Developing a representative community health survey sampling frame using open-source remote satellite imagery in Mozambique View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Bradley H. Wagenaar, Orvalho Augusto, Kristjana Ásbjörnsdóttir, Adam Akullian, Nelia Manaca, Falume Chale, Alberto Muanido, Alfredo Covele, Cathy Michel, Sarah Gimbel, Tyler Radford, Blake Girardot, Kenneth Sherr, with input from the INCOMAS Study Team

ABSTRACT

BACKGROUND: Lack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details our experience using remote satellite imagery to develop a provincial-level representative community survey sampling frame to evaluate the effects of a 7-year health system intervention in Sofala Province, Mozambique. METHODS: Mozambique's most recent census was conducted in 2007, and no data are readily available to generate enumeration areas for representative health survey sampling frames. To remedy this, we partnered with the Humanitarian OpenStreetMap Team to digitize every building in Sofala and Manica provinces (685,189 Sofala; 925,713 Manica) using up-to-date remote satellite imagery, with final results deposited in the open-source OpenStreetMap database. We then created a probability proportional to size sampling frame by overlaying a grid of 2.106 km resolution (0.02 decimal degrees) across each province, and calculating the number of buildings within each grid square. Squares containing buildings were used as our primary sampling unit with replacement. Study teams navigated to the geographic center of each selected square using geographic positioning system coordinates, and then conducted a standard "random walk" procedure to select 20 households for each time a given square was selected. Based on sample size calculations, we targeted a minimum of 1500 households in each province. We selected 88 grids within each province to reach 1760 households, anticipating ongoing conflict and transport issues could preclude the inclusion of some clusters. RESULTS: Civil conflict issues forced the exclusion of 8 of 31 subdistricts in Sofala and 15 of 39 subdistricts in Manica. Using Android tablets, Open Data Kit software, and a remote RedCap data capture system, our final sample included 1549 households in Sofala (4669 adults; 4766 children; 33 missing age) and 1538 households in Manica (4422 adults; 4898 children; 33 missing age). CONCLUSIONS: Other implementation or evaluation teams may consider employing similar methods to track population distributions for health systems planning or the development of representative sampling frames using remote satellite imagery. More... »

PAGES

37

References to SciGraph publications

  • 2007-12. Don't spin the pen: two alternative methods for second-stage sampling in urban cluster surveys in EMERGING THEMES IN EPIDEMIOLOGY
  • 2013-12. Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti in INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS
  • 2012-12. A two-stage cluster sampling method using gridded population data, a GIS, and Google EarthTM imagery in a population-based mortality survey in Iraq in INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS
  • 2012-12. Choosing a survey sample when data on the population are limited: a method using Global Positioning Systems and aerial and satellite photographs in EMERGING THEMES IN EPIDEMIOLOGY
  • 2016-12. Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam in INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS
  • 2015-12. Open-source satellite enumeration to map households: planning and targeting indoor residual spraying for malaria in MALARIA JOURNAL
  • 2009-12. Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries in INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS
  • 2013-05. Strengthening integrated primary health care in Sofala, Mozambique in BMC HEALTH SERVICES RESEARCH
  • 2002-02. Satellite imagery in the study and forecast of malaria in NATURE
  • 2015-12. Satellite-aided survey sampling and implementation in low- and middle-income contexts: a low-cost/low-tech alternative in EMERGING THEMES IN EPIDEMIOLOGY
  • 2012-12. Health and demographic surveillance systems: a step towards full civil registration and vital statistics system in sub-Sahara Africa? in BMC PUBLIC HEALTH
  • 2012-12. Internal construct validity of the Shirom-Melamed Burnout Questionnaire (SMBQ) in BMC PUBLIC HEALTH
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12942-018-0158-4

    DOI

    http://dx.doi.org/10.1186/s12942-018-0158-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1107901872

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30373621


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Public Health and Health Services", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Health Alliance International", 
              "id": "https://www.grid.ac/institutes/grid.429096.0", 
              "name": [
                "Department of Global Health, University of Washington, 1959 NE Pacific Street, 98195, Seattle, WA, USA", 
                "Health Alliance International, Seattle, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wagenaar", 
            "givenName": "Bradley H.", 
            "id": "sg:person.01053265520.02", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01053265520.02"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Eduardo Mondlane University", 
              "id": "https://www.grid.ac/institutes/grid.8295.6", 
              "name": [
                "Department of Global Health, University of Washington, 1959 NE Pacific Street, 98195, Seattle, WA, USA", 
                "Health Alliance International, Seattle, WA, USA", 
                "Universidade Eduardo Mondlane, Maputo, Mozambique"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Augusto", 
            "givenName": "Orvalho", 
            "id": "sg:person.01255203350.52", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01255203350.52"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Health Alliance International", 
              "id": "https://www.grid.ac/institutes/grid.429096.0", 
              "name": [
                "Department of Global Health, University of Washington, 1959 NE Pacific Street, 98195, Seattle, WA, USA", 
                "Health Alliance International, Seattle, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "\u00c1sbj\u00f6rnsd\u00f3ttir", 
            "givenName": "Kristjana", 
            "id": "sg:person.01027665030.46", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01027665030.46"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Institute for Disease Modeling, Bellevue, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Akullian", 
            "givenName": "Adam", 
            "id": "sg:person.01271204122.97", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01271204122.97"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Health Alliance International, Beira, Mozambique"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Manaca", 
            "givenName": "Nelia", 
            "id": "sg:person.012052602467.41", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012052602467.41"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Beira Operations Research Center, Beira, Mozambique"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chale", 
            "givenName": "Falume", 
            "id": "sg:person.013051721011.01", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013051721011.01"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Health Alliance International, Beira, Mozambique"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Muanido", 
            "givenName": "Alberto", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Health Alliance International, Beira, Mozambique"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Covele", 
            "givenName": "Alfredo", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Health Alliance International, Beira, Mozambique"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Michel", 
            "givenName": "Cathy", 
            "id": "sg:person.01163725250.73", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163725250.73"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Washington", 
              "id": "https://www.grid.ac/institutes/grid.34477.33", 
              "name": [
                "Health Alliance International, Beira, Mozambique", 
                "School of Nursing, University of Washington, Seattle, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gimbel", 
            "givenName": "Sarah", 
            "id": "sg:person.0764056502.11", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764056502.11"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Humanitarian OpenStreetMap Team", 
              "id": "https://www.grid.ac/institutes/grid.479406.8", 
              "name": [
                "Humanitarian OpenStreetMap Team, Washington, DC, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Radford", 
            "givenName": "Tyler", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Humanitarian OpenStreetMap Team", 
              "id": "https://www.grid.ac/institutes/grid.479406.8", 
              "name": [
                "Humanitarian OpenStreetMap Team, Washington, DC, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Girardot", 
            "givenName": "Blake", 
            "id": "sg:person.016430474604.06", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016430474604.06"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Health Alliance International", 
              "id": "https://www.grid.ac/institutes/grid.429096.0", 
              "name": [
                "Department of Global Health, University of Washington, 1959 NE Pacific Street, 98195, Seattle, WA, USA", 
                "Health Alliance International, Seattle, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sherr", 
            "givenName": "Kenneth", 
            "id": "sg:person.01325121002.78", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01325121002.78"
            ], 
            "type": "Person"
          }, 
          {
            "familyName": "with input from the INCOMAS Study Team", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1038/415710a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000974356", 
              "https://doi.org/10.1038/415710a"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/415710a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000974356", 
              "https://doi.org/10.1038/415710a"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12936-015-0831-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001546313", 
              "https://doi.org/10.1186/s12936-015-0831-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/ede.0b013e31819670dc", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002393258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/ede.0b013e31819670dc", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002393258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12942-016-0051-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003410533", 
              "https://doi.org/10.1186/s12942-016-0051-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12942-016-0051-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003410533", 
              "https://doi.org/10.1186/s12942-016-0051-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1476-072x-12-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003798257", 
              "https://doi.org/10.1186/1476-072x-12-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1472-6963-13-s2-s4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008097059", 
              "https://doi.org/10.1186/1472-6963-13-s2-s4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1742-7622-9-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011347681", 
              "https://doi.org/10.1186/1742-7622-9-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12982-015-0041-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014026078", 
              "https://doi.org/10.1186/s12982-015-0041-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/infdis/jit285", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021827472"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2458-12-741", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024031492", 
              "https://doi.org/10.1186/1471-2458-12-741"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2458-12-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024987889", 
              "https://doi.org/10.1186/1471-2458-12-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2471/blt.14.140756", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034365784"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1476-072x-11-12", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035871335", 
              "https://doi.org/10.1186/1476-072x-11-12"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jbi.2008.08.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039152312"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1476-072x-8-49", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039570390", 
              "https://doi.org/10.1186/1476-072x-8-49"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1742-7622-4-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045716255", 
              "https://doi.org/10.1186/1742-7622-4-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s2214-109x(14)70276-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048757992"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1728-4457.2013.00624.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052781537"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2018-12", 
        "datePublishedReg": "2018-12-01", 
        "description": "BACKGROUND: Lack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details our experience using remote satellite imagery to develop a provincial-level representative community survey sampling frame to evaluate the effects of a 7-year health system intervention in Sofala Province, Mozambique.\nMETHODS: Mozambique's most recent census was conducted in 2007, and no data are readily available to generate enumeration areas for representative health survey sampling frames. To remedy this, we partnered with the Humanitarian OpenStreetMap Team to digitize every building in Sofala and Manica provinces (685,189 Sofala; 925,713 Manica) using up-to-date remote satellite imagery, with final results deposited in the open-source OpenStreetMap database. We then created a probability proportional to size sampling frame by overlaying a grid of 2.106\u00a0km resolution (0.02 decimal degrees) across each province, and calculating the number of buildings within each grid square. Squares containing buildings were used as our primary sampling unit with replacement. Study teams navigated to the geographic center of each selected square using geographic positioning system coordinates, and then conducted a standard \"random walk\" procedure to select 20 households for each time a given square was selected. Based on sample size calculations, we targeted a minimum of 1500 households in each province. We selected 88 grids within each province to reach 1760 households, anticipating ongoing conflict and transport issues could preclude the inclusion of some clusters.\nRESULTS: Civil conflict issues forced the exclusion of 8 of 31 subdistricts in Sofala and 15 of 39 subdistricts in Manica. Using Android tablets, Open Data Kit software, and a remote RedCap data capture system, our final sample included 1549 households in Sofala (4669 adults; 4766 children; 33 missing age) and 1538 households in Manica (4422 adults; 4898 children; 33 missing age).\nCONCLUSIONS: Other implementation or evaluation teams may consider employing similar methods to track population distributions for health systems planning or the development of representative sampling frames using remote satellite imagery.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s12942-018-0158-4", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1031277", 
            "issn": [
              "1476-072X"
            ], 
            "name": "International Journal of Health Geographics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "17"
          }
        ], 
        "name": "Developing a representative community health survey sampling frame using open-source remote satellite imagery in Mozambique", 
        "pagination": "37", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "561612959e6a95ab3cb57974c43c14c524ff8819d8e4552b4f6ee66215bde067"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "30373621"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101152198"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s12942-018-0158-4"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1107901872"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s12942-018-0158-4", 
          "https://app.dimensions.ai/details/publication/pub.1107901872"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T00:26", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8695_00000574.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1186%2Fs12942-018-0158-4"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12942-018-0158-4'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12942-018-0158-4'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12942-018-0158-4'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12942-018-0158-4'


     

    This table displays all metadata directly associated to this object as RDF triples.

    244 TRIPLES      21 PREDICATES      47 URIs      21 LITERALS      9 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s12942-018-0158-4 schema:about anzsrc-for:11
    2 anzsrc-for:1117
    3 schema:author N7c190f73be484f7fa39608a933b63d09
    4 schema:citation sg:pub.10.1038/415710a
    5 sg:pub.10.1186/1471-2458-12-1
    6 sg:pub.10.1186/1471-2458-12-741
    7 sg:pub.10.1186/1472-6963-13-s2-s4
    8 sg:pub.10.1186/1476-072x-11-12
    9 sg:pub.10.1186/1476-072x-12-3
    10 sg:pub.10.1186/1476-072x-8-49
    11 sg:pub.10.1186/1742-7622-4-8
    12 sg:pub.10.1186/1742-7622-9-5
    13 sg:pub.10.1186/s12936-015-0831-z
    14 sg:pub.10.1186/s12942-016-0051-y
    15 sg:pub.10.1186/s12982-015-0041-8
    16 https://doi.org/10.1016/j.jbi.2008.08.010
    17 https://doi.org/10.1016/s2214-109x(14)70276-1
    18 https://doi.org/10.1093/infdis/jit285
    19 https://doi.org/10.1097/ede.0b013e31819670dc
    20 https://doi.org/10.1111/j.1728-4457.2013.00624.x
    21 https://doi.org/10.2471/blt.14.140756
    22 schema:datePublished 2018-12
    23 schema:datePublishedReg 2018-12-01
    24 schema:description BACKGROUND: Lack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details our experience using remote satellite imagery to develop a provincial-level representative community survey sampling frame to evaluate the effects of a 7-year health system intervention in Sofala Province, Mozambique. METHODS: Mozambique's most recent census was conducted in 2007, and no data are readily available to generate enumeration areas for representative health survey sampling frames. To remedy this, we partnered with the Humanitarian OpenStreetMap Team to digitize every building in Sofala and Manica provinces (685,189 Sofala; 925,713 Manica) using up-to-date remote satellite imagery, with final results deposited in the open-source OpenStreetMap database. We then created a probability proportional to size sampling frame by overlaying a grid of 2.106 km resolution (0.02 decimal degrees) across each province, and calculating the number of buildings within each grid square. Squares containing buildings were used as our primary sampling unit with replacement. Study teams navigated to the geographic center of each selected square using geographic positioning system coordinates, and then conducted a standard "random walk" procedure to select 20 households for each time a given square was selected. Based on sample size calculations, we targeted a minimum of 1500 households in each province. We selected 88 grids within each province to reach 1760 households, anticipating ongoing conflict and transport issues could preclude the inclusion of some clusters. RESULTS: Civil conflict issues forced the exclusion of 8 of 31 subdistricts in Sofala and 15 of 39 subdistricts in Manica. Using Android tablets, Open Data Kit software, and a remote RedCap data capture system, our final sample included 1549 households in Sofala (4669 adults; 4766 children; 33 missing age) and 1538 households in Manica (4422 adults; 4898 children; 33 missing age). CONCLUSIONS: Other implementation or evaluation teams may consider employing similar methods to track population distributions for health systems planning or the development of representative sampling frames using remote satellite imagery.
    25 schema:genre research_article
    26 schema:inLanguage en
    27 schema:isAccessibleForFree true
    28 schema:isPartOf N81e726b642124e469d6bfd516037c341
    29 Ne1aad0fe4db64c9f9aac02ee520c2fe5
    30 sg:journal.1031277
    31 schema:name Developing a representative community health survey sampling frame using open-source remote satellite imagery in Mozambique
    32 schema:pagination 37
    33 schema:productId N4f22fb9528694e688139cc7eafed70b2
    34 N6506c7143c7a490da3129e8d8ba0edfa
    35 Nba4201bb094f4f21935c34565f602dfd
    36 Nd135df6202cd4db499343c601f1a842a
    37 Nec5ecca4e7c347498ea915bc225d218e
    38 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107901872
    39 https://doi.org/10.1186/s12942-018-0158-4
    40 schema:sdDatePublished 2019-04-11T00:26
    41 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    42 schema:sdPublisher Nc9e483da0b5d4b8db72511f4927eedc5
    43 schema:url https://link.springer.com/10.1186%2Fs12942-018-0158-4
    44 sgo:license sg:explorer/license/
    45 sgo:sdDataset articles
    46 rdf:type schema:ScholarlyArticle
    47 N02350a2472ab46a7b68f80c428de5f53 rdf:first N37715aa5ef4c42f09a62594a3fd28740
    48 rdf:rest N631a0d8686544603b5f6e280b9d42846
    49 N275cbb23f2b54f44a8648410adab7904 rdf:first Na0d4ee45bb374b2ca3d4eced6bb7a790
    50 rdf:rest N02350a2472ab46a7b68f80c428de5f53
    51 N3030a7f1e2314dcfb0bcc11ca0dc78db rdf:first sg:person.013051721011.01
    52 rdf:rest N275cbb23f2b54f44a8648410adab7904
    53 N33f77e7f0f0740c4bdb2578548405fe0 rdf:first sg:person.01027665030.46
    54 rdf:rest N8d0468213ed24122b123a711a84b60e6
    55 N37715aa5ef4c42f09a62594a3fd28740 schema:affiliation Nb43880c2a05a4aeabca410f2431f468d
    56 schema:familyName Covele
    57 schema:givenName Alfredo
    58 rdf:type schema:Person
    59 N4f22fb9528694e688139cc7eafed70b2 schema:name pubmed_id
    60 schema:value 30373621
    61 rdf:type schema:PropertyValue
    62 N5120e472ad4c4fcc852c5f7c1cdfe4e7 schema:name Institute for Disease Modeling, Bellevue, WA, USA
    63 rdf:type schema:Organization
    64 N631a0d8686544603b5f6e280b9d42846 rdf:first sg:person.01163725250.73
    65 rdf:rest Nca690162faef403b98aea8fdea3b5535
    66 N636d8cb340b54e1882ab350a5baae523 schema:name Health Alliance International, Beira, Mozambique
    67 rdf:type schema:Organization
    68 N6506c7143c7a490da3129e8d8ba0edfa schema:name doi
    69 schema:value 10.1186/s12942-018-0158-4
    70 rdf:type schema:PropertyValue
    71 N7c190f73be484f7fa39608a933b63d09 rdf:first sg:person.01053265520.02
    72 rdf:rest Nd5649812b59d4b73a3efcc8f54e5bdef
    73 N7c6808e644df4bdea4211cf266450d42 rdf:first sg:person.012052602467.41
    74 rdf:rest N3030a7f1e2314dcfb0bcc11ca0dc78db
    75 N81e726b642124e469d6bfd516037c341 schema:issueNumber 1
    76 rdf:type schema:PublicationIssue
    77 N88c6a79471c64f2080687c1bed1ba95a rdf:first Naf2d1232e3cf420e95c0ca6af4954b64
    78 rdf:rest Nf39500411edd49ff97c975a3055bb448
    79 N8d0468213ed24122b123a711a84b60e6 rdf:first sg:person.01271204122.97
    80 rdf:rest N7c6808e644df4bdea4211cf266450d42
    81 N8d1704b113ae4453a4e61c0249c725e4 rdf:first sg:person.01325121002.78
    82 rdf:rest Na65e88fb3d08401cb79cd85a83fbb4ed
    83 Na0d4ee45bb374b2ca3d4eced6bb7a790 schema:affiliation Ndbd0ff5b82d6416fbc126e9c266a91ff
    84 schema:familyName Muanido
    85 schema:givenName Alberto
    86 rdf:type schema:Person
    87 Na65e88fb3d08401cb79cd85a83fbb4ed rdf:first Neba99956d38d4b51b469ba1d7c2e2c69
    88 rdf:rest rdf:nil
    89 Naf2d1232e3cf420e95c0ca6af4954b64 schema:affiliation https://www.grid.ac/institutes/grid.479406.8
    90 schema:familyName Radford
    91 schema:givenName Tyler
    92 rdf:type schema:Person
    93 Nb43880c2a05a4aeabca410f2431f468d schema:name Health Alliance International, Beira, Mozambique
    94 rdf:type schema:Organization
    95 Nba4201bb094f4f21935c34565f602dfd schema:name nlm_unique_id
    96 schema:value 101152198
    97 rdf:type schema:PropertyValue
    98 Nc748596cc42f4b1fb58f1c079cde23ca schema:name Beira Operations Research Center, Beira, Mozambique
    99 rdf:type schema:Organization
    100 Nc9e483da0b5d4b8db72511f4927eedc5 schema:name Springer Nature - SN SciGraph project
    101 rdf:type schema:Organization
    102 Nca690162faef403b98aea8fdea3b5535 rdf:first sg:person.0764056502.11
    103 rdf:rest N88c6a79471c64f2080687c1bed1ba95a
    104 Nd135df6202cd4db499343c601f1a842a schema:name dimensions_id
    105 schema:value pub.1107901872
    106 rdf:type schema:PropertyValue
    107 Nd5649812b59d4b73a3efcc8f54e5bdef rdf:first sg:person.01255203350.52
    108 rdf:rest N33f77e7f0f0740c4bdb2578548405fe0
    109 Nd8f59bccf97742cca98e611c82395149 schema:name Health Alliance International, Beira, Mozambique
    110 rdf:type schema:Organization
    111 Ndbd0ff5b82d6416fbc126e9c266a91ff schema:name Health Alliance International, Beira, Mozambique
    112 rdf:type schema:Organization
    113 Ne1aad0fe4db64c9f9aac02ee520c2fe5 schema:volumeNumber 17
    114 rdf:type schema:PublicationVolume
    115 Neba99956d38d4b51b469ba1d7c2e2c69 schema:familyName with input from the INCOMAS Study Team
    116 rdf:type schema:Person
    117 Nec5ecca4e7c347498ea915bc225d218e schema:name readcube_id
    118 schema:value 561612959e6a95ab3cb57974c43c14c524ff8819d8e4552b4f6ee66215bde067
    119 rdf:type schema:PropertyValue
    120 Nf39500411edd49ff97c975a3055bb448 rdf:first sg:person.016430474604.06
    121 rdf:rest N8d1704b113ae4453a4e61c0249c725e4
    122 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    123 schema:name Medical and Health Sciences
    124 rdf:type schema:DefinedTerm
    125 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
    126 schema:name Public Health and Health Services
    127 rdf:type schema:DefinedTerm
    128 sg:journal.1031277 schema:issn 1476-072X
    129 schema:name International Journal of Health Geographics
    130 rdf:type schema:Periodical
    131 sg:person.01027665030.46 schema:affiliation https://www.grid.ac/institutes/grid.429096.0
    132 schema:familyName Ásbjörnsdóttir
    133 schema:givenName Kristjana
    134 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01027665030.46
    135 rdf:type schema:Person
    136 sg:person.01053265520.02 schema:affiliation https://www.grid.ac/institutes/grid.429096.0
    137 schema:familyName Wagenaar
    138 schema:givenName Bradley H.
    139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01053265520.02
    140 rdf:type schema:Person
    141 sg:person.01163725250.73 schema:affiliation N636d8cb340b54e1882ab350a5baae523
    142 schema:familyName Michel
    143 schema:givenName Cathy
    144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163725250.73
    145 rdf:type schema:Person
    146 sg:person.012052602467.41 schema:affiliation Nd8f59bccf97742cca98e611c82395149
    147 schema:familyName Manaca
    148 schema:givenName Nelia
    149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012052602467.41
    150 rdf:type schema:Person
    151 sg:person.01255203350.52 schema:affiliation https://www.grid.ac/institutes/grid.8295.6
    152 schema:familyName Augusto
    153 schema:givenName Orvalho
    154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01255203350.52
    155 rdf:type schema:Person
    156 sg:person.01271204122.97 schema:affiliation N5120e472ad4c4fcc852c5f7c1cdfe4e7
    157 schema:familyName Akullian
    158 schema:givenName Adam
    159 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01271204122.97
    160 rdf:type schema:Person
    161 sg:person.013051721011.01 schema:affiliation Nc748596cc42f4b1fb58f1c079cde23ca
    162 schema:familyName Chale
    163 schema:givenName Falume
    164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013051721011.01
    165 rdf:type schema:Person
    166 sg:person.01325121002.78 schema:affiliation https://www.grid.ac/institutes/grid.429096.0
    167 schema:familyName Sherr
    168 schema:givenName Kenneth
    169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01325121002.78
    170 rdf:type schema:Person
    171 sg:person.016430474604.06 schema:affiliation https://www.grid.ac/institutes/grid.479406.8
    172 schema:familyName Girardot
    173 schema:givenName Blake
    174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016430474604.06
    175 rdf:type schema:Person
    176 sg:person.0764056502.11 schema:affiliation https://www.grid.ac/institutes/grid.34477.33
    177 schema:familyName Gimbel
    178 schema:givenName Sarah
    179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764056502.11
    180 rdf:type schema:Person
    181 sg:pub.10.1038/415710a schema:sameAs https://app.dimensions.ai/details/publication/pub.1000974356
    182 https://doi.org/10.1038/415710a
    183 rdf:type schema:CreativeWork
    184 sg:pub.10.1186/1471-2458-12-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024987889
    185 https://doi.org/10.1186/1471-2458-12-1
    186 rdf:type schema:CreativeWork
    187 sg:pub.10.1186/1471-2458-12-741 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024031492
    188 https://doi.org/10.1186/1471-2458-12-741
    189 rdf:type schema:CreativeWork
    190 sg:pub.10.1186/1472-6963-13-s2-s4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008097059
    191 https://doi.org/10.1186/1472-6963-13-s2-s4
    192 rdf:type schema:CreativeWork
    193 sg:pub.10.1186/1476-072x-11-12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035871335
    194 https://doi.org/10.1186/1476-072x-11-12
    195 rdf:type schema:CreativeWork
    196 sg:pub.10.1186/1476-072x-12-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003798257
    197 https://doi.org/10.1186/1476-072x-12-3
    198 rdf:type schema:CreativeWork
    199 sg:pub.10.1186/1476-072x-8-49 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039570390
    200 https://doi.org/10.1186/1476-072x-8-49
    201 rdf:type schema:CreativeWork
    202 sg:pub.10.1186/1742-7622-4-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045716255
    203 https://doi.org/10.1186/1742-7622-4-8
    204 rdf:type schema:CreativeWork
    205 sg:pub.10.1186/1742-7622-9-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011347681
    206 https://doi.org/10.1186/1742-7622-9-5
    207 rdf:type schema:CreativeWork
    208 sg:pub.10.1186/s12936-015-0831-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1001546313
    209 https://doi.org/10.1186/s12936-015-0831-z
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1186/s12942-016-0051-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1003410533
    212 https://doi.org/10.1186/s12942-016-0051-y
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1186/s12982-015-0041-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014026078
    215 https://doi.org/10.1186/s12982-015-0041-8
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1016/j.jbi.2008.08.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039152312
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1016/s2214-109x(14)70276-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048757992
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1093/infdis/jit285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021827472
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1097/ede.0b013e31819670dc schema:sameAs https://app.dimensions.ai/details/publication/pub.1002393258
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1111/j.1728-4457.2013.00624.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1052781537
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.2471/blt.14.140756 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034365784
    228 rdf:type schema:CreativeWork
    229 https://www.grid.ac/institutes/grid.34477.33 schema:alternateName University of Washington
    230 schema:name Health Alliance International, Beira, Mozambique
    231 School of Nursing, University of Washington, Seattle, WA, USA
    232 rdf:type schema:Organization
    233 https://www.grid.ac/institutes/grid.429096.0 schema:alternateName Health Alliance International
    234 schema:name Department of Global Health, University of Washington, 1959 NE Pacific Street, 98195, Seattle, WA, USA
    235 Health Alliance International, Seattle, WA, USA
    236 rdf:type schema:Organization
    237 https://www.grid.ac/institutes/grid.479406.8 schema:alternateName Humanitarian OpenStreetMap Team
    238 schema:name Humanitarian OpenStreetMap Team, Washington, DC, USA
    239 rdf:type schema:Organization
    240 https://www.grid.ac/institutes/grid.8295.6 schema:alternateName Eduardo Mondlane University
    241 schema:name Department of Global Health, University of Washington, 1959 NE Pacific Street, 98195, Seattle, WA, USA
    242 Health Alliance International, Seattle, WA, USA
    243 Universidade Eduardo Mondlane, Maputo, Mozambique
    244 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...