Evidence map›Paper›PMID 29791432›Full record

ArticlePLoS computational biology2018

Logistical constraints lead to an intermediate optimum in outbreak response vaccination.

Yun Tao, Katriona Shea, Matthew Ferrari

Abstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yun TaoDepartment of Biology and The Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.ORCID 0000-0001-5973-9422
Katriona SheaDepartment of Biology and The Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
Matthew FerrariDepartment of Biology and The Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.

Funding

Linking models and policy: Using active adaptive management for optimal control of disease outbreaksR01GM105247 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI FERRARI, MATTHEW · 2012 to 2016
$1.3M
Biotechnology and Biological Sciences Research Council BB/K010972/4NIGMS NIH HHS R01 GM105247NIH HHS 1 R01 GM105247-01
6 · The paper itself

Abstract

Dynamic models in disease ecology have historically evaluated vaccination strategies under the assumption that they are implemented homogeneously in space and time. However, this approach fails to formally account for operational and logistical constraints inherent in the distribution of vaccination to the population at risk. Thus, feedback between the dynamic processes of vaccine distribution and transmission might be overlooked. Here, we present a spatially explicit, stochastic Susceptible-Infected-Recovered-Vaccinated model that highlights the density-dependence and spatial constraints of various diffusive strategies of vaccination during an outbreak. The model integrates an agent-based process of disease spread with a partial differential process of vaccination deployment. We characterize the vaccination response in terms of a diffusion rate that describes the distribution of vaccination to the population at risk from a central location. This generates an explicit trade-off between slow diffusion, which concentrates effort near the central location, and fast diffusion, which spreads a fixed vaccination effort thinly over a large area. We use stochastic simulation to identify the optimum vaccination diffusion rate as a function of population density, interaction scale, transmissibility, and vaccine intensity. Our results show that, conditional on a timely response, the optimal strategy for minimizing outbreak size is to distribute vaccination resource at an intermediate rate: fast enough to outpace the epidemic, but slow enough to achieve local herd immunity. If the response is delayed, however, the optimal strategy for minimizing outbreak size changes to a rapidly diffusive distribution of vaccination effort. The latter may also result in significantly larger outbreaks, thus suggesting a benefit of allocating resources to timely outbreak detection and response.

Indexed as

Computer SimulationImmunity, HerdModels, BiologicalComputational BiologyDisease OutbreaksHumansTime FactorsVaccinationVaccinesVaccines

Identifiers

PMID29791432
PMCPMC5988332

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.