sensors, are powerful tools to contain the spread of this epidemic and minimize its resulting deaths.
Given that testing for the virus is sporadic at best, the numbers of cases of infection are often very uncertain, and the real danger of the virus is questioned. A decisive contribution to support epidemiological experts could come from data analysis techniques.
Data analysis plays a fundamental role, as does mathematics, which, together with physics, allows us to have an in-depth understanding of the details of nature and how things are made. As in the past years, the pioneers of data science have made an incredible impact on the world where data and analysis have been used to drive significant change in the course of a spread of the disease. One of the first historical applications of data analysis was in 1852, during a cholera outbreak in London. John Snow, one of the first data-driven epidemiologists, was able to geospatially analyze the deaths that occurred in London and thus isolate the source of the disease. Relying on his analysis, authorities were able to target their interventions to rapidly check the spread of the epidemic.
Let's evaluate the data
Running models through data analysis systems has proven to be able to approximate how trends might progress. An example is the SIR model; it is an epidemiological model that computes the theoretical number of people infected with a contagious illness in a closed population over time. The model uses coupled equations analyzing the number of susceptible people S(t), number of people infected I(t), and number of people who have recovered R(t). One of the simplest SIR models is the Kermack-McKendrick model. The Kermack-McKendrick epidemic model is considered the foundation on which many other compartmental models were based. In this regard, I found Ettore Mariotti's analysis very interesting. To read the full article, please click https://www.eetimes.com/big-data-and-artificial-intelligent-can-save-the-earth-from-covid-19/#.
Evolution of a virus [Source: graphen.ai]