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Formulating Anticipatory Action with Impact Forecasting in Humanitarian Risk Management

Year 2025, Volume: 9 Issue: 1, 167 - 188, 16.07.2025

Abstract

In the context of escalating humanitarian challenges exacerbated by climate change and socio-political dynamics, this study explores the formulation of anticipatory action with impact forecasting in humanitarian risk management. Recognizing the inadequacy of traditional reactive approaches, the research highlights the necessity for proactive strategies that leverage predictive data to mitigate disaster impacts. This study adopts a qualitative, exploratory research design, employing a mixed-methods approach to analyze the formulation and implementation of anticipatory action supported by impact forecasting within humanitarian risk management. Through a comprehensive analysis, the study identifies the integral relationship between anticipatory action and impact forecasting, presenting methodologies and best practices for implementation. Key findings indicate that regions employing anticipatory measures informed by accurate forecasting experience reduced disaster-related casualties and improved recovery outcomes. This research contributes to the discourse on enhancing humanitarian effectiveness by advocating for a paradigm shift toward anticipatory frameworks that foster resilience and adaptability via proposing a simple integration workflow and strategic guidance for Türkiye authorities.

References

  • Abdelmalek, G. (2024). Forecast-based financing: A decade after its introduction – Practices & experiences in the Red Cross Movement (Master’s dissertation). Ghent University.
  • Aljohani, A. (2023). Predictive analytics and machine learning for real-time supply chain risk mitigation and agility. Sustainability, 15(20), 15088.
  • Beduschi, A. (2022). Harnessing the potential of artificial intelligence for humanitarian action: Opportunities and risks. International Review of the Red Cross, 104(919), 1149-1169.
  • Bonfiglioli, A., & Watson, C. (2011, April). Bringing social protection down to earth: Integrating climate resilience and social protection for the most vulnerable. In Proceedings of the IDS–International Conference:“Social Protection for Social Justice” Institute of Development Studies, East Sussex, UK (pp. 13-15).
  • Chaves-Gonzalez, J., Milano, L., Omtzigt, D. J., Pfister, D., Poirier, J., Pople, A., ... & Zommers, Z. (2022). Anticipatory action: Lessons for the future. Frontiers in Climate, 4, 932336.
  • Coughlan de Perez, E., et al. (2015). Forecast-based financing: A new approach to reduce humanitarian impacts. International Federation of Red Cross and Red Crescent Societies.
  • Cowan, N. M. (2011, May). A geospatial data management framework for humanitarian response. In ISCRAM.
  • Crompton, P., Sánchez, C., & Regan, A. (2021). A framework for assessing the potential impact of Forecast-Based Financing on humanitarian needs. Disasters, 45(1), 41-66.
  • de Winter, L. (2023). Anticipatory Action in Conflict Areas: Mitigating the Impact of Access Constraints (Doctoral dissertation, University of Deusto).
  • Demiroz, F., & Haase, T. W. (2020). The concept of resilience: a bibliometric analysis of the emergency and disaster management literature. In Local Disaster Management (pp. 16-35). Routledge.
  • Edoh, N. L., Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024) The role of data analytics in reducing healthcare disparities: A review of predictive models for health equity. International Journal of Management & Entrepreneurship Research, 6(11) 3819-3829.
  • Enenkel, M., Dall, K., Huyck, C. K., McClain, S. N., & Bell, V. (2022). Monitoring, evaluation, accountability, and learning (MEAL) in anticipatory action—earth observation as a game changer. Frontiers in Climate, 4, 923852.
  • Forsgren, L., Tediosi, F., Blanchet, K., & Saulnier, D. D. (2022). Health systems resilience in practice: a scoping review to identify strategies for building resilience. BMC Health Services Research, 22(1), 1173.
  • Grass, E., Ortmann, J., Balcik, B., & Rei, W. (2023). A machine learning approach to deal with ambiguity in the humanitarian decision‐making. Production and Operations Management, 32(9), 2956-2974.
  • Haque, A., & Fatema, K. (2022). Disaster risk reduction for whom? The gap between centrally planned Disaster Management Program and people's risk perception and adaptation. International Journal of Disaster Risk Reduction, 82, 103229.
  • Hasani, A. (2013). Forecasting the End of Climate Change Litigation: Why Expert Testimony Based on Climate Models Should Not Be Admissible. Miss. CL REv., 32, 83.
  • Hasanuzzaman, M., Hossain, S., & Shil, S. K. (2023). Enhancing disaster management through AI-driven predictive analytics: improving preparedness and response. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 533-562.
  • Hernandez, K., & Roberts, T. (2020). Predictive analytics in humanitarian action: A preliminary mapping and analysis.
  • Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4, 1-23.
  • IFRC. (2020). Climate and disaster resilience framework. International Federation of Red Cross and Red Crescent Societies.
  • IFRC. (2021). Preparedness for effective response: A framework for disaster response. IFRC.
  • Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
  • Knox Clarke, P., & Campbell, L. (2020). Decision-making at the sharp end: a survey of literature related to decision-making in humanitarian contexts. Journal of International Humanitarian Action, 5, 1-14.
  • Kurdi, S., & Ruckstuhl, S. (2023). Crisis resilience: Humanitarian response and anticipatory action. In Global Food Policy Report 2023: Rethinking Food Crisis Responses. Chapter 3, Pp. 36-43.
  • Lentz, E., Gottlieb, G., Simmons, C., & Maxwell, D. (2020). The Ecosystem of Humanitarian Diagnostics and Its Application to Anticipatory Action.
  • Lin, H. C., Wu, Y., Huang, P. L., Lo, L. H., Chen, Y. J., Lee, C. T., & Teng, M. C. (2014, July). Scenario planning for supporting of disaster risk reduction innovation policy. In Proceedings of PICMET'14 Conference: Portland International Center for Management of Engineering and Technology; Infrastructure and Service Integration (pp. 2715-2731). IEEE.
  • Marciano, C., Peresan, A., Pirni, A., Pittore, M., Tocchi, G., & Zaccaria, A. M. (2024). A participatory foresight approach in disaster risk management: The multi-risk storylines. International Journal of Disaster Risk Reduction, 114, 104972.
  • Marzouk, J., Ali, M., Hassan, R., & El Ebrashi, R. (2024). A hybrid intelligence Decision-Making approach for humanitarian supply chains. In CSR, Governance and Value (pp. 223-239). Singapore: Springer Nature Singapore.
  • Mercer, J. (2010). Disaster risk reduction or climate change adaptation: Are we reinventing the wheel?. Journal of International Development: The Journal of the Development Studies Association, 22(2), 247-264.
  • Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., ... & Wurpts, A. (2020). Impact forecasting to support emergency management of natural hazards. Reviews of geophysics, 58(4), e2020RG000704.
  • Nakhaei, M., Nakhaei, P., Gheibi, M., Chahkandi, B., Wacławek, S., Behzadian, K., ... & Campos, L. C. (2023). Enhancing community resilience in arid regions: A smart framework for flash flood risk assessment. Ecological Indicators, 153, 110457.
  • Nordberg, A. L. (2018). The importance of Culture and Context in Disaster Risk Reduction: A Case Study of Women in Batticaloas Perceptions on Vulnerability to Natural Disasters and Disaster Risk Reduction efforts (Master's thesis, Universitetet i Agder; University of Agder).
  • Nuñez, L. (2005). Tools for forecasting or warning as well as hazard assessment to reduce impact of natural disasters on agriculture, forestry and fisheries. In Natural Disasters and Extreme Events in Agriculture: Impacts and Mitigation (pp. 71-92). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Nur, L., & Amarnath, G. (2023). Mapping and analysis of anticipatory action initiatives in Senegal and Zambia. CGIAR. https://cgspace.cgiar.org/items/cf5d7570-f02e-4b50-814d-e1f6c60c997d
  • OCHA. (2020). Ethiopia: Drought anticipatory actions in response to climate forecasts. United Nations Office for the Coordination of Humanitarian Affairs. https://www.unocha.org/publications/report/ethiopia/acting-early-when-world-isnt-watching-lessons-anticipatory-action-ethiopia-2021
  • Orsato, R. J., Ferraz de Campos, J. G., & Barakat, S. R. (2019). Social learning for anticipatory adaptation to climate change: evidence from a community of practice. Organization & Environment, 32(4), 416-440.
  • Rahman, M. T., Majchrzak, T. A., & Sein, M. K. (2022). Making decisions for effective humanitarian actions: a conceptual framework for relief distribution. Journal of International Humanitarian Action, 7(1), 24.
  • Reichel, C., & Frömming, U. U. (2014). Participatory mapping of local disaster risk reduction knowledge: An example from Switzerland. International Journal of Disaster Risk Science, 5, 41-54.
  • Rocque, R. J., Beaudoin, C., Ndjaboue, R., Cameron, L., Poirier-Bergeron, L., Poulin-Rheault, R. A., ... & Witteman, H. O. (2021). Health effects of climate change: an overview of systematic reviews. BMJ open, 11(6), e046333.
  • Salam, M. A., & Khan, S. A. (2020). Lessons from the humanitarian disaster logistics management: A case study of the earthquake in Haiti. Benchmarking: An International Journal, 27(4), 1455-1473.
  • Schneider, C., Jimenez, R., & Kyriazi, S. (2023). Artificial Intelligence-Based Predictive Analytics in the Humanitarian Sector: The Case of Project Jetson. Harnessing Data Innovation For Migration Policy, 66.
  • Seddiky, M. A., Giggins, H., & Gajendran, T. (2020). International principles of disaster risk reduction informing NGOs strategies for community based DRR mainstreaming: The Bangladesh context. International journal of disaster risk reduction, 48, 101580.
  • Tariq, H., Pathirage, C., & Fernando, T. (2021). Measuring community disaster resilience at local levels: An adaptable resilience framework. International Journal of Disaster Risk Reduction, 62, 102358.
  • Thalheimer, L., Simperingham, E., & Jjemba, E. W. (2022). The role of anticipatory humanitarian action to reduce disaster displacement. Environmental Research Letters, 17(1), 014043.
  • United Nations Office for Disaster Risk Reduction (UNDRR). (2015). Sendai Framework for Disaster Risk Reduction 2015-2030. https://www.unisdr.org/we/inform/publications/43291
  • United Nations Office for Disaster Risk Reduction (UNDRR). (2020). Words into Action guidelines: Implementation guide for local disaster risk reduction and resilience strategies. https://www.undrr.org/publication/words-action-guidelines-implementation-guide-local-disaster-risk-reduction-and
  • United Nations Office for Disaster Risk Reduction. (2019). Disaster risk reduction: Key messages for a sustainable future. UNDRR. https://sdgs.un.org/un-system-sdg-implementation/united-nations-office-disaster-risk-reduction-undrr-57099
  • Walker, B., & Salt, D. (2012). Resilience Thinking: Sustaining Ecosystems and People in a Changing World. Island Press.
  • Walters, W. C. (2013). Critical Exploration of Community Engagement and Accountability in Humanitarian Aid: redefining Working Relationships in the Field. Library and Archives Canada= Bibliothèque et Archives Canada, Ottawa.
  • Wicke, L., Dhami, M. K., Önkal, D., & Belton, I. K. (2022). Using scenarios to forecast outcomes of a refugee crisis. International Journal of Forecasting, 38(3), 1175-1184.
  • Wilkinson, E., Weingartner, L., Choularton, R., Bailey, M., & Leigh, R. (2018). Forecasting hazards, averting disasters: Implementing forecast-based early action at scale. Overseas Development Institute, 22(1), 1-20. https://doi.org/10.1002/odi
  • World Bank (WB). (2019). Resilience to disasters: A priority for development. Retrieved from https://www.worldbank.org/en/topic/disasterriskmanagement/overview
  • World Food Programme (WFP). (2020). The role of anticipatory action in food security: A framework for effective interventions. WFP.
  • World Meteorological Organization (WMO). (2021). State of the Climate: WMO Statement on the State of the Global Climate in 2020. https://public.wmo.int/en/resources/state-of-the-climate
  • Wright, T., & Sutherland, M. (2021). Conducting impact assessments for anticipatory action in humanitarian contexts. International Journal of Disaster Risk Reduction, 53, 102092
  • Zaman, T., Tahsin, K. T., Rousseau Rozario, S., Kamal, A. B., Khan, M. R., Huq, S., & Bodrud-Doza, M. (2022). An overview of disaster risk reduction and anticipatory action in Bangladesh. Frontiers in Climate, 4, 944736.

İnsani Risk Yönetiminde Etki Tahmini ile Öngörücü Eylem Formülasyonu

Year 2025, Volume: 9 Issue: 1, 167 - 188, 16.07.2025

Abstract

İklim değişikliği ve sosyo-politik dinamiklerle derinleşen insani zorlukların artışı bağlamında, bu çalışma insani risk yönetiminde etki tahmini ile birlikte öngörücü eylem formülasyonunu araştırmaktadır. Geleneksel reaktif yaklaşımların yetersizliğini kabul eden araştırma, afet zararlarını azaltmak için öngörü verilerini kullanan proaktif stratejilerin gerekliliğini vurgulamaktadır. Bu çalışma, insani risk yönetimi kapsamında etki tahminine dayalı olarak desteklenen öngörücü eylemlerin oluşturulması ve uygulanmasını analiz etmek amacıyla nitel, keşifsel bir araştırma tasarımı benimsemekte ve karma yöntem yaklaşımını kullanmaktadır. Kapsamlı bir analiz aracılığıyla, çalışma öngörücü eylem ile etki tahmini arasındaki integral ilişkiyi belirleyerek, uygulama için metodolojiler ve en iyi uygulamaları sunmaktadır. Ana bulgular, doğru tahminlerle bilgilendirilen öngörücü eylemlerin uygulandığı bölgelerin, afetle ilgili yaralanmaları ve kayıpları azaltırken, iyileşme sonuçlarını da iyileştirdiğini göstermektedir. Bu araştırma, insani yardım etkinliğinin artırılmasına yönelik literatüre anlamlı bir katkı sağlamakta; Türkiye’deki yetkili kurumlar için uygulanabilir bir entegrasyon iş akışı ve stratejik yol haritası önererek, öngörüye dayalı çerçevelere geçişi teşvik etmekte ve böylece dayanıklılık ile uyum kabiliyetini güçlendiren bir paradigma değişimini desteklemektedir.

References

  • Abdelmalek, G. (2024). Forecast-based financing: A decade after its introduction – Practices & experiences in the Red Cross Movement (Master’s dissertation). Ghent University.
  • Aljohani, A. (2023). Predictive analytics and machine learning for real-time supply chain risk mitigation and agility. Sustainability, 15(20), 15088.
  • Beduschi, A. (2022). Harnessing the potential of artificial intelligence for humanitarian action: Opportunities and risks. International Review of the Red Cross, 104(919), 1149-1169.
  • Bonfiglioli, A., & Watson, C. (2011, April). Bringing social protection down to earth: Integrating climate resilience and social protection for the most vulnerable. In Proceedings of the IDS–International Conference:“Social Protection for Social Justice” Institute of Development Studies, East Sussex, UK (pp. 13-15).
  • Chaves-Gonzalez, J., Milano, L., Omtzigt, D. J., Pfister, D., Poirier, J., Pople, A., ... & Zommers, Z. (2022). Anticipatory action: Lessons for the future. Frontiers in Climate, 4, 932336.
  • Coughlan de Perez, E., et al. (2015). Forecast-based financing: A new approach to reduce humanitarian impacts. International Federation of Red Cross and Red Crescent Societies.
  • Cowan, N. M. (2011, May). A geospatial data management framework for humanitarian response. In ISCRAM.
  • Crompton, P., Sánchez, C., & Regan, A. (2021). A framework for assessing the potential impact of Forecast-Based Financing on humanitarian needs. Disasters, 45(1), 41-66.
  • de Winter, L. (2023). Anticipatory Action in Conflict Areas: Mitigating the Impact of Access Constraints (Doctoral dissertation, University of Deusto).
  • Demiroz, F., & Haase, T. W. (2020). The concept of resilience: a bibliometric analysis of the emergency and disaster management literature. In Local Disaster Management (pp. 16-35). Routledge.
  • Edoh, N. L., Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024) The role of data analytics in reducing healthcare disparities: A review of predictive models for health equity. International Journal of Management & Entrepreneurship Research, 6(11) 3819-3829.
  • Enenkel, M., Dall, K., Huyck, C. K., McClain, S. N., & Bell, V. (2022). Monitoring, evaluation, accountability, and learning (MEAL) in anticipatory action—earth observation as a game changer. Frontiers in Climate, 4, 923852.
  • Forsgren, L., Tediosi, F., Blanchet, K., & Saulnier, D. D. (2022). Health systems resilience in practice: a scoping review to identify strategies for building resilience. BMC Health Services Research, 22(1), 1173.
  • Grass, E., Ortmann, J., Balcik, B., & Rei, W. (2023). A machine learning approach to deal with ambiguity in the humanitarian decision‐making. Production and Operations Management, 32(9), 2956-2974.
  • Haque, A., & Fatema, K. (2022). Disaster risk reduction for whom? The gap between centrally planned Disaster Management Program and people's risk perception and adaptation. International Journal of Disaster Risk Reduction, 82, 103229.
  • Hasani, A. (2013). Forecasting the End of Climate Change Litigation: Why Expert Testimony Based on Climate Models Should Not Be Admissible. Miss. CL REv., 32, 83.
  • Hasanuzzaman, M., Hossain, S., & Shil, S. K. (2023). Enhancing disaster management through AI-driven predictive analytics: improving preparedness and response. International Journal of Advanced Engineering Technologies and Innovations, 1(01), 533-562.
  • Hernandez, K., & Roberts, T. (2020). Predictive analytics in humanitarian action: A preliminary mapping and analysis.
  • Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4, 1-23.
  • IFRC. (2020). Climate and disaster resilience framework. International Federation of Red Cross and Red Crescent Societies.
  • IFRC. (2021). Preparedness for effective response: A framework for disaster response. IFRC.
  • Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
  • Knox Clarke, P., & Campbell, L. (2020). Decision-making at the sharp end: a survey of literature related to decision-making in humanitarian contexts. Journal of International Humanitarian Action, 5, 1-14.
  • Kurdi, S., & Ruckstuhl, S. (2023). Crisis resilience: Humanitarian response and anticipatory action. In Global Food Policy Report 2023: Rethinking Food Crisis Responses. Chapter 3, Pp. 36-43.
  • Lentz, E., Gottlieb, G., Simmons, C., & Maxwell, D. (2020). The Ecosystem of Humanitarian Diagnostics and Its Application to Anticipatory Action.
  • Lin, H. C., Wu, Y., Huang, P. L., Lo, L. H., Chen, Y. J., Lee, C. T., & Teng, M. C. (2014, July). Scenario planning for supporting of disaster risk reduction innovation policy. In Proceedings of PICMET'14 Conference: Portland International Center for Management of Engineering and Technology; Infrastructure and Service Integration (pp. 2715-2731). IEEE.
  • Marciano, C., Peresan, A., Pirni, A., Pittore, M., Tocchi, G., & Zaccaria, A. M. (2024). A participatory foresight approach in disaster risk management: The multi-risk storylines. International Journal of Disaster Risk Reduction, 114, 104972.
  • Marzouk, J., Ali, M., Hassan, R., & El Ebrashi, R. (2024). A hybrid intelligence Decision-Making approach for humanitarian supply chains. In CSR, Governance and Value (pp. 223-239). Singapore: Springer Nature Singapore.
  • Mercer, J. (2010). Disaster risk reduction or climate change adaptation: Are we reinventing the wheel?. Journal of International Development: The Journal of the Development Studies Association, 22(2), 247-264.
  • Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., ... & Wurpts, A. (2020). Impact forecasting to support emergency management of natural hazards. Reviews of geophysics, 58(4), e2020RG000704.
  • Nakhaei, M., Nakhaei, P., Gheibi, M., Chahkandi, B., Wacławek, S., Behzadian, K., ... & Campos, L. C. (2023). Enhancing community resilience in arid regions: A smart framework for flash flood risk assessment. Ecological Indicators, 153, 110457.
  • Nordberg, A. L. (2018). The importance of Culture and Context in Disaster Risk Reduction: A Case Study of Women in Batticaloas Perceptions on Vulnerability to Natural Disasters and Disaster Risk Reduction efforts (Master's thesis, Universitetet i Agder; University of Agder).
  • Nuñez, L. (2005). Tools for forecasting or warning as well as hazard assessment to reduce impact of natural disasters on agriculture, forestry and fisheries. In Natural Disasters and Extreme Events in Agriculture: Impacts and Mitigation (pp. 71-92). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Nur, L., & Amarnath, G. (2023). Mapping and analysis of anticipatory action initiatives in Senegal and Zambia. CGIAR. https://cgspace.cgiar.org/items/cf5d7570-f02e-4b50-814d-e1f6c60c997d
  • OCHA. (2020). Ethiopia: Drought anticipatory actions in response to climate forecasts. United Nations Office for the Coordination of Humanitarian Affairs. https://www.unocha.org/publications/report/ethiopia/acting-early-when-world-isnt-watching-lessons-anticipatory-action-ethiopia-2021
  • Orsato, R. J., Ferraz de Campos, J. G., & Barakat, S. R. (2019). Social learning for anticipatory adaptation to climate change: evidence from a community of practice. Organization & Environment, 32(4), 416-440.
  • Rahman, M. T., Majchrzak, T. A., & Sein, M. K. (2022). Making decisions for effective humanitarian actions: a conceptual framework for relief distribution. Journal of International Humanitarian Action, 7(1), 24.
  • Reichel, C., & Frömming, U. U. (2014). Participatory mapping of local disaster risk reduction knowledge: An example from Switzerland. International Journal of Disaster Risk Science, 5, 41-54.
  • Rocque, R. J., Beaudoin, C., Ndjaboue, R., Cameron, L., Poirier-Bergeron, L., Poulin-Rheault, R. A., ... & Witteman, H. O. (2021). Health effects of climate change: an overview of systematic reviews. BMJ open, 11(6), e046333.
  • Salam, M. A., & Khan, S. A. (2020). Lessons from the humanitarian disaster logistics management: A case study of the earthquake in Haiti. Benchmarking: An International Journal, 27(4), 1455-1473.
  • Schneider, C., Jimenez, R., & Kyriazi, S. (2023). Artificial Intelligence-Based Predictive Analytics in the Humanitarian Sector: The Case of Project Jetson. Harnessing Data Innovation For Migration Policy, 66.
  • Seddiky, M. A., Giggins, H., & Gajendran, T. (2020). International principles of disaster risk reduction informing NGOs strategies for community based DRR mainstreaming: The Bangladesh context. International journal of disaster risk reduction, 48, 101580.
  • Tariq, H., Pathirage, C., & Fernando, T. (2021). Measuring community disaster resilience at local levels: An adaptable resilience framework. International Journal of Disaster Risk Reduction, 62, 102358.
  • Thalheimer, L., Simperingham, E., & Jjemba, E. W. (2022). The role of anticipatory humanitarian action to reduce disaster displacement. Environmental Research Letters, 17(1), 014043.
  • United Nations Office for Disaster Risk Reduction (UNDRR). (2015). Sendai Framework for Disaster Risk Reduction 2015-2030. https://www.unisdr.org/we/inform/publications/43291
  • United Nations Office for Disaster Risk Reduction (UNDRR). (2020). Words into Action guidelines: Implementation guide for local disaster risk reduction and resilience strategies. https://www.undrr.org/publication/words-action-guidelines-implementation-guide-local-disaster-risk-reduction-and
  • United Nations Office for Disaster Risk Reduction. (2019). Disaster risk reduction: Key messages for a sustainable future. UNDRR. https://sdgs.un.org/un-system-sdg-implementation/united-nations-office-disaster-risk-reduction-undrr-57099
  • Walker, B., & Salt, D. (2012). Resilience Thinking: Sustaining Ecosystems and People in a Changing World. Island Press.
  • Walters, W. C. (2013). Critical Exploration of Community Engagement and Accountability in Humanitarian Aid: redefining Working Relationships in the Field. Library and Archives Canada= Bibliothèque et Archives Canada, Ottawa.
  • Wicke, L., Dhami, M. K., Önkal, D., & Belton, I. K. (2022). Using scenarios to forecast outcomes of a refugee crisis. International Journal of Forecasting, 38(3), 1175-1184.
  • Wilkinson, E., Weingartner, L., Choularton, R., Bailey, M., & Leigh, R. (2018). Forecasting hazards, averting disasters: Implementing forecast-based early action at scale. Overseas Development Institute, 22(1), 1-20. https://doi.org/10.1002/odi
  • World Bank (WB). (2019). Resilience to disasters: A priority for development. Retrieved from https://www.worldbank.org/en/topic/disasterriskmanagement/overview
  • World Food Programme (WFP). (2020). The role of anticipatory action in food security: A framework for effective interventions. WFP.
  • World Meteorological Organization (WMO). (2021). State of the Climate: WMO Statement on the State of the Global Climate in 2020. https://public.wmo.int/en/resources/state-of-the-climate
  • Wright, T., & Sutherland, M. (2021). Conducting impact assessments for anticipatory action in humanitarian contexts. International Journal of Disaster Risk Reduction, 53, 102092
  • Zaman, T., Tahsin, K. T., Rousseau Rozario, S., Kamal, A. B., Khan, M. R., Huq, S., & Bodrud-Doza, M. (2022). An overview of disaster risk reduction and anticipatory action in Bangladesh. Frontiers in Climate, 4, 944736.
There are 56 citations in total.

Details

Primary Language English
Subjects Climate Change Impacts and Adaptation (Other), Ecology, Sustainability and Energy, Disaster and Emergency Management
Journal Section Articles
Authors

Ahmet Efe 0000-0002-2691-7517

Publication Date July 16, 2025
Submission Date October 10, 2024
Acceptance Date July 9, 2025
Published in Issue Year 2025 Volume: 9 Issue: 1

Cite

APA Efe, A. (2025). Formulating Anticipatory Action with Impact Forecasting in Humanitarian Risk Management. Resilience, 9(1), 167-188.