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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

Well-established root system important for sustainable production in semi-arid grasslands
2015-02-24

Plot layout where production and root studies were done
Photo: Supplied

The importance of a well-established root system for sustainable production in the semi-arid grasslands cannot be over-emphasised.

A study of Prof Hennie Snyman from the Department of Animal and Wildlife and Grassland Sciences at the University of the Free State is of the few studies in which soil-water instead of rainfall has been used to estimate above- and below-ground production of semi-arid grasslands. “In the past, plant ecological studies have concentrated largely on above-ground parts of the grassland ecosystem with less emphasis on root growth. This study is, therefore, one of the few done on root dynamics in drier areas,” said Prof Snyman.

The longevity of grass seeds in the soil seed bank is another aspect that is being investigated at present. This information could provide guidelines in grassland restoration.

“Understanding changes in the hydrological characteristics of grassland ecosystems with degradation is essential when making grassland management decisions in arid and semi-arid areas to ensure sustainable animal production. The impact of grassland degradation on productivity, root production, root/shoot ratios, and water-use efficiency has been quantified for the semi-arid grasslands over the last 35 years. Because of the great impact of sustainable management guidelines on land users, this study will be continuing for many years,” said Prof Snyman.

Water-use efficiency (WUE) is defined as the quantity of above- and/or below-ground plant produced over a given period of time per unit of water evapotranspired. Sampling is done from grassland artificially maintained in three different grassland conditions: good, moderate, and poor.

As much as 86, 89 and 94% of the roots for grasslands in good, moderate and poor conditions respectively occur at a depth of less than 300 mm. Root mass is strongly seasonal with the most active growth taking place during March and April. Root mass appears to be greater than above-ground production for these semi-arid areas, with an increase in roots in relation to above-ground production with grassland degradation. The mean monthly root/shoot ratios for grasslands in good, moderate, and poor conditions are 1.16, 1.11, and 1.37 respectively. Grassland degradation lowered above- and below-ground plant production significantly as well as water-use efficiency. The mean WUE (root production included) was 4.79, 3.54 and 2.47 kg ha -1 mm -1 for grasslands in good, moderate, and poor conditions respectively.

These water-use efficiency observations are among the few that also include root production in their calculations.

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