Evidence map›Paper›PMID 32035034›Full record

ArticleThe Lancet. Global health2020

Estimates of aid for reproductive, maternal, newborn, and child health: findings from application of the Muskoka2 method, 2002-17.

Antonia Dingle, Marco Schäferhoff, Josephine Borghi, Miriam Lewis Sabin, Leonardo Arregoces, Melisa Martinez-Alvarez, Catherine Pitt

Abstract read
In one paragraph

Article in The Lancet. Global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. The need for standardized tracking of investments in digital health.Bulletin of the World Health Organization · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Antonia DingleDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.
Marco SchäferhoffOpen Consultants, Berlin, Germany.
Josephine BorghiDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.
Miriam Lewis SabinPartnership for Maternal, Newborn & Child Health, World Health Organization, Geneva, Switzerland.
Leonardo ArregocesDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.
Melisa Martinez-AlvarezDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK; Medical Research Council Unit in The Gambia, London School of Hygiene & Tropical Medicine, London, UK.
Catherine PittDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: catherine.pitt@lshtm.ac.uk.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundFour methods have previously been used to track aid for reproductive, maternal, newborn, and child health (RMNCH). At a meeting of donors and stakeholders in May, 2018, a single, agreed method was requested to produce accurate, predictable, transparent, and up-to-date estimates that could be used for analyses from both donor and recipient perspectives. Muskoka2 was developed to meet these needs. We describe Muskoka2 and present estimates of levels and trends in aid for RMNCH in 2002-17, with a focus on the latest estimates for 2017.

methodsMuskoka2 is an automated algorithm that generates disaggregated estimates of aid for reproductive health, maternal and newborn health, and child health at the global, donor, and recipient-country levels. We applied Muskoka2 to the Organisation for Economic Co-operation and Development's Creditor Reporting System (CRS) aid activities database to generate estimates of RMNCH disbursements in 2002-17. The percentage of disbursements that benefit RMNCH was determined using CRS purpose codes for all donors except Gavi, the Vaccine Alliance; the UN Population Fund; and UNICEF; for which fixed percentages of aid were considered to benefit RMNCH. We analysed funding by donor for the 20 largest donors, by recipient-country income group, and by recipient for the 16 countries with the greatest RMNCH need, defined as the countries with the worst levels in 2015 on each of seven health indicators.

findingsAfter 3 years of stagnation, reported aid for RMNCH reached $15·9 billion in 2017, the highest amount ever reported. Among donors reporting in both 2016 and 2017, aid increased by 10% ($1·4 billion) to $15·4 billion between 2016 and 2017. Child health received almost half of RMNCH disbursements in 2017 (46%, $7·4 billion), followed by reproductive health (34%, $5·4 billion), and maternal and newborn health (19%, $3·1 billion). The USA ($5·8 billion) and the UK ($1·6 billion) were the largest bilateral donors, disbursing 46% of all RMNCH funding in 2017 (including shares of their core contributions to multilaterals). The Global Fund and Gavi were the largest multilateral donors, disbursing $1·7 billion and $1·5 billion, respectively, for RMNCH from their core budgets. The proportion of aid for RMNCH received by low-income countries increased from 31% in 2002 to 52% in 2017. Nigeria received 7% ($1·1 billion) of all aid for RMNCH in 2017, followed by Ethiopia (6%, $876 million), Kenya (5%, $754 million), and Tanzania (5%, $751 million).

interpretationMuskoka2 retains the speed, transparency, and donor buy-in of the G8's previous Muskoka approach and incorporates eight innovations to improve precision. Although aid for RMNCH increased in 2017, low-income and middle-income countries still experience substantial funding gaps and threats to future funding. Maternal and newborn health receives considerably less funding than reproductive health or child health, which is a persistent issue requiring urgent attention.

fundingBill & Melinda Gates Foundation; Partnership for Maternal, Newborn & Child Health.

Indexed as

AlgorithmsInternational CooperationChildChild HealthDeveloping CountriesFemaleGlobal HealthHumansInfant HealthInfant, NewbornMaternal HealthPregnancyReproductive HealthUnited KingdomUnited States

Identifiers

PMID32035034
PMCPMC7031705

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.