The Impact of Mobility Restriction Strategies in the Control of the COVID-19 Pandemic: Modelling the Relation between COVID-19 Health and Community Mobility Data

Wahaibi, Adil Al; Maani, Amal Al; Alyaquobi, Fatma; Manji, Abdullah Al; Harthy, Khalid Al; Rawahi, Bader Al; Alqayoudhi, Abdullah; Khalili, Sulien Al; Al-Jardani, Amina; Al-Abri, Seif

doi:10.3390/ijerph181910560

Cited by 9 publications

(9 citation statements)

References 29 publications

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“…This finding underscores the influence of curfews on transportation patterns and highlights their effectiveness in controlling mobility. Some studies have found that imposing curfew was effective in altering the spread of COVID-19 epidemic ( 33 – 35 ). This study also reveals the significant impact of public transportation on the movement of people within the country.…”

Section: Discussionmentioning

confidence: 99%

The impact of public transportation on the transmission of COVID-19 in Rwanda

Umutoni,

Tumushime,

Hewins

et al. 2024

Front. Public Health

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IntroductionThe onset of the COVID-19 pandemic has placed a significant burden on healthcare systems worldwide, particularly in sub-Saharan regions where healthcare resources are limited. The transmission of SARS-CoV-2 is facilitated by the movement of people from place to place. Therefore, implementing measures that restrict movement of people and contacts is crucial in controlling the spread of the disease. Following the identification of the first COVID-19 case in Rwanda, the government implemented stringent measures, including a complete nationwide lockdown, border closures, curfews, reduced capacity in public transportation and businesses, and mandatory testing. This study aims to assess epidemiological trends in COVID-19 cases in relation to changes in population mobility within the public transportation system.MethodsA descriptive analysis using publicly available data on COVID-19 epidemiological indicators (cases, deaths, vaccinations, and stringency index) and mobility data was conducted.ResultsThe results reveal a strong correlation between mobility in public transportation and other activities, underscoring Rwanda’s reliance on its public transportation system. The study also identifies a pattern where increases in transit station mobility preceded spikes in COVID-19 cases, suggesting that the subsequent rise in public transportation usage may contribute to higher infection rates.DiscussionTherefore, this study emphasizes the importance of ongoing vigilance and regulatory measures regarding public transportation during infectious disease outbreaks.

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Section: Discussionmentioning

confidence: 99%

The impact of public transportation on the transmission of COVID-19 in Rwanda

Umutoni,

Tumushime,

Hewins

et al. 2024

Front. Public Health

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“…Similarly, the possibility of the same suburb having more infected patients will increase if it has direct road connections with suburbs with many COVID-19-infected patients. Controlling human mobility is challenging at the inter-suburban level; even strict lockdowns or curfews will be in place 23 , 24 .…”

Section: Our Approachmentioning

confidence: 99%

Road networks and socio-demographic factors to explore COVID-19 infection during its different waves

Uddin,

Khan,

et al. 2024

Sci Rep

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The COVID-19 pandemic triggered an unprecedented level of restrictive measures globally. Most countries resorted to lockdowns at some point to buy the much-needed time for flattening the curve and scaling up vaccination and treatment capacity. Although lockdowns, social distancing and business closures generally slowed the case growth, there is a growing concern about these restrictions' social, economic and psychological impact, especially on the disadvantaged and poorer segments of society. While we are all in this together, these segments often take the heavier toll of the pandemic and face harsher restrictions or get blamed for community transmission. This study proposes a road-network-based networked approach to model mobility patterns between localities during lockdown stages. It utilises a panel regression method to analyse the effects of mobility in transmitting COVID-19 in an Australian context, together with a close look at a suburban population’s characteristics like their age, income and education. Firstly, we attempt to model how the local road networks between the neighbouring suburbs (i.e., neighbourhood measure) and current infection count affect the case growth and how they differ between delta and omicron variants. We use a geographic information system, population and infection data to measure road connections, mobility and transmission probability across the suburbs. We then looked at three socio-demographic variables: age, education and income and explored how they moderate independent and dependent variables (infection rates and neighbourhood measures). The result shows strong model performance to predict infection rate based on neighbourhood road connection. However, apart from age in the delta variant context, the other variables (income and education level) do not seem to moderate the relationship between infection rate and neighbourhood measure. The results indicate that suburbs with a more socio-economically disadvantaged population do not necessarily contribute to more community transmission. The study findings could be potentially helpful for stakeholders in tailoring any health decision for future pandemics.

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“…Similarly, the possibility for the same suburb to have a higher number of infected patients will increase if it has direct road connections with suburbs with many COVID-19 infected patients. It would be difficult to control human mobility entirely at the inter suburban level; even strict lockdown or curfew will be in place (Zhou et al, 2020, Al Wahaibi et al, 2021.…”

Section: Our Approachmentioning

confidence: 99%

Road networks to explore COVID-19 infection

Uddin

Khan

et al. 2023

Preprint

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COVID-19 pandemic triggered an unprecedented level of restrictive measures globally. Most countries resorted to lockdowns at some point to buy the much-needed time for flattening the curve and scaling up vaccination and treatment capacity. Although lockdowns, social distancing and business closures generally slowed down the case growth, there is a growing concern about the social, economic and psychological impact of these restrictions, especially on the disadvantaged and poorer part of society. While we are all in this together, these segments are often taking the heavier toll of the pandemic and facing harsher restrictions or getting blamed for community transmission. This study tries to explore this perspective using quantitative analysis and network theory. The research is set in the context of the latest delta and omicron outbreaks in the Greater Sydney area, Australia, during late 2021. We first try to model how the local road networks between the neighbouring suburbs (i.e., neighbourhood measure) and current infection count affect the case growth and how they differ between delta and omicron variants. We use a geographic information system, population and infection data to measure road connections, mobility and transmission probability across the suburbs. We then looked at three socio-demographic variables: age, education and income and explored how they moderate independent and dependent variables (infection rates and neighbourhood measures). The result shows strong model performance to predict infection rate based on neighbourhood road connection. However, apart from age in the delta variant context, the other two variables (income and education level) do not seem to moderate the relation between infection rate and neighbourhood measure. The results indicate that suburbs with a more socio-economically disadvantaged population do not necessarily contribute to more community transmission. The study findings could be potentially helpful for stakeholders in tailoring any health decision for future pandemics.

show abstract

The Impact of Mobility Restriction Strategies in the Control of the COVID-19 Pandemic: Modelling the Relation between COVID-19 Health and Community Mobility Data

Cited by 9 publications

References 29 publications

The impact of public transportation on the transmission of COVID-19 in Rwanda

The impact of public transportation on the transmission of COVID-19 in Rwanda

Road networks and socio-demographic factors to explore COVID-19 infection during its different waves

Road networks to explore COVID-19 infection

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