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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

Kesa, UFS cross-country teams shine at USSA
2016-10-24

Description: ’Manapo UFS cross-country    Tags: UFS cross-country

The Kovsies 8 km women’s team
was crowned as champions at
the USSA cross-country meeting
in Richards Bay. From the left are
Marne Mentz, Lizandre Mulder,
and Kesa Molotsane.
Photo: Sarina Cronje

The University of the Free State (UFS) not only boasts a South African women’s cross-country champion, one of its women’s teams is also the best university team in the country.
The Kovsies 8 km women’s team was crowned the winners at the University Sports SA cross-country event in Richards Bay, while the 10 km men’s team finished second.

Kovsies men take second place

The women’s team consisted of Kesa Molotsane, Marne Mentz, and Lizandre Mulder. They respectively came in first, third and fifth at the USSA meeting held at the University of Zululand on 30 September and 1 October 2016. In the women’s competition, the times of the first three competitors are used to determine the team placements.

The UFS 4 km women’s team finished in 5th place.

The successful UFS 10 km men’s team consisted of four members from the Qwaqwa Campus – Lesedi Radebe (4th), Lebohang Miya (8th), Moorosi Semase (10th), and Lindobuhle Miya (11th). In the men’s competition, the times of the first four men in each team are taken into account.

The Kovsies 4 km men’s team finished sixth.

Molotsane’s dream year continues

Molotsane, assistant officer at KovsieSport, is experiencing a dream year. On 10 September 2016 she was crowned as national cross-country champion over 10 km when she represented the Free State in George. Mentz was third in George over 4 km.

Molotsane improved her own record in the 3 000 m at the Clover athletics meeting in Bloemfontein on 15 October 2016. Her time of 09:51.03 was much better than her previous record time of 10:03.97.

In the USSA road relay in Richards Bay on 1 October 2016, the Kovsies women’s team finished third in the 3 x 2 km relay. The men came fifth in the 4 x 4 km relay.

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