ABSTRACT
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to cause very high morbidity and mortality throughout Latin American countries. However, few population-based seroprevalence surveys have been conducted to quantify attack rates and characterize drivers of transmission.Methods: We conducted a population-based cross-sectional study to assess the seroprevalence of antibodies against SARS-CoV-2 in ten cities in Colombia between September and December, 2020. The study involved multi-stage cluster sampling at each city. Participants provided a serum sample and answered a demographic and risk factor questionnaire. Prior infection by SARS-CoV-2 was ascertained using the "SARS-CoV-2 Total (COV2T) Advia Centaur - Siemens" chemiluminescence assay.Findings: A total of 17863 participants from 7075 households participated in the study. Seroprevalence varied substantially between cities, ranging from 21% (95%CI 16-25%) in Medellín to 78% (95%CI 65-91%) in Guapi. There were no differences in seroprevalence by sex, but seropositivity was lower in adults 60 years or older and higher in certain ethnic groups. There was substantial heterogeneity in seroprevalence within cities, driven to a large extent by a strong association between socio-economic stratum and seropositivity.Interpretation: Colombia has been one of the Latin American countries most affected by the COVID-19 pandemic. This study documented very high attack rates in several Colombian cities by the end of 2020 and identified key drivers of heterogeneities including ethnicity and socio-economic stratum. Few studies of seroprevalence of SARS-CoV-2 have been conducted in Latin America, and therefore this study contributes to the fundamental understanding of the pandemic in the region.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
Background: Use of RT-qPCR pool testing in the diagnosis of SARS-CoV-2 infection has been limited due to a lack of data on its sensitivity and efficiency.Methods: We mixed single specimens of extracted RNA positive for the SARS-CoV-2 E gene by RT-qPCR with negative specimens, in pools of 4 (n=89), 8 (n=92), 16 (n=102), and 32 (n=105) specimens each. We estimated the average change in Ct for each pool size and added it to the Ct values of the first 1,350 tests in our lab, to obtain dilution-corrected Ct values. We estimated pool sensitivity as the proportion of samples with dilution-corrected Ct>40, and used it in simulations of the efficiency (tests used/true case detected) of binary split pool testing.Findings: We tested 388 pools. Average Ct changes were 2.21, 2.51, 3.27, and 3.94 cycles, for pools of 4, 8, 16, and 32 specimens, respectively. Corresponding pool tests sensitivities were 91.1%, 89.6%, 85.8% and 82.5%. Pool testing was substantially more efficient than individual testing. For prevalence of 0.5% to 2.0%, the efficiency of pools of ≥8 specimens was 30% to 280% higher, and the number of people tested was 4.4 to 13.9 times higher than those of individual testing were.Interpretation: Binary split pool testing substantially increases the number of people tested and the number of true cases detected per test. This strategy is key to curtail the transmission of SAR-CoV-2, by increasing efficiency in the identification and isolation of symptomatic and asymptomatic infected individuals.Funding: Major Office of Bucaramanga, Colombia.Declaration of Interests: None.Ethics Approval Statement: The study was approved by both the UIS’ and the University of Wisconsin-Madison’s Institutional Review Boards.