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Building a Sanitary Vulnerability Map from Open Source Data. Argentina, 2010-2018
Germán Federico Rosati
Universidad Nacional de San Martín
Corresponding Author
ORCiD: https://orcid.org/0000-0002-9775-0435
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Designing public health policies to target the needs of specific places requires highly granular data. When geographic health statistics from official sources are absent or lacking in spatial detail, Sanitary Vulnerabilitymetrics derived from Census and other georeferenced public data can be used to identify areas in particular need of attention. With that aim, a Vulnerability Map was developed, identifying areas with a substantial deficit in its population health coverage.
Methods: Census, official listings of public health facilities and crowdsourced georeferenced data are used. The Vulnerability Index is built using dimensionality reduction techniques such as Autoencoders and Non-parametric PCA.
Main results: The high resolution map shows the geographical distribution of a Sanitary Vulnerability Index, produced using official and crowdsourced open data sources, overcoming the lack of official sources on health indicators at the local level.
Conclusions: The Sanitary Vulnerability Map’s value as a tool for place specific policymaking was validated by using it to predict local health related metrics such as health coverage. Further lines of work contemplate using the Map to study the interaction between Sanitary Vulnerability and the prevalence of different diseases, and also applying its methodology in the context of other public services such as education, security, housing, etc.
Keywords
sample, article, Health, Vulnerability, Census, Public Policy, Open Data
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This preprint is under consideration at International Journal for Equity in Health. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Building a Sanitary Vulnerability Map from Open Source Data. Argentina, 2010-2018
Germán Federico Rosati
Universidad Nacional de San Martín
Corresponding Author
ORCiD: https://orcid.org/0000-0002-9775-0435
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 07 Jan, 2020
No community comments so far
Editorial decision: Minor Revision
On 24 Jul, 2020
Review #4 received
Received 08 Jul, 2020
Reviewer #4 agreed
On 02 Jul, 2020
Review #3 received
Received 02 Jun, 2020
Review #2 received
Received 02 Jun, 2020
Reviewer #3 agreed
On 25 May, 2020
Review #1 received
Received 10 May, 2020
Reviewer #2 agreed
On 08 May, 2020
Reviewer #1 agreed
On 27 Jan, 2020
Reviewers invited
Invitations sent on 14 Jan, 2020
Editor assigned
On 02 Jan, 2020
First submitted
On 01 Jan, 2020
Submission checks complete
On 01 Jan, 2020
Editor invited
On 01 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Designing public health policies to target the needs of specific places requires highly granular data. When geographic health statistics from official sources are absent or lacking in spatial detail, Sanitary Vulnerabilitymetrics derived from Census and other georeferenced public data can be used to identify areas in particular need of attention. With that aim, a Vulnerability Map was developed, identifying areas with a substantial deficit in its population health coverage.
Methods: Census, official listings of public health facilities and crowdsourced georeferenced data are used. The Vulnerability Index is built using dimensionality reduction techniques such as Autoencoders and Non-parametric PCA.
Main results: The high resolution map shows the geographical distribution of a Sanitary Vulnerability Index, produced using official and crowdsourced open data sources, overcoming the lack of official sources on health indicators at the local level.
Conclusions: The Sanitary Vulnerability Map’s value as a tool for place specific policymaking was validated by using it to predict local health related metrics such as health coverage. Further lines of work contemplate using the Map to study the interaction between Sanitary Vulnerability and the prevalence of different diseases, and also applying its methodology in the context of other public services such as education, security, housing, etc.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.