Evidence map›Paper›PMID 35389983›Full record

ArticlePLoS computational biology2022

Adaptive and optimized COVID-19 vaccination strategies across geographical regions and age groups.

Jeta Molla, Alejandro Ponce de León Chávez, Takayuki Hiraoka, Tapio Ala-Nissila, Mikko Kivelä, Lasse Leskelä

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Jeta MollaDepartment of Applied Physics, Aalto University, Espoo, Finland.ORCID 0000-0003-3381-4011
Alejandro Ponce de León ChávezDepartment of Mathematics and Systems Analysis, Aalto University, Espoo, Finland.ORCID 0000-0003-0175-2741
Takayuki HiraokaDepartment of Computer Science, Aalto University, Espoo, Finland.ORCID 0000-0001-7016-8560
Tapio Ala-NissilaQuantum Technology Finland Center of Excellence and Department of Applied Physics, Aalto University, Espoo, Finland.
Mikko KiveläDepartment of Computer Science, Aalto University, Espoo, Finland.ORCID 0000-0003-2049-1954
Lasse LeskeläDepartment of Mathematics and Systems Analysis, Aalto University, Espoo, Finland.ORCID 0000-0001-8411-8329

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluate the efficiency of various heuristic strategies for allocating vaccines against COVID-19 and compare them to strategies found using optimal control theory. Our approach is based on a mathematical model which tracks the spread of disease among different age groups and across different geographical regions, and we introduce a method to combine age-specific contact data to geographical movement data. As a case study, we model the epidemic in the population of mainland Finland utilizing mobility data from a major telecom operator. Our approach allows to determine which geographical regions and age groups should be targeted first in order to minimize the number of deaths. In the scenarios that we test, we find that distributing vaccines demographically and in an age-descending order is not optimal for minimizing deaths and the burden of disease. Instead, more lives could be saved by using strategies which emphasize high-incidence regions and distribute vaccines in parallel to multiple age groups. The level of emphasis that high-incidence regions should be given depends on the overall transmission rate in the population. This observation highlights the importance of updating the vaccination strategy when the effective reproduction number changes due to the general contact patterns changing and new virus variants entering.

Indexed as

COVID-19VaccinesCOVID-19 VaccinesHumansSARS-CoV-2VaccinationCOVID-19 VaccinesVaccines

Identifiers

PMID35389983
PMCPMC9017881

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.