A Cross-National Study of Disaster Risk Management: Strengths and Weaknesses in Bulgaria, Romania, and Albania with Reflections on Serbia

Authors

Anja Beli, Renate Renner, Vladimir M. Cvetković, Aleksandar Ivanov, Jasmina Gačić

Abstract

This study examines disaster risk management systems in Bulgaria, Romania, and Albania, highlighting their distinct strengths and weaknesses while drawing comparisons to Serbia’s framework. The research underscores the growing urgency of disaster risk management in addressing challenges posed by natural and man-made (technological) hazards, which are further aggravated by climate change, globalisation, and socio-economic shifts. The study identifies best practices alongside systemic weaknesses by assessing the normative, institutional, and strategic frameworks of these countries. Key strengths include comprehensive legal systems, robust international partnerships, and sophisticated early warning mechanisms. However, these strengths are counterbalanced by limited local capacity, fragmented institutional coordination, and inadequate public awareness. The analysis highlights the potential for regional cooperation through a comparative lens, emphasising the importance of engaging local communities, enhancing early warning technologies, and aligning with global disaster management standards. The findings offer valuable insights into ongoing discussions about constructing resilient societies, providing practical recommendations to enhance disaster risk management systems across Southeastern Europe.

Keywords

disaster risk management, strenghts, weaknesses, resilience, regional collaboration, institutional capacities, Bulgaria, Romania, Albania, Serbia

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 431-460
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Beli, A., Renner, R., Cvetković, V. M., Ivanov, A., & Gačić, J. (2025). A Cross-National Study of Disaster Risk Management: Strengths and Weaknesses in Bulgaria, Romania, and Albania with Reflections on Serbia. International Journal of Disaster Risk Management, 7(1), 431-460. https://doi.org/10.18485/ijdrm.2025.7.1.25

References

1. Adedigba, S., Khan, F., & Yang, M. (2018). An integrated approach for dynamic economic risk assessment of process systems. Process Safety and Environmental Protection, 116, 312-323. doi:https://doi.org/10.1016/J.PSEP.2018.01.013

2. Agence Europe. (n.d.). Bulletin article. Retrieved on October 19, 2024, from https://agenceurope.eu/en/bulletin/article/12117/12

3. Agjencia Kombëtare e Menaxhimit të Çështjeve Civile. (n.d.). Rreth AKMC [About AKMC]. Retrieved on October 23, 2024, from https://akmc.gov.al/rreth-akmc/

4. Albris, K., Lauta, K. C., & Raju, E. (2020). Disaster knowledge gaps: Exploring the interface between science and policy for disaster risk reduction in Europe. International Journal of Disaster Risk Science, 11, 1-12.

5. Alexander, D. E. (1993). Natural Disasters. Springer Science & Business Media.

6. Apostolov, N. (2013). Geografija turizma – jedan vek razvoja i dostignuća (Geography of Tourism: A Century of Development and Achievements). Varna: Nauka i Ekonomika.

7. Apostolov, N., Krstev, V. (2011). Za naučno izučavanje geografije turizma (For Scientific Study of Tourism Geography). Izvestija na IU, 2, 134-141.

8. Bedstviя, Available at: http://www.ipacbc-bgtr.eu/sites/ipacbc-bgtr-105.gateway.bg/files/uploads/eu_report_turkey_bulgaria_bg_teslim_final.pdf (Accessed: 15. oktobar 2024).

9. Cekrezi, B., 2024. Hydro-morphology, channel change and sediment transport dynamics of major Albanian Rivers. Rettrivied: https://iris.unitn.it/retrieve/handle/11572/407950/763604/phd_unitn_bestar_cekrezi.pdf Preuzeto: 20.10.2024.

10. Cheval, S., Bulai, A., Croitoru, A.-E., & Dorondel, S. (2022). Climate change perception in Romania. Theoretical and Applied Climatology, 149(9)

11. Comitetul Național pentru Situații de Urgență, 2020. Planul național de management al riscurilor de dezastre, Available at: https://legislatie.just.ro/Public/DetaliiDocument/178900 (Accessed: 15. oktobar 2024).

12. Council of the European Union. (2013). Council Decision 1313/2013/EU on the Union Civil Protection Mechanism. Official Journal of the European Union.

13. Cvetkovic, V. M., & Martinović, J. (2020). Innovative solutions for flood risk management. International Journal of Disaster Risk Management, 2(2), 71-100.

14. Cvetković, V. (2017). Prepreke unapređenju spremnosti za reagovanje u prirodnim katastrofama (Barriers to Improving Preparedness for Natural Disaster Response). Vojno delo, 69(2), 132-150.

15. Cvetković, V. (2018). Baze podataka o rizicima i informacioni servisi podrške odlučivanju u vanrednim situacijama – Risk Database and Management Support Information Services for Emergencies. Paper presented at Šesto savetovanje upravljanje rizicima, Požarevac, 25-34.

16. Cvetković, V. (2020). Disaster Risk Management. Belgrade: Scientific-Professional Society for Disaster Risk Management.

17. Cvetković, V. (2021). Jačanje sistema integrisanog upravljanja rizicima od katastrofa u Srbiji: DISARIMES (Strengthening the Integrated Disaster Risk Management System in Serbia: DISARIMES). Zbornik radova Naučno-stručnog društva za upravljanje rizicima u vanrednim situacijama, 77-111.

18. Cvetković, V. (2024b). Essential Tactics for Disaster Protection and Rescue. Scientific-Professional Society for Disaster Risk Management, Belgrade.

19. Cvetković, V. M. (2017). Metodologija istraživanja katastrofa i rizika: teorije, koncepti i metode (Methodology for Researching Disasters and Risks: Theories, Concepts, and Methods). Beograd: Zadužbina Andrejević.

20. Cvetković, V. M. (2023). A Predictive Model of Community Disaster Resilience based on Social Identity Influences (MODERSI). International Journal of Disaster Risk Management, 5(2), 57-80.

21. Cvetković, V. M. (2024). In-Depth Analysis of Disaster (Risk) Management System in Serbia: A Critical Examination of Systemic Strengths and Weaknesses.

22. Cvetković, V. M., & Šišović, V. (2024a). Capacity building in Serbia for disaster and climate risk education. In Disaster and Climate Risk Education: Insights from Knowledge to Action (pp. 299-323): Springer Nature Singapore Singapore.

23. Cvetković, V. M., & Šišović, V. (2024b). Community Disaster Resilience in Serbia. In: Scientific-Professional Society for Disaster Risk Management, Belgrade.

24. Cvetković, V. M., Radovanović, M. P., & Milašinović, S. M. (2021). Disaster risk communication: Attitudes of Serbian citizens. Sociološki pregled, 55(4), 1610-1647.

25. Cvetković, V. M., Roder, G., Öcal, A., Tarolli, P., Dragićević, S. (2018). The Role of Gender in Preparedness and Response Behaviors towards Flood Risk in Serbia. International Journal of Environmental Research and Public Health, 15, 2761.

26. Cvetković, V. M., Tanasić, J., Ocal, A., Kešetović, Ž., Nikolić, N., & Dragašević, A. (2021). Capacity Development of Local Self-Governments for Disaster Risk Management. International Journal of Environmental Research and Public Health, 18(19), 10406.

27. Cvetković, V. M., Tanasić, J., Öcal, A., Kešetović, Ž., Nikolić, N., Dragašević, A. (2022). Capacity Development of Local Self-Governments for Disaster Risk Management. International Journal of Environmental Research and Public Health, 18, 10406.

28. Cvetković, V., & Andrić, K. (2023). Comparative Analysis of Disaster Risk Management Systems in Germany, USA, Russia and China. Preprints, 2023020267 (doi: https://doi.org/10.20944/preprints202302.0267.v1).

29. Cvetković, V., & Ivković, T. (2022). Social Resilience to Flood Disasters: Demographic, Socio-economic and Psychological Factors of Impact. Paper presented at the 12th International Conference of the International Society for the Integrated Disaster Risk Management, Cluj-Napoca, Romania, 21-23 September 2022.

30. Cvetković, V., & Janković, B. (2020). Private security preparedness for disasters caused by natural and anthropogenic hazards. International Journal of Disaster Risk Management, 2(1), 23-33.

31. Cvetković, V., & Milašinović, S. (2017). Theory of vulnerability and disaster risk reduction. Kultura Polisa, 33(2), 217-228.

32. Cvetković, V., & Todorović, S. (2021). Comparative analysis of disaster risk management policies in the region of south-east Europe. International yearbook, Faculty of Security Studies, 0.20544/IYFS.20539.20541.20519.P20501.

33. Cvetković, V., Filipović, M., Gačić, J. (2019). Zbirka propisa iz oblasti upravljanja rizicima u vanrednim situacijama (Collection of Regulations on Disaster Risk Management in Emergency Situations). Beograd: Naučno-stručno društvo za upravljanje rizicima u vanrednim situacijama.

34. Cvetković, V., Öcal, A., Ivanov, A. (2019). Young Adults’ Fear of Disasters: A Case Study of Residents from Turkey, Serbia, and Macedonia. International Journal of Disaster Risk Reduction. doi:https://doi.org/10.1016/j.ijdrr.2019.101095.

35. Cvetković, V., Renner, R., Lukić, T., & Aleksova, B. (2024). Geospatial and Temporal Patterns of Natural and Man-made (Technological) Disasters (1900-2024): Insights from Different Perspectives. Preprints(https://doi.org/10.20944/preprints202408), 2024080175.

36. Đinović, Lj. (2011). Razvoj metode za procenu ugroženosti od samozapaljenja deponija uglja termoelektrana – magistarski rad (Development of a Method for Assessing Vulnerability to Spontaneous Combustion of Coal Dumps in Power Plants – Master's Thesis). Beograd: Univerzitet u Beogradu, Rudarsko-geološki fakultet.

37. EC 2014. Serbia Floods 2014, Available at: https://fpi.ec.europa.eu/system/files/2021-05/pdna_-_serbia_2014_-_report.pdf (Accessed: 15. oktobar 2024).

38. ES (2022). European Civil Protection and Humanitarian Aid Operations: Bulgaria. Available at: https://civil-protection-humanitarian-aid.ec.europa.eu/what/civil-protection/national-disaster-management-system/bulgaria_en (Accessed: 14. oktobar 2024).

39. EU 2020. Evropeйski podhodi i politiki za predotvratяvane i zaщita na gorskite požari i

40. European Commission. (2022). Press the corner document. Retrieved from https://ec.europa.eu/commission/presscorner/api/files/document/print/en/ip_22_6944/ip_22_6944_en.pdf

41. Federal Research Division, Library of Congress, 1994. Albania: a country study. Claitor's Pub. Division. ISBN 0844407925

42. French, K., & Kousky, C. (2023). The effect of disaster insurance on community resilience: a research agenda for local policy. Climate Policy, 23, 662-670. doi:https://doi.org/10.1080/14693062.2023.2170313

43. Gerds, T., Cai, T., & Schumacher, M. (2008). The Performance of Risk Prediction Models. Biometrical Journal, 50. doi:https://doi.org/10.1002/bimj.200810443

44. Grozdanić, G., & Cvetković, M. V. (2024). Exploring Multifaceted Factors Influencing Community Resilience to Earthquake-Induced Geohazards: Insights from Montenegro. In: Scientific-Professional Society for Disaster Risk Management, Belgrade.

45. Imperiale, A., & Vanclay, F. (2016). Experiencing local community resilience in action: Learning from post-disaster communities. Journal of Rural Studies, 47, 204-219. doi:https://doi.org/10.1016/J.JRURSTUD.2016.08.002

46. Interreg IPA CBC Bulgaria-Serbia Programme. (n.d.). Territorial strategy analysis BG-RS. Retrieved from http://www.ipacbc-bgrs.eu/sites/ipacbc-bgrs-105.gateway.bg/files/territorial_strategy_analysis_bg-rs_bg.pdf

47. Interreg IPA CBC Bulgaria-Turkey Programme. (n.d.). Activity book in Bulgarian. Retrieved from http://www.ipacbc-bgtr.eu/sites/ipacbc-bgtr-105.gateway.bg/files/uploads/activity_book_in_bulgarian.pdf

48. Izumi, T., Shaw, R., Djalante, R., Ishiwatari, M., Komino, T. (2019). Disaster Risk Reduction and Innovations. Progress in Disaster Science, 2, 100033.

49. Jamshidi, A., Ait-Kadi, D., Ruiz, A., & Rebaiaia, M. (2018). Dynamic risk assessment of complex systems using FCM. International Journal of Production Research, 56, 1070-1088. doi:https://doi.org/10.1080/00207543.2017.1370148

50. Just.ro. (2024). Detalii document. Retrieved on October 16, 2024, from https://legislatie.just.ro/Public/DetaliiDocument/285383

51. Just.ro. (2024). Detalii document. Retrieved on October 17, 2024, from https://legislatie.just.ro/Public/DetaliiDocument/84536

52. Kapucu, N., & Sadiq, A.-A. (2016). Disaster Policies and Governance: Promoting Community Resilience. Politics and Governance, 4, 58-61. doi:https://doi.org/10.17645/PAG.V4I4.829

53. Kapucu, N., Hawkins, C. V., & Rivera, F. I. (2013). Disaster preparedness and resilience for rural communities. Risk, Hazards & Crisis in Public Policy, 4(4), 215-233.

54. Keković, Z., Nikolić, V. (2006). Upravljanje rizicima kao preduslov efikasnog kriznog menadžmenta (Risk Management as a Prerequisite for Efficient Crisis Management). U: Z. Keković, N. Komazec, G. Glišić (ur.), Pristupi metodologiji procene rizika (Approaches to Risk Assessment Methodology). Nauka, Bezbednost, Policija, 14(3). Beograd: KPU.

55. Lavell, A., & Maskrey, A. (2014). The future of disaster risk management. Environmental Hazards, 13(4), 267-280.

56. Mankolli, H., Proko, V. and Asllani, A., 2008. Contribution towards identification of climate change aspects in Albania. Ohrid-Republic of Macedonia, Balwois.

57. Ministarstvo unutrašnjih poslova (2021). Nacionalna programa za namalяvane na riska ot bedstviя 2021-2025. [pdf] Retrieved from https://www.eufunds.bg/sites/default/files/uploads/eip/docs/2021-09/Nacionalna%20programa%20za%20namalяvane%20na%20riska%20ot%20bedstviя%202021-2025-%D0%B3.pdf [13. October 2024].

58. Ministerul Mediului, Apelor și Pădurilor. (n.d.). Strategia națională privind adaptarea la schimbările climatice pentru perioada 2022-2030. Retrieved on October 17, 2024, from https://www.mmediu.ro/categorie/strategia-nationala-privind-adaptarea-la-schimbarile-climatice-pentru-perioada-2022-2030/419

59. Ministry of Internal Affairs of Bulgaria. (2022). National strategy for risk reduction: Risk assessment [Nacionalna strategiя za namalяvane na riska ot bedstviя: Ocenka]. Retrieved on September 17, 2024, from https://iacpsofia.mvr.bg/docs/librariesprovider43/namalяvane-na-riska-ot-bedstviя/ocenka_nac-strategia_nrb-06042022.pdf?sfvrsn=e6345d6d_4Syrakov, D., Prodanova, M. Slavov, K. (2004). Description and performance of Bulgarian Emergency Response System in case of nuclear accident (BERS), International Journal of Environment and Pollution, Vol. 20, No. 1-6., pp. 286-296.

60. Morar, C., Lukić, T., Basarin, B., Valjarević, A., Vujičić, M., Niemets, L., . . . Nagy, G. (2021). Shaping Sustainable Urban Environments by Addressing the Hydro-Meteorological Factors in Landslide Occurrence: Ciuperca Hill (Oradea, Romania). International Journal of Environmental Research and Public Health, 18. doi:https://doi.org/10.3390/ijerph18095022

61. Nacionalna ctpategiя za namalяvane na picka ot bedctviя 2018-2030 g., doctypno na: https://mvr.bg/docs/librariesprovider43/dokymenti-ot-dipekciяta/nopmativna-ypedba/ctpategičecki-dokymenti/rms-strategijanrb.pdf?sfvrsn=119f000b_2 (04.09.2024.) (18.09.2024.)

62. NATO. (2024). Search results for Albania. Retrieved from https://www.nato.int/cps/en/natohq/search.htm?query=ALBANIA&submitSearch=Marinova, T., Malcheva, K., Bocheva, L., & Trifonova, L. 2017. Climate profile of Bulgaria in the period 1988-2016 and brief climatic assessment of 2017. *Bulgarian Journal of Meteorology and Hydrology*, 22(3-4), pp. 2-15.

63. Nikolova, M. (2023). Impact of climate change on the extreme weather hazards and natural disasters in Bulgaria. Review of the Bulgarian Geological Society. doi:https://doi.org/10.52215/rev.bgs.2023.84.2.77

64. Norris, F.H., Stevens, S.P., Pfefferbaum, B., Wyche, K.F. and Pfefferbaum, R.L., 2008. Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. American Journal of Community Psychology, 41, pp.127-150.

65. Oniga, V.E., Crenganiş, L., Diac, M. and Chiripa, C., 2020. Overview on remote sensing methods and data sources for floods and landslides management. Buletinul Institutului Politehnic din lasi. Sectia Constructii, Arhitectura, 66(4), pp.59-70.

66. Paltrinieri, N., Khan, F., & Cozzani, V. (2015). Coupling of advanced techniques for dynamic risk management. Journal of risk research, 18, 910-930. doi:https://doi.org/10.1080/13669877.2014.919515

67. Pavićević, O., Bylatović, A., Ilijić, Lj. (2019). Otpornost asimetrije makro-diskursa i mikro procesa (Resilience of Asymmetry in Macro-discourse and Micro-processes). Beograd: Institut za kriminološka i sociološka istraživanja.

68. Petrov, G. (2017). Disaster Risk Management: General Peer Review of the Disaster Management System in the Republic of Bulgaria. 27-30. doi:https://doi.org/10.1007/978-94-024-1071-6_6

69. Planul Național De Management Al Riscurilor de Dezastre https://igsu.ro/Resources/COJ/ProgrameStrategii/pdf24_merged.pdf

70. Pojani, E., & Hudhra, X. Disaster risk perception and risk communication case study research focused on Albanian flood-prone areas. In the book of proceedings (p. 139).

71. Posea, G., & Bucharest, I. (1975). The Socialist Republic of Romania-geographical characteristics. Geoforum, 6, 15-19. doi:https://doi.org/10.1016/0016-7185(75)90007-X

72. Radeva, K., Nikolova, N. (2020). Hydrometeorological Drought Hazard and Vulnerability Assessment for Northern Bulgaria. Geographica Pannonica, 24(2), 112-123.

73. Sandu I, Mateescu E, Vătămanu V., (2010). Schimbări climatice în România şi efectele asupra agriculturii. SITECH Publishing House, Craiova, p 406.

74. Sayers, P., Li, Y., Galloway, G., Penning-Rowsell, E. C., Fuxin, S., Kang, W., Yiwei, C., Le Quesne, T. (2013). Flood Risk Management: A Strategic Approach. Paris: UNESCO.

75. Secretariatul General al Guvernului. (2024). Anexa 17. Retrieved from https://sgg.gov.ro/1/wp-content/uploads/2024/07/ANEXA-17.pdf

76. SFÎCĂ, L. A. L. (2013). Thermal differentiations induced by the Carpathian Mountains on the Romanian territory.

77. Simova, I., Petrova, T., Velichkova, R., Markov, D., Uzunova, M., & Pushkarov, M. (2018). ANALYSIS OF CRITICAL DISASTERS IN BULGARIA BASED ON THEIR CLASSIFICATION. CBU International Conference Proceedings. doi:https://doi.org/10.12955/CBUP.V6.1315

78. Thornton, D. (2002). Constructing and Testing a Framework for Dynamic Risk Assessment. Sexual Abuse: A Journal of Research and Treatment, 14, 139-153. doi:https://doi.org/10.1177/107906320201400205

79. Trifonova, P., Metodiev, M., Solakov, D. and Simeonova, S., 2023. Safety and security planning and disaster management in case of an earthquake in Bulgaria. International Multidisciplinary Scientific GeoConference: SGEM, 23(5.1), pp.595-603.

80. Tsonkov, N.,Petrov, K., Slaveva, K., & Berberova-Vulcheva, C. (2023). Dynamics in regional development of municipalities with a population between 10 and 30 thousand in Eastern Bulgaria. Sofia.

81. Twigg, J. (2004). Disaster risk reduction: mitigation and preparedness in development and emergency programming. Retrieved from

82. United Nations Development Programme. (2024). Summary document. Retrieved on October 23, 2024, from https://www.undp.org/sites/g/files/zskgke326/files/2024-01/permbledhje_en_clear_8.6.2023.pdf ). 23,10

83. United Nations Office for Disaster Risk Reduction. (2015). Sendai Framework for Disaster Risk Reduction 2015–2030. Geneva, Switzerland.

84. Vasileva, R., Georgiev, A., Romanova, H., Vasileva, R., Georgiev, A., & Romanova, H. (2019). Floods - a leading disaster for Bulgaria. Varna Medical Forum. doi:https://doi.org/10.14748/VMF.V8I2.6075

85. Velichkova, R., Simova, I., Angelova, R., & Uzunova, M. (2021). Analysis of Hydrological Hazards Based on The Relief of Bulgaria. 2021 6th International Symposium on Environment-Friendly Energies and Applications (EFEA), 1-5. doi:https://doi.org/10.1109/EFEA49713.2021.9406223

86. Vlada Republike Albanije. (2019). Ligji për Mbrojtjen Civile Nr. 45/2019. Retrieved from https://www.qbz.gov.al/

87. World Bank. (2018). Romania: Disaster Risk Management Development Policy Loan with a Catastrophe Deferred Drawdown Option. Retrieved on October 20, 2024, from https://www.worldbank.org/en/news/loans-credits/2018/06/26/romania-disaster-risk-management-development-policy-loan-with-a-catastrophe-deferred-drawdown-optionDiaconu, Daniel Constantin. "Flood Risk Management in Romania." In Flood Handbook, pp. 179-200. CRC Press, 2022.

88. Xiong, J., & Espinet Alegre, X. (2019). Climate Resilient Road Assets in Albania. World Bank.

89. Yu, H. (2017). Dynamic risk assessment of complex process operations based on a novel synthesis of soft-sensing and loss function. Process Safety and Environmental Protection, 105, 1-11. doi:https://doi.org/10.1016/J.PSEP.2016.10.006

90. Zakon o civilnoj zaštiti Rumunije https://legislatie.just.ro/Public/DetaliiDocument/56923

91. Zakon za bezopacno izpolzvane na яdpenata enepgiя, doctypno na: https://lex.bg/laws/ldoc/2135455545 (03.09.2024.)

92. Zakon za ustrojstvo na teritorijata (Law on Territorial Organization). Available at: https://lex.bg/laws/ldoc/2135163904 (Accessed 1. septembra 2024).

93. Zakon za vodite, doctypno na: https://lex.bg/laws/ldoc/2134673412 (01.09.2024.)

94. Zakon za zaštitu pri bedstvija (Law on Disaster Protection). Available at: https://lex.bg/laws/ldoc/2135540282 (Accessed 1. septembra 2024).

95. Zakon za zaщita na okolnata cpeda, doctypno na: https://www.moew.government.bg/bg/zakon-za-opazvane-na-okolnata-sreda-6671/ (01.09.2024.)

96. Zoran, M., Zoran, L., Dida, A., & Dida, M. (2012). Climate changes and their impacts on Romanian mountain forests. 8531. doi:https://doi.org/10.1117/12.974389

97. Zulean, M., & Prelipcean, G. (2013). Emergency preparedness in Romania: Dynamics, shortcomings and policy proposals. Technological Forecasting and Social Change, 80(9), 1714-1724.

Smart Life Safety Jacket For Rescuers

Authors

Subhankar Sarkar

Abstract

Smart Life safety jackets have been widely used in flood rescue operations for many years. However, most of these jackets are outdated and lack integration with modern technology. Due to this, rescuers often encounter several operational challenges. Therefore, the implementation of advanced technology in the design of life safety jackets has been considered necessary for improving disaster response efficiency. The primary objective of this study is to develop a bright life safety jacket that incorporates modern technologies, including the Internet of Things (IoT), wireless sensor networks, GPS, and oxygen level monitoring. Real-time condition tracking, including rescue time, has also been set as a significant focus of this research. A design-based methodology has been adopted to integrate multiple advanced technologies into the bright jacket. Key components include IoT modules, sensors, GPS, wireless communication networks, and user interaction systems. Various technical and usability aspects have been explored through literature reviews and feasibility studies conducted during different stages of the research. Through this study, a bright life safety jacket has been proposed that is equipped with modern features intended to enhance rescue operations. Key functionalities, including GPS tracking, oxygen level detection, wireless sensor networks, and real-time communication through IoT platforms, have been incorporated to enhance coordination between rescuers and control rooms. The proposed clever life safety jacket design offers several advantages, including enhanced situational awareness and reduced risk of injury. By using modern sensor and cloud technologies, the safety and efficiency of both rescuers and victims during flood emergencies are expected to be significantly enhanced.

Keywords

Smart Life Safety Jacket, Internet of Things, GPS, sensors, ESP-32 microcontroller, results

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 367-384
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Sarkar, S. (2025). Smart Life Safety Jacket For Rescuers. International Journal of Disaster Risk Management, 7(1), 367-384. https://doi.org/10.18485/ijdrm.2025.7.1.21

References

1. A literature review on IoT-based soldier health monitoring e-jacket. (2023). International Research Journal of Modernization in Engineering Technology and Science ( Peer-Reviewed, Open Access, Fully Refereed International Journal), 05(02), e-ISSN: 2582-5208. https://www.irjmets.com/uploadedfiles/paper/issue_2_february_2023/33517/final/fin_irjmets1676464912.pdf

2. Akhil Xavier, Anila P. Udhayakumar, Arun T. A., Diniya Devassykutty, & Jayalakhmi P. K. (2018). Smart Jacket: A Water Safety System Utilising GPS Location. Global Research and Development Journal for Engineering, ERTEE-2018.

3. Balaji, M., Monika, S., Akshaya, N., Priya, R. S., & Swathi, A. (2023). The Shrewd Security Coat: An IoT-Based Smart Safety Jacket for Construction and Mining Worker Safety. International Research Journal of Engineering and Technology (IRJET), 10(5).

4. Cox, K. L., Bhaumik, S., Gupta, M., & Jagnoor, J. (2021). Facilitators and barriers of life jacket use for drowning prevention: Qualitative evidence synthesis. Journal of Safety Research. https://doi.org/10.1016/j.jsr.2021.11.010

5. Cvetković, V. M., & Miljković, N. (2024). Evaluation of the Effectiveness of Search and Rescue Dogs inFinding Survivors During Disasters: The Case of Serbia, Croatia, and Slovenia. 10. International European Congresson Advanced Studies in Basic Sciences, 26-28 July 2024, Amsterdam, Netherlands, pp. 1237-1253;

6. Cvetković, V. M., & Miljković, N. (2024). Legal and Organizational Framework for the Use of Search and Rescue Dogs in Disasters: A Comparative Analysis between Serbia, Croatia, and Slovenia. 10.International European Congress on Advanced Studies in Basic Sciences, 26-28 July 2024, Amsterdam, Netherlands,pp. 1254-1268;

7. Cvetković, V. M.,& Miljković, N. (2024). Challenges and Obstacles in the Use of Search and Rescue Dogs During Disaster Operations:A Case Study of the Earthquake in Turkey. 6th International Congress on Scientific Research, and we invite you to this meeting on July 24-26, 2024, organised by the IKSAD Institute, pp. 957-968.

8. D. B. Nguyen, T. Le Minh, N. Van Truc and H. Vu Tran, "Building a Smart Life Jacket Based on the IoT Platform," 2023 International Conference on Advanced Technologies for Communications (ATC), Da Nang, Vietnam, 2023, pp. 527-533, doi: https://doi.org/10.1109/ATC58710.2023.10318940.

9. El-Khozondar, H. J., Mtair, S. Y., Qoffa, K. O., Qasem, O. I., Munyarawi, A. H., Nassar, Y. F., Bayoumi, E. H., & Halim, A. a. E. B. a. E. (2024). A smart energy monitoring system using ESP32 microcontroller. e-Prime - Advances in Electrical Engineering Electronics and Energy, 9, 100666. https://doi.org/10.1016/j.prime.2024.100666

10. Espressif Systems. (n.d.). ESP32 Series Datasheet Version 4.9. https://www.espressif.com/sites/default/files/documentation/esp32_datasheet_en.pdf

11. G. E. M. Abro, S. A. Shaikh, S. Soomro, G. Abid, K. Kumar, and F. Ahmed, "Smart jacket for coal miners using IoT," 2018 International Conference on Computing, Electronic and Electrical Engineering (iCCECE), 2019. DOI: https://doi.org/10.1109/iCCECOME.2018.8658851

12. Gaikwad, S. B., Patil, P. P., Sangar, P. C., Patil, S. D., & Ashok, B. G. (2022). Smart Safety Jacket for Army. International Journal of Innovations in Engineering Research and Technology (IJIERT), 9(6), 31–37.

13. Hashimoto, K., Horie, S., Nagano, C., Hibino, H., Mori, K., Fukuzawa, K., Nakayama, M., Tanaka, H., & Inoue, J. (2021). A fan-attached jacket worn in an environment exceeding body temperature suppresses an increase in core temperature. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-00655-2

14. Hercog, D., Lerher, T., Truntič, M., & Težak, O. (2023). Design and implementation of ESP32-Based IoT devices. Sensors, 23(15), 6739. https://doi.org/10.3390/s23156739

15. Jindal, S. K., Mahajan, A., & Raghuwanshi, S. K. (2019). An inductive-capacitive-circuit-based micro-electromechanical system wireless capacitive pressure sensor for avionic applications: Preliminary investigations, theoretical modelling and simulation examination of newly proposed methodology. Measurement and Control, 52(7-8), 1029–1038. https://doi.org/10.1177/0020294019858095

16. Kundan Shingade, Sagar Pawar, Vipul Jadhav, Krunal Kadam (2018). "IoT Based Women Safety Jacket", International Journal of Creative Research Thoughts (IJCRT), Volume 6, Issue 2, ISSN: 2320-2882.

17. Lim, J., Choi, H., Roh, E. K., Yoo, H., & Kim, E. (2015). Assessment of airflow and microclimate for a running wear jacket with slits using computational fluid dynamics (CFD) simulation. Fashion and Textiles, 2(1). https://doi.org/10.1186/s40691-014-0025-2

18. LM35 LM35 Precision Centigrade Temperature Sensors Calibrated Directly in Celsius (Centigrade) • Linear + 10-mV/°C Scale Factor • 0.5°C Ensured Accuracy (at 25°C) • Rated for Full −55°C to 150°C Range • Suitable for Remote Applications • Low-Cost Due to Wafer-Level Trimming • Operates From 4 V to 30 V • Less Than 60-μA Current Drain • Low Self-Heating, 0.08°C in Still Air • Non-Linearity Only ±¼°C Typical • Low-Impedance Output, 0.1 Ω for 1-mA Load 2 Applications • Power Supplies • Battery Management • HVAC • Appliances 3 Description. (n.d.). https://www.ti.com/lit/ds/symlink/lm35.pdf

19. M. Jakarea et al., "Smart Savior: A Life Jacket Integrated IoT Emergency Response System Utilizing TTGO T-Call ESP32 and Advanced Sensor Technologies," 2025 4th International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, 2025, pp. 106-110, doi: https://doi.org/10.1109/ICREST63960.2025.10914402

20. M. Santhanalakshmi, M. Radhika, G. Elavel Visuvanathan, S. Dhanalakshmi, G. Kavitha and C. Srinivasan, "IoT Enabled Wearable Technology Jacket for Tracking Patient Health and Safety System," 2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon), Singapore, Singapore, 2023, pp. 918-922, doi: https://doi.org/10.1109/SmartTechCon57526.2023.10391431.

21. M. Suman and G. Jyothi, "Smart soldier system using GPS and health monitoring," JETIR, vol. 10, no. 10, Oct. 2023. www.jetir.org/papers/JETIR2310423.pdf

22. MACFOS. (2020, August 15). MQ Series Gas Sensor | Robu.in. Robu.in | Indian Online Store | RC Hobby | Robotics. https://robu.in/mq-series-gas-sensor/

23. Marceta, Ž., & Jurišic, D. (2024). Psychological Preparedness of the Rescuers and Volunteers: A Case Study of 2023Türkiye Earthquake. International Journal of Disaster Risk Management, 6(1), 27–40.

24. MAX30102. (n.d.). https://www.analog.com/media/en/technical-documentation/data-sheets/max30102.pdf

25. MECHANICAL DATA. (n.d.). https://www.vishay.com/docs/37484/lcd016n002bcfhet.pdf

26. Molnár, A. (2024). A Systematic Collaboration of Volunteer and Professional Fire Units in Hungary. International Journal of Disaster Risk Management, 6(1), 1–13.

27. N. S. Kumar, C. R, N. S. M, P. R and P. V. P, "Wearable IoT Life Jacket: Utilizing LoRa Technology to Combat Hypothermia," 2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), Coimbatore, India, 2024, pp. 23-27, doi: https://doi.org/10.1109/ICSSEECC61126.2024.10649536

28. Nacua, A. E., Dominguez, M., & Santos, N. O. (2016). Rescue boat and life vest design using recycled materials for flood disaster risk mitigation in Manila. International Journal of Current Microbiology and Applied Sciences, 5(4), 1036–1041. https://doi.org/10.20546/ijcmas.2016.504.118

29. O. Gatera, K. Mtonga, P. Kubwimana, D. F. Audace, E. Ndayishimiye and E. Basar, "Design and Performance Analysis of an IoT Network Based Smart Safety Jacket for Miners," 2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN), Bangkok, Thailand, 2023, pp. 117-122, doi: https://doi.org/10.1109/CICN59264.2023.10402243.

30. P. Randhawa, V. Shanthagiri, R. Mour, and A. Kumar, "Smart jacket for human posture and activity classification using fabric sensors and ML," 2018 International Conference on Soft-computing and Network Security (ICSNS), 2018. DOI: https://doi.org/10.1109/ICSCEE.2018.8538384

31. Rakshitha M1, Shreyas R2, Yeshas C Balaji3, Rakshitha Urs S4. (2019). Smart Soldier Jacket Using Internet of Things (IoT). International Research Journal of Engineering and Technology (IRJET), 06(08), 2019, IRJET. https://www.irjet.net/archives/V6/i8/IRJET-V6I8210.pdf

32. Renusha, K., Sindhumathy, S., Sujitha, S., & Udhayasuriya, B. (2024). Intelligent Safety Life Jacket Using LoRa Technology. Journal of Frontiers in Engineering and Technology, 19(3). https://doi.org/10.26634/jfet.19.3.20595

33. Sakhare, N. S. A., Kale, N. a. A., More, N. D. G., Kumkar, N. P. A., Mirase, N. J. M., & Sahu, N. U. S. (2023). Smart wearable safety jacket. International Journal of Advanced Research in Science Communication and Technology, 8–14. https://doi.org/10.48175/ijarsct-9311

34. Samrat D, & Dr. Shivalingapa. S. Kubsad. (2014). Design and Development of Safety Jacket. International Journal of Engineering Research & Technology, 3(7). https://doi.org/10.17577/IJERTV3IS070987

35. Smart Life Saver Jacket. (2020). Vasanthakumar.M,Etal. Journal of Engineering Research and Application, 10(4), 06–09. https://doi.org/10.9790/9622-1004050609

36. Srievatsan, B. U., & Jindal, S. K. (2022). Raspberry Pi Powered Communicatable Intelligent Life Jacket. WAC-2022: Workshop on Applied Computing, January 27–28, 2022, Chennai, India. CEUR Workshop Proceedings.

37. Sudar, S., Cvetković, V. M., & Ivanov, A. (2024). Harmonization of Soft Power and Institutional Skills: Montenegro’s Path to Accession to the European Union in the Environmental Sector. International Journal of Disaster Risk Management, 6(1), 41–74.

38. T. Zhou, J. Yang, Q. Long and S. Li, "Design of an Intelligent Water-Rescue Life Jacket System Based on Satellite Positioning," 2023 13th International Conference on Information Technology in Medicine and Education (ITME), Wuyishan, China, 2023, pp. 510-514, doi: https://doi.org/10.1109/ITME60234.2023.00107.

39. u-blox. (2011). NEO-6: u-blox 6 GPS Modules. https://content.u-blox.com/sites/default/files/products/documents/NEO-6_DataSheet_%28GPS.G6-HW-09005%29.pdf

40. Uses Of Integrated AI and Machine Learning: Machine Learning and AI Technologies for Smart Wearables by Kah Phooi Seng, Li-Minn Ang, Eno Peter and Anthony Mmonyi. Improved Communication Systems: Advancing Safety Standards with Real-Time Embedded Smart Jacket Dr. Sahana Raj B S, Abhishek Gowda B M, Nayana R, Dhanraj B M, Yeshwanth D S 10.17148/IARJSET.2024.11565

Project DINGGIN: Empowering Communities through Risk‐Based and Inclusive Cash Transfer in Disaster‐Prone Areas in Bangladesh and Philippines

Authors

Rhinadel M. Canete, Samantha Kay Lisay, Md. Nazmus Sayadat Mahmud

Abstract

Disaster-prone communities in Albay, Philippines and Bhola, Bangladesh, face recurring typhoons, cyclones, and floods that simultaneously destroy homes, disrupt livelihoods, and threaten food security. Traditional cash transfer programs (CTPs) for disaster relief often lack inclusive, risk-informed design and fail to account for the intersectional vulnerabilities of at-risk groups. Project DINGGIN (Dynamic Inclusive Network for Governance, Guidance, Intersectionality, and Nexus) addresses this gap by developing a risk-based, community-informed cash transfer framework. The approach bridges bottom-up risk data gathered through household surveys, participatory risk mapping, focus groups, and interviews with top-down policy frameworks within a humanitarian-development-peace nexus approach. Data from Albay and Bhola revealed that affected households prioritise simultaneous home rebuilding and income recovery; however, existing cash assistance is fragmented and not well-coordinated. Using a decision-support dashboard, local governments and communities co-developed tailored Cash Transfer Values (CTVs) reflecting each community’s specific disaster risks and socioeconomic needs. The results demonstrate that an integrated cash transfer strategy—addressing shelter, food, and livelihoods together—can provide immediate relief while strengthening long-term resilience. For example, households in high-risk zones received larger grants for shelter reinforcement and livelihood restoration, aligning assistance with locally identified needs. This risk-informed, inclusive CTP model improved community ownership and met humanitarian Sphere standards for equity and adequacy. The discussion of Project DINGGIN’s pilot indicates strengthened multi-sectoral coordination and highlights areas for improvement, such as providing multi-phase support beyond the emergency phase, offering financial literacy training to beneficiaries, and implementing adaptive disbursement schedules. The study concludes that empowering communities to co-design cash interventions not only ensures a more effective disaster response but also institutionalises resilience-building for future crises, aligning with national disaster management plans and international frameworks.

Keywords

community-managed disaster risk reduction (CMDRR), risk-based cash transfer, hybrid governance, participatory risk mapping, disaster preparedness, humanitarian nexus, community resilience

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 339-366
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

M. Canete, R., Lisay, S. K., & Sayadat Mahmud, M. N. (2025). Project DINGGIN: Empowering Communities through Risk‐Based and Inclusive Cash Transfer in Disaster‐Prone Areas in Bangladesh and Philippines. International Journal of Disaster Risk Management, 7(1), 339-366. https://doi.org/10.18485/ijdrm.2025.7.1.20

References

1. Binas, R. (2009). Making Community Managed Disaster Risk Reduction Operational at Community Level: A Guide. Caritas Czech Republic.Chambers, R. (1997). Whose Reality Counts? Putting the First Last. London: Intermediate Technology Publications.

2. Cañete, Rhinadel; Lisay, Samantha Kay; Sayadat, Md. (2025). Project DINGGIN: A Hybrid Approach to Empowering Communities through Risk-Based and Inclusive Cash Transfers. DOI: https://doi.org/10.13140/RG.2.2.21460.92804

3. Carla S, R. G. (2019). School-Community Collaboration: Disaster Preparedness for Building Resilient Communities. International Journal of Disaster Risk Management, 1(2), 45-59.

4. Crenshaw, K. (1989). Demarginalising the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 1989(1), 139–167.

5. Cvetković, V. M., Tanasić, J., Ocal, A., Kešetović, Ž., Nikolić, N., & Dragašević, A. (2021). Capacity Development of Local Self-Governments for Disaster Risk Management. International Journal of Environmental Research and Public Health, 18(19). doi:https://doi.org/10.3390/ijerph181910406

6. Cvetković, V., Öcal, A., & Ivanov, A. (2019). Young adults’ fear of disasters: A case study of residents from Turkey, Serbia and Macedonia. International Journal of Disaster Risk Reduction, 35, 101095. doi: https://doi.org/10.1016/j.ijdrr.2019.101095

7. Cvetković, V., Šišović, V. (2024). Community Disaster Resilience in Serbia. Belgrade: Scientific-Professional Society for Disaster Risk Management.

8. Global Forum on Innovation in Health Professional Education (Institute of Medicine). (2015). The Bridging Leadership Paradigm for Multi-Stakeholder Governance. Washington, DC: National Academies Press.

9. Government of Bangladesh. (2012). Disaster Management Act, 2012 (Act No. 34 of 2012). Dhaka: Government of the People’s Republic of Bangladesh.

10. Government of Bangladesh. (2013). Rights and Protection of Persons with Disabilities Act, 2013. Dhaka: Ministry of Social Welfare.

11. Government of Bangladesh. (2019). Standing Orders on Disaster (Revised Edition). Dhaka: Ministry of Disaster Management and Relief.

12. Government of Bangladesh. (2020). National Plan for Disaster Management (NPDM) 2021–2025. Dhaka: Ministry of Disaster Management and Relief.

13. Institute of Medicine. (2015). Envisioning the Future of Health Professional Education: Workshop Summary. (See Appendix F: Bridging Leadership Framework). Washington, DC: National Academies Press.

14. Kabir, M. H., Hossain, T., & Haque, M. W. (2022). Resilience to natural disasters: A case study on the southwestern region of coastal Bangladesh. International Journal of Disaster Risk Management, 4(2), 91-105.

15. Lisay, Samantha Kay & Sayadat, Md & Cañete, Rhinadel. (2025). A Risk-Informed, Inclusive Approach to Cash Transfers: Empowering Communities Through Hybrid Governance.

16. Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., & Pfefferbaum, R. L. (2008). Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. American Journal of Community Psychology, 41(1–2), 127–150.

17. Ostrom, E. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge, UK: Cambridge University Press.

18. Republic of the Philippines. (1992). Magna Carta for Disabled Persons (Republic Act No. 7277). Manila: Congress of the Philippines.

19. Republic of the Philippines. (2010). Philippine Disaster Risk Reduction and Management Act of 2010 (Republic Act No. 10121). Manila: Congress of the Philippines.

20. Republic of the Philippines. (2020). National Disaster Risk Reduction and Management Plan (NDRRMP) 2020–2030. Manila: National Disaster Risk Reduction and Management Council.

21. Sphere Association. (2018). The Sphere Handbook: Humanitarian Charter and Minimum Standards in Humanitarian Response. Geneva: Sphere.

22. Van Aalst, M. K., Cannon, T., & Burton, I. (2008). Community level adaptation to climate change: The potential role of participatory community risk assessment. Global Environmental Change, 18(1), 165–179.

Female Gender Empowerment, Individualism, Collectivism, and Resilience: A Comparative Study in the Context of Disaster Risk Management

Authors

Torkuma Matthew Garba, Ikenna Amuka, Richard Akaan

Abstract

The paper examines the relationship between female gender empowerment, societal ideologies (individualism and collectivism), and disaster resilience. It examines whether higher female empowerment is correlated with greater individualism and whether male empowerment aligns with collectivist values. Additionally, it evaluates how these ideological orientations influence societal resilience in disaster contexts. Utilising data from the Global Gender Gap Report, Hofstede’s Cultural Dimensions, and the UNDRR Resilience Index, this study employs Pearson’s correlation analysis to determine relationships between gender empowerment and ideology. At the same time, multiple regression modelling assesses their impact on disaster resilience. Findings reveal a strong correlation between female empowerment and individualism, as well as between male empowerment and collectivism. Regression results indicate that individualism has a negative influence on resilience, while collectivism enhances resilience. These results suggest that collectivist societies, often characterised as male-dominated, may provide stronger structural support for disaster risk management, whereas individualistic societies linked to female empowerment may face challenges in coordinating disaster responses. The findings underscore the need for policies that integrate both individualistic and collectivist strengths to enhance global disaster response and sustainable development.

Keywords

gender empowerment, individualism, collectivism, disaster resilience, risk management

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 313-324
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Garba, T. M., Amuka, I., & Akaan, R. (2025). Female Gender Empowerment, Individualism, Collectivism, and Resilience: A Comparative Study in the Context of Disaster Risk Management. International Journal of Disaster Risk Management, 7(1), 313-324. https://doi.org/10.18485/ijdrm.2025.7.1.18

References

1. Aleksandrina, M., Budiarti, D., Yu, Z., Pasha, F., & Shaw, R. (2019). Government incentivisation for SME's engagement in disaster risk management. International Journal of Disaster Management and Environmental Security Studies, 1(1), 32-50

2. Asgari, M., Ashtarian, H., Heidari, S., &Khezeli, M. (2018). Individualism-collectivism, social support, resilience, and suicidal ideation among women with the experience of the death of a young person. International Journal of Community Based Nursing and Midwifery, 6(2), 250–259.

3. Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242–261.

4. Cvetković, V. M., & Šišović, V. (2024). Understanding the sustainable development of community (social) disaster resilience in Serbia: Demographic and socio-economic impacts. Sustainability, 16(7), 2620

5. Cvetkovic, V., & Martinović, J. (2020). Innovative solutions for flood risk management. International Journal of Disaster Risk Management, 2(2), 71-100.

6. Cvetković, V., & Planić, J. (2022). Earthquake risk perception in Belgrade: implications for disaster risk management. International Journal of Disaster Risk Management, 4(1), 69-88.

7. Davis, I., & Alexander, D. (2016). Recovery from disaster. Routledge.

8. Enarson, E., & Morrow, B. H. (Eds.). (1998). The gendered terrain of disaster: Through women's eyes.Praeger Publishers.

9. Fordham, M. (2011). Gender, sexuality, and disaster. In B. Wisner, J. C. Gaillard, & I. Kelman (Eds.), Handbook of hazards and disaster risk reduction (pp. 424–435). Routledge.

10. Goyal, N. (2019). Disaster governance and community resilience: The law and the role of SDMAs. International Journal of Disaster Management and Environmental Security Studies, 1(2), 61-75

11. Gurung, J. D. (1999). Searching for women's voices in the Hindu-Kush Himalayas. Gender, Technology and Development, 3(1), 63–80.

12. Hasan, M. K., & Niger Sultana. (2024). Dynamics of Internal Migration in the Southwest Region of Bangladesh. International Journal of Disaster Risk Management, 6(1), 13–26.

13. Hofstede, G. (2001). Culture's consequences: Comparing values, behaviours, institutions, and organizations across nations (2nd ed.). Sage Publications.

14. International Federation of Red Cross and Red Crescent Societies. (2010). A practical guide to gender-sensitive approaches for disaster management. Retrieved from https://www.preventiveweb.net

15. Jaiye, D.J. & Benjamin, O. (2021). Building resilience through local and international partnerships: Nigeria experiences. International Journal of Disaster Management and Environmental Security Studies, 3(2), 11-24

16. Jenkins, P., & Phillips, B. (2008). Battered women, catastrophe, and the context of safety after Hurricane Katrina. NWSA Journal, 20(3), 49–68.

17. Kabir, M.H. Hossain, T. & Haque, M.W. (2022). Resilience to natural disasters: A case study on Southwestern region of coastal Bangladesh. International Journal of Disaster Management and Environmental Security Studies, 4(2), 91-105

18. Khan, S. (2016). Gender-responsive disaster management: A pathway to sustainable development. International Journal of Disaster Risk Reduction, 18, 82–88.

19. Lee, H., & Kim, A. (2020). Female gender empowerment and cultural ideologies: A comparative study of Eastern and Western societies. International Journal of Sociology, 18(2), 77–91.

20. Mileti, D. S. (1999). Disasters by design: A reassessment of natural hazards in the United States. Joseph Henry Press.

21. Molnár, A. (2024). A Systematic Collaboration of Volunteer and Professional Fire Units in Hungary. International Journal of Disaster Risk Management, 6(1), 1–13.

22. Morrow, B. H., &Enarson, E. (1996). Hurricane Andrew through women's eyes: Issues and recommendations. International Journal of Mass Emergencies and Disasters, 14(1), 5–22.

23. Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., &Pfefferbaum, R. L. (2008). Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. American Journal of Community Psychology, 41(1–2), 127–150.

24. Oxfam International. (2005). The tsunami's impact on women. Retrieved from https://policy-practice.oxfam.org

25. Pelling, M. (2003). The vulnerability of cities: Natural disasters and social resilience. Earthscan.

26. Smith, J. (2022). Female gender empowerment and societal development. Journal of Social Science, 44(1), 53–67.

27. UN Women. (2021). Gender dimensions of disaster risk and resilience: Existing evidence. Retrieved from https://wrd.unwomen.org

28. United Nations Development Programme. (2010). Gender, climate change, and community-based adaptation. Retrieved from https://www.undf.org

29. United Nations Office for Disaster Risk Reduction. (2021). Resilience index. Retrieved from https://www.undrr.org/publication/undrr-annual-report-2021

30. Wisner, B., Blaikie, P., Cannon, T., & Davis, I. (2004). At risk: Natural hazards, people's vulnerability, and disasters (2nd ed.). Routledge.

31. World Economic Forum (2023). Global gender gap report. Retrieved from https://www.weforum.org.

Assessing Agricultural Vulnerability to Climate Change: A Study on Flood-Induced Loss and Damage in Rajapur, Bardiya, Nepal

Authors

Shristi Paudel, Sanjay Nath Khanal, Ajay Bhakta Mathema, Pratap Maharjan, Sewak Bhatta

Abstract

More frequent and severe extreme climate events have caused both economic and non-economic losses to local communities in disaster-prone areas due to climate change. This study examines the economic loss and damage to agriculture caused by an unseasonal flood in October 2021 in Rajapur Municipality, located along the Karnali River. The lower Karnali basin is highly prone to flooding, and Rajapur, situated between two arms of the river, has a long history of such events. Using household surveys, focus group discussions (FGDs), key informant interviews (KIIs), and secondary literature, the study assessed flood-related losses among small, medium, and large farmers based on key indicators from the Building Information Platform Against Disaster (BIPAD), including agricultural land, paddy production, stored grains, livestock, and farm machinery. The October 2021 flood, which occurred just before harvest, caused significant economic losses. Small farmers incurred a loss of $21,709.77, medium farmers faced a loss of $50,225.24, and large farmers experienced a loss of $32,393.49, resulting in a total production loss of $104,328.10. Small and medium farmers suffered greater impacts on their livelihoods, income, and food security than large farmers. Coping mechanisms included purchasing rice, consuming wheat instead of rice, taking loans, working as labourers, abandoning education, and cultivating spring-season rice. While adaptation measures, such as early warning systems and embankments, have helped prevent human casualties, mitigating agricultural losses remains a challenge as floodwaters continue to devastate farmlands, underscoring the need for improved flood management strategies to safeguard agricultural productivity and rural livelihoods.

Keywords

climate change, flood damage, agricultural loss, economic loss, coping mechanisms, adaptation strategies

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 265-282
Published: 2025-06-30

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Paudel, S., Khanal, S. N., Mathema, A. B., Maharjan, P., & Bhatta, S. (2025). Assessing Agricultural Vulnerability to Climate Change: A Study on Flood-Induced Loss and Damage in Rajapur, Bardiya, Nepal. International Journal of Disaster Risk Management, 7(1), 265-282. https://doi.org/10.18485/ijdrm.2025.7.1.15

References

1. Amarnath G, Saikia P (2017), “Reducing vulnerability among smallholder farmers through index-based flood insurance in India : equity matters,” no. 19, p. 4, [Online]. Available: http://ibfi.iwmi.org/Data/Sites/37/pdf/ibfi-gender-equity-technical-brief.pdf

2. Aryal, D., Wang, L., Adhikari, T.R., Zhou, J., Li, A., Shrestha, M., Wang, Y. & Chen, D., (2020), “A model-based flood hazard mapping on the southern slope of Himalaya,” Water (Switzerland), vol. 12, no. 2, doi: https://doi.org/10.3390/w12020540.

3. Boyd, E., James, R.A., Jones, R.G., Young, H.R. & Otto, F.E.L. (2017), “A typology of loss and damage perspectives,” Nat. Clim. Chang., vol. 7, no. 10, pp. 723–729, doi: https://doi.org/10.1038/nclimate3389.

4. Bronstert, A. (2003), “Floods and Climate Change: Interactions and Impacts,” Risk Anal., vol. 23, no. 3, pp. 545-557(13) ST-Floods and Climate Change: Inter.

5. Cvetković, V. (2021). Innovative solutions for disaster early warning and alert systems: A literary review. https://doi.org/10.21203/rs.3.rs-923237/v1

6. DHM (2017), “Observed Climate Trend Analysis of Nepal,” Dep. Hydrol. Meteorol. Nepal.

7. Dugar, S. (2016), “Flood Dynamics in the Karnali Basin, West Nepal”. https://floodresilience.net/blogs/flood-dynamics-in-the-karnali-basin-west-nepal/

8. DWIDP (2014), “DISASTER REVIEW 2013”. https://reliefweb.int/report/nepal/disaster-review-2013

9. Eckstein, D. & Kreft, S. (2021), Global climate risk index 2021. Who suffers most from extreme weather events? Available: http://germanwatch.org/en/download/8551.pdf

10. EMDAT (2019), “International disasters database of the center for research on the epidemiology of disasters.” https://cred.be/sites/default/files/CredCrunch54.pdf

11. FAO (2020), FAO’s methodology for damage and loss assessment in agriculture. doi: https://doi.org/10.4060/ca6990en. https://openknowledge.fao.org/handle/20.500.14283/ca6990en

12. Gyawali, A. (2019), “Analysis of Annual and Seasonal Temperature Variability in The Karnali River Analysis of Annual and Seasonal Temperature Variability in The Karnali River Basin , Nepal,” doi: https://doi.org/10.5281/zenodo.3243460.

13. Huggel, C., Carey, M., Emmer, A., Frey, H., Walker-Crawford, N. &Wallimann-Helmer, I. (2020), “Anthropogenic climate change and glacier lake outburst flood risk: Local and global drivers and responsibilities for the case of lake Palcacocha, Peru,” Nat. Hazards Earth Syst. Sci., vol. 20, no. 8, pp. 2175–2193, doi: https://doi.org/10.5194/nhess-20-2175-2020.

14. Intergovernmental Negotiating Committee (1991), “Vanuatu: Draft annex relating to Article 23 (Insurance) for inclusion in the revised single text on elements relating to mechanisms (A/AC.237/WG.II/Misc.13) submitted by the Co-Chairmen of Working Group II.” p. 10,. [Online]. Available: https://unfccc.int/sites/default/files/resource/docs/a/wg2crp08.pdf

15. IPCC (2021), “Climate change widespread, rapid, and intensifying.” https://www.ipcc.ch/2021/08/09/ar6-wg1-20210809-pr/

16. Jha, S. (2017), “How Farmers Cope with Natural Disasters in Bangladesh, Pakistan,” Asian Development Blog. https://blogs.adb.org/blog/how-farmers-cope-with-natural-disasters-bangladesh-pakistan#:~:text=Instead of stashing away some, immediate losses from disaster exposure.

17. Khatiwada, K.R., Panthi, J. & Shrestha, M. (2015), “Hydro-climatic Trends in Karnali River Basin of Nepal Himalaya,” no. January, p. 2013, 2012, doi: https://doi.org/10.13140/2.1.1387.5526.

18. Khatiwada, K.R., Panthi, J., Shrestha, M.L. & Nepal, S. (2016), “Hydro-climatic variability in the Karnali River Basin of Nepal Himalaya,” Climate, vol. 4, no. 2, pp. 1–14, doi: https://doi.org/10.3390/cli4020017.

19. Kocanda, J & Puhakka, K. (2012), “Living with floods along the Karnali River.” https://lup.lub.lu.se/student-papers/record/2543562/file/2834893.pdf

20. MoFE (2021), “National Adaptation Plan (NAP) 2021-2050 Summary.” https://unfccc.int/sites/default/files/resource/NAP_Nepal_2021.pdf

21. MoFE (2021), “National Framework on Climate Induced Loss and Damage (L&D).” https://actalliance.org/wp-content/uploads/2021/11/LD_Final_DCANepal-RS.pdf

22. National Planning Commission (2017), “Post Flood Recovery Needs Assessment”. [Online]. Available: https://www.npc.gov.np/images/category/PFRNA_Report_Final.pdf

23. Neupane, B., Joshi, R., Ghimire, S., Bhatta, S. & Panta, M. (2023), “Nature-Based Solutions: Mitigating Flood Effects on Forest Tree Biodiversity and Societal Factors”, Scientific Reports in Life Sciences, vol. 4, no. 3. Zenodo, pp. 53–68. doi: https://doi.org/10.5281/zenodo.10198530.

24. Newar, N. (2014), “Nepal’s Poor Live in the Shadow of Natural Disasters,” Reliefweb. https://reliefweb.int/report/nepal/nepal-s-poor-live-shadow-natural-disasters

25. Oates, J.A.H. (2007), “Annex 1: Glossary of Terms,” Lime Limestone, pp. 403–424, doi: https://doi.org/10.1002/9783527612024.oth1.

26. Oxfam (2022), “Footing the bill. Fair finance for loss and damage in an era of escalating climate impacts,” vol. 18, no. 6. 2022. doi: https://doi.org/10.4135/9781446252055.n10.

27. Oxfam (2023), “Disaster Risk Reduction.” https://nepal.oxfam.org/what-we-do-sustainable-development-programme/disaster-risk-reduction#:~:text=Increased frequencies of disaster have,in terms of flood risk.

28. PMAMP (2022), “Prime Minister Agriculture Modernization Project.” http://bardiyasuperzone.pmamp.gov.np/welcome

29. Practical Action (2021), “Climate-Induced Loss and Damage in Nepal.” https://infohub.practicalaction.org/bitstreams/32a21f61-3bbb-427e-b9b1-013d04272653/download

30. Rajapur Municipality (2021), “Local Disaster and Climate Resilience Plan (LDCRP) of Rajapur Municipality”.

31. Rentschler, J. & Salhab, M. (2020), “Flood Exposure and Poverty in 189 Countries.Policy Research Working Paper,” no. October, p. Policy Working Paper 9447, [Online]. Available: https://openknowledge.worldbank.org/handle/10986/34655

32. Septiningsih, E.M., Pamplona, A.M., Sanchez, D.L., Neeraja, C.N., Vergara, G.V., Heuer, S., Ismail, A.M. & Mackillet, D.J..(2009), “Development of submergence-tolerant rice cultivars: The Sub1 locus and beyond,” Ann. Bot., vol. 103, no. 2, pp. 151–160, doi: https://doi.org/10.1093/aob/mcn206.

33. Shirzaei, M., Khoshmanesh, M., Ojha, C., Werth, S., Kerner, H., Carlson, G., Sherpa, S.F., Zhai, G. & Lee, J. (2021), “Persistent impact of spring floods on crop loss in U.S. Midwest,” Weather Clim. Extremes., vol. 34, no. October, p. 100392, doi: https://doi.org/10.1016/j.wace.2021.100392.

34. Sukhwani, V., Adu-Gyamfi, B., Zhang, R., Alhinai, A., & Shaw, R. (2019). Understanding the barriers restraining effective operation of flood early warning systems. International Journal of Disaster Risk Management, 1(2), 1–17. https://doi.org/10.18485/ijdrm.2019.1.2.1

35. Tamrakar, A. & Bajracharya, R. (2020), “Standardization of Loss and Damage datasets on BIPAD,” Youth Innov. Lab, pp. 1–33.

36. Tripathi, P. (2015) “Flood Disaster in India : An Analysis of trend and Preparedness,” Interdiscip. J. Contemp. Res., vol. 2, no. 4, pp. 91–98, [Online]. Available: https://www.researchgate.net/profile/Prakash_Tripathi/publication/292980782_Flood_Disaster_in_India_An_Analysis_of_trend_and_Preparedness/links/56b36ac208ae156bc5fb25bd.pdf

37. UNEP (2020), “How climate change is making record-breaking floods the new normal.” https://www.unep.org/news-and-stories/story/how-climate-change-making-record-breaking-floods-new-normal,

38. UNFCCC (2013), “Decision 14/CP.19: “Modalities for measuring, reporting and verifying,” Rep. Conf. Parties its Ninet. Sess. held Warsaw from 11 to 23 November. 2013 Add. Part two Action Tak. by Conf. Parties its Ninet. Sess”., pp. 39–43, [Online]. Available: https://unfccc.int/resource/docs/2013/cop19/eng/10a01.pdf#page=39

39. World Bank (2022), “In Nepal, 2 Major Climate Disasters in a Single Year Highlight the Need to Build Resilience.” [Online]. Available: https://www.worldbank.org/en/news/feature/2022/03/28/in-nepal-2-major-climate-disasters-in-a-single-year-highlight-the-need-to-build-resilience

40. Yu, G., Di, L., Zhang, B., Shao, Y., Shrestha, R. & Kang, L. (2013), “Remote-sensing-based flood damage estimation using crop condition profiles,” 2013 2nd Int. Conf. Agro-Geoinformatics Inf. Sustain. Agric. Agro-Geoinformatics 2013, no. Vci, pp. 205–210, doi: https://doi.org/10.1109/Argo-Geoinformatics.2013.6621908.

The Role of Spatial Analysis in Notifiable Disease Monitoring and Health Risk Management: A Case Study of Constantine

Authors

Samira Djebari, Siham Bestandji

Abstract

The study aims to enhance understanding of the distribution of notifiable diseases using maps created with ArcGIS in Constantine. Over six years, it focused on the prevalence rates of waterborne diseases and zoonoses (e.g., tuberculosis, meningitis, and COVID-19). A database was created for each municipality using official data, which was processed using SPSS and Microsoft Excel and integrated into a geographic information system (GIS). The maps revealed a high prevalence of diseases in the state's centre, particularly in the municipalities of Constantine, El Khroub, Didouche, and Mourad. The analysis also highlighted a positive relationship between the increase in disease cases and population density, emphasising the critical role of urbanisation in disease spread. Furthermore, seasonal variations were observed in the distribution of certain diseases, indicating that environmental factors, such as temperature and rainfall, influence disease outbreaks. As a result of this study, the maps have demonstrated a fundamental role in monitoring diseases and their development, offering valuable insights for public health surveillance and policy formulation. By visualising trends and patterns, these maps can support decision-making processes to manage health risks better and allocate resources effectively in the region.

Keywords

disaster, health risk, spatial analysis, management, Covid-19, Constantine

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 215-234
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Djebari, S., & Bestandji, S. (2025). The Role of Spatial Analysis in Notifiable Disease Monitoring and Health Risk Management: A Case Study of Constantine. International Journal of Disaster Risk Management, 7(1), 215-234. https://doi.org/10.18485/ijdrm.2025.7.1.12

References

1. Astagneau, P., & Mégarbane, M. M. (2011). Surveillance épidémiologique. In M. M. Mégarbane & J. M. Launay (Eds.), Santé publique (pp. 309–319

2. Beale, L. A. (2008). Methodological issues and approaches to spatial epidemiology. Environmental Health Perspectives, 1105–1110.https://doi.org/10.1289/ehp.10816

3. Beck, L. R., Lobitz, B. M., & Wood, B. L. (2000). Remote sensing and human health: New sensors and new opportunities. Emerging Infectious Diseases, 6(3), 217–227. https://doi.org/10.3201/eid0603.000302

4. Cvetković, V. M., Nikolić, N., Radovanović, D., & Milinović, S. (2020). Preparedness and preventive behaviours for a pandemic disaster caused by COVID-19 in Serbia. International Journal of Environmental Research and Public Health, 17(11), 4124. https://doi.org/10.3390/ijerph17114124

5. Cvetković, V. M., Nikolić, N., Ocal, A., Martinović, J., & Dragašević, A. (2022). A Predictive Model of Pandemic Disaster Fear Caused by Coronavirus (COVID-19): Implications for Decision-Makers. International journal of environmental research and public health, 19(2), 652.

6. Desjardins, M. R., Hohl, A., & Delmelle, E. M. (2020). Rapid assessment of COVID-19 spatial accessibility in the United States. PLOS ONE, 15(8), e0237294. https://doi.org/10.1371/journal.pone.0237294

7. Port, K. J. N., & Jawahar, G. G. P. (2024). Management of COVID: The Creeping Disaster in the Indian Scenario. IJDRM, 6(1), 103–110. https://ijdrm.com/archives/vol6issue1/port2024

8. Jerrett, M., Burnett, R. T., Pope, C. A., Ito, K., Thurston, G., Krewski, D., ... & Thun, M. J. (2005). Long-term ozone exposure and mortality. New England Journal of Medicine, 360(11), 1085–1095. https://doi.org/10.1056/NEJMoa1045616

9. Janković, B., & Cvetković, V. (2020). Public Perception of Police Behaviour in the COVID-19 Disaster – The Case of Serbia. Policing: An International Journal, 43(6), 979-992

10. Kirby, R. S., Delmelle, E., & Eberth, J. M. (2017). Advances in spatial epidemiology and geographic information systems. Annals of Epidemiology, 27(1), 1–9. https://doi.org/10.1016/j.annepidem.2016.12.001

11. Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics - Theory and Methods, 26(6), 1481–1496. https://doi.org/10.1080/03610929708831995

12. Ministry of Health, Population and Hospital Reform. (2022). Executive Decree No. 22-250 of 30 June 2022 establishing the list of communicable diseases subject to mandatory reporting under international surveillance

13. Öcal, A., Cvetković, V. M., Baytiyeh, H., Tedim, F. M. S., & Zečević, M. (2020). Public reactions to the disaster COVID-19: a comparative study in Italy, Lebanon, Portugal, and Serbia. Geomatics, Natural Hazards and Risk, 11(1), 1864-1885.

14. Pickle, L. W. (2009). Spatial analysis for epidemiology. Oxford University Press.

15. Rezaeian, M., Dunn, G., St Leger, S., & Appleby, L. (2007). Geographical epidemiology, spatial analysis and geographical information systems: A multidisciplinary glossary. Journal of Epidemiology and Community Health, 61(2), 98–102. https://doi.org/10.1136/jech.2005.043117.

16. Thacker, S. B., Stroup, D. F., & Parrish, R. G. (1996). Public health surveillance for chronic conditions: A scientific basis for decisions. Statistical Methods in Medical Research, 5(4), 293–309. https://doi.org/10.1177/096228029600500402

17. Ulal, S., & Karmakar, D. (2023). Hazard risk evaluation of COVID-19: A case study. International Journal of Disaster Risk Management, 5(2), 81–101.

Understanding Ransomware Through the Lens of Disaster Risk: Implications for Cybersecurity and Economic Stability

Authors

Nikola Vidović, Vladimir M. Cvetković, Hatidža Beriša, Srđan Milašinović

Abstract

Ransomware has emerged as a modern digital crisis, mirroring the widespread disruptions typically associated with natural or artificial disasters. As global economies grow increasingly interconnected through digital systems, the fallout from ransomware attacks stretches far beyond mere technical breaches. These incidents result in severe financial damage, disrupt operations, erode reputations, and contribute to broader socioeconomic instability. This study adopts a disaster risk perspective to examine the broader economic and social impact of ransomware, particularly its effects on critical infrastructure and public trust in institutions. Through a multi-case analysis of sixteen significant ransomware attacks between 2015 and 2025, the research highlights a recurring pattern: direct and indirect costs often compound, with impacts varying from ransom demands and halted services to reputational loss and sector-wide vulnerabilities. The rise of Ransomware-as-a-Service (RaaS) has also made these attacks more accessible and complex, deepening the threat landscape. The findings underscore the need to integrate cybersecurity into comprehensive disaster risk management strategies. Policymakers, institutions, and businesses must adopt a forward-looking approach—emphasising continuous risk evaluation, resilient digital infrastructure, and collaboration across sectors. To protect economies from escalating cyber threats, adaptive regulations and anticipatory defences are no longer optional—they're essential.

Keywords

ransomware, cybersecurity, disaster risk, digital economy, financial impact, critical infrastructure, cyber resilience, socio-economic consequences, risk governance, ransomware-as-a-service (RaaS)

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 247-264
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Vidović, N., Cvetković, V. M., Beriša, H., & Milašinović, S. (2025). Understanding Ransomware Through the Lens of Disaster Risk: Implications for Cybersecurity and Economic Stability. International Journal of Disaster Risk Management, 7(1), 247-264. https://doi.org/10.18485/ijdrm.2025.7.1.14

References

1. Aleksandrina, M., Budiarti, D., Yu, Z., Pasha, F., & Shaw, R. (2019). Governmental Incentivization for SMEs’ Engagement in Disaster Resilience in Southeast Asia. International Journal of Disaster Risk Management, 1(1), 32-50.

2. Al-ramlawi, A., El-Mougher, M., & Al-Agha, M. (2020). The Role of Al-Shifa Medical Complex Administration in Evacuation & Sheltering Planning. International Journal of Disaster Risk Management, 2(2).

3. Andersen, E. S. (2025). How to mitigate ransomware risk through data and risk quantification. Cyber Security: A Peer-Reviewed Journal. doi:https://doi.org/10.69554/ztgt3456

4. August, T., Dao, D., & Niculescu, M. F. (2019). Economics of ransomware attacks. Unpublished manuscript.

5. August, T., Dao, D., & Niculescu, M. F. (2022). Economics of ransomware: Risk interdependence and large-scale attacks. Management Science, 68(12), 8979–9002. https://doi.org/10.1287/mnsc.2021.4216

6. Axon, L., Erola, A., Agrafiotis, I., Uuganbayar, G., Goldsmith, M., & Creese, S. (2023). Ransomware as a Predator: Modelling the Systemic Risk to Prey. Digital Threats: Research and Practice, 4, 1-38. doi:https://doi.org/10.1145/3579648

7. Benmalek, M. (2024). Ransomware on cyber-physical systems: Taxonomies, case studies, security gaps, and open challenges. Internet of Things and Cyber-Physical Systems. doi:https://doi.org/10.1016/j.iotcps.2023.12.001

8. Carla S, R. G. (2019). School-community collaboration: disaster preparedness towards building resilient communities. International Journal of Disaster Risk Management, 1(2), 45-59.

9. Cashell, B., Jackson, W. D., Jickling, M., & Webel, B. (2004). The economic impact of cyber-attacks (CRS RL32331). Congressional Research Service.

10. Chen, S., Hao, M., Ding, F., Jiang, D., Dong, J., Zhang, S., Guo, Q., & Gao, C. (2023). Exploring the global geography of cybercrime and its driving forces. Humanities and Social Sciences Communications, 10, 71. doi:https://doi.org/10.1057/s41599-023-01560-x

11. Chin, K. (2024). The impact of cybercrime on the economy. Retrieved from https://www.upguard.com/blog/the-impact-of-cybercrime-on-the-economy

12. Cobos, E. V. (2024). Cybersecurity economics for emerging markets. Washington, DC: World Bank. doi:https://doi.org/10.1596/978-1-4648-2120-2

13. Cobos, V., Belen, E., & Selcen, C. (2024). A review of the economic costs of cyber incidents. Washington, DC: World Bank Group. Retrieved from http://documents.worldbank.org

14. Connolly, L., & Wall, D. (2019). The rise of crypto-ransomware in a changing cybercrime landscape: Taxonomising countermeasures. Comput. Secur., 87. doi:https://doi.org/10.1016/J.COSE.2019.101568

15. Connolly, L., Wall, D., Lang, M., & Oddson, B. (2020). An empirical study of ransomware attacks on organizations: an assessment of severity and salient factors affecting vulnerability. J. Cybersecur., 6. doi:https://doi.org/10.1093/cybsec/tyaa023

16. Cook, S., Giommoni, L., Trajtenberg Pareja, N., Levi, M., & Williams, M. L. (2023). Fear of economic cybercrime across Europe: A multilevel application of routine activity theory. The British Journal of Criminology, 63(2), 384–406. doi:https://doi.org/10.1093/bjc/azac093

17. Couce-Vieira, A., Insua, D. R., & Kosgodagan, A. (2020). Assessing and forecasting cybersecurity impacts. Decision Analysis, 17(4), 356–374. doi:https://doi.org/10.1287/deca.2020.0421

18. Cremer, F., Sheehan, B., Fortmann, M., Kia, A. N., Mullins, M., Murphy, F., & Materne, S. (2022). Cyber risk and cybersecurity: A systematic review of data availability. The Geneva Papers on Risk and Insurance - Issues and Practice, 47(3), 698–722. doi:https://doi.org/10.1057/s41288-021-00233-9

19. Cvetković, S. M., & V. (2013). Vulnerability of critical infrastructure by natural disasters. Paper presented at the National critical infrastructure protection, regional perspective., Belgrade.

20. Cvetković, V. (2019). Risk Perception of Building Fires in Belgrade. International Journal of Disaster Risk Management, 1(1), 81-91.

21. Cvetković, V. (2023). A Predictive Model of Community Disaster Resilience based on Social Identity Influences (MODERSI). International Journal of Disaster Risk Management, 5(2), 57-80.

22. Cvetković, V. (2024a). Disaster Risk Management. In: Scientific-Professional Society for Disaster Risk Management, Belgrade.

23. Cvetković, V. (2024b). Essential Tactics for Disaster Protection and Rescue. Scientific-Professional Society for Disaster Risk Management, Belgrade.

24. Cvetković, V. M. (2024a). Disaster Resilience: Guide for Prevention, Response and Recovery. In: Belgrade: Scientific-Professional Society for Disaster Risk Management.

25. Cvetković, V. M. (2024b). In-Depth Analysis of Disaster (Risk) Management System in Serbia: A Critical Examination of Systemic Strengths and Weaknesses.

26. Cvetković, V. M., & Šišović, V. (2024). Capacity building in Serbia for disaster and climate risk education. In Disaster and Climate Risk Education: Insights from Knowledge to Action (pp. 299-323): Springer Nature Singapore Singapore.

27. Cvetković, V. M., Dragašević, A., Protić, D., Janković, B., Nikolić, N., & Milošević, P. (2022). Fire safety behavior model for residential buildings: Implications for disaster risk reduction. International Journal of Disaster Risk Reduction, 76, 102981. doi:https://doi.org/10.1016/j.ijdrr.2022.102981

28. Cvetković, V. M., Renner, R., & Jakovljević, V. (2024). Industrial Disasters and Hazards: From Causes to Conse-quences—A Holistic Approach to Resilience. International Journal of Disaster Risk Management, 6(2), 149-168.

29. Cvetković, V. M., Tanasić, J., Ocal, A., Kešetović, Ž., Nikolić, N., & Dragašević, A. (2021). Capacity Development of Local Self-Governments for Disaster Risk Management. International Journal of Environmental Research and Public Health, 18(19), 10406.

30. Cvetković, V., & Grbić, L. (2021). Public perception of climate change and its impact on natural disasters. Journal of the Geographical Institute Jovan Cvijic.

31. Cvetković, V., & Janković, B. (2020). Private security preparedness for disasters caused by natural and anthropogenic hazards. International Journal of Disaster Risk Management, 2(1), 23-33.

32. Cvetković, V., & Kezunović, A. (2021). Security Aspects of Critical Infrastructure Protection in Anthropogenic Disasters: A Case Study of Belgrade. Research Squares - Preprint, 10.21203/rs.21203.rs-927528/v927521.

33. Cvetković, V., & Martinović, J. (2020). Inovative solutions for flood risk management. International Journal of Disaster Risk Management, 2(2), 71–100.

34. Cvetković, V., & Renner, R. (2024). Comprehensive Databases on Natural and Man-Made (Technological) Hazards and Disasters: Mapping Risks and Challenges. In: Belgrade: Scientific-Professional Society for Disaster Risk Management.

35. Cvetković, V., & Šišović, V. (2024). Understanding the Sustainable Development of Community (Social) Disaster Resilience in Serbia: Demographic and Socio-Economic Impacts. Sustainability, 16 (7), 2620. In.

36. Cvetković, V., Nikolić, A., & Ivanov, A. (2023). The Role of Social Media in the Process of Informing the Public About Disaster Risks. Journal of Liberty and International Affairs, 9(2), 104-119.

37. Cvetković, V., Tanasić, J., Renner, R., Rokvić, V., & Beriša, H. (2024). Comprehensive Risk Analysis of Emergency Medical Response Systems in Serbian Healthcare: Assessing Systemic Vulnerabilities in Disaster Preparedness and Response. Paper presented at the Healthcare.

38. Farahbod, K., Shayo, C., & Varzandeh, J. (2020). Cybersecurity indices and cybercrime annual loss and economic impacts. Journal of Business and Behavioral Sciences, 32(1), 63–71.

39. George, A. S., Baskar, T., & Srikaanth, P. B. (2024). Cyber threats to critical infrastructure: Assessing vulnerabilities across key sectors. Partners Universal International Innovation Journal, 2(1), 51–75. doi:https://doi.org/10.5281/zenodo.10639463

40. Goodell, J., & Corbet, S. (2022). Commodity market exposure to energy-firm distress: Evidence from the Colonial Pipeline ransomware attack. Finance Research Letters. doi:https://doi.org/10.1016/j.frl.2022.103329

41. Grace, J. (2023). Impact of cybersecurity measures on financial data breaches. International Journal of Modern Risk Management, 1(1). Retrieved from https://www.iprjb.org/journals/index.php/IJMRM/article/view/2097

42. Gulyas, O., & Kiss, G. (2023). Impact of cyber-attacks on the financial institutions. Procedia Computer Science, 219, 84–90.

43. HISCOX Group. (2024). Cyber readiness report 2024: Protecting reputation through cyber resilience. Retrieved from https://www.hiscoxgroup.com/sites/group/files/documents/2024-10/HSX245–2024-CRR.pdf

44. Hromada, M., & Lukas, L. (2012). Critical Infrastructure Protection and the Evaluation Process. International Journal of Disaster Recovery and Business Continuity, 3.

45. International Chamber of Commerce. (2024). Protecting the cybersecurity of critical infrastructure and their supply chains.

46. International Monetary Fund. (2024). Global financial stability report: The last mile – Financial vulnerabilities and risks.

47. Jimmy, F. (2024). Assessing the effects of cyber attacks on financial markets. Journal of Artificial Intelligence General Science, 6(1), 288–305. doi:https://doi.org/10.60087/jaigs.v6i1.254

48. Jurišić, D., & Marceta, Z. (2024). Collaborative Gaps: Investigating the Role of Civilian-Religious Authority Disconnection in Psychosocial Support Provision during the 2014 Floods. International Journal of Disaster Risk Management, 6(2), 1-18.

49. Kala, E. S. M. (2023). Critical role of cyber security in global economy. Open Journal of Safety Science and Technology, 13(4), 231–248.

50. Koliou, M., van de Lindt, J. W., Ellingwood, B., Dillard, M., Cutler, H., & McAllister, T. P. (2018). A critical appraisal of community resilience studies: Progress and challenges.

51. Krivokapić, Đ., Nikolić, A., Stefanović, A., & Milosavljević, M. (2023). Financial, accounting and tax implications of ransomware attack. Studia Iuridica Lublinensia, 32(1), 191–211. Retrieved from https://ssrn.com/abstract=4562912

52. Kumiko, F., & Shaw, R. (2019). Preparing International Joint Project: Use of Japanese Flood Hazard Map in Bangladesh. International Journal of Disaster Risk Management, 1(1), 62-80.

53. Künzler, F. (2023). Real cyber value at risk: An approach to estimate economic impacts of cyberattacks on businesses (Master's thesis). University of Zurich.

54. Kuzior, A., Brożek, P., Kuzmenko, O., Yarovenko, H., & Vasilyeva, T. (2022). Countering cybercrime risks in financial institutions: Forecasting information trends. Journal of Risk and Financial Management, 15(12), 613.

55. Kuzior, A., Tiutiunyk, I., Zielińska, A., & Kelemen, R. (2024). Cybersecurity and cybercrime: Current trends and threats. Journal of International Studies, 17(2), 220–239. doi:https://doi.org/10.14254/2071-8330.2024/17-2/12

56. Lee, I. (2021). Cybersecurity: Risk management framework and investment cost analysis. Business Horizons, 64(5), 659–671. doi:https://doi.org/10.1016/j.bushor.2021.02.022

57. Lis, P., & Mendel, J. (2019). Cyberattacks on critical infrastructure: An economic perspective. Economics and Business Review, 19(2), 24–47. doi:https://doi.org/10.18559/ebr.2019.2.2

58. Mijalković, S., & Cvetković, V. (2013). Vulnerability of critical infrastructure by natural disasters. Paper presented at the National critical infrastructure protection, regional perspective.

59. Mokhele, M. O. (2024). Centres or Units: Making Sense of Decentralisation of Disaster Management in South African Municipalities. International Journal of Disaster Risk Management, 6(2), 19-38.

60. Molina, R. M. A., Torabi, S., Sarieddine, K., Bou-Harb, E., Bouguila, N., & Assi, C. (2022). On Ransomware Family Attribution Using Pre-Attack Paranoia Activities. IEEE Transactions on Network and Service Management, 19, 19-36. doi:https://doi.org/10.1109/tnsm.2021.3112056

61. Molnár, A. (2024). A Systematic Collaboration of Volunteer and Professional Fire Units in Hungary. International Journal of Disaster Risk Management, 6(1), 1-13.

62. Mott, G., Turner, S., Nurse, J., Pattnaik, N., MacColl, J., Huesch, P., & Sullivan, J. (2024). 'There was a bit of PTSD every time I walked through the office door': Ransomware harms and the factors that influence the victim organization's experience. J. Cybersecur., 10. doi:https://doi.org/10.1093/cybsec/tyae013

63. Moussaileb, R., Cuppens-Boulahia, N., Lanet, J.-L., & Bouder, H. L. (2021). A Survey on Windows-based Ransomware Taxonomy and Detection Mechanisms. ACM Computing Surveys (CSUR), 54, 1-36. doi:https://doi.org/10.1145/3453153

64. Muniandy, M., Ismail, N., Al-Nahari, A., & Yao, D. N. (2024). Evolution and impact of ransomware: Patterns, prevention, and recommendations for organizational resilience. International Journal of Academic Research in Business and Social Sciences, 14. doi:https://doi.org/10.6007/IJARBSS/v14-i1/19803

65. Nagar, G. (2024). The Evolution of Ransomware: Tactics, Techniques, and Mitigation Strategies. International Journal of Scientific Research and Management (IJSRM). doi:https://doi.org/10.18535/ijsrm/v12i06.ec09

66. Pattnaik, N., Nurse, J., Turner, S., Mott, G., MacColl, J., Huesch, P., & Sullivan, J. (2023). It's more than just money: The real-world harms from ransomware attacks. ArXiv, abs/2307.02855. doi:https://doi.org/10.48550/arXiv.2307.02855

67. Perić, J., & Vladimir, C. M. (2019). Demographic, socio-economic and phycological perspective of risk perception from disasters caused by floods: case study Belgrade. International Journal of Disaster Risk Management, 1(2), 31-43.

68. Putnik, N. (2022). Sajber rat i sajber mir. Beograd: Akademska misao.

69. Putnik, N., Milošević, M., & Cvetković, V. (2022). Rensomver kao pretnja bezbednosti – društveni i krivičnopravni aspekti. Sociološki pregled, 56(1), 328–353.

70. Rahman, A. M., & Islam, S. (2022). Financial and social costs perspective impacts of cybercrime in the UAE: Policy-guidance addressing the problem in piecemeal approach. International Journal of Economics, Business and Management Studies, 9(2), 89–103. doi:https://doi.org/10.55284/ijebms.v9i2.718

71. Rebouh, N., Tout, F., Dinar, H., Benzid, Y., & Zouak, Z. (2024). Integrating Multi-Source Geospatial Data and AHP for Flood Susceptibility Mapping in Ain Smara, Constantine, Algeria. International Journal of Disaster Risk Management, 6(2), 245-264.

72. Reshmi, T. (2021). Information security breaches due to ransomware attacks - a systematic literature review. Int. J. Inf. Manag. Data Insights, 1, 100013. doi:https://doi.org/10.1016/J.JJIMEI.2021.100013

73. Robles-Carrillo, M., & García-Teodoro, P. (2022). Ransomware: An Interdisciplinary Technical and Legal Approach. Security and Communication Networks. doi:https://doi.org/10.1155/2022/2806605

74. Schwarz, M., Marx, M., & Federrath, H. (2021). A structured analysis of information security incidents in the maritime sector. arXiv preprint arXiv:2112.06545.

75. Seng, Y. J., Cen, T. Y., bin Mohd Raslan, M. A. H., Subramaniam, M. R., Xin, L. Y., Kin, S. J., Long, M. S., & Sindiramutty, S. R. (2024). In-depth analysis and countermeasures for ransomware attacks: Case studies and recommendations. Preprints. doi:https://doi.org/10.20944/preprints202408.2261.v1

76. Singh, H., & Sittig, D. (2016). A Socio-Technical Approach to Preventing, Mitigating, and Recovering from Ransomware Attacks. Applied Clinical Informatics, 7, 624-632. doi:https://doi.org/10.4338/ACI-2016-04-SOA-0064

77. Sudheer, S. (2024). Ransomware Attacks and Their Evolving Strategies: A Systematic Review of Recent Incidents. Journal of Technology and Systems. doi:https://doi.org/10.47941/jts.2399

78. Sviatun, O. V., Goncharuk, O. V., Roman, C., Kuzmenko, O., & Kozych, I. V. (2021). Combating cybercrime: Economic and legal aspects. WSEAS Transactions on Business and Economics, 18, 751–762.

79. Tariq, N. (2018). Impact of cyberattacks on financial institutions. Journal of Internet Banking and Commerce, 23(2), 1–11.

80. Tarter, A. (2017). Importance of cyber security. In Community policing – A European perspective: Strategies, best practices and guidelines (pp. 213–230).

81. Thakur, M. (2024). Cyber security threats and countermeasures in digital age. Journal of Applied Science and Education, 4(1), 1–20.

82. ThankGod, J. (2024). Cyber heists and trade turmoil: Uncovering the economic impact of cybersecurity breaches on global commerce. doi:https://doi.org/10.2139/ssrn.4858710

83. The Financial Action Task Force. (2023). Countering ransomware financing. FATF. Retrieved from http://www.fatf-gafi.org

84. Umer, S. S. (2024). Analysing in Post COVID-19 era: The Effect of Occupational Stress and Work-Life Balance on Employees Performance. International Journal of Disaster Risk Management, 6(1), 75-90.

85. Valackienė, A., & Odejayi, R. O. (2024). The impact of cyber security management on the digital economy: Multiple case study analysis. Intellectual Economics, 18(2), 261–283. doi:https://doi.org/10.13165/IE-24-18-2-02

86. Vibhas, S., Bismark, A. G., Ruiyi, Z., Anwaar, M. A., & Rajib, S. (2019). Understanding the barriers restraining effective operation of flood early warning systems. 1(2), In press.

87. Vidović, N., Cvetković, V. M., & Beriša, H. (2024). Optimising Disaster Resilience Through Advanced Risk Management and Financial Analysis of Critical Infra-structure in the Serbian Defence Industry. International Journal of Disaster Risk Management, 6(2), 183-200.

88. Wang, P., & Johnson, C. (2018). Cybersecurity incident handling: A case study of the Equifax data breach. Issues in Information Systems, 19(3), 66–72.

89. Wang, P., D'Cruze, H., & Wood, D. (2019). Economic costs and impacts of business data breaches. Issues in Information Systems, 20(2), 94–100.

90. Wedawatta, G. (2012). Resilience and adaptation of small and medium‐sized enterprises to flood risk. Disaster Prevention and Management: An International Journal, 21(4), 474-488. doi:https://doi.org/10.1108/09653561211256170

91. Wilner, A., Jeffery, A., Lalor, J., Matthews, K., Robinson, K., Rosolska, A., & Yorgoro, C. (2019). On the social science of ransomware: Technology, security, and society. Comparative Strategy, 38, 347-370. doi:https://doi.org/10.1080/01495933.2019.1633187

92. Wollerton, M. (2023). Ransomware Attacks. doi:https://doi.org/10.4135/cqresrre20230818

93. World Economic Forum. (2024). Global cybersecurity outlook 2024: Insight report. Retrieved from https://www3.weforum.org

94. World Economic Forum. (2025). Global cybersecurity outlook 2025: Insight report. Retrieved from https://reports.weforum.org

95. Yuste, J., & Pastrana, S. (2021). Avaddon ransomware: an in-depth analysis and decryption of infected systems. ArXiv, abs/2102.04796. doi:https://doi.org/10.1016/j.cose.2021.102388

96. Zimba, A., & Chishimba, M. (2019). On the Economic Impact of Crypto-ransomware Attacks: The State of the Art on Enterprise Systems. European Journal for Security Research, 4, 3-31. doi:https://doi.org/10.1007/s41125-019-00039-8

Leveraging Artificial Intelligence for Enhanced Disaster Response Coordination

Authors

Fikret Emre Ocal, Salih Torun

Abstract

This review critically examines the transformative role of artificial intelligence (AI) in coordinating the core phases of disaster response: preparedness, response, recovery, and mitigation. Drawing on illustrative case studies such as AI-driven flood forecasting with Delft-FEWS, post-disaster damage mapping via DroneDeploy, and optimised emergency dispatch through RescueME. It synthesises evidence on five core AI capabilities (machine learning, deep learning, computer vision, natural language processing, and optimisation algorithms). We find that AI can substantially improve predictive accuracy, real-time situational awareness, rapid decision-making, resource allocation, and inter-agency collaboration, thereby addressing the speed and complexity challenges of traditional disaster management. However, adoption is hindered by fragmented data ecosystems, opaque “black box” models, interoperability gaps, cybersecurity vulnerabilities, ethical and equity concerns, and limited accessibility in low-resource settings. To overcome these barriers, we argue for the development of interoperable data standards, explainable AI frameworks, robust cyber governance protocols, and inclusive stakeholder engagement. Emerging trends, such as the convergence of AI with IoT and edge computing, enhanced human-AI decision support, and the democratisation of AI tools, offer promising pathways for building more resilient, scalable, and ethically grounded disaster response systems. By aligning technological innovation with human oversight and participatory governance, strategic integration of AI can enhance preparedness, response effectiveness, and recovery efficiency, fostering safer and more resilient communities worldwide.

Keywords

artificial intelligence, disaster management, machine learning, computer vision, explainable AI, situational awareness

Publication Details

Journal: International Journal of Disaster Risk Management
Year: 2025
Volume: 7
Issue: 1
Pages: 235-246
Published: 2025-06-16

DOI and Full Text

DOI: View DOI record
Article Page: View article page
PDF: Download full-text PDF

Suggested Citation

Ocal, F. E., & Torun, S. (2025). Leveraging Artificial Intelligence for Enhanced Disaster Response Coordination. International Journal of Disaster Risk Management, 7(1), 235-246. https://doi.org/10.18485/ijdrm.2025.7.1.13

References

22. Harika, A., Balan, G., Thethi, H. P., Rana, A., Rajkumar, K. V., & Al Allak, M. A. (2024). Harnessing the power of artificial intelligence for disaster response and crisis management. In Proceedings of the 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) (pp. 1–8). IEEE. https://doi.org/10.1109/IC3SE62002.2024.10593506

23. Internal Displacement Monitoring Centre. (2024). How AI is advancing socioeconomic insights into disaster displacement. https://www.internal-displacement.org/expert-analysis/how-ai-is-advancing-socioeconomic-insights-into-disaster-displacement/

24. Jiao, J., Lewis, S. H., Xu, Y., Sussman, K., & Atkinson, L. (2024). Multilingual AI-assisted emergency preparedness [Poster presentation]. Bridging Barriers, The University of Texas at Austin. http://bridgingbarriers.utexas.edu/sites/default/files/documents/multilingual-ai-assisted-emergency-preparedness_48x35.pdf

25. Jing, Y., Ren, Y., Liu, Y., Wang, D., & Yu, L. (2022). Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi. Remote Sensing, 14(2), 382. https://doi.org/10.3390/rs14020382

26. Kumar, M. V. K. S. (2024). Leveraging AI in disaster management: Enhancing response and recovery for natural and man made disasters. International Journal for Multidisciplinary Research, 6(2), 42–59. https://doi.org/10.36948/ijfmr.2024.v06i02.26729

27. Matin SS, Pradhan B. Earthquake-Induced Building-Damage Mapping Using Explainable AI (XAI). Sensors (Basel). 2021 Jun 30;21(13):4489. doi: https://doi.org/10.3390/s21134489. PMID: 34209169; PMCID: PMC8271973.

28. Milenković, D., Cvetković, V. M., & Renner, R. (2024). A systematic literary review on community resilience indicators: Adaptation and application of the BRIC method for measuring disaster resilience. International Journal of Disaster Risk Management, 6(2), 6–24. https://doi.org/10.18485/ijdrm.2024.6.2.6.

29. Cvetkovic, V. M., & Martinović, J. (2021). Innovative solutions for flood risk management. International Journal of Disaster Risk Management, 2(2), 71–100. https://doi.org/10.18485/ijdrm.2020.2.2.5

30. Moon Technolabs. (2023). Edge AI vs Cloud AI: Use Cases and Benefits. Retrieved from https://www.moontechnolabs.com/blog/edge-ai-vs-cloud-ai/

31. Munich Re. (2023). Munich Re Group Annual Report 2023. https://www.munichre.com/content/dam/munichre/mrwebsiteslaunches/2023-annual-report/MunichRe-Group-Annual-Report-2023-en.pdf/_jcr_content/renditions/original./MunichRe-Group-Annual-Report-2023-en.pdf

32. NASA. (2024). NASA AI, Open Science Advance Disaster Research and Recovery. NASA Science. Retrieved from https://science.nasa.gov/open-science/artificial-intelligence-hurricane-response/

33. NCDP. (2025). The Promise and Challenges of AI in Wildfire Damage Assessment. National Center for Disaster Preparedness, Columbia University. Retrieved from https://ncdp.columbia.edu/ncdp-perspectives/transforming-disaster-management-the-promise-and-challenges-of-ai-in-wildfire-damage-assessment/

34. Odubola, O., Adeyemi, T. S., Olajuwon, O. O., Iduwet, N. P., Aniekan, A. I., & Odubola, T. (2025). AI in Social Good: LLM Powered Interventions in Crisis Management and Disaster Response. Journal of Artificial Intelligence, Machine Learning and Data Science, 3(1), 3353–3360. https://doi.org/10.51219/JAIMLD/Oluwatimilehin-Odubola/510

35. Ogunleye, O. I., & Arohunsoro, S. J. (2024). An assessment of socio-economic impacts of rainstorm disaster on the livelihood of the residents of Ikole Local Government Area in Ekiti State, Nigeria. International Journal of Disaster Risk Management, 6(2), 14–31. https://doi.org/10.18485/ijdrm.2024.6.2.14

36. Öcal, F. E., & Torun, S. (2024). An inevitable technological disaster type: Space debris. International Journal of Disaster Risk Management, 6(2), 62–76. https://doi.org/10.18485/ijdrm.2024.6.2.5

37. Raut, S. V. (2024). Artificial intelligence use in disaster management. International Journal of Innovative Science and Research Technology, 9(5), 101–109. https://doi.org/10.38124/ijisrt/IJISRT24MAY1679

38. Reichstein, M., Benson, V., Blunk, J., Camps Valls, G., Creutzig, F., Fearnley, C. J., Han, B., Kornhuber, K., Rahaman, N., Schölkopf, B., Tárraga, J. M., Vinuesa, R., Dall, K., Denzler, J., Frank, D., Martini, G., Nganga, N., Maddix, D. C., & Weldemariam, K. (2025). Early warning of complex climate risk with integrated artificial intelligence. Nature Communications, 16(1), e2564. https://doi.org/10.1038/s41467-025-57640-w

39. Schofield, M. (2022). An artificial intelligence (AI) approach to controlling disaster scenarios. In Advances in Electronic Government, Digital Divide, and Regional Development (pp. 45–62). IGI Global. https://doi.org/10.4018/978-1-7998-9815-3.ch003

40. Sharma, A., Rawal, T., Agarwal, S., & Aditaya, A. (2025). The application of support vector machine (SVM) and AI in enhancing disaster management. Social Science Research Network. https://doi.org/10.2139/ssrn.5076167

41. Simões Marques, M., & Figueira, J. R. (2018). How can AI help reduce the burden of disaster management decision making? In F. Y. Wang (Ed.), Multicriteria Decision Aid and Artificial Intelligence (pp. 271–284). Springer. https://doi.org/10.1007/978-3-319-94334-3_14

42. Singh, V. A., & Agnihotri, A. (2024). Addressing environmental challenges through AI-powered natural disaster management. International Journal of Applied and Scientific Research, 2(5), 88–99. https://doi.org/10.59890/ijasr.v2i5.1413

43. Sun, W., Bocchini, P., & Davison, B. D. (2020). Applications of artificial intelligence for disaster management. Natural Hazards, 104, 2435–2460. https://doi.org/10.1007/s11069-020-04124-3

44. Tout, F., Rebouh, N., Dinar, H., Benzid, Y., & Zouak, Z. (2024). The contribution of roads to forest fire protection in Tamza Municipality, Northeast Algeria. International Journal of Disaster Risk Management, 6(2), 3–13. https://doi.org/10.18485/ijdrm.2024.6.2.3.