Rural prioritization may increase the impact of COVID-19 vaccines in a representative COVAX AMC country setting due to ongoing internal migration: A modeling study
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Abstract
How COVID-19 vaccine is distributed within low- and middle-income countries has received little attention outside of equity or logistical concerns but may ultimately affect campaign impact in terms of infections, severe cases, or deaths averted. In this study we examined whether subnational (urban-rural) prioritization may affect the cumulative two-year impact on disease transmission and burden of a vaccination campaign using an agent-based model of COVID-19 in a representative COVID-19 Vaccines Global Access (COVAX) Advanced Market Commitment (AMC) setting. We simulated a range of vaccination strategies that differed by urban-rural prioritization, age group prioritization, timing of introduction, and final coverage level. Urban prioritization averted more infections in only a narrow set of scenarios, when internal migration rates were low and vaccination was started by day 30 of an outbreak. Rural prioritization was the optimal strategy for all other scenarios, e.g., with higher internal migration rates or later start dates, due to the presence of a large immunological naive rural population. Among other factors, timing of the vaccination campaign was important to determining maximum impact, and delays as short as 30 days prevented larger campaigns from having the same impact as smaller campaigns that began earlier. The optimal age group for prioritization depended on choice of metric, as prioritizing older adults consistently averted more deaths across all of the scenarios. While guidelines exist for these latter factors, urban-rural allocation is an orthogonal factor that we predict to affect impact and warrants consideration as countries plan the scale-up of their vaccination campaigns.
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SciScore for 10.1101/2021.06.18.21259164: (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 Vaccine availability followed the COVAX projections of vaccine supply available from GAVI [17]. GAVIsuggested: (GAVI, RRID:SCR_008528)Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study had several limitations. As an abstraction of a SSA country setting, our model represents an average in many respects: demographics (ages, contact patterns, urban-rural localization), COVID-19 response (as tracked by Oxford CGRT [30]), and a generic urban-seeded outbreak. This abstraction …
SciScore for 10.1101/2021.06.18.21259164: (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 Vaccine availability followed the COVAX projections of vaccine supply available from GAVI [17]. GAVIsuggested: (GAVI, RRID:SCR_008528)Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our study had several limitations. As an abstraction of a SSA country setting, our model represents an average in many respects: demographics (ages, contact patterns, urban-rural localization), COVID-19 response (as tracked by Oxford CGRT [30]), and a generic urban-seeded outbreak. This abstraction represents a trade-off that allowed us to focus on outbreak scenarios that may be applicable to many countries, though not precisely calibrated to any particular country. Our model also had several parameters that were abstractions of physical processes and not precisely matched to data. For example, internal migration did not correspond to a particular indicator such as mobile phone-based movement but represents an aggregate of this and other factors contributing to net migration [31]. We also made several simplifying assumptions on COVID-19 immunity and vaccines such as previous infection leading to perfect immunity and optimistic vaccine characteristics such as those based on mRNA vaccines [32, 33], as well as no opportunity for reinfection. We also did not explicitly account for any particular SARS-CoV-2 variants. However, by spanning a range of transmission rates, we accounted for increased infectiousness expected of new variants. In this case, our selected vaccine efficacy rates may represent best-case scenarios, with variants further reducing the impact on infections, severe cases, and deaths. In sum, our model supports the position that countries should consider spatial pri...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
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.
Results from scite Reference Check: We found no unreliable references.
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