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Published in: Emerging Themes in Epidemiology 1/2018

Open Access 01-12-2018 | Research article

The validity of an area-based method to estimate the size of hard-to-reach populations using satellite images: the example of fishing populations of Lake Victoria

Authors: Stephen Nash, Victoria Tittle, Andrew Abaasa, Richard E. Sanya, Gershim Asiki, Christian Holm Hansen, Heiner Grosskurth, Saidi Kapiga, Chris Grundy, Lake Victoria Consortium for Health Research

Published in: Emerging Themes in Epidemiology | Issue 1/2018

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Abstract

Background

Information on the size of populations is crucial for planning of service and resource allocation to communities in need of health interventions. In resource limited settings, reliable census data are often not available. Using publicly available Google Earth Pro and available local household survey data from fishing communities (FC) on Lake Victoria in Uganda, we compared two simple methods (using average population density) and one simple linear regression model to estimate populations of small rural FC in Uganda. We split the dataset into two sections; one to obtain parameters and one to test the validity of the models.

Results

Out of 66 FC, we were able to estimate populations for 47. There were 16 FC in the test set. The estimates for total population from all three methods were similar, with errors less than 2.2%. Estimates of individual FC populations were more widely discrepant.

Conclusions

In our rural Ugandan setting, it was possible to use a simple area based model to get reasonable estimates of total population. However, there were often large errors in estimates for individual villages.
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Metadata
Title
The validity of an area-based method to estimate the size of hard-to-reach populations using satellite images: the example of fishing populations of Lake Victoria
Authors
Stephen Nash
Victoria Tittle
Andrew Abaasa
Richard E. Sanya
Gershim Asiki
Christian Holm Hansen
Heiner Grosskurth
Saidi Kapiga
Chris Grundy
Lake Victoria Consortium for Health Research
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Emerging Themes in Epidemiology / Issue 1/2018
Electronic ISSN: 1742-7622
DOI
https://doi.org/10.1186/s12982-018-0079-5

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