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Prof Anthony Turton from the Centre for Environmental Management at the University of the Free State (UFS).

Since a South African team associated with the University of the Free State (UFS) became the first to isolate the SARS-CoV-2 virus from wastewater and developed a viable virus risk forensic service, there has been interest in this technology from a range of role players in North America, Africa, the Middle East, and Southeast Asia, to the South African government.

Prof Anthony Turton from the Centre for Environmental Management at the UFS says contact has been made with two separate scientific teams working in South Africa – one in the Western Cape associated with the Department of Health, and one coordinated by the Water Research Commission reporting to the Department of Water and Sanitation (DWS) – both of which are developing next-generation science. 

Prof Turton says the team has also presented a formal report to the DWS to show that first-generation science is quite capable of generating accurate data that is of great value to planners by feeding into national decision-making bodies.  

A proud achievement 
“As the person who conceptualised this service, I am very proud to be a South African citizen. My background is in national security, so it was that skill set which I applied to the problem when I asked the question – how can we provide the best available information in the shortest possible time, in the face of high risk and growing uncertainty, using the best available technology? This is only possible when one is trained in the intelligence sciences. Intelligence is about converting raw data, often from contested sources, into actionable bits of information with a defined level of certainty.” 
“However, the truly remarkable portion is the team that we rapidly assembled. By hand-picking the right kind of people for the team, we could unlock the power of synergy where 1 + 1 becomes 3. We, as South Africans, have developed a world first, and this is something we can collectively be deeply proud of. This is a proudly South African achievement, not an individual achievement. The benefits belong to society, because even when I was at the CSIR, I championed the notion of ‘science in the service of society’, and here we have another example,” says Prof Turton.

Using available technology
With the 824 wastewater treatment works (WWTW) in the country, the DWS can rapidly deploy this technology to any existing area of concern if they see value in it.  “At present, government is waiting for second-generation science to become available, but that is probably 24 months away at best. In the interim, a crisis is unfolding in the present, and first-generation science is clearly capable of providing sufficiently accurate information to assist in decision-making around the deployment of increasingly scarce resources.”

“DWS used similar technology in the cholera crisis a while back, so they are aware of the benefits. From a society perspective, the question is whether government must wait for the second-generation science to emerge before using the technology, even though first-generation technology can provide an important part of the missing data as explained above. This is what the foreign entities have grasped.”

According to Prof Turton, the interest shown in this technology is from both government and the private sector in North America, Africa, the Middle East, and Southeast Asia. A number of key decision-makers see the value of this technology in mitigating both financial and political risk. 

“They recognise that this pandemic is here to stay for a while, so they intend to get ahead of the curve, which is what the forensics service allows. An example is a condominium where a few hundred people live, but who are unable to use the facilities that they pay levies for. This service will enable all residents in a specific condominium to rebuild trust that they live in a ‘safe space’.” 

“For government, they recognise that this technology can feed data into their mapping systems. They refer to a ‘heat map’ that shows areas of viral activity and areas of relative safety. In one case, the focus is on monitoring each building in a city to identify which building is safe and which is a hot spot,” says Prof Turton. 

Next-generation science 
He explains that next-generation science refers to the algorithms used to extrapolate viral-load data to a larger cohort of people. The first-generation science was about the detection of the virus as a binary measurement: “Is the virus present, yes or no?”

“The current science can do this without a problem. Second-generation science is about how much virus is present? Is this more, or less, than we saw last week? If so, how much bigger or smaller is the signal? If so, can we mathematically calculate from a defined quantum of signal an accurate probability of the total viral load in the population being sampled?” 

“From this, can we say that 15% of the population is shedding virus (a number currently only possible from sewage surveillance) but personal testing shows us that only 5% of the population is positive? If so, we can then say that 10% of the population is both positive and asymptomatic. This has major implications for decision-makers, business owners, tourism operators, and governments who are losing revenue because of failing economies.” 
More importantly, says Prof Turton, is that this missing piece of data will become vital in testing for herd immunity, or the efficacy of a vaccine once available. 

The cost of the service 
By presenting a formal report to DWS, the team was able to get an accurate costing of the service. The cost of a single sewage sample, which can accurately monitor a geographically defined cohort (let’s say 100 000 people for the sake of illustration), is equivalent to 15–20 individual samples (nasal swabs, for example). “We can sample 100 000 people at the same cost as 15 can be sampled individually. More importantly, it is highly unlikely that any government in the world will ever reach anything more than 10% sampling at individual level. This tells us that while individual sampling might be very useful, it is logistically complex, and has a political risk when it cannot be rolled out across a large enough portion of society,” says Prof Turton.  

“The virus-risk forensic service that we have been developing can identify specific hot-spot areas, and those can be targeted for higher saturation coverage of individual testing. For example, in the DWS PoC, we identified one specific WWTW that is a definite hot spot, but another that has no viral signal at all. This means that those people living in the area with no viral signal are safe and do not need to be individually tested, but those in the hot spot need to be isolated and targeted for individual testing. More importantly, we can now say that the hot-spot area is likely to result in demand for medical services in a specific area, so planning can be done before the wave hits the hospital,” explains Prof Turton.   
With the submission of the formal report to government, the Business Water Chamber, and the Public Private Growth Initiative (PPGI), we can now announce a team to offer this virus-risk forensic service to any party with a need for this support in both the public and private sectors.

The team is:  
• Prof Anthony Turton – Centre for Environmental Management at the UFS, responsible for the conceptual design of the virus-risk forensic service. 

• Dr Mpafane Deyi – a graduate from the UFS and CEO of Amanzi-4-All, responsible for implementation of the service to both private and public sector partners.

• Dr Leon Geustyn – Director of Amanzi-4-All, responsible for the mathematical and technical aspects of the risk-based diagnostic service. 

• Dr Shaun Groenink – Director of GreenHill Laboratories, responsible for the laboratory support required.
• Dr Cara-Lesley Bartlett – Senior Scientist at GreenHill Laboratories.

• Mr Neil Madgwick – Director of Praecautio, responsible for the coordination of laboratories as the service grows across the African continent.

• Mr Kevin Lindsay – Director of Instru-Serve, responsible for the refinement of bulk sampling techniques and the supply chain from point of collection to the laboratories.
 

News Archive

Inaugural lecture: Prof. Phillipe Burger
2007-11-26

 

Attending the lecture were, from the left: Prof. Tienie Crous (Dean of the Faculty of Economic and Management Sciences at the UFS), Prof. Phillipe Burger (Departmental Chairperson of the Department of Economics at the UFS), and Prof. Frederick Fourie (Rector and Vice-Chancellor of the UFS).
Photo: Stephen Collet

 
A summary of an inaugural lecture presented by Prof. Phillipe Burger on the topic: “The ups and downs of the South African Economy: Rough seas or smooth sailing?”

South African business cycle shows reduction in volatility

Better monetary policy and improvements in the financial sector that place less liquidity constraints on individuals is one of the main reasons for the reduction in the volatility of the South African economy. The improvement in access to the financial sector also enables individuals to manage their debt better.

These are some of the findings in an analysis on the volatility of the South African business cycle done by Prof. Philippe Burger, Departmental Chairperson of the University of the Free State’s (UFS) Department of Economics.

Prof. Burger delivered his inaugural lecture last night (22 November 2007) on the Main Campus in Bloemfontein on the topic “The ups and downs of the South African Economy: Rough seas or smooth sailing?”

In his lecture, Prof. Burger emphasised a few key aspects of the South African business cycle and indicated how it changed during the periods 1960-1976, 1976-1994 en 1994-2006.

With the Gross Domestic Product (GDP) as an indicator of the business cycle, the analysis identified the variables that showed the highest correlation with the GDP. During the periods 1976-1994 and 1994-2006, these included durable consumption, manufacturing investment, private sector investment, as well as investment in machinery and non-residential buildings. Other variables that also show a high correlation with the GDP are imports, non-durable consumption, investment in the financial services sector, investment by general government, as well as investment in residential buildings.

Prof. Burger’s analysis also shows that changes in durable consumption, investment in the manufacturing sector, investment in the private sector, as well as investment in non-residential buildings preceded changes in the GDP. If changes in a variable such as durable consumption precede changes in the GDP, it is an indication that durable consumption is one of the drivers of the business cycle. The up or down swing of durable consumption may, in other words, just as well contribute to an up or down swing in the business cycle.

A surprising finding of the analysis is the particularly strong role durable consumption has played in the business cycle since 1994. This finding is especially surprising due to the fact that durable consumption only constitutes about 12% of the total household consumption.

A further surprising finding is the particularly small role exports have been playing since 1960 as a driver of the business cycle. In South Africa it is still generally accepted that exports are one of the most important drivers of the business cycle. It is generally accepted that, should the business cycles of South Africa’s most important trade partners show an upward phase; these partners will purchase more from South Africa. This increase in exports will contribute to the South African economy moving upward. Prof. Burger’s analyses shows, however, that exports have generally never fulfil this role.

Over and above the identification of the drivers of the South African business cycle, Prof. Burger’s analysis also investigated the volatility of the business cycle.

When the periods 1976-1994 and 1994-2006 are compared, the analysis shows that the volatility of the business cycle has reduced since 1994 with more than half. The reduction in volatility can be traced to the reduction in the volatility of household consumption (especially durables and services), as well as a reduction in the volatility of investment in machinery, non-residential buildings and transport equipment. The last three coincide with the general reduction in the volatility of investment in the manufacturing sector. Investment in sectors such as electricity and transport (not to be confused with investment in transport equipment by various sectors) which are strongly dominated by the government, did not contribute to the decrease in volatility.

In his analysis, Prof. Burger supplies reasons for the reduction in volatility. One of the explanations is the reduction in the shocks affecting the economy – especially in the South African context. Another explanation is the application of an improved monetary policy by the South African Reserve Bank since the mid 1990’s. A third explanation is the better access to liquidity and credit since the mid 1990’s, which enables the better management of household finance and the absorption of financial shocks.

A further reason which contributed to the reduction in volatility in countries such as the United States of America’s business cycle is better inventory management. While the volatility of inventory in South Africa has also reduced there is, according to Prof. Burger, little proof that better inventory management contributed to the reduction in volatility of the GDP.

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