Investigating the two-way relationship between mobility flows and COVID-19 cases

Boto‐García, David

doi:10.1016/j.econmod.2022.106083

Cited by 7 publications

(3 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous research has shown a strong correlation between mobility and COVID-19 transmission, with a lag of about 10 days observed in China [25]. Similar patterns have been observed in Spain [26]. Therefore, in this study, we determine the effective lockdown date by monitoring the initial decline in overall mobility data.…”

Section: Data Preprocessing and Exploratory Data Analysismentioning

confidence: 57%

Unlocking Insights: Analysing COVID-19 Lockdown Policies and Mobility Data in Victoria, Australia, through a Data-Driven Machine Learning Approach

Lyu,

Adegboye,

Adhinugraha

et al. 2023

Data

View full text Add to dashboard Cite

The state of Victoria, Australia, implemented one of the world’s most prolonged cumulative lockdowns in 2020 and 2021. Although lockdowns have proven effective in managing COVID-19 worldwide, this approach faced challenges in containing the rising infection in Victoria. This study evaluates the effects of short-term (less than 60 days) and long-term (more than 60 days) lockdowns on public mobility and the effectiveness of various social restriction measures within these periods. The aim is to understand the complexities of pandemic management by examining various measures over different lockdown durations, thereby contributing to more effective COVID-19 containment methods. Using restriction policy, community mobility, and COVID-19 data, a machine-learning-based simulation model was proposed, incorporating analysis of correlation, infection doubling time, and effective lockdown date. The model result highlights the significant impact of public event cancellations in preventing COVID-19 infection during short- and long-term lockdowns and the importance of international travel controls in long-term lockdowns. The effectiveness of social restriction was found to decrease significantly with the transition from short to long lockdowns, characterised by increased visits to public places and increased use of public transport, which may be associated with an increase in the effective reproduction number (Rt) and infected cases.

show abstract

Section: Data Preprocessing and Exploratory Data Analysismentioning

confidence: 57%

Unlocking Insights: Analysing COVID-19 Lockdown Policies and Mobility Data in Victoria, Australia, through a Data-Driven Machine Learning Approach

Lyu,

Adegboye,

Adhinugraha

et al. 2023

Data

View full text Add to dashboard Cite

show abstract

“…Therefore, according to the results of this paper, public policies had an indirect effect on positivity rate through mobility. Mobility is highly related to positivity rate (Boto‐García, 2023 ).…”

Section: Discussionmentioning

confidence: 99%

Assessing the Effect of the U.S. Vaccination Program on the Coronavirus Positivity Rate With a Multivariate Framework

et al. 2023

View full text Add to dashboard Cite

The factors influencing the incidence of COVID‐19, including the impact of the vaccination programs, have been studied in the literature. Most studies focus on one or two factors, without considering their interactions, which is not enough to assess a vaccination program in a statistically robust manner. We examine the impact of the U.S. vaccination program on the SARS‐CoV‐2 positivity rate while simultaneously considering a large number of factors involved in the spread of the virus and the feedbacks among them. We consider the effects of the following sets of factors: socioeconomic factors, public policy factors, environmental factors, and non‐observable factors. A time series Error Correction Model (ECM) was used to estimate the impact of the vaccination program at the national level on the positivity rate. Additionally, state‐level ECMs with panel data were combined with machine learning techniques to assess the impact of the program and identify relevant factors to build the best‐fitting models. We find that the vaccination program reduced the virus positivity rate. However, the program was partially undermined by a feedback loop in which increased vaccination led to increased mobility. Although some external factors reduced the positivity rate, the emergence of new variants increased the positivity rate. The positivity rate was associated with several forces acting simultaneously in opposite directions such as the number of vaccine doses administered and mobility. The existence of complex interactions, between the factors studied, implies that there is a need to combine different public policies to strengthen the impact of the vaccination program.

show abstract

“…Geoepidemiological investigations have shed light on the transmission dynamics of COVID-19 pandemic, elucidating how the virus spreads within and between communities ( 98 , 99 ). By examining patterns of mobility, social interactions, and travel, researchers have quantified the impact of human behavior on virus transmission ( 100 , 101 ). Furthermore, the integration of geographic information systems (GIS) and mathematical modeling has facilitated the prediction of future outbreaks and the evaluation of the effectiveness of control measures ( 62 , 102 ).…”

Section: Introductionmentioning

confidence: 99%

Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact

Vallée

2023

Front. Public Health

View full text Add to dashboard Cite

The COVID-19 pandemic showed major impacts, on societies worldwide, challenging healthcare systems, economies, and daily life of people. Geoepidemiology, an emerging field that combines geography and epidemiology, has played a vital role in understanding and combatting the spread of the virus. This interdisciplinary approach has provided insights into the spatial patterns, risk factors, and transmission dynamics of the COVID-19 pandemic at different scales, from local communities to global populations. Spatial patterns have revealed variations in incidence rates, with urban-rural divides and regional hotspots playing significant roles. Cross-border transmission has highlighted the importance of travel restrictions and coordinated public health responses. Risk factors such as age, underlying health conditions, socioeconomic factors, occupation, demographics, and behavior have influenced vulnerability and outcomes. Geoepidemiology has also provided insights into the transmissibility and spread of COVID-19, emphasizing the importance of asymptomatic and pre-symptomatic transmission, super-spreading events, and the impact of variants. Geoepidemiology should be vital in understanding and responding to evolving new viral challenges of this and future pandemics.

show abstract

Investigating the two-way relationship between mobility flows and COVID-19 cases

Cited by 7 publications

References 66 publications

Unlocking Insights: Analysing COVID-19 Lockdown Policies and Mobility Data in Victoria, Australia, through a Data-Driven Machine Learning Approach

Unlocking Insights: Analysing COVID-19 Lockdown Policies and Mobility Data in Victoria, Australia, through a Data-Driven Machine Learning Approach

Assessing the Effect of the U.S. Vaccination Program on the Coronavirus Positivity Rate With a Multivariate Framework

Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact

Contact Info

Product

Resources

About