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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

Right to Learn cyclists cross the finish line
2017-12-05

 Description: R2L Finish  Tags: cyclists, Right to Learn, Cape Town, Paarl, GivenGain Foundation, donations 

The Right to Learn cycling team are happy and thankful that they have completed
their journey.
Photo: Mike Rose

After a seven-day journey, the Right to Learn cycling team have finally reached their destination. Having travelled for over a 1 000 kilometres from Bloemfontein, they arrived safely in the Paarl on Monday 4 December 2017. During their final stretch, they travelled 130 kilometres from Montagu to Paarl, where they ended the Right to Learn Cycling Tour.
 
Gratitude for support
Asive Dlanjwa, Bloemfontein Campus SRC President, says, “It's been good, it's been tough, and it’s been an amazing journey.” He expressed his gratitude to everyone who has been supporting them throughout the journey. “Thank you so much for every cent that you have given, for every prayer, and every thought.”
 
Thulasizwe Mxenge, one of the guest cyclists from Johannesburg, says, “Asive had informed us that most students struggle with access to higher education, and we saw the need to assist and take part in the initiative.” He says the journey was tough, because they had to cycle for about five hours every time they went on the road. “I’m very tired but also happy to have completed the journey.”

Donations received
Since the beginning of the Right to Learn initiative, they have managed to raise R80 000 through corporate giving, R15 584 on Dlanjwa’s GivenGain page, and $500 (about R6 845) from the GivenGain Foundation as part of the #GivingTuesday Twitter campaign which took place on 28 November 2017.
 
Annamia van den Heever, Director: Institutional Advancement, says, “Congratulations to Asive and the team!  It has been an absolute pleasure to work with such positive and passionate young people.” She also thanked all donors to the Right to Learn campaign for their support, saying it will ensure that talented students who cannot afford university fees will have access to the UFS next year. “We are hoping that more people will donate now that the tour has been successfully completed. There is no better Christmas gift,” she says.

Dlanjwa says, “We are committed to helping learners who are coming to the UFS next year. The trip was amazing and I feel stronger than I expected. I’d definitely do this again.”
The community is still encouraged to donate towards the initiative, using the following details:

EFT transaction:
Please use the following bank details:
Bank: ABSA Bank
Account Number: 1570850721
Branch Code: 632005
Account Type: Cheque
Reference: R2L: Right to Learn
Send the proof of payment to Rinda Duraan: duraanmj@ufs.ac.za

Debit order: Download the form and email it to Rinda Duraan

All donations are tax deductible in terms of South African income tax legislation.  

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