Since the beginning of the COVID-19 pandemic, having updated data on how many people have been exposed to the virus SARS-CoV-2 has been key for policymakers and the population. Several databases from all over the globe are gathering and producing daily estimates of positive cases, hospitalizations, and deaths. Yet, data across countries are not necessarily comparable. For instance, Mexico relies on a sentinel surveillance system to follow up on Covid-19 cases. The system only collects information on symptomatic cases that fulfill an epidemiological definition, tracking all hospitalized and a fraction of ambulatory patients. Assuming definitions and coverage remain the same, this system allows to follow up trends over time, but it will not capture all Covid-19 cases. Cases with few or no symptoms, or who did not seek or get medical attention will not be counted by the system, leading to an underestimation of cases in the country. If this data is then compared to a country with a different testing system the conclusions could be biased, as data collection is not comparable.
Representative seroprevalence studies are a solution to this problem, as they can provide a fair comparison across populations. There are two key components to seroprevalence studies: 1) a complex random sample of the population to produce estimates that adequately represent a country’s situation, and 2) antibody detection to reflect exposure to the virus independently of symptoms, health system access, or other variables. Well-designed and conducted seroprevalence studies can then be used to compare the experience of infection across populations. In this paper, we did a seroprevalence study with a nationally representative sample of the Mexican population from August to November 2020, after the first wave of COVID-19 in Mexico. We found that one out of four people (25% of the population) were positive for SARS-CoV-2 antibodies. This means that 31 million people in Mexico had been infected by November 2020. This estimation occurred before vaccination, so all the antibodies were produced by natural infection.
Another question that is often asked is if the COVID-19 infection affected everyone the same. The answer in our study is no. We found that some groups in the population experienced higher rates of infection, particularly:
- People with lower educational attainment
- People in the lowest socioeconomic status
- People in the urban and metropolitan areas
- Working population
In summary, after the first COVID-19 wave in Mexico, the pandemic affected a quarter of the population, particularly workers, people with low education and socioeconomic status, and living in urban and metropolitan areas. Mexico is a highly unequal country and health inequalities were reflected in the infection rates experienced by the population. Also, a large proportion of people in Mexico live in cities, where high population density, poor living, and working conditions may have facilitated disease transmission. The pandemic has also been different across countries. In comparison with countries that conducted a seroprevalence study in a similar period, Mexico presented more infections than cities in the United States, but less than cities in Colombia. This helps to understand the extent of infections and provides comparable information to help policymakers set interventions according to each country's context.
Seroprevalence of SARS-CoV-2 in Mexico and other countries