Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.

<h4>Background</h4>Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF), generally collected using the recommended gold-standard cluster randomized surveys (CRS). Integrated Threshold Mapping (ITM) has been...

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Autores principales:	Jennifer L Smith, Hugh J W Sturrock, Casey Olives, Anthony W Solomon, Simon J Brooker
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/9070c33f2c234aed82b4dc83d67f2fea
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spelling	oai:doaj.org-article:9070c33f2c234aed82b4dc83d67f2fea2021-11-18T09:16:59ZComparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.1935-27271935-273510.1371/journal.pntd.0002389https://doaj.org/article/9070c33f2c234aed82b4dc83d67f2fea2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23991238/pdf/?tool=EBIhttps://doaj.org/toc/1935-2727https://doaj.org/toc/1935-2735<h4>Background</h4>Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF), generally collected using the recommended gold-standard cluster randomized surveys (CRS). Integrated Threshold Mapping (ITM) has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1-9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters.<h4>Methodology/principal findings</h4>Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i) the district prevalence of TF; (ii) the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii) the enrollment rate in schools.<h4>Conclusions/significance</h4>Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates the use of a simulated approach in addressing operational research questions for trachoma but also other NTDs.Jennifer L SmithHugh J W SturrockCasey OlivesAnthony W SolomonSimon J BrookerPublic Library of Science (PLoS)articleArctic medicine. Tropical medicineRC955-962Public aspects of medicineRA1-1270ENPLoS Neglected Tropical Diseases, Vol 7, Iss 8, p e2389 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270
spellingShingle	Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Jennifer L Smith Hugh J W Sturrock Casey Olives Anthony W Solomon Simon J Brooker Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
description	<h4>Background</h4>Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF), generally collected using the recommended gold-standard cluster randomized surveys (CRS). Integrated Threshold Mapping (ITM) has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1-9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters.<h4>Methodology/principal findings</h4>Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i) the district prevalence of TF; (ii) the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii) the enrollment rate in schools.<h4>Conclusions/significance</h4>Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates the use of a simulated approach in addressing operational research questions for trachoma but also other NTDs.
format	article
author	Jennifer L Smith Hugh J W Sturrock Casey Olives Anthony W Solomon Simon J Brooker
author_facet	Jennifer L Smith Hugh J W Sturrock Casey Olives Anthony W Solomon Simon J Brooker
author_sort	Jennifer L Smith
title	Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
title_short	Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
title_full	Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
title_fullStr	Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
title_full_unstemmed	Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
title_sort	comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/9070c33f2c234aed82b4dc83d67f2fea
work_keys_str_mv	AT jenniferlsmith comparingtheperformanceofclusterrandomsamplingandintegratedthresholdmappingfortargetingtrachomacontrolusingcomputersimulation AT hughjwsturrock comparingtheperformanceofclusterrandomsamplingandintegratedthresholdmappingfortargetingtrachomacontrolusingcomputersimulation AT caseyolives comparingtheperformanceofclusterrandomsamplingandintegratedthresholdmappingfortargetingtrachomacontrolusingcomputersimulation AT anthonywsolomon comparingtheperformanceofclusterrandomsamplingandintegratedthresholdmappingfortargetingtrachomacontrolusingcomputersimulation AT simonjbrooker comparingtheperformanceofclusterrandomsamplingandintegratedthresholdmappingfortargetingtrachomacontrolusingcomputersimulation
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Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.

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