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Summary
Background
Population-based data on COVID-19 are essential for guiding policies. There are few such studies, particularly from low or middle-income countries. Brazil is currently a hotspot for COVID-19 globally. We aimed to investigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence by city and according to sex, age, ethnicity group, and socioeconomic status, and compare seroprevalence estimates with official statistics on deaths and cases.
Methods
In this repeated cross-sectional study, we did two seroprevalence surveys in 133 sentinel cities in all Brazilian states. We randomly selected households and randomly selected one individual from all household members. We excluded children younger than 1 year. Presence of antibodies against SARS-CoV-2 was assessed using a lateral flow point-of-care test, the WONDFO SARS-CoV-2 Antibody Test (Wondfo Biotech, Guangzhou, China), using two drops of blood from finger prick samples. This lateral-flow assay detects IgG and IgM isotypes that are specific to the SARS-CoV-2 receptor binding domain of the spike protein. Participants also answered short questionnaires on sociodemographic information (sex, age, education, ethnicity, household size, and household assets) and compliance with physical distancing measures.
Findings
We included 25 025 participants in the first survey (May 14–21) and 31 165 in the second (June 4–7). For the 83 (62%) cities with sample sizes of more than 200 participants in both surveys, the pooled seroprevalence increased from 1·9% (95% CI 1·7–2·1) to 3·1% (2·8–3·4). City-level prevalence ranged from 0% to 25·4% in both surveys. 11 (69%) of 16 cities with prevalence above 2·0% in the first survey were located in a stretch along a 2000 km of the Amazon river in the northern region. In the second survey, we found 34 cities with prevalence above 2·0%, which included the same 11 Amazon cities plus 14 from the northeast region, where prevalence was increasing rapidly. Prevalence levels were lower in the south and centre-west, and intermediate in the southeast, where the highest level was found in Rio de Janeiro (7·5% [4·2–12·2]). In the second survey, prevalence was similar in men and women, but an increased prevalence was observed in participants aged 20–59 years and those living in crowded conditions (4·4% [3·5–5·6] for those living with households with six or more people). Prevalence among Indigenous people was 6·4% (4·1–9·4) compared with 1·4% (1·2–1·7) among White people. Prevalence in the poorest socioeconomic quintile was 3·7% (3·2–4·3) compared with 1·7% (1·4–2·2) in the wealthiest quintile.
Interpretation
Antibody prevalence was highly heterogeneous by country region, with rapid initial escalation in Brazil’s north and northeast. Prevalence is strongly associated with Indigenous ancestry and low socioeconomic status. These population subgroups are unlikely to be protected if the policy response to the pandemic by the national government continues to downplay scientific evidence.
Funding
Brazilian Ministry of Health, Instituto Serrapilheira, Brazilian Collective Health Association, and the JBS Fazer o Bem Faz Bem.
Introduction
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few nationwide surveys are available.
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The first COVID-19 case in Brazil was reported on Feb 26, 2020, in the city of São Paulo, and as of Sept 4, approximately 125 000 deaths have been reported.
Three population-based antibody surveys done in the south and southeast regions of Brazil showed prevalence ranging from 0·05% to 2·1%.
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However, physical distancing policies vary widely across the country and the implementation of such policies depends primarily on city and state governments.
Testing is limited to patients with severe illnesses and evidence suggests that COVID-19 deaths are undercounted.
Thus, periodic, population-based data on the pandemic are urgently needed.
Evidence before this study
Brazil has become a global hotspot for the COVID-19 pandemic in terms of reported cases and deaths. We searched PubMed, Web of Science and Scielo for papers in any language, published from Jan 1, 2019 onwards. We used the search terms: ((“severe acute respiratory syndrome coronavirus 2”[All Fields] OR “severe acute respiratory syndrome coronavirus 2”[All Fields] OR “ncov”[All Fields] OR “2019-nCoV”[All Fields] OR “COVID-19”[All Fields] OR “SARS-CoV-2”[All Fields] AND (Brasil OR Brazil)). Globally, few nationwide population-based studies on the prevalence of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are available, and none from low-income or middle-income countries. Existing studies in Brazil have focused on the more developed parts of the country, represented by the southern and southeastern regions.
Added value of this study
We did two household surveys in the most populous cities in all 133 mesoregions of Brazil, covering 26 states and the Federal District. We included more than 25 000 participants in the period May 14–21 and over 32 000 in June 4–7. We documented an increase in prevalence during this time interval, with strong concentration in 11 cities along the Amazon River, where prevalence was as high as 25% in both surveys. In the second survey, rapid increases in prevalence were also observed in the northeast. High-prevalence areas are poorer and less well-served by health and other services than areas in the rest of the country are. Prevalence among Indígena (Indigenous) individuals was over four times higher than among Branco (White) people, and prevalence in the poorest socioeconomic quintile was over twice as high as in the richest quintile.
Implications of all the available evidence
The poorest areas of Brazil, particularly the Amazon River basin, were the first to present high prevalence of antibodies against SARS-CoV-2, by contrast with the initially low prevalence observed in the southern and centre-western regions. Our geographical-level and individual-level analyses showed remarkable inequality in the prevalence of infection, with poverty and Indígeno ethnicity driving the progression of the pandemic in the country. The controversial handling of the epidemic by the federal government is likely to have contributed to the rapid spread of COVID-19 in the country’s most susceptible populations.
We aimed to investigate antibody prevalence by city and according to sex, age, ethnicity group, and socioeconomic status, and compare seroprevalence estimates with official statistics on deaths and cases.
Methods
Study design and sampling
Figure 1Location of the 133 sentinel cities in Brazil
Figures shows cities with prevalence of 5% or higher for antibodies against SARS-CoV-2 in the second survey. SARS-CoV-2=severe acute respiratory syndrome coronavirus 2.
We selected 25 urban census tracts with probability proportionate to size in each sentinel city, and ten households at random in each tract, using maps and household listings made available by the Brazilian Institute of Geography and Statistics. One individual was randomly selected from a listing of all household members. Children younger than 1 year were excluded because parents or guardians were not likely to have consented to the collection of blood. If the selected individual did not provide a sample, another household member was randomly selected. If this person also refused, the interviewers moved on to the next household on the right, which was also selected in the case of absent residents.
Interviewers were tested on the day before fieldwork using the antibody test and only participated in the study if the result was negative, and were provided with personal protective equipment (aprons, gloves, surgical face masks, and shoe and hair covers) that were discarded as hospital waste after each interview. Ethics approval was obtained from the Brazilian’s National Ethics Committee (CAAE 30721520.7.1001.5313), with written informed consent from all participants or by parents for minors. Positive cases were reported to the municipal COVID-19 surveillance systems; participants agreed to the disclosure in the consent form.
Procedures
Specificity estimates were obtained with frozen sera and might have been underestimated.
In early April 2020, we did a household probability survey in nine cities in the state of Rio Grande do Sul,
when the pandemic was at an early stage in the state. Of 4188 participants we found only two (
Analyses using the same sensitivity level and a specificity of 99·0% are presented in the appendix (pp 1, 2).
Data collection
A smartphone app for data collection was used for listing household members, selecting one at random, recording answers to the questionnaire, photographing test results, and obtaining the geographic coordinates of each home. For quality control purposes, each interview was also voice recorded, and 10% of all recordings were listened to by a supervisor.
Participants answered short questionnaires on sociodemographic information (sex, age, education, ethnicity, household size, and household assets) and compliance with physical distancing measures. Fieldworkers used tablet computers to voice record the full interviews, register answers, and photograph the test results.
The official Brazilian classification of ethnicity recognises five groups: Branco (White), Pardo (Brown), Preto (Black), Amarelo (East Asian), and Indígena (Indigenous).
All positive or inconclusive tests were read by a second observer, as well as 20% of the negative tests. If a participant in a household had a positive result, all other household members were invited to be tested. Results from household members were not included in the analyses, except for results on family clustering.
Data analysis
We multiplied the corrected antibody prevalence in each city by the city’s population to obtain an estimate of the number of people infected, and used this number to calculate under-reporting of cases and infection-fatality rates.
With 250 individuals per city, the margin of error (1·96 standard errors) for estimating prevalence at the city level is 1·92 percentage points at 2% prevalence, 2·93 at 5%, and 4·12 at 10%. At the national level the margin of error is 0·15 percentage points at 2% prevalence, 0·24 at 5%, and 0·33 for a design effect of 1·18 derived from the study results.
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was used to account for the sampling design. Meta-regression was implemented using the “metafor” package.
Role of the funding source
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Results
We interviewed 25 025 individuals in the first survey in 132 cities. During the first survey, we could not do any interviews in Picos, in the northeast region, which was under lockdown. 250 individuals were tested in 46 cities, 200–249 in 44 cities, 100–199 in 14 cities, and 1–99 in 28. The sample fell short of the planned number because of lockdown measures imposed in several cities with restrictions to mobility for the interviewers, and because of poor coordination between the Ministry of Health and the city and state governments. These difficulties were compounded by the rapid spread of disinformation through social media characterising the interviewers as swindlers, or of even being part of a plot to spread the virus. Interviewers were arrested in 27 cities and in eight cities tests were destroyed by local police forces.
In the second survey we overcame some of these problems because of repeated contact with the city health and police authorities and local media before data collection. The research team was not allowed to enter one city that was under lockdown. 31 165 individuals were tested in 132 cities. 250 individuals were tested in 98 cities, 200–249 in 22 cities, 100–199 in 11 cities, and 1–99 in one city. Overall, 31 165 (93·7%) of the planned 33 250 tests were carried out.
We found 347 (1·39%) positive results in 24 995 individuals with valid test results in the first survey, and 746 (2·40%) in 31 128 in the second survey. The corrected prevalence estimates were 1·6% (95% CI 1·4–1·8) in the first survey and 2·8% (2·5–3·1) in the second.
The largest difference in city prevalence levels using the two methods was 1·1 percentage point.
Figure 2Comparison on antibody prevalence by survey
Figures shows 83 cities with at least 200 participants in both surveys. The solid line indicates the diagonal (equal prevalence in both surveys) and the dashed line shows the linear regression slope.
When a participant tested positive, other household members were also tested. 21·6% of positive participants had at least one other positive household member in the first survey, and 33·0% in the second survey.
We used the mean number of deaths on May 13, and June 3, before the two rounds of testing. We found a correlation between prevalence estimated by the survey and the number of reported deaths per population, with a correlation coefficient of 0·826 (pappendix p 23).
Figure 3Scatter diagram for survey-based seroprevalence versus reported cases and deaths per population
We calculated the ratio of estimated infections to reported cases in 83 cities with 200 or more tests in both surveys. Taken together, these cities reported 172 420 cases by May 23, compared with our estimate of 1 778 401 infected individuals. The ratio of estimated infections to reported cases was equal to 10·3.
TableSeroprevalence according to sociodemographic characteristics
Missing values represented 2·1% of the responses on ethnicity, and less than 0·1% for the remaining variables.
Discussion
This finding of high prevalence in a tropical region contradicts common wisdom that continents such as Africa might be protected against COVID-19 because of high ambient temperature.
Long boat trips—eg, 36 h from Manaus to Tefé—offer the possibility of intense contagion in overcrowded boats, where most passengers use hammocks for sleeping or resting on the decks. One study
showed an inverse association (Pearson’s r −0·78; p
Our analyses suggest that the excess risk of Indígena individuals is largely explained by geographical region, household size, and socioeconomic status. Nevertheless, the adjusted results do not negate the finding that Indígena people are at higher risk than people of other ethnicities are, if not for genetic reasons then because of Indígena people’s exposure to poverty and to crowded living conditions. Historically, mortality rates among Indígena peoples have been substantially higher than those in other ethnic groups,
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and Indígena populations were left behind when Brazil made rapid progress in health during the 1990s.
High seroprevalence, combined with comorbidity with metabolic and cardiovascular diseases that are also increasing rapidly among Indigenous Brazilians
will probably place those people at increased risk of death due to COVID-19.
Baqui and colleagues
reported that hospital case-fatality from COVID-19 was higher among individuals with Preto or mixed ethnicity, compared with Branco people. The number of Indígena participants in that study was not sufficient for analyses.
A 14% decline in positive results in the same participants was observed in the Spanish national surveys between the first to the third survey (approximately 40 days).
These findings might have important implications for the interpretation of seroprevalence studies, which are likely to underestimate true prevalence because previously positive individuals become negative over a short time. Longitudinal or repeated panel studies are required to confirm these findings.
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We found that young children displayed similar prevalence to that observed in older age groups in the first survey, but in the second survey prevalence was lower in those aged up to 19 years, compared with adults aged 20–59 years.
Our response rate of 53–54% is similar to that in the Spanish survey (60%) and higher than that achieved in national surveys in Iceland and Austria.
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We found that many families have been moving away from large cities to towns or rural areas since physical distancing was recommended. We could not collect information from household members who were either away at the time of visit or refused to participate.
Our sample had fewer children than was expected, which was probably due to children’s reluctance to undergo a finger prick when randomly selected within the household; also, infants were excluded from our sample. In terms of ethnicity, Branco people were under-represented in the sample compared with the national population, possibly because of low response rates in apartment buildings and gated communities, where many Branco people live.
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The test we used is one of the most precise lateral-flow tests.
We used two sets of sensitivity and specificity parameters for correction, and the largest prevalence difference between the two approaches was 1·1 percentage point. Additionally, the possibility of spectrum bias should be considered because sensitivity assessments are usually limited to samples from patients with severe disease and thus with higher antibody levels;
this limitation applies to all antibody tests.
Testing was restricted to individuals with severe symptoms during the early stages of the pandemic and contact tracing was virtually non-existent. Two consecutive health ministers were either dismissed or resigned in less than 1 month because of opposition to the president’s stance regarding physical distancing and the use of hydroxychloroquine to treat COVID-19, and since May 15, the country has not had a health minister. By contrast with the federal government, most state governors and city mayors enforced closure of schools, shops, and non-essential services, and recommended the use of face masks. Nevertheless, hospital services have been at the brink of collapse due to the high numbers of patients requiring intensive care. Several mayors and governors have relaxed physical distancing policies throughout the country, despite the persisting high incidence of new cases and deaths. The effect of these measures is still too early to assess, but further waves of serological surveys will allow monitoring of the progression of the pandemic and help assess the effectiveness of policy changes.
PCH, FPH, BLH, MFS, CJS, LPV, LCP, OAD, MNB, GDV, AMBM, FCB, AJDB, and CGV contributed to the conception and design of the work, to the acquisition, analysis, and interpretation of data, and the draft of the manuscript. NAN contributed to the acquisition of data. All authors have approved the submitted version.
We declare no competing interests.
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