Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
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

Nanotechnology breakthrough at UFS
2010-08-19

 Ph.D students, Chantel Swart and Ntsoaki Leeuw


Scientists at the University of the Free State (UFS) made an important breakthrough in the use of nanotechnology in medical and biological research. The UFS team’s research has been accepted for publication by the internationally accredited Canadian Journal of Microbiology.

The UFS study dissected yeast cells exposed to over-used cooking oil by peeling microscopically thin layers off the yeast cells through the use of nanotechnology.

The yeast cells were enlarged thousands of times to study what was going on inside the cells, whilst at the same time establishing the chemical elements the cells are composed of. This was done by making microscopically small surgical incisions into the cell walls.

This groundbreaking research opens up a host of new uses for nanotechnology, as it was the first study ever in which biological cells were surgically manipulated and at the same time elemental analysis performed through nanotechnology. According to Prof. Lodewyk Kock, head of the Division Lipid Biotechnology at the UFS, the study has far reaching implications for biological and medical research.

The research was the result of collaboration between the Department of Microbial, Biochemical and Food Biotechnology, the Department of Physics (under the leadership of Prof. Hendrik Swart) and the Centre for Microscopy (under the leadership of Prof.Pieter van Wyk).

Two Ph.D. students, Chantel Swart and Ntsoaki Leeuw, overseen by professors Kock and Van Wyk, managed to successfully prepare yeast that was exposed to over-used cooking oil (used for deep frying of food) for this first ever method of nanotechnological research.

According to Prof. Kock, a single yeast cell is approximately 5 micrometres long. “A micrometre is one millionth of a metre – in laymen’s terms, even less than the diameter of a single hair – and completely invisible to the human eye.”

Through the use of nanotechnology, the chemical composition of the surface of the yeast cells could be established by making a surgical incision into the surface. The cells could be peeled off in layers of approximately three (3) nanometres at a time to establish the effect of the oil on the yeast cell’s composition. A nanometre is one thousandth of a micrometre.

Each cell was enlarged by between 40 000 and 50 000 times. This was done by using the Department of Physics’ PHI700 Scanning Auger Nanoprobe linked to a Scanning Electron Microscope and Argon-etching. Under the guidance of Prof. Swart, Mss. Swart en Leeuw could dissect the surfaces of yeast cells exposed to over-used cooking oil. 

The study noted wart like outgrowths - some only a few nanometres in diameter – on the cell surfaces. Research concluded that these outgrowths were caused by the oil. The exposure to the oil also drastically hampered the growth of the yeast cells. (See figure 1)  

Researchers worldwide have warned about the over-usage of cooking oil for deep frying of food, as it can be linked to the cause of diseases like cancer. The over-usage of cooking oil in the preparation of food is therefore strictly regulated by laws worldwide.

The UFS-research doesn’t only show that over-used cooking oil is harmful to micro-organisms like yeast, but also suggests how nanotechnology can be used in biological and medical research on, amongst others, cancer cells.

 

Figure 1. Yeast cells exposed to over-used cooking oil. Wart like protuberances/ outgrowths (WP) is clearly visible on the surfaces of the elongated yeast cells. With the use of nanotechnology, it is possible to peel off the warts – some with a diameter of only a few nanometres – in layers only a few nanometres thick. At the same time, the 3D-structure of the warts as well as its chemical composition can be established.  

Media Release
Issued by: Mangaliso Radebe
Assistant Director: Media Liaison
Tel: 051 401 2828
Cell: 078 460 3320
E-mail: radebemt@ufs.ac.za  
18 August 2010
 

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept