Coronaviruses, which were discovered in the 1960s, are important human and animal pathogens that cause different diseases that can range from a cold to pneumonia. As of December 2019, six types of coronaviruses that could cause diseases in humans had been identified, including those that caused the two previous epidemic outbreaks: the severe acute respiratory syndrome (SARS) coronavirus, which first appeared in 2002, and the Middle East respiratory syndrome coronavirus (MERS-CoV), which was first identified in the Middle East in 2012.
In late December 2019, a new coronavirus was identified as the causal agent of a cluster of cases of pneumonia of unknown etiology in Wuhan, the capital of the Hubei province of China. In February 2020, the World Health Organization (WHO) named this new coronavirus as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the disease that causes it COVID-19, which stands for coronavirus disease 2019. The virus spread rapidly from Wuhan, initially causing an epidemic throughout China, and shortly after followed by a growing number of cases worldwide that eventually resulted in the current pandemic and health emergency. The WHO declared COVID-19 a pandemic on 20 January 2020.
As of March 25, 2022, COVID-19 was present in 220 countries and territories, with 488,049,014 confirmed cases and 6,121,794 deaths. In Spain, which in terms of population ranks sixth in Europe and thirty in the world, at this time 11,451,676 cases had been confirmed (ranking sixth in Europe, behind France, Germany, the United Kingdom, Italy and Russia, and 11th in the world) and 102,392 had been produced (ranking 8th in Europe, behind Russia, UK, Italy, France, Germany, Poland and Ukraine, and 17th in the world). In relative terms, there had been 24,677.63 cases per 100,000 inhabitants (36th in Europe and 49th in the world) and 218.43 deaths per 100,000 inhabitants (27th in Europe and 39th in the world). In Catalonia, COVID-19 affected 2,351,841 people (the first Spanish autonomous community by number of affected, followed by the community of Madrid with 1,631,877 people), with 102,392 deaths in Spain and 18,756 in Catalonia (again, the first community by number of deaths, followed by Madrid, with 17,848 deaths). In relative terms, the pandemic affected almost 25% of the Spanish population in 2022. This percentage is repeated in Madrid, being higher in Catalonia (just over 30%). Regarding the lethality of the pandemic, the highest figure occurred in Castilla La Mancha (with 1.5% vs. 0.9% in Spain as a whole), followed by Asturias (1.3% ), Aragón (1.2%), Castilla-León, Madrid (1.1%), the Basque Country (1.0%), La Rioja (1.0%), Extremadura (0.9%) and Andalusia ( 0.9%), while in the other communities the lethality was below the Spanish average. In Catalonia, for example, the lethality was 0.8%.
On March 23, 2022, the Ministry of Health of the Government of Spain published the document "Surveillance and control strategy against COVID-19 after the acute phase of the pandemic" in which it is argued that the high levels of immunity reached in the Spanish population determined a change in the epidemiology of COVID-19. This change affected the information system for the pandemic and, therefore, the updating of the data, since from that moment only confirmed cases were monitored in people with (medical) vulnerability factors or those associated with vulnerable areas and serious cases. This means that the time series of cases has been interrupted and therefore the data provided above is the most up-to-date.
Although COVID-19 causes very similar symptoms to those of the seasonal flu, it differs from said condition in several ways. Firstly, SARS-CoV-2 has a much higher transmissibility, with a basic reproduction number (R0) (number of cases directly generated by a single case) reaching between 2.2 and 2.68, whereas the R0 of the seasonal flu is equal to 1.3 and that of the H1N1 influenza A virus is equal to 1.5 (the SARS had an R0 of 2-3 and the MERS had an R0 below 1). Secondly, the incidence of infection by this virus is much lower in children. The mean age of patients with COVID‑19 is 47 years, whereas that of flu is 23.4 years (that of SARS was 39.9 and MERS was 50 years). Thirdly, the mean incubation period for SARS-CoV-2 is 4 days, with a range of 2-7 days, whereas the seasonal influenza virus has a mean incubation period of 2 days, with a range of 1-7 days (in SARS, the mean incubation period was 4.6 days, with a range of 2-14 days, and in MERS it was 5.2 days, with a range of 2-13 days). Finally, the mortality rate is also much higher for SARS-CoV-2 in all cases except for the MERS (1% for COVID-19 compared with 0.13% for the seasonal flu, 0.20% for H1N1 influenza, 0.10% for SARS, and between 20% and 40% for MERS), although the mortality rate of COVID-19 should be interpreted with caution, as there is a significant underreporting of cases.
Disease Epidemiology
Knowledge of other viral respiratory diseases suggests that SARS-CoV-2 transmission may be modulated by environmental factors that vary seasonally, such as temperature and humidity. In fact, many studies, both online and published in scientific journals undergoing a quality review process, have evaluated the environmental sensitivity of COVID-19. At least until June 2020, all of these studies hypothesized that the climatic conditions of regions entering into the summer period (higher temperatures and lower humidity) would reduce the rate of transmission of the virus. However, in a systematic review performed in July 2020, in which 42 articles published in scientific journals and 80 preprints (i.e., articles not yet reviewed and published online) were critically evaluated, it was concluded that the evidence collected thus far suggested that either the summer weather conditions (high temperature and low humidity) had no modulating effect on this virus or that this effect was weak. On the other hand, the second wave of the pandemic that started around mid-July and August 2020 and mainly occurred in Spain, but also in other European countries such as the United Kingdom, Italy, France, and Germany, contradicted the alleged temperature modulating effect on the transmission of the virus causing the disease.
However, as COVID-19 is a recent disease, much is still unknown about its epidemiology, transmission, treatment, etc., although it is evident that it has had a greater impact on population groups with fewer resources, as demonstrated by studies carried out in Madrid and Barcelona neighborhoods, where, in the former case, there were 8.37% more cases than in the rest of Madrid's neighborhoods, and, in the latter, there were 66% more cases in the poorer neighborhoods of Barcelona compared with the rest of the region. Likewise, the towns toward the south of Madrid and the Henares corridor, which are characterized by a lower per capita income, have a higher incidence of cases than those located toward the north and west, which have a higher per capita income. There is a clear need for studies considering the socioeconomic status to explain mortality and morbidity secondary to COVID-19.
Unfortunately, there are few studies that allow for evaluating inequalities within the Autonomous Regions themselves and at the small-area level, and those that do exist do not enable a full analysis of the relationship between COVID-19 and socioeconomic level, given that very different socioeconomic conditions are grouped together even in the same small area (e.g., the same neighborhood). We should be able to have access to data at the individual level in order to carry out studies that would allow us to confirm this relationship. Thus, with this in mind, I have been working on two projects lately:
First, the “Impact and Seroprevalence of the COVID-19 Disease (IMPSEROCOVID19, Impacto y Seroprevalencia de la enfermedad COVID-19)” project. In order to prepare and provide an effective public health response in the context of the current SARS-CoV‑2 pandemic, there is a need to offer specific, early, reliable, and timely results on the current situation in different affected populations. This is the rationale of our project, whose general objectives are, on the one hand, to determine the magnitude, characteristics, and evolution of the social, economic, and health impact of COVID-19, as well as the prevalence of its infection and, on the other hand, to identify the socioeconomic and environmental risk factors and the population dynamics involved in the propagation of the SARS-CoV-2 infection in space and time and its impact on mortality and morbidity. The study populations are both the general population and the vulnerable population; i.e. people living in economically disadvantaged areas and those with complex chronic conditions. To achieve these objectives, we propose a multidimensional, Open Science study with a Real World Data design, in which we have integrated data from multiple sources of information on the seroprevalence and characteristics of the study populations (physical and mental health, well-being, functional capacity, exposure to COVID-19, and socioeconomic information) obtained from longitudinal surveys, on clinical practice, on other characteristics of these populations extracted from population records, as well as on the distribution of certain socioeconomic, demographic, housing, climatic, or environmental factors in the areas of residence of these populations. The analyses will be carried out using advanced statistical, sampling, and automatic learning techniques. Our project will be very useful for conducting mass testing in a systematic, organized, and informed manner, as well as for managing further outbreaks of this epidemic and possible future pandemics.
Second, the “Seroprevalence and the Socioeconomic and Health Impact of COVID-19 on General and Vulnerable Populations” project, whose general purpose is to understand the magnitude, characteristics, and evolution of the impact of the COVID-19 disease on both the general population and the most vulnerable populations of Andalusia and Catalonia. The specific goals of this study are to identify the social, economic, and health impact that COVID-19 is having on the general population and the population living in disadvantaged areas; to analyze the impact of COVID-19 on the self-care of people with chronic diseases; to discern the geographical and temporal distribution of the epidemic (incidence, intensive care unit [ICU] admissions, recovered cases, and mortality) by provinces, municipalities, and basic health care areas of the Autonomous Regions of Catalonia and Andalusia; to identify the social and environmental characteristics of the areas of residence of people affected by COVID-19; and, finally, to analyze the association between the epidemic (incidence, ICU admissions, recovered cases, and mortality) and the socioeconomic and environmental determinants of the areas of residence.
More recently I am leading the project 'Socioeconomic and environmental inequalities in health and COVID-19'. The project is based on the fact that the COVID-19 pandemic, as well as the measures to combat it, have had important effects on health, in general, and on the mental health of subjects, in particular. These effects have been unequal between population groups defined by the axes of inequality: gender, age, socioeconomic conditions, as well as in the territory and throughout the pandemic period. On the other hand, it could have happened that the barriers to the use of telemedicine, forced by the pandemic situation, have increased these health inequalities. In our project we intend to evaluate the differential effects of COVID-19 on health inequalities and their determinants, between population groups, as well as their dynamics in space and time, and determine if the barriers to the use of telemedicine have increased them.