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dc.contributor.authorBostoen, K
dc.contributor.authorChalabi, Z
dc.contributor.authorGrais, R
dc.date.accessioned2009-03-06T15:53:18Z
dc.date.available2009-03-06T15:53:18Z
dc.date.issued2007-06
dc.date.submitted2009-03-04
dc.identifier.citationOptimisation of the T-square sampling method to estimate population sizes. 2007, 4:7notEmerg Themes Epidemiolen
dc.identifier.issn1742-7622
dc.identifier.pmid17543101
dc.identifier.doi10.1186/1742-7622-4-7
dc.identifier.urihttp://hdl.handle.net/10144/52694
dc.description.abstractPopulation size and density estimates are needed to plan resource requirements and plan health related interventions. Sampling frames are not always available necessitating surveys using non-standard household sampling methods. These surveys are time-consuming, difficult to validate, and their implementation could be optimised. Here, we discuss an example of an optimisation procedure for rapid population estimation using T-Square sampling which has been used recently to estimate population sizes in emergencies. A two-stage process was proposed to optimise the T-Square method wherein the first stage optimises the sample size and the second stage optimises the pathway connecting the sampling points. The proposed procedure yields an optimal solution if the distribution of households is described by a spatially homogeneous Poisson process and can be sub-optimal otherwise. This research provides the first step in exploring how optimisation techniques could be applied to survey designs thereby providing more timely and accurate information for planning interventions.
dc.description.sponsorshipEpicentreen
dc.language.isoenen
dc.publisherBioMed Centralen
dc.rightsArchived with thanks to Emerging Themes in Epidemiology and Open Access.en
dc.subjectPopulation estimationen
dc.titleOptimisation of the T-square sampling method to estimate population sizes.en
dc.typeArticleen
dc.contributor.departmentDepartment of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. Kristof.Bostoen@lshtm.ac.uken
dc.identifier.journalEmerging Themes in Epidemiologyen
refterms.dateFOA2019-03-04T12:17:51Z
html.description.abstractPopulation size and density estimates are needed to plan resource requirements and plan health related interventions. Sampling frames are not always available necessitating surveys using non-standard household sampling methods. These surveys are time-consuming, difficult to validate, and their implementation could be optimised. Here, we discuss an example of an optimisation procedure for rapid population estimation using T-Square sampling which has been used recently to estimate population sizes in emergencies. A two-stage process was proposed to optimise the T-Square method wherein the first stage optimises the sample size and the second stage optimises the pathway connecting the sampling points. The proposed procedure yields an optimal solution if the distribution of households is described by a spatially homogeneous Poisson process and can be sub-optimal otherwise. This research provides the first step in exploring how optimisation techniques could be applied to survey designs thereby providing more timely and accurate information for planning interventions.


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