Masking against COVID-19, yes or no?

Some governments are using the mandatory or voluntary use of masks for political gain, for there are many people who do not like them, and the rulers think that lifting the obligation can give them votes. Some people deny that masking does prevent contagion, despite the fact that the use of masks to prevent the transmission of a respiratory disease is common sense. Is there any scientific study that clarifies the situation?

Towards a reasonable use of COVID vaccines

There is a lot of controversy regarding the use of vaccines against COVID-19. Although they are very varied, the reactions to this problem can be classified into three large groups:

1.     Some (especially governments) are frankly in favor of everyone getting vaccinated.

2.     Others (usually specific individuals) openly oppose vaccination, either because they deny that the disease exists (deniers), or because they doubt the usefulness of vaccines, or because they consider them dangerous.

3.     A third group is in favor of the conscious and reasoned use of vaccines, but opposes compulsory vaccination, considering that such compulsion would be a violation of individual freedom and human rights.

How are we measuring the effects of the pandemia?

Politicians and the media are usually measuring the effects of the COVID-19 disease pandemic, caused by a coronavirus, by the number of positive cases detected, either the day before, or in the previous 14 days (number of cases per 100,000).

I believe that this is a mistake, as it makes it very difficult to make comparisons along the evolution of the pandemic, for the number of positive cases detected clearly depends on the number of tests carried out (the more tests, more positive cases will be detected), and since the number of tests carried out varies constantly, the data they provide cannot be compared.

COVID-19 vaccines

The four main vaccines against COVID-19 can be classified into the following groups:

a)      Astra Zeneca and Janssen: Adenoviruses genetically modified to produce a protein, a part of the coronavirus causing COVID-19. This protein should give rise to the manufacture of antibodies to fight it, which would also attack the virus if it is present. These vaccines can cause blood clots that can even lead to death.

b)      Pfizer and Moderna: A messenger RNA molecule that synthesizes a coronavirus protein. These vaccines can cause heart ailments, according to studies conducted in Israel and other countries.

Mathematics of the pandemic

The May issue of the Spanish magazine on popular science Investigación y Ciencia, associated to Scientific American, contains an article authored by Bartolo Luque, Fernando Ballesteros and Octavio Miramontes, in which they apply to the current pandemic a mathematical model that dates back over a century. This model describes the first phase of the pandemic, the exponential rise of the first part of the logistics curve that I referred to in a previous post in this blog, and makes it possible to compare the evolution of the disease in various countries, depending on the virus containment measures that have been taken in each of them. It could also serve to explain why Spain has become the country with the most cases in Europe and with the most deaths per 100,000 inhabitants in the world.

The evolution of the pandemic in Spain

Logistic curve

Using the data provided every day by the Spanish Ministry of Health, about the number of new cases affected by the pandemic each day, and the number of deaths, we have carried out the following analysis:

1. We have manipulated slightly the real data to take into account the weekend effect, pointed out by the minister, which consists in the fact that the figures for new cases for March 28, 29 and 30 are not faithful to the reality, because fewer cases are declared on the weekend (we are used to waiting until Monday to do it), and then, on Monday, all the missing cases get accumulated. As by then the curve had flattened, what we’ve done is replacing the data about new cases for those three days by the average of the three, thus redistributing the Monday excess between Saturday and Sunday. The following weekend, April 4, 5 and 6, we made the same correction. The attached figure represents the number of new cases for each day (red curve) and the number of deaths (green curve). The numbers in the abscissa of the figure represent days counted from the beginning of the data. Day 1 corresponds to March 3. Day 36 is April 7, the last day about which there were data when this post was published.

The heralded pandemic

SARS-CoV-2

The November 2005 issue of Scientific American published an article signed by W. Wayt Gibbs and Christine Soares titled Preparing for a Pandemic. The article had the following subtitle-summary:

One day a highly contagious and lethal strain of influenza will sweep across all humanity, claiming millions of lives. It may arrive in months or not for years--but the next pandemic is inevitable. Are we ready?

Fourteen years later, the pandemic is here, although the authors were mistaken in one detail: they thought it would be caused by the influenza virus, but it was actually a coronavirus. These viruses belong to two different families:

Productivity measures for the increase in life expectancy

In my previous post in this blog I spoke about the article entitled Are ideas getting harder to find? which can be downloaded from the Stanford University website. In this paper, the authors also analyze the increase in life expectancy in the USA and the effort necessary to achieve it, and reach the following results:

What are scientists researching about?

Plant research in space (NASA)

In previous posts I have mentioned some dangers faced by the future of science in the face of the growing obstacles suffered by basic research and the tendency of politicians to prioritize practical applications. The arguments I offered in those posts were qualitative. It is possible, however, to obtain real quantitative data, extracted from the journal Science News, which publishes a fairly complete summary of the results of research in all fields of science and technology. By analyzing 23,946 articles published during 30 years, I have obtained the following table, which shows the number of scientific news related to fourteen of the most researched topics in the fields of biology and medicine during that period of time. (More than half the research results belong to those two fields).

Is scientific research well done?

Tabby Cat
Oliver-Bonjoch, CC BY-SA 3.0

Sometimes, while reading items published by journals such as Science News, it looks like some research currently being carried out is platitudinous. Either it leads to the discovery of things everyone knows, or time and efforts are spent to investigate in fields that no one cares about. We know that many researchers are anxious to publish, and they must justify somewhat the funds they receive, but up to that point?

Let’s look at a very recent news (April 2019):

Cats recognize their name. A study suggests our feline friends can tell the familiar sound of their name from other words. A paragraph of this news adds: As for whether or not a cat understands what a name is, well, only the cat knows that.

Anyone who has had a cat (I had one half a century ago) knows that cats recognize their name. Was it necessary to do a research about this, probably spending public money, to discover something that everyone knows?