Evidence map›Paper›PMID 32070357›Full record

ArticleMalaria journal2020

Evaluating malaria programmes in moderate- and low-transmission settings: practical ways to generate robust evidence.

Ruth A Ashton, Debra Prosnitz, Andrew Andrada, Samantha Herrera, Yazoumé Yé

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 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 3 institutions in 1 country.

Ruth A AshtonMEASURE Evaluation, Center for Applied Malaria Research and Evaluation, Tulane School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2300, New Orleans, LA, USA. rashton@tulane.edu.ORCID http://orcid.org/0000-0002-7248-7730
Debra ProsnitzMEASURE Evaluation, ICF, Rockville, MD, USA.
Andrew AndradaMEASURE Evaluation, ICF, Rockville, MD, USA.
Samantha HerreraMEASURE Evaluation, ICF, Rockville, MD, USA.
Yazoumé YéMEASURE Evaluation, ICF, Rockville, MD, USA.
ICF International (United States) · USSave the Children · USTulane University · US

Funding

United States Agency for International Development AIDOAA-L-14-00004
6 · The paper itself

Abstract

backgroundMany countries have made substantial progress in scaling-up and sustaining malaria intervention coverage, leading to more focalized and heterogeneous transmission in many settings. Evaluation provides valuable information for programmes to understand if interventions have been implemented as planned and with quality, if the programme had the intended impact on malaria burden, and to guide programmatic decision-making. Low-, moderate-, and heterogeneous-transmission settings present unique evaluation challenges because of dynamic and targeted intervention strategies. This paper provides illustration of evaluation approaches and methodologies for these transmission settings, and suggests how to answer evaluation questions specific to the local context.

methodsThe Roll Back Malaria Monitoring and Evaluation Reference Group formed a task force in October 2017 to lead development of this framework. The task force includes representatives from National Malaria Programmes, funding agencies, and malaria research and implementing partners. The framework builds on existing guidance for process and outcome evaluations and impact evaluations specifically in high transmission settings.

resultsThe theory of change describes how evaluation questions asked by national malaria programmes in different contexts influence evaluation design. The transmission setting, existing stratification, and data quality and availability are also key considerations. The framework is intended for adaption by countries to their local context, and use for evaluation at sub-national level. Confirmed malaria incidence is recommended as the primary impact indicator due to its sensitivity to detect changes in low-transmission settings. It is expected that process evaluations provide sufficient evidence for programme monitoring and improvement, while impact evaluations are needed following adoption of new mixes of interventions, operational strategies, tools or policies, particularly in contexts of changing malaria epidemiology. Impact evaluations in low-, moderate-, or heterogeneous-transmission settings will likely use plausibility designs, and methods highlighted by the framework include interrupted time series, district-level dose-response analyses, and constructed control methods. Triangulating multiple data sources and analyses is important to strengthen the plausibility argument.

conclusionsThis framework provides a structure to assist national malaria programmes and partners to design evaluations in low-, moderate- or heterogeneous-transmission settings. Emphasizing a continuous cycle along the causal pathway linking process evaluation to impact evaluation and then programmatic decision-making, the framework provides practical guidance in evaluation design, analysis, and interpretation to ensure that the evaluation meets national malaria programme priority questions and guides decision-making at national and sub-national levels.

Indexed as

National Health ProgramsProgram EvaluationCommunicable Disease ControlHumansMalariaDecision-makingImpact evaluationLow transmissionMalaria interventionsModerate transmissionMonitoring evaluationProcess evaluationRoutine health information systems (RHIS)Surveillance

Identifiers

PMID32070357
PMCPMC7027277
OpenAlexW3012666603

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.