We examined the asymptomatic rates of SARS-CoV-2 infection during the Delta and Omicron waves in the city of São Paulo. Nasopharyngeal swabs were collected at strategic points of the city (open-air markets, bus terminals, airports) for SARS-CoV-2 RNA testing. Applying the questionnaire, the symptomatic individuals were excluded, and only asymptomatic cases were analyzed. During the Delta wave, a total of 4315 samples were collected, whereas 2372 samples were collected during the first Omicron wave. The incidence of the asymptomatic SARS-CoV-2 infection was 0.6% during the Delta wave and 0.8% during the Omicron wave. No statistical differences were found in the threshold amplification cycle. However, there was a statistical difference observed in the sublineage distribution between asymptomatic and symptomatic individuals. Our study determined the incidence of asymptomatic infection by monitoring individuals who remained symptom-free, thereby providing a reliable evaluation of asymptomatic SARS-CoV-2 carriage. Our findings reveal a relatively low proportion of asymptomatic cases, which could be attributed to our rigorous monitoring protocol for the presence of clinical symptoms. Investigating asymptomatic infection rates is crucial to develop and implement effective disease control strategies.
Keywords: asymptomatic infection; SARS-CoV-2; epidemiology; molecular testing; genomic surveillance; Brazil
SARS-CoV-2 infection might take symptomatic or asymptomatic course. The symptomatic infection is presented as a diversity of symptoms ranging from mild to severe needing mechanical ventilation and supportive oxygen related to high lethality. Both forms of SARS-CoV-2 infection bring important information for the pandemic dynamics. One of the most important consequences of the asymptomatic SARS-CoV-2 carriage is that these individuals might act as an efficient source for viral dissemination. For that reason, the estimation of the asymptomatic rates of SARS-CoV-2 carriage has been crucial for the implementation of non-pharmaceutical measures to control the viral spread and mitigation of the pandemic [[
The city of São Paulo (SP) is the largest Brazilian and Latin American metropolis. This city was an important entry point for different SARS-CoV-2 variants of concern (VOC) during the pandemic [[
Therefore, the objective of this study was to evaluate the asymptomatic SARS-CoV-2 infection rate in the city of SP during two distinct pandemic waves (Delta and Omicron VOCs). The collection of samples was performed by specialized professionals at the most important hot spots of the city distributed across all regions of the city like airports, bus terminals, and open-air markets to evaluate the burden of the asymptomatic SARS-CoV-2 infection. Moreover, the differential of this study was that the positive individuals were followed for symptom evolution by regular phone calls. Thus, it was possible to estimate the likely-real rates of asymptomatic infection in the largest Brazilian city.
The flowchart of the activities of this study is presented in Figure 1A. The nasopharyngeal samples (NPS) collection was performed in two distinct time periods that coincided with the Delta and Omicron VOCs in the city of SP. The sample collection during the Delta wave was performed between 25 November and 17 December 2021, achieving 4315 collected samples from asymptomatic individuals (confidence level of 99% and power of 99.9%). The sample collection during the Omicron wave was conducted between 28 April and 13 May 2022, obtaining 2372 NPS (confidence level of 99% and power of 99.9%). Both sample collections were taken from important regions of the city with high people circulation (transport terminals and airports) and mass gatherings (open-air public markets) across all regions of the city. As shown in Figure 1B, the city was subdivided into macro-regions: (i) East region, the Municipal open-air market of São Miguel Paulista; (ii) South region: Congonhas national airport and Santo Amaro bus terminal; (iii) Central region: the Municipal Market of São Paulo and Brás (a famous spot for clothing trade); (iv) West region: Municipal Market of Pinheiros; and (v) North region: the Tietê bus terminal (which is the world's second-largest terminal of its kind). All positive individuals were contacted during their quarantine by health authorities to determine if they exhibited symptoms. The contact was performed by phone call or e-mail. Those individuals who were not accessible both ways were visited by employees of the São Paulo prefecture. The applied questionnaire included the following questions: (
Individuals with any clinical symptoms (fever, cough, sore throat, headache, shortness of breath, coryza, smell and taste disturbances, or diarrhea) were excluded from the study. Positive individuals were contacted again after the mandatory quarantine period to confirm their asymptomatic status, with a mean follow-up period of 10 days. For this study, we focused on individuals aged 18 years and above and did not include children.
The SARS-CoV-2 RNA testing and whole genome sequencing were performed using previously described protocols [[
We utilized the COVIDSeq kit (Illumina, San Diego, CA, USA) to sequence the complete genomes of SARS-CoV-2 following the manufacturer's protocol. The resulting reads were then assembled and assigned to a lineage as previously described [[
This study involved a statistical descriptive analysis of both quantitative and qualitative variables that characterized the incidence of SARS-CoV-2 positive rates in asymptomatic individuals during the first and second sample collections. To compare the PCR cycle thresholds (Cts) between symptomatic and asymptomatic individuals during the first and second sample collections, we employed the Kruskal–Wallis or Wilcoxon test, depending on the data distribution. In addition, we conducted proportion tests based on the age group of asymptomatic individuals during the first and second sample collections, as well as on the sex of the SARS-CoV-2 positive and negative individuals, the region of sample collection, the use of face masks, and the number of received vaccine doses. In order to compare the distribution of SARS-CoV-2 lineages between asymptomatic and symptomatic individuals during the first and second sample collections, we conducted a Fisher´s exact test.
- During the Delta VOC wave sampling, we were able to detect 25 asymptomatic cases out of 4315 collected samples (incidence 0.6%), and during the Omicron VOC wave, we detected 20 asymptomatic infections out of 2372 collected samples (incidence 0.8%). The proportion of symptomatic cases during the Delta wave was 46% (21 cases), and during the Omicron wave, it was 50% (20 cases).
- There was no statistically significant difference in the incidence of asymptomatic infection between the first and second sample collections. The predominant age range of asymptomatic individuals who tested positive for SARS-CoV-2 was between 21 and 59 years during the first sample collection and between 41 and 59 years during the second sample collection, with no statistically significant difference between both collections (p = 0.92). During the first sample collection, none of the asymptomatic individuals reported any comorbidities, but in the second collection, three positive individuals reported comorbidities (diabetes, hypertension, and hepatic disease, respectively) (18.75%). In both sample collections, the majority of the asymptomatically infected individuals were female, but without a statistically significant difference between samplings (56% and 55%, respectively, p = 0.95). The majority of the asymptomatic individuals in both sample collections reported complete SARS-CoV-2 vaccination (first and second dose), with no statistically significant difference between collections (88% and 90%, respectively, p = 0.39). In the first sample collection, a higher proportion (44%) of the positive participants were from the North region of the city of SP, whereas in the second sample collection, a higher proportion (25%) were from the East and South zones of the city of SP, but without a statistically significant difference between samplings (p = 0.22).
We evaluated the PCR Cts of the SARS-CoV-2 infection in asymptomatic individuals and the circulating sublineage. The evaluation of the mean Ct showed that there is no statistical difference between the symptomatic and asymptomatic SARS-CoV-2 individuals (Wilcoxon test p = 0.57, first collection = 27.4 + 5.8 and second collection 28.4 + 6.1). The same result was obtained within the groups of the symptomatic (Wilcoxon test p = 0.53, first collection = 26.9 + 5.8 and second collection 28.5 + 6.0) and the asymptomatic individuals (Wilcoxon test, p = 0.96, first collection = 28.0 = 5.9 and second collection = 28.2 + 6.4%).
In order to gain a more precise understanding of the circulating sublineages among asymptomatic individuals, we conducted sequencing and phylogenetic classification of obtained complete SARS-CoV-2 genomes from the two samplings. However, seven genomes were excluded from the analysis due to low genomic coverage and/or lack of follow-up information on the individuals. Therefore, we analyzed 23 complete genomes obtained during the Delta VOC wave and 15 obtained during the Omicron VOC wave. In general, the average coverage of these samples selected for phylogenetic analysis of the delta variant was 99.42%, whereas the average of the omicron variant was 97.67%. As shown in Figure 2A, during the Delta VOC wave, the most common sublineage infecting asymptomatic individuals was AY.99.2 (56.52%), followed by sublineages AY.43.1, AY.43.2, AY.34.1.1, AY.34, AY.43, and AY.43.7. This sublineage diversity was different compared to that obtained from symptomatic patients (the most represented sublineage was AY.34.1.1, followed by the sublineages AY.99.2 and AY.43), which contributed to shaping the Delta VOC in the SP city (Fisher´s exact test, p = 0.002501). During the second sampling, conducted during the Omicron VOC wave, the predominant lineage detected was BA.2 (80.0%), followed by sublineages BA.1.1 and BA.2.9.3, and the recombinant variant XAG (Figure 2A). The XAG identified in this study, when compared to 410 other globally isolated XAG genomes, harbors two unique mutations: A8302G and G25088T. The latter induces a non-synonymous mutation V1176F in the Spike protein, which exhibits a frequency of 0.99% among globally sequenced genomes (including all lineages collected from 1 January 2020 to 7 October 2023), corresponding to a total of 154,900 genomes. Within this dataset, the S:V1176F mutation displays a high frequency in P.1 (Gamma VOC) lineage and its sublineages, and it is detected in 82.75% of the samples (https://cov-spectrum.org/explore/World/AllSamples/AllTimes/variants?aaMutations=S%3AV1176F&, accessed on 10 October 2023). Additionally, between 12 April 2022, and 1 July 2022, 21 sequences with the S:V1176F mutation were recorded in Brazil, with a higher prevalence in the BA.2 (19.05%) and P.2 (14.29%) lineages (https://cov-spectrum.org/explore/Brazil/AllSamples/from%3D2022-04-12%26to%3D2022-07-01/variants?aaMutations=S%3AV1176F&, accessed on 10 October 2023). Similar to the Delta VOC wave, the sublineage diversity was different between symptomatic and asymptomatic individuals (the most prevalent sublineage was also BA.2, followed by the sublineages BA.2.23, BA.2.12.1, and BA.2.56) (Fisher´s exact test, p = 0.004622).
We also conducted a phylogenetic analysis of the obtained complete SARS-CoV-2 genomes, including the symptomatic background samples generated by the Butantan Network for Pandemic Alert of SARS-CoV-2 Variants (Figure 2B). Based on our analysis, we observed that the asymptomatic samples were randomly interspersed with genomes obtained from symptomatic individuals. The interactive phylogenetic tree can be obtained by accessing the following link: https://nextstrain.org/fetch/api.onedrive.com/v1.0/shares/u!aHR0cHM6Ly8xZHJ2Lm1zL3UvcyFBczlRcWdFZl9kakF4VFdZc3Q3cUJTOW56cDlpP2U9ejRqMklJ/root/content?d=tree,entropy,frequencies&p=full (accessed on 30 October 2023).
In this study, we investigated the incidence of asymptomatic SARS-CoV-2 infections in strategic areas of the SP city and found a low occurrence of such infections while observing sublineage diversity comparable to that determined during the concurrent pandemic waves. A significant advantage of our study was that the sample collection was conducted in strategic areas of the city, and positive individuals were monitored for the development of clinical symptoms, allowing for the exclusion of presymptomatic positive individuals. The incidence of asymptomatic SARS-CoV-2 infections during the Delta wave was slightly lower (0.6%) than that during the Omicron wave (0.8%), as also observed in other studies evaluating asymptomatic infections during both pandemic waves [[
There is considerable variability in the incidence of asymptomatic SARS-CoV-2 infections reported by different studies and in various geographic locations worldwide. Asymptomatic SARS-CoV-2 infection rates have varied significantly from 0.03% to above 15% [[
Our study investigated the distinction in Ct values, which are directly related to the viral load, between symptomatic and asymptomatic patients with SARS-CoV-2 infection. Our findings revealed no significant difference in Cts between these groups. This result was similar to other studies that examine real-time PCR data and show that there are no differences between the expressions of the most important viral genes like RdRp, E, and N [[
Such observations underscore the potential impact of public health interventions aimed at controlling the SARS-CoV-2 spread [[
While we observed variations in the sublineage distribution percentages between symptomatic and asymptomatic individuals across multiple samplings, our analysis revealed a random interspersion of the analyzed genomes within the phylogenetic tree. These genomes formed clades, with a maximum of two for the Omicron VOC and three for the Delta VOC. Associating specific lineages and their mutations with clinical outcomes presents a challenging task, as they may be linked to divergent health outcomes. Establishing a reliable association necessitates adjustments for individual risk factors, including the presence of comorbidities such as hypertension, obesity, cardiovascular disease, immunosuppression, smoking, and diabetes mellitus. These comorbidities emerge as more substantial predictors of disease severity, hospitalization, and mortality than the influence of SARS-CoV-2 variants [[
Similar to investigations into asymptomatic rates of SARS-CoV-2, our study carries certain limitations. We deem the most salient limitations to be the following:
- (i) The substantial geographical expanse of the city: While our SARS-CoV-2 testing facilities were strategically situated in vital commercial hubs within the city, such as open-air markets, bus terminals, and airport terminals, the city's vast peripheries, notably including densely populated slum areas, were not encompassed within our study. The omission of these areas may have an impact on the reported rates of asymptomatic SARS-CoV-2 infections.
- (ii) Voluntary participation in the study: It is imperative to acknowledge that our study relied on voluntary participation. Consequently, not all individuals present within the covered areas availed themselves for testing. This, in turn, may have influenced the estimated rates of asymptomatic SARS-CoV-2 infection.
Notwithstanding these limitations, it is crucial to underscore that they do not compromise the integrity of our findings. Instead, they are germane to any study endeavoring to assess asymptomatic SARS-CoV-2 infection within expansive urban settings.
In this study, we sought to examine the incidence of asymptomatic SARS-CoV-2 infection during two epidemic waves in the largest Brazilian metropolis. Our findings revealed a relatively low proportion of asymptomatic cases, which may be attributed to our rigorous follow-up protocol that included monitoring for the development of clinical symptoms. Investigating the rates of asymptomatic infections is crucial for effective disease control, particularly in high-risk populations. Moreover, the asymptomatic rates of infection are essential for advancing vaccine development and for anticipating the emergence of new variants in future scenarios.
MAP: Figure 1 (A) Flowchart illustrating the primary field and laboratory procedures involved in assessing the prevalence of asymptomatic SARS-CoV-2 infection in São Paulo city. (B) Map of São Paulo, presenting the locations of the sampling points. The map features distinct color-coded lines representing the major city regions, grouped together based on neighborhood proximity. The shaded neighborhoods on the map indicate the precise sampling points chosen for data collection and analysis. (C) Image showcasing the collection points for the samples.
Graph: Figure 2 Lineage distribution across samplings. Outer circles: genomes obtained from symptomatic individuals (used as background); inner circles: genomes obtained from asymptomatic individuals (from this study). (A—left) Lineage distribution from the Delta wave, containing 23 genomes from asymptomatic individuals and 318 genomes from symptomatic individuals. (A—right) Lineage distribution from the Omicron wave, containing 15 genomes from asymptomatic individuals and 54 genomes from symptomatic individuals. (B) Maximum likelihood tree of genomic sequences from São Paulo city. (B—left) Samples from Delta wave. (B—right) Samples from Omicron wave. Genomes from symptomatic individuals are represented by triangles in the tip of the trees, while asymptomatic genomes are represented by circles, pointed by red arrows.
Conceptualization: S.N.S., C.R.d.S.B., E.C.M., A.J.M., M.M., M.P., L.A.V.C., S.K., M.G., L.C.J.A., S.C.S. and M.C.E.; formal analysis: A.R.J.L., G.R., L.P.O.d.L., C.R.d.S.B., E.C.M., M.M., M.P., L.A.V.C., F.E.V.d.S., G.C. and A.L.N.; data analysis: S.N.S., A.R.J.L., G.R., C.R.d.S.B., E.C.M., A.J.M., M.M., M.P., L.A.V.C., F.E.V.d.S., G.C., A.L.N., S.C.S. and M.C.E.; writing—original draft preparation: S.N.S.; writing—review and editing: A.R.J.L., G.R., M.G., M.C.E. and M.P.; molecular screening and SARS-CoV-2 genomic data production: A.R.J.L. and G.R.; epidemiological data analysis: C.R.d.S.B. All authors have read and agreed to the published version of the manuscript.
This research was reviewed and approved by the Ethical Committee of the Medical School of Ribeirão Preto (HCRP-FMRP/USP) (CAAE 53243621.9.1001.5440) and the Ethical Committee of the Health Secreteriat of Sao Paulo (CEP da SMS SP) (CAAE 53243621.9.2002.0086).
Not applicable.
All sequences that were generated and used in the present study are listed in Table S3, accessible in the GISAID repository, which can be obtained using the respective sequence IDs, sampling dates, the origin and sending laboratories, and the main authors.
The authors declare no conflict of interest.
We thank all those who have kindly deposited and shared genome data on GISAID. The authors acknowledge the Network for Pandemic Alert of Emerging SARS-CoV-2 Variants (CeVIVAS team) for its contribution towards the sequencing effort and for its commitment and work during the fight against the COVID-19 pandemic. MG is funded by PON "Ricerca e Innovazione" 2014–2020.
The following supporting information can be downloaded at: https://
By Svetoslav N. Slavov; Alex R. J. Lima; Gabriela Ribeiro; Loyze P. O. de Lima; Claudia R. dos S. Barros; Elaine C. Marqueze; Antonio J. Martins; Maiara Martininghi; Melissa Palmieri; Luiz A. V. Caldeira; Fabiana E. V. da Silva; Giselle Cacherik; Aline L. Nicolodelli; Simone Kashima; Marta Giovanetti; Luiz Carlos Junior Alcantara; Sandra C. Sampaio and Maria C. Elias
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