Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects.
Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects.
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DOI：
10.1080/16549716.2021.1974676
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发表时间：
2021-10-26
影响因子：
2.6
通讯作者：
Collinson MA
中科院分区：
文献类型：
--
作者：
Herbst K;Juvekar S;Jasseh M;Berhane Y;Chuc NTK;Seeley J;Sankoh O;Clark SJ;Collinson MA
卫生和人口监测系统（HDSS）已经在非洲和亚洲的一些低收入和中等收入国家（LMICs）发展起来。本文回顾了他们的历史，艺术状态和未来的潜力，并强调了已故教授彼得·比亚斯实质性的贡献领域。从历史上看，HDSS出现在二十世纪下半叶，是为了应对资源贫乏的环境中缺乏准确的人口数据，以便将改善健康和福祉的干预措施研究置于背景下。从Pholela开始，通过Gwembe、Balabgarh、Niakhar、Matlab、Navrongo、Agincourt、Farafenni和Butajira，以及20世纪90年代初INDEPTH网络的出现，描述了该网络的发展进展。优势在于它们的时间覆盖范围、细节、紧密联系，以及它们存在于HDSS站点运行的中低收入国家长期记录不足的人群中。主要的限制是对全国人口的普遍性和潜在的霍桑效应，即项目本身可能改变了人口的特征。未来将包括HDSS数据协调、可访问性和保护方面的进展。数据的关键应用是验证和评估其他数据集中的偏差。南非和塞拉利昂以国家HDSS网络和国家统计局之间的强有力合作为榜样，其他低收入和中等收入国家可能会看到这种好处并采取这种方法。
Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass. Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990’s The paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population. The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.
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影响因子：
7.7
作者：
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Sokhna, Cheikh
影响因子：
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通讯作者：
Collinson, Mark A
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影响因子：
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队列概况：拉丁美洲和加勒比海（CC-LAC）的队列联盟。
影响因子：
7.7
作者：
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通讯作者：
Tartaglione J