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05 September 2022 | Story Andrè Damons | Photo Andrè Damons
Prof Abdon Atangana
Prof Abdon Atangana, Professor of Applied Mathematics in the Institute for Groundwater Studies (IGS) and a highly cited mathematician for the years 2019-2021, says existing mathematical models are used to first fit collected data and then predict future events. It is for this reason he introduced a new concept that can be used to test whether the spread will have one or several waves.

With a new outbreak of the Ebola Virus Disease (EVD) reported this year in Democratic Republic of the Congo (DRC) – the 14th EVD outbreak in the country – researchers at the University of the Free State (UFS) introduced a new concept that can be used to test whether the spread will have one or several waves. They believe the focus should be to identify the source or the hosts of this virus for it to be a complete eradication. 

According to the Centers for Disease Control and Prevention (CDC), the Ministry of Health in the Democratic Republic of the Congo (DRC) declared an outbreak of Ebola in Mbandaka health zone, Equateur Province on April 23, 2022. EVD, formerly known as Ebola haemorrhagic fever, is a severe, often fatal illness affecting humans and other primates. The virus is transmitted to people from wild animals (such as fruit bats, porcupines and non-human primates) and then spreads in the human population through direct contact with the blood, secretions, organs or other bodily fluids of infected people, and with surfaces and materials (e.g. bedding, clothing) contaminated with these fluids, according to the World Health Organisation (WHO).
 
Prof Abdon Atangana, Professor of Applied Mathematics in the Institute for Groundwater Studies (IGS), says existing mathematical models are used to first fit collected data and then predict future events. Predictions help lawmakers to take decisions that will help protect their citizens and their environments. The outbreaks of COVID-19 and other infectious diseases have exposed the weakness of these models as they failed to predict the number of waves and in several instances; they failed to predict accurately day-to-day new infections, daily deaths and recoveries.

Solving the challenges of the current models

In the case of COVID-19 in South Africa, it is predicted that the country had far more infections than what was recorded, which is due to challenges faced by the medical facilities, poverty, inequality, and other factors. With Ebola in the DRC, data recorded are not far from reality due to the nature of the virus and its symptoms. However, the predictions show although some measures have been put in place in DRC and other places where the Ebola virus spread, they will still face some challenges in the future, as the virus will continue to spread but may have less impact. 

“To solve the challenges with the current models, we suggested a new methodology. We suggested that each class should be divided into two subclasses (Detected and undetected) and we also suggested that rates of infection, recovery, death and vaccination classes should be a function of time not constant as suggested previously. These rates are obtained from what we called daily indicator functions. For example, an infection rate should be obtained from recorded data with the addition of an uncertain function that represents non-recorded data (Here more work is still to be done to get a better approximation).

“I introduced a new concept called strength number that can be used to test whether the spread will have one or several waves. The strength number is an accelerative force that helps to provide speed changes, thus if this number is less than zero we have deceleration, meaning there will be a decline in the number of infections. If the number is positive, we have acceleration, meaning we will have an increase in numbers. If the number is zero, the current situation will remain the same,” according to Prof Atangana. 

To provide better prediction, he continues, reliable data are first fitted with the suggested mathematical model. This helps them to know if their mathematical model is replicating the dynamic process of the spread. The next step is to predict future events, to do this, we create three sub-daily indicator functions (minimum, actual, and maximum). These will lead to three systems, the first system represents the worst-case scenario, the second is the actual scenario, and the last is a best-case scenario.

Virus will continue to spread but with less impact

Using this method, Prof Atangana, a highly cited mathematician for the years 2019-2021, says he and Dr Seda Igret Araz, postdoctoral student, were able to predict that, although some measures have been put in place in DRC and other places where the Ebola virus spreads, they will still face some challenges in the future as the virus will continue to spread but may have less impact. 

To properly achieve the conversion from observed facts into mathematical formulations and to address these limitations, he had to ask fundamental questions such as what is the rate of infection, what is the strength of the infection, what are the crossover patterns presented by the spread, how can day-to-day new infected numbers be predicted and what differential operator should be used to model a dynamic process followed by the spread?

This approach was tested for several infectious diseases where we present the case of Ebola in Congo and Covid-19 in South Africa.  

News Archive

Pianoboost a hit on Google Play Store
2017-03-01

Description: Pianoboost Tags: Pianoboost

Pianoboost is an interactive app developed by
Dr Frelet de Villiers, lecturer in the Odeion School of Music
at the University of the Free State.
Photo: Supplied

“I got the idea after watching my children play Sing Star on PlayStation, where the game can detect how accurately you sing. I realised this could turn my dream into a reality if I looking into the possibility of an app that can do note recognising,” says Dr Frelet de Villiers, developer of the Pianoboost app, about her brainchild.

Dr De Villiers, lecturer in the Odeion School of Music (OSM) at the University of the Free State (UFS), developed this interactive app for piano learners to learn music. She started the developing process three years ago, but the project only got momentum when she  approached LivX, a digital developing company in Pretoria, six months ago.

Useful for other instruments
Pianoboost has been live since 9 February 2017 and already received positive reviews, with a five-star rating on the Google Play Store. “In my experience as piano teacher, I know that learners struggle to learn their notes. They can’t recognise the note on the music sheet and therefore cannot play it on the piano,” says Dr De Villiers. Although this app is developed for piano, it is also successfully used for other instruments like the marimba, violin, and guitar, because it can pick up sounds from almost any instrument.

Ideal for use in academic programme
There are students in the certificate and diploma modules at the OSM who haven’t received any formal music training. Therefore, the app is ideal for them to use. “We have instrument-specific methodology in our degree courses. So, those students could also be exposed to the app for use in their own teaching of young learners,” says Dr De Villiers.

Different features sets app apart
The app, available on Android devices, has instant music recognition and impressive features that already sets it apart from existing learning apps. It is used on a real acoustical piano (you do not need to plug the tablet into a keyboard), has instant note recognition, shows the correct position of the note on the piano when you are wrong, and works like a flash card system, to name a few. “By using the app, you also learn the names of notes whether you played it right or wrong,” says Dr De Villiers.

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