scholarly journals Time Series Analysis as a Tool To Predict the Impact of Antimicrobial Restriction in Antibiotic Stewardship Programs Using the Example of Multidrug-Resistant Pseudomonas aeruginosa

2013 ◽  
Vol 57 (4) ◽  
pp. 1797-1803 ◽  
Author(s):  
Matthias Willmann ◽  
Matthias Marschal ◽  
Florian Hölzl ◽  
Klaus Schröppel ◽  
Ingo B. Autenrieth ◽  
...  
Keyword(s):  
Time Series ◽  
Pseudomonas Aeruginosa ◽  
Time Series Analysis ◽  
Antibiotic Stewardship ◽  
Multidrug Resistant ◽  
Antimicrobial Consumption ◽  
Content Type ◽  
Series Analysis ◽  
Resistance Rates ◽  
The Impact

ABSTRACTThe association between antimicrobial consumption and resistance in nonfermentative Gram-negative bacteria is well-known. Antimicrobial restriction, implemented in clinical routines by antibiotic stewardship programs (ASPs), is considered a means to reduce resistance rates. Whether and how antimicrobial restriction can accomplish this goal is still unknown though. This leads to an element of uncertainty when designing strategies for ASPs. From January 2002 until December 2011, an observational study was performed at the University Hospital Tübingen, Tübingen, Germany, to investigate the association between antimicrobial use and resistance rates inPseudomonas aeruginosa. Transfer function models were used to determine such associations and to simulate antimicrobial restriction strategies. Various positive associations between antimicrobial consumption and resistance were observed in our setting. Surprisingly, impact estimations of different antimicrobial restriction strategies revealed relatively low intervention expenses to effectively attenuate the observed increase in resistance. For example, a simulated intervention of an annual 4% reduction in the use of meropenem over 3 years from 2009 until 2011 yielded a 62.5% attenuation (95% confidence interval, 15% to 110%) in the rising trend of multidrug-resistantPseudomonas aeruginosa(three- and four-class-resistantP. aeruginosa[34MRGN-PA]). Time series analysis models derived from past data may be a tool to predict the outcome of antimicrobial restriction strategies, and could be used to design ASPs.

Impact of COVID-19 lockdown on prices of potato and onion in metropolitan cities of India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kuldeep Rajpoot ◽  
Saurav Singla ◽  
Abhishek Singh ◽  
Shashi Shekhar
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Moving Average ◽  
Extensive Study ◽  
Series Data ◽  
Content Type ◽  
Analysis Techniques ◽  
Series Analysis ◽  
Price Series ◽  
The Impact

PurposeThis study focuses on accessing the impact of lockdown implemented to curb the pandemic of coronavirus disease 2019 (COVID-19) on prices of potato and onion crops using the time series analysis techniques.Design/methodology/approachThe present study uses secondary price series data for both crops. Along with the study of percent increase or decrease, the time series analysis techniques of autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH), as well as machine learning; neural network autoregressive (NNAR) models were used to model the prices. For the purpose of comparison, the data from past years were taken as the period of normalcy. The behaviour of the forecasts for the normal periods and during the pandemic based on respective datasets was compared.FindingsThe results show that there was an unprecedented rise in prices during the months of lockdown. It could be attributed to the decline in arrivals due to several reasons like issues with transportation and labour availability. Also, towards the end of lockdown (May 2020), the prices seemed to decrease. Such a drop could be attributed to the relaxations in lockdown and reduced demand. The study also discusses that how some unique approaches like e-marketing, localized resource development for attaining self-sufficiency and developing transport chain, especially, for agriculture could help in such a situation of emergency.Research limitations/implicationsA more extensive study could be conducted to mark the factors specifically that caused the increase in price.Originality/valueThe study clearly marks that the prices of the crops increased more than expectations using time series methods. Also, it surveys the prevailing situation through available resources to link up the reasons behind it.

scholarly journals Impact of Generic Entry on Hospital Antimicrobial Use: A Retrospective Quasi-Experimental Interrupted Time Series Analysis

Antibiotics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1149
Author(s):  
Mercè Espona ◽  
Daniel Echeverria-Esnal ◽  
Sergi Hernandez ◽  
Alexander Almendral ◽  
Silvia Inés Gómez-Zorrilla ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Economic Benefit ◽  
Interrupted Time Series ◽  
Antimicrobial Consumption ◽  
Interrupted Time Series Analysis ◽  
Generic Entry ◽  
Series Analysis ◽  
Quasi Experimental ◽  
The Impact

Background: The impact of antimicrobials generic entry (GE) is controversial. Their introduction could provide an economic benefit yet may also increase their consumption, leading to a higher risk of resistance. Our aim was to analyze the impact of GE on trends of antimicrobial consumption in an acute-care hospital. Methods: A retrospective quasi-experimental interrupted time series analysis was conducted at a 400-bed tertiary hospital in Barcelona, Spain. All antimicrobials for systemic use for which a generic product entered the hospital from January 2000 to December 2019 were included. Antimicrobial consumption was expressed as DDD/100 bed days. Results: After GE, the consumption of cefotaxime (0.09, p < 0.001), meropenem (0.54, p < 0.001), and piperacillin-tazobactam (0.13, p < 0.001) increased, whereas the use of clindamycin (−0.03, p < 0.001) and itraconazole (−0.02, p = 0.01) was reduced. An alarming rise in cefepime (0.004), daptomycin (1.02), and cloxacillin (0.05) prescriptions was observed, despite not achieving statistical significance. On the contrary, the use of amoxicillin (−0.07), ampicillin (−0.02), cefixime (−0.06), fluconazole (−0.13), imipenem–cilastatin (−0.50) and levofloxacin (−0.35) decreased. These effects were noticed beyond the first year post GE. Conclusions: GE led to an increase in the consumption of broad-spectrum molecules. The potential economic benefit of generic antibiotics could be diluted by an increase in resistance. Antimicrobial stewardship should continue to monitor these molecules despite GE.

scholarly journals Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanne Martin ◽  
Edwin Amalraj Raja ◽  
Steve Turner
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Emergency Admission ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Emergency Admissions ◽  
Series Analysis ◽  
Inpatient Services ◽  
The Impact ◽  
Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

Recession and risk of suicide in Denmark during the 2009 global financial crisis: an ecological register-based study

2021 ◽  
pp. 140349482110132
Author(s):  
Agnieszka Konieczna ◽  
Sarah Grube Jakobsen ◽  
Christina Petrea Larsen ◽  
Erik Christiansen
Keyword(s):  
Time Series ◽  
Financial Crisis ◽  
Time Series Analysis ◽  
Suicide Rate ◽  
Global Financial Crisis ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Prevention Programmes ◽  
The Impact

Aim: The aim of this study is to analyse the potential impact from the financial crisis (onset in 2009) on suicide rates in Denmark. The hypothesis is that the global financial crisis raised unemployment which leads to raising the suicide rate in Denmark and that the impact is most prominent in men. Method: This study used an ecological study design, including register data from 2001 until 2016 on unemployment, suicide, gender and calendar time which was analysed using Poisson regression models and interrupted time series analysis. Results: The correlation between unemployment and suicide rates was positive in the period and statistically significant for all, but at a moderate level. A dichotomised version of time (calendar year) showed a significant reduction in the suicide rate for women (incidence rate ratio 0.87, P=0.002). Interrupted time series analysis showed a significant decreasing trend for the overall suicide rate and for men in the pre-recession period, which in both cases stagnated after the onset of recession in 2009. The difference between the genders’ suicide rate changed significantly at the onset of recession, as the rate for men increased and the rate for women decreased. Discussion: The Danish social welfare model might have prevented social disintegration and suicide among unemployed, and suicide prevention programmes might have prevented deaths among unemployed and mentally ill individuals. Conclusions: We found some indications for gender-specific differences from the impact of the financial crises on the suicide rate. We recommend that men should be specifically targeted for appropriate prevention programmes during periods of economic downturn.

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

Vaccines ◽  
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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