How AI Can Help The People When Covid19 Pandemic Breakout

Posted by: Dr. Lavern Mraz at 05/12/2021 519 views

Introduction

Despite the difficulty of deployment of future robotics and autonomous vehicles, the COVID-19 pandemic has dramatically accelerated the use of Artificial Intelligence in various fields. We have seen the outcome of two years of digital disruption compressed into just a few months. As one of the first influenza pandemics to spread through our hyper-connected world, COVID-19 has impacted many aspects of our society significantly and rapidly.

BlueDot, a machine-learning-driven algorithm, not only successfully detected the outbreak of Zika in Florida4 but also detected COVID-19 9 days before the World Health Organization issued its statement alerting people to the emergence of a new coronavirus. Chinese researchers are using AI to classify COVID-19 from other strains of pneumonia using patients' chest CT scan images.

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Before the Pandemic

Despite the inconceivable difficulty of avoiding a pandemic, many approaches can be taken to prevent its spread. Infectious diseases are contracted when a pathogen infects one person and spreads to another from one person.

Based on phases 1-3 of the WHO procedure, which this first analyzed period corresponds to, individuals who present this threat should have a healthcare organization that is prepared to scale up and efficient animal health monitoring systems.

For optimal hospital operations, diagnosis, prevention, and therapeutics, surveillance strategies should be supported by centralized, oft-accessed databases covering epidemiological, clinical, and genetic data (Alimadadi et al., 2020). A letter signed by more than 70 scientists, Bogner et al. (2006), was created in response to the outbreak of avian H5N1 influenza to facilitate global access to new virus sequence data

At the Verge of the Pandemic

The WHO recommends that countries that are experiencing an influenza outbreak implement containment strategies, while regions not affected need to be prepared for an immediate response. At this point, infections will have been confirmed in several parts of the world, and the risk of a pandemic is higher.

In this phase, there is little information about the phenomena. The difficulties of predicting accurately and designing accurate control strategies are compounded by uncertainty, social-political dynamics, and a lack of data. Except for public datasets dealing with similar problems,

Not much data is available. The SARS-CoV-2 genome sequence was the first scientific information available regarding the COVID-19 pandemic which helped identify potential treatments for it (Beck et al. 2020).

At the first peak

Dr. Hebreyesus used the word pandemic for the first time on 11th March 2020 to describe COVID-19, with over 100 countries and over 120,000 individuals infected by then. A collaboration between society, medical and research centers was necessary to deal with this global issue.

As a result, it becomes increasingly important to contain the spread of the diseases, and the development of tools to estimate the number of infected people in specific geographic locations is crucial to wise planning of ICUs and emergency structures.

As a result, it becomes increasingly important to contain the spread of the diseases, and the development of tools to estimate the number of infected people in specific geographic locations is crucial to wise planning of ICUs and emergency structures.

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After the First Peak

In stages 3 and 4, the level of pandemic influenza activity is decreasing because of the implementation of restrictive measures and adequate surveillance. But since the level of activity might rise again in later phases, evaluating the response of social and healthcare systems becomes essential to avoid a potential new wave of contagion.

In this context, undertaking retrospective studies helps minimize the impact of the pandemic and decrease the possibility of future outbreaks, as it helps determine whether the interventions employed to date were effective and possibly update guidelines, procedures, and strategies.

After the Pandemic

During this phase, all the strategies put into place during the different phases of the pandemic have paid off, and infection levels are under control; they are comparable to seasonal influenza in most countries with appropriate monitoring.

The Ebola epidemic in 2015 made Gates (2015) point out that the world needed global notification and response mechanisms. The COVID-19 pandemic demonstrates that the world is still not prepared to deal with such a challenge and that this event may serve as a wake-up call.

Gates' proposal, which includes the kind of mechanisms Gates proposed, can be used to highlight the measures that have proved effective and those that have failed to provide guidelines on the best strategies to implement during a health crisis.

Conclusion

Toward the end of the article, we describe an integrative approach that demonstrates how AI is fighting the COVID-19 pandemic. We have presented recent research, described how AI observes and acts on society, and described the data types. The pandemic could provide important solutions for today's society despite the limited contributions of AI research to a small set of tasks, such as image diagnostics. However, AI research has still a long way to go.

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