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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

Champagne and cancer have more in common than you might think
2013-05-08

 

Photo: Supplied
08 May 2013

No, a glass of champagne will not cure cancer....

…But they have more in common than you might think.

Researchers from the Departments of Microbial Biochemical and Food Biotechnology, Physics and the Centre for Microscopy at the University of the Free State in South Africa were recently exploring the properties of yeast cells in wine and food to find out more of how yeast was able to manufacture the gas that caused bread to rise, champagne to fizz and traditional beer to foam. And the discovery they made is a breakthrough that may have enormous implications for the treatment of diseases in humans.

The team discovered that they could slice open cells with argon gas particles, and look inside. They were surprised to find a maze of tiny passages like gas chambers that allowed each cell to ‘breathe.’ It is this tiny set of ‘lungs’ that puts the bubbles in your bubbly and the bounce in your bread.

But it was the technique that the researchers used to open up the cells that caught the attention of the scientists at the Mayo Clinic (Tumor Angiogenesis and Vascular Biology Research Centre) in the US.

Using this technology, they ultimately aim to peer inside cells taken from a cancer patient to see how treatment was progressing. In this way they would be able to assist the Mayo team to target treatments more effectively, reduce dosages in order to make treatment gentler on the patient, and have an accurate view of how the cancer was being eliminated.

“Yes, we are working with the Mayo Clinic,” said Profes Lodewyk Kock from the Microbial, Biochemical and Food Biotechnology Department at the UFS.

“This technique we developed has enormous potential for cell research, whether it is for cancer treatment or any other investigation into the working of cells. Through nanotechnology, and our own invention called Auger-architectomics, we are able to see where no-one has been able to see before.”

The team of Prof Kock including Dr Chantel Swart, Kumisho Dithebe, Prof Hendrik Swart (Physics, UFS) and Prof Pieter van Wyk (Centre for Microscopy, UFS) unlocked the ‘missing link’ that explains the existence of bubbles inside yeasts, and incidentally have created a possible technique for tracking drug and chemotherapy treatment in human cells.

Their work has been published recently in FEMS Yeast Research, the leading international journal on yeast research. In addition, their discovery has been selected for display on the cover page of all 2013 issues of this journal.

One can most certainly raise a glass of champagne to celebrate that!

There are links for video lectures on the technique used and findings on the Internet at:

1. http://vimeo.com/63643628 (Comic version for school kids)

2. http://vimeo.com/61521401 (Detailed version for fellow scientists)

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