A protocol for a multi-site, spatially-referenced household survey in slum settings: methods for access, sampling frame construction, sampling, and field data collection.


Journal

BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545

Informations de publication

Date de publication:
30 05 2019
Historique:
received: 26 10 2018
accepted: 12 04 2019
entrez: 1 6 2019
pubmed: 31 5 2019
medline: 9 4 2020
Statut: epublish

Résumé

Household surveys are a key epidemiological, medical, and social research method. In poor urban environments, such as slums, censuses can often be out-of-date or fail to record transient residents, maps may be incomplete, and access to sites can be limit, all of which prohibits obtaining an accurate sampling frame. This article describes a method to conduct a survey in slum settings in the context of the NIHR Global Health Research Unit on Improving Health in Slums project. We identify four key steps: obtaining site access, generation of a sampling frame, sampling, and field data collection. Stakeholder identification and engagement is required to negotiate access. A spatially-referenced sampling frame can be generated by: remote participatory mapping from satellite imagery; local participatory mapping and ground-truthing; and identification of all residents of each structure. We propose to use a spatially-regulated sampling method to ensure spatial coverage across the site. Finally, data collection using tablet devices and open-source software can be conducted using the generated sample and maps. Slums are home to a growing population who face some of the highest burdens of disease yet who remain relatively understudied. Difficulties conducting surveys in these locations may explain this disparity. We propose a generalisable, scientifically valid method that is sustainable and ensures community engagement.

Sections du résumé

BACKGROUND
Household surveys are a key epidemiological, medical, and social research method. In poor urban environments, such as slums, censuses can often be out-of-date or fail to record transient residents, maps may be incomplete, and access to sites can be limit, all of which prohibits obtaining an accurate sampling frame. This article describes a method to conduct a survey in slum settings in the context of the NIHR Global Health Research Unit on Improving Health in Slums project.
METHODS
We identify four key steps: obtaining site access, generation of a sampling frame, sampling, and field data collection. Stakeholder identification and engagement is required to negotiate access. A spatially-referenced sampling frame can be generated by: remote participatory mapping from satellite imagery; local participatory mapping and ground-truthing; and identification of all residents of each structure. We propose to use a spatially-regulated sampling method to ensure spatial coverage across the site. Finally, data collection using tablet devices and open-source software can be conducted using the generated sample and maps.
DISCUSSION
Slums are home to a growing population who face some of the highest burdens of disease yet who remain relatively understudied. Difficulties conducting surveys in these locations may explain this disparity. We propose a generalisable, scientifically valid method that is sustainable and ensures community engagement.

Identifiants

pubmed: 31146676
doi: 10.1186/s12874-019-0732-x
pii: 10.1186/s12874-019-0732-x
pmc: PMC6543601
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

109

Investigateurs

Pauline Bakibinga (P)
Caroline Kabaria (C)
Catherine Kyobutungi (C)
Anthony Manyara (A)
Nelson Mbaya (N)
Shukri Mohammed (S)
Anne Njeri (A)
Iqbal Azam (I)
Romaina Iqbal (R)
Shahida Mazaffar (S)
Narjis Rizvi (N)
Tayyaba Rizvi (T)
Hamid Ur Rehman (H)
Syed A K Shifat Ahmed (SAK)
Ornob Alam (O)
Afreen Zaman Khan (AZ)
Omar Rahman (O)
Rita Yusuf (R)
Doyin Odubanjo (D)
Montunrayo Ayobola (M)
Funke Fayehun (F)
Akinyinka Omigbodun (A)
Eme Owoaje (E)
Olalekan Taiwo (O)
Peter Diggle (P)
Navneet Aujla (N)
Yen-Fu Chen (YF)
Paramjit Gill (P)
Frances Griffiths (F)
Bronwyn Harris (B)
Jason Madan (J)
Richard J Lilford (RJ)
Oyinlola R Oyobode (OR)
Vangelis Pitidis (V)
Joao Porto de Albequerque (JP)
Jo Sartori (J)
Celia Taylor (C)
Philip Ulbrich (P)
Olalekan Uthman (O)
Samuel I Watson (SI)
Godwin Yeboah (G)

Références

Lancet. 2017 Feb 4;389(10068):547-558
pubmed: 27760703
J R Stat Soc Ser A Stat Soc. 2018 Oct;181(4):1033-1056
pubmed: 37637975
Lancet. 2017 Feb 4;389(10068):559-570
pubmed: 27760702
J Urban Health. 2016 Feb;93(1):6-18
pubmed: 26830423
J Infect Dis. 2017 Jul 1;216(suppl_1):S337-S342
pubmed: 28838181
J Urban Health. 2011 Jun;88 Suppl 2:S200-18
pubmed: 21713553

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