Big data analytics and COVID-19: investigating the relationship between government policies and cases in Poland, Turkey and South Korea

Abstract

We used big data analytics for exploring the relationship between government response policies, human mobility trends and numbers of coronavirus disease 2019 (COVID-19) cases comparatively in Poland, Turkey and South Korea. We collected daily mobility data of retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential areas. For quantifying the actions taken by governments and making a fairness comparison between these countries, we used stringency index values measured with the ‘Oxford COVID-19 government response tracker’. For the Turkey case, we also developed a model by implementing the multilayer perceptron algorithm for predicting numbers of cases based on the mobility data. We finally created scenarios based on the descriptive statistics of the mobility data of these countries and generated predictions on the numbers of cases by using the developed model. Based on the descriptive analysis, we pointed out that while Poland and Turkey had relatively closer values and distributions on the study variables, South Korea had more stable data compared to Poland and Turkey. We mainly showed that while the stringency index of the current day was associated with mobility data of the same day, the current day’s mobility was associated with the numbers of cases 1 month later. By obtaining 89.3% prediction accuracy, we also concluded that the use of mobility data and implementation of big data analytics technique may enable decision-making in managing uncertain environments created by outbreak situations. We finally proposed implications for policymakers for deciding on the targeted levels of mobility to maintain numbers of cases in a manageable range based on the results of created scenarios.

Big data analytics and the effects of government restrictions and prohibitions in the COVID-19 pandemic on emergency department sustainable operations

“…From these findings, it is concluded that the restrictions and prohibitions imposed by the government in coping with COVID-19 have had significant impacts on the management of ED operations. This result is in line with the existing studies (Akter & Wamba, 2019 ; Haldane & Morgan, 2021 ; Sözen et al, 2022 ). Our findings contribute to the literature by investigating the effects of system dynamics-related and government-imposed actions together and comparatively for different operations of EDs.…”

“…However, we aimed to identify the impacts of policy-based factors on ED operations by adopting our model into a case study representing the overcrowding of ED environments and frequently unnecessary ED visits. This result supports the existing studies reporting decreased patient volumes due to the governmental actions taken in fighting COVID-19 (Kendzerska et al, 2021 ; Sözen et al, 2022 ). It also enhances literature by considering this effect in developing prediction models for patient volumes, average stay lengths of patients, and resource utilization of EDs during this pandemic period.…”

“…Moreover, big data and BDA implementations in real-time systems will have great importance in providing sustainable ED operations (Das et al, 2021 ; Goli et al, 2019 , 2021 ; Midya et al, 2021 ; Mondal & Roy, 2022 ). Having such capabilities and advantages, BDA has attracted researchers, decision, and policymakers in coping with COVID-19 as a current global emergency (Abdel-Basset et al, 2021 ; Bag et al, 2021 ; Huang et al, 2020 ; Kapoor et al, 2021 ; Lee & Trimi, 2021 ; Mondal & Roy, 2021 ; Papadopoulos et al, 2020 ; Sharma et al, 2020 ; Sözen et al, 2022 ; Tirkolaee et al, 2022 ).…”

Fiscal responses to COVID-19 outbreak for healthy economies: Modelling with big data analytics

“…This raises the question of whether these fiscal measures can be used as useful indicators of the spread of COVID-19. The most commonly used statistics in the literature are either unstandardized or standardized measures of COVID-19 cases and deaths, whereby unstandardized variables are placed on the same scale to allow comparisons ( Sözen, Sarıyer & Ataman, 2022 ). Another critical statistic for measuring a country's success in fighting the pandemic is the case-fatality ratio, defined as the ratio of COVID-19-related deaths to confirmed COVID-19 cases (Ivanda et al, 2021; Spychalski, Błażyńska-Spychalska & Kobiela, 2020 ).…”

Event Study Design for Modeling Early Relaxation in Turkish Public with COVID-19 Vaccine

“…1 In fighting against the pandemic, there exist tremendous worldwide efforts to keep the spread of the virus under control and protect the functioning of health systems. 2,3 Mask-wearing and stay-at-home campaigns and obligations, travel bans, school and work closures, entertainment place closures, and so on, are just a few of the policies taken by governments in managing the pandemic environment.…”