https://doi.org/10.4081/gh.2024.1284

Geospatial tools and data for health service delivery: opportunities and challenges across the disaster management cycle

Vol. 19 No. 2 (2024)
Submitted: 15 March 2024
Accepted: 4 October 2024
Published: 29 October 2024
Geospatial analysis, disaster management, climate change, health service delivery, natural hazard
Abstract Views: 5083
PDF: 238
Supplementary Materials: 45
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Authors

Fleur Hierink
https://orcid.org/0000-0002-2727-0540
GeoHealth group, Institute of Global Health, University of Geneva, Geneva, Switzerland; Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland.
Nima Yaghmaei
https://orcid.org/0000-0001-7740-8037
KIT Royal Tropical Institute, Global Health, Centre for Applied Spatial Epidemiology, Amsterdam, Netherlands.
Mirjam I. Bakker
https://orcid.org/0000-0002-5104-3727
KIT Royal Tropical Institute, Global Health, Centre for Applied Spatial Epidemiology, Amsterdam, Netherlands.
Nicolas Ray
nicolas.ray@unige.ch
https://orcid.org/0000-0002-4696-5313
GeoHealth group, Institute of Global Health, University of Geneva, Geneva, Switzerland; Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland.
Marc van den Homberg
https://orcid.org/0000-0003-1436-254X
510, an initiative of the Netherlands Red Cross; Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands.

As extreme weather events increase in frequency and intensity, the health system faces significant challenges, not only from shifting patterns of climate-sensitive diseases but also from disruptions to healthcare infrastructure, supply chains and the physical systems essential for delivering care. This necessitates the strategic use of geospatial tools to guide the delivery of healthcare services and make evidence-informed priorities, especially in contexts with scarce human and financial resources. In this article, we highlight several published papers that have been used throughout the phases of the disaster management cycle in relation to health service delivery. We complement the findings from these publications with a rapid scoping review to present the body of knowledge for using spatial methods for health service delivery in the context of disasters. The main aim of this article is to demonstrate the benefits and discuss the challenges associated with the use of geospatial methods throughout the disaster management cycle. Our scoping review identified 48 articles employing geospatial techniques in the disaster management cycle. Most of them focused on geospatial tools employed for preparedness, anticipatory action and mitigation, particularly for targeted health service delivery. We note that while geospatial data analytics are effectively deployed throughout the different phases of disaster management, important challenges remain, such as ensuring timely availability of geospatial data during disasters, developing standardized and structured data formats, securing pre-disaster data for disaster preparedness, addressing gaps in health incidence data, reducing underreporting of cases and overcoming limitations in spatial and temporal coverage and granularity. Overall, existing and novel geospatial methods can bridge specific evidence gaps in all phases of the disaster management cycle. Improvement and ‘operationalization’ of these methods can provide opportunities for more evidence-informed decision making in responding to health crises during climate change.

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Scopus
Google Scholar
Europe PMC
Alcayna T, Fletcher I, Gibb R, Tremblay L, Funk S, Rao B, Lowe R. 2022. Climate-sensitive disease outbreaks in the aftermath of extreme climatic events: A scoping review. One Earth 5;336–350. DOI: https://doi.org/10.1016/j.oneear.2022.03.011
Colombo S, Pavignani E. 2017. Recurrent failings of medical humanitarianism: Intractable, ignored, or just exaggerated? Lancet 390:2314–24. DOI: https://doi.org/10.1016/S0140-6736(17)31277-1
Di Napoli C, Romanello M, Minor K, Chambers J, Dasgupta S, Escobar LE, Hang Y, Hänninen R, Liu Y, Lotto Batista M, Lowe R, Murray KA, Owfi F, Rabbaniha M, Shi L, Sofiev M, Tabatabaei M, Robinson EJZ. 2023. The role of global reanalyses in climate services for health: Insights from the Lancet Countdown. Meteorol Applicat 30:e2122. DOI: https://doi.org/10.1002/met.2122
EM-DAT. 2024. Classification glossary: definitions of disaster types. EM-DAT Documentation. Available from: https://doc.emdat.be/docs/data-structure-and-content/glossary/
Fletcher IK, Stewart-Ibarra AM, García-Díez M, Shumake-Guillemot J, Lowe R. 2021. Climate services for health: From global observations to local interventions. Medicine 2:355–361. DOI: https://doi.org/10.1016/j.medj.2021.03.010
Greenough PG, Nelson EL. 2019. Beyond mapping: A case for geospatial analytics in humanitarian health. Conflict Health 13:50. DOI: https://doi.org/10.1186/s13031-019-0234-9
Haak E, Ubacht J, Van Den Homberg M, Cunningham S, Van Den Walle B. 2018. A framework for strengthening data ecosystems to serve humanitarian purposes. Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, 1–9. https://doi.org/10.1145/3209281.3209326 DOI: https://doi.org/10.1145/3209281.3209326
Hierink F, Margutti J, van den Homberg M, Ray N. 2022. Constructing and validating a transferable epidemic risk index in data scarce environments using open data: A case study for dengue in the Philippines. PLoS Neglected Trop Dis 16:e0009262. DOI: https://doi.org/10.1371/journal.pntd.0009262
Hierink F, Rodrigues N, Muñiz M, Panciera R, Ray N. 2020. Modelling geographical accessibility to support disaster response and rehabilitation of a healthcare system: An impact analysis of Cyclones Idai and Kenneth in Mozambique. BMJ Open 10:e039138. DOI: https://doi.org/10.1136/bmjopen-2020-039138
IASC. 2015, July. Multi-Sector Initial Rapid Assessment (MIRA). Inter-Agency Standing Committee. Available from: https://interagencystandingcommittee.org/sites/default/files/migrated/2019-02/mira_manual_2015.pdf
Jabbour S, Attal B. 2020. Geospatial analysis: A new frontier in humanitarian health research? Lancet Global Health 8:e1353–4. DOI: https://doi.org/10.1016/S2214-109X(20)30390-9
Jones RL, Guha-Sapir D, Tubeuf S. 2022. Human and economic impacts of natural disasters: Can we trust the global data? Sci Data, 9572. DOI: https://doi.org/10.1038/s41597-022-01667-x
Kamel Boulos MN, Wilson JP. 2023. Geospatial techniques for monitoring and mitigating climate change and its effects on human health. Internat J Health Geograph 22:s12942-023-00324–00329. DOI: https://doi.org/10.1186/s12942-023-00324-9
Klein TA, Irizarry L. 2023. EMS Disaster Response. In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/books/NBK560710/
McMichael C. 2020. Human mobility, climate change, and health: Unpacking the connections. Lancet Planetary Health 4:e217–e218. DOI: https://doi.org/10.1016/S2542-5196(20)30125-X
Mroz EJ, Willis T, Thomas C, Janes C, Singini D, Njungu M, Smith M. 2023. Impacts of seasonal flooding on geographical access to maternal healthcare in the Barotse Floodplain, Zambia. Internat J Health Geograph 22:17. DOI: https://doi.org/10.1186/s12942-023-00338-3
Nelson EL, Saade DR, Gregg Greenough P. (202. Gender-based vulnerability: Combining Pareto ranking and spatial statistics to model gender-based vulnerability in Rohingya refugee settlements in Bangladesh. Internat J Health Geograph 19;20. DOI: https://doi.org/10.1186/s12942-020-00215-3
Romanello M, Di Napoli C, Drummond P, Green C, Kennard H, Lampard P, Scamman D, Arnell N, Ayeb-Karlsson S, Ford LB, Belesova K, Bowen K, Cai W, Callaghan M, Campbell-Lendrum D, Chambers J, Van Daalen KR, Dalin C, Dasandi N, … Costello A. 2022. The 2022 report of the Lancet Countdown on health and climate change: Health at the mercy of fossil fuels. Lancet 400;1619–54. DOI: https://doi.org/10.1016/S0140-6736(22)01540-9
Rood E, Khan A, Modak P, Mergenthaler C, van Gurp M, Blok L, Bakker M. 2018. A Spatial Analysis Framework to Monitor and Accelerate Progress towards SDG 3 to End TB in Bangladesh. ISPRS Internat J Geo-Informat 8:0014 DOI: https://doi.org/10.3390/ijgi8010014
Royal Tropical Institute (KIT). 2018. The MATCH manual. https://www.kit.nl/wp-content/uploads/2018/11/The-MATCH-Manual_2018.pdf
Simonin V, Vaghefi SA, Abdelgadir ZM, Eltayeb D, Sidahmed MAM, Monet J-P, Ray N. 2023. Present and Future drinking water security and its impacts on maternities: a multi-scale assessment of Sudan. Internat J Environ Res Public Health 20:2204. DOI: https://doi.org/10.3390/ijerph20032204
Soothoane R, Maime LM, van Gurp M, Semakula M, Curti A, Sello P, Letsie TR, Morienyane K, Khetheng M, Ray N. (2023, November 17). Abstract 543: Using spatial analysis of routine data through MATCH and AccessMod to inform subnational TB program planning in Lesotho. https://doi.org/10.1111/tmi.13931 DOI: https://doi.org/10.1111/tmi.13931
Tricco AC, Antony J, Zarin W, Strifler L, Ghassemi M, Ivory J, Perrier L, Hutton B, Moher D, Straus SE. 2015. A scoping review of rapid review methods. BMC Med 13:224. DOI: https://doi.org/10.1186/s12916-015-0465-6
UNDRR. (2016). Report of the open-ended intergovernmental expert working group on indicators and terminology relating to disaster risk reduction. Available from: https://www.preventionweb.net/files/50683_oiewgreportenglish.pdf
Van Den Homberg M, Monné R, Spruit M. 2018. Bridging the information gap of disaster responders by optimizing data selection using cost and quality. Computers Geosci 120:60–72. DOI: https://doi.org/10.1016/j.cageo.2018.06.002
Van Den Homberg M, Susha I. 2018. Characterizing data ecosystems to support official statistics with open mapping data for reporting on sustainable development goals. ISPRS Internat J Geo-Informat 7:456. DOI: https://doi.org/10.3390/ijgi7120456
van den Homberg M, Visser J, Veen M. (2017). Unpacking Data Preparedness from a humanitarian decision making perspective: Toward an assessment framework at subnational level. 14th ISCRAM Conference – Albi, France, May 2017.
Warsame A, Bashiir F, Freemantle T, Williams C, Vazquez Y, Reeve C, Aweis A, Ahmed M, Checchi F, Dalmar A. 2021. Excess mortality during the COVID-19 pandemic: A geospatial and statistical analysis in Mogadishu, Somalia. Internat J Infect Dis 113:190–9. DOI: https://doi.org/10.1016/j.ijid.2021.09.049
World Bank Group. 2024. World Bank Country and Lending Groups [Dataset]. Available from: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups
World Health Organization (WHO). 2021. Global tuberculosis report 2021. Available from: https://www.who.int/publications/i/item/9789240037021

How to Cite

Hierink, F., Yaghmaei, N., Bakker, M. I., Ray, N., & van den Homberg, M. (2024). Geospatial tools and data for health service delivery: opportunities and challenges across the disaster management cycle. Geospatial Health, 19(2). https://doi.org/10.4081/gh.2024.1284
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