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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

Good quality wheat essential for bread production
2016-11-29

Description: Robbie Lindeque Tags: Robbie Lindeque 

Robert Lindeque, wheat breeder at the ARC
Small Grain Institute in Bethlehem.
Photo: Supplied

“Wheat quality, specifically grain protein, is of the most crucial components determining the profitability of wheat farmers.”

This is according to Robbie Lindeque, wheat breeder at the ARC Small Grain Institute in Bethlehem. As a wheat breeder, one of his primary aims is to make a contribution to sustainable wheat production in the inland of South Africa.

A closer analysis of bread wheat protein

With his PHD thesis, "Protein quality versus quantity in South African commercial bread wheat cultivars”, Lindeque answered critical questions regarding the South African wheat industry. The major question of his PhD, which he received on 30 June 2016, was whether protein quality could compensate for protein quantity as a measure of bread quality in South Africa.

The three main wheat-producing areas in South Africa, the dryland summer rainfall region (Free State), dryland winter rainfall region (Western Cape), and the cooler irrigation regions (Northern Cape), were used as a starting point for the study.

Proteins are essential for the baking of good quality bread. Worldwide, the utilisation of wheat flour shipments in the baking industry is determined by the protein proportion of the shipment.

Lindeque says the aim of his thesis was to determine whether a closer analysis of bread wheat protein would provide a better indication of good or bad bread quality. “The conclusion from this study was that both protein quantity and protein quality from all three production areas in South Africa varies constantly in accuracy regarding the estimation of bread volume, mainly as a result of environmental factors,” says Lindeque.

Results relevant to the wheat industry

In 2012, application was made to the Winter Cereal Trust for funding of the project. After funding was approved – thus making the Winter Cereal Trust the main partner – seed samples were collected from the 2012 and 2013 national cultivar adaptation trials.

“After this, the seed underwent protein and flour analyses, which added a third year to the study, with the fourth year consisting of statistical processing and documenting of the results,” says Lindeque.

Funding by the Winter Cereals Trust contributed to the fact that the study constantly attempted to keep issues and results as relevant as possible to the wheat industry.

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