Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 873

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

The global health workforce stock and distribution in 2020 and 2030: a threat to equity and ‘universal’ health coverage?

Open access
Boniol, Mathieu, Kunjumen, Teena, Nair, Tapas Sadasivan, Siyam, Amani, Campbell, James, Diallo, Khassoum·2022·BMJ Global Health

Abstract

Objective: The 2016 Global Strategy on Human Resources for Health: Workforce 2030 projected a global shortage of 18 million health workers by 2030. This article provides an assessment of the health workforce stock in 2020 and presents a revised estimate of the projected shortage by 2030. Methods: Latest data reported through WHO’s National Health Workforce Accounts (NHWA) were extracted to assess health workforce stock for 2020. Using a stock and flow model, projections were computed for the year 2030. The global health workforce shortage estimation was revised. Results: In 2020, the global workforce stock was 29.1 million nurses, 12.7 million medical doctors, 3.7 million pharmacists, 2.5 million dentists, 2.2 million midwives and 14.9 million additional occupations, tallying to 65.1 million health workers. It was not equitably distributed with a 6.5-fold difference in density between high-income and low-income countries. The projected health workforce size by 2030 is 84 million health workers. This represents an average growth of 29% from 2020 to 2030 which is faster than the population growth rate (9.7%). This reassessment presents a revised global health workforce shortage of 15 million health workers in 2020 decreasing to 10 million health workers by 2030 (a 33% decrease globally). WHO African and Eastern Mediterranean regions’ shortages are projected to decrease by only 7% and 15%, respectively. Conclusions: The latest NHWA data show progress in the increasing size of the health workforce globally as more jobs are and will continue to be created in the health economy. It however masks considerable inequities, particularly in WHO African and Eastern Mediterranean regions, and alarmingly among the 47 countries on the WHO Support and Safeguards List. Progress should be acknowledged with caution considering the immeasurable impact of COVID-19 pandemic on health workers globally.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/bmjgh-2022-009316

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

See all 873

Metadata

Authors
Boniol, M., Kunjumen, T., Nair, T. S., Siyam, A., Campbell, J., & Diallo, K.
Venue
BMJ Global Health
Publisher
BMJ
Published
2022-06
Volume
7
Issue
6
Pages
e009316
ISSN
2059-7908 (ISSN-L)
OpenAlex
W4283578429
Cited by
873
References
3
FWCI
175.25
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The global health workforce stock and distribution in 2020 and 2030: a threat to equity and ‘universal’ health coverage? https://app.cochat.ai/papers/10.1136/bmjgh-2022-009316
The paper
Boniol, M., Kunjumen, T., Nair, T. S., Siyam, A., Campbell, J., & Diallo, K. (2022). The global health workforce stock and distribution in 2020 and 2030: a threat to equity and ‘universal’ health coverage? BMJ Global Health. https://doi.org/10.1136/bmjgh-2022-009316

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.