Transition Speed Day to Convergence to Peak
Figure 28. Transition Speed of The Countries: Day to converge Peak
Transition rates tabulated with bar graphs in Figure 25 have been placed in the World map above. As can be seen from the map, the speed of transition as the blue tones goes, that is, the number of days when the epidemic started to accelerate, and the number of days increases as the red goes. As we explained in item 5, when the threshold parameter , that is, in the early periods of the epidemic, the transition speed parameter gets high values. The fact that the transition rate parameter gets high values appears as an indication that the epidemic has just begun. This appears to have occurred in Africa and the Middle East on the Global map. Although it is thought in the first place that getting blue (ending the epidemic in a short time) is a good situation, it appears from the World map that the epidemic in Africa and the Middle East has just begun or measures are being taken recently due to the high transition rate parameter in the LSTT model. Looking at the map, Egypt, Saudi Arabia and Iran appear in dark red. In this sense, in countries that have been able to take measures in Africa and the Middle East, it seems that the outbreak will last long. In this sense, WHO must prepare an emergency action plan for these regions. The regions in orange and yellow tones show the developed and developing countries. In this sense, it seems that they will reach the peak day between 50-70 days from the first day of the average outbreak. Since the data of these country groups and the measures taken are more transparent, we can interpret the information obtained on the map in a correct way. China, Australia and South Korea appear close to yellow, while North America and Europe appear in orange and dark orange tones. The colour spectrum shows us that around 40-50 days in the yellow countries, around 50-60 days in the orange regions and around 60-70 days in the dark orange regions, the outbreak will see its peak after the first acceleration day. It seems that the epidemic will peak in different days in May for groups of these countries. In order to reveal this information more effectively, we can also use the epidemic start map, which we obtained from the threshold parameter below. Countries with low thresholds indicate countries that are in the late stages of the epidemic. As can be seen countries in the early stages of the epidemic are the ones with the blue colour scale in Figure 28. We talked about the World Health Organization preparing emergency action planning for these country groups. However, it seems that in countries where the epidemic is seen to be under control before these countries, it may be necessary to impose flight restrictions on these country groups. In addition, it seems that developed countries such as Sweden, which support herd immunity, and Pakistan, Afghanistan and some Turkic Republics, which have not completed their technological and institutional evolution, will undergo a problematic epidemic in the Asian region. It is seen that WHO and the countries of the region should plan emergency action in these regions; otherwise the second wave of epidemic cannot be prevented.
Threshold of the Countries
Figure 29. Treshold of the Countries: Starting day comparison
As mentioned above, the prediction of the threshold day with the LSTT model also shows which country started the process early. As can be seen from the world map, China and South Korea appear in the dark red colour as the earliest countries to start the process. The threshold values obtained are the lowest in the range compared to other countries. Again, it is understood that some of Africa, Middle East and Asia mentioned above are at the very beginning of the process as they close to the blue colour scale. As we mentioned above, these regions compared to other regions do not seem to be able to resolve the epidemic problem in a short time. As long as the convergence of the predicted transition speed parameter prolongs, the probability of the threshold parameter going towards red is not possible in the short term.
Potential Cases at Peak day
Figure 30. Potential Cases at the Peak day
While the map is being prepared, the numbers of the United States are standardized to the beginning of the colour spectrum so that other country comparisons look better. The blue spectrum indicates that the number of cases will be high, while red indicates that the numbers will be low. As we already mentioned the effects of the epidemic are early or uncontrollable in certain countries of Africa, the Middle East and Asia and this makes the selection of red in spectrum is difficult indicating the danger. As can be seen in the countries on yellow scale and above, these are the developed and developing ones with high population density in the Northern hemisphere. From the maps above, it will be seen that the increase in the number of infected cases of countries shown in this red colour in certain countries of Africa, Middle East and Asia will be too high if the data are available. Besides, Brazil is another remarkable example in the southern hemisphere country. While it was expected that the epidemic will not be spread due to the temperature in the Southern hemisphere compared to the Northern hemisphere, serious number of cases has already been reached in Brazil. It is obvious that increases will be expected in the coming summer period, primarily in the Middle East and other southern half countries, especially in the southern parts of Africa. With the arrival of summer, Asian countries and other Northern hemisphere countries, which have difficulty in control in the early stages of the epidemic, will have relative advantages. In this sense, if the epidemic can be taken under control in the summer, it can be said that it is beneficial to increase the isolation with the Southern hemisphere. Countries with a relatively low population density in the northern hemisphere seem lucky in terms of their number of infected cases. It can be said that these countries can enter the normalization process in the summer months. Finally, we will reflect the variance parameter estimates obtained from the LSTT model to the map.
Variance of the Countries LSTT estimate
Figure 31. Variance of the LSTT model estimated by countries
The variance variable obtained by countries’ LSTT model estimation show the countries which started the epidemic process early compared to other countries and the countries in the late period of the epidemic. In this sense, this map shows why these countries are mostly empirically examined. Including China, South Korea, Iran, Italy, Spain, United States, United Kingdom, Turkey, Germany and France to the model showed that whether our proposed model worked correctly or not. If we look at other maps, the model performed very well and produced the necessary information in order to stop the outbreaks in the early period.
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22/03/2020 Son Durum
22/03/2020 Son Durum