{"doi":"10.7554/elife.69302","title":"Quantifying the relationship between SARS-CoV-2 viral load and infectiousness","abstract":"<jats:p>\n                    The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 10\n                    <jats:sup>10</jats:sup>\n                    copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.\n                  </jats:p>","journal":"eLife","year":2021,"id":636108,"datarank":0.7565137675378871,"base_score":5.043425116919247,"endowment":5.043425116919247,"self_citation_contribution":0.7565137675378871,"citation_network_contribution":0.0,"self_endowment_contribution":0.7565137675378871,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":154,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":1,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1159099,"name":"Marion Kerioui","orcid":"0000-0002-1694-9021","position":1,"is_corresponding":false},{"id":571640,"name":"François Blanquart","orcid":"0000-0003-0591-2466","position":2,"is_corresponding":false},{"id":567607,"name":"Julie Bertrand","orcid":"0000-0002-6568-1041","position":3,"is_corresponding":false},{"id":585053,"name":"Oriol Mitjà","orcid":null,"position":4,"is_corresponding":false},{"id":1650686,"name":"Marc Corbacho-Monné","orcid":null,"position":5,"is_corresponding":false},{"id":561785,"name":"Michael Marks","orcid":"0000-0002-7585-4743","position":6,"is_corresponding":false},{"id":548532,"name":"Jérémie Guedj","orcid":"0000-0002-5534-5482","position":7,"is_corresponding":false},{"id":805515,"name":"Aurélien Marc","orcid":"0000-0002-6936-5388","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.","abstract":"The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 10<sup>10</sup> copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":1,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"34569939","pmcid":"PMC8476126","openalex_id":null,"authors":[],"funders":[{"funder_name":"National Institute for Health Research (NIHR)","grant_id":"CL-2016-20-001","title":null},{"funder_name":"European Research Council","grant_id":"ERC Starting Grant under the European Union's Horizon 2020 research and innovation programme","title":null},{"funder_name":"European Research Council","grant_id":"ERC Starting Grant under the European Union&apos;s Horizon 2020 research and innovation programme","title":null},{"funder_name":"Bill and Melinda Gates Foundation","grant_id":"INV-017335","title":null},{"funder_name":"YoMeCorono","grant_id":"Crowdfunding campaign","title":null},{"funder_name":"French National Research Agency","grant_id":"ANR-20-COVI-0018","title":"Viral dynamics at the individual and population levels: impact for antiviral treatment optimization"},{"funder_name":"Generalitat de Catalunya","grant_id":"","title":null}],"total_grants":7,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.7554/elife.69302","host_type":"publisher"},{"url":"https://doaj.org/article/fa4469bd37f34dfaa035cee38753eef9","host_type":"repository"},{"url":"http://europepmc.org/pmc/articles/PMC8476126","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8476126","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC8476126","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC8476126?pdf=render","host_type":"Europe_PMC"},{"url":"https://doi.org/10.1101/2021.05.07.21256341","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/34569939","host_type":""},{"url":"http://dx.doi.org/10.7554/eLife.69302","host_type":""},{"url":"https://fundanet.igtp.cat/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1838","host_type":""},{"url":"https://i3pt.portalinvestigacion.com/publicaciones/1947","host_type":""},{"url":"https://researchonline.lshtm.ac.uk/id/eprint/4662788/7/Marc_etal_2021_Quantifying-the-relationship-between-sars.pdf","host_type":""},{"url":"https://dx.doi.org/10.7554/elife.69302","host_type":""},{"url":"https://dx.doi.org/10.1101/2021.05.07.21256341","host_type":""},{"url":"https://hal.science/hal-03405884v1/document","host_type":""},{"url":"https://hal.science/hal-03405884v1","host_type":""},{"url":"https://doi.org/https://doi.org/10.7554/eLife.69302","host_type":""}],"fields_of_study":["0301 basic medicine","03 medical and health sciences","0303 health sciences"],"mesh_terms":["Humans","Viral Load","Contact Tracing","Logistic Models","Risk Factors","Cohort Studies","Virus Replication","Adult","Middle Aged","Female","Male","Young Adult","COVID-19","SARS-CoV-2","COVID-19 Vaccines"],"keywords":["Human","Infectious diseases","Microbiology","Infectious disease","computational biology","epidemiology","Sars-cov-2","Adult","Male","COVID-19 Vaccines","QH301-705.5","Science","610","Virus Replication","Cohort Studies","Young Adult","[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]","Risk Factors","616","Humans","Biology (General)","[SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology","[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]","[SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology","Microbiology and Infectious Disease","Q","R","COVID-19","Middle Aged","Viral Load","[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation","[SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology","Logistic Models","[SDV.SP.PHARMA] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology","[SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology","[SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology","Medicine","Female","[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation","Contact Tracing"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. Good health"}],"linked_datasets":[{"doi":"10.6084/m9.figshare.17434961","title":"Quantifying the relationship between SARS-CoV-2 viral load and infectiousness","publisher":"figshare","resource_type":"Software"}],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"nct"},{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T16:13:01.032087Z","pmid":null,"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":[]}