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1.
J Med Virol ; 93(12): 6628-6633, 2021 12.
Article in English | MEDLINE | ID: covidwho-1544311

ABSTRACT

As the emergence of new variants of SARS-CoV-2 persists across the world, it is of importance to understand the distributional behavior of the incubation period of the variants for both medical research and public health policy-making. We collected the published individual-level data of 941 patients of the 2020-2021 winter pandemic wave in Hebei province, North China. We computed some epidemiological characteristics of the wave and estimated the distribution of the incubation period. We further assessed the covariate effects of sex, age, and living with a case with respect to the incubation period by a model. The infection-fatality rate was only 0.1%. The estimated median incubation period was at least 22 days, significantly extended from the estimates (ranging from 4 to 8.5 days) of the previous wave in mainland China and those ever reported elsewhere around the world. The proportion of asymptomatic patients was 90.6%. No significant covariate effect was found. The distribution of incubation period of the new variants showed a clear extension from their early generations.


Subject(s)
COVID-19/epidemiology , Infectious Disease Incubation Period , SARS-CoV-2/physiology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/virology , Child , Child, Preschool , China/epidemiology , Female , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Pandemics/statistics & numerical data , Young Adult
2.
Medicine (Baltimore) ; 100(30): e26738, 2021 Jul 30.
Article in English | MEDLINE | ID: covidwho-1475910

ABSTRACT

ABSTRACT: This study assessed the proportion of ABO blood groups and clinical characteristics among Saudi patients with coronavirus disease 2019 (COVID-19) in Jazan, Saudi Arabia.This retrospective cohort study included 404 Saudi adults with COVID-19, confirmed by the real-time reverse transcription-polymerase chain reaction. The participants were selected randomly between July 1, 2020, and July 31, 2020, from the Health Electronic Surveillance Network system, which contains the primary data on COVID-19 infections in Jazan.Blood type O (62.4%) represented the highest proportion in COVID-19 Saudi patients followed by the other blood groups which distributed as follows: blood type A (25.5%), blood type B (10.1%), and blood type AB (2%). Men, and people aged 18-44 years, represented the higher percentage than women and those of a younger age. The majority of the patients with COVID-19 had clinical symptoms (88.4%), and the remainder (11.6%) were asymptomatic. Ninety four percent of the patients had mild COVID-19 symptoms and self-isolated at home. Only 6.4% of the cases were severe and admitted to hospital. There was no significant association between a specific ABO blood group and COVID-19 clinical symptoms (P = .950), incubation period (P = .780), disease duration (P = .430), and disease severity (P = .340). Old age and diabetes were the significant predictors of COVID-19 severity and hospital admission (P = .010).Blood group O represented the highest proportion of COVID-19 Saudi patients as it is the most common blood group in Saudi individuals in Jazan. However, no specific blood group was associated with COVID-19 severity and hospital admission. Old age and diabetes mellitus were shown to be significant predictors of severe COVID-19 and hospital admission.


Subject(s)
ABO Blood-Group System , COVID-19/blood , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/pathology , Female , Humans , Infectious Disease Incubation Period , Male , Middle Aged , Retrospective Studies , Risk Factors , Saudi Arabia , Severity of Illness Index , Sex Factors , Young Adult
4.
Nihon Koshu Eisei Zasshi ; 68(8): 550-558, 2021 Aug 11.
Article in Japanese | MEDLINE | ID: covidwho-1352943

ABSTRACT

Objectives There is little evidence supporting the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from presymptomatic or asymptomatic SARS-CoV-2-infected individuals in Japan, where the incidence of SARS-CoV-2 infection is lower than that in other developed countries. This study aimed to determine whether SARS-CoV-2 transmission can occur from presymptomatic or asymptomatic SARS-CoV-2-infected individuals.Methods We surveyed all directors of Japanese public health centers for index cases and secondary patients who possibly contracted SARS-CoV-2 infection from a presymptomatic or asymptomatic SARS-CoV-2-infected individual who came under their care before June 20, 2020. The professional staff at the centers routinely perform contact tracing of infected persons based on the guidelines of the Infection Control Act. Four authors independently reviewed reports of 9 index cases of SARS-CoV-2-infected individuals with 17 secondary patients from 8 prefectures and examined the cases to determine whether transmission from a SARS-CoV-2-infected individual in the presymptomatic or asymptomatic state occurred.Results We reported 7 index cases with 13 secondary patients. 1) An elderly woman acquired SARS-CoV-2 infection from her sustained asymptomatic granddaughter at home, 2) 4 guests and 1 accompanying child waiting at a hair salon acquired infection from the presymptomatic female hair stylist, 3) 2 inpatients acquired infection from a presymptomatic nurse while providing nursing care in close contact, 4) an elderly couple acquired SARS-CoV-2 infection from their presymptomatic relative who was in the 50s during household care at their home, 5) a man acquired SARS-CoV-2 infection from a presymptomatic adult neighbor in an enclosed space with poor ventilation, 6) a presymptomatic man had transmitted infection to another man at a coffee shop while having a discussion on business, and 7) a man in his 50s acquired SARS-CoV-2 infection from a presymptomatic man during 50 minutes of close contact at their office and in a car. These secondary patients had no other likely routes of infection. The interval between the date of symptom onset in the presymptomatic index case and the secondary patient ranged from 2 to 6 days. The incidence rates at the time these infections occurred in the corresponding prefectures ranged from 0.00 to 6.56 cases/1 million person-days.Conclusion We report the first case of SARS-CoV-2 transmission from a sustained asymptomatic index case in Japan. All secondary patients came into close contact with presymptomatic index cases in areas with poor ventilation.


Subject(s)
Asymptomatic Diseases/epidemiology , COVID-19/epidemiology , COVID-19/transmission , Carrier State/epidemiology , Carrier State/transmission , Contact Tracing , SARS-CoV-2 , Adult , Aged , Female , Humans , Infectious Disease Incubation Period , Japan/epidemiology , Male , Middle Aged , Young Adult
6.
Pharmacol Res ; 157: 104821, 2020 07.
Article in English | MEDLINE | ID: covidwho-1318924

ABSTRACT

AIM: Since December 2019, new COVID-19 outbreaks have occurred and spread around the world. However, the clinical characteristics of patients in other areas around Wuhan, Hubei Province are still unclear. In this study, we performed epidemiological and clinical characteristics analysis on these regional cases. METHODS: We retrospectively investigated COVID-19 patients positively confirmed by nucleic acid Q-PCR at Taihe Hospital from January 16 to February 4, 2020. Their epidemiological, clinical manifestations, and imaging characteristics were analysed. RESULTS: Among the 73 patients studied, 12.3 % developed symptoms after returning to Shiyan from Wuhan, and 71.2 % had a history of close contact with Wuhan personnel or confirmed cases. Among these patients, 9 cases were associated with family clustering. The first main symptoms presented by these patients were fever (84.9 %) and cough (21.9 %). The longest incubation period was 26 days, and the median interval from the first symptoms to admission was 5 days. Of the patients, 67.1 % were originally healthy people with no underlying diseases, others mostly had common comorbidities including hypertension (12.3 %) and diabetes (5.5 %), 10.9 % were current smokers, 30.1 % had low white blood cell counts and 45.2 % showed decreased lymphocytes at the first time of diagnosis. CT scans showed that multiple patchy ground glass shadows outside of the patient lungs were commonly observed, and a single sub-pleural sheet of ground glass shadow with enhanced vascular bundles was also found located under the pleura. Patient follow-up to February 14 presented 38.4 % severe cases and 2.7 % critical cases. After follow-up, the parameter of lymphocyte counts below 0.8 × 109/L cannot be used to predict severe and critical groups from the ordinary group, and a lower proportion of smokers and higher proportion of diabetes patients occur in the poor outcome group. Other co-morbidities are observed but did not lead to poor outcomes. CONCLUSION: The epidemiological characteristics of patients in the area around Wuhan, such as Shiyan, at first diagnosis are described as follows: Patients had histories of Wuhan residences in the early stage and family clustering in the later period. The incubation period was relatively long, and the incidence was relatively hidden, but the virulence was relatively low. The initial diagnosis of the patients was mostly ordinary, and the percentage of critical patients who evolved into the ICU during follow-up is 2.7 %, which is lower than the 26.1 % reported by Wuhan city. According to the Shiyan experience, early diagnosis with multiple swaps of the Q-PCR test and timely treatment can reduce the death rate. Diabetes could be one of the risk factors for progression to severe/critical outcomes. No evidence exists that smoking protects COVID-19 patients from developing to severe/critical cases, and the absolute number of lymphocytes at initial diagnosis could not predict the progression risk from severe to critical condition. Multivariate regression analysis should be used to further guide the allocation of clinical resources.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Cough/epidemiology , Diabetes Mellitus/epidemiology , Fever/epidemiology , Hypertension/epidemiology , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Adult , Aged , COVID-19 , China/epidemiology , Comorbidity , Coronavirus Infections/diagnostic imaging , Female , Hospitalization , Humans , Infectious Disease Incubation Period , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnostic imaging , Retrospective Studies , SARS-CoV-2 , Time Factors , Young Adult
7.
Sci Rep ; 11(1): 12569, 2021 06 15.
Article in English | MEDLINE | ID: covidwho-1270672

ABSTRACT

We propose a novel model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost computational complexity to estimate the incubation period.


Subject(s)
COVID-19/transmission , Infectious Disease Incubation Period , COVID-19/epidemiology , Canada/epidemiology , Humans , Models, Statistical
8.
Sci Rep ; 11(1): 11274, 2021 05 28.
Article in English | MEDLINE | ID: covidwho-1246384

ABSTRACT

The number of new daily infections is one of the main parameters to understand the dynamics of an epidemic. During the COVID-19 pandemic in 2020, however, such information has been underestimated. Here, we propose a retrospective methodology to estimate daily infections from daily deaths, because those are usually more accurately documented. Given the incubation period, the time from illness onset to death, and the case fatality ratio, the date of death can be estimated from the date of infection. We apply this idea conversely to estimate infections from deaths. This methodology is applied to Spain and its 19 administrative regions. Our results showed that probable daily infections during the first wave were between 35 and 42 times more than those officially documented on 14 March, when the national government decreed a national lockdown and 9 times more than those documented by the updated version of the official data. The national lockdown had a strong effect on the growth rate of virus transmission, which began to decrease immediately. Finally, the first inferred infection in Spain is about 43 days before the official data were available during the first wave. The current official data show delays of 15-30 days in the first infection relative to the inferred infections in 63% of the regions. In summary, we propose a methodology that allows reinterpretation of official daily infections, improving data accuracy in infection magnitude and dates because it assimilates valuable information from the National Seroprevalence Studies.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Communicable Disease Control/methods , Humans , Infectious Disease Incubation Period , Pandemics , Retrospective Studies , Seroepidemiologic Studies , Spain
10.
BMC Infect Dis ; 21(1): 424, 2021 May 05.
Article in English | MEDLINE | ID: covidwho-1216888

ABSTRACT

BACKGROUND: Although by late February 2020 the COVID-19 epidemic was effectively controlled in Wuhan, China, estimating the effects of interventions, such as transportation restrictions and quarantine measures, on the early COVID-19 transmission dynamics in Wuhan is critical for guiding future virus containment strategies. Since the exact number of infected cases is unknown, the number of documented cases was used by many disease transmission models to infer epidemiological parameters. This means that it was possible to produce biased estimates of epidemiological parameters and hence of the effects of intervention measures, because the percentage of all cases that were documented changed during the first 2 months of the epidemic, as a consequence of a gradually improving diagnostic capability. METHODS: To overcome these limitations, we constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, accounting for intervention measures and temporal changes in the proportion of new documented infections out of total new infections, to characterize the transmission dynamics of COVID-19 in Wuhan across different stages of the outbreak. Pre-symptomatic transmission was taken into account in our model, and all epidemiological parameters were estimated using the Particle Markov-chain Monte Carlo (PMCMC) method. RESULTS: Our model captured the local Wuhan epidemic pattern as two-peak transmission dynamics, with one peak on February 4 and the other on February 12, 2020. The impact of intervention measures determined the timing of the first peak, leading to an 86% drop in the Re from 3.23 (95% CI, 2.22 to 4.20) to 0.45 (95% CI, 0.20 to 0.69). The improved diagnostic capability led to the second peak and a higher proportion of documented infections. Our estimated proportion of new documented infections out of the total new infections increased from 11% (95% CI 1-43%) to 28% (95% CI 4-62%) after January 26 when more detection kits were released. After the introduction of a new diagnostic criterion (case definition) on February 12, a higher proportion of daily infected cases were documented (49% (95% CI 7-79%)). CONCLUSIONS: Transportation restrictions and quarantine measures together in Wuhan were able to contain local epidemic growth.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Models, Theoretical , Basic Reproduction Number , COVID-19/diagnosis , China/epidemiology , Hospitalization/statistics & numerical data , Humans , Infection Control , Infectious Disease Incubation Period , Markov Chains , Monte Carlo Method , Quarantine , Stochastic Processes
11.
Pan Afr Med J ; 38: 168, 2021.
Article in English | MEDLINE | ID: covidwho-1206454

ABSTRACT

Introduction: incubation period for COVID-19, 2-14 (average 5-6) days. Timing of onset of COVID-19 signs and symptoms amongst cases in Uganda is however not known. Methods: we utilized data on real-time reverse transcription polymerase chain reaction (RT-PCR) confirmed cases to investigate symptom onset timing, from 21st March to 4th September 2020. Since timing of COVID-19 symptom onset is highly likely to be an interval rather than a point estimate, we generated 3-tertile categories: 1st, 2nd and 3rd tertile denoting symptom presentation within 3, 4 to 6 and at least 7 days. We considered all signs and symptoms in the database and analysed using Chi-square test and multinomial logistic regression, controlling for age and sex. Results: we analysed a total of 420 symptomatic case-patients; 72.0% were males, median age of 33 years. Common symptoms were cough (47.6%), running nose (46.2%), fever (27.4%), headache (26.4%) and sore throat (20.5%). We utilized 293 cases with clinical symptom onset date recorded. Most of the patients, 37.5%, presented symptom within 3 days, 31.4% had symptoms in the 2nd and 31.4% in 3rd tertile, denoting 4 to 6 days and at least 7 days after exposure. Running nose (RRR=0.45, 95%CI: 0.24-0.84) and chest pain (RRR=0.64, 95%CI: 0.09-0.72) were more likely to occur in 3rd tertile than 1st or 2nd tertile. Cases aged ≥20 years were less likely to have symptoms in the 1st and 2nd tertile compared to ≤20 years (p<0.05). Conclusion: our study provides empirical evidence for epidemiological characterization of cases by signs and symptoms which complements current proposals for the length of active monitoring of persons exposed to SARS-CoV-2.


Subject(s)
COVID-19/diagnosis , Infectious Disease Incubation Period , Adult , Age Factors , Female , Humans , Male , Middle Aged , Real-Time Polymerase Chain Reaction , Reverse Transcriptase Polymerase Chain Reaction , Time Factors , Uganda , Young Adult
12.
Infect Dis Poverty ; 10(1): 56, 2021 Apr 26.
Article in English | MEDLINE | ID: covidwho-1204112

ABSTRACT

BACKGROUND: As one of the non-pharmacological interventions to control the transmission of COVID-19, determining the quarantine duration is mainly based on the accurate estimates of the incubation period. However, patients with coarse information of the exposure date, as well as infections other than the symptomatic, were not taken into account in previously published studies. Thus, by using the statistical method dealing with the interval-censored data, we assessed the quarantine duration for both common and uncommon infections. The latter type includes the presymptomatic, the asymptomatic and the recurrent test positive patients. METHODS: As of 10 December 2020, information on cases have been collected from the English and Chinese databases, including Pubmed, Google scholar, CNKI (China National Knowledge Infrastructure) and Wanfang. Official websites and medias were also searched as data sources. All data were transformed into doubly interval-censored and the accelerated failure time model was applied. By estimating the incubation period and the time-to-event distribution of worldwide COVID-19 patients, we obtain the large percentiles for determining and suggesting the quarantine policies. For symptomatic and presymptomatic COVID-19 patients, the incubation time is the duration from exposure to symptom onset. For the asymptomatic, we substitute the date of first positive result of nucleic acid testing for that of symptom onset. Furthermore, the time from hospital discharge or getting negative test result to the positive recurrence has been calculated for recurrent positive patients. RESULTS: A total of 1920 laboratory confirmed COVID-19 cases were included. Among all uncommon infections, 34.1% (n = 55) of them developed symptoms or were identified beyond fourteen days. Based on all collected cases, the 95th and 99th percentiles were estimated to be 16.2 days (95% CI 15.5-17.0) and 22.9 days (21.7‒24.3) respectively. Besides, we got similar estimates based on merely symptomatic and presymptomatic infections as 15.1 days (14.4‒15.7) and 21.1 days (20.0‒22.2). CONCLUSIONS: There are a certain number of infected people who require longer quarantine duration. Our findings well support the current practice of the extended active monitoring. To further prevent possible transmissions induced and facilitated by such infectious outliers after the 14-days quarantine, properly prolonging the quarantine duration could be prudent for high-risk scenarios and in regions with insufficient test resources.


Subject(s)
COVID-19/prevention & control , Quarantine/methods , SARS-CoV-2/physiology , Adolescent , Adult , Aged , Asymptomatic Diseases/epidemiology , Asymptomatic Infections/epidemiology , Carrier State/epidemiology , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Infectious Disease Incubation Period , Male , Middle Aged , Models, Statistical , Time Factors , Young Adult
13.
Infect Dis Poverty ; 10(1): 53, 2021 Apr 19.
Article in English | MEDLINE | ID: covidwho-1191906

ABSTRACT

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy. METHODS: We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f). RESULTS: Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%). CONCLUSIONS: Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/prevention & control , SARS-CoV-2/drug effects , Adolescent , Age Factors , Aged , COVID-19/epidemiology , COVID-19/virology , China/epidemiology , Humans , Infectious Disease Incubation Period , Middle Aged , Models, Statistical , Young Adult
14.
Epidemiol Infect ; 149: e74, 2020 11 19.
Article in English | MEDLINE | ID: covidwho-1189171

ABSTRACT

The outbreak of coronavirus disease-2019 (COVID-19) impacts public health dramatically around the world. The demographic characteristics, exposure history, dates of illness onset and dates of confirmed diagnosis were collected from the data of 24 family clusters from Beijing. The characteristics of the cases and the estimated key epidemiologic time-to-event distributions were described. The basic reproductive number (R0) was calculated. Among 89 confirmed COVID-19 patients from 24 family clusters, the median age was 38.0 years and 43.8% were male. The median of incubation period was 5.08 days (95% confidence interval (CI) 4.17-6.21). The median of serial interval was 6.00 days (95% CI 5.00-7.00). The basic reproductive number (R0) was 2.06 (95% CI 2.02-2.08). The median of onset-to-care-seeking days and the median of onset-to-hospital admission days were significantly reduced after 23 January 2020, which implied the enhanced public health awareness among families. With epidemic containment measures in place, the results can inform health authorities about possible extent of epidemic transmission within families. Furthermore, following initiation of interventions, public health measures are not only important for curbing the epidemic spread at the community level but also improve health seeking behaviour at the individual level.


Subject(s)
COVID-19/transmission , Contact Tracing , Disease Outbreaks/statistics & numerical data , Family , SARS-CoV-2 , Adolescent , Adult , Beijing/epidemiology , COVID-19/epidemiology , Child , Cluster Analysis , Female , Humans , Infectious Disease Incubation Period , Male , Middle Aged
15.
J Infect Dev Ctries ; 15(3): 326-332, 2021 03 31.
Article in English | MEDLINE | ID: covidwho-1175617

ABSTRACT

INTRODUCTION: This paper aims to estimate the incubation period and serial intervals for SARS-CoV-2 based on confirmed cases in Jiangxi Province of China and meta-analysis method. METHODOLOGY: Distributions of incubation period and serial interval of Jiangxi epidemic data were fitted by "fitdistrplus" package of R software, and the meta-analysis was conducted by "meta" package of R software. RESULTS: Based on the epidemic data of Jiangxi, we found the median days of incubation period and serial interval were 5.9 days [IQR: 3.8 - 8.6] and 5.7 days [IQR: 3.6 - 8.3], respectively. The median days of the infectivity period at pre-symptomatic was 1.7 days [IQR: 1.1 - 2.4]. The meta-analysis based on 64 papers showed the pooled means of the incubation period and serial interval were 6.25 days (95% CrI: 5.75 - 6.75) and 5.15 days (95% CrI: 4.73 - 5.57), respectively. CONCLUSIONS: Our results contribute to a better understanding of COVID-19 and provide useful parameters for modelling the dynamics of disease transmission. The serial interval is shorter than the incubation period, which indicates that the patients are infectious at pre-symptomatic period, and isolation of detected cases alone is likely to be difficult to halt the spread of SARS-CoV-2.


Subject(s)
COVID-19/epidemiology , Infectious Disease Incubation Period , SARS-CoV-2/physiology , Statistics as Topic , Adolescent , Adult , Aged , Child , Child, Preschool , China/epidemiology , Female , Humans , Infant , Male , Middle Aged , Software , Time Factors , Young Adult
16.
J Infect Dev Ctries ; 15(3): 389-397, 2021 03 31.
Article in English | MEDLINE | ID: covidwho-1175608

ABSTRACT

INTRODUCTION: At the end of 2019, the COVID-19 broke out, and spread to Guizhou province in January of 2020. METHODOLOGY: To acquire the epidemiologic characteristics of COVID-19 in Guizhou province, we collected data from 169 laboratory-confirmed COVID-19 related cases. We described the demographic characteristics of the cases and estimated the incubation period, serial interval and the effective reproduction number. We also presented two representative case studies in Guizhou province: Case Study 1 was an example of the asymptomatic carrier; while Case Study 2 was an example of a large and complex infection chain that involved four different regions, spanning three provinces and eight families. RESULTS: Two peaks in the incidence distribution associated with COVID-19 in Guizhou province were related to the 6.04 days (95% CI: 5.00 - 7.10) of incubation period and 6.14±2.21 days of serial interval. We also discussed the effectiveness of the control measures based on the instantaneous effective reproduction number that was a constantly declining curve. CONCLUSIONS: As of February 2, 2020, the estimated effective reproduction number was below 1, and no new cases were reported since February 26. These showed that Guizhou Province had achieved significant progress in preventing the spread of the epidemic. The medical isolation of close contacts was consequential. Meanwhile, the asymptomatic carriers and the super-spreaders must be isolated in time, who would cause a widespread infection.


Subject(s)
COVID-19/epidemiology , Carrier State/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/prevention & control , COVID-19/transmission , Carrier State/virology , Child , Child, Preschool , China/epidemiology , Female , Geography , Humans , Incidence , Infant , Infectious Disease Incubation Period , Male , Middle Aged , Young Adult
17.
Syst Rev ; 10(1): 101, 2021 04 08.
Article in English | MEDLINE | ID: covidwho-1175346

ABSTRACT

BACKGROUND: The aim of our study was to determine through a systematic review and meta-analysis the incubation period of COVID-19. It was conducted based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). Criteria for eligibility were all published population-based primary literature in PubMed interface and the Science Direct, dealing with incubation period of COVID-19, written in English, since December 2019 to December 2020. We estimated the mean of the incubation period using meta-analysis, taking into account between-study heterogeneity, and the analysis with moderator variables. RESULTS: This review included 42 studies done predominantly in China. The mean and median incubation period were of maximum 8 days and 12 days respectively. In various parametric models, the 95th percentiles were in the range 10.3-16 days. The highest 99th percentile would be as long as 20.4 days. Out of the 10 included studies in the meta-analysis, 8 were conducted in China, 1 in Singapore, and 1 in Argentina. The pooled mean incubation period was 6.2 (95% CI 5.4, 7.0) days. The heterogeneity (I2 77.1%; p < 0.001) was decreased when we included the study quality and the method of calculation used as moderator variables (I2 0%). The mean incubation period ranged from 5.2 (95% CI 4.4 to 5.9) to 6.65 days (95% CI 6.0 to 7.2). CONCLUSIONS: This work provides additional evidence of incubation period for COVID-19 and showed that it is prudent not to dismiss the possibility of incubation periods up to 14 days at this stage of the epidemic.


Subject(s)
COVID-19 , Infectious Disease Incubation Period , Pandemics , Argentina , China , Humans , Singapore
18.
Public Health ; 194: 149-155, 2021 May.
Article in English | MEDLINE | ID: covidwho-1157677

ABSTRACT

Definition of the incubation period for COVID-19 is critical for implementing quarantine and thus infection control. Whereas the classical definition relies on the time from exposure to time of first symptoms, a more practical working definition is the time from exposure to time of first live virus excretion. For COVID-19, average incubation period times commonly span 5-7 days which are generally longer than for most typical other respiratory viruses. There is considerable variability reported however for the late right-hand statistical distribution. A small but yet epidemiologically important subset of patients may have the late end of the incubation period extend beyond the 14 days that is frequently assumed. Conservative assumptions of the right tail end distribution favor safety, but pragmatic working modifications may be required to accommodate high rates of infection and/or healthcare worker exposures. Despite the advent of effective vaccines, further attention and study in these regards are warranted. It is predictable that vaccine application will be associated with continued confusion over protection and its longevity. Measures for the application of infectivity will continue to be extremely relevant.


Subject(s)
COVID-19/transmission , Infectious Disease Incubation Period , Adult , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , Child , Health Personnel , Humans , Infection Control/methods , Models, Statistical , Public Health , Quarantine/methods , SARS-CoV-2/isolation & purification
19.
Clin Infect Dis ; 71(16): 2099-2108, 2020 11 19.
Article in English | MEDLINE | ID: covidwho-1153161

ABSTRACT

BACKGROUND: To illustrate the extent of transmission, identify affecting risk factors and estimate epidemiological modeling parameters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in household setting. METHODS: We enrolled 35 confirmed index cases and their 148 household contacts, January 2020-February 2020, in Zhuhai, China. All participants were interviewed and asked to complete questionnaires. Household contacts were then prospectively followed active symptom monitoring through the 21-day period and nasopharyngeal and/or oropharyngeal swabs were collected at 3-7 days intervals. Epidemiological, demographic, and clinical data (when available) were collected. RESULTS: Assuming that all these secondary cases were infected by their index cases, the second infection rate in household context is 32.4% (95% confidence interval [CI]: 22.4%-44.4%), with 10.4% of secondary cases being asymptomatic. Multivariate analysis showed that household contacts with underlying medical conditions, a history of direct exposure to Wuhan and its surrounding areas, and shared vehicle with an index patient were associated with higher susceptibility. Household members without protective measures after illness onset of the index patient seem to increase the risk for SARS-CoV-2 infection. The median incubation period and serial interval within household were estimated to be 4.3 days (95% CI: 3.4-5.3 days) and 5.1 days (95% CI: 4.3-6.2 days), respectively. CONCLUSION: Early isolation of patients with coronavirus disease 2019 and prioritizing rapid contact investigation, followed by active symptom monitoring and periodic laboratory evaluation, should be initiated immediately after confirming patients to address the underlying determinants driving the continuing pandemic.


Subject(s)
COVID-19/transmission , SARS-CoV-2/pathogenicity , Adolescent , Adult , China/epidemiology , Confidence Intervals , Female , Humans , Infectious Disease Incubation Period , Male , Middle Aged , Multivariate Analysis , Young Adult
20.
Epidemics ; 35: 100454, 2021 06.
Article in English | MEDLINE | ID: covidwho-1135321

ABSTRACT

The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI: 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event.


Subject(s)
COVID-19/transmission , Infectious Disease Incubation Period , Viral Load/statistics & numerical data , Adult , COVID-19/virology , China , Hospitalization , Humans , Male , Models, Theoretical , SARS-CoV-2
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