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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

Research eradicates bacteria from avocado facility
2017-01-17

 Description: Listeria monocytogenes Tags: Listeria monocytogenes

Listeria monocytogenes as seen under an electron
microscope. The photo was taken with a transmission
electron microscope at the microscopy unit of the UFS.
Bacteriophages (lollipop-like structures) can be seen
next to the bacterial cells.
Photo: Supplied

“The aim of my project was to identify and characterise the contamination problem in an avocado-processing facility and then to find a solution,” said Dr Amy Strydom, postdoctoral fellow in the Department of Microbial Biochemical and Food Biotechnology at the University of the Free State (UFS).

Her PhD, “Control of Listeria monocytogenes in an Avocado-processing Facility”, aimed to identify and characterise the contamination problem in a facility where avocados were processed into guacamole. Dr Strydom completed her MSc in food science in 2009 at Stellenbosch University and this was the catalyst for her starting her PhD in microbiology in 2012 at the UFS. The research was conducted over a period of four years and she graduated in 2016. The research project was funded by the National Research Foundation.

The opportunity to work closely with the food industry further motivated Dr Strydom to conduct her research. The research has made a significant contribution to a food producer (avocado facility) that will sell products that are not contaminated with any pathogens. The public will then buy food that is safe for human consumption.


What is Listeria monocytogenes?

Listeria monocytogenes is a food-borne pathogenic bacterium. When a food product is contaminated with L. monocytogenes, it will not be altered in ways that are obvious to the consumer, such as taste and smell. When ingested, however, it can cause a wide range of illnesses in people with impaired immune systems. “Risk groups include newborn babies, the elderly, and people suffering from diseases that weaken their immune systems,” Dr Strydom said. The processing adjustments based on her findings resulted in decreased numbers of Listeria in the facility.

The bacteria can also survive and grow at refrigeration temperatures, making them dangerous food pathogens, organisms which can cause illnesses [in humans]. Dr Strydom worked closely with the facility and developed an in-house monitoring system by means of which the facility could test their products and the processing environment. She also evaluated bacteriophages as a biological control agent in the processing facility. Bacteriophages are viruses that can only infect specific strains of bacteria. Despite bacteriophage products specifically intended for the use of controlling L. monocytogenes being commercially available in the food industry, Dr Strydom found that only 26% of the L. monocytogenes population in the facility was destroyed by the ListexP100TM product. “I concluded that the genetic diversity of the bacteria in the facility was too high and that the bacteriophages could not be used as a control measure. However, there is much we do not understand about bacteriophages, and with a few adjustments, we might be able to use them in the food industry.”

Microbiological and molecular characterisation of L. monocytogenes

The bacteria were isolated and purified using basic microbiological culturing. Characterisation was done based on specific genes present in the bacterial genome. “I amplified these genes with polymerase chain reaction (PCR), using various primers targeting these specific genes,” Dr Strydom said. Some amplification results were analysed with a subsequent restriction digestion where the genes were cut in specific areas with enzymes to create fragments. The lengths of these fragments can be used to differentiate between strains. “I also compared the whole genomes of some of the bacterial strains.” The bacteriophages were then isolated from waste water samples at the facility using the isolated bacterial strains. “However, I was not able to isolate a bacteriophage that could infect the bacteria in the facility.

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