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

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.

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

Pathogens ◽

10.3390/pathogens10040480 ◽

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.

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

BMC Public Health ◽

10.1186/s12889-021-10655-6 ◽

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.

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The Impact of an Inactivated Hepatitis A Vaccine with One Dose in Brazil: A Retrospective Time-Series

Vaccines ◽

10.3390/vaccines9040407 ◽

2021 ◽

Vol 9 (4) ◽

pp. 407

Author(s):

Ana Luiza Bierrenbach ◽

Yoonyoung Choi ◽

Paula de Mendonça Batista ◽

Fernando Brandão Serra ◽

Cintia Irene Parellada ◽

...

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Hepatitis A ◽

National Level ◽

Age Groups ◽

High Rate ◽

Series Analysis ◽

Annual Reduction ◽

The Impact ◽

Vaccination Period

Background: In 2014, a recommended one-dose of inactivated hepatitis A vaccine was included in the Brazilian National Immunization Program targeting children 12–24 months. This decision addressed the low to intermediate endemicity status of hepatitis A across Brazil and the high rate of infection in children and adolescents between 5 and 19 years old. The aim of the study was to conduct a time-series analysis on hepatitis A incidence across age groups and to assess the hepatitis A distribution throughout Brazilian geographic regions. Methods: An interrupted time-series analysis was performed to assess hepatitis A incidence rates before (2010–2013) and after (2015–2018) hepatitis A vaccine program implementation. The time-series analysis was stratified by age groups while a secondary analysis examined geographic distribution of hepatitis A cases. Results: Overall incidence of hepatitis A decreased from 3.19/100.000 in the pre-vaccine period to 0.87/100.000 (p = 0.022) post-vaccine introduction. Incidence rate reduction was higher among children aged 1-4 years old, with an annual reduction of 67.6% in the post-vaccination period against a 7.7% annual reduction in the pre-vaccination period (p < 0.001). Between 2015 and 2018, the vaccination program prevented 14,468 hepatitis A cases. Conclusion: Our study highlighted the positive impact of a recommended one-dose inactivated hepatitis A vaccine for 1–4-years-old in controlling hepatitis A at national level.

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NONLINEAR TIME SERIES ANALYSIS OF ELECTROENCEPHALOGRAM TRACINGS OF CHILDREN WITH AUTISM

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127412500447 ◽

2012 ◽

Vol 22 (03) ◽

pp. 1250044

Author(s):

LANCE ONG-SIONG CO TING KEH ◽

ANA MARIA AQUINO CHUPUNGCO ◽

JOSE PERICO ESGUERRA

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Prediction Error ◽

Children With Autism ◽

Nonlinear Time Series ◽

Nonlinear Time Series Analysis ◽

Normal Children ◽

Series Analysis ◽

Significant Difference ◽

Severe Autism

Three methods of nonlinear time series analysis, Lempel–Ziv complexity, prediction error and covariance complexity were employed to distinguish between the electroencephalograms (EEGs) of normal children, children with mild autism, and children with severe autism. Five EEG tracings per cluster of children aged three to seven medically diagnosed with mild, severe and no autism were used in the analysis. A general trend seen was that the EEGs of children with mild autism were significantly different from those with severe or no autism. No significant difference was observed between normal children and children with severe autism. Among the three methods used, the method that was best able to distinguish between EEG tracings of children with mild and severe autism was found to be the prediction error, with a t-Test confidence level of above 98%.

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Functional time series analysis of age-specific fertility rates: visualizing the change in the age-pattern of fertility in India

International Journal of Advanced Statistics and Probability ◽

10.14419/ijasp.v4i2.6182 ◽

2016 ◽

Vol 4 (2) ◽

pp. 79

Author(s):

Mallika Deb ◽

Tapan Kumar Chakrabarty

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Rural Women ◽

Age Groups ◽

Reproductive Age ◽

Data Series ◽

Fertility Rates ◽

Registration System ◽

Series Analysis ◽

Functional Time Series

Functional Time Series Analysis (FTSA) is carried out in this article to uncover the temporal variations in the age pattern of fertility in India. Attempt is made to find whether there is any typical age pattern in the nation’s fertility across the reproductive age groups. If so, how do we characterize the role of changing age pattern of fertility across reproductive age groups in the nation’s fertility transition? We have used region-specific (rural-urban) and country level data series on Age-Specific Fertility Rates (ASFRs) available from Sample Registration System (SRS), India during 1971-2013. Findings of this study are very impressive. It is observed that the youngest age group of women in 15-19 years has contributed to the maximum decline in fertility with a substantially accelerated pace during the period of study. The major changes in fertility rates among Indian women dominated by the rural representation occur at the ages after 30. Further, the study also suggests that the future course of demographic transition in India from third phase to the fourth phase of replacement fertility would depend on the degree and pace of decline among the rural women aged below 30 years.

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Decrease in blood donation rates in Japan: a time series analysis

Revista Brasileira de Epidemiologia ◽

10.1590/1980-549720200047 ◽

2020 ◽

Vol 23 ◽

Author(s):

Yutaka Owari ◽

Nobuyuki Miyatake ◽

Hiromi Suzuki

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Goodness Of Fit ◽

Blood Donation ◽

Initial Value ◽

Post Intervention ◽

Series Analysis ◽

Average Analysis ◽

Slope Difference ◽

The Impact

ABSTRACT: Objective: To clarify that one of the causes for the decrease in blood donation (BD) rates was the introduction of the 400 ml BD program in 1986. Method: BP rates were monitored over 48 years (1965-2012) and were divided into pre- and post-intervention periods prior to analysis. An interrupted time series analysis was performed using annual data on BD rates, and the impact of the 400 ml BD program was investigated. Results: In a raw series, autoregressive integrated moving average analysis revealed a significant change in slope between the pre- and post-intervention periods in which the intervention factor was the 400 ml BD program. The parameters were as follows: intercept (initial value) = 0.315, confidence interval (CI) = (0.029, 0.601); slope (pre-intervention) = 0.316, CI = (0.293, 0.340); slope difference = -0.435, CI = (-0.462, -0.408); slope (post-intervention) = -0.119, CI = (-0.135, -0.103); all, p = 0.000; goodness-of-fit, R2 = 0.963. After adjusting for stationarity and autocorrelation, the parameters were as follows: intercept (initial value) = -0.699, CI = (-0.838, -0.560); slope (pre-intervention) = 0.136, CI = (0.085, 0.187); slope difference = -0.165, CI = (-0.247, -0.083); slope (post-intervention) = -0.029, CI = (-0.070, 0.012); all, p = 0.000 (except for slope (post-intervention), p = 0.170); goodness-of-fit, R2 = 0.930. Conclusion: One of the causes for decrease in BD rates may be due to the introduction of the 400 ml BD program in Japan.

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Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence

Malaria Journal ◽

10.1186/s12936-016-1602-1 ◽

2016 ◽

Vol 15 (1) ◽

Cited By ~ 33

Author(s):

Mohammad Y. Anwar ◽

Joseph A. Lewnard ◽

Sunil Parikh ◽

Virginia E. Pitzer

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Future Trends ◽

Arima Models ◽

Series Analysis

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Analysis of Bridge Deflection Based on Time Series

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.71-78.4545 ◽

2011 ◽

Vol 71-78 ◽

pp. 4545-4548 ◽

Cited By ~ 1

Author(s):

Lei Sun ◽

Xian Wu Hao

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Goodness Of Fit ◽

Arima Model ◽

Least Square Method ◽

Least Square ◽

Monitoring Data ◽

Goodness Of Fit Test ◽

Bridge Monitoring ◽

Series Analysis

The bridge health monitoring system can collect large amounts of data, but it lacks the trend analysis of monitoring data. This article introduced the method of Time series analysis into the analysis of bridge monitoring data, and adopted ARIMA model in time series analysis of monitoring data, used the least square method for parameter estimation, established the prediction model for bridge deflection, and conducted the goodness of fit test. Take the actual bridge monitoring data as an example, it was demonstrated that the method is feasible in the prediction of bridge condition trend.

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STUDY OF THE INFLUENCE OF CHANGING THE PARAMETERS OF THE ARIMA MODEL ON THE QUALITY OF THE FORECAST FOR SHORT DATA SETS

Bulletin of the South Ural State University Ser Computer Technologies Automatic Control & Radioelectronics ◽

10.14529/ctcr210304 ◽

2021 ◽

Vol 21 (3) ◽

pp. 36-46

Author(s):

M.N. Fel’ker ◽

◽

V.V. Chesnov

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Arima Model ◽

Annual Data ◽

Data Sets ◽

Arima Models ◽

Data Set ◽

Series Analysis ◽

The Future

Time series, i.e. data collected at various times. The data collection segments may differ de-pending on the task. Time series are used for decision making. Time series analysis allows you to get some result that will determine the format of the decision. Time series analysis was carried out in very ancient times, for example, various calendars became a consequence of the analysis. Later, time series analysis was applied to study and forecast economic, social and other systems. Time se-ries appeared a long time ago. Once upon a time, ancient Babylonian astronomers, studying the po-sition of the stars, discovered the frequency of eclipses, which allowed them to predict their appearance in the future. Later, the analysis of time series, in a similar way, led to the creation of various calen-dars, for example, harvest calendars. In the future, in addition to natural areas, social and economic ones were added. Aim. Search for classification patterns of time series, allowing to understand whether it is possible to apply the ARIMA model for their short-term (3 counts) forecast. Materials and methods. Special software with ARIMA implementation and all need services is made. We examined 59 data sets with a short length and step equal a year, less than 20 values in the paper. The data was processed using Python libraries: Statsmodels and Pandas. The Dickey – Fuller test was used to de-termine the stationarity of the series. The stationarity of the time series allows for better forecasting. The Akaike information criterion was used to select the best model. Recommendations for a rea-sonable selection of parameters for adjusting ARIMA models are obtained. The dependence of the settings on the category of annual data set is shown. Conclusion. After processing the data, four categories (patterns) of year data sets were identified. Depending on the category ranges of parame-ters were selected for tuning ARIMA models. The suggested ranges will allow to determine the starting parameters for exploring similar datasets. Recommendations for improving the quality of post-forecast and forecast using the ARIMA model by adjusting the settings are given.

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