The spread of infection due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been ongoing worldwide since December 2019. In Brazil, the first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) was reported on February 26, 2020. The patient was a 61-year-old male resident of São Paulo city, who had returned from a visit to Lombardy (Italy) a few days previously.1 On March 13, 2020, the Brazilian Ministry of Health declared that community transmission had been established as an upsurge of COVID-19 cases had been observed in multiple sites in the country.2 By May 23, 2020, approximately 350,000 laboratory-confirmed COVID-19 cases and 22,000 deaths had been reported in Brazil.3

The municipality of São Paulo, located in the Southeastern region of Brazil, is highly urbanized, with a population of approximately 11.6 million and a high level of socioeconomic inequality. The city has been an epicenter of the pandemic in the country and as of May 26, 2020, it had registered 425 cumulative cases per 100,000 inhabitants, compared to the national figure of 163 cases per 100,000.3,4

Knowledge about the magnitude of the SARS-CoV-2 epidemic is essential for future planning activities, such as formulation of public policies and control programs. It also underpins communication to the general population about the need for preventive measures.5 The number of laboratory-confirmed cases of COVID-19 and deaths reported to health authorities have been used as indicators of the extent of the epidemic. However, such data have not reflected the actual infection status in São Paulo, or Brazil, due to extremely low testing capacity and the high frequency of asymptomatic and oligosymptomatic SARS-CoV-2 infections which remain undetected. As seroprevalence surveys measure the proportion of the general population who have been infected and have produced anti-SARS-CoV-2 antibodies, they are useful for evaluating the dimension of the epidemic and to track its dynamic over time. Not only they do assess and monitor the spread of the virus regionally, but they are of paramount importance in informing vaccination plans.5,6

This study aimed to estimate the prevalence of anti-SARS-CoV-2 antibodies in a representative sample of the general adult population living in the six most affected districts in São Paulo city in the early epidemic phase. The potential associations between SARS-CoV-2 seropositivity and sociodemographic characteristics and self-reported COVID-19 compatible symptoms in the past two weeks were investigated.

Table 1 shows weighted seroprevalence estimates and prevalence ratios by participant characteristics. The overall weighted seroprevalence for SARS-CoV- 2 was 6% (95%CI 3.9–8.3%), based on dual tests on the serum samples of 463 participants living in 299 households. Briefly, 46.6% were male, mean age 47.1 years (range 18-89), 66.5% self-reported as being white, and 48.8% had a university degree (16 years or more of schooling). In this sample, 46.6% of the 30 seropositive individuals did not report SARS-CoV-2 compatible symptoms in the preceding two weeks.

No significant differences in seroprevalence were observed between sexes or age groups. People who reported brown and black skin color showed a 2.7-fold increase in the prevalence of SARS-CoV-2 antibodies, compared to those with white skin (p = 0.007). Although participants who reported eight or fewer years of schooling had higher seroprevalence than those who had 16 years or more of education (10.4% vs 5.6%), this difference was not statistically significant.

The distribution of positive laboratory results by Maglumi IgG, Maglumi IgM, or Roche tests is shown on the Venn diagram in Fig. 1. Among the 30 seropositive participants, eight were both Maglumi and Roche reactive; one of the seven IgM positives was also IgG reactive. The combination of the two antibody tests enhanced the detection rate by 28%, from 4.7% using Maglumi only, to 6.0%, using Maglumi and Roche.

Fig. 1.

Concordance (overlap area) of anti-SARS-CoV-2 reactivity between Maglumi IgG, Maglumi IgM and Roche in all seropositive participants (n = 30). Maglumi IgM, Maglumi SARS-CoV-2 chemiluminescence assay Immunoglobulin M (IgM); Maglumi IgG, Maglumi SARS-CoV-2 chemiluminescence assay Immunoglobulin G (IgG); Roche, Elecsys® Anti-SARS-CoV-2 electrochemiluminescence assay total immunoglobulin (Ig).

(0.07MB).

Frequencies of self-reported symptoms during the two-week period before the study visit stratified by SARS-CoV-2 seroreactivity are shown in Table 2. Seropositive individuals were significantly more likely to have experienced symptoms such as fever, shortness of breath, fatigue, myalgia, ageusia, and anosmia than seronegative participants. The most frequently reported symptoms among seropositive participants were fatigue (33.1%), rhinorrhea (31.5%), myalgia (28.8%), and ageusia (26%). None of the participants reported previous diagnoses of infection.

This study estimated an overall weighted prevalence of antibodies against SARS- CoV-2 of 6% in a representative sample of residents of the six most affected districts in São Paulo city, in the initial phase of the pandemic, i.e., 10 weeks after the first case of COVID-19 was confirmed. Combining two tests, Maglumi and Roche, resulted in a 28% improvement in sensitivity, thus a more accurate seroprevalence estimate. Differences in the isotypes of antibodies, in the composition of viral antigens and in the technology may partially explain this finding.17,18

At the time of the current study, two other seroprevalence studies were performed in the city of São Paulo.19,20 and although there were differences in the methodolog, their estimates are similar to ours. One, based on an 826-convenience sample of blood donors and using the Abbott SARS-CoV-2 IgG chemiluminescence assay (Abbott, Chicago, USA) reported a weighted prevalence of 5.1% (95%CI 3.4–7.2%).19 The other was part of a nationwide population-based serosurvey and, in São Paulo, it was based on 212 participants. The authors found a seroprevalence of 3.3% (95%CI 1.3–6.7%) using a rapid capillary blood test (Wondfo Biotech One step COVID-19, Guangzhou, China).20 Their study probably underestimated the true SARS-CoV-2 seroprevalence due to use of lateral flow immunoassays that have lower sensitivity than fully automated assays such as those used in both our study and the blood donors’ study.17,21,22 Our estimate might reflect the upper limit of the SARS-CoV-2 seroprevalence in the city considering that we studied the districts with the highest number of cases and deaths at the time the pandemics started in São Paulo.

Few other studies in Brazil estimated the seroprevalence of SARS-CoV-2 in the general population based on household surveys or blood donors around the period of our data collection. In Espirito Santo, in the Southeast region, the estimate was 2.1% (95%CI 1.7–2.5%),23 in Rio Grande do Sul, in the South, 0.2% (95%CI 0.4–2.0),24 and in Manaus, in the North, 37.4% (95%CI 33–42%).19 These prevalence rates, as well as the results of our study, may not be easily compared because they represent distinct moments of the pandemic in specific locations. Moreover, the use of different laboratory tests, different characteristics of the populations, and different study designs might be responsible for the observed prevalence heterogeneity.

Also, in April and May 2020, seroprevalence population-based surveys were performed in several other countries. The seropositivity rates were 10.8% in Geneva (Switzerland),25 4.6% in Spain,26 14% in New York State (USA),27 and 0.9% in Iceland.28 A modeling study estimated that 4.4% of the French population had been infected as of May 2020.29 As discussed before, the heterogeneity in prevalence estimates may be explained by the substantial differences between studies in terms of laboratory testing methods and sampling strategies, making comparisons difficult. Additionally, countries and regions faced different stages of the epidemic at different times and seroprevalence estimates not only change over time, but also vary according to adherence to a reduction of social proximity, home quarantine, and to the overall behavior of the population.30,31

Besides assessing the magnitude of cumulative infections in the chosen areas of São Paulo city, we looked at possible associations between sociodemographic factors and SARS-CoV-2 seroreactivity. No difference in seroprevalence was found between male and female participants; likewise, several reports indicated that seroprevalence is not significantly associated with sex.30,31 Prevalence rates were similar amongst age groups, in line with findings reported in a meta-analysis study.31 The infection rate was lower among participants with white skin than those with black and brown skin color, as also found in the Brazilian nationwide survey20 and in other international studies.31 SARS-CoV-2 seroprevalence depends on isolation adherence, which in turn, varies according to multiple socioeconomic aspects such as employment, transportation, income, housing, population density, health, and education. Inequality and exposure to poverty are historically related to race and black and brown skin color in Brazil10 and the concept of poverty-related diseases might apply to COVID-19.32

Previous reports have linked SARS-CoV-2 infections with no or minor symptoms.33-35 In our study, 46.6% of seropositive individuals reported no symptoms during the two weeks before the study visit. In line with findings from other studies,20,26 several SARS-CoV-2 compatible symptoms such as anosmia, ageusia, fatigue, myalgia, shortness of breath, and fever were significantly associated with seropositivity. It is noteworthy that SARS-CoV-2 compatible clinical symptoms and signs of mild infections remain poorly documented in Brazil.

An accurate estimate of the number of infected people requires an accurate measure of both documented and undocumented infections. The strengths of the current research are that it is the first household population-based serosurvey in Brazil to assess the prevalence of anti-SARS-CoV-2 immunoglobulins based on two validated, fully automated sensitive tests, the Maglumi and Roche immunoassays. These tests, together with the probabilistic sampling design, provided a clear picture of the extent of human exposure to SARS-CoV-2 in the studied regions. Also, although we have only surveyed six districts in the city, the sample is truly representative of the adult general population and reflects the heterogeneity in susceptibility or exposure to infection across population groups.

Our study has some limitations. First, due to its cross-sectional design, causal associations cannot be established. Second, refusal bias may have been introduced as a result of non-response which occurred mainly due to non-cooperation by the managers of some residential blocks and residents’ unwillingness to donate blood. Third, we have not included children or young people under 18 years due to logistic restrictions. Fourth, the statistical power may have been insufficient to detect differences between subgroups, such as education level. Last, the generalizability of the results of this study is somewhat limited as we only included six districts in São Paulo city at the beginning of the pandemic in the region. However, we believe that these issues have not affected our findings significantly, considering that they may have led to underestimation and overestimation, counterbalancing their effects on the prevalence estimates.

In conclusion, this study represents the first assessment of SARS-CoV-2 seroprevalence in the city of São Paulo, providing a baseline estimate. The low prevalence of 6% indicated that the COVID-19 pandemic was in its early phase, meaning that most of the population was susceptible to infection. This is the initial study of a series of consecutive household population-based seroprevalence surveys of adults aged 18 years or older in the municipality of São Paulo. The ongoing surveys use a similar methodology and testing strategy, based on random selection of households each time. Monitoring the progress of the pandemic throughout the entire city is an essential strategy to inform transmission control decisions and to appraise and update the vaccination plan for São Paulo city.