There is now a general consensus among scientists on occurrences of more and intense climatic disasters, floods and droughts, everywhere in the future. To act sooner and smarter against these negative impacts, we must shift our focus in better understanding of the future climate change and possible implications of that to better manage our water resources. Certainly, there is a link between the future effects of climate change on water resources and trends of climatic variables. In this study, by using Mann-Kendall trend analysis method, it is concluded that from 1961 to 2010 only temperature has an upward trend, in all the seasons and yearly, in all the 16 studied stations from north, middle and south of Sweden. Furthermore, runoff simulated by HBV model shows increasing trend in summer and winter which is in partially agreement with the recorded one that discerns a growth in the mentioned seasons, as well as yearly. What is more, potential evapotranspiration estimated by FAO Penman-Monteith equation and actual one simulated by CoupModel reveal a rise in spring for the former and both spring and winter for the latter. Other meteorological variables do not show any significant trend, while intensive precipitation increased in winter and summer in the majority of the stations. Comparing the runoffs simulated by CoupModel and HBV model shows that HBV works better for three selected stations which can enforce the claim that HBV works better for smaller fields.

There is a debate within the field of policy studies whether disasters are drivers of policy reforms, as encapsulated by the disaster-reform hypothesis. Since the disaster rate for extreme weather events are increasing in frequency and severity due to climate change, it is of high relevance to study if these disasters have any effect on climate polices. The aim of this thesis is therefore to empirically explore if there are any discernible global trends of disasters preceding a subsequent increase in Climate resilient development (CRD) policies and to show the variation of “effect lag” between income groups and regions. The research design operationalises the most severe disasters through “milestone events” and creates a CRD index by the arithmetical mean of sustainable development, climate adaptation, and climate mitigation. The results show a proportional share of countries experienced an effect lag of 1-3 years after their milestone events, while a large incidence of HIC and LMIC countries had a lag of 4-6 years. This explorative thesis has provided a research design and results on CRD, previously undescribed, that suggests several pathways for future studies such as interesting samples for case studies and alternative designs to the operationalisation of concepts.

This study is a spatiotemporal analysis of the COVID-19 pandemic in school-age children (5-18 years) in Tennessee, from 2020-03-19 to 2022-02-12. Trend Analysis, Emerging Hot Spot Analysis, and a time series revealed three significant waves in both age groups. Therefore, Change Point Detection at the county level was completed using six defined change points to identify the wax and wane of the three COVID-19 waves. Hierarchical Cluster Analysis grouped counties with similar change points into six clusters. No spatial pattern was observed in distribution of the six clusters, however, when each change point was evaluated separately, spatial autocorrelation was present, showing that timing of the individual waves was clustered in space. This research describes appropriate spatioanalytical methods useful at different stages of a pandemic and could inform policymaking by public health officials.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

Background: This study compared patient profiles and clinical courses of SARS-CoV-2 infected inpatients over different pandemic periods. Methods: In a retrospective cross-sectional analysis, we examined administrative data of German Helios hospitals using ICD-10-codes at discharge. Inpatient cases with SARS-CoV-2 infection admitted between 03/04/2020 and 07/19/2022 were included irrespective of the reason for hospitalization. All endpoints were timely assigned to admission date for trend analysis. The first pandemic wave was defined by change points in time-series of incident daily infections and compared with different later pandemic phases according to virus type predominance. Results: We included 72,459 inpatient cases. Patients hospitalized during the first pandemic wave (03/04/2020–05/05/2020; n = 1,803) were older (68.5 ± 17.2 vs. 64.4±22.6 years, p<0.01) and severe acute respiratory infections were more prevalent (85.2 vs. 53.3%, p < 0.01). No differences were observed with respect to distribution of sex, but comorbidity burden was higher in the first pandemic wave. The risk of receiving intensive care therapy was reduced in all later pandemic phases as was in-hospital mortality when compared to the first pandemic wave. Trend analysis revealed declines of mean age and Elixhauser comorbidity index over time as well as a decline of the utilization of intensive care therapy, mechanical ventilation and in-hospital mortality. Conclusion: Characteristics and outcomes of inpatients with SARS-CoV-2 infection changed throughout the observational period. An ongoing evaluation of trends and care pathways will allow for the assessment of future demands