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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

Researchers receive study grant for research into Congo Fever
2015-03-10

UFS researchers will be contributing significantly to the search for a vaccine against the deadly tick-borne disease known as Congo Fever.

Prof Felicity Burt from the Department of Medical Microbiology and Virology was recently awarded a research grant by the National Health Laboratory Service (NHLS) to study candidate vaccines for Crimean-Congo heamorrhagic fever (CCHF) virus and other arboviruses.

Arboviruses are viruses transmitted by mosquitoes, ticks, or other arthropods.

Prof Burt is an internationally-recognised expert on the Crimean-Congo haemorrhagic fever (CCHF). The Crimean-Congo haemorrhagic fever (CCHF) virus is a tick-borne virus that is associated with severe haemorrhagic disease in South Africa and other parts of Africa, Asia, and eastern Europe. Her interests focus on medically significant viruses that are transmitted by ticks and mosquitoes. Her research group is involved in determining the immune responses that are induced by different viral proteins.

Crimean-Congo haemorrhagic fever (CCHF) virus, a tick- borne virus found in Africa, Asia, the Balkans, and eastern Europe, causes severe viral haemorrhagic fever outbreaks.

Although a number of tick species are capable of becoming infected with CCHF virus, ticks of the genus Hyalomma, commonly referred to in SA as the “bont-legged ticks”, are the principal vector. The ticks have distinctive brown and white bands on their legs.

In February 1981, the first case of CCHF was recognised in South Africa (SA). To date, there have been nearly 200 cases of CCHF infection in SA with a 20% fatality rate. The majority of cases occurring in SA were in patients from the Northern Cape and Free State provinces.

“The funding that has been awarded will be used to profile immune responses against CCHF viral proteins, and investigate mechanisms and strategies to enhance these immune responses. We hope that the study will contribute knowledge towards the development of a vaccine against this medically significant virus.”

For more information or enquiries contact news@ufs.ac.za.

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