Science Technology

Ways AI and Data is helping in our Fight with COVID-19

Businesses rushing to realign themselves to this emerging reality are searching for innovations to help proceed problems manifested in the aftermath of COVID-19. Data processing proves to be an ally for epidemiologists as they collaborate with data scientists to counter the epidemic’s scale.

The spread of COVID-19 and the public demand for knowledge have spurred the development forward in the new norm of open-source data sets and visualizations, paving the way for a pandemic analytics discipline that we will launch. Analytics is the collection and interpretation of data from multiple fields to extract insights. Pandemic analytics is a new approach to tackle a phenomenon as ancient as humanity itself when used to research and global combat outbreaks: the spread of disease.

To sculpt the correct approach.

John Snow, the father of modern epidemiology, discovered cluster clusters of cholera cases around water pumps in the early 1850s when London fought a rampant increase in cholera cases. For the first time, this breakthrough allowed scientists to exploit data to battle pandemics, guide their efforts to measure the danger, identify the enemy, and formulate an effective response plan.

The Predictive and ability to analyze

The accessibility of information from reputable sources has contributed to the exchange of visualizations and tweets to teach the public without precedent. Take the complex world map created by the Center for Systems Science and Engineering of Johns Hopkins, such as these beautifully basic but enlightening animations from the Washington Post. These visualizations quickly show the public how viruses spread and which human behavior will assist or impede viruses’ spread. The democratization of data and computational resources, along with the vast capacity to exchange information over the internet, has allowed us to see the impressive impact of data being used for good.

In recent months, corporations have launched in-house pandemic data processing to develop their proprietary intelligence. To direct their personnel, clients, and the broader partner community through the ongoing crisis, some of the more enterprising organizations have also set up internal Track & Reply Command Centers.

Early in the epidemic, Oaperg learned that it would require its own COVID-19 response command center. It allows Oaperg data scientists the autonomy to create new and pragmatic ideas for more educated decision making, orchestrated by senior leadership. For example, the application of predictive analytics on the future effect of Oaperg clients and the industries where Oaperg represents them.

We used statistics, control theory, simulation modeling, and natural language processing to enable management to react rapidly during the COVID situation.

The condition to grasp its magnitude quantitatively and qualitatively.

Perform real-time subject modeling through thousands of international health agency publications and reputable news outlets; automate the extraction of quantifiable patterns (alerts) and actionable knowledge related to the position & duty. Build forecasting that can map and estimate directionally when regions vital to Oaperg and its clients will hit peak infection and, conversely, an improvement in recovery rate.

How we respond to matters. As a substitute for the real pandemic, using a statistical model of the scenario and using versatile and realistic variables to construct a multi-dimensional simulation model to deliver a practical forecast tailored to the leader using it.

The early burst of creativity has since matured, and 170 years of accumulated intelligence have demonstrated that the transmission of the disease is interrupted by early interventions. However, research, decision-making, and corresponding intervention can only be successful when all accessible/meaningful data points are first considered.

With machine learning and algorithms, healthcare officials at the Sheba Medical Center in Israel use data-driven planning to maximize the deployment of staff and services in anticipation of future cases. such as reported cases, deaths, test outcomes, touch tracing, population growth, demographics, migration traffic, medical resource supply, and stockpiles of pharmaceuticals.

There is a small silver lining to the viral spread: the exponential development of new evidence that we can benefit from and respond upon. Healthcare practitioners may address questions with the right analytical skills, such as where the next cluster is most likely to occur, which population is most vulnerable, and how the virus may mutate over time.

To Detect, Cure, and Recover

On December 21, 2019, the earliest anomalies linked to what was then considered a mystery pneumonia strain in Wuhan were found by an AI system run by a Toronto-based startup named BlueDot. To identify a resemblance to the 2003 SARS epidemic, the AI system had access to over one million publications in 65 languages. Only nine days later did the WHO alert the general public to the existence of this new threat.

It is a struggle to solve data at scale to build healthcare technologies, and this is where AI will play a key role. To better diagnose the Coronavirus by imaging research, AI technology has also been deployed, reducing the diagnostic time from CT scan findings from around 5 minutes to 20 seconds. AI can help cope with the growing workloads of diagnostics by automation and free up precious money to spend on treating patients.

It is also possible to use AI and ML to speed up the process of pharmaceutical production. Just one AI-developed drug has completed clinical trials in humans so far. But when the system could speed up a method that usually takes years, even the solitary achievement is highly remarkable.

It’s also likely that AI can help reduce drug production periods to mere months or weeks in collaboration with medical researchers. This human-machine synergy in the pharmaceutical room is the need of the hour, with the world still in desperate need of a COVID-19 vaccine months after the first reported death.

Conclusion

It is important to note that technology is nothing but humanity’s collective innovation over time as the planet prepares itself for the effects of the COVID-19 epidemic. With technology, we have the resources required to help us live and defend ourselves. In the coming weeks and months, we do not know what lies in store for us, but we sure can interpret, and draw wisdom from our everyday experience. We have the opportunity to contain and mitigate the effects of illness now and in the future, with the right technologies applied in the right way.