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A magnitude 6.8 strike-slip earthquake (EQ) struck Luding, Sichuan Province, China, on 5 September 2022, resulting in significant damage to nearby Ganzi Prefecture and the city of Ya'an. In this research, the near-surface atmospheric electric field (AEF) recorded at four sites 15 d before the Luding EQ was analyzed and differentiated, and multisource auxiliary data including precipitation, cloud base height, and low cloud cover were used at the same time. Nine possible seismic AEF anomalies at four sites were obtained preliminarily. Accordingly, microwave brightness temperature (MBT) data, which are very sensitive to the surface dielectrics and are closely related to the air ionization, together with surface soil moisture, lithology, and a 3D-simulated crustal stress field, were jointly analyzed to confirm the seismic relations of the obtained negative AEF anomalies. The geophysical environment for crustal high-stress concentration, positive charge carrier transfer, and surface accumulation was demonstrated to exist and to meet the conditions necessary to generate local negative AEF anomalies. Furthermore, to deal with the spatial disparities in sites and regions with potential atmospheric ionization, near-surface wind field data were employed to scrutinize the reliability of the AEF anomalies by comprehensively analyzing the spatial relationships among surface charges accumulation areas, wind direction and speed, and the AEF sites. Finally, four negative AEF anomalies were deemed to be closely related to the Luding EQ, and the remaining five possible anomalies were ruled out. A possible mechanism of negative AEF anomalies before the Luding EQ is proposed: positive charge carriers were generated from the underground high-stress concentration areas and then transferred to and accumulated on the ground surface to ionize the surface air, thus disturbing the AEF above the ground. This study presents a method for identifying and analyzing seismic AEF anomalies and is also beneficial for the examination of the pre-earthquake coupling process between the coversphere and the atmosphere.

The article proposes a quality inspection process for the monitoring data of remote sensing arable farmland resources, including an overall review, detailed inspection, and sample external review. The necessary parameters for analysis are determined, and the detection methods for different inspection items are differentiated. Some inspection items that can be automatically checked by the program are distinguished, and a rule library is established to achieve batch automatic inspection of some inspection items. Then, the implementation methods for the remaining quality inspection items are studied, the common problems are identified, and the human-machine interaction inspection of the quality inspection items is improved. Finally, the monitoring data results of arable farmland resources in 161 counties were tested, and the results showed that the proposed technical route is feasible, and the quality evaluation result is objective.

In order to improve our understanding of the characteristics of raindrop size distribution (DSD) over complex mountainous terrain, the differences in DSD over the southern slopes, northern slopes, and interior of the Qilian Mountains were analyzed using 6 months of observations. For all rainfall events, the number concentrations of small and large raindrops in the interior and on the southern slopes were greater than on the northern slopes, but midsize raindrops were less. The DSD spectrum of the interior was more variable and differed significantly from that of the northern slopes. The differences in the normalized intercept parameters of the DSD for stratiform and convective rainfall were 8.3 % and 10.4 %, respectively, and those of the mass-weighted mean diameters were 10.0 % and 23.4 %, respectively, while the standard deviations of DSD parameters at interior sites were larger. The differences in the coefficient and exponent of the Z–R relationship were 2.5 % and 10.7 %, respectively, with an increasing value of the coefficient from the southern to the northern slopes for stratiform rainfall but the opposite for convective rainfall. In addition, the DSD characteristics and Z–R relationships were more similar at the ipsilateral sites and had smaller differences between the southern slopes and interior of the mountains.

Introduction Transitioning from mental health inpatient care to community care is often a vulnerable time in the treatment process where additional risks and anxiety may arise. Objectives The objective of this paper was to evaluate the progression of mental health symptoms in patients six weeks after their discharge from the hospital as the first phase of an ongoing innovative supportive program. In this study, factors that may contribute to the presence or absence of anxiety and depression symptoms, and the quality of life following a return to the community were examined. The results of this study provide evidence and baseline data for future phases of the project. Methods An observational design was used in this study. We collected sociodemographic and clinical data using REDCap at discharge and six weeks later. Anxiety, depression, and well-being symptoms were assessed using the Generalized Anxiety Disorder (GAD-7) questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the World Health Organization-Five Well-Being Index (WHO-5) respectively. Descriptive, Chi-square, independent T-test, and multivariate regression analyses were conducted. Results The survey was completed by 88 participants out of 144 (61.1% response rate). A statistically non-significant reduction in anxiety and depression symptoms was found six weeks after returning to the community based on the Chi-squared/Fisher exact test and independent t-test. As well, the mean anxiety and depression scores showed a non-significant marginal reduction after discharge compared to baseline. In the period following discharge, a non-significant increase in participants experiencing low well-being symptoms was observed, as well as a decline in the mean well-being scores. Based on logistic regression models, only baseline symptoms were significant predictors of symptoms six weeks after inpatient discharge. Image: Image 2: Image 3: Conclusions In the short term following hospital discharge, no significant changes were observed in mental health conditions. A collaboration between researchers and policymakers is essential for the implementation and maintenance of effective interventions to support and maintain the mental health of patients following discharge. Disclosure of Interest None Declared

Introduction Hundreds of fires have been burning from coast to coast across the country since March 2023, putting Canada on track to experience the worst wildfire season ever. From East to West, provinces such as Quebec, Ontario, Nova Scotia, Alberta, and British Columbia have been particularly affected by large and uncontrollable wildfires. Objectives This study aimed to determine the prevalence and predictors of depression symptoms among residents of Alberta and Nova Scotia during the Canadian wildfires of 2023. Methods This study conducted a cross-sectional quantitative survey for data collection. In the period between 14th May and 23rd June 2023, an online survey was administered using REDCap. Through the Text4Hope program, participants subscribe to receive supportive SMS messages daily. After the first message, participants were invited to complete an online questionnaire, containing demographic information, wildfire-related information, and responses to the Patient Health Questionnaire-9 (PHQ-9) for depression assessment. SPSS version 25 was used to analyze the data. Descriptive, univariate, and multivariate regression analyses were employed. Results A total of 298 respondents completed the online survey out of 1802 who accessed it, resulting in a response rate of 16.54 %. Most of the respondents were females (85.2%, 253), below 40 years of age (28.3%, 84), employed (63.6%, 189), and in a relationship (56.4%, 167). A historical depression diagnosis (OR = 3.15; 95% CI: 1.39–7.14) was a significant predictor of moderate to severe MDD in our study. While employment status did not significantly predict MDD, unemployed individuals were two times more likely to report moderate-to-severe symptoms of MDD than employed individuals (OR = 2.46; 95% CI: 1.06–5.67). Among the total sample population, the moderate to severe MDD prevalence was 50.4%, whereas it was 56.1% among those living in wildfire-affected areas. Image: Image 2: Conclusions As a result of our study, the development of moderate to severe MDD symptoms during wildfire disasters was significantly associated with a history of depression diagnosis. Although employment status did not significantly predict MDD, unemployed individuals had a greater likelihood of experiencing moderate-to-severe symptoms than employed individuals. Further research is necessary to ascertain reliable predictors of mental health issues among those who have experienced disasters, as well as to offer appropriate interventions and treatment options to the communities and individuals who are most vulnerable. Disclosure of Interest None Declared

Introduction The transition from hospital to community settings for most mental health service users is often hindered by challenges that affect community adjustment and continuity of care. The first few weeks and days after discharge from mental health inpatient units represent a critical phase for many service users. Objectives This paper aims to evaluate the changes in quality of Life status, resilience, and personal recovery of individuals with mental health challenges recently discharged from acute mental health care into the community. Methods Data for this study were collected as part of a pragmatic stepped-wedge cluster-randomized, longitudinal approach in Alberta. A paired sample t-test and Chi-squared/Fisher test were deployed to assess changes from baseline to six weeks in the recovery assessment scale (RAS), brief resilience scale (BRS), and EuroQol-5d (EQ-5D), using an online questionnaire. Results A total of 306 service users were recruited, and 88 completed both baseline and six weeks, giving a response rate of 28.8%. There was no statistically significant change in the level of resilience, recovery and quality of life as measured with the brief resilience scale, recovery assessment scale and EQ-5D from baseline to six weeks (p > 0.05). Conclusions The study showed that there was neither an improvement nor deterioration in resilience, recovery, or quality of life status of service users six weeks post-discharge from inpatient mental health care. The lack of further progress calls into question whether the support available in the community when patients leave inpatient care is adequate to promote full recovery. Disclosure of Interest None Declared

The continuous increasing of Earth observations benefits geosciences and seismicity study but increases greatly the difficulties in understanding and discriminating multiple source data. Although the lithosphere–coversphere–atmosphere-ionosphere (LCAI) coupling paradigm and the deviation–time–space (DTS) criterion were presented for better searching for and understanding the potential seismic anomalies from multiple observations, the strict consistency of spatiotemporal characteristics and homologous physics of multiple-parameter seismic anomalies has not been investigated sufficiently. With the 2015 Nepal earthquake sequence being a typical case, the reported multi-parameter anomalies were systematically reviewed, and their space–time characteristics were summarized thoroughly in this study. Numerical simulation with refined geological structures in three-dimensional space revealed the inhomogeneous crustal stress field alteration (CSFA) along the faults and around the hypocenters of the 2015 Nepal earthquake sequence, which is expected to be the root of the seismic anomalies. The stress-activated positive charge carriers would have given rise to different responses near the ground surface (coversphere), including the microwave dielectric reduction, the additional infrared radiation, and the atmospheric ionization, which subsequently affected the physical properties of the atmosphere and the ionosphere and resulted in abnormal phenomena therein. Based on the DTS criterion and LCAI coupling paradigm, the seismic anomalies of the 2015 Nepal earthquakes were scrutinized strictly, and the retained anomalies were rooted carefully to the regional CSFA as well as its local blocking. Therefore, an integrated LCAI coupling framework with strict space–time correspondence and homologous physics in CSFA was proposed for the 2015 Nepal earthquake sequence. This research provides a definite philosophy as well as a practical solution for scrutinizing the rootable seismic anomalies from multi-parameter observations of earthquakes, which is of scientific meanings for searching earthquake precursors and reaching earthquake prediction.

To the land cover classification product of geographic national conditions monitoring, how to scientifically and objectively inspect and evaluate the results is a problem that if quality review can play a key role in quality control. Based on the characteristics of the land cover classification product, it was carried out a quality inspection for important quality elements and key contents on the basis of quality acceptance to ensure the consistency and compliance of the national results. This paper put forward the content and method of review. The results over the years since the review showed that the classification accuracy was not only a difficulty but also a short board in quality control. Through summarizing the main problems of the land cover classification product found in the review, the causes were analyzed, and suggestions were put forward for production.

In view of the problems that the permanent scatterer synthetic aperture radar interferometry (PS-InSAR) technology was limited by the difference of processing algorithms and the professional level of data processing personnel, and its monitoring results were still difficult to fully achieve the theoretical accuracy, a new technical process suitable for the detection of PS-InSAR surface deformation monitoring results was proposed in this paper. Based on the analysis of the characteristics of monitoring results, the inspection work was carried out by means of overall inspection. The test parameters, test objects and test items to be tested, as well as the test methods of different test parameters were determined; The key links of PS-InSAR surface deformation monitoring data processing were analyzed in detail, and the technical flow of mathematical accuracy detection was given. Finally, the quality detection of surface deformation monitoring results based on PS-InSAR technology of 3000 square kilometres were carried out, the results showed that the proposed technical route was feasible and quality evaluation result was objective.

Based on the epidemic situation in recent years, it has become an urgent need to study how to use many open-source or existed geographical names to evaluate the quality of newly produced geographical names. By analysing the quality characteristics of geographical names data, we can find the key quality elements of geographical names data. We obtained a method of using multi-source data to evaluate newly produced geographical names. This method based on adaptive weight distribution of multi-source data. This method can not only evaluate the whole quality of geographical names, but also grade the specific quality of geographical names. The experiment shows that this method is effective and has strong reference for users and producers.

This paper uses UAV low-altitude aerial photography technology, equipped with orthophoto camera, tilt camera and LiDAR camera, to obtain and process high-precision evaluation data, which is used to evaluate the correctness of land cover classification. Through the design of aerial photography scheme and data collection and processing, the rapidly acquired digital orthophoto, oblique 3D model data and laser LiDAR form a complete set of technical processes, which can relatively accurately and objectively monitor the quality of surface data for the existing geographical conditions. situation is assessed. The main purpose of this study is to further enrich the technical means of quality inspection of surveying and mapping products, to improve the technical level of quality inspection and acceptance of geographic condition monitoring data, and to improve the accuracy and reliability of data quality evaluation.

Introduction As a result of the wildfire that engulfed Fort McMurray (FMM), Alberta, Canada in May 2016, over 90,000 residents were evacuated from the city. Approximately 2400 homes, or 10% of the housing stock, were destroyed in Fort McMurray. About 200,000 hectors of forest were destroyed by the fire, which reached into Saskatchewan. In the aftermath of a major disaster, a community’s infrastructure is disrupted, and psychological, economic, and environmental effects can last for many years. Objectives Intensive research was conducted in Fort McMurray five years after the wildfire disaster to determine the prevalence of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) among residents of the community and to determine the demographic, clinical, and other risk factors of probable MDD and PTSD. Methods An online questionnaire administered via REDCap was used to collect data in a quantitative cross-sectional study between 24 April and 2 June 2021. Patients were asked to complete the Patient Health Questionnaire (PHQ-9) in order to assess the presence of symptoms associated with MDD. An assessment of likely PTSD in respondents was conducted using the PTSD Checklist for DSM-5 (PCL-C). In this study, descriptive, univariate, and multivariate regression analyses were conducted. Results Out of 249 people who accessed the survey link, 186 completed it (74.7% response rate). There was a median age of 42 among the subscribers. A majority of the sample consisted of 159 (85.5%) females; 98 (52.7%) over the age of 40; 136 (71%) in a relationship; and 175 (94.1%) employed. Our study sample had an overall prevalence of 45.0% (76) of MDD symptoms. The multivariate logistic regression model revealed four variables that were independently associated with MDD symptoms, including being unemployed, diagnosed with MDD, taking sedative-hypnotics, and willingness to receive mental health counseling. A total of 39.6% of our respondents (65) reported having likely PTSD. Three independent variables: received a mental health depression diagnosis from a health professional, would like to receive mental health counseling, and have only limited or no support from familycontributed significantly to the model for predicting likely PTSD among respondents while controlling the other factors in the regression model. Conclusions The findings of this study indicate that unemployment, the use of sleeping pills, the presence of a previous depression diagnosis, and the willingness to seek mental health counseling are significant factors associated with the increase in the prevalence of MDD and PTSD following wildfires. Support from family members may prevent these conditions from developing. Disclosure of Interest None Declared

Introduction The Coronavirus disease (COVID-19) pandemic affected the mental health of many individuals, especially vulnerable communities, who have experienced multiple traumas. Objectives To examine the prevalence and associated factors of likely major depressive disorder (MDD) among inhabitants of Fort McMurray. Methods A study adopted a cross-sectional design, and questionnaires were distributed online. Sociodemographic, COVID-19-related, and clinical data were obtained. The Patient Health Questionnaire (PHQ-9) scale was used to assess likely MDD. SPSS version 25 used employed to analyze the data. Results The prevalence of likely MDD among participants was 45%. Participants who desire mental health counselling are more likely to exhibit depression symptoms during the COVID-19 pandemic (OR = 5.48; 95% CI: 1.95–15.40). History of depression (OR = 4.64; 95% CI: 1.49–14.44) and hypnotics (OR = 5.72; 95% CI: 1.08–30.30) were more likely to experience depression symptoms during the pandemic than other participants without a history. Participants who received absolute support from the employer (OR = 3.50; 95% CI: 1.24–9.82) were protective against depression symptoms amid the pandemic. Conclusions Clinical factors and employer support are associated with depression symptoms during the pandemic. Communities that have experienced multiple traumas need to reduce any psychopathology, and governmental bodies need to implement holistic policies to increase support to individuals during traumatic eras like the CVID-19 pandemic. Disclosure of Interest None Declared

Introduction Patients with mental health issues visit the emergency department (ED) more often than those with other disorders. Frequently ED visiting not only adversely impacts patients and their families, but also burdens the healthcare system economically. Identifying ways to minimize avoidable ED readmissions has become a hot research topic worldwide. Objectives The purpose of this scoping review was to identify influential factors and possible interventions to reduce psychiatric frequent ED visits. Methods This scoping review was conducted through a systematic search in major scientific databases, including PubMed, PsycINFO, MEDLINE, JSTOR, Scopus, and Web of Science, to identify factors and interventions contributing to decreasing repeat visits to the emergency department for mental health concerns up to January 2022. Results From 6951 publications, 31 articles met the inclusion criteria and were included in this review. This review showed six influential factors and 26 potential interventions were aimed to reduce the ED visits, such as receiving methadone & having a regular family physician, readiness for hospital discharge assessment & perceived coping skills and strategies; The High Alert Program (HAP) & the Patient-Centered Medical Home (PCMH), the Primary Behavioral Health Care Integration (PBHCI) & the Collaborative Care (CC) Program etc. Conclusions Worldwide, several initiatives have been taken to reduce ED visits and the associated burden on healthcare systems. Interventions involving comprehensive and multidisciplinary services, incorporating evidence-based behavioral and pharmacological strategies and emphasizing case management were found to be effective. Additionally, there were a marked consideration for diverse mental health groups, such as those with substance use disorder and of young age. This review highlights the greater need for addressing more influential factors, developing accessible interventions, as well as setting up a comprehensive community health care systems aiming to reduce frequent ED presentations. Disclosure of Interest None Declared

Introduction Both natural disasters such as wildfires, earthquakes, tsunamis, and hurricanes, as well as man-made disasters such as civil wars, have been known to result in significant mental health effects on their victims. Objectives The purpose of this general literature review is to analyze the impact and contribution of social determinants to mental health and resilience following natural and man-made disasters. Methods In this paper, we specifically explore some of the most studied factors relating to vulnerability and protection, such as gender, age, ethnicity, social support, and socioeconomic status on mental health and resiliency in disaster survivors. In addition, several other possible factors were discussed, such as previous trauma, childhood abuse, family psychiatric history, and subsequent life stress. Results Using key words such as mental health, social determinants, disasters, wildfires, earthquakes, terrorism attacks, and resilience, we conducted a literature search in major scientific databases Conclusions A discussion of the implications for public health policy and practice is presented Disclosure of Interest None Declared

Introduction The COVID-19 pandemic has produced negative mental health outcomes, which were more prominent in vulnerable communities, such as Fort McMurray (FMM), the community that experienced prior similar disasters. Objectives This study aimed to examine the likelihood and correlates of anxiety symptoms among FMM residents, during the COVID-19 pandemic. Methods A cross-sectional online survey questionnaire was applied between 24 April and 2 June 2021, at FMM community to gather a set of data, including sociodemographic, COVID-19, and clinical information. Generalized anxiety disorder was the main outcome of the study, and was measured using GAD-7 scale. Results Overall, 186 individuals completed the survey (response rate 74.7%). Most of the respondents were females (159, 85.5%); above 40 years (98, 52.7%); employed (175, 94.1%); and in relationship (132, 71%). The prevalence of moderate-to-severe anxiety was (42.5%, 71) on GAD-7 self-reported scale. Subscribers who reported that they would like to receive mental health support; have received no family support since COVID-19 declaration; and have lost their job during the pandemic were all more likely to report moderate-to-severe anxiety (OR = 3.39; 95% CI: 1.29-8.88), (OR = 4.85; 95% CI: 1.56-15.03), and (OR = 4.40; 95% CI: 1.01-19.24), respectively. Conclusions Anxiety levels were high among FMM residents, compared to levels before COVID-19. Clinical and social factors related to the COVID-19 pandemic significantly predicted likely anxiety among Fort McMurray population. It is imperative to mobilize resources to support vulnerable communities during the COVID-19 pandemic. Disclosure of Interest None Declared

Introduction Fort McMurray, a city in northern Alberta, Canada, has experienced multiple traumatic events in the last five years, including the 2016 wildfire, the 2020 floods, and the COVID-19 pandemic. Traumatic events often lead to increased mental health burdens in affected communities. Objectives To assess if the number of traumatic events experienced by residents of Fort McMurray correlates with the prevalence and severity of mental health issues experienced. Methods A cross-sectional study using an online survey questionnaire was used to gather demographic, trauma (wildfire, flooding, and COVID-19), and clinical information from the resident of Fort McMurray between April 24 to June 2 2021. Likely Generalized Anxiety Disorder (GAD), Major Depressive Disorder (MDD), Post-Traumatic Stress Disorder (PTSD) and low resilience were measured using standardized rating scales. Data were analyzed with SPSS version 26 using Chi-Square tests and multivariate regression analysis. Results Respondents who experienced COVID-19 and either flood or wildfire traumas (N = 101) were eleven times more likely to have GAD symptoms (OR: 11.39; 95% CI: 1.43-91.04), four times more likely to have likely MDD, (OR: 3.85; 95% CI: .995-14.90), ten times more likely to have likely PTSD (OR: 10.47; 95% CI: 1.28-85.67), and low resilience (OR: 10.56; 95% CI: 1.21-92.17). Respondents who experienced COVID-19, flooding, and wildfire traumas (N = 47) were eighteen times more likely to express GAD symptoms (OR: 18.30; 95% CI: 2.20-152.45) and more than eleven times likely to have likely PTSD (OR: 11.41; 95% CI: 1.34-97.37) in comparison to the respondents who experienced COVID-19 only trauma (N = 19). Conclusions Measures to reduce climate change and associated natural disasters could reduce the impact of cumulative trauma and associated mental health burden in vulnerable populations. It is essential that more mental health resources are mobilized to support communities impacted by multiple natural disasters. Disclosure of Interest None Declared

Introduction Fort McMurray, a city in northern Alberta, Canada, has experienced multiple traumas in the last five years, including the 2016 wildfire, the 2020 floods, and the COVID-19 pandemic. Eighteen months after the wildfire, major depressive disorder (MDD), generalized anxiety disorder (GAD), and Post Traumatic Stress Disorder (PTSD) symptoms were elevated among school board employees in the city. Objectives This study aimed to compare employees of the school board and other employees of Fort McMurray in respect to the impact the 2016 wildfires, the 2019 COVID pandemic, and the 2020 floods had on their mental health. Methods A quantitative cross-sectional survey was conducted in Fort McMurray from 24 April to 2 June 2021. Online questionnaires were administered through REDCap and were designed to capture socio-demographic characteristics, clinical as well as wildfire, COVID-19, and flooding-related variables. Mental health outcome variables were captured using self-reported standardized assessment scales. Data were analysed with descriptive statistics, Chi-square/Fisher’s Exact tests, and binary regression analysis. Results Of the 249 residents who accessed the online survey, 186 completed the survey, giving a response rate of 74.7%. Of these respondents, 93.5% (174) indicated their employment status and were included in the Chi-square analysis. Most of the respondents were female (86.2%, (150)), above 40 years (53.4%, (93)), and were in a relationship (71.3%, (124)). The prevalence values for MDD, GAD and PTSD among respondents were 42.4%, 41.0, and 36.8%, respectively. There was a statistically significant difference between employees of the school board and other employees with respect to likely PTSD prevalence (28% vs. 45%, respectively, p < 0.05), although with other factors controlled for, in a binary logistic regression model, employer type did not significantly predict likely PTSD. Conclusions The study has established that likely PTSD symptoms were significantly higher in other employees compared to those of school board employees. Greater exposure to the traumatic events and a greater perceived lack of support from other employers might have contributed to the significantly higher prevalence of PTSD in other employees Disclosure of Interest None Declared

Introduction The Fort McMurray wildfire (2016) was one of the most expensive and devastating natural disasters that ever happened in the history of Canada. According to the Insurance Bureau of Canada (2016), the cost of this disaster was estimated at USD 3.6 billion in insured losses. Despite the fundamental role of resilience in the daily functioning of individuals in the form of a protective shield that ameliorates the devastating impact of disasters on their mental well-being, to date, the long-term impact of wildfires on resilience and its associated predictors of low resilience has not been well studied and evaluated. Objectives The study aimed to enhance the understanding of the psychological impact of wildfires through the evaluation of the prevalence and predictors of resilience among the affected residents of Fort McMurray five years after the devastating wildfires. Methods This study applied a cross-sectional survey design which was used to gather quantitative data through an online-based self-administered questionnaire. The surveys included standardized rating scales for resilience (BRS), depression (PHQ-9), anxiety disorder (GAD-7), and post-traumatic stress disorder (PTSD) (PCL-C) was used to measure the prevalence of resilience and its demographic, clinical, as well as wildfire-related predictors. The data collection spanned between April and June of 2021. Data were analyzed using the Statistical Package for Social Sciences (SPSS) version 25 and univariate analysis with done using a chi-squared test and binary logistic regression analysis. Results A total of 249 residents accessed the online survey and 186 completed the survey. Therefore, there was a response rate of 74.7%. Most of the respondents were females (85.5%, 159), above 40 years of age (81.6%, 80), employed (94.1%, 175), and in a relationship (71%, 132). The study identified two variables, thus having PTSD symptoms (OR = 2.85; 95% CI: 1.06–7.63), and the age of respondents significantly predicted low resilience in our sample. The prevalence of low resilience in our sample was found to be about 37.4%. Conclusions The study finding demonstrated that age and the presence of PTSD were the independent significant risk factors associated with low resilience in the affected population of Fort McMurray five years after the devastating wildfire disaster. This result further provides new information about the association between resilience, demographic, and clinical characteristics while adding to the rising body of evidence on the benefits of resilience in individuals during and after disasters. However, further research is needed to enhance understanding of the pathways to Disclosure of Interest None Declared

Introduction As a result of the floods in Fort McMurray (FMM) and the surrounding area in 2020, more than $228 million in insured damage was sustained, over 1200 structures were damaged, and more than 13,000 people were evacuated from their homes. Objectives The aim of the study was to determine the prevalence of post-traumatic stress disorder (PTSD)-like symptoms among the population of FMM one year after the flood in 2020 and the risk predictors associated with such symptoms. Methods In order to collect sociodemographic, clinical, and flood-related information from residents of FMM via REDCap, an online quantitative cross-sectional survey was administered between April 24 and June 02, 2021. Respondents were assessed for probable PTSD using the PTSD Checklist for DSM-5 (PCL-C). Results An overall response rate of 74.7% was achieved among 186 of 249 respondents. The prevalence of likely post-traumatic stress disorder was 39.6% (65). There was a significantly increased likelihood of developing PTSD symptoms in respondents with a history of depression (OR= 5.71; 95% CI: 1.68 - 19.36). As well, disaster responders experiencing limited and no family support after the disaster were more likely to report PTSD symptoms (OR= 2.87; 95% CI: 1.02 - 8.05) and (OR= 2.87; 95% CI: 1.06 - 7.74), respectively. Conclusions As a result of our study, we found that those who had a history of depression and had sought health counseling were significantly more likely to develop PTSD symptoms following flooding, while those with family support were less likely to suffer from PTSD symptoms. There is a need for further studies to investigate the relationship between the need for counseling and the presentation of potential symptoms of post-traumatic stress disorder. Disclosure of Interest None Declared

Introduction Natural disasters adversely impact individuals living in places where they occur, resulting in emotional distress. The wildfire that occurred in Fort McMurray (FMM), Alberta in 2016 is no different. Objectives This study aims to identify the prevalence and predictors of Generalized Anxiety Disorder (GAD) symptoms in residents of FMM five years after the devastating wildfires. Methods Data for the study were collected through a cross-sectional survey conducted online from the 24th of April to the 2nd of June 2021. A validated instrument, the GAD-7 scale, was used to collect information on anxiety. Results Of the total number of 186 residents who took part in the study, the majority were females (85.5%), employed (94.1%), working at school boards (50.0%), and were either married, cohabiting, or partnered (71.0%). The prevalence of likely GAD among the study sample was 42.5%. Unemployed respondents were seventeen times more likely to develop GAD symptoms (OR = 16.62; 95% C.I. 1.23-223.67) while respondents who would like to receive mental health counseling were five times more likely to experience GAD symptoms (OR = 5.35; 95% C.I. 2.03-14.15). Respondents who suffered a loss of property because of the wildfire were two times more likely to develop GAD symptoms (OR = 2.36; 95% C.I. 1.01-22.62). Conclusions Formulators of policy may mitigate GAD symptoms, particularly after natural disasters, by making long-term mental health counseling available and a key component of post-disaster management, and by investing in the social capital of the people to build resilience and support to deal with the post-disaster mental health effects. Disclosure of InterestNone Declared

Introduction The flood in Fort McMurray (FMM) which occurred between April 26 and May 2, 2020, is known to have displaced an estimated population of 1,500 people, and destroyed or damaged about 1,230 buildings. In all, it is estimated to have caused about $228 million in losses. Objectives This study aims to identify the determinants of likely Generalized Anxiety disorder (GAD) among respondents 12 months after the 2020 flooding Methods Data for the study were collected through a cross-sectional survey sent through REDCap and hosted online from the 24th of April to the 2nd of June 2021. The self-administered questionnaire was emailed to respondents using community, government, school, and occupational platforms. Demographic, flooding-related variables and clinical data were collected. A validated instrument, the GAD-7 was used to collect information on likely GAD. Consent was implied by completing the survey forms, and the University of Alberta Health Research Ethics Committee approved the study. Results Of the 249 residents surveyed, 74.7% (186) respondents completed the online survey, 81.6% (80) were above 40 years, 71% (132) were in a relationship, 85.5% (159) were females, and 94.1% (175) were employed. The prevalence of likely GAD was 42.5% in our study. Predictors of likely GAD among respondents included positive employment status (OR = 30.70; 95% C.I. 2.183–423.093), prior diagnosis of depression (OR = 3.30; 95% C.I. 1.157–9.43), and the perceived need to have mental health counseling (OR = 6.28; 95% C.I. 2.553–15.45). Conclusions This study showed that there was an increased magnitude of moderate to high anxiety symptoms among respondents following the natural disaster, particularly the flood in 2020. The predictors of likely GAD include positive employment status, a history of depression diagnosis, and the need to have mental health counseling. Policy formulators may reduce the risk of anxiety after flooding in vulnerable areas by addressing these factors. Disclosure of Interest None Declared

Introduction A natural disaster like flooding causes loss of properties and evacuation and effective mental health. Resilience after natural disasters is a crucial area of research which needs attention. Objectives To explore the prevalence and associated factors of low resilience a year after the 2020 floods in Fort McMurray. Methods A cross-sectional study was conducted in Fort McMurray using online surveys. The data were analyzed with SPSS version 25 using univariate analysis with the chi-squared test and binary logistic regression analysis. Results The prevalence of low resilience was 37.4%. Respondents under 25 years were nearly 26 times more likely to show low resilience (OR= 0.038; 95% CI 0.004 - 0.384). Responders with a history of depression and anxiety (OR= 0.212; CI 95% 0.068-0.661) were nearly four to five times more likely to show low resilience. Similarly, respondents willing to receive mental health counselling (OR=0.134 95%CI: 0.047-0.378) were 7.5 times more likely to show low resilience. Participants residing in the same house before the flood were almost 11 times more likely to show low resilience (OR=0.095; 95% CI 0.021- 0.427), and support from the Government of Alberta was a protective factor. Conclusions The study showed demographic, clinical, and flood-related variables contributing to low resilience. Receiving support from the Government was shown to be a protective factor against low resilience. More robust measures must be in place to promote normal to high resilience among flood victims in affected communities. Disclosure of Interest None Declared

In order to improve the efficiency of identifying parameters using the maximum likelihood method and to avoid the sensitivity of initial values, a proposed method that combines the micro-genetic algorithm with the advance and retreat method is presented in order to identify the eccentricity of the spindle-tool system with random input and output parameters, which obey a certain probability distribution. Eccentricity without prior information is determined through an iterative procedure. The initial value starts from zero, and the interval is determined by the advance and retreat method. Then, the optimal value is searched in the corresponding interval, utilizing the micro-genetic algorithm. The initial value and interval at each of iterations are changed to ensure a fast and stable convergence. Eventually, a numerical example with three kinds of random deviations verifies the feasibility and validity of the proposed method.

For computationally efficient modeling of unsaturated–saturated flow in regional scales, the quasi-three-dimensional (3-D) scheme that considers one-dimensional (1-D) soil water flow and 3-D groundwater flow is an alternative method. However, it is still practically challenging for regional-scale problems due to the highly nonlinear and intensive input data needed for soil water modeling and the reliability of the coupling scheme. This study developed a new quasi-3-D model coupled to the UBMOD 1-D soil water balance model with the MODFLOW 3-D hydrodynamic model. A new implementation method of the iterative scheme was developed in which the vertical net recharge and unsaturated zone depth were used as the exchange information. A modeling framework was developed to organize the coupling scheme of the soil water model and the groundwater model and to handle the pre- and post-processing information. The strength and weakness of the coupled model were evaluated by using two published studies. The comparison results show that the coupled model is satisfactory in terms of computational accuracy and mass balance error. The influences of spatial and temporal discretization as well as the stress period on the model accuracy were discussed. Additionally, the coupled model was used to evaluate groundwater recharge in a real-world study. The measured groundwater table and soil water content were used to calibrate the model parameters, and the groundwater recharge data from a 2-year tracer experiment were used to evaluate the recharge estimation. The field application further shows the practicability of the model. The developed model and the modeling framework provide a convenient and flexible tool for evaluating unsaturated–saturated flow systems at the regional scale.