Journal Article > ResearchFull Text
Emerg Themes Epidemiol. 2007 June 1; Volume 4 (Issue 1); DOI:10.1186/1742-7622-4-7
Bostoen K, Chalabi Z, Grais RF
Emerg Themes Epidemiol. 2007 June 1; Volume 4 (Issue 1); DOI:10.1186/1742-7622-4-7
Population 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.
Journal Article > ResearchFull Text
Emerg Themes Epidemiol. 2010 July 19; Volume 7 (Issue 1); 4.; DOI:10.1186/1742-7622-7-4
Cairns KL, Nandy R, Grais RF
Emerg Themes Epidemiol. 2010 July 19; Volume 7 (Issue 1); 4.; DOI:10.1186/1742-7622-7-4
ABSTRACT
Measles, a highly infectious vaccine-preventable viral disease, is potentially fatal. Historically, measles case-fatality ratios (CFRs) have been reported to vary from 0.1% in the developed world to as high as 30% in emergency settings. Estimates of the global burden of mortality from measles, critical to prioritizing measles vaccination among other health interventions, are highly sensitive to the CFR estimates used in modeling; however, due to the lack of reliable, up-to-date data, considerable debate exists as to what CFR estimates are appropriate to use. To determine current measles CFRs in high-burden settings without vital registration we have conducted six retrospective measles mortality studies in such settings. This paper examines the methodological challenges of this work and our solutions to these challenges, including the integration of lessons from retrospective all-cause mortality studies into CFR studies, approaches to laboratory confirmation of outbreaks, and means of obtaining a representative sample of case-patients. Our experiences are relevant to those conducting retrospective CFR studies for measles or other diseases, and to those interested in all-cause mortality studies.
Measles, a highly infectious vaccine-preventable viral disease, is potentially fatal. Historically, measles case-fatality ratios (CFRs) have been reported to vary from 0.1% in the developed world to as high as 30% in emergency settings. Estimates of the global burden of mortality from measles, critical to prioritizing measles vaccination among other health interventions, are highly sensitive to the CFR estimates used in modeling; however, due to the lack of reliable, up-to-date data, considerable debate exists as to what CFR estimates are appropriate to use. To determine current measles CFRs in high-burden settings without vital registration we have conducted six retrospective measles mortality studies in such settings. This paper examines the methodological challenges of this work and our solutions to these challenges, including the integration of lessons from retrospective all-cause mortality studies into CFR studies, approaches to laboratory confirmation of outbreaks, and means of obtaining a representative sample of case-patients. Our experiences are relevant to those conducting retrospective CFR studies for measles or other diseases, and to those interested in all-cause mortality studies.