Epidemiological impact of prioritising SARS-CoV-2 vaccination by antibody status: mathematical modelling analyses
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Abstract
Vaccines against SARS-CoV-2 have been developed, but their availability falls far short of global needs. This study aimed to investigate the impact of prioritising available doses on the basis of recipient antibody status, that is by exposure status, using Qatar as an example.
Methods
Vaccination impact (defined as the reduction in infection incidence and the number of vaccinations needed to avert one infection or one adverse disease outcome) was assessed under different scale-up scenarios using a deterministic meta-population mathematical model describing SARS-CoV-2 transmission and disease progression in the presence of vaccination.
Results
For a vaccine that protects against infection with an efficacy of 95%, half as many vaccinations were needed to avert one infection, disease outcome or death by prioritising antibody-negative individuals for vaccination. Prioritisation by antibody status reduced incidence at a faster rate and led to faster elimination of infection and return to normalcy. Further prioritisation by age group amplified the gains of prioritisation by antibody status. Gains from prioritisation by antibody status were largest in settings where the proportion of the population already infected at the commencement of vaccination was 30%–60%. For a vaccine that only protects against disease and not infection, vaccine impact was reduced by half, whether this impact was measured in terms of averted infections or disease outcomes, but the relative gains from using antibody status to prioritise vaccination recipients were similar.
Conclusions
Major health and economic gains can be achieved more quickly by prioritizing those who are antibody-negative while doses of the vaccine remain in short supply.
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SciScore for 10.1101/2021.01.10.21249382: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources The considered vaccination scenarios included administering the vaccine only to those who are antibody-negative, or irrespective of antibody status, administering a specific number of vaccinations or vaccinating to reach a specific coverage in a specific target population, and prioritizing specific age brackets as opposed to others. antibody-negative,suggested: NoneSoftware and Algorithms Sentences Resources The model was coded, fitted, and analyzed using MATLAB R2019a [15]. MATLABsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: We did not detect open data. We also did not detect open code. …
SciScore for 10.1101/2021.01.10.21249382: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources The considered vaccination scenarios included administering the vaccine only to those who are antibody-negative, or irrespective of antibody status, administering a specific number of vaccinations or vaccinating to reach a specific coverage in a specific target population, and prioritizing specific age brackets as opposed to others. antibody-negative,suggested: NoneSoftware and Algorithms Sentences Resources The model was coded, fitted, and analyzed using MATLAB R2019a [15]. MATLABsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has some limitations. Model estimates are contingent on the validity and generalizability of input data and assumptions. Our results are based on current understanding of SARS-CoV-2 natural history and disease progression, but our understanding of this infection is still evolving. A key assumption is that those infected acquire protective immunity against reinfection that lasts for at least a year. While this assumption is supported by current evidence [8-10], studies with longer-term follow-up are still needed to assess the duration of natural immunity. Vaccine-induced immunity is assumed to last for one year, but the duration of this immunity is also unknown. Therefore, model predictions may not be valid if either duration of natural immunity or vaccine-induced immunity lasts less than a year, whether because of waning immunity or appearance of mutant virus strains that escape immunity. The model assumes that vaccinated persons are protected immediately once vaccinated, but vaccine protection builds up gradually over the course of a month following inoculation and peaks after the second does [6]. This may slightly reduce the gains projected here. In conclusion, major health, societal, and economic gains can be attained by prioritizing vaccination for those who are antibody-negative, as long as doses of the vaccine remain in short supply.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2021.01.10.21249382: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The model was coded, fitted, and analyzed using MATLAB R2019a [15]. MATLABsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
This study has some limitations. Model estimates are contingent on the validity and …
SciScore for 10.1101/2021.01.10.21249382: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The model was coded, fitted, and analyzed using MATLAB R2019a [15]. MATLABsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
This study has some limitations. Model estimates are contingent on the validity and generalizability of input data and assumptions. Our results are based on current understanding of SARS-CoV-2 natural history and disease progression, but our understanding of this infection is still evolving. A key assumption is that those infected acquire protective immunity against reinfection that lasts for at least a year. While this assumption is supported by current evidence [8-10], studies with longer-term follow-up are still needed to assess the duration of natural immunity. Vaccine-induced immunity is assumed to last for one year, but the duration of this immunity is also unknown. Therefore, model predictions may not be valid if either duration of natural immunity or vaccine-induced immunity lasts less than a year, whether because of waning immunity or appearance of mutant virus strains that escape immunity. The model assumes that vaccinated persons are protected immediately once vaccinated, but vaccine protection builds up gradually over the course of a month following inoculation and peaks after the second does [6]. This may slightly reduce the gains projected here. In conclusion, major health, societal, and economic gains can be attained by prioritizing vaccination for those who are antibody-negative, as long as doses of the vaccine remain in short supply.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
About SciScore
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