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

Research conducted on economic impact of recent international soccer and rugby matches for Bloemfontein
2004-09-09

The Centre for Development Support at the University of the Free State (UFS) recently conducted a survey on the economic impact of the international soccer and rugby games that were played in Bloemfontein earlier this year.

The research focused on the soccer match between Bafana Bafana and the Cape Verdic Isle and the rugby match between the Springboks and Ireland .

“The survey was done as a result of a research agenda about local economic development in Bloemfontein ,” said Dr Lochner Marais, researcher at the centre.

“We conducted the research by doing 402 interviews with soccer supporters and 376 interviews with rugby supporters from outside Bloemfontein ,” said Dr Marais.

The centre distributed questionnaires, collecting the following information on the soccer and rugby supporters: their age, gender and origin, the number of nights spend in Bloemfontein , their household expenditure in Bloemfontein and their rating on the quality of service.

“It is estimated that 10 800 soccer supporters and 27 000 rugby supporters came from outside Bloemfontein . Of the rugby supporters 14,4% were female and 85,6% were men. For the soccer international the percentage was 33% females and 67% males,” said Dr Marais.

The highest number of people who came to watch the soccer game in Bloemfontein (35,8%) was from the Northern Free State . The rugby supporters mainly came from Gauteng (21,8%) and the Northern Free State (18%).

When visiting Bloemfontein soccer supporters spend R912 per household, whilst rugby supporters reached deeper in their pockets and spent R1 807 per household.

“The survey indicated that the two international matches resulted in approximately R58 million been spent in Bloemfontein . Rugby supporters were accountable for the largest part (R48 787 205) spent. The largest chunk of the money spent was on accommodation (R14 593 279). On average soccer and rugby supporters from outside Bloemfontein spent 1,4 and 1,9 nights in Bloemfontein ,” said Dr Marais.

Rugby and soccer supporters were also asked to rate the quality of service received from amongst others hotels, guest houses, restaurants, and transport and entertainment facilities. Soccer supporters rated their satisfaction with services higher as rugby supporters. The rugby supporters gave the services at hotels a 3,9 rating, whilst soccer supporters awarded 4,6 rating out of a possible five.

Media release
Issued by: Lacea Loader
Media Representative
Tel: (051) 401-2584
Cell: 083 645 2454
E-mail: loaderl.stg@mail.uovs.ac.za
9 September 2004
 

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