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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

UFS praised for hosting international research development programme
2013-03-05

 

At the farewell function were, from the left: Dr GansenPillay (deputy executive officer of the NRF), Emile Goofo (Cameroon), his son Tylio in the arms of Prof Nicky Morgan (Vice-Rector: Operations), Avelino Mondhane from Stockholm University (originally from Mozambique) and Prof Neil Heideman (Dean of the Faculty of Natural and Agricultural Sciences).
Photo: Leatitia Pienaar
05 March 2013

“I must congratulate the University of the Free State on doing something like this,” Dr Gansen Pillay said at the farewell function for the participants in the Southern African Young Scientists Summer Programme (SA-YSSP) at the UFS.

The 19 young scientists from 16 countries completed their three-month programme at the end of February 2013. As another step in the process the participants must write articles for reputable journals and complete their doctoral studies. Their performance in the research world will also be tracked.

Dr Pillay, deputy executive officer of the National Research Foundation (NRF), said an investment was made in the researchers to secure the future of the programme. A lot of persuasion and proof was necessary to convince the Austrian Institute for Applied Systems Analysis (IIASA) that a programme of this nature could be presented in Africa.

The SA-YSSP was hosted and managed by the UFS. The programme was developed by the NRF in collaboration with the Department of Science and Technology (DST) and IIASA into a novel and innovative initiative.  The official launch was by the Minister of Science and Technology during November 2011.

The SA-YSSP will be an annual three-month education, academic training and research capacity-building programme. Aligned with the YSSP model, annually presented in Austria, the SA-YSSP offered scientific seminars covering themes in the social and natural sciences, often with policy dimensions, to broaden the participants’ perspectives and strengthen their analytical and modelling skills, further enriching a demanding academic and research programme.

Prof Martin Mtwaeaborwa, SA-YSSP deputy dean, said the academic performance of the young scientists superseded the expectations. “I hope the scholars will look back at the programme as the moment their careers began.”

The added, “The UFS received positive remarks for organising the programme and we hope to get it again in future.”

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