{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T18:11:09Z","timestamp":1789495869701,"version":"build-2803163510"},"reference-count":24,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100004325","name":"AstraZeneca","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004325","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Seasonal respiratory viruses, including respiratory syncytial virus (RSV) and human metapneumovirus (hMPV), are major contributors to global respiratory infection burden. Estimating viral incidence using real-world data (RWD) is challenging as misalignment of data collection with seasonal circulation can lead to underestimated incidence and hinder inter-study comparisons.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We developed a regression-based approach to retrospectively correct partial-season time series with contiguous missing weeks at the start or end of a season. Weekly RSV clinical incidence (per 100,000) was extracted from U.S. RWD sources (Optum\n                      <jats:sup>\u00ae<\/jats:sup>\n                      CDM and PharMetrics Plus, adults \u226565 years; Kaiser Permanente Northwest [KPNW], all ages) for seasons 2018\u201319 to 2023\u201324 and aligned to RSV\u2011Net hospitalization surveillance. Weekly early- and late-season missingness scenarios were created (approximately 10%, 15%, 20%, and 25% of weeks removed). Models were fit within each season using harmonic terms and the surveillance-aligned covariate. Uncertainty was quantified using moving block bootstrap 95% prediction intervals. Weekly accuracy was evaluated using RMSE and normalized RMSE, and seasonal burden reconstruction accuracy using cumulative percent error and signed difference. For hMPV, we evaluated an illustrative extension using Optum\n                      <jats:sup>\u00ae<\/jats:sup>\n                      CDM (adults \u226565 years; 2022\u201323 and 2023\u201324) and NREVSS test positivity; because positivity is bounded and depends on testing volume, we used a denominator-aware binomial\/logit model (positives out of tests).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      For RSV, weekly prediction error increased with missingness level, while reconstructed seasonal burden generally remained close to observed totals in applicable scenarios. Early-season gaps were associated with larger cumulative errors than late-season gaps in Optum\n                      <jats:sup>\u00ae<\/jats:sup>\n                      CDM and PharMetrics Plus, whereas late-season median percent errors were closer to zero across missingness levels. Applicability was reduced primarily for higher early-season missingness in KPNW due to peak overlap (e.g., early 25% scenarios not applicable). For hMPV test positivity (illustrative; two seasons), weekly prediction RMSE was on the order of ~1\u20132 percentage points across missingness scenarios.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Across multiple RSV seasons and data sources, reconstructed seasonal burden generally agreed with observed totals when missingness was confined to contiguous early- or late-season weeks and did not overlap peak activity. This approach provides a transparent method to improve the utility and comparability of partial-season respiratory virus time series. However, applicability is reduced when peak weeks are missing, and hMPV findings are illustrative given limited seasons and the use of test positivity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0353681","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T17:49:17Z","timestamp":1789494557000},"page":"e0353681","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Estimating cumulative incidence from partially missing time series of respiratory viral infections"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2093-5781","authenticated-orcid":true,"given":"Sudhir","family":"Venkatesan","sequence":"first","affiliation":[{"name":"BPM Evidence Statistics, BioPharmaceuticals Medical, AstraZeneca","place":["Cambridge, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6523-185X","authenticated-orcid":true,"given":"Lisa","family":"White","sequence":"additional","affiliation":[{"name":"Model Health Ltd","place":["Brixham, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyewon Nina","family":"Koo","sequence":"additional","affiliation":[{"name":"Data Science and Artificial Intelligence, BioPharmaceuticals R&D, AstraZeneca","place":["M\u00f6lndal, Sweden"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Dickerson","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Center for Health Research","place":["Portland, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiming","family":"Hu","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Center for Health Research","place":["Portland, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Kuntz","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Center for Health Research","place":["Portland, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Center for Health Research","place":["Portland, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylvia","family":"Taylor","sequence":"additional","affiliation":[{"name":"Medical Evidence, Vaccines and Immune Therapies, BioPharmaceuticals Medical, AstraZeneca","place":["Cambridge, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carla","family":"Talarico","sequence":"additional","affiliation":[{"name":"Medical Evidence, Vaccines and Immune Therapies, BioPharmaceuticals Medical, AstraZeneca","place":["Gaithersburg, Maryland, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"pone.0353681.ref001","doi-asserted-by":"crossref","first-page":"1028525","DOI":"10.3389\/fpubh.2022.1028525","article-title":"Global burden of lower respiratory infections during the last three decades","volume":"10","author":"S Safiri","year":"2023","journal-title":"Front Public Health"},{"issue":"1","key":"pone.0353681.ref002","first-page":"010408","article-title":"Aetiological role of common respiratory viruses in acute lower respiratory infections in children under five years: a systematic review and meta-analysis","volume":"5","author":"T Shi","year":"2015","journal-title":"J Glob Health"},{"key":"pone.0353681.ref003","article-title":"The etiological role of common respiratory viruses in acute respiratory infections in older adults: a systematic review and meta-analysis","volume":"222","author":"T Shi","year":"2020","journal-title":"J Infect Dis"},{"key":"pone.0353681.ref004","unstructured":"Centers for Disease Control and Prevention. 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