A major problem of the Covid-19 pandemic lies with asymptomatic infections – people that carry and transmit the virus without symptoms. A recently developed AI against Covid-19 has a sharp algorithmic ability to detect both symptomatic and asymptomatic cases by analyzing the sound of a person’s cough.
Pioneered by a group of researchers from MIT, the newly developed AI technology against Covid-19 is currently in clinical trials and the group have reached out to the Food and Drug Administration (FDA) for it to be used as a screening tool.
Based on previous studies, the current algorithm has already proven successful in previous cases where it managed to identify conditions such as Alzheimer’s, pneumonia and asthma.
The team took a systematic approach to develop their COVID-19 detecting tool. The researchers began by creating a website, whereby both healthy and infected people were asked to record their coughs via phones or computers. Participants were also asked to complete a survey of questions regarding their diagnosis and any symptoms they were experiencing.
With the data collected, the researchers built their AI tool and found that it was able to pick up differences in coughs directly related to four COVID-19 symptom categories: vocal cord strength, muscular degradation, sentiment, and respiratory/lung performance.
Through the website, the researchers gathered more than 70,000 individual recordings of forced-cough samples, according to their studies. Of those, 2,660 were patients who had COVID-19 both symptomatic and asymptomatic. The research team then used 4,256 of the samples to train their AI model and used 1,064 of the samples to test their model to see whether or not it could accurately detect the difference in coughs between COVID-19 patients and healthy individuals.
The research team’s results yielded 98.5 percent success rate in identifying people with COVID-19 and a 94.2 percent success rate in accurately identifying people who are not infected. For asymptomatic individuals, the technology successfully identified 100 percent of people with the virus and can correctly rule out 83.2 percent of individuals without the virus.
The team is currently seeking regulatory approval for the app that incorporates the COVID-19 model. The team is also testing the technology in a number of medical institutions worldwide.
*The study can be found in the IEEE Open Journal of Engineering in Medicine and Biology
Why GovTech adoption during COVID-19 is a must
GovTech is a new term that refers to the modernization and/or digitization of government services for better accessibility and efficiency of public services. A mouth full, but this suggests a need for governments to do what the private sector has been doing from the start: embrace and incorporate industry 4.0 technology. However, to do so on a governmental level is complex.
The tech revolution occurring around the world, accelerated by the pandemic will not wait for governments to search their paper file cabinet for a solution. Citizens’ expectations of speed and efficiency are set higher by the private sector.
Too many authorities in developing nations, and many government-managed institutions in developed nations, are woefully behind on tech adoption within their systems.
According to the World Bank’s definition as stated in their brief, GovTech is essentially about putting people first.
“GovTech is a whole-of-government approach to public sector modernization that promotes simple, accessible, and efficient government”.
Governments who had already begun improving their digital infrastructure before the pandemic, had a better chance of curbing outbreaks after the initial wave with known exceptions. Namely the US and UK.
Examples of GovTech used well during the pandemic can be found more to the east, in Singapore and South Korea among others, where data-gathering and citizen compliance with safety measures worked well to begin with.
Still, in the United states we see examples of GovTech being implemented even before the pandemic.
In areas of infrastructure, 120 Water Audit was recently launched, a cloud-based water management software, that a government on any level and size can use to minimize water waste.
During the pandemic, we have seen companies like BlueDot develop early warning systems to predict outbreaks, allowing governments to react preemptively. These systems used data gathered from numerous data sets from news, medical records and airlines to detect certain trends using their algorithm.
In the future, we should expect better GovTech adoption in public health services. Governments must work with the private sector to secure the right systems and consolidate their systems for better data collection. Undoubtedly, this is a long-term process.
Vaccine warriors: University of Oxford COVID-19 vaccine update
As the race for a new COVID-19 vaccine continues, the University of Oxford vaccine is effective at stopping people from developing COVID-19 symptoms. Overall, results indicated 70 percent protection rate, however, researchers claim that figures can increase to 90% if the dose is modified.
Study lead, Andrew Pollard, Professor of Paediatric Infection and Immunity at the University of Oxford, has vast experience in clinical trials of new and improved vaccines for children and adults.
In comparison to the Pfizer and Moderna vaccines, the University of Oxford vaccine is far cheaper, easier to store and can be transported to every country around the world. It shows highly promising use in tackling the current pandemic, if it gets the approval from regulators, who will assess the vaccine based on safety, efficacy and manufacturing standards. This process is set to take place in the coming weeks.
While typical vaccines usually take around a decade to be developed, the University of Oxford vaccine was developed in about 10 months. Initial trials involved a sample size of 20,000 individuals: 10,000 participants in the UK and 10,000 participants in Brazil. From the study, there were 30 Coronavirus cases from those who received two doses of the vaccine and 101 cases in people receiving placebo treatment.
The researchers say it works out at 70 percent protection however, it increased to 90 percent when people were given a “low” dose followed by a high one. It remains unclear why there is a difference.
Although nothing will happen until the University of Oxford vaccine receives full approval, the UK is preparing for an unprecedented immunization campaign. Care home residents and staff will be the first in line while healthcare workers and citizens 80 years and above, will be the next priority. The plan is to steadily work down the age groups.
After Pfizer and Moderna introduced their vaccine candidates with a protection rate of 95 and 90 percent respectively, a figure of 70 percent might be perceived by some as disappointing. However, in reality, anything above 50 percent is considered promising.
AstraZeneca, Oxford University’s manufacturing partner is prepping to make three billion doses of the vaccine to be made available worldwide.
Research finds UV light technology capable of neutralizing COVID-19 air particles
Recent research conducted by researchers from Queen Mary University of London and Leeds Beckett University suggests that UV light technology can be used to neutralize COVID-19 particles traveling through the air. This kind of UV light called ‘Upper room UVGI’ (UV Germicidal Irradiation) could then be used to curb the spread of the virus.
Although we know that UVC light can be harmful to humans, upper room UVGI works through UV light technology by creating an irradiation field above people’s heads where it inactivates COVID-19 particles in the room’s atmosphere – while people remain untouched.
The research published in the journal PeerJ details that the technology has already been used against airborne diseases such as measles and tuberculosis within buildings. By analyzing the historical data around it, the researchers concluded that using UVGI technology could be used to do the same for COVID-19.
“Now we know that COVID-19 infection can occur from airborne exposure to the virus, finding ways to minimise the risk of transmission, particularly in buildings is becoming increasingly important”, said Professor Clive Beggs, Emeritus Professor of Applied Physiology at Leeds Beckett University, “Whilst we know wearing masks and opening windows are effective ways to minimise the spread of Covid-19 indoors, these measures aren’t always practical, especially in winter.”
The research underlines the feasibility of using the technology in crowded areas where space is limited like hospital hallways or in places like cafes and restaurants, or in areas of poor ventilation. In addition to respecting traditional social safety measures, the high UV light technology can help minimize the number of transmissions that can occur.
“Now it becomes more of an engineering problem of how we can use this technique to prevent the spread in buildings”, said Dr Eldad Avital, Reader in Computational Fluids and Acoustics at Queen Mary. “This is where computational fluid dynamics becomes important as it can start to address questions around how many UVGI lights are needed and where they should be used. One thing we know is particularly important for these systems is air movement, so for them to work effectively in poorly ventilated spaces, you might need to use ceiling fans or other devices to ensure that larger aerosol particles are adequately irradiated.”
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