When it left the Chinese province of Hubei towards Europe and Asian neighbors – between December 2019 and January 2020 – the SARS-CoV-2 coronavirus found conditions particularly favorable to its spread in some regions of the globe.
After analyzing data from 126 countries, including Brazil, researchers from the universities of Campinas (Unicamp) and Barcelona identified a set of factors that would have favored the rapid spread of the virus in the initial phase of the epidemic, that is, before policies were adopted public to contain contagion.
According to the study, supported by FAPESP, among the factors that contributed to the higher initial growth rate of COVID-19 are: low temperature and, consequently, a population less exposed to the sun's ultraviolet rays and with a lower level of vitamin D in the blood; greater proportion of elderly people and, therefore, greater life expectancy; greater number of international tourists in the early days of the epidemic; early onset of the outbreak (countries where the disease arrived first took longer to take prevention measures); higher prevalence of lung cancer, cancer in general and COPD (chronic obstructive pulmonary disease); higher proportion of obese men; higher rate of urbanization, greater consumption of alcohol and tobacco; and greeting habits that involve physical contact, such as kissing, hugging or shaking hands.
“We chose as the starting point of our analysis the day on which each country registered the 30th case of COVID-19 and analyzed the following days [between 12 and 20 days, depending on the country]. The objective was to understand what happened in the phase in which the disease grew freely, almost exponentially”, explains to Agência FAPESP Giorgio Torrieri, professor at the Gleb Wataghin Institute of Physics (IFGW-Unicamp) and co-author of the article published on the medRxiv platform, not yet peer reviewed.
According to the researcher, the proposal was to apply statistical analyzes commonly used in the area of physics – including simple linear regression and the calculation of the coefficient of determination – to try to understand what happened at the beginning of the pandemic. The data used in the analyzes came from different sources – much of it from a public repository known as Our World in Data.
“The idea was to assess the following: if nothing was done to contain the disease, how quickly would the virus spread in different countries or different social groups? Do factors such as temperature, demographic density, urbanization and health conditions of the population influence the speed of contagion?
Reliable sources
Some studies suggest that the BCG vaccine against tuberculosis may have some protective effect in the case of COVID-19. The analyzes carried out by researchers from Unicamp and the University of Barcelona indicate the existence of a weak correlation between the two variables (rate of immunization against tuberculosis and rate of contagion by SARS-CoV-2). According to Torrieri, however, it is possible that the result was hampered by the lack of reliable data in countries where vaccination is not mandatory.
“When we exclude countries without vaccination data, the correlation becomes weak. But when we include these places in the analysis and assume that they have a low immunization rate, the correlation becomes stronger”, says the researcher.
For some of the factors analyzed – including the prevalence of diseases such as anemia, hepatitis B (in women) and hypertension – the researchers identified a negative correlation. In other words, in countries with a higher proportion of hypertensive people, for example, the initial contagion rate of SARS-CoV-2 was lower.
“We can imagine that in these places there is more cardiovascular disease and, therefore, lower life expectancy”, assesses Torrieri.
Among the factors analyzed that did not show a correlation with contagion (neither positive nor negative) are: number of inhabitants; prevalence of asthma; population density; vaccination coverage for polio, diphtheria, tetanus, whooping cough and hepatitis B; prevalence of diabetes; air pollution level; number of holidays; and proportion of rainy days. In the case of Gross Domestic Product (GDP) per capita, as Torrieri explained, the correlation was positive only in values above 5 thousand euros.
“GDP is related to the quality of public infrastructure. The higher a country's GDP per capita, the better its health and housing infrastructure, for example. But below 5 thousand euros it made no difference, probably because the infrastructure is of low quality”, says the researcher.
As the authors highlight in the text, several variables analyzed are correlated with each other and, therefore, are likely to have a common interpretation and it is not easy to separate them. “The correlation structure is quite rich and non-trivial, and we encourage interested readers to study the tables [in the article] in detail,” they state.
According to the researchers, some of the correlations highlighted are “obvious”, for example, between temperature, UV radiation and vitamin D level. “Others are accidental, historical and sociological. For example, habits such as alcohol consumption and smoking are correlated with climate variables. Similarly, the correlation between smoking and lung cancer is very high and probably contributes to the latter's correlation with climate. Historical reasons also explain the correlation between climate and GDP per capita”, say the researchers.
Although it is impossible for countries to change some of the variables studied, such as climate, life expectancy and the proportion of elderly people, for example, their influence on the spread of the disease must be taken into account in the formulation of public policies, helping to define strategies of testing and social isolation, they argue.
Other variables, according to the authors, can be controlled by governments: testing and isolation of international travelers; restriction of flights to regions most affected by the pandemic; promoting social distancing habits and campaigns aimed at reducing physical contact while the virus is spreading; and campaigns aimed at encouraging the population to take vitamin D supplements and reduce smoking and obesity.
“We also emphasize that some variables mentioned are useful to inspire and support research in the medical field, such as the correlation of contagion with lung cancer, obesity, low vitamin D levels and different blood types and type 1 diabetes. This definitely deserves further study in-depth, with patient data”, conclude the scientists.
Read the article "COVID-19 transmission risk factors".
