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12 May 2020 | Story Andre Damons | Photo Pexels

A data scientist and research coordinator at the University of the Free State (UFS), in collaboration with his supervisor at the University of Pretoria (UP), is at the forefront of the fight against the Covid-19 virus with accurate data and analysis.
Herkulaas Combrink of the Centre for Teaching and Learning at the UFS and PhD candidate in Computer Science at the UP, said accurate data is important to prevent widespread panic and sensationalism during a global disaster such as the current pandemic. This information helps people to make informed decisions and to reduce their exposure to the threat of the virus.

Assisting decision-makers

“I, along with colleagues from the World Health Organization, the Centers for Disease Control and Prevention in the USA, the provincial office of the Centers for Disease Control and Prevention, provincial clinicians, and the Free State Department of Health led by Dr David Motau, have been able to progress significantly in terms of evidence-based tools to assist provincial and national decision-makers during these turbulent times.”
“It does come at a cost, though, in that we have worked continuously since the lockdown, dedicating all our time and efforts to the department from all over to ensure that we are not part of some of the global statistics we have seen,” said Combrink. 

A paper written together with his supervisor, Dr Vukosi Marivate, has also been accepted by the Department of Higher Education and Training (DHET)-accredited Data Science Journal.  This paper is related to a framework for sharing public data to the public in a way that is useful, usable, and understandable. 

Ongoing projects

Combrink said it is hard to name all those who are/were involved in the great work done by the Free State Department of Health, but some of them include Dr Elizabeth Reji (Head of Department, Family Medicine), Dr Collin Noel (surgeon, senior lecturer at the UFS), Dr Sammy Mokoena (community health registrar, UFS), Dr Ming-Han Motloung (public health medicine specialist, senior lecturer, UFS), Dr Perpetual Chikobvu (Director: Information Management at the Department of Health, affiliated lecturer at the UFS), as well as Alfred Deacon (lecturer at the UFS), who have worked at some point during this short space of time on one of the many projects. 

Some of the projects include the following:

• A provincial database for screening and monitoring.
• A data pipeline and assembly of hospital information flow, liaised with the NICD, Vodacom, and the different district managers to ensure that the pipeline occurs in a timely manner.
• Digitised paper-based capturing tools for rapid data capturing and processing.
• Incorporated state-of-the-art visualisation tools to action data into useful information for decision-makers in certain areas.
• Provided both provincial and national projections, stress testing different scenarios using a variety of statistical, computational, and/or machine-learning approaches to add to the already existing projections of the Council for Scientific and Industrial Research (CSIR).
• Training healthcare professionals in the field to apply these tools within their own districts.
No easy task

“These aforementioned feats were by no means easy and are not completed yet, but we are getting there. In the foreseeable future, I will be working closely with national and international researchers to deploy a tool for hospital managers in the Free State that will assist them when we move from level 5 to any level below.”

“In addition to this, I am constantly providing support to the Free State Department of Health regarding any analysis required for decision-making purposes. The teams we work in comprise highly competent individuals with a passion for solving problems from multidisciplinary perspectives,” according to Combrink.

News Archive

Researcher works on finding practical solutions to plant diseases for farmers
2017-10-03

 Description: Lisa read more Tags: Plant disease, Lisa Ann Rothman, Department of Plant Sciences, 3 Minute Thesis,  

Lisa Ann Rothman, researcher in the Department of
Plant Sciences.
Photo: Supplied

 


Plant disease epidemics have wreaked havoc for many centuries. Notable examples are the devastating Great Famine in Ireland and the Witches of Salem. 

Plant diseases form, due to a reaction to suitable environments, when a susceptible host and viable disease causal organism are present. If the interactions between these three factors are monitored over space and time the outcome has the ability to form a “simplification of reality”. This is more formally known as a plant disease model. Lisa Ann Rothman, a researcher in the Department of Plant Sciences at the University of the Free State (UFS) participated in the Three Minute Thesis competition in which she presented on Using mathematical models to predict plant disease. 

Forecast models provide promise fighting plant diseases
The aim of Lisa’s study is to identify weather and other driving variables that interact with critical host growth stages and pathogens to favour disease incidence and severity, for future development of risk forecasting models. Lisa used the disease, sorghum grain mold, caused by colonisation of Fusarium graminearum, and concomitant mycotoxin production to illustrate the modelling process. 

She said: “Internationally, forecasting models for many plant diseases exist and are applied commercially for important agricultural crops. The application of these models in a South African context has been limited, but provides promise for effective disease intervention technologies.

Contributing to the betterment of society
“My BSc Agric (Plant Pathology) undergraduate degree was completed in combination with Agrometeorology, agricultural weather science. I knew that I wanted to combine my love for weather science with my primary interest, Plant Pathology. 
“My research is built on the statement of Lord Kelvin: ‘To measure is to know and if you cannot measure it, you cannot improve it’. Measuring the changes in plant disease epidemics allows for these models to be developed and ultimately provide practical solutions for our farmers. Plant disease prediction models have the potential ability to reduce the risk for famers, allowing the timing of fungicide applications to be optimised, thus protecting their yields and ultimately their livelihoods. I am continuing my studies in agriculture in the hope of contributing to the betterment of society.” 

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