Analysis of contamination in cluster randomized trials of malaria interventions.
Malaria
Mosquitoes
Nonlinear analysis
Sigmoid random effects analysis
Simulation study
Journal
Trials
ISSN: 1745-6215
Titre abrégé: Trials
Pays: England
ID NLM: 101263253
Informations de publication
Date de publication:
10 Sep 2021
10 Sep 2021
Historique:
received:
19
08
2020
accepted:
13
08
2021
entrez:
11
9
2021
pubmed:
12
9
2021
medline:
15
9
2021
Statut:
epublish
Résumé
In cluster randomized trials (CRTs) of interventions against malaria, mosquito movement between households ultimately leads to contamination between intervention and control arms, unless they are separated by wide buffer zones. This paper proposes a method for adjusting estimates of intervention effectiveness for contamination and for estimating a contamination range between intervention arms, the distance over which contamination measurably biases the estimate of effectiveness. A sigmoid function is fitted to malaria prevalence or incidence data as a function of the distance of households to the intervention boundary, stratified by intervention status and including a random effect for the clustering. The method is evaluated in a simulation study, corresponding to a range of rural settings with varying intervention effectiveness and contamination range, and applied to a CRT of insecticide treated nets in Ghana. The simulations indicate that the method leads to approximately unbiased estimates of effectiveness. Precision decreases with increasing mosquito movement, but the contamination range is much smaller than the maximum distance traveled by mosquitoes. For the method to provide precise and approximately unbiased estimates, at least 50% of the households should be at distances greater than the estimated contamination range from the discordant intervention arm. A sigmoid approach provides an appropriate analysis for a CRT in the presence of contamination. Outcome data from boundary zones should not be discarded but used to provide estimates of the contamination range. This gives an alternative to "fried egg" designs, which use large clusters (increasing costs) and exclude buffer zones to avoid bias.
Sections du résumé
BACKGROUND
BACKGROUND
In cluster randomized trials (CRTs) of interventions against malaria, mosquito movement between households ultimately leads to contamination between intervention and control arms, unless they are separated by wide buffer zones.
METHODS
METHODS
This paper proposes a method for adjusting estimates of intervention effectiveness for contamination and for estimating a contamination range between intervention arms, the distance over which contamination measurably biases the estimate of effectiveness. A sigmoid function is fitted to malaria prevalence or incidence data as a function of the distance of households to the intervention boundary, stratified by intervention status and including a random effect for the clustering. The method is evaluated in a simulation study, corresponding to a range of rural settings with varying intervention effectiveness and contamination range, and applied to a CRT of insecticide treated nets in Ghana.
RESULTS
RESULTS
The simulations indicate that the method leads to approximately unbiased estimates of effectiveness. Precision decreases with increasing mosquito movement, but the contamination range is much smaller than the maximum distance traveled by mosquitoes. For the method to provide precise and approximately unbiased estimates, at least 50% of the households should be at distances greater than the estimated contamination range from the discordant intervention arm.
CONCLUSIONS
CONCLUSIONS
A sigmoid approach provides an appropriate analysis for a CRT in the presence of contamination. Outcome data from boundary zones should not be discarded but used to provide estimates of the contamination range. This gives an alternative to "fried egg" designs, which use large clusters (increasing costs) and exclude buffer zones to avoid bias.
Identifiants
pubmed: 34507602
doi: 10.1186/s13063-021-05543-8
pii: 10.1186/s13063-021-05543-8
pmc: PMC8434732
doi:
Substances chimiques
Insecticides
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
613Subventions
Organisme : Schweizerischer Nationalfonds zur F?rderung der Wissenschaftlichen Forschung
ID : 310030_162837
Informations de copyright
© 2021. The Author(s).
Références
Biometrics. 1986 Mar;42(1):121-30
pubmed: 3719049
Emerg Themes Epidemiol. 2017 Sep 21;14:12
pubmed: 28947911
Am J Trop Med Hyg. 1998 Jul;59(1):80-5
pubmed: 9684633
Trans R Soc Trop Med Hyg. 2000 Jul-Aug;94(4):357-60
pubmed: 11127232
Sci Rep. 2015 Dec 03;5:17581
pubmed: 26631604
Epidemiology. 1991 Sep;2(5):331-8
pubmed: 1742381
J Infect Dis. 2016 Dec 15;214(12):1831-1839
pubmed: 27923947
Parasit Vectors. 2019 Sep 3;12(1):421
pubmed: 31477155
Contemp Clin Trials. 2007 Feb;28(2):182-91
pubmed: 16829207
Vaccine. 2015 Mar 24;33(13):1518-26
pubmed: 25681064
Am J Epidemiol. 1981 Dec;114(6):906-14
pubmed: 7315838
PLoS Negl Trop Dis. 2012;6(11):e1937
pubmed: 23209869
Stat Med. 2006 Dec 30;25(24):4279-92
pubmed: 16947139
Int J Epidemiol. 2018 Dec 1;47(6):2015-2024
pubmed: 30376050
Trop Med Int Health. 1996 Apr;1(2):147-54
pubmed: 8665378
Am J Trop Med Hyg. 2019 Dec;101(6):1434-1441
pubmed: 31595867
Am J Trop Med Hyg. 2003 Apr;68(4 Suppl):121-7
pubmed: 12749495
PLoS One. 2015 Nov 16;10(11):e0142671
pubmed: 26569492
Stat Med. 2019 May 20;38(11):2074-2102
pubmed: 30652356
Biometrika. 1949 Jun;36(Pt. 1-2):18-25
pubmed: 18146215
Trials. 2016 Jun 06;17(1):278
pubmed: 27266269
Int J Epidemiol. 1999 Apr;28(2):319-26
pubmed: 10342698
BMC Med. 2017 Dec 29;15(1):223
pubmed: 29287587
Lancet. 2018 Apr 21;391(10130):1577-1588
pubmed: 29655496
Lancet. 2016 Sep 17;388(10050):1193-201
pubmed: 27520594