A city cluster risk-based approach for Sars-CoV-2 and isolation barriers based on anonymized mobile phone users' location data

By employing the city-level data from China during the spring of 2020, this study investigates the relationship between city-level resilience against the outbreak of COVID-19 pandemics and its affecting factors, including the inflow risk pressure of COVID-19 virus (population inflow from the epicenter), city agglomeration characteristics (urban population density and city size), healthcare resource adequacy, among others. The results reveal that, while managing COVID-19 inflow risk pressure plays a critical role in the city’s pandemic disaster resilience. city agglomeration characteristics also matters. To be exact, we find that large and high-density cities with high inter and intra-city mobility flows have more difficulties in containing the epidemic spread, but improving healthcare infrastructure adequacy and urban governance capacity can increase time efficacy of pandemic control and then improve the city’s resilience against pandemic. Although our analysis is based on the performance of Chinese cities in the case of COVID-19, the research framework can be applied in understanding COVID-19 control performance of cities in other countries and the findings can be useful for improving health-related urban resilience and sustainability.

Section: Empirical Results and Discussionmentioning

confidence: 99%

What determines city’s resilience against epidemic outbreak: evidence from China’s COVID-19 experience

Chen¹,

Guo

Pan³

et al. 2021

“…Moreover, no study reported how the proximity/location accuracy may affect the effectiveness of digital contact tracing, a significant literature gap. However, the digital contact tracing efficiency is directly linked to how the proximity is determined and how data are retrieved, processed, and stored ( Silva et al, 2021 ). On this account, more focus should be placed on the joint analysis of the technological and epidemiological components of a digital contact tracing system.…”

Section: Discussionmentioning

confidence: 99%

Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review

Grekousis

Liu

2021

Digital contact tracing provides an expeditious and comprehensive way to collect and analyze data on people’s proximity, location, movement, and health status. However, this technique raises concerns about data privacy and its overall effectiveness. This paper contributes to this debate as it provides a systematic review of digital contact tracing studies between January 1, 2020, and March 31, 2021. Following the PRISMA protocol for systematic reviews and the CHEERS statement for quality assessment, 580 papers were initially screened, and 19 papers were included in a qualitative synthesis. We add to the current literature in three ways. First, we evaluate whether digital contact tracing can mitigate COVID-19 by either reducing the effective reproductive number or the infected cases. Second, we study whether digital is more effective than manual contact tracing. Third, we analyze how proximity/location awareness technologies affect data privacy and population participation. We also discuss proximity/location accuracy problems arising when these technologies are applied in different built environments (i.e., home, transport, mall, park). This review provides a strong rationale for using digital contact tracing under specific requirements. Outcomes may inform current digital contact tracing implementation efforts worldwide regarding the potential benefits, technical limitations, and trade-offs between effectiveness and privacy.

“…We address this limitation by using anonymized mobile phone movement data from SafeGraph. Recent research has similarly used mobile phone data to highlight mobility patterns during the pandemic to identify the effectiveness of control measures, social distancing, and isolation ( Aleta et al., 2020 ; Pepe et al., 2020 ; ( Silva et al., 2021 )). Illinois also instituted a stay-at-home order on March 20 and closed all public and private schools on March 13, which decreases the possibility of any significant rise of cases due to people infected with the virus moving into the city.…”

Section: Methodsmentioning

confidence: 99%

“…However, limited research explores how these factors affected COVID-19 cases over time or how study time-periods may influence the findings. Mobility patterns at the local level are also not considered in most studies, although studies at broader geographic level (e.g., County or city level) showed the significance of mobility on COVID-19 transmission ( Badr et al., 2020 ; ( Silva et al., 2021 )). This study aims to fill these research gaps while highlighting the importance of considering social vulnerability at different stages in COVID-19 recovery strategies.…”

Section: Planning Disease Spread and Social Vulnerabilitymentioning

confidence: 99%

Exploring the nexus between social vulnerability, built environment, and the prevalence of COVID-19: A case study of Chicago

Kashem

Baker

González

et al. 2021

COVID-19 has significantly and unevenly impacted the United States, disproportionately affecting socially vulnerable communities. While epidemiologists and public health officials have suggested social distancing and shelter-in-place orders to halt the spread of this virus, the ability to comply with these guidelines is dependent on neighborhood, household, and individual characteristics related to social vulnerability. We use structural equation modeling and multiple data sources, including anonymized mobile phone location data from SafeGraph, to examine the effects of different social vulnerability and built environment factors on COVID-19 prevalence over two overlapping time periods (March to May and March to November of 2020). We use Chicago, Illinois as a case study and find that zip codes with low educational attainment consistently experienced higher case rates over both periods. Though population density was not significantly related to the prevalence in any period, movement of people made a significant contribution only during the longer time period. This finding highlights the significance of analyzing different timeframes for understanding social vulnerability. Our results suggest social vulnerability played an influential role in COVID-19 prevalence, highlighting the needs to address socioeconomic barriers to pandemic recovery and future pandemic response.