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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

Nuclear Medicine on the forefront of cancer research
2017-07-10

Description: Nuclear Medicine on the forefront of cancer research Tags: Nuclear Medicine, cancer research, Dr Je’nine Horn-Lodewyk’s, tumour detection method, cancer, Department of Nuclear Medicine 

Dr Je’nine Horn-Lodewyk’s tumour detection method
could be the cost-effective breakthrough needed to decrease
the mortality rate in breast cancer patients.
Photo: Anja Aucamp

The field of Nuclear Medicine in South Africa and the rest of the world are expanding rapidly due to the development of hybrid cameras and new radiopharmaceuticals. These developments have a huge impact on the diagnosis and therapy of cancer.

The most advanced of these cameras, Positron emission tomography combined with normal CTs (PETCT), are not yet widely available in South Africa due to the cost of the cameras and the radiopharmaceuticals. A more cost-effective alternative can be of great benefit. To achieve this, the focus should be on developing new radiopharmaceuticals that can be used with the current cost-effective gamma cameras, according to University of the Free State researcher, Dr Je’nine Horn-Lodewyk from the Department of Nuclear Medicine.

Fluorodeoxyglucose (18F-FDG), a radiolabelled glucose analogue, is currently the radiopharmaceutical most commonly used in PET/CT imaging for mainly oncology indications. Although it is considered the gold standard for imaging in several malignancies, it does have certain disadvantages. An 18F-FDG PET/CT diagnostic imaging study can cost between R25 000 and R35 000 for a single patient in the private sector. The 18F-FDG is also more radioactive, which requires much stricter handling and shielding to avoid high radiation dosages to staff and patients.

Successful research potential innovative solution
In the search for the ideal radiopharmaceutical for tumour detection, the South African National Nuclear Energy Corporation (Necsa) developed a local synthesis process for ethylenedicysteine-deoxyglucose (EC-DG). EC-DG is also a glucose analogue similar to FDG. They succeeded in labelling the compound with Technetium-99-metastable-pertechnetate (99mTcO4-), the most common nuclear medicine isotope used for approximately 95% of nuclear medicine procedures, creating 99mTc-EC-DG.

In partnership with Dr Horn-Lodewyk, this compound was successfully used in various animal models and clinical scenarios, resulting in approval by the Medicine Control Council to use it in a human study. Research is also planned in order to investigate diagnostic accuracy in other cancers like lymphoma.  The end result of this research can produce a radiopharmaceutical that is cost effective, does not require the use of costly specialised equipment, has no significant side-effects, no special patient preparation, renders late imaging possible, and has decreased radiation risks.

Dr Horn-Lodewyk is grateful for the support of her mentor, Prof Anton Otto, as well as Dr Gert Engelbrecht, Head of the Department of Nuclear Medicine, Prof Jan Rijn Zeevaart from North-West University’s Preclinical Drug Development Platform and Necsa, and Judith Wagener from Necsa. This innovative research would also not have been possible without the financial assistance of Dr Glen Taylor and Eleanor van der Westhuizen in the Directorate of Research Development.

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