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Containing COVID-19 with digital technology, AI

By Chukwuma Muanya
02 July 2020   |   3:07 am
Recent studies suggest that Digital Technology (DT) and Artificial Intelligence (AI) could be effectively used to contain the Coronavirus disease

Digital tachnology and artificial intelligence for COVID-19 CREDIT: HITInfrastructure

Recent studies suggest that Digital Technology (DT) and Artificial Intelligence (AI) could be effectively used to contain the Coronavirus disease (COVID-19) pandemic.

DT and AI have also proved to be effective in other aspects of pandemic response. In France, an artificial intelligence-based virtual phone assistant is able to respond to more than a thousand people at the same time. Italy is trialling the use of an AI-based technology that utilises a smartphone app and camera to capture vital statistics such as heart rate, heart rate variability, oxygen saturation and respiration rate in real-time. In Sweden, telemedicine has been used to support traditional care, particularly in rural settings, and is now being used for enhanced COVID-19 response.

Indeed, digital technologies have proved to be powerful tools to fight COVID-19. Critics, however, say these same technologies have exposed humans to a tsunami of information and have raised many issues around data protection and privacy.

Regional Director for Europe, World Health Organisation (WHO), Dr. Hans Henri P. Kluge, in a statement titled “Digital health, is about empowering people”, said: “… we need to get smarter in using the evidence and the information we have from our COVID-19 surveillance systems to improve the only way we have to minimise transmission: find, isolate, test and care for every case. Trace and quarantine every contact.

“Here, digital technology can play a leading role, not least to support contact tracing. Austria, Georgia and North Macedonia are among the 27 countries that have released national solutions for digital contact tracing in Europe; with at least another four countries (Andorra, Finland, Ireland, Portugal) having solutions underway.”

Kluge said digital helps health systems cope with the delivery of essential health care, particularly during emergencies; but integrating digital health must be done carefully and wisely, in partnership with the public and patients.

He warned that digital tools rely on public trust. “Interventions must consider the privacy and security of individuals and their data. Fundamental human and gender rights must be preserved in digital environments and must not be forgone in times of a pandemic. It is the responsibility of governments to address data ownership, use, consent and protection,” Kluge said.

According to him, the world cannot afford to have people then cannot afford digital health. He said not all social groups are equally able to harness the potential of digital technologies to combat the virus. The WHO chief said, in the European Region, national data on household Internet access varies from 74 per cent to 87 per cent, with greater variation at subnational levels and between population groups. “We cannot afford a digital divide on top of the social and economic divide,” Kluge said.

So, three messages, according to Kluge, are: go digital, but go wisely; build trust by respecting privacy; and address the digital gap.

He said the full potential of digital health is yet to be realized and that it is about empowering people to make healthy lifestyle decisions to create a culture of health. “Ultimately, it is about leaving no one behind.”

Also, researchers suggest with the ongoing battle against the spread of COVID-19, timely and accurate data can help governments stay ahead of new transmissions and flatten the curve.

As the COVID-19 pandemic unfolds, IBM Research Africa and WITS University are actively developing machine learning-powered and cloud-driven technologies to aggregate and understand data to yield insights which researchers, policymakers and governments can apply in their battle against coronavirus.

As part of this, IBM Research Africa, WITS University and the Gauteng provincial government have developed a powerful data-driven dashboard to help government make data-driven decisions when it comes to halting the spread of the virus. This dashboard gives health officials a clear, timely and accurate overview aimed at preventing the next hot spot from popping up.

Also, an online application can show in real-time whether the disease is spreading faster or slower in over 200 countries and helps evaluate the effectiveness of public policies aimed at containing the pandemic.

Researchers at São Paulo State University (UNESP) in Araçatuba, Brazil, have developed a computational tool that acts like a “COVID-19 accelerometer,” plotting in real time the rate at which growth is accelerating or decelerating in more than 200 countries and territories.

Available free of charge online, the application automatically loads the most recently notified case numbers from the European Center for Disease Prevention and Control (ECDC), updated daily, and applies mathematical modelling techniques to diagnose the current stage of the pandemic in each country.

Yuri Tani Utsunomiya is a professor at UNESP’s Araçatuba School of Veterinary Medicine (FMVA) and first author of an article published in Frontiers in Medicine journal showing how the mathematical modelling framework can be used to assess the effects of public health measures.

Utsunomiya said: “The application democratizes access to information. Everyone can understand exactly what’s happening in his or her city, state or country. It also helps public administrators and policymakers evaluate whether measures taken to mitigate transmission of the novel coronavirus are having the desired effect.”

To explain how an epidemic progresses, Utsunomiya offered an analogy to a fast car. Initially, the disease spreads slowly, and daily cases grow slowly, just as a car takes some time to pick up speed. The rate of growth is called the ‘incidence’ and is measured by the number of new cases per day. Prevalence is the total number of cases since counting began and can be compared to the distance travelled by this imaginary car.

“Stepping on the throttle makes the number of cases rise rapidly, like a car accelerating and picking up speed. Exponential growth in the number of cases occurs in this second stage of the epidemic. What every country wants is to stop this acceleration and begin to slow transmission. These are two distinct operations,” Utsunomiya explained. “The first consists of taking one’s foot off the throttle so that the acceleration falls to zero. Incidence peaks as a result. The second operation entails exerting negative acceleration on the disease [stepping on the brake] so that the rate of growth falls to zero. Without velocity, the car stops. This is what we all want. We want COVID-19 to stop spreading.”

The COVID-19 accelerometer shows almost in real-time whether a country is accelerating or braking, with a degree of imprecision in countries with under-notification of cases.

However, Utsunomiya stressed that the four stages of growth in the epidemic – flow (green), exponential (pink), deceleration (yellow) and stationary (blue) – may not unfold in that order. Even after a period of deceleration or stationary growth, the disease could again start spreading exponentially if control measures are abandoned. Hence, tools that help continuously monitor transmission are important.

“Our analysis of more than 200 countries and territories showed that effective control measures quickly affect the acceleration curve, well before the number of daily cases starts to fall. This behavior of the curve is highly relevant to any assessment of public policy to control the disease,” Utsunomiya said.

Using official notification data, the application plots incidence – the growth curve everyone wants to flatten so that hospitals are not overwhelmed – and acceleration in real-time, and detects transitions between the four stages. This is made possible by two mathematical techniques: moving regression and a hidden Markov model.

“We developed a simple but highly robust method that takes data available from national and international databases to produce precise information on the progress and movement of the pandemic. Of course, the calculations are based on data that essentially depend on diagnosis [testing],” noted José Fernando Garcia, a professor at UNESP Jaboticabal and a co-author of the article.

While the under-notification of cases is a limitation and may create scale distortions, the epidemiological curves produced by the model are sufficiently accurate, according to the researchers.

An analysis of the curves for Brazil at this time shows that no state has thus far succeeded in leaving behind the exponential growth stage, despite quarantine measures and lockdowns. China reached the stationary stage after only six weeks of well-organized social isolation. Australia, New Zealand, Austria and South Korea have now reached the stationary stage. Italy, Spain and Germany are in the deceleration stage, in which the number of new cases falls daily, thanks to the confinement measures taken.

Utsunomiya divides the measures designed to contain the spread of COVID-19 into two categories: suppression, meaning more intense and severe measures aimed at rapidly reversing the growth curve, example, lockdown, and mitigation measures aimed at lowering the growth rate, example, requiring face masks and discouraging crowds.

“Our study clearly points to the effectiveness of suppression in combating COVID-19,” he said. “However, suppressive measures have been criticized for creating social problems and having a profoundly negative effect on the economy. Mitigation has less severe social and economic impacts, but it’s also less efficient. There really isn’t a silver bullet.”

According to Utsunomiya, Japan is one of the only countries that managed to decelerate the growth of new cases with mitigation measures alone. “Comparing strategies across countries requires caution,” he said. “The effectiveness of mitigation depends on factors like healthcare infrastructure, the amount and frequency of testing, population density, and the extent to which people, in general, comply with the recommendations of the health authorities.”

Also, scientists have developed a wellness app called HearMe.

HearMe is a wellness app, which offers peer-to-peer emotional support. Since the coronavirus outbreak began, the app has seen an increase in new users as people turn to technology to bridge the gap caused by social distancing and feel less alone.

HearMe allows anyone to instantly text with an empathetic listener—trained volunteers who understand what members may be experiencing and offer their support. Listeners go through specialized training to learn effective strategies commonly used in counselling, doctor-patient relationships and crisis interventions. These are real people who want to help—never bots.

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