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1.
Environment and planning. B, urban analytics and city science ; 2022.
Article in English | EuropePMC | ID: covidwho-1877469

ABSTRACT

Since the first confirmed case was reported in January 2020, Hong Kong has experienced multiple waves of COVID-19 outbreaks. Recent literature has explored the spatial patterns of disease incidence and their relationships with the built environment and demographic characteristics. Nonetheless, few studies aim at the comparative patterns of different epidemic waves occurring in the same spatial context. This study analyses spatial patterns of the third and fourth COVID-19 epidemic waves and then evaluates the spatial relationship between case incidence and built environment and socio-demographic characteristics. By collecting local-related cases, this study incorporates a two-fold analytical strategy: (1) Using rank-size distribution and log-odd ratio to depict the spatial pattern of COVID-19 incidence rates;(2) through global and local regression models, investigating incidence’s associations with the urban built environment and socio-demographic characteristics. The results reveal that the two different epidemic waves have far distinct spatial tendencies to their infection risk factors, reflecting location-specific associations with the built environments and socio-demographics. Collectively, we discover that the third and fourth COVID-19 waves are likely associated with residential context and urban activities, respectively. Practical implications are discussed that would be of interest to policymakers and health professionals.

2.
ISPRS International Journal of Geo-Information ; 11(2):135, 2022.
Article in English | MDPI | ID: covidwho-1686804

ABSTRACT

Environmental exposure of people plays an important role in assessing the quality of human life. The most existing methods that estimate the environmental exposure either focus on the individual level or do not consider human mobility. This paper adopts a vector field generated from the observed locations of human activities to model the environmental exposure at the population level. An improved vector-field-generation method was developed by considering people’s decision-making factors, and we proposed two indicators, i.e., the total exposure indicator (TEI) and the average exposure indicator (AEI), to assess various social groups’environmental exposure. A case study about the risky environmental exposure of coronavirus disease 2019 (COVID-19) was conducted in Guangzhou, China. Over 900 participants with various socioeconomic backgrounds were involved in the questionnaire, and the survey-based activity locations were extracted to generate the vector field using the improved method. COVID-19 pandemic exposure (or risk) was estimated for different social groups. The findings show that people in the low-income group have an 8% to 10% higher risk than those in the high-income group. This new method of vector field may benefit geographers and urban researchers, as it provides opportunities to integrate human activities into the metrics of pandemic risk, spatial justice, and other environmental exposures.

3.
Int J Environ Res Public Health ; 18(14)2021 07 14.
Article in English | MEDLINE | ID: covidwho-1314641

ABSTRACT

With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revive the tourism economy, there is a growing prospect for relieving the social distancing regulation and reopening borders in tourism-oriented countries and regions. This need incentivizes stakeholders to develop border control strategies that fully evaluate health risks if mandatory quarantines are lifted. In this study, we have employed a computational approach to investigate the contact tracing integrated policy in different border-reopening scenarios in Hong Kong, China. Explicitly, by reconstructing the COVID-19 transmission from historical data, specific scenarios with joint effects of digital contact tracing and other concurrent measures (i.e., controlling arrival population and community nonpharmacological interventions) are applied to forecast the future development of the pandemic. Built on a modified SEIR epidemic model with a 30% vaccination coverage, the results suggest that scenarios with digital contact tracing and quick isolation intervention can reduce the infectious population by 92.11% compared to those without contact tracing. By further restricting the inbound population with a 10,000 daily quota and applying moderate-to-strong community nonpharmacological interventions (NPIs), the average daily confirmed cases in the forecast period of 60 days can be well controlled at around 9 per day (95% CI: 7-12). Two main policy recommendations are drawn from the study. First, digital contact tracing would be an effective countermeasure for reducing local virus spread, especially when it is applied along with a moderate level of vaccination coverage. Second, implementing a daily quota on inbound travelers and restrictive community NPIs would further keep the local infection under control. This study offers scientific evidence and prospective guidance for developing and instituting plans to lift mandatory border control policies in preparing for the global economic recovery.


Subject(s)
COVID-19 , Quarantine , COVID-19 Vaccines , China , Contact Tracing , Hong Kong , Humans , Models, Theoretical , Policy , Prospective Studies , SARS-CoV-2
4.
Transp Policy (Oxf) ; 106: 173-184, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1171853

ABSTRACT

The COVID-19 outbreak has necessitated a critical review of urban transportation and its role in society against the backdrop of an exogenous shock. This article extends the transportation literature regarding community responses to the COVID-19 pandemic and what lessons can be obtained from the case of Hong Kong in 2020. Individual behavior and collective responsibility are considered crucial to ensure both personal and community wellbeing in a pandemic context. Trends in government policies, the number of infectious cases, and community mobility are examined using multiple data sources. The mobility changes that occurred during the state of emergency are revealed by a time-series analysis of variables that measure both the epidemiological severity level and government stringency. The results demonstrate a high response capability of the local government, inhabitants, and communities. Communities in Hong Kong are found to have reacted faster than the implementation of health interventions, whereas the government policies effectively reduced the number of infection cases. The ways in which community action are vital to empower flexible and adaptive community responses are also explored. The results indicate that voluntary community involvement constitutes a necessary condition to help inform and reshape future transport policy and response strategies to mitigate the pandemic.

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