Analysis of the impact of COVID-19 on collisions, fatalities and injuries using time series forecasting: The case of Greece

被引:49
|
作者
Sekadakis, Marios [1 ]
Katrakazas, Christos [1 ]
Michelaraki, Eva [1 ]
Kehagia, Fotini [2 ]
Yannis, George [1 ]
机构
[1] Natl Tech Univ Athens, Dept Transportat Planning & Engn, 5 Heroon Polytech Str, GR-15773 Athens, Greece
[2] Aristotle Univ Thessaloniki, Sch Civil Engn, Div Transportat & Construct Management, Highway Lab, Thessaloniki 54124, Greece
来源
ACCIDENT ANALYSIS AND PREVENTION | 2021年 / 162卷 / 162期
关键词
COVID-19; Road collisions; Road Safety; Fatalities; Injuries; Time Series; TRAFFIC FATALITIES; SPEED LIMITS;
D O I
10.1016/j.aap.2021.106391
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
The current study aims to investigate the impact of the COVID-19 pandemic on road traffic collisions, fatalities, and injuries using time series analyses. To that aim, a database containing road collisions, fatalities, and slight injuries data from Greece were derived from the Hellenic Statistical Authority (HSA) and covered a ten-year timeframe (from January 2010 to August 2020. The chosen time period contained normal operations, as well as the period of the first COVID-19-induced lockdown period in Greece. Three different Seasonal Autoregressive Integrated Moving Average (SARIMA) time series models were implemented in order to compare the observed measurements to forecasted values that were intended to depict assumed conditions; namely, without the appearance of the COVID-19 pandemic. Modelling results revealed that the total number of road collisions, fatalities, and slightly injured were decreased, mainly due to the sharp traffic volume decrease. However, the percentage reduction of the collision variables and traffic volume were found to be disproportionate, which probably indicates that more collisions occurred with regard to the prevailing traffic volume. An additional finding is that fatalities and slightly injured rates were significantly increased during the lockdown period and the subsequent month. Overall, it can be concluded that a worse performance was identified in terms of road safety. Since subsequent waves of COVID-19 cases and other pandemics may reappear in the future, the outcomes of the current study may be exploited for the improvement of road safety from local authorities and policymakers.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Analysis and Prediction of COVID-19 using Regression Models and Time Series Forecasting
    Shaikh, Saud
    Gala, Jaini
    Jain, Aishita
    Advani, Sunny
    Jaidhar, Sagar
    Edinburgh, Mani Roja
    2021 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2021), 2021, : 989 - 995
  • [2] Forecasting of Covid-19 Using Time Series Regression Models
    Radwan, Akram M.
    2021 PALESTINIAN INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (PICICT 2021), 2021, : 7 - 12
  • [3] Analysis and Forecasting Covid-19 Spread in India using Logistic Regression and Prophet Time Series
    Verghese, Ashok
    Sudalaimuthu, T.
    Visalaxi, S.
    2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2021), 2021, : 928 - 932
  • [4] Time Series Forecasting of US COVID-19 Transmission
    Ding, Yongmei
    Huang, Rui
    Shao, Ningyi
    ALTERNATIVE THERAPIES IN HEALTH AND MEDICINE, 2021, 27 : 4 - 11
  • [5] A Time Series Forecast of COVID-19 Infections, Recoveries and Fatalities in Nigeria
    Inegbedion, Henry Egbezien
    SUSTAINABILITY, 2023, 15 (09)
  • [6] Forecasting the Trends of Covid-19 and Causal Impact of Vaccines Using Bayesian Structural time Series and ARIMA
    Navas Thorakkattle M.
    Farhin S.
    khan A.A.
    Annals of Data Science, 2022, 9 (05) : 1025 - 1047
  • [7] Impact of COVID-19 pandemic on road traffic injuries in Iran: An interrupted time-series analysis
    Kolivand, Pirhossein
    Saberian, Peyman
    Arabloo, Jalal
    Behzadifar, Masoud
    Karimi, Fereshteh
    Rajaie, Soheila
    Moradipour, Morteza
    Parvari, Arash
    Azari, Samad
    PLOS ONE, 2024, 19 (06):
  • [8] Impact of mobility on COVID-19 spread - A time series analysis
    Zargari, Faraz
    Aminpour, Nima
    Ahmadian, Mohammad Amir
    Samimi, Amir
    Saidi, Saeid
    TRANSPORTATION RESEARCH INTERDISCIPLINARY PERSPECTIVES, 2022, 13
  • [9] Time series forecasting of COVID-19 transmission in Canada using LSTM networks
    Chimmula, Vinay Kumar Reddy
    Zhang, Lei
    CHAOS SOLITONS & FRACTALS, 2020, 135
  • [10] A time series-based statistical approach for outbreak spread forecasting: Application of COVID-19 in Greece
    Katris, Christos
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 166