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Abstract We present a new open source dataset FLODIS that links estimates of flood-induced human displacements, fatalities, and economic damages to flooded areas observed through remote sensing. The dataset connects displacement data from the Internal Displacement Monitoring Centre (IDMC), as well as data on fatalities and damages from the Emergency Events Database (EM-DAT), with the Global Flood Database (GFD), a satellite-based inventory of historic flood footprints. It thereby provides a spatially explicit estimate of the flood hazard underlying each individual disaster event. FLODIS contains two datasets with event-specific information for 335 human displacement events and 695 mortality/damage events that occurred around the world between 2000 and 2018. Additionally, we provide estimates of affected population, GDP, and critical infrastructure, as well as socio-economic indicators; and we provide geocoding for displacement events ascribed to other types of disasters, such as tropical cyclones, so that they may be linked to corresponding hazard estimates in future work. FLODIS facilitates integrated flood risk analysis, allowing, for example, for detailed assessments of local flood-damage and displacement vulnerability.
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Abstract. Large-scale socioeconomic studies of the impacts of floods are difficult and costly for countries such as Canada and the United States due to the large number of rivers and size of watersheds. Such studies are however very important for analyzing spatial patterns and temporal trends to inform large-scale flood risk management decisions and policies. In this paper, we present different flood occurrence and impact models based upon statistical and machine learning methods of over 31 000 watersheds spread across Canada and the US. The models can be quickly calibrated and thereby easily run predictions over thousands of scenarios in a matter of minutes. As applications of the models, we present the geographical distribution of the modelled average annual number of people displaced due to flooding in Canada and the US, as well as various scenario analyses. We find for example that an increase of 10 % in average precipitation yields an increase in the displaced population of 18 % in Canada and 14 % in the US. The model can therefore be used by a broad range of end users ranging from climate scientists to economists who seek to translate climate and socioeconomic scenarios into flood probabilities and impacts measured in terms of the displaced population.
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There is increasing evidence that exposure to weather-related hazards like storms and floods adversely affects mental health. However, evidence of treated and untreated mental disorders based on diagnostic criteria for the general population is limited. We analysed the Adult Psychiatric Morbidity Survey, a large probability sample survey of adults in England (n = 7525), that provides the only national data on the prevalence of mental disorders assessed to diagnostic criteria. The most recent survey (2014–2015) asked participants if they had experienced damage to their home (due to wind, rain, snow or flood) in the six months prior to interview, a period that included months of unprecedented population exposure to flooding, particularly in Southern England. One in twenty (4.5%) reported living in a storm- or flood-damaged home in the previous six months. Social advantage (home ownership, higher household income) increased the odds of exposure to storm or flood damage. Exposure predicted having a common mental disorder over and above the effects of other known predictors of poor mental health. With climate change increasing the frequency and severity of storms and flooding, improving community resilience and disaster preparedness is a priority. Evidence on the mental health of exposed populations is key to building this capacity.
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Abstract Objective To examine mental health and community cohesion in women living in Calgary after a natural disaster considering previously collected mental health data. Methods Data from an ongoing longitudinal cohort, the All Our Families study, were used to examine mental health and community cohesion 5 months after a major flood in Calgary, Canada. Participants who had completed a baseline questionnaire before the flood were eligible for inclusion in this study (N=923). Four multivariable logistic regression models were built to examine predictors of post-traumatic stress, depression, anxiety, and community cohesion. Results Elevated anxiety before the flood was associated with 2.49 (95% CI: 1.17, 5.26) increased odds of experiencing high levels of post-traumatic stress, regardless of whether respondents lived in a flood-risk community or not. Women who experienced damage to property, or who provided help to others, were more likely to perceive an increased sense of community cohesion (adjusted ods ratio (AOR): 1.67; 95% CI: 1.09, 2.54 and AOR: 1.68; 95% CI: 1.13, 2.52, respectively). Conclusions Women with underlying mental health conditions may be more vulnerable to the psychological impacts of a natural disaster regardless of their level of exposure. Natural disasters may bring communities together, especially those who were more tangibly impacted. ( Disaster Med Public Health Preparedness . 2018;12:470–477)
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Objective To assess the association between flooding/repeat flooding and: (1) psychological morbidity (anxiety, depression, post-traumatic stress disorder (PTSD)) and (2) health-related quality of life (HRQoL) at 6 months post-flooding. Design Cross-sectional analysis of data from the English National Study of Flooding and Health. Setting Cumbria, England. Participants Questionnaires were sent to 2500 residential addresses at 6 months post-flooding; 590 people responded. Outcomes Probable depression was assessed using the Patient Health Questionnaire, probable anxiety using the Generalised Anxiety Disorder scale and probable PTSD using the short-form PTSD checklist (PCL-6). HRQoL was assessed using the EQ-5D-5L. Mental health outcomes were analysed using logistic regression; HRQoL dimensions using ordinal regression; and summary index/Visual Analogue Scale scores using linear regression. Results One hundred and nineteen participants had been flooded, over half of whom were experiencing a repeat flooding event (54%; n=64). Mental health outcomes were elevated among flooded compared with unaffected participants (adjusted OR for probable depression: 7.77, 95% CI: 1.51 to 40.13; anxiety: 4.16, 95% CI: 1.18 to 14.70; PTSD: 14.41, 95% CI: 3.91 to 53.13). The prevalence of depression was higher among repeat compared with single flooded participants, but this was not significant after adjustment. There was no difference in levels of anxiety or PTSD. Compared with unaffected participants, those flooded had lower EQ-5D-5L index scores (adjusted coefficient: −0.06, 95% CI: −0.12 to −0.01) and lower self-rated health scores (adjusted coefficient: −6.99, 95% CI: −11.96 to −2.02). There was, however, little difference in HRQoL overall between repeat and single flooded participants. Conclusions Interventions are needed to help minimise the impact of flooding on people’s mental health and HRQoL.