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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 scientists involved in groundbreaking research to protect rhino horns
2010-07-27

Pictured from the left are: Prof. Paul Grobler (UFS), Prof. Antoinette Kotze (NZG) and Ms. Karen Ehlers (UFS).
Photo: Supplied

Scientists at the University of the Free State (UFS) are involved in a research study that will help to trace the source of any southern white rhino product to a specific geographic location.

This is an initiative of the National Zoological Gardens of South Africa (NZG).

Prof. Paul Grobler, who is heading the project in the Department of Genetics at the UFS, said that the research might even allow the identification of the individual animal from which a product was derived. This would allow law enforcement agencies not only to determine with certainty whether rhino horn, traded illegally on the international black market, had its origin in South Africa, but also from which region of South Africa the product came.

This additional knowledge is expected to have a major impact on the illicit trade in rhino horn and provide a potent legal club to get at rhino horn smugglers and traders.

The full research team consists of Prof. Grobler; Christiaan Labuschagne, a Ph.D. student at the UFS; Prof. Antoinette Kotze from the NZG, who is also an affiliated professor at the UFS; and Dr Desire Dalton, also from the NZG.

The team’s research involves the identification of small differences in the genetic code among white rhino populations in different regions of South Africa. The genetic code of every species is unique, and is composed of a sequence of the four nucleotide bases G, A, T and C that are inherited from one generation to the next. When one nucleotide base is changed or mutated in an individual, this mutated base is also inherited by the individual's progeny.

If, after many generations, this changed base is present in at least 1% of the individuals of a group, it is described as a single nucleotide polymorphism (SNP), pronounced "snip". Breeding populations that are geographically and reproductively isolated often contain different patterns of such SNPs, which act as a unique genetic signature for each population.

The team is assembling a detailed list of all SNPs found in white rhinos from different regions in South Africa. The work is done in collaboration with the Pretoria-based company, Inqaba Biotech, who is performing the nucleotide sequencing that is required for the identification of the SNPs.

Financial support for the project is provided by the Advanced Biomolecular Research cluster at the UFS.

The southern white rhino was once thought to be extinct, but in a conservation success story the species was boosted from an initial population of about 100 individuals located in KwaZulu-Natal at the end of the 19th century, to the present population of about 15 000 individuals. The southern white rhino is still, however, listed as “near threatened” by the World Wildlife Fund (WWF).

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



 

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