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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

Researcher part of project aimed at producing third-generation biofuels from microalgae in Germany
2016-05-09

Description: Novagreen bioreactor  Tags: Novagreen bioreactor

Some of the researchers and technicians among the tubes of the Novagreen bioreactor (Prof Grobbelaar on left)

A researcher from the University of the Free State (UFS), Prof Johan Grobbelaar, was invited to join a group of scientists recently at the Institute for Bio- and Geo-Sciences of the Research Centre Jülich, in Germany, where microalgae are used for lipid (oil) production, and then converted to kerosene for the aviation industry.

The project is probably the first of its kind to address bio-fuel production from microalgae on such a large scale.  

“The potential of algae as a fuel source is undisputed, because it was these photoautotrophic micro-organisms that were fixing sunlight energy into lipids for millions of years, generating the petroleum reserves that modern human civilisation uses today.  However, these reserves are finite, so the challenge is marrying biology with technology to produce economically-competitive fuels without harming the environment and compromising our food security.  The fundamental ability that microalgae have to produce energy-rich biomass from CO2, nutrients, and sunlight through photosynthesis for biofuels, is commonly referred to as the Third-Generation Biofuels (3G),” said Prof Grobbelaar.

The key compounds used for bio-diesel and kerosene production are the lipids and, more particularly, the triacylglyserols commonly referred to as TAGs.  These lipids, once extracted, need to be trans-esterified for biodiesel, while a further “cracking” step is required to produce kerosene.  Microalgae can store energy as lipids and/or carbohydrates. However, for biofuels, microalgae with high TAG contents are required.  A number of such algae have been isolated, and lipid contents of up to 60% have been achieved.

According to Prof Grobbelaar, the challenge is large-scale, high-volume production, since it is easy to manipulate growth conditions in the laboratory for experimental purposes.  

The AUFWIND project (AUFWIND, a German term for up-current, or new impetus) in Germany consists of three different commercially-available photobioreactor types, which are being compared for lipid production.

Description: Lipid rich chlorella Tags: Lipid rich chlorella

Manipulated Chlorella with high lipid contents (yellow) in the Novagreen bioreactor

The photobioreactors each occupies 500 m2 of land surface area, are situated next to one another, and can be monitored continuously.  The three systems are from Novagreen, IGV, and Phytolutions.  The Novagreen photobioreactor is housed in a glass house, and consist of interconnected vertical plastic tubes roughly 150 mm in diameter. The Phytolutions system is outdoors, and consists of curtains of vertical plastic tubes with a diameter of about 90 mm.  The most ambitious photobioreactor is from IGV, and consists of horizontally-layered nets housed in a plastic growth hall, where the algae are sprayed over the nets, and allowed to grow while dripping from one net to the next.

Prof Grobbelaar’s main task was to manipulate growth conditions in such a way that the microalgae converted their stored energy into lipids, and to establish protocols to run the various photobioreactors. This was accomplished in just over two months of intensive experimentation, and included modifications to the designs of the photobioreactors, the microalgal strain selection, and the replacement of the nutrient broth with a so-called balanced one.

Prof Grobbelaar has no illusions regarding the economic feasibility of the project.  However, with continued research, optimisation, and utilisation of waste resources, it is highly likely that the first long-haul flights using microalgal-derived kerosene will be possible in the not-too-distant future.

Prof Grobbelaar from the Department of Plant Sciences, although partly retired, still serves on the editorial boards of several journals. He is also involved with the examining of PhDs, many of them from abroad.  In addition, he assisted the Technology Innovation Agency of South Africa in the formulation of an algae-biotechnology and training centre.  “The chances are good that such a centre will be established in Upington, in the Northern Cape,” Prof Grobbelaar said.

 

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