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.

IF 3.6 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Emerging Themes in Epidemiology Pub Date : 2018-08-13 eCollection Date: 2018-01-01 DOI:10.1186/s12982-018-0079-5
Stephen Nash, Victoria Tittle, Andrew Abaasa, Richard E Sanya, Gershim Asiki, Christian Holm Hansen, Heiner Grosskurth, Saidi Kapiga, Chris Grundy
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引用次数: 4

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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利用卫星图像估计难以到达的种群规模的基于区域的方法的有效性:以维多利亚湖的捕鱼种群为例。
背景:关于人口规模的信息对于规划向需要保健干预措施的社区提供服务和分配资源至关重要。在资源有限的情况下,往往没有可靠的人口普查数据。利用公开的Google Earth Pro和来自乌干达维多利亚湖渔业社区(FC)的当地家庭调查数据,我们比较了两种简单的方法(使用平均人口密度)和一种简单的线性回归模型来估计乌干达小型农村FC的人口。我们将数据集分成两部分;一个是获取参数,一个是检验模型的有效性。结果:在66个FC中,我们能够估计47个的种群。测试集中有16个FC。三种方法对人口总数的估计是相似的,误差小于2.2%。个体FC种群的估计差异更大。结论:在我们的乌干达农村环境中,可以使用一个简单的基于区域的模型来合理估计总人口。然而,对个别村庄的估计往往有很大的误差。
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来源期刊
Emerging Themes in Epidemiology
Emerging Themes in Epidemiology Medicine-Epidemiology
CiteScore
4.40
自引率
4.30%
发文量
9
审稿时长
28 weeks
期刊介绍: Emerging Themes in Epidemiology is an open access, peer-reviewed, online journal that aims to promote debate and discussion on practical and theoretical aspects of epidemiology. Combining statistical approaches with an understanding of the biology of disease, epidemiologists seek to elucidate the social, environmental and host factors related to adverse health outcomes. Although research findings from epidemiologic studies abound in traditional public health journals, little publication space is devoted to discussion of the practical and theoretical concepts that underpin them. Because of its immediate impact on public health, an openly accessible forum is needed in the field of epidemiology to foster such discussion.
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