Total: 126
Treatment-seeking behaviour in low- and middle-income countries estimated using a Bayesian model
BMC Medical Research Methodology. 2017 17:67 .
Author(s): Victor A. Alegana author, Jim Wright, Carla Pezzulo, Andrew J. Tatem and Peter M. Atkinson
Type: method. Year: 2017
DOI: 10.1186/s12874-017-0346-0.

Abstract: Seeking treatment in formal healthcare for uncomplicated infections is vital to combating disease in low- and middle-income countries (LMICs). Healthcare treatment-seeking behaviour varies within and between communities and is modified by socio-economic, demographic, and physical factors. As a result, it remains a challenge to quantify healthcare treatment-seeking behaviour using a metric that is comparable across communities. Here, we present an application for transforming individual categorical responses (actions related to fever) to a continuous probabilistic estimate of fever treatment for one country in Sub-Saharan Africa (SSA).
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Sub-national mapping of population pyramids and dependency ratios in Africa and Asia
Scientific Data 4, Article number: 170089 (2017).
Author(s): Carla Pezzulo, Graeme M. Hornby, Alessandro Sorichetta, Andrea E. Gaughan, Catherine Linard, Tomas J. Bird, David Kerr, Christopher T. Lloyd & Andrew J. Tatem.
Type: method. Year: 2017
DOI: 10.1038/sdata.2017.89.

Abstract: The age group composition of populations varies substantially across continents and within countries, and is linked to levels of development, health status and poverty. The subnational variability in the shape of the population pyramid as well as the respective dependency ratio are reflective of the different levels of development of a country and are drivers for a country's economic prospects and health burdens. Whether measured as the ratio between those of working age and those young and old who are dependent upon them, or through separate young and old-age metrics, dependency ratios are often highly heterogeneous between and within countries. Assessments of subnational dependency ratio and age structure patterns have been undertaken for specific countries and across high income regions, but to a lesser extent across the low income regions. In the framework of the WorldPop Project, through the assembly of over 100 million records across 6,389 subnational administrative units, subnational dependency ratio and high resolution gridded age/sex group datasets were produced for 87 countries in Africa and Asia.
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GridSample: an R package to generate household survey primary sampling units (PSUs) from gridded population data.
International Journal of Health Geographics (2017) 16:25.
Author(s): Dana R. Thomson author, Forrest R. Stevens, Nick W. Ruktanonchai, Andrew J. Tatem and Marcia C. Castro.
Type: method. Year: 2017
DOI: 10.1186/s12942-017-0098-4.

Abstract: Household survey data are collected by governments, international organizations, and companies to prioritize policies and allocate billions of dollars. Surveys are typically selected from recent census data; however, census data are often outdated or inaccurate. This paper describes how gridded population data might instead be used as a sample frame, and introduces the R GridSample algorithm for selecting primary sampling units (PSU) for complex household surveys with gridded population data. With a gridded population dataset and geographic boundary of the study area, GridSample allows a two-step process to sample “seed” cells with probability proportionate to estimated population size, then “grows” PSUs until a minimum population is achieved in each PSU. The algorithm permits stratification and oversampling of urban or rural areas. The approximately uniform size and shape of grid cells allows for spatial oversampling, not possible in typical surveys, possibly improving small area estimates with survey results.
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Census-independent population mapping in northern Nigeria
Remote Sensing of Environment (2017).
Author(s): Eric M. Weber, Vincent Y. Seaman, Robert N. Stewart, Tomas J. Bird, Andrew J. Tatem, Jacob J. McKee, Budhendra L. Bhaduri, Jessica J. Moehl, Andrew E. Reith
Type: method. Year: 2017
DOI: 10.1016/j.rse.2017.09.024.

Abstract: Although remote sensing has long been used to aid in the estimation of population, it has usually been in the context of spatial disaggregation of national census data, with the census counts serving both as observational data for specifying models and as constraints on model outputs. Here we present a framework for estimating populations from the bottom up, entirely independently of national census data, a critical need in areas without recent and reliable census data. To make observations of population density, we replace national census data with a microcensus, in which we enumerate population for a sample of small areas within the states of Kano and Kaduna in northern Nigeria. Using supervised texture-based classifiers with very high resolution satellite imagery, we produce a binary map of human settlement at 8-meter resolution across the two states and then a more refined classification consisting of 7 residential types and 1 non-residential type. Using the residential types and a model linking them to the population density observations, we produce population estimates across the two states in a gridded raster format, at approximately 90-meter resolution. We also demonstrate a simulation framework for capturing uncertainty and presenting estimates as prediction intervals for any region of interest of any size and composition within the study region. Used in concert with previously published demographic estimates, our population estimates allowed for predictions of the population under 5 in ten administrative wards that fit strongly with reference data collected during polio vaccination campaigns.
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