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 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 ◽  
Underlying Disease ◽  
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 Wuahn. We analysed the surveillance data of COVID-19 to understand the transmission dynamics and epidemiology in Hong Kong. Methods: Based on cases recorded from 23 January to 6 April 2020, we constructed the epidemic curve of daily COVID-19 incidence and used this data to estimate 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 and the second one in early March. The Rt increased to approximately 2 and approximately 1, respectively, following these importations; it decreased to below 1 afterwards, 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 Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends

2020 ◽  
Author(s):  
Xinyin Xu ◽  
Jing Zeng ◽  
Runyou Liu ◽  
Yang Liu ◽  
Xiaobo Zhou ◽  
...  
Keyword(s):  
Early Stage ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Sichuan Province ◽  
Control Measures ◽  
Health Crisis ◽  
First Case ◽  
Imported Cases ◽  
And Control ◽  
Epidemiological Characteristics

Abstract Background: The COVID-19 spread worldwide quickly. Exploring the epidemiological characteristics could provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas where COVID-19 is still spreading rapidly. Methods: The number of confirmed cases, daily growth, incidence and length of time from the first reported case to the end of the local cases (i.e., non-overseas imported cases) were compared by spatial (geographical) and temporal classification and visualization of the development and changes of the epidemic situation by layers through maps. Results: In the first wave, a total of 539 cases were reported in Sichuan, with an incidence rate of 0.6462/100,000. The closer to Hubei the population centres were, the more pronounced the epidemic was. The peak in Sichuan Province occurred in the second week. Eight weeks after the Wuhan lockdown, the health crisis had eased. The longest epidemic length at the city level in China (except Wuhan, Taiwan, and Hong Kong) was 53 days, with a median of 23 days. Spatial autocorrelation analysis of China showed positive spatial correlation (Moran's Index >0, p<0.05). Most countries outside China began to experience a rapid rise in infection rates 4 weeks after their first case. Some European countries experienced that rise earlier than the USA. The pandemic in Germany, Spain, Italy, and China took 28, 29, 34, and 18 days, respectively, to reach the peak of daily infections, after their daily increase of up to 20 cases. During this time, countries in the African region and Southeast Asian region were at an early stage of infections, those in the Eastern Mediterranean region and region of the Americas were in a rapid growth phase. Conclusions: After the closure of the outbreak city, appropriate isolation and control measures in the next 8 weeks were key to control the outbreak, which reduced the peak value and length of the outbreak. Some countries with improved epidemic situations need to develop a continuous "local strategy at entry checkpoints" to respond to a possible second local epidemic.

scholarly journals Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: a statistical analysis in Tunisia from February 29 to May 5, 2020

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Khouloud Talmoudi ◽  
Mouna Safer ◽  
Hejer Letaief ◽  
Aicha Hchaichi ◽  
Chahida Harizi ◽  
...  
Keyword(s):  
Credible Interval ◽  
Emerging Diseases ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Epidemic Threshold ◽  
Illness Onset ◽  
Intervention Measures ◽  
Temporal Reproduction ◽  
Serial Interval

Abstract Background Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (Rt) of SARS-CoV-2 in Tunisia. Methods We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29–May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of Rt. Results Four hundred ninety-one of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% Confidence Interval (CI) 4.66–5.95] and standard deviation 0.26 [95% CI 0.23–0.30]. Also, we estimated large changes in Rt in response to the combined lockdown interventions. The Rt moves from 3.18 [95% Credible Interval (CrI) 2.73–3.69] to 1.77 [95% CrI 1.49–2.08] with curfew prevention measure, and under the epidemic threshold (0.89 [95% CrI 0.84–0.94]) by national lockdown measure. Conclusions Overall, our findings highlight contribution of interventions to interrupt transmission of SARS-CoV-2 in Tunisia.

scholarly journals Should we remain hopeful? The key 8 weeks: spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Xinyin Xu ◽  
Jing Zeng ◽  
Runyou Liu ◽  
Yang Liu ◽  
Xiaobo Zhou ◽  
...  
Keyword(s):  
Early Stage ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Sichuan Province ◽  
Control Measures ◽  
Health Crisis ◽  
First Case ◽  
Imported Cases ◽  
And Control ◽  
Epidemiological Characteristics

Abstract Background The COVID-19 spread worldwide quickly. Exploring the epidemiological characteristics could provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas where COVID-19 is still spreading rapidly. Methods The number of confirmed cases, daily growth, incidence and length of time from the first reported case to the end of the local cases (i.e., non-overseas imported cases) were compared by spatial (geographical) and temporal classification and visualization of the development and changes of the epidemic situation by layers through maps. Results In the first wave, a total of 539 cases were reported in Sichuan, with an incidence rate of 0.6462/100,000. The closer to Hubei the population centres were, the more pronounced the epidemic was. The peak in Sichuan Province occurred in the second week. Eight weeks after the Wuhan lockdown, the health crisis had eased. The longest epidemic length at the city level in China (except Wuhan, Taiwan, and Hong Kong) was 53 days, with a median of 23 days. Spatial autocorrelation analysis of China showed positive spatial correlation (Moran’s Index > 0, p < 0.05). Most countries outside China began to experience a rapid rise in infection rates 4 weeks after their first case. Some European countries experienced that rise earlier than the USA. The pandemic in Germany, Spain, Italy, and China took 28, 29, 34, and 18 days, respectively, to reach the peak of daily infections, after their daily increase of up to 20 cases. During this time, countries in the African region and Southeast Asian region were at an early stage of infections, those in the Eastern Mediterranean region and region of the Americas were in a rapid growth phase. Conclusions After the closure of the outbreak city, appropriate isolation and control measures in the next 8 weeks were key to control the outbreak, which reduced the peak value and length of the outbreak. Some countries with improved epidemic situations need to develop a continuous “local strategy at entry checkpoints” to to fend off imported COVID-19.

scholarly journals Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: A statistical analysis in Tunisia from February 29 to May 5, 2020 

2020 ◽  
Author(s):  
Khouloud Talmoudi ◽  
Mouna Safer ◽  
Hejer Letaief ◽  
Aicha Hchaichi ◽  
Chahida Harizi ◽  
...  
Keyword(s):  
Credible Interval ◽  
Emerging Diseases ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Epidemic Threshold ◽  
Illness Onset ◽  
Intervention Measures ◽  
Temporal Reproduction ◽  
Serial Interval

Abstract Background: Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (Rt) of SARS-CoV-2 in Tunisia. Methods: We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29-May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of Rt. Results: 491 of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% Confidence Interval (CI) 4.66-5.95] and standard deviation 0.26 [95% CI 0.23-0.30]. Also, we estimated large changes in Rt in response to the combined lockdown interventions. The Rt moves from 3.18 [95% Credible Interval (CrI) 2.73-3.69] to 1.77 [95% CrI 1.49-2.08] with curfew prevention measure, and under the epidemic threshold (0.89 [95% CrI 0.84-0.94]) by national lockdown measure.Conclusions: Overall, our findings highlight contribution of interventions to interrupt transmission of SARS-CoV-2 in Tunisia.

scholarly journals Universal community nucleic acid testing for COVID-19 in Hong Kong reveals insights into transmission dynamics

2021 ◽  
Author(s):  
Bingyi Yang ◽  
Tim K. Tsang ◽  
Huizhi Gao ◽  
Eric H. Y. Lau ◽  
Yun Lin ◽  
...  
Keyword(s):  
Public Health ◽  
Hong Kong ◽  
Clinical Diagnosis ◽  
Public Health Surveillance ◽  
Credible Interval ◽  
Health Surveillance ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Third Wave ◽  
Epidemiological Characteristics

Abstract Background: Testing of an entire community has been used as an approach to control COVID-19. In Hong Kong, a universal community testing programme (UCTP) was implemented at the fadeout phase of a community epidemic in July to September 2020, to determine the prevalence of unrecognised cases and limit any remaining transmission chains. We described the utility of the UCTP in finding unrecognised cases, and analysed data from the UCTP and other sources to characterise transmission dynamics.Methods: We described the characteristics of people participating in the UCTP, and compared the clinical and epidemiological characteristics of COVID-19 cases detected by the UCTP versus those detected by clinical diagnosis and public health surveillance. We developed a Bayesian model to estimate the age-specific incidence of infection and the proportion of cases detected by clinical diagnosis and public health surveillance.Findings: 1.77 million people, 24% of the Hong Kong population, participated in the UCTP from 1 to 14 September 2020. The UCTP identified 32 new infections (1.8 per 100,000 samples tested), consisting of 29% of all local cases reported during the two-week UCTP period. Compared with the existing clinical diagnosis and public health surveillance, the UCTP detected a higher proportion of sporadic cases (62% versus 27%, p <0.01) and identified 6 (out of 18) additional transmission chains during that period. We estimated that 27% (95% credible interval: 22%, 34%) of all infections were detected by the existing clinical diagnosis and public health surveillance in the third wave.Interpretation: We reported empirical evidence of the utility of population-wide COVID-19 testing in detecting unrecognised infections and transmission chains. Around three quarters of infections have not been identified through existing surveillance approaches including contact tracing.

scholarly journals Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends

2020 ◽  
Author(s):  
Xinyin Xu ◽  
Jing Zeng ◽  
Runyou Liu ◽  
Yang Liu ◽  
Xiaobo Zhou ◽  
...  
Keyword(s):  
Early Stage ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Sichuan Province ◽  
Control Measures ◽  
Health Crisis ◽  
First Case ◽  
Imported Cases ◽  
And Control ◽  
Epidemiological Characteristics

Abstract Background: The COVID-19 spread worldwide quickly. Exploring the epidemiological characteristics could provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas where COVID-19 is still spreading rapidly.Methods: The number of confirmed cases, daily growth, incidence and length of time from the first reported case to the end of the local cases (i.e., non-overseas imported cases) were compared by spatial (geographical) and temporal classification and visualization of the development and changes of the epidemic situation by layers through maps.Results: In the first wave, a total of 539 cases were reported in Sichuan, with an incidence rate of 0.6462/100,000. The closer to Hubei the population centres were, the more pronounced the epidemic was. The peak in Sichuan Province occurred in the second week. Eight weeks after the Wuhan lockdown, the health crisis had eased. The longest epidemic length at the city level in China (except Wuhan, Taiwan, and Hong Kong) was 53 days, with a median of 23 days. Spatial autocorrelation analysis of China showed positive spatial correlation (Moran's Index >0, p<0.05). Most countries outside China began to experience a rapid rise in infection rates 4 weeks after their first case. Some European countries experienced that rise earlier than the USA. The pandemic in Germany, Spain, Italy, and China took 28, 29, 34, and 18 days, respectively, to reach the peak of daily infections, after their daily increase of up to 20 cases. During this time, countries in the African region and Southeast Asian region were at an early stage of infections, those in the Eastern Mediterranean region and region of the Americas were in a rapid growth phase.Conclusions: After the closure of the outbreak city, appropriate isolation and control measures in the next 8 weeks were key to control the outbreak, which reduced the peak value and length of the outbreak. Some countries with improved epidemic situations need to develop a continuous "local strategy at entry checkpoints" to to fend off imported COVID-19.

scholarly journals Should we keep hope? Key 8 weeks - Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trend

2020 ◽  
Author(s):  
Xinyin Xu ◽  
Jing Zeng ◽  
Runyou Liu ◽  
Yang Liu ◽  
Xiaobo Zhou ◽  
...  
Keyword(s):  
Early Stage ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Sichuan Province ◽  
Control Measures ◽  
First Case ◽  
Local Case ◽  
Imported Cases ◽  
And Control ◽  
Epidemiological Characteristics

Abstract Background: To compare the epidemiological characteristics of Sichuan Province, other provinces in China and the world epidemic trends by analyzing the prevalence and length of epidemic time. in order to provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas that are still rapidly circulating.Methods: The number of confirmed cases, daily growth, incidence and the length of time from the first reported case to the end of local case(non-overseas imported cases) were compared by spatial and temporal (geographical, temporal) classification. Visualizing the development and changes of epidemic situation by layer through maps.Results: In the first wave, total of 539 cases were reported in Sichuan Province, with the incidence rate of 0.6462 / 100,000. The closer to Hubei, the heavier the epidemic. The peak of Sichuan Province came earlier and the value was lower. Eight weeks after Wuhan lockdown, all became better. The longest epidemic length in city level of China was 53 days, median 23 days. It was released quickly in the 1st month, and accelerated in the 2ed month (three times of 1st month). Most countries outside China began to rise rapidly 4 weeks after their first case. Some European countries was earlier than USA. Germany, Spain, Italy, and China cost 28, 29, 34, and 18 days to reached the peak of daily increment, after their daily increase up to 20 cases. Countries in African Region and South-East Asia Region were at the early stage, in Eastern Mediterranean Region and Region of the Americas were at rapid growth phase,in European presented an inflection point or at a plateau period but falling slowly.Conclusions: Adopting appropriate isolation and control measures is necessary to actively respond to the epidemic situation. If effective measures were implemented at the 8 key weeks, the peak value of the confirmed cases will be lower and decrease quickly. Some countries with improved epidemic situations also need to develop a continuous "local strategy at entry checkpoints" to respond to a possible second local epidemic.

scholarly journals Epidemiological Characteristics of Confirmed Cases and Nepal’s Response for Prevention and Control of COVID-19

2020 ◽  
Vol 10 (1) ◽  
pp. 30-35
Author(s):  
Sasmita Poudel
Keyword(s):  
Prevention And Control ◽  
Control Strategies ◽  
Geographical Location ◽  
Control Measures ◽  
First Case ◽  
Imported Cases ◽  
The Government ◽  
Using Data ◽  
And Control ◽  
Epidemiological Characteristics

Introduction: The first case of COVID-19 was reported in Wuhan, China. "COVID- 19 has already spread worldwide with the total number of 2,241, 778 confirmed cases and 152, 551 deaths. There are 31 confirmed cases of COVID-19 in Nepal as of 19 April 2020." This article aims to analyze the epidemiological characteristics of confirmed cases of COVID-19 in the context of Nepal and discuss prevention and control measures taken by the Government of Nepal (GoN). Methods: The epidemiological characteristics of 31 confirmed cases in Nepal were analyzed using data available from a daily press release and Nepal situation report published by the Ministry of Health and Population, GoN. The data were analyzed and presented using SPSS and Arc GIS. Results: Of these 31confirmed cases, 29 (93.5%) cases were imported into the country and 2 (6.5%) were suspected to be secondary cases originating in Nepal either through the family contact or community contact. Among the confirmed cases, 77.4% are males and four cases have already been recovered. The mean age of confirmed cases in Nepal is 36.7 years, with the age ranging from 19 years to 81 years with the highest number (13) reported from province 1.The highest number of cases (14) were reported on 17 April 2020. Conclusion: The distribution of confirmed cases varied with age, sex, and geographical location. The cases are high in males, in the age group of 20-29 years, and in Udayapur district of Province 1. Most of the confirmed cases in Nepal was reported among the individuals who have recently returned to Nepal from foreign countries with evidence of local transmission in the country linked with the imported cases. Different prevention and control strategies are being implemented at the provincial and national levels with the expansion of laboratory facilities for testing COVID-19.

scholarly journals Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria

2020 ◽  
Vol 17 (9) ◽  
pp. 3054 ◽  
Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan
Keyword(s):  
Doubling Time ◽  
Reproduction Number ◽  
Infected Individual ◽  
Credible Interval ◽  
World Health ◽  
Time Interval ◽  
Serial Interval ◽  
Imported Cases ◽  
Novel Coronavirus ◽  
Health Organization

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

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