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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

Game farming a lens to analyse challenges facing democratic SA – Dr Kamuti
2017-05-30

 Description: Dr Kamuti Tags: Dr Kamuti

Dr Tariro Kamuti, Postdoctoral Fellow at the Centre
for Africa Studies at the University of the Free State.
Photo: Rulanzen Martin

One of the challenges facing South Africa’s developing game farming policy is the fractured state in the governance of the private game farming sector, says Dr Tariro Kamuti.

Dr Kamuti, a Postdoctoral Research Fellow at the Centre for Africa Studies (CAS) at the University of the Free State (UFS), was presenting a seminar on Wednesday 17 May 2017 under the topic, Private Wildlife Governance in a Context of Radical Uncertainty: Challenges of South Africa’s Developing Game Farming Policy, which takes material from his PhD. He received his PhD from both the Vrije University in Amsterdam and the UFS in 2016.

His presentation explored how the private game industry positions itself in accordance with existing agricultural and environmental regulations. It also investigated the state’s response to the challenge of competing needs over land and wildlife resources which is posed by the gaming sector. “The transformation of the institutional processes mediating governance of the private game farming sector has been a long and enduring arrangement emerging organically over time,” Dr Kamuti said.

Game farming links wildlife and agricultural sectors
“I decided on this topic to highlight that game farming links the wildlife sector (associated with conservation and tourism) and the agricultural sector. Both make use of land whose resources need to be sustainably utilised to meet a broad spectrum of needs for the diverse South African population.

“The continuous skewed ownership of land post-1994 justifies questioning of the role of the state in confronting challenges of social justice and transformation within the economy.”

“Game farming can thus be viewed as a lens through which to study the broad challenges facing a democratic South Africa, and to interrogate the regulatory and policy framework in the agricultural and wildlife sectors at their interface,” Dr Kamuti said.

Challenges facing game farming policies

The state alone does not apply itself to the regulation of private gaming as a sector. “There is no clear direction on the position of private game farming at the interface of environmental and agricultural regulations, hence game farmers take advantage of loopholes in these institutional arrangements to forge ahead,” Dr Kamuti said.

He further went on to say that the state lacked a coherent plan for the South African countryside, “as shown by the outstanding land restitution and labour tenant claims on privately owned land earmarked for wildlife production”.

The South African government was confronted with a context in which the status quo of the prosperity of the middle classes under neoliberal policies was pitted against the urgent need to improve the material well-being of the majority poor.  Unless such issues were addressed, this necessarily undermined democracy as a participatory social force, Dr Kamuti said.

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