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These scenarios show what a second wave of COVID-19 could look like



With the new corona virus spreading rapidly in February and March 2020, many governments introduced strict blocking measures. Through massive public efforts, these countries have managed to slow the pandemic.

Countries like Slovenia and New Zealand have combined different approaches to public health and eradicated the virus within their borders. Other countries, including the UK, have made significant progress in containing the spread of the disease.

However, the ban has resulted in significant economic and social losses in countries where strict social distance measures have been applied. Both governments and the public are now interested in lifting the restrictions and returning to normal life.

With the relaxation of the blocking rules, warnings of a possible recurrence of COVID-1

9 cases are issued – a so-called second wave.

The second wave of the Spanish flu pandemic in 1918-20 was particularly devastating, as was the second wave of the H1N1 epidemic in 2009-10. So what can be done to avoid a second wave of COVID-19?

(Public domain)(Public domain)

Susceptible and infected hosts and successful transmission are required for the virus to spread. These factors are conveniently identified by the reproductive number R, the average number of new cases caused by an infected person.

A value of R above one means that the number of cases increases as they decrease below one. Coronavirus R was estimated to be two to four prior to blocking.

Countries such as China, South Korea, New Zealand, Great Britain and most European countries have now reduced this value to less than one. In other countries such as Sweden or Russia, the value of R remains close to or above one, reflecting the increase in the number of cases.

The relationship between population behavior and the value of R is complicated, but we can still use this concept to illustrate how the second wave might appear.

You can find simulation details at https://statisticinsignificant.uk/2nd-wave/. Adam KleczkowskiYou can find simulation details here. (Adam Kleczkowski)

Over: Single wave epidemic. The upper diagram shows the time dependency of the model reproduction number. The lower diagram shows the predicted number of cases. The initial value of R is 2.7 and falls to 0.8 with the block.

As long as there are vulnerable and infected people in the population, the virus can spread. There is evidence that the first wave of the epidemic resulted in limited immunity that was far below herd immunity.

There are also pockets of a population in which the virus not only survives but spreads further. Transfer to nursing homes is now a large percentage of cases in many countries.

As the lockdown measures relax, people begin to interact more with each other. This can lead to increased values ​​of R. However, it is important that the value of R be kept below or equal to one, as shown in the following figure.

More details here. (Adam Kleczkowski)More details here. (Adam Kleczkowski)

Over: Single wave epidemic with rebound due to lockdown relaxation. The initial value of R (upper diagram) is 2.7 and drops to 0.8 with the lock, but drops back to 1 when the lock measures are relaxed.

But even a relatively modest change from R to 1.2 would lead to a big breakout causing the second wave, which shows how important it is to get the control measures right.

More details here. (Adam Kleczkowski)More details here. (Adam Kleczkowski)

Over: Second wave. The initial value of R (upper diagram) is 2.7 and drops to 0.8 with the lock, but drops back to 1.2 when the lock measures are relaxed.

The response to the second wave requires recurrent blocking measures, as shown below. Although society has followed the restrictions remarkably well so far, fatigue could make it more difficult to re-enforce such strict guidelines.

More details here. (Adam Kleczkowski)More details here. (Adam Kleczkowski)

Over: A scenario with multiple outbreaks and blackout periods. The value of R (upper graph) is periodically increased to 1.2 when the lock is released and then falls back to 0.8 when it is re-imposed.

The epidemic could continue into fall and winter if seasonal flu could be common. While it appears that the SARS-CoV-2 virus is not greatly affected by the weather, the health care system could be overwhelmed if COVID-19 and the flu coincided.

On the positive side, preventive measures against the SARS-CoV-2 virus (such as masks and hand washing) could reduce the spread of the flu virus.

Eventually, the virus could mutate, which would result in a more infectious strain. Such a mutation could have made the second medium wave of Spanish flu particularly severe.

If something similar happened to the SARS-CoV-2 virus, the resulting epidemic would dwarf the current outbreak, even if the new R-value was only four, compared to 10-12 for mumps or 12-18 for Measles. Mumps and measles cannot be spread widely only by vaccination.

More details here. (Adam Kleczkowski)More details here. (Adam Kleczkowski)

Over: Great autumn wave. The value of R (upper diagram) is briefly increased to 4 in November. Note the changed number of cases compared to other diagrams.

In the near future, governments must carefully reconcile the needs of the economy and social life and suppress the spread of the virus. Testing, tracking, and containment, as well as local responses, are key elements of the strategy.

Epidemiological models and concepts like R can help determine where, how, when and for how long the government needs to intervene to prevent the second wave. The conversation

Adam Kleczkowski, Professor of Mathematics and Statistics, Strathclyde University.

This article is republished by The Conversation under a Creative Commons license. Read the original article.


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