Challenging a paradigm: Staggered versus single-pulse mass dog vaccination strategy for rabies elimination.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2025-02-07 eCollection Date: 2025-02-01 DOI:10.1371/journal.pcbi.1012780
Brinkley Raynor Bellotti, Elvis W Díaz, Micaela De la Puente-León, Maria T Rieders, Sergio E Recuenco, Michael Z Levy, Ricardo Castillo-Neyra
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引用次数: 0

Abstract

Background: From smallpox to poliomyelitis, halting contagion transmission through simultaneous mass vaccination is ubiquitous and often perceived as the only possible solution. But implementing mass vaccination campaigns in large populations within a short period poses many challenges. For example, in Arequipa, Peru, sweeping mass vaccination campaigns conducted yearly over a single weekend have failed to achieve the required 'herd immunity' to halt canine rabies transmission. Contrary to the global paradigm of a simultaneous campaign, the 2022 Arequipa rabies campaign was implemented at the sub-district level (patches), with dates of the campaign staggered across 6 months.

Methods: We constructed a stochastic, metapopulation model to examine how the timing of pulsed vaccination campaigns across patches can affect metapopulation dynamics. We explore general metapopulation dynamics for pulsed vaccinations as well as parameterizing the model for canine rabies in Arequipa, Peru. We simulated how the timing of the planned vaccination campaign, staggered over 6 months versus a single yearly pulse, affected the prospects for regional rabies elimination.

Results: Metapopulation dynamics can affect the efficacy of pulsed vaccination campaigns. In the case of Arequipa, Peru, the planned staggered mass dog vaccination campaign has the potential for local elimination with the tradeoffs of increased time to elimination and increased outbreak size due to metapopulation dynamics.

Conclusions: Heterogeneities caused by control strategies enactment at sub-population scales should be accounted for when modeling transmission dynamics. In Arequipa, Peru, although metapopulation dynamics may allow for re-introduction of canine rabies in previously vaccinated patches when mass dog vaccination campaigns are staggered temporally over 6 months, continuous mass vaccination reaching recommended vaccination coverage levels is sufficient to eliminate canine rabies.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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