COVID-19 Test Allocation Strategy to Mitigate SARS-CoV-2 Infections across School Districts.

In response to COVID-19, schools across the United States closed in early 2020; many did not fully reopen until late 2021. Although regular testing of asymptomatic students, teachers, and staff can reduce transmission risks, few school systems consistently used proactive testing to safeguard return to classrooms. Socioeconomically diverse public school districts might vary testing levels across campuses to ensure fair, effective use of limited resources. We describe a test allocation approach to reduce overall infections and disparities across school districts. Using a model of SARS-CoV-2 transmission in schools fit to data from a large metropolitan school district in Texas, we reduced incidence between the highest and lowest risk schools from a 5.6-fold difference under proportional test allocation to 1.8-fold difference under our optimized test allocation. This approach provides a roadmap to help school districts deploy proactive testing and mitigate risks of future SARS-CoV-2 variants and other pathogen threats.

Software-Assisted Manual Review of Clinical Next-Generation Sequencing Data: An Alternative to Routine Sanger Sequencing Confirmation with Equivalent Results in >15,000 Germline DNA Screens.

Clinical genomic tests increasingly use a next-generation sequencing (NGS) platform due in part to the high fidelity of variant calls, yet rare errors are still possible. In germline DNA screening, failure to correct such errors could have serious consequences for patients, who may follow an unwarranted screening or surgical management path. It has been suggested that routine orthogonal confirmation by Sanger sequencing is required to verify NGS results, especially low-confidence positives with depressed allele fraction (<30% of alternate allele). We evaluated whether an alternative method of confirmation-software-assisted manual call review-performed comparably with Sanger confirmation in >15,000 samples. Licensed reviewers manually inspected both raw and processed data at the batch, sample, and variant levels, including raw NGS read pileups. Of ambiguous variant calls with <30% allele fraction (1707 total calls at 38 unique sites), manual call review classified >99% (n = 1701) as true positives (enriched for long insertions or deletions and homopolymers) or true negatives (often conspicuous NGS artifacts), with the remaining <1% (n = 6) being mosaic. Critically, results from software-assisted manual review and retrospective Sanger sequencing were concordant for samples selected from all ambiguous sites. We conclude that the confirmation required for high confidence in NGS-based germline testing can manifest in different ways; a trained NGS expert operating platform-tailored review software achieves quality comparable with routine Sanger confirmation.