{"doi":"10.3389/fpubh.2024.1322797","title":"Using SCENTinel® to predict SARS-CoV-2 infection: insights from a community sample during dominance of Delta and Omicron variants","abstract":"Introduction: Based on a large body of previous research suggesting that smell loss was a predictor of COVID-19, we investigated the ability of SCENTinel®, a newly validated rapid olfactory test that assesses odor detection, intensity, and identification, to predict SARS-CoV-2 infection in a community sample. Methods: Between April 5, 2021, and July 5, 2022, 1,979 individuals took one SCENTinel® test, completed at least one physician-ordered SARS-CoV-2 PCR test, and endorsed a list of self-reported symptoms. Results: Among the of SCENTinel® subtests, the self-rated odor intensity score, especially when dichotomized using a previously established threshold, was the strongest predictor of SARS-CoV-2 infection. SCENTinel® had high specificity and negative predictive value, indicating that those who passed SCENTinel® likely did not have a SARS-CoV-2 infection. Predictability of the SCENTinel® performance was stronger when the SARS-CoV-2 Delta variant was dominant rather than when the SARS-CoV-2 Omicron variant was dominant. Additionally, SCENTinel® predicted SARS-CoV-2 positivity better than using a self-reported symptom checklist alone. Discussion: These results indicate that SCENTinel® is a rapid assessment tool that can be used for population-level screening to monitor abrupt changes in olfactory function, and to evaluate spread of viral infections like SARS-CoV-2 that often have smell loss as a symptom.","journal":"Frontiers in Public Health","year":2024,"id":475624,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7486,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1312616,"name":"Anne Zola","orcid":"0000-0001-7111-1515","position":1,"is_corresponding":false},{"id":915535,"name":"Emily Ho","orcid":"0000-0002-3522-3779","position":2,"is_corresponding":false},{"id":443067,"name":"Michael A. Kallen","orcid":null,"position":3,"is_corresponding":false},{"id":1312959,"name":"Edith Adjei-Danquah","orcid":null,"position":4,"is_corresponding":false},{"id":283131,"name":"Chad J. Achenbach","orcid":"0000-0003-4847-7249","position":5,"is_corresponding":false},{"id":1312617,"name":"G. Randy Smith","orcid":"0000-0002-1296-4881","position":6,"is_corresponding":false},{"id":304194,"name":"Richard Gershon","orcid":"0000-0003-0085-0112","position":7,"is_corresponding":false},{"id":247555,"name":"Danielle R. Reed","orcid":"0000-0002-4374-6107","position":8,"is_corresponding":false},{"id":302779,"name":"Benjamin D. Schalet","orcid":"0000-0001-7486-0204","position":9,"is_corresponding":false},{"id":231553,"name":"Valentina Parma","orcid":"0000-0003-0276-7072","position":10,"is_corresponding":false},{"id":577315,"name":"Pamela Dalton","orcid":"0000-0003-2474-2888","position":11,"is_corresponding":false},{"id":926975,"name":"Stephanie Hunter","orcid":"0000-0002-2540-7929","position":0,"is_corresponding":true}],"reference_count":64,"raw_metadata":null,"created_at":"2026-07-19T02:06:21.071690Z","pmid":"38660364","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}