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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

Kovsies / Pukke Intervarsity 2008: Results
2008-08-14

SPORTKODE SPANNE TEAMS   UITSLAE / RESULTS
      UV / UFS PUK
GHOLF / GOLF MANS / MEN   1 7
      * *
KARATE MANS / MEN   * *
  DAMES / LADIES   * *
TAFELTENNIS / TABLE TENNIS UV USSA TEAM PUK USSA TEAM 4 2
PLUIMBAL/ BADMINTON UV / UFS PUK 1 0
  UV / UFS PUK 0 1
VLUGBAL / VOLLEYBALL UV MANS / UFS MEN PUK MANS 5 0
MUURBAL / SQUASH UV USSA TEAM PUK USSA TEAM 4 2
LANDLOOP / CROSS COUNTRY UV MANS / UFS MEN PUK MANS * *
  UV VROUE / UFS WOMEN PUK VROUE * *
BASKETBAL / BASKETBALL UV MANS / UFS MEN PUK MANS * *
SOKKER FOOTBALL UFS 1 MEN ALS PUK MEN 2 1
SOCCER UFS 2 MEN PUK 2 MEN 0 1
  UFS WOMEN PUK WOMEN 4 0
TENNIS UV MANS / UFS MEN PUK MANS 4 11
  UV VROUE / UFS WOMEN PUK VROUE 14 1
HOKKIE HOCKEY ABSA KOVSIES WOMEN PUK WOMEN 0 8
HOCKEY ABSA UFS 2 WOMEN PUK 2 WOMEN 1 3
  SOETDORING VMN 1 2
  SONNEDOU WNB 2 1
  ROOSMARYN DINKI 2 1
  EMILY HOBHOUSE HEIDE 0 5
  ABSA KOVSIES MEN PUK MEN 0 3
  ARMENTUM VERITAS 2 1
  VERITAS EXCELSIOR 5 0
  KNIGHTS PATRIA (DAAG NIE OP) 1 0
NETBAL NETBALL SOETDORING DINKI 35 25
NETBALL WNB EIKENHOF 39 24
  MARJOLEIN MINJONET 14 20
  VMN 2 BELLATRIX 12 28
  VMN 1 WANDA 16 25
  ROOSMARYN VMN 22 35
  EMILY HOBHOUSE KARLIEN 11 26
  SOETDORING 2 WNB 17 23
RUGBY FNB SHIMLAS PUKKE 20 21
  IRAWAS IBBIES 12 18
  UV / UFS U/21 PUK O/21 30 13
  UV / UFS U/19 PUK O/19 24 11
  UV RITSIMS PUK 3 0 19
  ARMENTUM VERITAS 7 5
  VISHUIS WILGERS 22 31
  KAREE CAPUT 13 43
  JBM VILLAGERS 18 17
  LANDBOU INGENIEURS 33 10
  REITZ PATRIA 40 8
  VERITAS OVERS 3 38
INTERVARSITY OPSOMMING / SUMMARY 2008      
      KOVSIES PUKKE
         
WEDSTRYDE / GAMES     41 41
GEWEN / WON     0 0
VERLOOR / LOST     0 0
GELYK / DRAWN     0 0
         
INTERVARSITY OPSOMMING / SUMMARY 2007      
      KOVSIES PUKKE
         
WEDSTRYDE / GAMES     41 41
GEWEN / WON     13 27
VERLOOR / LOST     27 13
GELYK / DRAWN     1 1
INTERVARSITY OPSOMMING / SUMMARY 2006      
      KOVSIES PUKKE
WEDSTRYDE / GAMES     46 46
GEWEN / WON     27 16
VERLOOR / LOST     16 27
GELYK / DRAWN     3 3

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