scholarly journals Effectiveness of quarantine measure on transmission dynamics of COVID-19 in Hong Kong

2020 ◽  
Author(s):  
Hsiang-Yu Yuan ◽  
Axiu Mao ◽  
Guiyuan Han ◽  
Hsiangkuo Yuan ◽  
Dirk Pfeiffer
Keyword(s):  
Hong Kong ◽  
Symptom Onset ◽  
Mainland China ◽  
Economic Loss ◽  
Control Measures ◽  
Rapid Expansion ◽  
Transmission Dynamics ◽  
Reproductive Number ◽  
Suspected Case ◽  
Infected Case

AbstractThe rapid expansion of COVID-19 has caused a global pandemic. Although quarantine measures have been used widely, the critical steps among them to suppress the outbreak without a huge social-economic loss remain unknown. Hong Kong, unlike other regions in the world, had a massive number of travellers from Mainland China during the early expansion period, and yet the spread of virus has been relatively limited. Understanding the effect of control measures to reduce the transmission in Hong Kong can improve the control of the virus spreading.We have developed a susceptible-exposed-infectious-quarantined-recovered (SEIQR) meta-population model that can stratify the infections into imported and subsequent local infections, and therefore to obtain the control effects on transmissibility in a region with many imported cases. We fitted the model to both imported and local confirmed cases with symptom onset from 18 January to 29 February 2020 in Hong Kong with daily transportation data and the transmission dynamics from Wuhan and Mainland China.The model estimated that the reproductive number was dropped from 2.32 to 0.76 (95% CI, 0.66 to 0.86) after an infected case was estimated to be quarantined half day before the symptom onset, corresponding to the incubation time of 5.43 days (95% CI, 1.30-9.47). If the quarantine happened about one day after the onset, community spread would be likely to occur, indicated by the reproductive number larger than one. The results suggest that the early quarantine for a suspected case before the symptom onset is a key factor to suppress COVID-19.

scholarly journals The importance of the timing of quarantine measures before symptom onset to prevent COVID-19 outbreaks - illustrated by Hong Kong’s intervention model

2020 ◽  
Author(s):  
Hsiang-Yu Yuan ◽  
Guiyuan Han ◽  
Hsiangkuo Yuan ◽  
Susanne Pfeiffer ◽  
Axiu Mao ◽  
...  
Keyword(s):  
Hong Kong ◽  
Symptom Onset ◽  
Reproduction Number ◽  
Model Fitting ◽  
Mainland China ◽  
Control Measures ◽  
Rapid Expansion ◽  
Transmission Dynamics ◽  
Population Immunity ◽  
Key Factor

AbstractBackgroundThe rapid expansion of the current COVID-19 outbreak has caused a global pandemic but how quarantine-based measures can prevent or suppress an outbreak without other more intrusive interventions has not yet been determined. Hong Kong had a massive influx of travellers from mainland China, where the outbreak began, during the early expansion period coinciding with the Lunar New Year festival; however, the spread of the virus has been relatively limited even without imposing severe control measures, such as a full city lockdown. Understanding how quarantine measures in Hong Kong were effective in limiting community spread can provide us with valuable insights into how to suppress an outbreak. However, challenges exist in evaluating the effects of quarantine on COVID-19 transmission dynamics in Hong Kong due to the fact that the effects of border control have to be also taken into account.MethodsWe have developed a two-layered susceptible-exposed-infectious-quarantined-recovered (SEIQR) meta-population model which can estimate the effects of quarantine on virus transmissibility after stratifying infections into imported and subsequent community infections, in a region closely connected to the outbreak’s source. We fitted the model to both imported and local confirmed case data with symptom onset from 18 January to 29 February 2020 in Hong Kong, together with daily transportation data and the transmission dynamics of COVID-19 from Wuhan and mainland China. After model fitting, epidemiological parameters and the timing of the start of quarantine for infected cases were estimated.ResultsThe model estimated that the reproduction number of COVID-19 in Hong Kong was 0.76 (95% CI, 0.66 to 0.86), achieved through quarantining infected cases −0.57 days (95% CI, −4.21 − 3.88) relative to symptom onset, with an estimated incubation time of 5.43 days (95% CI, 1.30 − 9.47). However, if delaying the quarantine start by more than 1.43 days, the reproduction number would be greater than one, making community spread more likely. The model also determined the timing of the start of quarantine necessary in order to suppress an outbreak in the presence of population immunity.ConclusionThe results suggest that the early quarantine for infected cases before symptom onset is a key factor to prevent COVID-19 outbreak.

scholarly journals Effective COVID-19 Control: A Comparative Analysis of the Stringency and Timeliness of Government Responses in Asia

2021 ◽  
Vol 18 (16) ◽  
pp. 8686
Author(s):  
Shu Chen ◽  
Lei Guo ◽  
Taghred Alghaith ◽  
Di Dong ◽  
Mohammed Alluhidan ◽  
...  
Keyword(s):  
Public Health ◽  
Hong Kong ◽  
South Korea ◽  
Health System ◽  
Mainland China ◽  
Initial Response ◽  
Control Measures ◽  
System Control ◽  
East And Southeast Asia ◽  
Study Sites

Aim: Many governments in East and Southeast Asia responded promptly and effectively at the onset of the COVID-19 pandemic. Synthesizing and analyzing these responses is vital for disease control evidence-based policymaking. Methods: An extensive review of COVID-19 control measures was conducted in selected Asian countries and subregions, including Mainland China, Hong Kong, Taiwan, South Korea, Singapore, Japan, and Vietnam from 1 January to 30 May 2020. Control measures were categorized into administrative, public health, and health system measures. To evaluate the stringency and timeliness of responses, we developed two indices: the Initial Response Index (IRI) and the Modified Stringency Index (MSI), which builds on the Oxford COVID-19 Government Response Tracker (OxCGRT). Results: Comprehensive administrative, public health, and health system control measures were implemented at the onset of the outbreak. Despite variations in package components, the stringency of control measures across the study sites increased with the acceleration of the outbreak, with public health control measures implemented the most stringently. Variations in daily average MSI scores are observed, with Mainland China scoring the highest (74.2), followed by Singapore (67.4), Vietnam (66.8), Hong Kong (66.2), South Korea (62.3), Taiwan (52.1), and Japan (50.3). Variations in IRI scores depicting timeliness were higher: Hong Kong, Taiwan, Vietnam, and Singapore acted faster (IRI > 50.0), while Japan (42.4) and Mainland China (4.2) followed. Conclusions: Timely setting of stringency of the control measures, especially public health measures, at dynamically high levels is key to optimally controlling outbreaks.

scholarly journals Epidemiological characteristics of the first 100 cases of coronavirus disease 2019 (COVID-19) in Hong Kong Special Administrative Region, China, a city with a stringent containment policy

2020 ◽  
Vol 49 (4) ◽  
pp. 1096-1105 ◽  
Author(s):  
Christopher K C Lai ◽  
Rita W Y Ng ◽  
Martin C S Wong ◽  
Ka Chun Chong ◽  
Yun Kit Yeoh ◽  
...  
Keyword(s):  
Hong Kong ◽  
Incubation Period ◽  
Mainland China ◽  
Control Measures ◽  
Contact Tracing ◽  
Border Control ◽  
Government Information ◽  
Epidemic Curve ◽  
Containment Policy ◽  
Epidemiological Characteristics

Abstract Background Hong Kong (HK) is a densely populated city near the epicentre of the coronavirus disease 2019 (COVID-19) outbreak. Stringent border control together with aggressive case finding, contact tracing, social distancing and quarantine measures were implemented to halt the importation and spread of the virus. Methods We performed an epidemiological study using government information covering the first 100 confirmed cases to examine the epidemic curve, incidence, clusters, reproduction number (Rt), incubation period and time to containment. Results A total of 93 of the 100 cases were HK residents (6 infected in Mainland China, 10 on the Diamond Princess Cruise). Seven were visitors infected in Mainland China before entering HK. The majority (76%) were aged ≥45 years, and the incidence increased with age (P < 0.001). Escalation of border control measures correlated with a decrease in the proportion (62.5% to 0%) of cases imported from Mainland China, and a reduction in Rt (1.07 to 0.75). The median incubation period was 4.2 days [95% confidence interval (CI), 4.0–4.5; 5th and 95th percentiles: 1.3 and 14.0). Most clusters with identifiable epidemiological links were households involving 2–4 people. Three medium-spreading events were identified: two from New Year gatherings (6–11 people), and another from environmental contamination of a worship hall (12 people). Despite intensified contact tracing, containment was delayed in 78.9% of cases (mean = 5.96 days, range = 0–24 days). An unusual transmission in a multi-storey building via faulty toilet plumbing was suspected with >100 residents evacuated overnight. Our analysis indicated that faulty plumbing was unlikely to be the source of this transmission. Conclusion Timely stringent containment policies minimized the importation and transmission of COVID-19 in HK.

scholarly journals Transmission dynamics, serial interval and epidemiology of COVID-19 diseases in Hong Kong under different control measures

2020 ◽  
Vol 5 ◽  
pp. 91
Author(s):  
Yung-Wai Desmond Chan ◽  
Stefan Flasche ◽  
Tin-Long Terence Lam ◽  
Mei-Hung Joanna Leung ◽  
Miu-Ling Wong ◽  
...  
Keyword(s):  
Hong Kong ◽  
Population Level ◽  
Credible Interval ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Local Data ◽  
First Case ◽  
Serial Interval ◽  
Imported Cases ◽  
Epidemiological Characteristics

Background: The outbreak of coronavirus disease 2019 (COVID-19) started in Wuhan, China in late December 2019, and subsequently became a pandemic. Hong Kong had implemented a series of control measures since January 2020, including enhanced surveillance, isolation and quarantine, border control and social distancing. Hong Kong recorded its first case on 23 January 2020, who was a visitor from Wuhan. We analysed the surveillance data of COVID-19 to understand the transmission dynamics and epidemiology in Hong Kong. Methods: We constructed the epidemic curve of daily COVID-19 incidence from 23 January to 6 April 2020 and estimated the time-varying reproduction number (Rt) with the R package EpiEstim, with serial interval computed from local data. We described the demographic and epidemiological characteristics of reported cases. We computed weekly incidence by age and residential district to understand the spatial and temporal transmission of the disease. Results: COVID-19 disease in Hong Kong was characterised with local cases and clusters detected after two waves of importations, first in late January (week 4 to 6) and the second one in early March (week 9 to 10). The Rt increased to approximately 2 95% credible interval (CI): 0.3-3.3) and approximately 1 (95%CI: 0.2-1.7), respectively, following these importations; it decreased to below 1 afterwards from weeks 11 to 13, which coincided with the implementation, modification and intensification of different control measures. Compared to local cases, imported cases were younger (mean age: 52 years among local cases vs 35 years among imported cases), had a lower proportion of underlying disease (9% vs 5%) and severe outcome (13% vs 5%). Cases were recorded in all districts but the incidence was highest in those in the Hong Kong Island region. Conclusions: Stringent and sustained public health measures at population level could contain the COVID-19 disease at a relatively low level.

scholarly journals Effectiveness of control measures during the SARS epidemic in Beijing: a comparison of the Rt curve and the epidemic curve

2007 ◽  
Vol 136 (4) ◽  
pp. 562-566 ◽  
Author(s):  
B. J. COWLING ◽  
L. M. HO ◽  
G. M. LEUNG
Keyword(s):  
Public Health ◽  
Quantitative Assessment ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Reproductive Number ◽  
Primary Case ◽  
Epidemic Curve ◽  
Health Control

SUMMARYOne of the areas most affected by SARS was Beijing with 2521 reported cases. We estimate the effective reproductive number Rt for the Beijing SARS epidemic, which represents the average number of secondary cases per primary case on each day of the epidemic and is therefore a measure of the underlying transmission dynamics. Our results provide a quantitative assessment of the effectiveness of public health control measures. More generally, our results illustrate how changes in Rt will reflect changes in the epidemic curve.

scholarly journals Country distancing reveals the effectiveness of travel restrictions during COVID-19

2020 ◽  
Author(s):  
Lu Zhong ◽  
Mamadou Diagne ◽  
Weiping Wang ◽  
Jianxi Gao
Keyword(s):  
Mainland China ◽  
Credible Interval ◽  
Economic Loss ◽  
Geographic Area ◽  
Strategic Action ◽  
Infected Case ◽  
Travel Restrictions ◽  
In Series ◽  
Backbone Tree ◽  
Novel Coronavirus

Travel restrictions are the current central strategy to globally stop the transmission of the novel coronavirus disease (COVID-19). Despite remarkably successful approaches in predicting the spatiotemporal patterns of the ongoing pandemic, we lack an intrinsic understanding of the travel restriction's effectiveness. We fill this gap by developing a surprisingly simple measure, country distancing, that is analogical to the effective resistance in series and parallel circuits and captures the propagation backbone tree from the outbreak locations globally. This approach enables us to map the effectiveness of travel restrictions to arrival time delay (ATD) or infected case reduction (ICR) systematically. Our method estimates that 50.8\% of travel restrictions as of Apr-4 are ineffective, resulting in zero ATD or ICR worldwide. Instead, by imposing Hubei's lockdown on Jan-23 and national lockdown on Feb-8, mainland China alone leads to 11.66 [95\% credible interval (CI), 9.71 to 13.92] days of ATD per geographic area and 1,012,233 (95\% CI, 208,210 -4,959,094) ICR in total as of Apr-4. Our result unveils the trade-off between the country distancing increase and economic loss, offering practical guidance for strategic action about when and where to implement travel restrictions, tailed to the real-time national context.

scholarly journals A simple transmission dynamics model for predicting the evolution of COVID-19 under control measures in China

2020 ◽  
Author(s):  
Chenjing Shang ◽  
Yang Yang ◽  
Gui-Ying Chen ◽  
Xiao-Dong Shang
Keyword(s):  
Growth Rate ◽  
Prediction Models ◽  
Mainland China ◽  
Health Sector ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Disease Spread ◽  
Chinese Government ◽  
Model Parameters ◽  
Estimation Of Model Parameters

Abstract Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when an outbreak occurs and plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modeling rely on the estimation of model parameters, which yields unreliable and unsustainable results. Herein, we proposed a simple model for predicting the epidemic transmission dynamics based on nonlinear regression of the epidemic growth rate and iterative methods, which is applicable to the progression of the COVID-19 outbreak under the strict control measures of the Chinese government. Our model yields reliable and accurate results as confirmed by the available data: we predicted that the total number of infections in mainland China would be 91,253, and the maximum number of beds required for hospitalized patients would be 62,794. We inferred that the inflection point (when the growth rate turns from positive to negative) of the epidemic across China would be mid-February, and the end of the epidemic would be in late March. This model is expected to contribute to resourceallocation and planning in the health sector while providing a theoretical basis forgovernments to respond to future global health crises or epidemics.

Transmission Dynamics of COVID-19 in Mainland China: Impact of Public Health Control Measures

2020 ◽  
Author(s):  
Lin Zhao ◽  
Yun-Xia Liu ◽  
Jia-Te Wei ◽  
Yu-Chen Zhu ◽  
Jie Qian ◽  
...  
Keyword(s):  
Public Health ◽  
Mainland China ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Health Control

scholarly journals Characterizing superspreading events and age-specific infectiousness of SARS-CoV-2 transmission in Georgia, USA

2020 ◽  
Vol 117 (36) ◽  
pp. 22430-22435 ◽  
Author(s):  
Max S. Y. Lau ◽  
Bryan Grenfell ◽  
Michael Thomas ◽  
Michael Bryan ◽  
Kristin Nelson ◽  
...  
Keyword(s):  
Rural Areas ◽  
The Elderly ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Reproductive Number ◽  
Individual Level ◽  
Mobility Data ◽  
Multiple Data ◽  
Main Driver ◽  
Associated Risk Factors

It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and superspreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatiotemporal mechanistic framework to integrate individual surveillance data with geolocation data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the state of Georgia. First, our results show that the reproductive number reduced to below one in about 2 wk after the shelter-in-place order. Superspreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance toward later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected nonelderly cases (<60 y) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of superspreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of superspreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.

scholarly journals The effects of border control and quarantine measures on global spread of COVID-19

2020 ◽  
Author(s):  
M. Pear Hossain ◽  
Alvin Junus ◽  
Xiaolin Zhu ◽  
Pengfei Jia ◽  
Tzai-Hung Wen ◽  
...  
Keyword(s):  
Arrival Time ◽  
Control Measure ◽  
Control Measures ◽  
Rapid Expansion ◽  
Reproductive Number ◽  
Mathematical Framework ◽  
Border Control ◽  
Travel History ◽  
Global Spread ◽  
Imported Cases

AbstractThe rapid expansion of coronavirus (COVID-19) has been observed in many parts of the world. Many newly reported cases of this new coronavirus during early outbreak phases have been associated with travel history from an epidemic region (identified as imported cases). For those cases without travel history, the risk of wider spreads through community contact is even higher. However, most population models assume a homogeneous infected population without considering that the imported and secondary cases contracted by the imported cases can pose a different risk to community spread.We have developed an “easy-to-use” mathematical framework extending from a meta-population model embedding city-to-city connections to stratify the dynamics of transmission waves caused by imported, secondary, and others from an outbreak source region when control measures are considered. Using the dynamics of the secondary cases, we are able to determine the probability of community spread.Using the top 10 visiting cities from Wuhan in China as an example, we first demonstrated that the arrival time and the dynamics of the outbreaks at these cities can be successfully predicted under the reproductive number R0 = 2.92 and latent period τ = 5.2 days. Next, we showed that although control measures can gain extra 32.5 and 44.0 days in arrival time through a high intensive border control measure and a shorter time to quarantine under a low R0 (1.4), if the R0 is higher (2.92), only 10 extra days can be gained for each of the same measures. This suggests the importance of lowering the incidence at source regions together with infectious disease control measures in susceptible regions. The study allows us to assess the effects of border control and quarantine measures on the emergence and the global spread in a fully connected world using the dynamics of the secondary cases.

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