Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
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

Two scientists part of team that discovers the source of the highest energy cosmic rays at the centre of the Milky Way
2016-03-22

Description: Giant molecular clouds  Tags: Giant molecular clouds

Artist's impression of the giant molecular clouds surrounding the Galactic Centre, bombarded by very high energy protons accelerated in the vicinity of the central black hole and subsequently shining in gamma rays.
Artist's impression: © Dr Mark A. Garlick/ H.E.S.S. Collaboration

Spotlight photo:
Dr Brian van Soelen and Prof Pieter Meintjes of the UFS Department of Physics.
Photo: Charl Devenish

H.E.S.S. (High Energy Stereoscopic System) scientists publically revealed their latest galactic discovery in the international science journal, Nature, on 16 March 2016. These scientists were able to pinpoint the most powerful source of cosmic radiation – which, up to now, remained a mystery.

Part of this team of scientists are Prof Pieter Meintjes and Dr Brian van Soelen, both in the University of the Free State (UFS) Department of Physics. Dr Van Soelen explains that they have discovered a proton PeVatron – a source that can accelerate protons up to energies of ~1 PeV (10^15 eV) – at the centre of the Milky Way. The supermassive black hole called Sagittarius A has been identified as the most plausible source of this unprecedented acceleration of protons.

The protons are accelerated to Very High Energy (VHE) gamma rays. The energy of these protons are 100 times larger than those achieved by the Large Hadron Collider at CERN (the European Organization for Nuclear Research).

According to Dr Van Soelen, the fact that this research has been published in Nature demonstrates the importance and pioneering nature of the research conducted by H.E.S.S. The H.E.S.S. observatory – operational in Namibia – is a collaboration between 42 scientific institutions in 12 countries.

In 2006, H.E.S.S. was awarded the Descartes Prize of the European Commission – the highest recognition for collaborative research – and in 2010 the prestigious Rossi Prize of the American Astronomical Society. The extent of the observatory’s significance places it among the ranks of the Hubble Space Telescope and the telescopes of the European Southern Observatory in Chile.

“The next generation VHE gamma-ray telescope,” Dr Van Soelen says, “will be the Cherenkov Telescope Array (CTA), which is currently in the design and development stage.” Both Dr Van Soelen and Prof Meintjes are part of this project as well.

H.E.S.S. has issued a complete statement about the paper published in Nature.

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept