Amazon Web Services has made available in open source form a new simulator and a series of tools machine learning that allow to study and try to predict the spread of the COVID pandemic infections – 19 . It is a set of tools and data that can help shed light on the complexities of this virus, offering a spread simulator and various models to test the impact of various intervention strategies.

Although today we know something more about COVD – 19 compared to the pandemic, the construction of a correct epidemiological model is still an arduous task. This is because it is necessary first to identify the variables that can influence the spread of the disease at the city level, then at the country level and finally at the population level. An effective intervention model must then be able to modify strategies (closures, quarantines) by exploring the trends of diseases that have shown trends similar to those of COVID – 19

Studying and preventing the spread of the COVID pandemic – 19 with AWS Machine Learning

The machine learning models made available by AWS estimate the progression of disease by comparing the data with the historical results. This offers the possibility for scientists and researchers to exploit a simulator to reproduce hypothetical scenarios for different intervention approaches and to use state-level models in the US, India and European countries.

The AWS simulator is able to assign a series of probabilities to the disease variables for each individual , such as the length of time between exposure to the pathogen and the development of symptoms. It is also possible to study the dynamics at the population level, in such a way that the passage of an individual from one state to the next is conditioned by the states of the other individuals in the population. For example, an individual may go from “susceptible” to “exposed” depending on factors such as vulnerability due to pre-existing conditions or external interventions such as social distancing.

“Our open source code simulates COVID case projections – 19 a various levels of regional granularity. The output is the projection of total confirmed cases on a specific timeline for a target state or country, for a given degree of intervention. Our solution first seeks to understand the approximate time to peak and the expected case percentages of COVID cases – 19 per day for the target entity (state / country) by analyzing the incidence of the disease. Next, it selects the optimal parameters using optimization techniques on a simulation model. Finally, it generates the projections of the daily and cumulative confirmed cases, starting from the beginning of the outbreak up to a specified time period in the future “yes read on the official AWS blog.

Amazon Web Services is not alone in releasing ML models and datasets to help develop adequate intervention measures to contain the spread of the pandemic: Google has made public its in March, while Facebook released them a few days ago.