Evidence map›Paper›PMID 32381005›Full record

ArticleMalaria journal2020

Improving the efficiency of reactive case detection for malaria elimination in southern Zambia: a cross-sectional study.

Fiona R P Bhondoekhan, Kelly M Searle, Harry Hamapumbu, Mukuma Lubinda, Japhet Matoba, Michael Musonda, Ben Katowa, Timothy M Shields, Tamaki Kobayashi, Douglas E Norris and 5 more

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 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 13% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 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

15 authors at 3 institutions in 2 countries.

Fiona R P BhondoekhanMACS/WIHS Combined Cohort Study, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. Fbhondo1@jhu.edu.
Kelly M SearleMACS/WIHS Combined Cohort Study, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Harry HamapumbuMacha Research Trust, Choma District, Zambia.
Mukuma LubindaMacha Research Trust, Choma District, Zambia.
Japhet MatobaMacha Research Trust, Choma District, Zambia.
Michael MusondaMacha Research Trust, Choma District, Zambia.
Ben KatowaMacha Research Trust, Choma District, Zambia.
Timothy M ShieldsMACS/WIHS Combined Cohort Study, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Tamaki KobayashiMACS/WIHS Combined Cohort Study, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Douglas E NorrisDepartment of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Frank C CurrieroMACS/WIHS Combined Cohort Study, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Jennifer C StevensonMacha Research Trust, Choma District, Zambia.
Philip E ThumaMacha Research Trust, Choma District, Zambia.
William J MossMACS/WIHS Combined Cohort Study, Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0001-6579-3513
Southern and Central Africa International Centers of Excellence for Malaria Research
Johns Hopkins University · USGolden Valley Agricultural Research Trust · ZMUniversity of Minnesota · US

Funding

TransmissionU19AI089680 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WILLIAM J MOSS · 2010 to 2026
$25.6M
National Institute of Allergy and Infectious Diseases U19AI089680NIAID NIH HHS U19 AI089680
6 · The paper itself

Abstract

backgroundReactive case detection (RCD) seeks to enhance malaria surveillance and control by identifying and treating parasitaemic individuals residing near index cases. In Zambia, this strategy starts with passive detection of symptomatic incident malaria cases at local health facilities or by community health workers, with subsequent home visits to screen-and-treat residents in the index case and neighbouring (secondary) households within a 140-m radius using rapid diagnostic tests (RDTs). However, a small circular radius may not be the most efficient strategy to identify parasitaemic individuals in low-endemic areas with hotspots of malaria transmission. To evaluate if RCD efficiency could be improved by increasing the probability of identifying parasitaemic residents, environmental risk factors and a larger screening radius (250 m) were assessed in a region of low malaria endemicity.

methodsBetween January 12, 2015 and July 26, 2017, 4170 individuals residing in 158 index and 531 secondary households were enrolled and completed a baseline questionnaire in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia. Plasmodium falciparum prevalence was measured using PfHRP2 RDTs and quantitative PCR (qPCR). A Quickbird™ high-resolution satellite image of the catchment area was used to create environmental risk factors in ArcGIS, and generalized estimating equations were used to evaluate associations between risk factors and secondary households with parasitaemic individuals.

resultsThe parasite prevalence in secondary (non-index case) households was 0.7% by RDT and 1.8% by qPCR. Overall, 8.5% (n = 45) of secondary households had at least one resident with parasitaemia by qPCR or RDT. The risk of a secondary household having a parasitaemic resident was significantly increased in proximity to higher order streams and marginally with increasing distance from index households. The adjusted OR for proximity to third- and fifth-order streams were 2.97 (95% CI 1.04-8.42) and 2.30 (95% CI 1.04-5.09), respectively, and that for distance to index households for each 50 m was 1.24 (95% CI 0.98-1.58).

conclusionApplying proximity to streams as a screening tool, 16% (n = 3) more malaria-positive secondary households were identified compared to using a 140-m circular screening radius. This analysis highlights the potential use of environmental risk factors as a screening strategy to increase RCD efficiency.

Indexed as

AdolescentAdultChildChild, PreschoolCross-Sectional StudiesDiagnostic Tests, RoutineDisease EradicationHumansInfantInfant, NewbornMalaria, FalciparumMiddle AgedPlasmodium falciparumPrevalenceYoung AdultZambiaEliminationEnvironmentMalariaReactive case detectionScreeningZambia

Identifiers

PMID32381005
PMCPMC7206707
OpenAlexW3021055111

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.