Evidence map›Paper›PMID 27965266›Full record

ArticleGlobal health, science and practice2016

Indoor Residual Spraying Delivery Models to Prevent Malaria: Comparison of Community- and District-Based Approaches in Ethiopia.

Benjamin Johns, Yemane Yeebiyo Yihdego, Lena Kolyada, Dereje Dengela, Sheleme Chibsa, Gunawardena Dissanayake, Kristen George, Hiwot Solomon Taffese, Bradford Lucas

Abstract readComparative Study
In one paragraph

Article in Global health, science and practice, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
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  8. Article
  9. New Ways of Approaching Indoor Residual Spraying for Malaria.Global health, science and practice · 2016
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Benjamin JohnsAbt Associates, Inc., The President's Malaria Initiative Africa Indoor Residual Spraying Project, Bethesda, MD, USA.
Yemane Yeebiyo YihdegoAbt Associates, Inc., The President's Malaria Initiative Africa Indoor Residual Spraying Project, Addis Ababa, Ethiopia.
Lena KolyadaAbt Associates, Inc., The President's Malaria Initiative Africa Indoor Residual Spraying Project, Bethesda, MD, USA. lena_kolyada@abtassoc.com.
Dereje DengelaAbt Associates, Inc., The President's Malaria Initiative Africa Indoor Residual Spraying Project, Bethesda, MD, USA.
Sheleme ChibsaU.S. President's Malaria Initiative, U.S. Agency for International Development, Addis Ababa, Ethiopia.
Gunawardena DissanayakeU.S. President's Malaria Initiative, U.S. Agency for International Development, Addis Ababa, Ethiopia.
Kristen GeorgeU.S. President's Malaria Initiative, U.S. Agency for International Development, Bureau for Global Health, Office of Health, Infectious Disease & Nutrition, Arlington, VA, USA.
Hiwot Solomon TaffeseNational Malaria Control Program, Federal Ministry of Health, Addis Ababa, Ethiopia.
Bradford LucasAbt Associates, Inc., The President's Malaria Initiative Africa Indoor Residual Spraying Project, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndoor residual spraying (IRS) for malaria prevention has traditionally been implemented in Ethiopia by the district health office with technical and operational inputs from regional, zonal, and central health offices. The United States President's Malaria Initiative (PMI) in collaboration with the Government of Ethiopia tested the effectiveness and efficiency of integrating IRS into the government-funded community-based rural health services program.

methodsBetween 2012 and 2014, PMI conducted a mixed-methods study in 11 districts of Oromia region to compare district-based IRS (DB IRS) and community-based IRS (CB IRS) models. In the DB IRS model, each district included 2 centrally located operational sites where spray teams camped during the IRS campaign and from which they traveled to the villages to conduct spraying. In the CB IRS model, spray team members were hired from the communities in which they operated, thus eliminating the need for transport and camping facilities. The study team evaluated spray coverage, the quality of spraying, compliance with environmental and safety standards, and cost and performance efficiency.

resultsThe average number of eligible structures found and sprayed in the CB IRS districts increased by 19.6% and 20.3%, respectively, between 2012 (before CB IRS) and 2013 (during CB IRS). Between 2013 and 2014, the numbers increased by about 14%. In contrast, in the DB IRS districts the number of eligible structures found increased by only 8.1% between 2012 and 2013 and by 0.4% between 2013 and 2014. The quality of CB IRS operations was good and comparable to that in the DB IRS model, according to wall bioassay tests. Some compliance issues in the first year of CB IRS implementation were corrected in the second year, bringing compliance up to the level of the DB IRS model. The CB IRS model had, on average, higher amortized costs per district than the DB IRS model but lower unit costs per structure sprayed and per person protected because the community-based model found and sprayed more structures.

conclusionEstablished community-based service delivery systems can be adapted to include a seasonal IRS campaign alongside the community-based health workers' routine activities to improve performance efficiency. Further modifications of the community-based IRS model may reduce the total cost of the intervention and increase its financial sustainability.

Indexed as

Community Health ServicesEthiopiaHumansInsecticidesMalariaMosquito ControlRural PopulationTreatment OutcomeInsecticides

Identifiers

PMID27965266
PMCPMC5199172

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LicenceCC BY
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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.