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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

UFS first to mechanise agricultural technique
2006-05-09

    

Small farmers from Thaba `Nchu were the biggest group attending the farmers day at the UFS Paradys experimental farm.  From the left are Mr David Motlhale (a small farmer from Thaba 'Nchu), Prof Leon van Rensburg (lecturer at the UFS Department of Soil, Crop and Climate Sciences and project leader), Mr Nhlonipho Nhlabatsi (Agricultural Research Council, Glen), Ms Meisie Mthethwa (small farmer from Bloemspruit).  In front is Mr Patrick Molatodi (chairperson of the Tswelopele Small Farmer Association).
 

 

Some of the participants of the farmers day at the UFS Paradys experimental farm were from the left Prof Leon van Rensburg (lecturer at the UFS Department of Soil, Crop and Climate Sciences and project leader, Mr Patrick Molatodi (chairperson of the Tswelopele Small Farmers Association) and Prof Herman van Schalkwyk (Dean: UFS Faculty of Natural and Agricultural Sciences).

UFS first tertiary institution in world to mechanise agricultural technique
The University of the Free State (UFS) is the first tertiary institution in the world to mechanise the in-field rain water harvesting technique on a commercial scale.

The technique was recently demonstrated to about 100 small farmers at the UFS Paradys experimental farm outside Bloemfontein. 

“With this technique rain water is channeled to the plant and in this way food security is increased.  The advantage of the technique for commercial farmers lies in the reduced cultivation of land.  Small farmers will benefit from this because they can now move out into the fields and away from farming in their back yards,” says Prof Leon van Rensburg, lecturer at the UFS Department of Soil, Crop and Climate Sciences and project leader.    

Rain water harvesting is an antique concept that was used by communities before the birth of Christ.  In South Africa the technique is mainly used in the plots of small farmers where they make surface structures by hand. 

"The technique is also used for the first time by the UFS on commercial scale by means of the cultivation of a summer crop on 100 ha at the Paradys experimental farm,” says Prof Leon van Rensburg,

Of the farmers who attended the farmers day most represented about 42 rural communities in the vicinity of Thaba ‘Nchu.  A group of seven from KwaZulu-Natal also attended the proceedings.  These small farmers can for example apply this technique successfully on the 250-300 ha communal land that is available in the Thaba ‘Nchu area. 

The project is funded by the UFS and the National Research Foundation (NRF) and the farmers’ day was funded by the Water Research Commission.   

Media release
Issued by: Lacea Loader
Media Representative
Tel:   (051) 401-2584
Cell:  083 645 2454
E-mail:  loaderl.stg@mail.uovs.ac.za
9 May 2006

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