scholarly journals Moon/sun – suicide

2018 ◽  
Vol 33 (2) ◽  
pp. 213-217 ◽  
Author(s):  
Zoltán Kmetty ◽  
Álmos Tomasovszky ◽  
Károly Bozsonyi
Keyword(s):  
Time Series ◽  
Regression Models ◽  
Geomagnetic Storms ◽  
Age Groups ◽  
International Literature ◽  
Arima Models ◽  
Moon Phases ◽  
Gender And Age ◽  
Solar Events ◽  
Sun Activity

Abstract Introduction: Findings concerning the effects of moon phases and sun activity on suicide are mixed in the international literature. Aim: Our aim was to examine the hypothesised effects according to gender and age on Hungarian data covering more than 30 years. Methods: Time series ARIMA models and dynamic regression models were applied in our analysis. Results: Among women aged 20–49 years, a significant increase in the risk of suicide has been observed during proton solar events. At the same time, among women aged 50–59 years a slight but significant decrease has been identified in the risk of suicide during magnetic storms and full moons. Conclusion: Proton solar events, geomagnetic storms and moon phases caused changes in the risk of suicide in certain age groups in the case of women only.

scholarly journals Correlation between Acinetobacter baumannii Resistance and Hospital Use of Meropenem, Cefepime, and Ciprofloxacin: Time Series Analysis and Dynamic Regression Models

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 480
Author(s):  
Rania Kousovista ◽  
Christos Athanasiou ◽  
Konstantinos Liaskonis ◽  
Olga Ivopoulou ◽  
George Ismailos ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Acinetobacter Baumannii ◽  
Regression Models ◽  
Tertiary Care ◽  
Antimicrobial Use ◽  
Care Hospital ◽  
Arima Models ◽  
Series Analysis ◽  
Resistance Rates

Acinetobacter baumannii is one of the most difficult-to-treat pathogens worldwide, due to developed resistance. The aim of this study was to evaluate the use of widely prescribed antimicrobials and the respective resistance rates of A. baumannii, and to explore the relationship between antimicrobial use and the emergence of A. baumannii resistance in a tertiary care hospital. Monthly data on A. baumannii susceptibility rates and antimicrobial use, between January 2014 and December 2017, were analyzed using time series analysis (Autoregressive Integrated Moving Average (ARIMA) models) and dynamic regression models. Temporal correlations between meropenem, cefepime, and ciprofloxacin use and the corresponding rates of A. baumannii resistance were documented. The results of ARIMA models showed statistically significant correlation between meropenem use and the detection rate of meropenem-resistant A. baumannii with a lag of two months (p = 0.024). A positive association, with one month lag, was identified between cefepime use and cefepime-resistant A. baumannii (p = 0.028), as well as between ciprofloxacin use and its resistance (p < 0.001). The dynamic regression models offered explanation of variance for the resistance rates (R2 > 0.60). The magnitude of the effect on resistance for each antimicrobial agent differed significantly.

scholarly journals Epidemiological and time series analysis on the incidence and death of AIDS and HIV in China

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Bin Xu ◽  
Jiayuan Li ◽  
Mengqiao Wang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Goodness Of Fit ◽  
Intervention Strategy ◽  
Age Groups ◽  
Arima Models ◽  
Optimal Model ◽  
Series Analysis ◽  
Infectious Disease Reporting ◽  
Significant Difference

Abstract Background To investigate the regional and age-specific distribution of AIDS/HIV in China from 2004 to 2017 and to conduct time series analysis of the epidemiological trends. Method Using official surveillance data from publicly accessible database of the national infectious disease reporting system, we described long-term patterns of incidence and death in AIDS/HIV, analyzed age group and regional epidemic characteristics, and established Autoregressive Integrated Moving Average (ARIMA) models for time series analysis. Result The incidence and death of AIDS/HIV have increased rapidly from 2004 to 2017, with significant difference regarding age groups and provincial regions (a few provinces appear as hot spots). With goodness-of-fit criteria and using data from 2004 to 2015, ARIMA (0,1,3) × (2,0,0), ARIMA (3,1,0) × (1,0,1), and ARIMA (0,1,2) × (2,0,0) were chosen as the optimal model for the incidence of AIDS, HIV, and combined; ARIMA (0,1,3) × (1,0,0) was chosen as the optimal model for the death of AIDS, HIV, and combined. ARIMA models robustly predicted the incidence and death of AIDS/HIV in 2016 and 2017. Conclusion A focused intervention strategy targeting specific regions and age groups is essential for the prevention and control of AIDS/HIV. ARIMA models function as data-driven and evidence-based methods to forecast the trends of infectious diseases and formulate public health policies.

scholarly journals Influenza and pneumonia hospitalizations in Ontario: a time-series analysis

2004 ◽  
Vol 132 (6) ◽  
pp. 1167-1174 ◽  
Author(s):  
ERIC J. CRIGHTON ◽  
RAHIM MOINEDDIN ◽  
MUHAMMAD MAMDANI ◽  
ROSS E. G. UPSHUR
Keyword(s):  
Gender Differences ◽  
Time Series ◽  
Age Groups ◽  
Population Based ◽  
Prevention Strategies ◽  
Specific Population ◽  
Service Allocation ◽  
Gender And Age ◽  
Comprehensive Examination ◽  
Kolmogorov Smirnov

A comprehensive examination of gender and age-specific influenza and pneumonia hospitalization seasonality is currently lacking. Using population-based data for Ontario, Canada between April 1988 and March 2002 (n=339803 hospitalizations), findings from this study revealed clear seasonality [Fisher's Kappa (FK) test=68·64, P<0·001; Bartlett's Kolmogorov–Smirnov (BKS) test=0·68, P<0·001] with consistent summer troughs and winter peaks for both sexes and all ages combined. The very young (both sexes 0–4 years) demonstrated the strongest seasonality (Rautoreg2=0·97) and females aged 10–19 years, the weakest (Rautoreg2=0·59). Gender differences were most pronounced in the oldest age groups (80+ years) where females had an average annualized peak rate of 250/100000 compared to 400/100000 for males. These findings can contribute to more population-specific prevention strategies and effective resource and service allocation based on seasonal and specific population demands.

Measurement Invariance of Divergent Thinking Across Gender, Age, and School Forms

2009 ◽  
Vol 25 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Heinz Holling
Keyword(s):  
Measurement Invariance ◽  
Divergent Thinking ◽  
Factor Model ◽  
Age Groups ◽  
Thinking Skills ◽  
Specific Model ◽  
Confirmatory Factor Analyses ◽  
Domain Specific ◽  
Gender And Age ◽  
Confirmatory Factor

The present study explores the factorial structure and the degree of measurement invariance of 12 divergent thinking tests. In a large sample of German students (N = 1328), a three-factor model representing verbal, figural, and numerical divergent thinking was supported. Multigroup confirmatory factor analyses revealed that partial strong measurement invariance was tenable across gender and age groups as well as school forms. Latent mean comparisons resulted in significantly higher divergent thinking skills for females and students in schools with higher mean IQ. Older students exhibited higher latent means on the verbal and figural factor, but not on the numerical factor. These results suggest that a domain-specific model of divergent thinking may be assumed, although further research is needed to elucidate the sources that negatively affect measurement invariance.

Values and occupational choose

2014 ◽  
Author(s):  
Angela Furfari ◽  
Sílvio Brito ◽  
Valeria Caggiano
Keyword(s):  
Construct Validity ◽  
Value Theory ◽  
Human Values ◽  
International Literature ◽  
Professional Background ◽  
Gender And Age ◽  
Abstract Method

Several studies demonstrate that Schwartz’s (2006) theory of human values is valid in cultures previously beyond its range. We measured the 10 value constructs in the theory with the Portrait Values Questionnaire (PVQ), a new and less abstract method. This study explores the influence of values in a professional choose, focusing on the associations between social and professional background. The findings support the construct validity of the test. The results suggest, there is a matching between values and occupational choose, there are evident differences between gender and age. These results confirm the international literature about different gender and value system’s. Its theoretical meaning in the context of Schwartz’s culture-level value theory is discussed.

Fortuna

2018 ◽  
Author(s):  
Daniele Miano
Keyword(s):  
Middle Ages ◽  
Historical Development ◽  
Conceptual Analysis ◽  
Dominant Role ◽  
Age Groups ◽  
New Approach ◽  
Good Fortune ◽  
Gender And Age ◽  
New Meanings ◽  
And Gender

This book focuses on the Latin goddess Fortuna, one of the better known deities in ancient Italy. The earliest forms of her worship can be traced back to archaic Latium, and she was still a widely recognized allegorical figure during the Middle Ages and the Renaissance. The main reason for her longevity is that she was a conceptual deity, and had strong associations with chance and good fortune. When they were interacting with the goddess, communities, individuals, and gender and age groups were inevitably also interacting with the concept. These relations were not neutral: they allowed people to renegotiate the concept, enriching it with new meanings and challenging established ones. The geographical and chronological scope of this book is Italy from the archaic age to the late Republic. In this period Italy was a fragmented, multicultural and multilinguistic environment, characterized by a wide circulation of people, customs, and ideas, in which Rome played an increasingly dominant role. All available sources on Fortuna have been used: literary, epigraphic, and archaeological. The study of the goddess based on conceptual analysis will serve to construct a radically new picture of the historical development of this deity in the context of the cultural interactions taking place in ancient Italy. The book also aims at experimenting with a new approach to polytheism, based on the connection between gods and goddesses and concepts.

scholarly journals Hybrid Model for Time Series of Complex Structure with ARIMA Components

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1122
Author(s):  
Oksana Mandrikova ◽  
Nadezhda Fetisova ◽  
Yuriy Polozov
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Hybrid Model ◽  
Complex Structure ◽  
Arima Model ◽  
Ionospheric Parameter ◽  
Arima Models ◽  
Complicated Structure ◽  
Threshold Functions ◽  
Anomalous Component

A hybrid model for the time series of complex structure (HMTS) was proposed. It is based on the combination of function expansions in a wavelet series with ARIMA models. HMTS has regular and anomalous components. The time series components, obtained after expansion, have a simpler structure that makes it possible to identify the ARIMA model if the components are stationary. This allows us to obtain a more accurate ARIMA model for a time series of complicated structure and to extend the area for application. To identify the HMTS anomalous component, threshold functions are applied. This paper describes a technique to identify HMTS and proposes operations to detect anomalies. With the example of an ionospheric parameter time series, we show the HMTS efficiency, describe the results and their application in detecting ionospheric anomalies. The HMTS was compared with the nonlinear autoregression neural network NARX, which confirmed HMTS efficiency.

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals Seasonality in extra-pulmonary tuberculosis notifications in Germany 2004-2014- a time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tanja Charles ◽  
Matthias Eckardt ◽  
Basel Karo ◽  
Walter Haas ◽  
Stefan Kröger
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Disease Onset ◽  
Age Groups ◽  
Age Group ◽  
Pulmonary Tb ◽  
Series Analysis ◽  
Disease Site ◽  
Extra Pulmonary

Abstract Background Seasonality in tuberculosis (TB) has been found in different parts of the world, showing a peak in spring/summer and a trough in autumn/winter. The evidence is less clear which factors drive seasonality. It was our aim to identify and evaluate seasonality in the notifications of TB in Germany, additionally investigating the possible variance of seasonality by disease site, sex and age group. Methods We conducted an integer-valued time series analysis using national surveillance data. We analysed the reported monthly numbers of started treatments between 2004 and 2014 for all notified TB cases and stratified by disease site, sex and age group. Results We detected seasonality in the extra-pulmonary TB cases (N = 11,219), with peaks in late spring/summer and troughs in fall/winter. For all TB notifications together (N = 51,090) and for pulmonary TB only (N = 39,714) we did not find a distinct seasonality. Additional stratified analyses did not reveal any clear differences between age groups, the sexes, or between active and passive case finding. Conclusion We found seasonality in extra-pulmonary TB only, indicating that seasonality of disease onset might be specific to the disease site. This could point towards differences in disease progression between the different clinical disease manifestations. Sex appears not to be an important driver of seasonality, whereas the role of age remains unclear as this could not be sufficiently investigated.

Sign in / Sign up

Export Citation Format

Share Document