scholarly journals The Impact of Liquor Restrictions on Serious Assaults across Queensland, Australia

2019 ◽  
Vol 16 (22) ◽  
pp. 4362 ◽  
Author(s):  
Nicholas Taylor ◽  
Kerri Coomber ◽  
Richelle Mayshak ◽  
Renee Zahnow ◽  
Jason Ferris ◽  
...  
Keyword(s):  
Public Perception ◽  
Moving Average ◽  
Cumulative Impact ◽  
Autoregressive Integrated Moving Average ◽  
Times Series ◽  
Average Analysis ◽  
The Impact ◽  
Alcohol Related Harm ◽  
The Relationship ◽  
Related Harm

Aims: This study aimed to explore the relationship between a 00:00 liquor restriction, introduced on 1 July 2016, and alcohol-related harm by examining its impact on serious assault numbers during high-alcohol hours (20:00–6:00 Friday and Saturday night), from 1 January 2009 to 30 June 2018. Methods: Two types of locations only impacted by the liquor restriction were identified: designated safe night precincts (SNPs) and other local government areas (LGAs). A times series autoregressive integrated moving average analysis was used to estimate the influence of liquor restrictions on police-recorded serious assaults in the two years following the policy introduction, for SNPs and LGAs separately. Results: Contrarily to our predictions, monthly police-recorded serious assaults did not significantly change within SNPs or LGAs following the introduction of liquor restrictions. Conclusion: The implementation of the Queensland liquor restriction did not result in a clear, unique reduction in serious assault trends. Further investigation should consider the impact of liquor restrictions in conjunction with other policy changes as public perception of restrictions and their cumulative impact may produce varied outcomes.

Alcohol-related harm and health inequalities

2017 ◽  
Author(s):  
Katherine Smith ◽  
Jon Foster ◽  
Katherine Brown
Keyword(s):  
Health Inequalities ◽  
Welfare Spending ◽  
Younger Women ◽  
Disadvantaged Groups ◽  
Unit Pricing ◽  
The Impact ◽  
Alcohol Related Harm ◽  
The Relationship ◽  
Related Harm

This chapter examines the relationship between alcohol use and health inequalities. It first reviews the evidence and theories concerning health inequalities in morbidity and mortality as well as evidence and theories that specifically relate to the role of alcohol within these broader inequalities. The available evidence suggests that alcohol-related harms follow the expected social gradient; greater harms are suffered by more disadvantaged groups, at least for men and for younger women. However, some statistics indicate that people living in deprived communities consume less alcohol than more advantaged communities. The chapter analyses potential explanations for this apparent tension, often referred to as the alcohol harm paradox, along with evidence concerning the impact of alcohol-related interventions, such as minimum unit pricing (MUP), Reducing the Strength (RTS) schemes and welfare spending, on inequalities. It concludes with a range of relevant research and policy recommendations.

Intervention Modeling

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Moving Average ◽  
Intervention Model ◽  
Noise Component ◽  
Autoregressive Integrated Moving Average ◽  
Noise Function ◽  
Modeling Strategy ◽  
The Impact ◽  
True Structure

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.

scholarly journals Relationship between Changes over Time in Factors, Including the Impact of Meteorology on Photochemical Oxidant Concentration and Causative Atmospheric Pollutants in Kawasaki

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 446
Author(s):  
Akinori Fukunaga ◽  
Takaharu Sato ◽  
Kazuki Fujita ◽  
Daisuke Yamada ◽  
Shinya Ishida ◽  
...  
Keyword(s):  
Moving Average ◽  
Atmospheric Pollutants ◽  
Important Indicator ◽  
Photochemical Oxidant ◽  
Oxidant Concentration ◽  
Using Data ◽  
Changes Over Time ◽  
The Impact ◽  
The Relationship ◽  
The City

To clarify the relationship between changes in photochemical oxidants’ (Ox) concentrations and their precursors in Kawasaki, a series of analyses were conducted using data on Ox, their precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), and meteorology that had been monitored throughout the city of Kawasaki for 30 years from 1990 to 2019. The trend in air temperature was upward, wind speed was downward, and solar radiation was upward, indicating an increasing trend in meteorological factors in which Ox concentrations tend to be higher. Between 1990 and 2013, the annual average Ox increased throughout Kawasaki and remained flat after that. The three-year moving average of the daily peak increased until 2015, and after that, it exhibited a slight decline. The amount of generated Ox is another important indicator. To evaluate this, a new indicator, the daytime production of photochemical oxidant (DPOx), was proposed. DPOx is defined by daytime averaged Ox concentrations less the previous day’s nighttime averaged Ox concentrations. The trend in DPOx from April to October has been decreasing since around 2006, and it was found that this indicator reflects the impact of reducing emissions of NOx and VOCs in Kawasaki.

scholarly journals Estimating COVID-19 cases in Makkah region of Saudi Arabia: Space-time ARIMA modeling

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250149
Author(s):  
Fuad A. Awwad ◽  
Moataz A. Mohamoud ◽  
Mohamed R. Abonazel
Keyword(s):  
Saudi Arabia ◽  
Moving Average ◽  
Arima Model ◽  
Daily Basis ◽  
World Health ◽  
Arima Models ◽  
Autoregressive Integrated Moving Average ◽  
First Case ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus COVID-19 is spreading across the globe. By 30 Sep 2020, the World Health Organization (WHO) announced that the number of cases worldwide had reached 34 million with more than one million deaths. The Kingdom of Saudi Arabia (KSA) registered the first case of COVID-19 on 2 Mar 2020. Since then, the number of infections has been increasing gradually on a daily basis. On 20 Sep 2020, the KSA reported 334,605 cases, with 319,154 recoveries and 4,768 deaths. The KSA has taken several measures to control the spread of COVID-19, especially during the Umrah and Hajj events of 1441, including stopping Umrah and performing this year’s Hajj in reduced numbers from within the Kingdom, and imposing a curfew on the cities of the Kingdom from 23 Mar to 28 May 2020. In this article, two statistical models were used to measure the impact of the curfew on the spread of COVID-19 in KSA. The two models are Autoregressive Integrated Moving Average (ARIMA) model and Spatial Time-Autoregressive Integrated Moving Average (STARIMA) model. We used the data obtained from 31 May to 11 October 2020 to assess the model of STARIMA for the COVID-19 confirmation cases in (Makkah, Jeddah, and Taif) in KSA. The results show that STARIMA models are more reliable in forecasting future epidemics of COVID-19 than ARIMA models. We demonstrated the preference of STARIMA models over ARIMA models during the period in which the curfew was lifted.

scholarly journals Effectiveness and Forecasting of Interest Rate Reversal BI 7-Day Repo Rate in Indonesia: Lower Bound on Monetary Policy?

2018 ◽  
Vol 9 (1) ◽  
pp. 171-180
Author(s):  
I Gede Sanica ◽  
I Ketut Nurcita ◽  
I Made Mastra ◽  
Desak Made Sukarnasih
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Time Series Data ◽  
Moving Average ◽  
Series Data ◽  
Autoregressive Integrated Moving Average ◽  
Implementation Of Monetary Policy ◽  
Repo Rate ◽  
The Right ◽  
The Impact

AbstractThis study aims to analyze effectivity and forecast of interest rate BI 7-Day Repo Rate as policy reference in the implementation of monetary policy. The method was used in this study contains Vector Autoregression (VAR) to estimate effectivity of BI 7-Day Repo Rate and Autoregressive Integrated Moving Average (ARIMA) to forecast of BI 7-Day Repo Rate. Period of observation in this study used time series data during 2016.4 until 2017.6. The result of this research shows that the transformation of the BI Rate to BI 7-Day Repo Rate is the right step in the monetary policy operation in the effort to reach deepening of the financial market and strengthen the interbank money market structure so that it will decrease loan interest rate and encourage credit growth. The effectiveness of the use of BI 7 Day-Repo Rate on price stability is indicated by the positive relationship between the benchmark interest rate and inflation compared to the BI Rate. The impact of BI 7-Day Repo Rate on economic growth that tends to be positive. Forecasting the use of BI 7-Day Repo Rate shows good results with declining value levels, so this will encourage deepening the financial markets.

Estimating the Impact of Non-pharmaceutical Interventions Against COVID-19 on Mumps Incidence in Sichuan, China

2021 ◽  
Author(s):  
Wenqiang Zhang ◽  
Rongsheng Luan
Keyword(s):  
Public Health ◽  
Respiratory Virus ◽  
Moving Average ◽  
Sarima Model ◽  
Potential Reduction ◽  
Autoregressive Integrated Moving Average ◽  
Health Measures ◽  
Virus Incidence ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Background: A series of social and public health measures have been implemented to contain coronavirus disease 2019 (COVID-19) in China. We examined the impact of non-pharmaceutical interventions against COVID-19 on mumps incidence as an agent to determine the potential reduction in other respiratory virus incidence.Methods: We modelled mumps incidence per month in Sichuan using a seasonal autoregressive integrated moving average (SARIMA) model, based on the reported number of mumps cases per month from 2017-2020. Results: The epidemic peak of mumps in 2020 is lower than in the preceding years. Whenever compared with the projected cases or the average from corresponding periods in the preceding years (2017-2019), the reported cases in 2020 markedly declined (P<0.001). From January to December, the number of mumps cases was estimated to decrease by 36.3% (33.9% - 38.8%), 34.3% (31.1% - 37.8%), 68.9% (66.1% - 71.6%), 76.0% (73.9% - 77.9%), 67.0% (65.0% - 69.0%), 59.6% (57.6% - 61.6%), 61.1% (58.8% - 63.3%), 49.2% (46.4% - 52.1%), 24.4% (22.1% - 26.8%), 30.0% (27.5% - 32.6%), 42.1% (39.6% - 44.7%), 63.5% (61.2% - 65.8%), respectively. The total number of mumps cases in 2020 was estimated to decrease by 53.6% (52.9% - 54.3%).Conclusion: Our study shows that non-pharmaceutical interventions against COVID-19 have had an effective impact on mumps incidence in Sichuan, China.

scholarly journals Alcohol-related harm to others in England: a cross-sectional analysis of national survey data

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e021046 ◽  
Author(s):  
Caryl Beynon ◽  
David Bayliss ◽  
Jenny Mason ◽  
Kate Sweeney ◽  
Clare Perkins ◽  
...  
Keyword(s):  
Negative Impact ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Factors Associated ◽  
Harm To Others ◽  
Using Data ◽  
Socioeconomic And Demographic Factors ◽  
The Impact ◽  
Alcohol Related Harm ◽  
Related Harm

ObjectivesTo estimate the prevalence, the frequency and the perpetrators of alcohol-related harm to others (AHTO) and identify factors associated with experiencing harm and aggressive harm.DesignCross-sectional survey.SettingEngland.ParticipantsAdults (general population) aged 16 and over.Outcome measuresPercentage of respondents who experienced harm. Socioeconomic and demographic factors associated with the outcomes. Outcomes were (1) experienced harm/did not experience harm and (2) experienced aggressive harm (physically threatened, physically hurt and forced/pressured into something sexual)/did not experience an aggressive harm (no aggressive harm plus no harm at all).ResultsData to support a response rate calculation were not collected; 96.3% of people surveyed completed the AHTO questions. The weighted sample was 4874; 20.1% (95% CI 18.9 to 21.4, N=980) reported experiencing harm in the previous 12 months and 4.6% (95% CI 4.0 to 5.4, N=225) reported experiencing an aggressive harm. Friends and strangers were the dominant perpetrators. Most harms (74.8%) occurred less than monthly. Factors associated with experiencing harm were: younger age (p<0.001), drinking harmfully/hazardously (p<0.001), white British (p<0.001 compared to other white groups and Asian groups and p=0.017 compared to black groups), having a disability (p<0.001), being educated (p<0.001 compared to no education) and living in private rented accommodation (p=0.004 compared with owned outright). Being in the family stage of life (defined as having children in the household) had significantly lower odds of harm (p=0.006 compared to being single), as did being retired (p<0.001 compared to being employed). Factors associated with experiencing an aggressive harm were similar.ConclusionsThis exploratory study, using data collected through the Alcohol Toolkit Survey, shows that AHTO affects 20.1% of the population of England. Even apparently minor harms, like being kept awake, can have a negative impact on health, while aggressive harms are clearly of concern. Using a standard methodology to measure harm across studies would be advantageous. Policies that focus on alcohol must take into consideration the impact of drinking on those other than the drinker.

scholarly journals The Impact of Lengths of Time Series on the Accuracy of the ARIMA Forecasting

2019 ◽  
Vol 4 (3) ◽  
pp. 58
Author(s):  
Lu Qin ◽  
Kyle Shanks ◽  
Glenn Allen Phillips ◽  
Daphne Bernard
Keyword(s):  
Time Series ◽  
Historical Data ◽  
Moving Average ◽  
Arima Model ◽  
Forecasting Accuracy ◽  
Autoregressive Integrated Moving Average ◽  
Enrollment Forecasting ◽  
Moving Average Model ◽  
The Impact ◽  
Practical Impact

The Autoregressive Integrated Moving Average model (ARIMA) is a popular time-series model used to predict future trends in economics, energy markets, and stock markets. It has not been widely applied to enrollment forecasting in higher education. The accuracy of the ARIMA model heavily relies on the length of time series. Researchers and practitioners often utilize the most recent - to -years of historical data to predict future enrollment; however, the accuracy of enrollment projection under different lengths of time series has never been investigated and compared. A simulation and an empirical study were conducted to thoroughly investigate the accuracy of ARIMA forecasting under four different lengths of time series. When the ARIMA model completely captured the historical changing trajectories, it provided the most accurate predictions of student enrollment with 20-years of historical data and had the lowest forecasting accuracy with the shortest time series. The results of this paper contribute as a reference to studies in the enrollment projection and time-series forecasting. It provides a practical impact on enrollment strategies, budges plans, and financial aid policies at colleges and institutions across countries.

scholarly journals Quantifying the impact of Ramadan on global raw sugar prices

2018 ◽  
Vol 11 (4) ◽  
pp. 510-528
Author(s):  
Kazi Abrar Hossain ◽  
Syed Abul Basher ◽  
A.K. Enamul Haque
Keyword(s):  
Moving Average ◽  
Global Market ◽  
Unobserved Components ◽  
Content Type ◽  
Autoregressive Integrated Moving Average ◽  
Sugar Price ◽  
Raw Sugar ◽  
Moving Average Model ◽  
Unobserved Components Model ◽  
The Impact

Purpose The purpose of this study is to quantify the impact of Ramadan on both the level and the growth of global raw sugar price. Design/methodology/approach The study uses a dummy and a fractional variable to capture Ramadan to overcome the asynchronicity of time between Ramadan fasting (which is based on the Islamic lunar calendar) and the movement in prices (which follows the Gregorian solar calendar). To capture the seasonality of sugar production, the data on sugar price span 34 years so that the Islamic calendar makes a complete cycle of the Gregorian calendar. The empirical model is estimated using both autoregressive integrated moving average model and unobserved components model. Findings The results show that monthly raw sugar prices in the global market increases by roughly 6.06 per cent (or $17.78 per metric ton) every year ahead of Ramadan. Practical implications The study illustrates the implications of the results for the consumption of imported sugar in Bangladesh. Originality/value The study uses a broader set of Ramadan indicators in its empirical models and checks the robustness of its baseline model using the unobserved components model. It also performs seasonal unit root tests on the global raw sugar prices.

scholarly journals The price of a drink: the potential of alcohol minimum unit pricing as a public health measure in the UK

2012 ◽  
Vol 201 (3) ◽  
pp. 169-171 ◽  
Author(s):  
Peter Rice ◽  
Colin Drummond
Keyword(s):  
Control Measures ◽  
The Past ◽  
Alcohol Control ◽  
Health Measure ◽  
Alcohol Taxation ◽  
Unit Pricing ◽  
The Uk ◽  
The Impact ◽  
Alcohol Related Harm ◽  
Related Harm

SummaryThe UK has seen a dramatic increase in alcohol consumption and alcohol-related harm over the past 30 years. Alcohol taxation has long been considered a key method of controlling alcohol-related harm but a combination of factors has recently led to consideration of methods which affect the price of the cheapest alcohol as a means of improved targeting of alcohol control measures to curb the consumption of the heaviest drinkers. Although much of the evidence in favour of setting a minimum price of a unit of alcohol is based on complex econometric models rather than empirical data, all jurisdictions within the UK now intend to make selling alcohol below a set price illegal, which will provide a naturalistic experiment allowing assessment of the impact of minimum pricing.

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