Evidence map›Paper›PMID 28959436›Full record

ArticleJournal of global health2017

Expanding the population coverage of evidence-based interventions with community health workers to save the lives of mothers and children: an analysis of potential global impact using the Lives Saved Tool (LiST).

Victoria B Chou, Ingrid K Friberg, Mervyn Christian, Neff Walker, Henry B Perry

Open access · goldAbstract read
In one paragraph

Article in Journal of global health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
6.9field-weighted citation impact, top 4% 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Bangladesh: 50 Years of Advances in Health and Challenges Ahead.Global health, science and practice · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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 2 countries.

Victoria B ChouInstitute for International Programs, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Ingrid K FribergNorwegian Institute of Public Health, Oslo, Norway.
Mervyn ChristianJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Neff WalkerInstitute for International Programs, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Henry B PerryJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Johns Hopkins University · USNorwegian Institute of Public Health · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvidence has been accumulating that community health workers (CHWs) providing evidence-based interventions as part of community-based primary health care (CBPHC) can lead to reductions in maternal, neonatal and child mortality. However, investments to strengthen and scale-up CHW programs still remain modest.

methodsWe used the Lives Saved Tool (LiST) to estimate the number of maternal, neonatal and child deaths and stillbirths that could be prevented if 73 countries effectively scaled up the population coverage of 30 evidence-based interventions that CHWs can deliver in these high-burden countries. We set population coverage targets at 50%, 70%, and 90% and summed the country-level results by region and by all 73 high-burden countries combined. We also estimated which specific interventions would save the most lives.

findingsLiST estimates that a total of 3.0 (sensitivity bounds 1.8-4.0), 4.9 (3.1-6.3) and 6.9 (3.7-8.7) million deaths would be prevented between 2016 and 2020 if CBPHC is gradually scaled up during this period and if coverage of key interventions reaches 50%, 70%, and 90% respectively. There would be 14%, 23%, and 32% fewer deaths in the final year compared to a scenario assuming no intervention coverage scale up. The Africa Region would receive the most benefit by far: 58% of the lives saved at 90% coverage would be in this region. The interventions contributing the greatest impact are nutritional interventions during pregnancy, treatment of malaria with artemisinin compounds, oral rehydration solution for childhood diarrhea, hand washing with soap, and oral antibiotics for pneumonia.

conclusionsScaling up CHW programming to increase population-level coverage of life-saving interventions represents a very promising strategy to achieve universal health coverage and end preventable maternal and child deaths by 2030. Numerous practical challenges must be overcome, but there is no better alternative at present. Expanding the coverage of key interventions for maternal nutrition and treatment of childhood illnesses, in particular, may produce the greatest gains. Recognizing the millions of lives of mothers and their young offspring that could be achieved by expanding coverage of evidence-based interventions provided by CHWs and strengthening the CBPHC systems that support them underscores the pressing need for commitment from governments and donors over the next 15 years to prioritize funding, so that robust CHW platforms can be refined, strengthened, and expanded.

Indexed as

Community Health WorkersGlobal HealthAfricaChild MortalityChild, PreschoolEvidence-Based PracticeFemaleHumansInfantInfant MortalityInfant, NewbornMaternal-Child Health ServicesMaternal MortalityPregnancyPrimary Health CareStillbirth

Identifiers

PMID28959436
PMCPMC5592116
OpenAlexW2750852651

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.