Analytical Insights

Unique Cross-Practice Analysis reveals 23 Countries which are likely to experience COVID19 Second Wave

What do you get when you apply price analysis methods commonly practiced by financial analysts to COVID19 data? Sunway University has discovered that applying the concepts of support and resistance in the analysis of case trend data can enable the identification of countries that are in the process of facing second waves of COVID19 infections.

The concept of support level in price analysis is when a variable is expected to worsen, but a myriad of factors causes the variable to slow in its worsening progress. On the contrary, a resistance level works in the opposite where an improvement in the variable is met with various factors that cause the improvement to be slowed down.

Figure 1. Global trend of COVID-19. Three supports (indicated by yellow bars) predict increased number of COVID-19 cases.

Using these concepts on COVID19 case data, Sunway University first analysed Total Case data globally in the initial stage of the pandemic as a control mechanism. Based on Figure 1, it is observed that daily confirmed cases vary day-to-day but are generally on a rising trend. This is where the Sunway University team led by Dr Chook Jack Bee, and supported by Prof David Bradley, Prof Teo Kok Lay, Dr Lai Kee Huong, Dr Jane Teh Kimm Lii and Dr Peh Suat Cheng, introduced the idea of supports in the analysis (indicated by the yellow bars).

Figure 2. Trends of COVID-19 infection in United Kingdom. Three supports (indicated by yellow bars) predict increased number of COVID-19 cases. Three resistances (indicated by red bars) predict decreased number of COVID-19 cases.

Applying this simple concept to individual countries reveals more revealing observations. Figure 2 illustrates an example undertaken on United Kingdom. “These support and resistance thresholds are determined from the observed ‘valleys’ of the data plot. The first ‘valley’ will serve as baseline. If the second and third ‘valley’ are higher than the baseline, then it is likely that there is support for a rising trend and vice versa. The red line shows stringency and in respect of incidence would seem to show that even a relatively small relaxation in the former can produce a steep rise in incidence (subsequent to a period of latency). The UK data do not represent a singularity, there being a good many other examples of national data that support such an emergent picture,” explains Dr Chook.

Using 90-day COVID-19 data up till 27th September, the Sunway University team have identified 23 countries that are likely on a trend of new waves of COVID19 in the very near future. These include Bulgaria, Canada, Czech Republic, Denmark, Finland, Georgia, Iceland, Indonesia, Jordan, Malaysia, Montenegro, Mozambique, Myanmar, Netherland, Poland, Portugal, Russia, Uganda, Ukraine, United Arab Emirates, United Kingdom, United States and Uruguay.

Sunway University is currently applying machine learning methods to be able to quickly ascertain similar patterns as the infection continues to evolve. “We hope this analysis will prompt respective countries the urgency to undertake proper measures to counter the rising trend of COVID-19 cases,” added Dr Chook.

Credit to: Dr Chook Jack Bee, Prof David Bradley, Prof Teo Kok Lay, Dr Lai Kee Huong, Dr Jane Teh Kimm Lii and Dr Peh Suat Cheng, Sunway University

Note: The above analysis was made possible by the collaboration of Sunway University with the Global COVID-19 Index (GCI) initiative.

GCI Updates

The GCI Recovery Index Methodology Update – 4 September 2020 (Spain, Serbia)

We are pleased to update that we have applied new Recovery Case Data derivative calculations for Spain and have also updated the formula for Serbia. This enables a more consistent alignment of calculation methods applied for countries which similarly do not report Recoveries such as the United Kingdom, Sweden and Netherlands.

For Spain, we have recognised that there has been no information released on recoveries for over 90 days as at end August 2020. As such, for the purpose of the GCI recovery index calculations, we have applied the same derivative formula as that of United Kingdom and Sweden and taken the sum of 3 weeks of new cases. For the moment we have omitted hospitalisation data as this too is unavailable. The new calculations will be effective 3 June 2020.

For Serbia, we recognise that the Republic of Serbia’s Ministry of Health in collaboration with the Dr. Milan Jovanovic Batut Institute of Health publish a daily dashboard which includes information on hospitalised patients and also those on ventilators. As mentioned in our previous methodology update, we make reference to the World Health Organisation Report (Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19)) dated February 2020, which indicates that “…the median time from onset to clinical recovery for mild cases is approximately 2 weeks and is 3-6 weeks for patients with severe or critical disease.” For the purpose of the GCI recovery index calculations, we have now updated to the derivative formula to replace ventilator-cases with hospitalisation data. This is aligned to the same methodology we currently apply to the United Kingdom and Sweden. As such, the calculation is now the sum of 3 weeks of new cases and the latest reported total of patients in hospital. This new calculation method will be active as of 30 August 2020.

We will continue to monitor the respective countries’ progress and provide further updates should there be new changes to the derivative formulas. These changes ultimately are aimed at ensuring their respective Governments’ efforts are better represented as part of our GCI efforts.