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1.
Research square ; 2020.
Article | WHO COVID | ID: covidwho-669637

ABSTRACT

Studies of novel coronavirus disease (COVID-19) have reported varying estimates of epidemiological parameters such as serial intervals and reproduction numbers By compiling a unique line-list database of transmission pairs in mainland China, we demonstrated that serial intervals of COVID-19 have shortened substantially from a mean of 7 8 days to 2 6 days within a month This change is driven by enhanced non-pharmaceutical interventions, in particular case isolation We also demonstrated that using real-time estimation of serial intervals allowing for variation over time would provide more accurate estimates of reproduction numbers, than by using conventional definition of fixed serial interval distributions These findings are essential to improve the assessment of transmission dynamics, forecasting future incidence, and estimating the impact of control measures

2.
Science ; 2020 Jul 21.
Article in English | MEDLINE | ID: covidwho-658227

ABSTRACT

Studies of novel coronavirus disease (COVID-19) have reported varying estimates of epidemiological parameters including serial interval distributions, i.e., the time between illness onset in successive cases in a transmission chain, and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 have shortened substantially from 7.8 days to 2.6 days within a month (January 9 to February 13, 2020). This change is driven by enhanced non-pharmaceutical interventions, in particular case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time, provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings could improve assessment of transmission dynamics, forecasting future incidence, and estimating the impact of control measures.

3.
Clin Infect Dis ; 2020 Jun 18.
Article in English | MEDLINE | ID: covidwho-603806

ABSTRACT

BACKGROUND: Knowledge on the epidemiological features and transmission patterns of COVID-19 is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics. METHODS: A unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1,407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9,120 COVID-19 confirmed cases reported during January 15 - February 29, 2020. Statistical model fittings were used to identify the super-spreaders and estimate serial interval distributions. Age and gender-stratified hazard of infection were estimated for household versus non-household transmissions. RESULTS: There were 34 primary cases identified as super-spreaders, with 5 super-spreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% CrI: 4.4, 5.5) and 5.2 (95% CrI: 4.9, 5.7) days for household transmissions and 5.2 (95% CrI: 4.6, 5.8) and 5.3 (95% CrI: 4.9, 5.7) days for non-household transmissions, respectively. Hazard of being infected outside of households is higher for age between 18 and 64 years, whereas hazard of being infected within households is higher for young and old people. CONCLUSIONS: Non-negligible frequency of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced non-pharmaceutical interventions to mitigate this pandemic.

4.
Clin. Infect. Dis. ; 5(70): 850-858, 20200301.
Article in English | ELSEVIER | ID: covidwho-326398

ABSTRACT

Background. Respiratory virus-laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at nonhealthcare locations vs surveillance data obtained by conventional means has not been fully assessed. Methods. From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong. Viral genomes were detected and quantified by real-time reverse-transcription polymerase chain reaction. Logistic regression models were fitted to examine the adjusted odds ratios (aORs) of ecological and environmental factors associated with the detection of virus-laden airborne particles. Results. Influenza A (16.9% [117/694]) and influenza B (4.5% [31/694]) viruses were detected at higher frequencies in air than rhinovirus (2.2% [6/270]), respiratory syncytial virus (0.4% [1/270]), or human coronaviruses (0% [0/270]). Multivariate analyses showed that increased crowdedness (aOR, 2.3 [95% confidence interval {CI}, 1.5-3.8]; P < .001) and higher indoor temperature (aOR, 1.2 [95% CI, 1.1-1.3]; P < .001) were associated with detection of influenza airborne particles, but absolute humidity was not (aOR, 0.9 [95% CI, .7-1.1]; P = .213). Higher copies of influenza viral genome were detected from airborne particles >4 μm in spring and <1 μm in autumn. Influenza A(H3N2) and influenza B viruses that caused epidemics during the study period were detected in air prior to observing increased influenza activities in the community. Conclusions. Air sampling as a surveillance tool for monitoring influenza activity at public locations may provide early detection signals on influenza viruses that circulate in the community.

5.
Lancet Public Health ; 5(5): e289-e296, 2020 05.
Article in English | MEDLINE | ID: covidwho-96229

ABSTRACT

BACKGROUND: When a new infectious disease emerges, appropriate case definitions are important for clinical diagnosis and for public health surveillance. Tracking case numbers over time is important to establish the speed of spread and the effectiveness of interventions. We aimed to assess whether changes in case definitions affected inferences on the transmission dynamics of coronavirus disease 2019 (COVID-19) in China. METHODS: We examined changes in the case definition for COVID-19 in mainland China during the first epidemic wave. We used exponential growth models to estimate how changes in the case definitions affected the number of cases reported each day. We then inferred how the epidemic curve would have appeared if the same case definition had been used throughout the epidemic. FINDINGS: From Jan 15 to March 3, 2020, seven versions of the case definition for COVID-19 were issued by the National Health Commission in China. We estimated that when the case definitions were changed, the proportion of infections being detected as cases increased by 7·1 times (95% credible interval [CrI] 4·8-10·9) from version 1 to 2, 2·8 times (1·9-4·2) from version 2 to 4, and 4·2 times (2·6-7·3) from version 4 to 5. If the fifth version of the case definition had been applied throughout the outbreak with sufficient testing capacity, we estimated that by Feb 20, 2020, there would have been 232 000 (95% CrI 161 000-359 000) confirmed cases in China as opposed to the 55 508 confirmed cases reported. INTERPRETATION: The case definition was initially narrow and was gradually broadened to allow detection of more cases as knowledge increased, particularly milder cases and those without epidemiological links to Wuhan, China, or other known cases. These changes should be taken into account when making inferences on epidemic growth rates and doubling times, and therefore on the reproductive number, to avoid bias. FUNDING: Health and Medical Research Fund, Hong Kong.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Epidemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Public Health Surveillance/methods , China/epidemiology , Coronavirus Infections/diagnosis , Humans , Models, Theoretical , Pandemics , Pneumonia, Viral/diagnosis
6.
Nat Med ; 26(5): 672-675, 2020 05.
Article in English | MEDLINE | ID: covidwho-65153

ABSTRACT

We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 25-69%) of secondary cases were infected during the index cases' presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home. Disease control measures should be adjusted to account for probable substantial presymptomatic transmission.


Subject(s)
Betacoronavirus/physiology , Coronavirus Infections/transmission , Pneumonia, Viral/transmission , Virus Shedding , Coronavirus Infections/epidemiology , Humans , Pandemics , Pneumonia, Viral/epidemiology
7.
Euro Surveill ; 25(3)2020 Jan.
Article in English | MEDLINE | ID: covidwho-89

ABSTRACT

A novel coronavirus (2019-nCoV) causing severe acute respiratory disease emerged recently in Wuhan, China. Information on reported cases strongly indicates human-to-human spread, and the most recent information is increasingly indicative of sustained human-to-human transmission. While the overall severity profile among cases may change as more mild cases are identified, we estimate a risk of fatality among hospitalised cases at 14% (95% confidence interval: 3.9-32%).


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Coronavirus/isolation & purification , Disease Outbreaks , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/transmission , China/epidemiology , Communicable Diseases, Emerging/epidemiology , Communicable Diseases, Emerging/transmission , Coronavirus/classification , Coronavirus Infections/mortality , Hospital Mortality , Hospitalization , Humans , Public Health , Risk Assessment
8.
N Engl J Med ; 382(13): 1199-1207, 2020 03 26.
Article in English | MEDLINE | ID: covidwho-57

ABSTRACT

BACKGROUND: The initial cases of novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. METHODS: We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. RESULTS: Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). CONCLUSIONS: On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.).


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Disease Transmission, Infectious/statistics & numerical data , Epidemics , Infectious Disease Incubation Period , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Adolescent , Adult , Aged , Betacoronavirus/genetics , China/epidemiology , Communicable Disease Control/methods , Coronavirus Infections/virology , Disease Transmission, Infectious/prevention & control , Epidemics/prevention & control , Female , Humans , Incidence , Male , Middle Aged , Pandemics , Pneumonia, Viral/virology , Polymerase Chain Reaction , Young Adult
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