Evidence map›Paper›PMID 34725040›Full record

ArticleBMJ global health2021

Projections of human papillomavirus (HPV) vaccination impact in Ethiopia, India, Nigeria and Pakistan: a comparative modelling study.

Allison Portnoy, Kaja Abbas, Steven Sweet, Jane J Kim, Mark Jit

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 10% of its field
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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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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 at 2 institutions in 4 countries.

Allison PortnoyCenter for Health Decision Science, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA aportnoy@mail.harvard.edu.ORCID 0000-0002-8467-1324
Kaja AbbasDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0003-0563-1576
Steven SweetCenter for Health Decision Science, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA.
Jane J KimCenter for Health Decision Science, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA.
Mark JitDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-6658-8255
Harvard University · USLondon School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCervical cancer is the second most common cancer among women in Ethiopia, India, Nigeria and Pakistan. Our study objective was to assess similarities and differences in vaccine-impact projections through comparative modelling analysis by independently estimating the potential health impact of human papillomavirus (HPV) vaccination.

methodsUsing two widely published models (Harvard and Papillomavirus Rapid Interface for Modelling and Economics (PRIME)) to estimate HPV vaccination impact, we simulated a vaccination scenario of 90% annual coverage among 10 cohorts of 9-year-old girls from 2021 to 2030 in Ethiopia, India, Nigeria and Pakistan. We estimated potential health impact in terms of cervical cancer cases, deaths and disability-adjusted life years averted among vaccinated cohorts from the time of vaccination until 2100. We harmonised the two models by standardising input data to comparatively estimate HPV vaccination impact.

resultsPrior to harmonising model assumptions, the range between PRIME and Harvard models for number of cervical cancer cases averted by HPV vaccination was: 262 000 to 2 70 000 in Ethiopia; 1 640 000 to 1 970 000 in India; 330 000 to 3 36 000 in Nigeria and 111 000 to 1 33 000 in Pakistan. When harmonising model assumptions, alignment on HPV type distribution significantly narrowed differences in vaccine-impact estimates.

conclusionDespite model differences, the Harvard and PRIME models yielded similar vaccine-impact estimates. The main differences in estimates are due to variation in interpretation around data on cervical cancer attribution to HPV-16/18. As countries make progress towards WHO targets for cervical cancer elimination, continued explorations of underlying differences in model inputs, assumptions and results when examining cervical cancer prevention policy will be critical.

Indexed as

Papillomavirus InfectionsChildDisability-Adjusted Life YearsEthiopiaFemaleHuman papillomavirus 16Human papillomavirus 18HumansIndiaNigeriaPakistanVaccinationcancerhealth policypublic healthvaccines

Identifiers

PMID34725040
PMCPMC8562528
OpenAlexW3210433174

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.