Long-Term Trends of Extra-Tropical Cyclones in the Extended ERA5 Reanalysis

<p>Long-term reanalysis data sets are needed to determine the natural variability of extra-tropical cyclone tracks and for the assessment of the response to global warming. Using a systematic change-point analysis we provide evidence that the pre-satellite ERA5 data of the Backward Extension (ERA5-BE, covering 1950-1978) is highly compatible with the standard ERA5 (1979-2021) data sets. We observe that the joint ERA5 data from 1950 to 2021 is consistent in all storm-related quantities, allowing long-term studies. Despite the high inter-annual variability, a trend analysis suggests that the intensity of extra-tropical cyclones has increased significantly in the Northern Hemisphere from 1950 to 2021. The propagation speed of extra-tropical cyclones has notably decreased and the North Atlantic cyclone track, in particular, has shifted northward. Furthermore, the number of North Pacific storms increased significantly; these storms exhibit longer life cycles and travel larger distances, while they also grow more slowly. From 1979 to 2021 we find increases in wind gusts and cyclone-related precipitation. The central geopotential height, a measure for storminess, has decreased in both storm track areas. The observed changes originating from potential changes in the atmospheric circulation are the result of natural variability and anthropogenic global warming. Future storm adaptation planning should consider the observed increase in storm-related impacts.</p>

Motor Behavior Changes Are Predictive of Acute Events in Skilled Nursing

Background Common acute medical conditions among older adults with dementia in skilled nursing include falls, delirium, and pneumonia. This study utilized a sensor technology to examine how motor behaviors may predict these acute events. Methods Radio frequency identification (RFID) technology continuously measured time and distance travelled, gait speed, and continuous walking with little/no breaks (paths) across 3 long-term facilities for up to 1 year (N=51). Change point analysis estimates the probability of whether a sudden change occurred and provides the location of the change point (in days prior to the event) in a time series model. Results Gait speed had very low probability to detect a change point across all events (22 falls, 10 delirium and 8 pneumonia). Sensitivity estimates ranged from 63% (number of paths) to 90% (distance travelled) for a fall; 37.5% (number of paths) to 100% (rest of the motor behaviors) for pneumonia. Except for gait speed, all other motor behaviors had high probability (100%) to detect a delirium change point. There was intra-individual variability in the location of the change points (mean of 10 days). Linear regression models for time and distance travelled using baseline predictors of age, ethnicity, gait and balance explained 89% and 90% of the variance in change point locations. Conclusions Prior to an acute event there is a significant change in motor behavior, suggesting these are an early signal that may be used to prevent a fall or provide for the earlier recognition and treatment of delirium and pneumonia.

Hospitalizations and emergency department visits trends among elderly individuals in proximity to death: a retrospective population-based study

Acute healthcare services are extremely important, particularly during the COVID-19 pandemic, as healthcare demand has rapidly intensified, and resources have become insufficient. Studies on specific prepandemic hospitalization and emergency department visit (EDV) trends in proximity to death are limited. We examined time-trend specificities based on sex, age, and cause of death in the last 2 years of life. Datasets containing all hospitalizations and EDVs of elderly residents in Friuli-Venezia Giulia, Italy (N = 411,812), who died between 2002 and 2014 at ≥ 65 years, have been collected. We performed subgroup change-point analysis of monthly trends in the 2 years preceding death according to sex, age at death (65–74, 75–84, 85–94, and ≥ 95 years), and main cause of death (cancer, cardiovascular, or respiratory disease). The proportion of decedents (N = 142,834) accessing acute healthcare services increased exponentially in proximity to death (hospitalizations = 4.7, EDVs = 3.9 months before death). This was inversely related to age, with changes among the youngest and eldest decedents at 6.6 and 3.5 months for hospitalizations and at 4.6 and 3.3 months for EDVs, respectively. Healthcare use among cancer patients intensified earlier in life (hospitalizations = 6.8, EDVs = 5.8 months before death). Decedents from respiratory diseases were most likely to access hospital-based services during the last month of life. No sex-based differences were found. The greater use of acute healthcare services among younger decedents and cancer patients suggests that policies potentiating primary care support targeting these at-risk groups may reduce pressure on hospital-based services.

744. Incidence and Duration of Diagnostic Delays Associated with Dengue Fever

Background Dengue fever is a prominent emerging arboviral infection in the tropics and subtropics, and an important cause of systemic febrile illness among some international travelers. Signs and symptoms are similar to more common infectious illnesses in temperate climates, and dengue may not be promptly considered when patients seek evaluation. Methods We conducted a retrospective cohort study of patients diagnosed with dengue fever using the IBM MarketScan Research database from 2001-2017. We identified cases of dengue fever where patients were enrolled ≥ 1 year prior to the index diagnosis. All healthcare visits in the year prior to the index diagnosis were collected and we identified visits with signs/symptoms compatible with dengue or a diagnosis made of an illness with similar symptoms (e.g., influenza) before the index dengue diagnosis. We used a time-series change-point analysis to identify the time before diagnosis in which symptoms of dengue became more prominent. We conducted a bootstrap-based simulation analysis to estimate the duration and frequency of missed diagnostic opportunities. Results We identified 4,449 cases of dengue fever that met eligibility criteria. We found that 2,791 (62.7%) had ≥ 1 healthcare visit(s) prior to diagnosis with characteristic symptoms of dengue recorded. Our simulations analysis supports that 32.9% (95% CI: 31.1-35.0) experienced 1 or more missed opportunities for diagnosis. Among these patients, the average duration of diagnostic delay was 8.26 (CI: 6.32-11.38) days and ~21% of patients had a diagnostic delay of 2 or more weeks. Patients with a delayed diagnosis averaged 2.2 (CI 2.11-2.29) healthcare visits which represented missed opportunities. Missed opportunities were more likely during weekend, ED or outpatient visits. Conclusion Dengue fever is not considered in the majority of patients at the time of the initial symptomatic evaluation in the U.S., indicating delays in diagnosis are common. Enhanced education of providers about dengue fever could lead to more prompt diagnosis that should help optimize patient management. Disclosures All Authors: No reported disclosures

When and Why Did Human Brains Decrease in Size? A New Change-Point Analysis and Insights From Brain Evolution in Ants

Human brain size nearly quadrupled in the six million years since Homo last shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution of Homo and technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history of Homo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.

Application of Change Point Analysis of Response Time Data to Detect Test Speededness

Computer-based and web-based testing have become increasingly popular in recent years. Their popularity has dramatically expanded the availability of response time data. Compared to the conventional item response data that are often dichotomous or polytomous, response time has the advantage of being continuous and can be collected in an unobstrusive manner. It therefore has great potential to improve many measurement activities. In this paper, we propose a change point analysis (CPA) procedure to detect test speededness using response time data. Specifically, two test statistics based on CPA, the likelihood ratio test and Wald test, are proposed to detect test speededness. A simulation study has been conducted to evaluate the performance of the proposed CPA procedure, as well as the use of asymptotic and empirical critical values. Results indicate that the proposed procedure leads to high power in detecting test speededness, while keeping the false positive rate under control, even when simplistic and liberal critical values are used. Accuracy of the estimation of the actual change point, however, is highly dependent on the true change point. A real data example is also provided to illustrate the utility of the proposed procedure and its contrast to the response-only procedure. Implications of the findings are discussed at the end.