Evidence map›Paper›PMID 26376980›Full record

ArticleMalaria journal2015

Open-source satellite enumeration to map households: planning and targeting indoor residual spraying for malaria.

Aniset Kamanga, Silvia Renn, Derek Pollard, Daniel J Bridges, Brian Chirwa, Jessie Pinchoff, David A Larsen, Anna M Winters

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

28 citing papers in PubMed, 46 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

8 authors at 3 institutions in 1 country.

Aniset KamangaAkros, Cresta Golfview Grounds, Great East Road, Unit 5, Lusaka, Zambia. akamanga@akros.com.
Silvia RennAkros, Cresta Golfview Grounds, Great East Road, Unit 5, Lusaka, Zambia. silvia.renn@gmail.com.
Derek PollardAkros, Cresta Golfview Grounds, Great East Road, Unit 5, Lusaka, Zambia. dpollard@akros.com.
Daniel J BridgesAkros, Cresta Golfview Grounds, Great East Road, Unit 5, Lusaka, Zambia. dbridges@akros.com.
Brian ChirwaPresidents Malaria Initiative, Africa Indoor Residual Spray Project, Bethesda, USA. brian_chirwa@africairs.net.
Jessie PinchoffJohn Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. jpinchoff@gmail.com.
David A LarsenAkros, Cresta Golfview Grounds, Great East Road, Unit 5, Lusaka, Zambia. dlarsen@akros.com.
Anna M WintersAkros, Cresta Golfview Grounds, Great East Road, Unit 5, Lusaka, Zambia. awinters@akros.com.
Johns Hopkins University · USSyracuse University · USU.S. President's Malaria Initiative · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDefining the number and location of sprayable structures (houses) is foundational to plan and monitor indoor residual spray (IRS) implementation, a primary intervention used to control the transmission of malaria. Only by mapping the location and type of all sprayable structures can IRS operations be planned, estimates of spray coverage determined, and targeted delivery of IRS to specific locations be achieved. Previously, field-based enumeration has been used to guide IRS campaigns, however, this approach is costly, time-consuming and difficult to scale. As a result, field-based enumeration typically fails to map all structures in a given area, making estimations less reliable and reducing the enumerated coverage.

methodsUsing open source satellite imagery and Geographic Information System software, satellite enumeration was conducted to guide IRS operations in 15 districts (91,302 km(2)) in northern Zambia during the 2014 spray season. Cost of satellite enumeration was compared to standard enumeration. Enumerated households were sampled to estimate sprayable surface area and wall type from the satellite enumeration using linear and logistic regression, respectively.

resultsIn comparison to the traditional field-based enumeration procedure, satellite-based enumeration was 22 times faster, and 10 times less costly. An estimated 98 % of the satellite enumerated buildings correctly classified roof type. Predicted surface area of each household correlated at a value of 0.91 with measured surface area of each household.

conclusionFor IRS campaigns, high quality and high coverage enumeration data aid in planning, through informed insecticide procurement. Through the identification of geographical areas and populations to target, enumeration data guide operations and assist monitoring and evaluation of IRS through the unbiased estimation of coverage achieved. Satellite enumeration represents a quick, cheap and accurate system to provide these data, and has potential applications beyond IRS for delivery of other targeted or non-targeted interventions (e.g. net distributions, mass drug administration, immunization campaigns, or even sampling frames for field studies).

Indexed as

Geographic Information SystemsMosquito ControlHumansInsecticidesMalariaZambiaInsecticides

Identifiers

PMID26376980
PMCPMC4574022
OpenAlexW2139769744

What OpenQuestion holds

Textmetadata
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.