Evidence map›Paper›PMID 31684960›Full record

ArticleInternational journal of health geographics2019

Using Google Earth™ and Geographical Information System data as method to delineate sample domains for an urban household surveys: the case of Maroua (Far North Region-Cameroon).

Ronald R B Ngom Vougat, Steven Chouto, Sylvain Aoudou Doua, Rebecca Garabed, André Zoli Pagnah, Bernard Gonne

Abstract read
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Article in International journal of health geographics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ronald R B Ngom VougatNational Advanced School of Engineering, University of Maroua, Maroua, Cameroon.
Steven ChoutoDepartment of Geography, Doctoral Research and Training Unit of "Human and Social Sciences", University of Maroua, Maroua, Cameroon. stevenchouto@gmail.com.ORCID 0000-0002-4926-1039
Sylvain Aoudou DouaNational Advanced School of Engineering, University of Maroua, Maroua, Cameroon.
Rebecca GarabedDepartment of Veterinary Preventive Medicine, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA.
André Zoli PagnahSchool of Veterinary Medicine and Sciences, University of Ngaoundéré, Ngaoundéré, Cameroon.
Bernard GonneDepartment of Geography, Doctoral Research and Training Unit of "Human and Social Sciences", University of Maroua, Maroua, Cameroon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGetting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist. This study aimed to test an alternative method using freely available aerial imagery.

methodsA gridded map and random selection method was used to select households for interviews. A hundred numbered of points were put along the edges of an updated map of Maroua. Then two numbers were randomly draw at a time and a line was drawn between those two numbers. A lot of different kinds of shapes of different sizes obtained were numbered. Ten shapes were randomly draw and the one selected were considered as 'neighbourhoods'. A grid of 30 m × 30 m was drawn over each and then numbered. 202 grids considered here as households were randomly selected from the ten neighbourhoods for interviews.

resultsOut of 202 households visited, only 4 were found to be something other than a house. In addition, 30 sampled households (14.85%) were abandoned or the occupants had relocated elsewhere. This method resulted in an accuracy level of 72%, its advantage is the ability to generate efficient random sample at relatively low cost as well the time required.

conclusionsThe method proposed in this study was efficient and cost-effective when compared to the infield generation of a household inventory or Global Positioning System (GPS) tracking of households. It can then be used by researchers in low-incomes countries where funding for research is a challenge. However, this method needs to train the investigators on how to use the GPS.

Indexed as

Data Interpretation, StatisticalFamily CharacteristicsGeographic Information SystemsSurveys and QuestionnairesUrban PopulationCameroonHumansRandom AllocationCameroonGoogle EarthHousehold samplingMarouaSurvey

Identifiers

PMID31684960
PMCPMC6829818

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.