Mapping Rural Household Vulnerability to Flood-Induced Health Risks in Disaster-Stricken Khyber Pakhtunkhwa, Pakistan

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10578 - 10578

Published: Dec. 3, 2024

This study maps the rural household vulnerability to flood-induced health risks in flood-affected Khyber Pakhtunkhwa (KPK), Pakistan, focusing on devastating 2022 flood. Using data from 600 households severely impacted districts of province (including Charsadda and Nowshera), this research examines influence demographic, socioeconomic, infrastructural factors vulnerability. assesses flooding issues using logistic regression. The current findings revealed that female-headed households, those with younger heads, families lower educational levels are particularly vulnerable. Income disparities significantly shape coping capacity, wealthier more likely adopt effective risk-mitigation strategies. Proximity functioning healthcare facilities emerged as a crucial factor reducing vulnerability, these faced fewer hazards. Conversely, areas where water infrastructure were damaged experienced higher disease outbreaks, including cholera malaria, due contamination inadequate sanitation. highlights urgent need for resilient infrastructure, strengthened public systems, improved education, enhanced sanitation services mitigate risks. Policymakers urged sustainable development practices by adopting gender-sensitive disaster management strategies, prioritizing initiatives, fostering community support networks enhance resilience future flood events KPK.

Language: Английский

Transforming disaster response: The role of agentic AI in crisis management

i-manager’s Journal on Structural Engineering, Journal Year: 2024, Volume and Issue: 13(2), P. 48 - 48

Published: Jan. 1, 2024

One revolutionary step in redefining disaster response procedures is the use of agentic AI crisis management. Conventional methods management mostly depend on human judgement, which frequently sluggish, prone to mistakes, and overpowered by complexity ever-changing emergency situations. A new paradigm for handling such difficulties provided AI, distinguished its capacity autonomous decisionmaking, adaptive learning, real-time data processing. This paper examines how can be incorporated into systems, emphasising it automate crucial decision-making, maximise resource allocation, offer insights scenarios. We explore underlying technologies, including natural language processing (NLP), machine multi-agent show they used improve situational awareness, coordination, precision decisions. experimental demonstrating effectiveness Agentic enhancing distribution efficiency times using mathematical modelling. Furthermore, we provide case studies from both man-made disasters highlight practical benefits implementing systems. describe possible development AI-driven systems talking about prospective trends, touching scalability ethical issues. With real-world uses future potential more robust, efficient, effective frameworks, this provides a thorough knowledge might reinvent

Language: Английский