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22 June 2020 | Story Andre Damons | Photo Anja Aucamp
Herkulaas Combrink.

A lot can be said about forecasting and modelling, its accuracy, and how it works. Forecasting and modelling provide any decision-maker with plausible predictions or outcomes to give some kind of estimated consequence. Without this field of science, planning would be difficult, as one would simply make decisions without knowing what might potentially happen to a specific cohort, market, or product. Forecasting as a concept can be seen as a set of mathematical, statistical and/or computational tools applied to a set of assumptions about something.

This is according to Herkulaas Combrink of the Centre for Teaching and Learning at the University of the Free State (UFS) and PhD candidate in Computer Science at the University of Pretoria (UP), following the South African government’s modelling of how many people would contract COVID-19 and die, which has come under fire in recent times – with one expert saying it was “flawed and illogical and made wild assumptions”. 

Combrink is of the opinion that South Africa – by using the MASHA Consortium – is using the best minds that the country has to offer. The fact that the leadership took a pragmatic stance and reached out to the scientific community has mitigated a medical disaster in a healthcare system that was not ready a few months ago.

“The government is looking at as many models as they can, but is working very closely with MASHA and the CSIR” says Combrink, who has been involved in clinical surveillance, and also forms part of the modelling team during his secondment to the Free State Department of Health. 

Prof Shabhir Madhi, the former head of the SA National Institute for Communicable Diseases (NICD), recently said that the initial modelling and fatality estimates were “back-of-envelope calculations”.

According to a news report, the government’s initial model also predicted that 600 COVID-19 patients would need treatment in intensive care units (ICU) in SA by April 1. But by April 18, the last publicly released figures showed that there were 32 COVID-19 patients in ICU.

Tried-and-tested models
The models currently used are tried-and-tested epidemiological models, mathematical models, and economic forecasting models that have been used in the past. It has now been calibrated to the specifications that we know of this disease, which come from publications. The reason why you would use more than one model is to compare models retrospectively, so that you can see what is going on.

“The government immediately reached out to the best minds in the country, and with the aid of the consortium, took a stance to throw scenarios at the different models and stress test them so that they could know that they are using the best possible models to assist in resource management and decision-making. If government responded in a different way and didn’t reach out, we might not have had a lockdown and subsequently would probably have been in a different position where the country wouldn’t be ready.” 

“We can say with a high degree of confidence that the lockdown really helps to ease and flatten the curve in the country. In light of flattening the curve, the right decisions have been made,” says Combrink.

COVID-19 still new
Unfortunately, says Combrink, during the COVID-19 pandemic, there was not enough information related to the disease assumptions and it lacked the rigour and perfection associated with the already existing prediction models. Although it may feel like a lifetime, the first COVID-19 case was only reported in December 2019. Add to this that not all the parameters related to the disease were known in January, it was challenging to determine all the ‘ins and outs’ of this disease. 

“Luckily, the mathematics and statistics of an outbreak have been extensively studied, and as a result, we only needed to use the correct parameters to estimate the spread of the disease in some of the outbreak models. The Minister of Health, Dr Zweli Mkhize, and the national modellers led by Dr Harry Moultrie, were transparent with not only their projections, but also how they derived their conclusions and what parameters they used,” says Combrink.

The most important thing in modelling is to calibrate according to what is known about the disease and people, explains Combrink. “It is impossible to predict people and a disease100% accurately, because you don’t always know how a virus will react to every single person’s body and you can’t predict human behaviour.” 

“So, there is a certain degree of error and a certain degree of confidence that lies within each model, and that is why you evaluate these models on a regular basis. And this is important. You will never be able to say this is the exact number. Just like the weather. If the weather patterns were predicted to be 12 degrees tomorrow, and it turns out to be 16 degrees, you at least packed a jersey. You knew it was going to be cold. The chances that the weather predicts that it will be 12 and it turns out to be 57 degrees, is virtually zero. It gives you more or less an indication what to prepare for

Models are useful, but can also be wrong
Combrink says if you want to apply any model, you need to understand the assumptions and the limitations of the models. Given a certain set of criteria – what are the assumptions you are making and what are the expected outcomes – you can only act according to that. He says, as time goes by, we can now see that there are some models that yield much better results because we can now compare what was predicted two months ago and what is actually happening. 
 “Some models are useful. We can get a better understanding of the pandemic’s possible trajectories or gain an understanding of the impact that different interventions have made. Models are used for decision-making. These decision-making strategies can save lives. That is the purpose of models and modelling during these times.”

Combrink uses the weather forecast to explain how modelling works and that models can be wrong. “Yes, models are wrong all the time. Take the concept of weather as an example. How many times has the weather forecast predicted that there is an 80% chance of rain, and then it doesn’t rain? Models can give you a certain degree of confidence in an outcome related to a specific event or scenario, so that you, with some degree of confidence, can go forth and plan accordingly.” 

“However, models can’t tell you what exactly will happen tomorrow, or the day after. It is not a crystal ball, and it is not a mirror into the future, but it can give you an indication of what is likely possible related to a specific scenario if you used the right variables. Let us consider that there is an 80% chance of rain in the weather forecast; will you a) go to work without an umbrella or b) with an umbrella? If it doesn’t rain, you are at least prepared for the rain because you took your umbrella. If you didn’t take the umbrella and it does rain, you may run into trouble because you did not appreciate the warning of the weather forecast. I think it is this concept that makes modelling so powerful. You can use it as a tool to prepare for things, in the event that it does happen, with a certain degree of confidence. Just like the previous example, there is also a 20% chance that it might not rain, but wouldn’t you want to be prepared?” explains Combrink. 
 
Models are tools that can be used to base decisions on
No one truly knows how the pandemic will play out, and according to Combrink, it can be said with a high degree of confidence that if nothing is done about the pandemic, we know how it would turn out from a healthcare perspective. 
“If you look at some of the global projections they gave months ago (in January and February) and compare it to what they said for March and April, you can see that they predicted, with a fairly good degree of confidence, what actually happened in certain countries. We have a good idea in terms of numbers and how it will play out, but what we will never know is what the impact will be on the socio-economic status of a person, the economy, and the impact on other diseases.”

“We do not know what is going to happen when it comes to mental health and COVID-19, for example. This is why modelling is a multidimensional approach, requiring inputs from various fields. Models can help us in the same way the weather forecast does. It is a tool that we can use to base certain decisions on, to be more prepared, because without it we won’t know to pack an ‘umbrella’ if it is predicted to rain or pack a ‘jersey’ if it is projected to cool down.”

News Archive

Institutional research culture a precondition for research capacity building and excellence
2004-11-16

A lecture presented by Dr. Andrew M. Kaniki at the University of the Free State Recognition Function for research excellence

16 November 2004
The Vice Chancellor, Prof. Frederick Fourie
Deputy Vice Chancellors, Deans
Awardees
Colleagues and ladies and gentlemen

It is a great pleasure to be here at the University of the Free State. I am particularly honoured to have been invited to present this lecture at the First Annual Recognition Function for Research Excellence to honour researchers who have excelled in their respective fields of expertise. I would like to sincerely thank the office of the Director of Research and Development (Professor Swanepol), and in particular Mr. Aldo Stroebel for facilitating the invitation to this celebration.

I would like to congratulate you (the UFS) for institutionalizing “celebration of research excellence”, which as I will argue in this lecture is one of the key characteristics of institutional research culture that supports research capacity building and sustains research excellence.

Allow me to also take this opportunity to congratulate the University of the Free State for clocking 100 years of existence.

Ahmed Bawa and Johan Mouton (2000) in their chapter entitled Research, in the book: Transformation in higher education: global pressures and local realities in South Africa (ed. N. Cloete et. al Pretoria: CHET. 296-333) have argued that “…the sources of productivity and competitiveness [in the knowledge society and global economy] are increasingly dependent on [quality] knowledge and information being applied to productivity”. The quality knowledge they refer to here is research output or research products and the research process, which (research) as defined by the [OECD] Frascati Manual (2002: 30) is:

“…creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications”

The South African Government has set itself the objective of transforming South Africa into a knowledge society that competes effectively in the global system. A knowledge society requires appropriate numbers of educated and skilled people to create quality new knowledge and to translate the knowledge in innovative ways. To this end a number of policies and strategies like the Human Resource Development [HRD] Strategy for South Africa, the National Plan for Higher Education (NPHE) and the South Africa’s Research and Development [R&D] Strategy, have highlighted human resource development and the concomitant scarce skills development as critical for wealth creation in the context of globalization. The key mission of the HRD Strategy for instance is:

To maximize the potential of the people of South Africa, through the acquisition of knowledge and skills, to work productively and competitively in order to achieve a rising quality of life for all, and to set in place an operational plan, together with the necessary institutional arrangements, to achieve this.

The R&D Strategy emphasizes that maximum effort must be exerted to train the necessary numbers of our people in all fields required for development, running and management of modern economies. Higher education institutions like the University of the Free State have a key role to play in this process, because whatever form or shape a university takes, it is expected to conduct research (quality research); teach (quality teaching – and good graduates); and contribute to the development of its community! Thus the NPHE states that the role of higher education in a knowledge-driven world is threefold:

Human resource development;

High-level skills training and

Production, acquisition and application of knowledge.

Quality research output or knowledge which as argued is critical in determining the degree of competitiveness of a country in the knowledge economy is dependent upon quality research (process). Both the process of producing quality research and its utilization cannot and does not happen in a vacuum. It requires an environment that facilitates the production of new knowledge, its utilization and renewal. It requires skilled persons that can produce new knowledge and facilitate the production of new skills for quality knowledge production. Such an environment or in essence a university must have the culture that supports research activity. Institution research culture (that is a conducive and enabling institutional research culture) is a precondition to research capacity building. Without an institutional research culture that facilitates the development and nurturing of new young researchers it is difficult, if not impossible for a university to effectively and efficiently generate new and more quality researchers. Institutional research culture is also necessary to sustain quality research and quality research output or research excellence. It facilitates the development and sustenance of the institutional and people capacities required to do research produce quality research and generally attain research excellence!

We do recognize that the patterns of information and knowledge seeking, and knowledge generation vary among field or disciplines. For example, we know that in the humanities knowledge workers often work individually, and not as collaboratively as do those of the sciences, they all however, require supportive environments – institutional research culture to achieve and sustain research excellence. An institution does not simply attain a supportive research culture, but as Patricia Clements (English Department, University of Alberta, Edmonton) in her presentation Growing a research culture argues, research culture has to be grown [and maintained]. It unifies all natural and engineering scientists; medical researchers, humanists, and social scientists.

I therefore am of the view that Institutional Research Culture is critical to research capacity building and research excellence. I therefore want to spend a few minutes looking at the characteristics of research culture. To be effective, institutional research culture has grown and sustained not only at the institutional level, but also at the faculty, school and departmental levels of any university.

What is Research Culture?

In the process of researching on institutional research culture I identified several characteristics. Many of these overlap in some way. I want to deal with some of these characteristics; some in a little more detail while others simply cursorily. In the process what we should be asking ourselves is the extent to which an institution, like the University of the Free State, and its faculties, individually and severally, is growing and or sustaining this culture.

Institutional Research Strategy: As a plan of action or guide for a course of action, the institutional research strategy must spell out research goals that a university wants to achieve. It must be a prescription of what the university needs to be done with respect to research. As a strategy it is neither an independent activity nor an end in itself, but a component part and operationalization of the university policy or mission. ( Related to this is the Establishment of Institutional research policies)

Includes and makes public the targets, e.g. achieve so many rated scientists and make sure that every year we have so many SAPSE publications. That way people keep an eye on research agendas of the university and nation.

The UFS is obviously on its way, having launched its own Research strategy (A Strategic framework for the development of research at the University of the Free Sate. August 2003). Note that this strategy refers specifically to the “Culture of research” Fig 1

A set of administrative practices to support and encourage research. Patricia Clements (English Department, University of Alberta, Edmonton) in her presentation Growing a research culture argues that that research activity and output within the her Faculty (Arts) were very low and, in spite of the numbers of staff, with no Associate Dean for Research in the Faculty as though they had accepted that research belonged to Medicine and Science and Engineering, and teaching, separated from inquiry, belonged to the Arts. With the change in the thinking about research and development of research culture, it became clear that there was a major role for research support in a faculty her size (now about 360 full time continuing academic staff). The faculty developed a support system for research and began to address the SSHRC issues.

Reduce the bureaucracy system and micromanagement of research! This however, also implies that there is capacity and policies and procedure to manage and guide research processes

Establishment of Intellectual Property regulations and assistance

Research ethics policy and safeguarding by research administration

Focused, applied and suitable nature of the delivery mode (an institution open to new methodologies for conducting research

Programmes suited both full and part-time study particularly at graduate level (Mainly at Faculty/school and department level, and depending on what’s manageable)

Hiring senior academics to engage in, teach on and supervise postgraduate students to facilitate exchange of and transfer ideas and most importantly mentorship especially in view of declining numbers of researchers in particular fields

Quality instruction and facilitation in learning about research processes

A high retention rate of students maintained by the supportive and challenging learning environment and the use of online facilities to support collaboration and in-class learning

Availability of research grants: and awareness of sourcing funds from external sources like the National Research Foundation; Water Research Commission; Medical Research Council, private philanthropies and others outside the country. For example an institution should be able to assess how much of the slice the available funds (NRF etc) its able acquire and possibly top slice from institutional budget.

Adequacy of the financial reward system to encourage university staff members to do research (General Celebration of achievement for research excellence and achievement. This ranges form Annual reports mention; celebratory dinner. At Alberta researchers were given lapels. I don’t know of any academic who do not feel a sense of achievement to get into print or recognised. Access to research facilities within and outside the institution

Provision of infrastructure to support university-based research (e.g. equipment, admin support, etc.) – but also awareness of publicly funded and available research facilities and equipment!

Internet connectivity and changes in the bandwidth of the internet to download articles

Subscription to related bodies by the library so that researcher can download articles

Facilities and resources to attend international conferences to keep one updated

Number of visiting professors/speakers targeting senior scholars and invite them to lunch to ask them to participate and to encourage their best graduate students to do so within the institution and across institutions

Research training seminars for research students including young academics

Participation of staff/students in delivering research papers to national and international conferences

Establishment of research groups to provide interaction frameworks to achieve critical mass of research-active staff

Facilitation for more research time: Targeting new scholars and giving them reduced teaching loads in their first year or two for the purpose of developing their research programs. For the purpose of helping new colleagues to see the shape of South African research support, personalizing it, and creating research community

Take research to the community and argue its necessity, and utility

And, finally celebrating excellence. We must recognize achievement - parties and public recognition for colleagues who achieve splendid things in their research.

In conclusion, I want to reemphasize that research culture has to be grown it does not simply exist in an institution. If it is grown it needs to be nourished, nurtured and sustained. An institution cannot simply leave on borrowed reputation and expect to remain research excellent. It is on this basis that instruments like the National Research Foundation rating system recognizes excellence within a given period of time and not necessarily for a life time! This it is believed encourages continued research excellence.

THANK YOU and best wishes

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