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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

Plant-strengthening agent a result of joint effort between UFS and German company
2015-07-27

Research over the past few years has showed that the agent applied mostly as a foliar spray subsequently leads to better seedlings as well as growth and yield enhancement of various crops.

The application of a plant-strengthening agent in the agricultural industry has, until recently, been largely ignored, says Dr Elmarie van der Watt of the Department of Soil, Crop, and Climate Sciences at the University of the Free State (UFS). The agent was co-developed by researchers at the UFS and a German company.

The product is moving into new markets, such as China, Vietnam, the USA, and Australia.

ComCat® was the result of extensive research by the German company Agraforum AG. Commercialisation was limited initially to Europe, while research was expanded to other parts of the world, with the University of the Free State as the main research centre.  ComCat® is a unique, non-toxic plant strengthening agent derived from wild plants. It enhances plant growth and yield, as well as resistance against abiotic and biotic stress factors.

Dr Van der Watt says that, in nature, plants communicate and interact by means of allelochemicals (the inherent silent tool of self-protection among plants) and other phytochemicals (chemical compounds that occur naturally in plants), as part of their resistance mechanisms towards biotic and abiotic stress conditions.

Most wild-plant varieties are usually well-adapted to resist these stress factors. However, monoculture crops have lost this ability to a large extent. “Active compounds contained in extracts from wild plants applied to monoculture crops can potentially supply the signal for the latter to activate their dormant resistance mechanisms.” 

Research over the past few years has showed that the agent applied mostly as a foliar spray subsequently leads to better seedlings as well as growth and yield enhancement of various crops.  A major advantage is that, despite its enhancing effects on root development and yield, it does not induce unwanted early vegetative growth that could jeopardise the final yield, as happened in the past for nitrogen application at an early growth stage. 

Dr Van der Watt says, “Physiological data on the effect of the natural bio-stimulant product on photosynthesis, respiration, and resistance towards biotic stress conditions indicate that it can be regarded as a useful tool to manipulate agricultural crops. Research also showed that the field of application for this natural product is never-ending, and new applications are being investigated every day.”

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