Italy as a case in point
Italy is now at a dire situation battling COVID-19, due to the continuous escalation in the number of confirmed cases and deaths. The first two isolated cases of COVID-19 related to Italy were detected as early as 31st January and 6th February. Despite being one of the first countries in the EU to suspend all flights to and from China, and having employed screening facilities at various locations, Italy reported of a clustered surge of COVID-19 positive cases in the area of Lombardy, approximately a month after China declared war against COVID-19, on 21st February. The surge expanded at a greater rate and in a matter of few days, clustered surges arising from other regions from Italy were also reported. Although, quarantine procedures were imposed on several municipalities, the rate of propagation could not be retarded.
The Figure – 1 witnesses to the fact that the remedial process followed by Italy did not yielded results similar to those of China, South Korea, or Japan. It is certain that the rate of recovery has stunted at a critical level compared to the rate of China. The graph presented in Figure – 2 shows the fluctuation of the percentage of recovery during the course of the first 31 days of the epidemic in respective countries (China: 22nd January, Italy: 21st February).
The opposing trends shown by the two countries have much to do with the ‘buffer’ that was discussed early. The important dates in each country that would attribute to the above point are marked on the Figure – 2. By the second day of the Chinese timeline, the authorities initiated the construction of the first makeshift hospital facility – Hoshenshan Hospital, to cater to the exponential increase of patients that was forecasted to take place. By the 13th day, the first phase of the Hoshenshan Hospital was complete and had started to admit patients until the completion was seen on the 17th day. During the 4 day period, the total number of active cases within Mainland China had risen from 18,677 to 31,393. Subsequently several other locations were designated to have field hospitals constructed. By the 23rd day, a total of 10 field hospitals were constructed to admit 5600 patients. Moreover, by the 37th day (not shown on the graph), a total of 16 field hospitals were operational with a total capacity of 13,000 beds. A workforce of 42,600 healthcare professionals including 19,000 specialists in intensive care was deployed to Hubei Province to accelerate the remedial process. This rapid infrastructure reinforcement associated with intricate stunts of strategy, forecasting, and manpower resulted in a sharp increase in the percentage of recovery.
Although the first 14 days in Italy were somewhat progressive over China, the situation shortly preceded into a stunted progress. On the 13th day in Italy, the total active cases stood at 2706 – only about one seventh of the cases recorded in China. The marker on the Italian timeline corresponds to when Italy showed the first signs in reaching the capacity threshold in the hospitals during the battle. Despite the number of active cases in Italy were significantly less compared to China, the increasing influx of new patients had started to ‘fill the buffer’ in hospitals. This led the remedial process to decelerate, instigating an acceleration of mortality due to patients having left untreated. Also, Italy reported an increased number of deaths among healthcare officials from contracting COVID-19. Casualties among healthcare personnel battling the disease and inadequate health infrastructure expansions would directly cause the disease to steer towards an uncontrolled state and to cause high casualty rates. The collapse in the remedial process resulted in a mortality rate in Italy around 10% in contrast with the world average of about 3%. As apparent from the Figure – 3, the percentage of mortality in Mainland China during the pandemic had not fluctuated drastically and remained at a steady level between 2.0% ~ 4.0% at a Standard Deviation of 0.70.
Common Trends in Europe
Immediately after, if not concurrently, Wuhan in China was hit by the Coronavirus, whole Europe began to experience rapidly increasing cases of COVID-19. Italy is still the most affected country in Europe characterized by catastrophe. However, by considering the current statistics, it can be figured out that the proliferation is decreasing. A semi-logarithmic representation of the cumulative active cases on a chronological timeline indicated in Figure – 4 shows an apparent decrease of the gradient. The number of cases is assigned on a logarithmic scale of base 2. This would give an intuitive idea about the doubling time as it is possible to obtain an average doubling time value by approximately measuring the difference of days between two adjacent levels on the vertical axis. It could be seen that Italy is currently reaching a plateau in the number of active cases. In an ideal situation, this indicates that the disease has finished spreading across majority of the population amidst controlling and preventive methods. Due to external factors, exponential growths do not tend to continue indefinitely in real life situations. On a brief standpoint, despite the very high casualties being reported it can be concluded that Italy may have reached the peak of the epidemic. External factors that have stopped the disease in reaching the entire Italian population could be the effectiveness of the remediation program, development of herd immunity among the communities that recorded clustered outbreaks, high immunity individuals that were able to fight off the disease, and adequate social distancing measures.
Several other European countries can be opted for conducting a comparative study by means of disease propagation. According to Figure – 4, Switzerland shows promising results of the remediation process carried out by the authorities. While other countries have not yet reached a definite plateau on their respective curves even with active case counts in the order of approximately 60,000 or above, Switzerland has been able to limit the peak at about 16,000; a 1/4th compared to the other countries, and has already reached the declining phase in active cases. It can be concluded that Switzerland has so far been successful in controlling the disease compared to the other countries of Europe. Germany has recorded a decline in active cases since 7th April. This indicates that Germany has also passed the peak of the epidemic. However, to avoid prejudice Germany has to confirm that it has reached the peak of the curve not due to inconsistency in data collection or subjective changes in clinical diagnosis that define a patient as recovered. The situation of Spain is somewhat similar to that of Italy. Spain has shown a less adverse increase compared to that of Italy in the beginning of the outbreak. But the controlling has not been adequate to curtail the active cases and thus the gap between two respective curves has been closed rapidly along the timeline. Despite the numbers of recoveries between Spain and Italy show a significant difference in Spain’s favor, Italy has been able to control the spread of the disease efficiently than Spain, which is why Spain now has a greater number of confirmed cases over Italy. The major surge of active cases in Spain took place six days after Italy reported its major surge, and the first death was reported 12 days after Italy reported its first COVID-19 related death. Although Spain had given a head-start, the numbers surpassed those of Italy in a rapid succession. It should also be noted that Italy has a larger population of 60.36 million (2019) compared to 46.95 million of Spain (2019). In proportion, 0.24% and 0.33% of the total populations of Italy and Spain have respectively contracted COVID-19. It can be concluded that there is a significant amount of risk still present in the Spanish scenario.
Switzerland has gradually implemented strict measures to hinder the growth of the disease within the country. Within three days after the first case was reported the Swiss government imposed restrictions in mass gatherings starting from the 28th February. By 16th March more stringent social distancing regulations were implemented and schools were closed to contain the spread of the disease. And by 26th March at stage of total confirmed cases of about 12,000 a complete lockdown status, closing all non-essential operations including those of the private sector, was imposed. These measures have exerted a positive effect in containing the disease as it is apparent that the gradient of the active cases curve has decreased rapidly and far more effectively in comparison to other countries. Although the United Kingdom imposed a lockdown status two days before Switzerland did and with only about 8000 cases reported, the measures that were taken until the lockdown have failed to generate the desired controlling effect similar to that of Switzerland. The measures in the United Kingdom have been implemented on a delayed onset and the severity of the regulations was raised rather in a reactive manner instead of a proactive manner to prevent the spread of the disease. France despite having implemented a lockdown status as early as by 16th March, only around 6600 individuals were tested positive for COVID-19. It is certain that a lockdown would only be best effective when a follow up of preventive measures are taken.
The current situation of the COVID-19 pandemic in Europe is a reflection of how proactive and reactive measures could take turns of spread of the disease. Nevertheless, the situation of Europe has started to make slow progress. The distribution of the doubling times of the European continent has started to increase at a promising rate. These positive trends are shown in the Figure – 5. However, there is a considerable threat present in kick-starting second wave in all the countries that might revert the doubling time to a rapid level again. Persistent preventive measures should be taken to avert possible second waves. It is apparent that the doubling times are inconsistent across countries and thus only a graph that presents chronological progress of doubling times in all countries is suitable to illustrate the results.
To derive a quantitative result and a less complex graph, the daily ranges and the median values can be used. Although the data of the Figure – 5 are not different from those of the Figure – 6, the median doubling time presented in it provides a much clear image of the direction of the disease. The median value was opted over the mean as some doubling values were identified as outliers due to inconsistencies in data collection etc. While this representation does not signify the behavior of individual countries, it shows the collective trend of the doubling times in the continent. An intuitive measurement can be derived as an approximate method to observe the growth of the confirmed cases. The value of the doubling time tends to change over time due to external factors. A positive change occurs when the value moves away from zero. The rapidity of the doubling time moving away or towards zero over time shows how slow or fast the disease growth is. The behavior of the doubling time of cumulative confirmed cases over a 14-day period can be used as an adequate interval to observe a noticeable change. It can be assumed that the change is occurred in a linear manner. A gradient of a linear graph and the direction shows how fast the doubling time is changing over time at a distinct direction. Due to various external factors, this change may not tend to follow a linear path, thus it is necessary to measure how ‘straight’ the overall change is. The linear correlation coefficient (r) which spans from -1 to +1 of which the magnitude indicates how well the original data is scattered to either side of the hypothetical straight line (best fitting line) that fits best to the distribution of the original data. The plus-minus sign indicates the direction where the distribution is progressing; in this scenario a positive sign indicates that the change in doubling time shows an increase over time. In short, the linear correlation coefficient indicates how strongly a distribution would align with a straight line and at which direction. In casual terms, it indicates how much one should believe when a set of data is said to follow a linear path. For an instance, a line with an r = +0.85 would mean that the original data would align in a highly linear manner with a positive gradient with the best fitting line, and a line with r = -0.05 would mean that the original data fits very weakly with the best fitting line.
The Figure – 7 shows the magnitude of change in doubling time in confirmed cases and its direction over the last 14 days until 9th April. It is certain that the majority of the countries shows a positive change in doubling time at a moderate to high linear manner. Three extremely high risk countries identified (Belarus, San Marino and Malta) show a negative magnitude in the change of doubling time. Montenegro and Finland show smaller gradients but at a weaker correlation value. An abrupt spike has been recorded in the doubling times of Montenegro which explains the weak correlation. When the time interval is adjusted to account for the last 10 days, Montenegro shows a positive change of 2.79 at a correlation of 0.75. However, the situation in Finland is that the distribution shows vast fluctuations over a very small net increase in the magnitude over time. It can be approximated that the majority of European countries is showing promising signs by means of increasing the doubling time in confirmed cases, despite many countries having recorded larger numbers of deaths. The proactive measures taken in a gradual and a timely manner have yet again shown to have a positive effect in hindering the spread of the disease, increasing the rate of recovery, and reducing the number of deaths caused by a disease outbreak.