Feb 15, 2024
Scoping Review: Analytical Approaches to Estimating Malaria Intervention Effectiveness and Impact
- Jessica Craig1,
- Donal Bisanzio1,
- Richard Reithinger1
- 1RTI International
Protocol Citation: Jessica Craig, Donal Bisanzio, Richard Reithinger 2024. Scoping Review: Analytical Approaches to Estimating Malaria Intervention Effectiveness and Impact. protocols.io https://dx.doi.org/10.17504/protocols.io.36wgq38nolk5/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 03, 2024
Last Modified: February 15, 2024
Protocol Integer ID: 94642
Keywords: malaria, intervention, coverage, effectiveness, estimating malaria intervention effectiveness, impact of malaria intervention, malaria intervention effectiveness, malaria intervention, national malaria control program, national malaria control, analysis extension for scoping review, objective of this scoping review, impact of intervention, scoping review, systematic review, items for systematic review, objective of this scoping, preferred reporting, scoping, ministries of health, health management information system
Funders Acknowledgements:
United States Agency for International Development
Grant ID: 7200AA20CA00009
Abstract
Context: Ministries of Health and National Malaria Control
Programs need simple approaches to be able to regularly estimate the
effectiveness and impact of malaria interventions. Traditionally, this has been
done by analyzing data from post-intervention campaign surveys or periodic
nationally-representative surveys, or estimated by complex mathematical
modelling. As health management information systems collecting routine
programmatic data are maturing, there increasingly is an opportunity to use
these data to measure effectiveness and impact of interventions more
continuously and readily. The objective of this scoping review is to map and
summarize the different analytical approaches for estimating the
effectiveness and impact of malaria interventions using routine surveillance and health
management information system data.
Methods: We will follow the PRISMA-ScR (Preferred Reporting
Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews)
to conduct and report this scoping review.
Attachments
Troubleshooting
Rationale
Malaria is an acute febrile illness caused by a parasitic
infection transmitted by Anopheles mosquitoes. Human malaria is caused by five
different Plasmodium parasites, with P. falciparum being the predominant
species in sub-Saharan Africa (SSA) [1]. In the past 15–20 years, the combined
efforts of Ministries of Health (MOHs) and National Malaria Control Programs
(NMCPs), and their partners, including PMI, have made tremendous progress
against malaria. This progress resulted from the massive scale-up of various
malaria prevention and control interventions, including facility and
community-based confirmatory testing and treatment of malaria cases,
intermittent preventive treatment in pregnancy (IPTp), and seasonal malaria
chemoprevention (SMC), along with indoor residual spraying (IRS) and
insecticide-treated nets (ITNs).
MOH / NMCPs use programmatic intervention coverage and
effectiveness data to regularly monitor impact of interventions; modify
intervention implementation approaches (e.g., if coverage estimates are
sub-par) or switch interventions altogether (e.g., if effectiveness is observed
to be lower than expected). Intervention coverage and effectiveness has
traditionally been assessed by post-intervention campaign surveys or periodic
nationally-representative surveys (e.g., Demographic and Health Surveys [DHS],
Malaria Indicator Surveys [MIS], Multiple Indicator Cluster Surveys [MICS]), or
estimated by complex mathematical modelling. The limitations of surveys are
that—while generally robust—they only occur every 2–5 years; take time; require
significant human, logistical and financial resources and capabilities; and may
not be powered sufficiently enough to provide sub-national intervention
estimates. Similarly, mathematical modelling may be limited by the available
data and the significant technical expertise needed to develop and run the
models, let alone run them continuously. Additionally, neither surveys or
modeling may avail necessary estimates at key strategic moments in the malaria
programming planning, implementation and monitoring cycle, such as the
development of national strategies or design of necessary donor documents
(e.g., Global Fund Concept Notes or PMI Malaria Operational Plans).
Countries health
management information systems (HMIS) have been dramatically strengthened in
the past few years, with countries being able to consistently and fully report
on outpatient, inpatient and other programmatic data—much of this progress has
been made by adopting, piloting and rolling out the district health management
information system 2 (DHIS2), an open-source data-system software specifically
developed to capture health data in lower-and-middle income countries. Because
of their sheer volume across space and time, data collected and reported through
HMIS like DHIS2 complement and even offer an alternative to nationally
representative and other ad hoc surveys to assess health intervention coverage
and effectiveness, and ultimately impact on health outcomes. [2–4]
Objectives
The objective of this scoping review is to map and summarize different
analytical approaches for estimating the impact and effectiveness of malaria
interventions using routine surveillance and health management information
system data. To our knowledge, such review has not been conducted. A
preliminary search for existing scoping and systematic reviews on the topic was
conducted on December 15, 2023, using PubMed and no similar reviews were found.
We will follow the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews
and Meta-Analysis extension for Scoping Reviews) to conduct and report this
scoping review [5].
Information Sources
A systematic search of PubMed was conducted on January 2,
2024, to identify studies and analyses that had used routine surveillance and
health management information systems data to assess the effectiveness of
malaria interventions. A detailed search strategy was designed and piloted to
identify the optimal combination of keywords used.
Search Strategy
We examined the available electronic databases using
combination searches of the following Boolean terms: “Malaria” AND
“Intervention” AND “effect*” OR “impact*” AND “System” OR “Surveillance.” Other
key terms for such as "routine” or “information systems” control were not
included in the search strategy to have a more comprehensive search and will be
used during abstract and full text screening.
Study Records
All identified studies will be imported into Rayyan, a systematic review
management software, to screen (title, abstract, and full text) and manage the
results of the search. Two reviewers will independently assess the titles and
abstracts of the included articles based on the inclusion criteria. In the
event of discordance between the two reviewers, a third reviewer will review
the titles and abstracts and will come to a final decision. From the included
articles, the two reviewers will identify relevant publications by reviewing
the full text. Any discordance will again be resolved by a third reviewer. A
PRISMA flow diagram will be used to report final numbers of articles that are
included and excluded at each stage.
Eligibility Criteria
We limited inclusion to studies and analyses that were
conducted in the past decade (i.e., 2014), which we purposefully chose as a
time point when countries’ routine health management information systems had
begun to substantially mature, with data reported by these systems
progressively becoming more robust.
Data Items
From the included articles, each reviewer will work
independently to extract data from the articles following a pre-specified
extraction sheet. The following data will be extracted from each paper into an
MS Excel spreadsheet: (1) author; (2) year of publication; (3) geography; (4)
study design; (5) study period / time period covered; (6) intervention(s) for
which effectiveness and impact was measured; (7) approach to measure
effectiveness and impact; (8) health information system platform used for
analyses; (9) indicator variables included in the analyses; (10) target
population; (11) key findings; and (12) items from the Template for
Intervention Description and Replication (TIDieR) checklist. TIDieR is a
12-item checklist that includes the brief name, why, what (materials), what
(procedure), who provided, how, where, when and how much, tailoring,
modifications, how well (planned), how well (actual) of a program.
Data Synthesis
The proposed scoping review will outline the approaches to
estimate the effectiveness of malaria interventions using routine surveillance
and health management information systems data. The scoping review does not
involve data on human subjects and ethical approval is not required.
Protocol references
- World Health Organization (2023) World Malaria Report 2022.
- Mwinnyaa G, Hazel E, Maïga A, Amouzou A (2021) Estimating population-based coverage of reproductive, maternal, newborn, and child health (RMNCH) interventions from health management information systems: a comprehensive review. BMC Health Serv Res. 21( Suppl 2): 1083.
- Epstein A, Namuganga JF, Kamya EV, Nankabirwa JI, Bhatt S, Rodriguez-Barraquer I, Staedke SG, Kamya MR, Dorsey G, Greenhouse B (2020) Estimating malaria incidence from routine health facility-based surveillance data in Uganda. Malar J. 19: 445.
- Ashton RA, Bennett A, Yukich J, Bhattarai A, Keating J, Eisele TP (2017) Methodological Considerations for Use of Routine Health Information System Data to Evaluate Malaria Program Impact in an Era of Declining Malaria Transmission. Am J Trop Med Hyg. 97 (3_Suppl): 46-57.
- PRISMA [Internet]. [cited 2021 Dec 2]. Available from: http://www.prismastatement.org/Extensions/ScopingReviews