{"title":"Vulnerability of Communities to Climate Change Induced Disaster Risks and Potential Mental Health Outcomes in Isiolo County, Kenya","authors":"Peninah K. Mwenda, D. Olago, F. Okatcha, A. Ali","doi":"10.47941/jps.751","DOIUrl":null,"url":null,"abstract":"Purpose: The study was conducted to identify and evaluate disaster risks and mental health outcomes caused by extreme climate events.\nMethodology: Quantitative data was obtained from existing climate and mental health (1984-2019) records, while qualitative data was obtained from literature review of case studies and content analysis, Focus Group Discussion and household survey in four major zones for two consecutive years. ArcGIS software method explored various properties of the climate systems to infer the distribution of climate parameters, select extremes value and calculate linear trend of time series. The quantitative data was analyzed using statistical tools in Excel, IBM SPSS version 20 while climate data analysis was done using R software (version 3.21).\nResults: The exceedance threshold of 𝜇 = 340 𝑚𝑚 was chosen. On the other hand, mean exceedance threshold of 𝜇 = 36.50𝐶 and 𝜇 = 11.380𝐶 for minimum and maximum temperatures respectively. The rainfall band was very high or very low, deemed to create disaster risks. The results revealed that the most common disaster risks include: drought and heatwaves, strong sand storms, flash floods and floods. The duration of time, frequency and unpredictable weather variability events were above critical threshold, hence categorized as high risk, rated 1, hence fatal.\nUnique Contribution to Theory and Practice: The study provides historical empirical data on hazard mapping and mental health outcomes to enable policy and programmes formulation by state and nonstate actors. The study recommends development of robust environmental health procedures to diagnose mental disorders, mapping of disasters; mental disorder epidemiology and make it user friendly to advice policy, scale up solutions and accelerate evidence informed advocacy on adaptation and resilience mental health programme strategies","PeriodicalId":14294,"journal":{"name":"International Journal of Physical Sciences","volume":"57 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Physical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47941/jps.751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: The study was conducted to identify and evaluate disaster risks and mental health outcomes caused by extreme climate events.
Methodology: Quantitative data was obtained from existing climate and mental health (1984-2019) records, while qualitative data was obtained from literature review of case studies and content analysis, Focus Group Discussion and household survey in four major zones for two consecutive years. ArcGIS software method explored various properties of the climate systems to infer the distribution of climate parameters, select extremes value and calculate linear trend of time series. The quantitative data was analyzed using statistical tools in Excel, IBM SPSS version 20 while climate data analysis was done using R software (version 3.21).
Results: The exceedance threshold of 𝜇 = 340 𝑚𝑚 was chosen. On the other hand, mean exceedance threshold of 𝜇 = 36.50𝐶 and 𝜇 = 11.380𝐶 for minimum and maximum temperatures respectively. The rainfall band was very high or very low, deemed to create disaster risks. The results revealed that the most common disaster risks include: drought and heatwaves, strong sand storms, flash floods and floods. The duration of time, frequency and unpredictable weather variability events were above critical threshold, hence categorized as high risk, rated 1, hence fatal.
Unique Contribution to Theory and Practice: The study provides historical empirical data on hazard mapping and mental health outcomes to enable policy and programmes formulation by state and nonstate actors. The study recommends development of robust environmental health procedures to diagnose mental disorders, mapping of disasters; mental disorder epidemiology and make it user friendly to advice policy, scale up solutions and accelerate evidence informed advocacy on adaptation and resilience mental health programme strategies
目的:本研究旨在识别和评估极端气候事件造成的灾害风险和心理健康后果。方法:定量数据来自现有的气候与心理健康(1984-2019)记录,定性数据来自连续两年的四个主要区域的案例研究和内容分析文献综述、焦点小组讨论和住户调查。ArcGIS软件方法探索气候系统的各种特性,推断气候参数的分布,选取极值,计算时间序列的线性趋势。定量数据分析采用统计工具Excel, IBM SPSS version 20,气候数据分析采用R软件(version 3.21)。结果:选取了超标阈值(≥340𝑚𝑚)。最低气温和最高气温的平均超标阈值分别为:≥36.50舍不得舍不得,≥11.380舍不得舍不得。降雨量非常高或非常低,被认为会产生灾害风险。结果显示,最常见的灾害风险包括:干旱和热浪、强沙尘暴、山洪暴发和洪水。事件的持续时间、频率和不可预测的天气变异性高于临界阈值,因此被归类为高风险,评级为1,因此是致命的。对理论和实践的独特贡献:该研究提供了关于危害绘图和心理健康结果的历史经验数据,使国家和非国家行为体能够制定政策和方案。该研究建议制定强有力的环境卫生程序,以诊断精神障碍、绘制灾害地图;精神障碍流行病学,使其便于用户提供政策咨询,扩大解决办法,并加快关于适应和复原力精神卫生规划战略的循证宣传