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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

Newly operational sequencing unit in genomics at UFS
2016-09-09

Description: Next Generation Sequencing  Tags: Next Generation Sequencing

Dr Martin Nyaga and his research assistant,
Tshidiso Mogotsi in the Next Generation
Sequencing Laboratory.
Photo: Charl Devenish

The Next Generation Sequencing (NGS) unit at the UFS was established as an interdisciplinary facility under the Directorate for Research Development, Faculty of Health Sciences and Faculty of Natural and Agricultural Sciences.

The aim of the NGS facility is to aid internal and external investigators undertaking studies on Deoxyribonucleic acid (DNA) sequencing, assembly and bioinformatics approaches using the more advanced Illumina MiSeq NGS platform.

The NGS unit became operational in 2016 and is managed by Dr Martin Nyaga and administered through the office of the Dean, Faculty of Health Sciences, under the leadership of Prof Gert Van Zyl. Dr Nyaga has vast experience in microbial genomics, having done his PhD in Molecular Virology.

He has worked and collaborated with globally recognised centres of excellence in Prokaryotic and Eukaryotic genomics, namely the J. Craig Venter Institute and the Laboratory of Viral Metagenomics, Rega Institute, among others.

The unit has undertaken several projects and successfully generated data on bacterial, viral and human genomes. Currently, work is ongoing on bacterial and fungal metagenomics studies through 16S rRNA sequencing.

In addition, the unit is also working on plasmid/insert sequencing and whole genome sequencing of animal and human rotaviruses. The unit has capacity to undertake other kinds of panels like the HLA, Pan-cancer and Tumor 15 sequencing, among others.

Several investigators from the UFS including but not limited to Prof Felicity Burt, Prof Wijnand Swart, Dr Frans O’Neil, Dr Trudi O'Neill, Dr Charlotte Boucher, Dr Marieka Gryzenhout and Dr Kamaldeen Baba are actively in collaboration with the NGS unit.

The unit has also invested in other specialised equipment such as the M220 Focused-ultrasonicator (Covaris), 2100 Bioanalyzer system (Agilent) and the real-time PCR cycler, the Rotor-Gene Q (Qiagen), which both the UFS and external investigators can use for their research.

Investigators working on molecular and related studies are encouraged to engage with Dr Nyaga on how they would like to approach their genomics projects at the UFS NGS unit. 

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