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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

Water erosion research help determine future of dams
2017-03-07

Description: Dr Jay le Roux Tags: Dr Jay le Roux

Dr Jay le Roux, one of 31 new NRF-rated
researchers at the University of the Free State,
aims for a higher rating from the NRF.
Photo: Rulanzen Martin

“This rating will motivate me to do more research, to improve outcomes, and to aim for a higher C-rating.” This was the response of Dr Jay le Roux, who was recently graded as an Y2-rated researcher by the National Research Foundation (NRF).

Dr Le Roux, senior lecturer in the Department of Geography at the University of the Free State (UFS), is one of 31 new NRF-rated researchers at the UFS. “This grading will make it possible to focus on more specific research during field research and to come in contact with other experts. Researchers are graded on their potential or contribution in their respective fields,” he said.

Research assess different techniques
His research on water erosion risk in South Africa (SA) is a methodological framework with three hierarchal levels presented. It was done in collaboration with the University of Pretoria (UP), Water Research Commission, Department of Agriculture, Forestry and Fisheries, and recently Rhodes University and the Department of Environmental Affairs. Dr Le Roux was registered for 5 years at UP, while working full-time for the Agricultural Research Council – Institute for Soil, Climate and Water (ARC-ISCW).

Water erosion risk assessment in South Africa: towards a methodological framework
, illustrates the most feasible erosion assessment techniques and input datasets that can be used to map water erosion features in SA. It also emphasises the simplicity required for application at a regional scale, with proper incorporation of the most important erosion-causal factors.

The main feature that distinguishes this approach from previous studies is the fact that this study interprets erosion features as individual sediment sources. Modelling the sediment yield contribution from gully erosion (also known as dongas) with emphasis on connectivity and sediment transport, can be considered as an important step towards the assessment of sediment produce at regional scale. 
 
Dams a pivotal element in river networks

Soil is an important, but limited natural resource in SA. Soil erosion not only involves loss of fertile topsoil and reduction of soil productivity, but is also coupled with serious off-site impacts related to increased mobilisation of sediment and delivery to rivers.

The siltation of dams is a big problem in SA, especially dams that are located in eroded catchment areas. Dr Le Roux recently developed a model to assess sediment yield contribution from gully erosion at a large catchment scale. “The Mzimvubu River Catchment is the only large river network in SA on record without a dam.” The flow and sediment yield in the catchment made it possible to estimate dam life expectancies on between 43 and 55 years for future dams in the area.
 
Future model to assess soil erosion
“I plan to finalise a soil erosion model that will determine the sediment yield of gully erosion on a bigger scale.” It will be useful to determine the lifespan of dams where gully erosion is a big problem. Two of his PhD students are currently working on project proposals to assess soil erosion with the help of remote sensing techniques.

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