ABSTRACT
RT-qPCR-based diagnostic tests play important roles in combating virus-caused pandemics such as Covid-19. However, their dependence on sophisticated equipment and the associated costs often limits their widespread use. Loop-mediated isothermal amplification after reverse transcription (RT-LAMP) is an alternative nucleic acid detection method that overcomes these limitations. Here, we present a rapid, robust, and sensitive RT-LAMP-based SARS-CoV-2 detection assay. Our 40-min procedure bypasses the RNA isolation step, is insensitive to carryover contamination, and uses a colorimetric readout that enables robust SARS-CoV-2 detection from various sample types. Based on this assay, we have increased sensitivity and scalability by adding a nucleic acid enrichment step (Bead-LAMP), developed a version for home testing (HomeDip-LAMP), and identified open-source RT-LAMP enzymes that can be produced in any molecular biology laboratory. On a dedicated website, rtlamp.org (DOI: 10.5281/zenodo.6033689), we provide detailed protocols and videos. Our optimized, general-purpose RT-LAMP assay is an important step toward population-scale SARS-CoV-2 testing.
ABSTRACT
BACKGROUND: The role of schools in the SARS-CoV-2 pandemic is much debated. We aimed to quantify reliably the prevalence of SARS-CoV-2 infections at schools detected with reverse-transcription quantitative polymerase-chain-reaction (RT-qPCR). METHODS: This nationwide prospective cohort study monitors a representative sample of pupils (grade 1-8) and teachers at Austrian schools throughout the school year 2020/2021. We repeatedly test participants for SARS-CoV-2 infection using a gargling solution and RT-qPCR. We herein report on the first two rounds of examinations. We used mixed-effects logistic regression to estimate odds ratios and robust 95% confidence intervals (95% CI). FINDINGS: We analysed data on 10,734 participants from 245 schools (9465 pupils, 1269 teachers). Prevalence of SARS-CoV-2 infection increased from 0·39% at round 1 (95% CI 028-0·55%, 28 September-22 October 2020) to 1·39% at round 2 (95% CI 1·04-1·85%, 10-16 November). Odds ratios for SARS-CoV-2 infection were 2·26 (95% CI 1·25-4·12, P = 0·007) in regions with >500 vs. ≤500 inhabitants/km2, 1·67 (95% CI 1·42-1·97, P<0·001) per two-fold higher regional 7-day community incidence, and 2·78 (95% CI 1·73-4·48, P<0·001) in pupils at schools with high/very high vs. low/moderate social deprivation. Associations of regional community incidence and social deprivation persisted in a multivariable adjusted model. Prevalence did not differ by average number of pupils per class nor between age groups, sexes, pupils vs. teachers, or primary (grade 1-4) vs. secondary schools (grade 5-8). INTERPRETATION: This monitoring study in Austrian schools revealed SARS-CoV-2 infection in 0·39%-1·39% of participants and identified associations of regional community incidence and social deprivation with higher prevalence. FUNDING: BMBWF Austria.
ABSTRACT
The COVID-19 pandemic has demonstrated the need for massively-parallel, cost-effective tests monitoring viral spread. Here we present SARSeq, saliva analysis by RNA sequencing, a method to detect SARS-CoV-2 and other respiratory viruses on tens of thousands of samples in parallel. SARSeq relies on next generation sequencing of multiple amplicons generated in a multiplexed RT-PCR reaction. Two-dimensional, unique dual indexing, using four indices per sample, enables unambiguous and scalable assignment of reads to individual samples. We calibrate SARSeq on SARS-CoV-2 synthetic RNA, virions, and hundreds of human samples of various types. Robustness and sensitivity were virtually identical to quantitative RT-PCR. Double-blinded benchmarking to gold standard quantitative-RT-PCR performed by human diagnostics laboratories confirms this high sensitivity. SARSeq can be used to detect Influenza A and B viruses and human rhinovirus in parallel, and can be expanded for detection of other pathogens. Thus, SARSeq is ideally suited for differential diagnostic of infections during a pandemic.