Evidence map›Paper›PMID 27824885›Full record

Observational studyPLoS medicine2016

Measures of Malaria Burden after Long-Lasting Insecticidal Net Distribution and Indoor Residual Spraying at Three Sites in Uganda: A Prospective Observational Study.

Agaba Katureebe, Kate Zinszer, Emmanuel Arinaitwe, John Rek, Elijah Kakande, Katia Charland, Ruth Kigozi, Maxwell Kilama, Joaniter Nankabirwa, Adoke Yeka and 12 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in PLoS medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 115 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
115citing papers in PubMed, 3 pooled it
15.1field-weighted citation impact, top 1% 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

115 citing papers in PubMed, 3 syntheses or guidelines pooled it, 175 citations in OpenAlex.

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55 more citing papers are in PubMed but not listed here.

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

22 authors at 9 institutions in 3 countries.

Agaba KatureebeInfectious Diseases Research Collaboration, Kampala, Uganda.
Kate ZinszerHealthMap, Boston Children's Hospital, Boston, Massachusetts, United States of America.
Emmanuel ArinaitweInfectious Diseases Research Collaboration, Kampala, Uganda.
John RekInfectious Diseases Research Collaboration, Kampala, Uganda.ORCID http://orcid.org/0000-0003-4063-0763
Elijah KakandeInfectious Diseases Research Collaboration, Kampala, Uganda.ORCID http://orcid.org/0000-0001-9532-5710
Katia CharlandIMS Brogan Health, Montreal, Quebec, Canada.
Ruth KigoziInfectious Diseases Research Collaboration, Kampala, Uganda.
Maxwell KilamaInfectious Diseases Research Collaboration, Kampala, Uganda.
Joaniter NankabirwaInfectious Diseases Research Collaboration, Kampala, Uganda.
Adoke YekaInfectious Diseases Research Collaboration, Kampala, Uganda.
Henry MawejjeInfectious Diseases Research Collaboration, Kampala, Uganda.
Arthur MpimbazaUganda Malaria Surveillance Project, Kampala, Uganda.
Henry KatambaUganda Ministry of Health, Kampala, Uganda.ORCID http://orcid.org/0000-0002-8347-6922
Martin J DonnellyDepartment of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Philip J RosenthalDepartment of Medicine, San Francisco General Hospital, University of California, San Francisco, San Francisco, California, United States of America.
Chris DrakeleyLondon School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID http://orcid.org/0000-0003-4863-075X
Steve W LindsaySchool of Biological and Biomedical Sciences, Durham University, Durham, United Kingdom.
Sarah G StaedkeLondon School of Hygiene and Tropical Medicine, London, United Kingdom.
David L SmithInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
Bryan GreenhouseDepartment of Medicine, San Francisco General Hospital, University of California, San Francisco, San Francisco, California, United States of America.ORCID http://orcid.org/0000-0003-0287-9111
Moses R KamyaInfectious Diseases Research Collaboration, Kampala, Uganda.
Grant DorseyDepartment of Medicine, San Francisco General Hospital, University of California, San Francisco, San Francisco, California, United States of America.
Infectious Diseases Research Collaboration · UGMalaria Consortium · UGSan Francisco General Hospital · USLondon School of Hygiene & Tropical Medicine · GBBoston Children's Hospital · USDurham University · GBLiverpool School of Tropical Medicine · GBMinistry of Health · UGUniversity of Washington · US

Funding

Transmission ProjectU19AI089674 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MATTHEW G DORSEY · 2010 to 2026
$29.3M
NIAID NIH HHS U19 AI089674
6 · The paper itself

Abstract

backgroundLong-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) are the primary vector control interventions used to prevent malaria in Africa. Although both interventions are effective in some settings, high-quality evidence is rarely available to evaluate their effectiveness following deployment by a national malaria control program. In Uganda, we measured changes in key malaria indicators following universal LLIN distribution in three sites, with the addition of IRS at one of these sites. METHODS AND

findingsComprehensive malaria surveillance was conducted from October 1, 2011, to March 31, 2016, in three sub-counties with relatively low (Walukuba), moderate (Kihihi), and high transmission (Nagongera). Between 2013 and 2014, universal LLIN distribution campaigns were conducted in all sites, and in December 2014, IRS with the carbamate bendiocarb was initiated in Nagongera. High-quality surveillance evaluated malaria metrics and mosquito exposure before and after interventions through (a) enhanced health-facility-based surveillance to estimate malaria test positivity rate (TPR), expressed as the number testing positive for malaria/number tested for malaria (number of children tested for malaria: Walukuba = 42,833, Kihihi = 28,790, and Nagongera = 38,690); (b) cohort studies to estimate the incidence of malaria, expressed as the number of episodes per person-year [PPY] at risk (number of children observed: Walukuba = 340, Kihihi = 380, and Nagongera = 361); and (c) entomology surveys to estimate household-level human biting rate (HBR), expressed as the number of female Anopheles mosquitoes collected per house-night of collection (number of households observed: Walukuba = 117, Kihihi = 107, and Nagongera = 107). The LLIN distribution campaign substantially increased LLIN coverage levels at the three sites to between 65.0% and 95.5% of households with at least one LLIN. In Walukuba, over the 28-mo post-intervention period, universal LLIN distribution was associated with no change in the incidence of malaria (0.39 episodes PPY pre-intervention versus 0.20 post-intervention; adjusted rate ratio [aRR] = 1.02, 95% CI 0.36-2.91, p = 0.97) and non-significant reductions in the TPR (26.5% pre-intervention versus 26.2% post-intervention; aRR = 0.70, 95% CI 0.46-1.06, p = 0.09) and HBR (1.07 mosquitoes per house-night pre-intervention versus 0.71 post-intervention; aRR = 0.41, 95% CI 0.14-1.18, p = 0.10). In Kihihi, over the 21-mo post-intervention period, universal LLIN distribution was associated with a reduction in the incidence of malaria (1.77 pre-intervention versus 1.89 post-intervention; aRR = 0.65, 95% CI 0.43-0.98, p = 0.04) but no significant change in the TPR (49.3% pre-intervention versus 45.9% post-intervention; aRR = 0.83, 95% 0.58-1.18, p = 0.30) or HBR (4.06 pre-intervention versus 2.44 post-intervention; aRR = 0.71, 95% CI 0.30-1.64, p = 0.40). In Nagongera, over the 12-mo post-intervention period, universal LLIN distribution was associated with a reduction in the TPR (45.3% pre-intervention versus 36.5% post-intervention; aRR = 0.82, 95% CI 0.76-0.88, p < 0.001) but no significant change in the incidence of malaria (2.82 pre-intervention versus 3.28 post-intervention; aRR = 1.10, 95% 0.76-1.59, p = 0.60) or HBR (41.04 pre-intervention versus 20.15 post-intervention; aRR = 0.87, 95% CI 0.31-2.47, p = 0.80). The addition of three rounds of IRS at ~6-mo intervals in Nagongera was followed by clear decreases in all outcomes: incidence of malaria (3.25 pre-intervention versus 0.63 post-intervention; aRR = 0.13, 95% CI 0.07-0.27, p < 0.001), TPR (37.8% pre-intervention versus 15.0% post-intervention; aRR = 0.54, 95% CI 0.49-0.60, p < 0.001), and HBR (18.71 pre-intervention versus 3.23 post-intervention; aRR = 0.29, 95% CI 0.17-0.50, p < 0.001). High levels of pyrethroid resistance were documented at all three study sites. Limitations of the study included the observational study design, the lack of contemporaneous control groups, and that the interventions were implemented under programmatic conditions.

conclusionsUniversal distribution of LLINs at three sites with varying transmission intensity was associated with modest declines in the burden of malaria for some indicators, but the addition of IRS at the highest transmission site was associated with a marked decline in the burden of malaria for all indicators. In highly endemic areas of Africa with widespread pyrethroid resistance, IRS using alternative insecticide formulations may be needed to achieve substantial gains in malaria control.

Indexed as

InsecticidesMosquito ControlPopulation SurveillanceChildChild, PreschoolCohort StudiesCross-Sectional StudiesFemaleHumansIncidenceInfantInsecticide-Treated BednetsMalariaMaleProspective StudiesUgandaInsecticides

Identifiers

PMID27824885
PMCPMC5100985
OpenAlexW2517961452

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.