Fassen Sie diesen Blogbeitrag wie folgt zusammen:
Während das Coronavirus mehr als 159 Länder erreicht hat, die weltweiten Fälle 174.379.088 übersteigen und die Zahl der Todesopfer 37 Lakhs (Stand: 7. Juni 2021) übersteigt, tut die ganze Welt ihr Bestes, um das Virus einzudämmen.
„Die Weltgesundheitsorganisation hat den Coronavirus-Ausbruch zu einer globalen Notlage erklärt. Hier erfahren Sie, wie Öffentlichkeit und Regierungen mithilfe von Analysetools die Ausbreitung des Virus verfolgen.“
Die Weltgesundheitsorganisation (WHO) und die US-amerikanischen Zentren für Krankheitskontrolle und -prävention (CDC) verfolgen den Ausbruch einer Krankheit, die sich zu einer weltweiten Epidemie ausweiten könnte. Sie begann in China, hat sich aber mittlerweile in viele Länder der Welt verbreitet. Die WHO erklärte den Coronavirus-Ausbruch am 30. Januar 2020 zu einer globalen Gesundheitsnotlage.
Heute erleben wir einen wichtigen Anwendungsfall für Analysen, der es in die Schlagzeilen schafft. Es ist einer jener Fälle, in denen Leben von Technologie abhängen.
1. Visualization of Global Cases
The Johns Hopkins University’s Center for Systems Science and Engineering has built a real-time visualization dashboard of the outbreak that includes – listings of total numbers of cases, maps, deaths, active patients, closed, and recovered cases.
The statistics are further broken down by countries and cases represented on the map by the size of the dot. The quoted sources include – CDC, WHO, and more. The university is using Esri’s ArcGIS (Geographic information system) for the visualization, which is published through the web. The dashboard is a beneficial way for the general public and doctors to track the status of the outbreak. And from this, people can also know how the CDC and other government agencies are analyzing the data.
According to, Theresa Do, professor of epidemiology and biostatistics at George Washington University and SAS analytics manager for infectious diseases epidemiology and biostatistics, says data, analytics, AI and other technology have a significant role to play in helping to understand, identify, and assist in predicting disease spread and progression. She knows how organizations use the data and analytics to make the right decisions.
2. Live-updates of Bed availability
We have seen that the Mumbai model of handling the crisis has been applauded by everyone. One of the key areas of such information relay is the dashboarding of the information like the availability of beds in a real-time basis such that doctors, physicians as well the government authorities can take relevant actions without delay. As such we can see how analytics is not only helping to analyze the past data but also the present data to ensure free flow of information.
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3. GeoSpatial Analytics
Analytics has been helping doctors in identifying the hot-spots with the help of geographical data. For example – The suspected new cases would be tackled by physicians and then sent to the CDC for confirmation. AI and ML technologies will also help doctors and government agencies to track down the confirmed cases and come out with the information like – where they’ve traveled and who they came in contact with, to predict the spread. So, analytics that include Artificial Intelligence and Machine Learning can help organizations in this outbreak to learn from past events to create new knowledge swiftly from millions of data points.
Likewise, organizations can also go for syndromic surveillance which helps to track down the size, spread, and tempo of outbreaks, to monitor disease trends, and to provide reassurance that an outbreak has not occurred. Social media is often used as a sentinel source in this outbreak. In the future, technologies like smartwatches may play a crucial role, as data can track sleep and heart rates to provide early indications that a person is not doing well.
4. API Usage
Social media is often used as a sentinel source in this outbreak. In the recent past we have seen new websites showing the data of twitter for bed availability. Such ease of information is made possible by the use of API. Even websites that show availability of vaccines now, think of notification by 3rd party apps regarding availability of vaccines with CoWin.
5. Predictive analytics
Predictive analytics can also be applied to data from – airports, hospitals, and other public places to predict disease spread and risk. Hospitals can use the data to plan for the impact of an outbreak in their operations.
In the future, technologies like smartwatches may play a crucial role, as data can track sleep and heart rates to provide early indications that a person is not doing well.
Die wichtigste Lehre für die IT aus dem Ausbruch ist, dass Datenanalysen im Kampf gegen Covid-19 eine entscheidende Rolle spielen und sich zu einer Grundlage für alle Arten von Organisationen und Abläufen entwickelt haben. Zwar werden Analysen und maschinelles Lernen nicht direkt in Arztpraxen eingesetzt, um Proben für Tests zu entnehmen, doch tragen diese Technologien dazu bei, die Gesamtbemühungen zu unterstützen und Ärzte sowie Gesundheitseinrichtungen effizienter und besser für die Bekämpfung der Ausbreitung eines virusähnlichen Coronavirus auszurüsten.