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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

Fighting the tuberculosis battle as a collective
2015-09-28



The team hard at work making South Africa a
healthier place

Tuberculosis (TB) is second only to HIV/AIDS as the greatest killer worldwide due to a single infectious agent. More than 95% of TB deaths occur in low- and middle-income countries. Despite being more prevalent among men than women, TB remains one of the top five causes of death amongst women between the ages of 15 and 44 years. While everyone is at risk for contracting TB, those most at risk include children under the age of five and the elderly. In addition, research indicates that individuals with compromised immune systems, household contacts with pulmonary TB patients, and healthcare workers are also at increased risk for contracting TB.

According to the Deputy Director of the Centre for Health Systems Research and Development (CHSR&D) at the UFS, Dr Michelle Engelbrecht, research has found that healthcare workers may be three times more likely to be infected by TB than the general population.

The unsettling fact

“Research done in health facilities in South Africa has found that nurses do not often participate in basic prevention acts, such as opening windows and wearing respirators when attending to infectious TB patients,” she explained. 

In response to this concern, CHSR&D, which operates within the Faculty of Humanities at the the University of the Free State (UFS) Bloemfontein Campus has developed a research project to investigate TB prevention and infection control in primary healthcare facilities and households in Mangaung Metropolitan.

Action to counter the statistics

A team of four researchers and eight field workers from CHSR&D are in the process of gathering baseline data from the 41 primary healthcare facilities in Mangaung. The baseline comprises a facility assessment conducted with the TB nurse, and observations at each of the facilities. Individual interviews are also conducted with community caregivers, as well as TB and general patients. Self-administered questionnaires on knowledge, attitudes, and practices about TB infection control are completed by all nurses and facility-based community caregivers.

Healthcare workers are the main focus of this research, given their increased risk of acquiring TB in healthcare settings. At clinics, interventions will be developed to improve infection control practices by both healthcare workers and patients. TB patients’ households are also visited to screen household contacts for TB. Those found to have symptoms suggesting TB infection are referred to the clinics for further assessment and treatment.

The findings of this study will serve to inform the development of an intervention to address TB prevention and infection control in primary healthcare facilities. Further funding will be sought to implement and evaluate the intervention.

Curbing future infections and subsequent deaths as a result of TB is the priority for the UFS. The cooperation and collaboration of the community, government, and sponsors will ensure that this project is a success, hence prolonging life expectancy.


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