Is compulsory home quarantine less effective than centralized quarantine in controlling the COVID-19 outbreak? Evidence from Hong Kong

Abstract

Faced with the global spread of COVID-19, the Hong Kong government imposed compulsory home quarantine on all overseas arrivals, while cities in mainland China and Macau adopted a more stringent centralized quarantine approach. This study evaluates the effectiveness of compulsory home quarantine as a means of pandemic control. Combining epidemiological data with traditional socioeconomic and meteorological data from over 250 cities, we employ the Synthetic Control Method (SCM) to construct a counterfactual “synthetic Hong Kong”. This model simulates the infection trends for a hypothetical situation in which HK adopts centralized quarantine measures, and compares them to actual infection numbers. Results suggest that home quarantine would have been less effective than centralized quarantine initially. However, the infection rate under home quarantine later converges with the counterfactual estimate under centralized quarantine (0.136% vs. 0.174%), suggesting similar efficacy in the later phase of implementation. Considering its minimal reliance on public resources, home quarantine with heightened enforcement may therefore be preferable to centralized quarantine in countries with limited public health resources. Home quarantine as a quarantine alternative balances public protection and individual freedom, while conserving resources, making it a more sustainable option for many cities.

Data-driven multiscale modelling and analysis of COVID-19 spatiotemporal evolution using explainable AI

“…Hence, their findings are generally consistent with our reported results that X-16 (COVID-STRINGENCY-INDEX) (1 of our top 3 control measures) is expected to be best minimize the reported G-rates across all clusters of countries from the previous country-scale analysis. The effectiveness of X-12 (PUBLIC-GATHERING-RULES) to control the G-rate parameter also aligned with the recent reported studies by Das et al (2021) and Zhu and Tan (2021) where the authors highlighted that the level of spatial interactions among individuals, in the forms of home quarantines and level of living conditions, significantly affect the spread of COVID-19, especially in urbanized cities. Overall, there is a good level of confidence that the recommended control measures of (1) X-4 (COVID-CONTACT-TRACING), (2) X-12 (PUBLIC-GATHERING-RULES), and (3) X-16 (COVID-STRINGENCY-INDEX), can be both conservative and effective to control the spread of COVID-19 in the foreseeable future, and its subsequent death rates (D-rates), while not severely compromising one nation's economic stability.…”

“…Chen et al (2021) exploited city-level data from China using multiple linear regression models to report that healthcare infrastructure adequacy and urban governance capacity are the optimal factors which can maximize the nation's resilience towards the current pandemic situation. For the case of Hong Kong, Zhu and Tan (2021) combined epidemiological data with relevant socioeconomic and meteorological data from over 250 cities to examine the effectiveness of home quarantines where the authors reported that the control measure can be as useful as centralized quarantine, while balancing public protection, individual freedom, and general resources. In the European continent, Sannigrahi et al (2020) extensively investigated the global and local spatial association between key socio-demographic variables and the growth and death rates due to COVID-19 in 31 different European countries by documenting that poverty and income can best minimize both COVID-19 related conditions in the European region.…”

“…To the very best of our knowledge, we note that the present literature lacks a comprehensive model framework which can systematically investigate the impacts of the multitude of control policies on the growth and death rates of COVID-19 from the global to individual country scales, followed by recommending the most critical/effective control measures which can best minimize the growth and death rates due to COVID-19. By far, it is worth highlighting that most research studies are restricted to local countries (Jie Chen et al, 2021 ; Zhou et al, 2021 ; Zhu & Tan, 2021 ), or individual continents (Y. Pan et al, 2021 ; Sannigrahi et al, 2020 ) for either investigating the relationship between specific control factors (work resumption policies, home quarantines) and COVID-19, or to determine the optimal policies to control the spread of COVID-19, respectively.…”

Causal Effect of the Tokyo 2020 Olympic and Paralympic Games on the Number of COVID-19 Cases under COVID-19 Pandemic: An Ecological Study Using the Synthetic Control Method

“…In this method, a counterfactual trend is created after considering the time trends and the demographic and geographic disparities; it is then compared with the actual trend to evaluate the effectiveness of the policy. Some policies under the COVID-19 pandemic, such as the implementation of lockdowns, use of face masks, compulsory home quarantining, and mandatory COVID-19 vaccination certificates, have been evaluated using the SCM [2][3][4][5][6][7].…”

Optimization of energy efficiency and COVID-19 pandemic control in different indoor environments

“…For example, in China, low-risk, medium-risk and high-risk regions represent the country's different epidemic states. Even in the same city, there may be several areas with different levels of risk, where the open requirements of indoor environments and people's activities are distinct [54] . Since the priority for medium and high-risk areas is to suppress any outbreak quickly, and to minimize the number of people infected as far as possible, the goal is not confined to restricting R 0 <=1, but to get R 0 as low as possible, while paying less attention to energy consumption.…”