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What Is Role of Computing Professionals in covid19 Pandemic?

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Computer scientists tracking the deadly coronavirus epidemic have been working diligently to predict the virus’s next moves. The novel virus, which causes a respiratory illness dubbed COVID-19, has taken the lives of more than 2,100 people. It first emerged in December in the Chinese city of Wuhan, and has since infected more than 75,000 people, mostly in China

The numbers of new cases have begun to drop in China, but concern is growing over expanding outbreaks of COVID-19 in Singapore, Japan, South Korea, Hong Kong, and Thailand.

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Scientists who use math and computers to simulate the course of epidemics are taking on the new coronavirus to try to predict how this global outbreak might evolve and how best to tackle it

But some say more could be done to take advantage of these modeling tools and the researchers' findings. "It is sort of an ad hoc, volunteer effort, and I think that's something that we could improve upon," says Caitlin Rivers, an infectious diseases modeler with the Johns Hopkins Center for Health Security. In her view, "modeling plays a really important role in understanding how an outbreak is unfolding, where it might be going, and what we should be thinking through." But only a small number of the modelers of epidemics work for the federal government, she says. Most are in academia, and they don't have formal relationships with officials who have to make key public health decisions.

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Although their model – and others like them – could be important for predicting the spread of current viruses and targeting disease-control measures, population flow between cities is not always known to high accuracy. In a preprint posted online in February this year, however, Piet Van Mieghem and colleagues at the Delft University of Technology in the Netherlands showed that it is possible to make short-term predictions about the rate of progression of the latest coronavirus, SARS-CoV-2, from Wuhan to other cities in the Chinese province of Hubei if population interactions between cities are inferred from initial observations of the spread, rather than relying on prior knowledge. Comparing their model with real data, they found that its predictions for infections in Hubei cities three days ahead were within 7.5% of the actual numbers (arXiv:2002.04482)

“The coronavirus pandemic has been a good case to demonstrate the power of our method,” says Van Mieghem.

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All things considered, the COVID-19 pandemic will likely continue presenting challenges beyond those that come up in the course of routine virtual education. Even if this viral spread subsides, or a vaccination becomes readily available, the shift from online classes back to in-person learning may create disruptions of its own—adjusting back to higher standards of accountability, weaning off of phone-checking habits, and transferring comments back to hard copies instead of digital notes.

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Bastian Prasse, Massimo A. Achterberg, Long Ma, Piet Van Mieghem
Network-Based Prediction of the 2019-nCoV Epidemic Outbreak in the Chinese Province Hubei, submitted on 11 Feb 2020 (v1), last revised 12 Feb 2020 (this version, v2)]

New York State Department of Health’s COVID-19 Webpage:

Centers for Disease Control and Prevention Webpage:

New York State Green Cleaning Program:

Enhanced Green Cleaning Guidance To Reduce The Spread Of Communicable Disease:

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