| Author: | Yuan, Ziyue |
| Title: | Epidemiological evidence of COVID-19 and potential strategies for the construction industry in Hong Kong |
| Advisors: | Hsu, Shu-chien Mark (CEE) |
| Degree: | Ph.D. |
| Year: | 2023 |
| Subject: | Construction industry -- China -- Hong Kong -- Health aspects COVID-19 (Disease) Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Civil and Environmental Engineering |
| Pages: | xx, 150 pages : color illustrations |
| Language: | English |
| Abstract: | The first coronavirus disease 2019 (COVID-19) outbreak was reported in December 2019, developing into a global pandemic by March 2020 and producing shutdowns of business and industry across the world. In comparison with other industries, the disease produced particularly acute health crises and economic losses in the construction industry. This high vulnerability to COVID-19 was due in part to the unavoidable close proximity required during manual labour. In an attempt to mitigate these effects, the construction industry followed macro-level non-pharmaceutical interventions (NPIs), which were established based on transmission patterns at the city level. Since the pandemic, most recent research regarding the construction industry has investigated the effects and challenges of COVID-19 and the responses taken to address them. There is, however, still limited discussion of the specific and major transmission patterns within the construction industry and how a knowledge of such patterns can help decision-makers to align targeted NPIs proactively in order to mitigate such transmission. In this dissertation, epidemiological evidence has been gathered in order to produce a comprehensive understanding of COVID-19 transmission within the construction industry, which has then been used to design targeted NPI response strategies. Primary data from confirmed cases and case clusters of COVID-19 in the construction industry in Hong Kong (including demographic information, epidemiological information regarding symptom onset date and date reported, and contact tracing data) are used. All cases were confirmed by the government and identified by the local authority of disease surveillance (Centre for Health Protection). Several epidemiological methods were used, including compartment models, spatiotemporal analysis, and K-shell decomposition analysis. There are four objectives of this study: 1) to explore the transmission dynamics of COVID-19 and the effectiveness of macro-level NPIs in Hong Kong; 2) to uncover the transmission patterns of COVID-19 in the construction industry in Hong Kong; 3) to estimate the effectiveness of contact restrictions and vaccinations for construction workers and their close contacts on a construction site; and 4) to investigate the feasibility of a priori identification of potential super-spreaders in a construction project. The present study contributes to the ongoing efforts to control and prevent the spread of COVID-19 in the construction industry in Hong Kong. In this study, the transmission dynamics of COVID-19 and the effectiveness of macro-level NPIs (such as restrictions on gathering sizes and quarantine policies) are explored based on a modified Susceptible-Exposed-Infectious-Hospitalized-Recovered (SEIHR) model with nine-month data from 2020 in Hong Kong. These phenomena indicate "pandemic fatigue," as demonstrated by lower and lower adherence to macro-level NPIs among people in Hong Kong. At the same time, from an epidemiological standpoint, the possibility of backward bifurcation makes it imperative for the construction industry to design targeted strategies for adapting to the post-pandemic environment. In order to identify the specific transmission pattern of COVID-19, a spatiotemporal analysis was used with data from five COVID-19 case clusters associated with construction sites in Hong Kong. In these cases, COVID-19 transmission diffused spatially from the workplace to the residential neighbourhoods in which the infected construction workers live, but not to the community surrounding the infected construction sites. Temporally, these outbreaks demonstrated three to five generations in 25.8 days. Several super-spreading events were identified, both at the workplace and within households. Around 18% of seed cases (those who can infect others) infected 79.6% of offspring cases (those who can be infected). It is estimated that, if super-spreaders were restricted before they infect others, it would be possible to eliminate at least half of the offspring cases. Based on the transmission pattern found above, the feasibility and effectiveness of several response strategies, including contact restrictions, vaccinations, and a priori identification of potential super-spreaders, are discussed. A dual-community compartment model is developed to describe the transmission patterns of COVID-19 among construction workers and their close contacts, and to evaluate the effectiveness of contact restrictions. The best-performing scenario is found to be one in which the movements of the close contacts exposed to COVID-19 by infected construction workers are restricted. Such restrictions reduce the total attack rate (TAR) with 25% absolute efficiency (AE) and decrease the duration of an outbreak (DO) in the whole population by 1.8 days, according to the model. In addition to contact restrictions, the vaccination of all construction workers along with at least 67% of their close contacts can extinguish an ongoing wave. In order to identify potential super-spreaders, this study develops a network-based computational framework based on K-shell decomposition approach with the input of the topological interaction network of all project participants. The feasibility of the developed framework is evaluated by three numerical cases: one sample case with a hierarchical structure with an average accuracy of 98.45%, one sample case with a matrix structure with an average accuracy of 92.25%, and an empirical case related to a COVID-19 outbreak in a construction project in Hong Kong with an accuracy of over 80.13%. All potential super-spreaders, especially if they are employed by the main contractor, are suggested to take Rapid Antigen Tests (RATs) regularly. If all potential super-spreaders are detected through regular RATs and all potential secondary cases were detected by contract tracing, up to 82.35% of infected cases could be prevented. The main contribution of this study is threefold: (1) a comprehensive investigation of COVID-19 in the construction industry; (2) a more thorough understanding of the transmission dynamics of COVID-19 and super-spreading patterns; and (3) estimating the effectiveness of NPIs and vaccinations. The main epidemiological evidence includes the high infection risks demonstrated both at the workplace and in households, and the existence of super-spreaders. The proposed response strategies include contact restrictions between targeted groups (e.g., exposed individuals and their close contacts), vaccination plans, and the priori identification of potential super-spreaders. |
| Rights: | All rights reserved |
| Access: | open access |
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