Time Series Analysis Of Variability Research Articles

COVID-19, community response, public policy, and travel patterns: A tale of Hong Kong.

The COVID-19 outbreak has necessitated a critical review of urban transportation and its role in society against the backdrop of an exogenous shock. This article extends the transportation literature regarding community responses to the COVID-19 pandemic and what lessons can be obtained from the case of Hong Kong in 2020. Individual behavior and collective responsibility are considered crucial to ensure both personal and community wellbeing in a pandemic context. Trends in government policies, the number of infectious cases, and community mobility are examined using multiple data sources. The mobility changes that occurred during the state of emergency are revealed by a time-series analysis of variables that measure both the epidemiological severity level and government stringency. The results demonstrate a high response capability of the local government, inhabitants, and communities. Communities in Hong Kong are found to have reacted faster than the implementation of health interventions, whereas the government policies effectively reduced the number of infection cases. The ways in which community action are vital to empower flexible and adaptive community responses are also explored. The results indicate that voluntary community involvement constitutes a necessary condition to help inform and reshape future transport policy and response strategies to mitigate the pandemic.

BOLHA DE PREÇOS NO MERCADO ACIONÁRIO: UMA ANÁLISE DO SETOR DA CONSTRUÇÃO CIVIL NO BRASIL

O desempenho dos diversos setores da economia ao longo do tempo está sujeito a uma série de interferências e influências que determinam a dinâmica de sua evolução, passando por momentos de grande euforia, num extremo, a outros de profunda estagnação e recessão. Sabendo-se que o mercado de ações funciona como um verdadeiro termômetro destas mudanças, o presente trabalho teve por objetivo investigar indícios que pudessem caracterizar a ocorrência de um processo de formação de bolha de preços no setor imobiliário. Para tanto, o estudo partiu da análise de cotações históricas das ações e seus respectivos dividendos de empresas da construção civil do Brasil presentes na BM&F Bovespa. As análises estatísticas dos valores estudados mostraram que as cotações, na grande maioria dos casos, apresentam um alto nível de dispersão e que os retornos esperados destas ações se distribuem em um intervalo percentual nada uniforme. Do ponto de vista econométrico, o estudo empregou testes de cointegração para análise de séries históricas das variáveis, concluindo que mais da metade da amostra de dados não possui cointegração, revelando a possibilidade de presença de um componente especulativo. Tendo em vista as disparidades dos dados, o trabalho postula, desta maneira, que o setor de construção civil brasileiro possui componente de bolha nos preços de suas ações.

Time Series Analysis of Variables Associated With Daily Mean Emergency Department Length of Stay

We measure the effect of various input, throughput, and output factors on daily emergency department (ED) mean length of stay per patient (daily mean length of stay). The study was a retrospective review of 93,274 ED visits between April 15, 2002, and December 31, 2003. The association between the daily mean length of stay and the independent variables was assessed with autoregressive moving average time series analysis (ARIMA). The following independent variables were measured per 24-hour period: number of elective surgical admissions, ED volume, number of ED admissions, number of ED ICU admissions, number of ED clinical attending hours, hospital medical-surgical occupancy (hospital occupancy), and day of the week. Three factors were independently associated with daily mean length of stay in time series analysis: number of elective surgical admissions, number of ED admissions, and hospital occupancy. The daily mean length of stay increased by 0.21 minutes for every additional elective surgical admission, 2.2 minutes for every additional admission, and 4.1 minutes for every 5% increase in hospital occupancy. Elective surgical admissions were associated with a maximum of 35 hours of additional ED dwell time. The model accounted for 31.5% of the variability in daily mean length of stay. The final model parameters for the ARIMA analysis were autoregressive term (1) moving average (1). Hospital occupancy and the number of ED admissions are associated with daily mean length of stay. Every additional elective surgical admission prolonged the daily mean length of stay by 0.21 minutes per ED patient. Autocorrelation exists between the daily mean length of stay of the current day and the previous day.

Heart Rate Variability in Intensive Care

Clinicians have long been aware that the normal oscillations in a heart beat are lost during fetal distress, during the early stages of heart failure, with advanced aging, and with critical illness and injury. However, these oscillations, or variability in heart rate and other cardiovascular signals, have largely been ignored or discounted as variances from the mean or average values. It is becoming increasingly clear that these oscillations reflect the dynamic interactions of many physiologic processes, including neuroautonomic regulation of heart rate and blood pressure. We present a synthesis and review of the current literature concerning heart rate variability with special reference to intensive care. This article describes the background of time series analysis of heart rate variability including time and frequency domain and nonlinear measurements. The implications and potential for time series analysis of variability in cardiovascular signals in clinical diagnosis and management of critically ill and injured patients are discussed.