Countries controlling Covid-19: Headed for a Coronavirus recovery or a second wave?

It is crucial for economies and companies to recover from the first wave of the Coronavirus and to prevent a second wave. In this article, we discuss the impact of the first wave of the Coronavirus and use Data Science analysis to derive a complete Coronavirus recovery ranking. It shows how well a country controlling Covid-19 and how far away a second wave might be. We then interpret the data for Coronavirus recovery to find out what actions the leading countries took to control Covid-19.

The economy needs to recover from the consequence of Covid-19 response

Governments worldwide enforced nationwide lockdowns to flatten the curve. In other words, to buy more time to respond to the pandemic using limited medical capacity (as in healthcare staff, personal protective equipment, test kits, hospital beds, ventilators, hospital space, and so on).

While requiring people to stay at home has been effective in minimising the risk of a health apocalypse happening, the social distancing strategy has forced governments to enforce travel restrictions and the closure of ‘non-essential’ services, industries and events including cinemas, tourism, film shoots, nightclubs, concerts, festivals, arcades, sports, religious venues, farmers’ markets, schools, colleges and most offices.

Almost everyone, whose workplaces and educational institutions have closed during the lockdown, had to bring their daily activities online while at home. While some were able to work or attend online classes using their devices, others were not as lucky due to retrenchment and the shutting down of businesses that couldn’t cope with the lockdown conditions.

And because companies have to minimise costs due to lower business activity, they’re also delaying their recruitment drives, so job seekers have to wait longer to get hired or to even get shortlisted.

Consequently, lacking a source of income will result in lower levels of consumption and spending because they’re trying to save money and spread whatever savings they have over a longer period of time. Even stimulus packages are not enough to avoid a recession. The World Bank’s Global Economic Prospects of June 2020 estimates a 5.2% contraction in global GDP this year.

When the Covid-19 is eradicated, more people will be able to earn a living and industries affected by this pandemic can resume operations. The economy will have a chance to get back up after a fall.

Nobody wants a second wave

Another reason for controlling Covid-19 is to avoid a second wave. A second wave would mean a second lockdown. And that would mean a repeat or extension of the economic problems that happened in the first wave (as mentioned above). In this scenario, global growth could shrink by almost 8% in 2020.

And of course, people really miss having fun, right? Well, the impact of Covid-19 goes beyond a receding economy and the lack of out-of-home entertainment. The obvious victims of Covid-19 are those who tested positive for the Coronavirus and the people around them. At the time of writing, a total of over 13.1 million people around the world have tested positive, of which 7.23 million have recovered while 572,411 have passed away.

Another health impact of this pandemic is the disruption of prevention and treatment services of non-communicable diseases like diabetes, hypertension, cancer and cardiovascular diseases. A survey by the World Health Organisation (WHO) found that such health services have been partially or completely disrupted in many countries mainly because most medical staff have been reassigned to test and treat Covid-19 patients.

Not to forget, this pandemic has also lead to negative mental health outcomes, not only due to social isolation, but also job loss and income insecurity, worries about physical health, and burnout of frontline workers.

None of us would want to experience these issues again, do we? Let’s analyse the data to see which countries are more likely to escape a second Coronavirus wave and return to normalcy.

Using control scoring to rate how well countries are doing

In order to determine which countries are doing a good job in controlling Covid-19, we use Data Science and calculate a control score to rate each country’s performance. The formula to compute a control score rating for each country is:

Control Score = activepercent × normalisedStability ÷ activeToPopulation1000

As we can see from the formula of the control score, the variables are activepercent, normalisedStability and activeToPopulation1000.

Active percent

active cases = Total Infected – Cured – Deaths

activepercent = current active cases ÷ maximum number of active cases

• The activepercent shows the number of current active cases compared to the highest number of active cases ever.
• Active cases exclude those who have recovered and the victims who have passed away.

Normalised stability

normalisedStability = log [(activepercent 28 days ago) – (current activepercent)]

• Normalised stability shows how stable the changes in the number of cases are. A higher normalised stability figure (which is absolute) shows that the changes are more stable.
• A trend of 28 days was used because measuring over 14 days does not show enough change in some countries. However, there are other countries in the data set where the changes are huge.
• Normalisation of data is used when there are extremely large changes in values over time in certain countries, and hence, the changes need to be reorganised in a way that they can all be analysed more easily.
• Based on the data available, using logarithms is a suitable method for normalising data.

Active to Population1000

activeToPopulation1000 = current active cases ÷ 1000 of the population

• The active to population1000 figure reflects the infection risk. That is, the risk of each person in every 1000 people in a country getting infected.
• 1000 is used to standardise the population size. Comparing the number of active cases to a million or billion people will result in a very small number.

Control Score

Control Score = activepercent × normalisedStability ÷ activeToPopulation1000

• The control score shows the control of cases with respect to infection risk (again, infection risk is the active cases per population).
• The control score has a positive relationship with activepercent and normalised stability, and a negative relationship with infection risk. That’s why activepercent and normalised stability are multiplied and then divided by the infection risk.

Voilà! A complete ranking of Coronavirus control

We measured the data in the following table on the 13th of June 2020. The figures might be updated at another time.

The highest control score indicates that the country is best at controlling Covid-19. At the time of writing, Vietnam got the trophy for scoring the highest with a control score of 19,549, while the rest of the top 10 were occupied by other Asian and African countries.

Cuba scored the highest in the Americas with a score of 577 at 12th place while Malta scored the highest in Europe with a score of 280 at 16th place. However, the highest in Oceania is… Australia, with a low score of 33 at 45th place.

If you want to see which countries scored the lowest and are likely to experience a second wave of infections, click on the Index column to rearrange the order of the table.

However, control scoring has its limitations

There are certain challenges that stand in the way of comparing the performance of different countries with complete certainty.

Some countries were not included in the ranking because they have small population sizes, nearly no cases or no reported recovery numbers, leading to skewed figures of cases growth trend. For example, Ireland has a small population of 4.9 million people and reported a total of 25,670 cases. So it would look as if Ireland is doing badly although the number of cases have dropped significantly since May.

Another possible limitation that could affect the control scores is the selective testing of symptomatic people, which may have influenced the daily reports of cases. This means that people who display the symptoms of Covid-19 or are likely to be exposed to the Coronavirus have been tested, due to the scarcity of testing kits and medical capacity, instead of a random testing method or testing the whole country.

Examples of groups of people with a higher risk of exposure are the homeless and the foreign blue-collar workers living in cramped spaces. Their circumstances didn’t allow them to take the necessary precautions to prevent transmission. Meanwhile, people who stayed at home were less likely to show up at a testing facility, so the asymptomatic cases were probably not taken into account.

Nevertheless, we can learn something from the high ranking countries

There may be imperfections in data collection and control score computation but the control scores still give us a rough idea of how well (or not well) the countries are doing.

Over the past few months, we’ve seen some of the high ranking countries being praised for their efforts in handling the pandemic situation. They implemented some strategies that seem similar to one another. Here’s a summary of the steps taken:

1. They quickly cancelled outgoing flights, closed the borders, implemented health checks at airports and quarantined everyone flying into these countries upon hearing initial reports of infections in China.
2. Contact tracing has been conducted in an attempt to break the chain of transmission. Anyone suspected of exposure to Covid-19 would have to report themselves through the respective health ministry’s online reporting system.
3. Strict lockdown conditions were enacted to reduce exposure to Covid-19 and make social distancing, contact tracing and testing much easier to handle.
4. Awareness campaigns were held to communicate the seriousness of the Coronavirus and the importance of measures like social distancing and handwashing to the public.
5. They were quick in restocking their test kits to enable more tests to be done.

To avoid undoing every effort put into controlling the virus, we should continue taking the necessary measures. We know that some governments are starting to allow people to go out (equipped with masks and hand sanitisers) in light of a Coronavirus recovery.

But the loosening of movement restrictions doesn’t mean that the Covid-19 has been defeated. Recovery doesn’t mean recovered, so continue the social distancing, handwashing and public mask-wearing, okay?

Summary