Evidence map›Paper›PMID 33662812›Full record

SynthesisEpidemics2021

Mathematical modelling of respiratory syncytial virus (RSV) in low- and middle-income countries: A systematic review.

Alex Mezei, Jamie Cohen, Matthew J Renwick, Jessica Atwell, Allison Portnoy

Abstract readSystematic Review
In one paragraph

Synthesis in Epidemics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

5 authors.

Alex MezeiDepartment of Medicine, University of British Columbia, Vancouver, BC, Canada. Electronic address: alexmezei@alumni.ubc.ca.
Jamie CohenInstitute for Disease Modeling, Seattle, WA, United States.
Matthew J RenwickDepartment of Medicine, University of British Columbia, Vancouver, BC, Canada.
Jessica AtwellJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Allison PortnoyCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, United States.

Funding

PROGRAM FOR AIDS CLINICAL RESEARCH TRAINING (PACRT)T32AI007433 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI MARK J SIEDNER · 1992 to 2026
$11.4M
NIAID NIH HHS T32 AI007433
6 · The paper itself

Abstract

backgroundDue to high burden of respiratory syncytial virus (RSV) in low- and middle-income countries (LMIC), international funding organizations have prioritized the development of RSV vaccines. Mathematical models of RSV will play an important role in assessing the relative value of these interventions. Our objectives were to provide an overview of the existing RSV modelling literature in LMIC and summarize available results on population-level effectiveness and cost-effectiveness.

methodsWe searched MEDLINE from 2000 to 2020 for English language publications that employed a mathematical model of RSV calibrated to LMIC. Qualitative data were extracted on study and model characteristics. Quantitative data were collected on key model input assumptions and base case effectiveness and cost-effectiveness estimates for various immunization strategies.

findingsOf the 283 articles reviewed, 15 met inclusion criteria. Ten studies used modelling techniques to explore RSV transmission and/or natural history, while eight studies evaluated RSV vaccines and/or monoclonal antibodies, three of which included cost-effectiveness analyses. Six studies employed deterministic compartmental models, five studies employed individual transmission models, and four studies used different types of cohort models. Nearly every model was calibrated to at least one middle-income country, while four were calibrated to low-income countries.

interpretationThe mathematical modelling literature in LMIC has demonstrated the potential effectiveness of RSV vaccines and monoclonal antibodies. This review has demonstrated the importance of accounting for seasonality, social contact rates, immunity from prior infection and maternal antibody transfer. Future models should consider incorporating individual-level risk factors, subtype-specific effects, long-term sequelae of RSV infections, and out-of-hospital mortality.

Indexed as

Respiratory Syncytial Virus, HumanRespiratory Syncytial Virus InfectionsRespiratory Syncytial Virus VaccinesDeveloping CountriesHumansModels, TheoreticalRespiratory Syncytial Virus VaccinesCost-effectivenessLow- and middle-income countriesMathematical modellingRespiratory syncytial virusSystematic reviewVaccine

Identifiers

PMID33662812
PMCPMC8262087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.