ArticleInfectious Disease Modelling2026
A predictive model for rapid assessment of protective efficacy against emerging SARS-CoV-2 variants.
Article in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Current Vaccination Principles and Practices in Adult Cancer Patients.Journal of clinical practice and research · 2026Review
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6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An effective predictive model of protection would be very helpful to provide a timely and reliable evaluation of the vaccine induced protection against corresponding to rapidly emerging evolving SARS-CoV-2 variants. By integrating the validated "neutralizing antibody-vaccine efficacy" and "modified genetic distance-vaccine efficacy" models, we developed a composite sieve analysis framework (the "neutralizing antibody-genetic distance-vaccine efficacy" model) to predict the protective efficacy of COVID-19 vaccine regimens, particularly for different heterologous prime-boost COVID-19 vaccination regimens. Data for the model building were extracted from 23 published studies. Leave-one-out method was used to validate the model. Model validation demonstrated that the composite framework achieved high predictive accuracy, with concordance correlation coefficients of 0.95 (95% CI: 0.82-0.98) for the "neutralizing antibody-vaccine efficacy" submodel and 0.93 (95% CI: 0.49-0.99) for the "modified genetic distance-vaccine efficacy" submodel. Most prediction errors were within 5% and 10%, respectively. By applying this framework with neutralizing antibody data and SARS-CoV-2 variant sequencing data, we predicted the protective efficacy of different heterologous prime-boost regimens. The regimen of two-dose CoronaVac plus one-dose aerosolized Ad5-nCoV was estimated to confer 95.40% (95% CI: 92.67-98.13%) protection against symptomatic infection with wild-type SARS-CoV-2 at day 28 post-boost, 79.56% (95% CI: 53.31-100.00%) against the Delta variant, and 68.21% (95% CI: 42.53-93.89%) against Omicron BA.5.2.20. Predicted efficacy against other Omicron sublineages was generally below 50%, with near-zero efficacy for KP.2, KP.3 and XDV.1. Compared with this regimen, two-dose CoronaVac plus one-dose intramuscular Ad5-nCoV booster or three-dose CoronaVac yielded consistently lower predicted efficacy across all variants. This study offers a generalizable approach for rapidly evaluating the efficacy of COVID-19 vaccines against emerging variants, providing timely evidence to guide vaccine deployment in future outbreaks.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.