Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case
International policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifying and localizing vulnerable populations for sc...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/13/2/33 |
| _version_ | 1797298087437271040 |
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| author | Linda Petutschnig Thomas Clemen E. Sophia Klaußner Ulfia Clemen Stefan Lang |
| author_facet | Linda Petutschnig Thomas Clemen E. Sophia Klaußner Ulfia Clemen Stefan Lang |
| author_sort | Linda Petutschnig |
| collection | DOAJ |
| description | International policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifying and localizing vulnerable populations for scaling resources and prioritizing aid delivery. However, the reliability of these assessments is often uncertain due to data quality issues. This article introduces a data evaluation framework to assist risk modelers in evaluating data adequacy. We operationalize the concept of “data adequacy” by considering “quality by design” (suitability) and “quality of conformance” (reliability). Based on a use case we developed in collaboration with Médecins Sans Frontières, we assessed data sources popular in spatial malaria risk assessments and related domains, including data from the Malaria Atlas Project, a healthcare facility database, WorldPop population counts, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation estimates, European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation forecast, and Armed Conflict Location and Event Data Project (ACLED) conflict events data. Our findings indicate that data availability is generally not a bottleneck, and data producers effectively communicate contextual information pertaining to sources, methodology, limitations and uncertainties. However, determining such data’s adequacy definitively for supporting humanitarian intervention planning remains challenging due to potential inaccuracies, incompleteness or outdatedness that are difficult to quantify. Nevertheless, the data hold value for awareness raising, advocacy and recognizing trends and patterns valuable for humanitarian contexts. We contribute a domain-agnostic, systematic approach to geodata adequacy evaluation, with the aim of enhancing geospatial risk assessments, facilitating evidence-based decisions. |
| first_indexed | 2024-03-07T22:29:48Z |
| format | Article |
| id | doaj.art-84bf1695b0b14f94a1dc22b27f142c9c |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-07T22:29:48Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-84bf1695b0b14f94a1dc22b27f142c9c2024-02-23T15:19:04ZengMDPI AGISPRS International Journal of Geo-Information2220-99642024-01-011323310.3390/ijgi13020033Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use CaseLinda Petutschnig0Thomas Clemen1E. Sophia Klaußner2Ulfia Clemen3Stefan Lang4Christian Doppler Laboratory for Geospatial and EO-Based Humanitarian Technologies, Department of Geoinformatics—Z_GIS, Paris Lodron University of Salzburg, 5020 Salzburg, AustriaDepartment of Computer Science, Hamburg University of Applied Sciences, Berliner Tor 7, 20099 Hamburg, GermanyChristian Doppler Laboratory for Geospatial and EO-Based Humanitarian Technologies, Department of Geoinformatics—Z_GIS, Paris Lodron University of Salzburg, 5020 Salzburg, AustriaDepartment of Computer Science, Hamburg University of Applied Sciences, Berliner Tor 7, 20099 Hamburg, GermanyChristian Doppler Laboratory for Geospatial and EO-Based Humanitarian Technologies, Department of Geoinformatics—Z_GIS, Paris Lodron University of Salzburg, 5020 Salzburg, AustriaInternational policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifying and localizing vulnerable populations for scaling resources and prioritizing aid delivery. However, the reliability of these assessments is often uncertain due to data quality issues. This article introduces a data evaluation framework to assist risk modelers in evaluating data adequacy. We operationalize the concept of “data adequacy” by considering “quality by design” (suitability) and “quality of conformance” (reliability). Based on a use case we developed in collaboration with Médecins Sans Frontières, we assessed data sources popular in spatial malaria risk assessments and related domains, including data from the Malaria Atlas Project, a healthcare facility database, WorldPop population counts, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation estimates, European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation forecast, and Armed Conflict Location and Event Data Project (ACLED) conflict events data. Our findings indicate that data availability is generally not a bottleneck, and data producers effectively communicate contextual information pertaining to sources, methodology, limitations and uncertainties. However, determining such data’s adequacy definitively for supporting humanitarian intervention planning remains challenging due to potential inaccuracies, incompleteness or outdatedness that are difficult to quantify. Nevertheless, the data hold value for awareness raising, advocacy and recognizing trends and patterns valuable for humanitarian contexts. We contribute a domain-agnostic, systematic approach to geodata adequacy evaluation, with the aim of enhancing geospatial risk assessments, facilitating evidence-based decisions.https://www.mdpi.com/2220-9964/13/2/33geospatial datadata qualityrisk assessmentmalaria riskspatial indicators |
| spellingShingle | Linda Petutschnig Thomas Clemen E. Sophia Klaußner Ulfia Clemen Stefan Lang Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case ISPRS International Journal of Geo-Information geospatial data data quality risk assessment malaria risk spatial indicators |
| title | Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case |
| title_full | Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case |
| title_fullStr | Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case |
| title_full_unstemmed | Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case |
| title_short | Evaluating Geospatial Data Adequacy for Integrated Risk Assessments: A Malaria Risk Use Case |
| title_sort | evaluating geospatial data adequacy for integrated risk assessments a malaria risk use case |
| topic | geospatial data data quality risk assessment malaria risk spatial indicators |
| url | https://www.mdpi.com/2220-9964/13/2/33 |
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