scholarly journals Epidemiological parameters of COVID-19 and its implication for infectivity among patients in China, 1 January to 11 February 2020

2020 ◽  
Vol 25 (40) ◽  
Author(s):  
Qing-Bin Lu ◽  
Yong Zhang ◽  
Ming-Jin Liu ◽  
Hai-Yang Zhang ◽  
Neda Jalali ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Age Groups ◽  
Control Measures ◽  
Adult Age ◽  
Secondary Infections ◽  
History Of ◽  
Early Case ◽  
Relative Infectivity ◽  
Epidemiological Parameters

Background The natural history of disease in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remained obscure during the early pandemic. Aim Our objective was to estimate epidemiological parameters of coronavirus disease (COVID-19) and assess the relative infectivity of the incubation period. Methods We estimated the distributions of four epidemiological parameters of SARS-CoV-2 transmission using a large database of COVID-19 cases and potential transmission pairs of cases, and assessed their heterogeneity by demographics, epidemic phase and geographical region. We further calculated the time of peak infectivity and quantified the proportion of secondary infections during the incubation period. Results The median incubation period was 7.2 (95% confidence interval (CI): 6.9‒7.5) days. The median serial and generation intervals were similar, 4.7 (95% CI: 4.2‒5.3) and 4.6 (95% CI: 4.2‒5.1) days, respectively. Paediatric cases < 18 years had a longer incubation period than adult age groups (p = 0.007). The median incubation period increased from 4.4 days before 25 January to 11.5 days after 31 January (p < 0.001), whereas the median serial (generation) interval contracted from 5.9 (4.8) days before 25 January to 3.4 (3.7) days after. The median time from symptom onset to discharge was also shortened from 18.3 before 22 January to 14.1 days after. Peak infectivity occurred 1 day before symptom onset on average, and the incubation period accounted for 70% of transmission. Conclusion The high infectivity during the incubation period led to short generation and serial intervals, necessitating aggressive control measures such as early case finding and quarantine of close contacts.

scholarly journals Epidemiological parameters of coronavirus disease 2019: a pooled analysis of publicly reported individual data of 1155 cases from seven countries

2020 ◽  
Author(s):  
Shujuan Ma ◽  
Jiayue Zhang ◽  
Minyan Zeng ◽  
Qingping Yun ◽  
Wei Guo ◽  
...  
Keyword(s):  
Latent Period ◽  
Incubation Period ◽  
Symptom Onset ◽  
Severe Disease ◽  
Individual Data ◽  
Robust Estimates ◽  
Upper Limit ◽  
Serial Interval ◽  
Epidemiological Parameters ◽  
Time Point

SummaryBackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has been declared a pandemic by the World Health Organization, while several key epidemiological parameters of the disease remain to be clarified. This study aimed to obtain robust estimates of the incubation period, upper limit of latent period (interval between infector’s exposure and infectee’s exposure), serial interval, time point of exposure (the day of infectee’s exposure to infector relative to the latter’s symptom onset date) and basic reproduction number (R0) of COVID-19.MethodsBetween late February and early March of 2020, the individual data of laboratory confirmed cases of COVID-19 were retrieved from 10728 publicly available reports released by the health authorities of and outside China and from 1790 publications identified in PubMed and CNKI. To be eligible, a report had to contain the data that allowed for estimation of at least one parameter. As relevant data mainly came from clustering cases, the clusters for which no evidence was available to establish transmission order were all excluded to ensure accuracy of estimates. Additionally, only the cases with an exposure period spanning 3 days or less were included in the estimation of parameters involving exposure date, and a simple method for determining exposure date was adopted to ensure the error of estimates be small (< 0.3 day). Depending on specific parameters, three or four of normal, lognormal, Weibull, and gamma distributions were fitted to the datasets and the results from appropriate models were presented.FindingsIn total, 1155 cases from China, Japan, Singapore, South Korea, Vietnam, Germany and Malaysia were included for the final analysis. The mean and standard deviation were 7.44 days and 4.39 days for incubation period, 2.52 days and 3.95 days for the upper limit of latent period, 6.70 days and 5.20 days for serial interval, and −0.19 day (i.e., 0.19 day before infector’s symptom onset) and 3.32 days for time point of exposure. R0 was estimated to be 1.70 and 1.78 based on two different formulas. For 39 (6.64%) cases, the incubation periods were longer than 14 days. In 102 (43.78%) infector-infectee pairs, transmission occurred before infectors’ symptom onsets. In 27 (3.92%) infector-infectee pairs, infectees’ symptom onsets occurred before those of infectors. Stratified analysis showed that incubation period and serial interval were consistently longer for those with less severe disease and for those whose primary cases had less severe disease. Asymptomatic transmission was also observed.InterpretationThis study obtained robust estimates of several key epidemiological parameters of COVID-19. The findings support current practice of 14-day quarantine of persons with potential exposure, but also suggest that longer monitoring periods might be needed for selected groups. The estimates of serial interval, time point of exposure and latent period provide consistent evidence on pre-symptomatic transmission. This together with asymptomatic transmission and the generally longer incubation and serial interval of less severe cases suggests a high risk of long-term epidemic in the absence of appropriate control measures.FundingThis work received no funding from any source.

scholarly journals Seroprevalence of Middle East Respiratory Syndrome Corona Virus in dromedaries and their traders in upper Egypt

2020 ◽  
Vol 14 (02) ◽  
pp. 191-198 ◽  
Author(s):  
Amal SM Sayed ◽  
Safaa S Malek ◽  
Mostafa FN Abushahba
Keyword(s):  
Middle East ◽  
Age Groups ◽  
Control Measures ◽  
Protein Domain ◽  
Seropositivity Rate ◽  
Upper Egypt ◽  
Gender And Age ◽  
History Of ◽  
Specific Igg ◽  
Respiratory Coronavirus

Introduction: Camel trade in Egypt depends mainly on importation. Seemingly healthy imported camels are responsible for the ingress of serious diseases into Egypt. A striking example of this concerning public health globally is the Middle East respiratory coronavirus (MERS-CoV) which causes case fatalities of over 34%. Here, we determined the seroepidemiological situation of the MERS-CoV in imported camels and their traders in Upper Egypt. Methodology: Sera of sixty-three dromedaries and twenty-eight camel traders were recruited (January 2015-December 2016). The age, gender, and sampling locality of each sampled camel and human were obtained. Semi-quantitative anti-MERS-CoV IgG ELISAs which utilize the purified spike protein domain S1 antigen of MERS coronavirus (MERS-CoV S1) were used to detect specific IgG antibodies against the virus. Results: The data showed that 58.73% of imported camels and 25% of traders had antibodies specific to MERS-CoV. Interestingly, like seroreactive camels, all seropositive humans were apparently healthy without any history of developing severe respiratory disease in the 14 days prior to sampling. Having specific antibodies among the examined camel sera was significantly different (P < 0.0001) in relation to various sampling localities, gender and age groups. In contrast, the seropositivity rate of MERS-CoV IgG in humans did not differ significantly by any of the studied factors. Conclusions: The current study provides the first serological evidence of occupational exposure of humans to MERS-CoV in Africa. Additionally, it reports that imported camels could be implicated in introducing MERS-CoV into Egypt. Accordingly, application of strict control measures to camel importation is a priority.

scholarly journals Transmission of corona virus disease 2019 during the incubation period may lead to a quarantine loophole

2020 ◽  
Author(s):  
Wei Xia ◽  
Jiaqiang Liao ◽  
Chunhui Li ◽  
Yuanyuan Li ◽  
Xi Qian ◽  
...  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
First Generation ◽  
Virus Disease ◽  
Demographic Characteristics ◽  
Corona Virus ◽  
Serial Interval ◽  
History Of ◽  
Exposure History ◽  
Close Contacts

AbstractBackgroundThe ongoing outbreak of novel corona virus disease 2019 (COVID-19) in Wuhan, China, is arousing international concern. This study evaluated whether and when the infected but asymptomatic cases during the incubation period could infect others.MethodsWe collected data on demographic characteristics, exposure history, and symptom onset day of the confirmed cases, which had been announced by the Chinese local authorities. We evaluated the potential of transmission during the incubation period in 50 infection clusters, including 124 cases. All the secondary cases had a history of contact with their first-generation cases prior to symptom onset.ResultsThe estimated mean incubation period for COVID-19 was 4.9 days (95% confidence interval [CI], 4.4 to 5.4) days, ranging from 0.8 to 11.1 days (2.5th to 97.5th percentile). The observed mean and standard deviation (SD) of serial interval was 4.1±3.3 days, with the 2.5th and 97.5th percentiles at −1 and 13 days. The infectious curve showed that in 73.0% of the secondary cases, their date of getting infected was before symptom onset of the first-generation cases, particularly in the last three days of the incubation period.ConclusionsThe results indicated the transmission of COVID-9 occurs among close contacts during the incubation period, which may lead to a quarantine loophole. Strong and effective countermeasures should be implemented to prevent or mitigate asymptomatic transmission during the incubation period in populations at high risk.

scholarly journals Transmission characteristics of the COVID-19 outbreak in China: a study driven by data

2020 ◽  
Author(s):  
Meili Li ◽  
Pian Chen ◽  
Qianqian Yuan ◽  
Baojun Song ◽  
Junling Ma
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
First Generation ◽  
Reproduction Number ◽  
Public Awareness ◽  
Control Measures ◽  
Transmission Characteristics ◽  
Median Period ◽  
Sources Of Infection ◽  
And Control

Abstract Background The COVID-19 outbreak has been a serious public health threat worldwide. Individually documented case descriptions of COVID-19 are published by Chinese provinces (excluding Hubei). We use these descriptions to study the transmission characteristics in China, and how they are influenced by public awareness and control measures. Methods Dates for infection, symptom onset, quarantine, hospitalization and diagnosis, and sources of infection are tabulated from published cases descriptions. We use MCMC to estimate the exponential growth rate of cases infected in Hubei, and parametrize the distributions for the incubation period, and periods from symptom onset to hospitalization and diagnosis. Graph of infection is constructed and used to estimate the reproduction number in each generation. Results The median incubation period is 6.2 days overall, and 7.3% patients have an incubation period longer than the recommended 14-day quarantine period. The median period from symptom onset to hospitalization is 4.4 days before the lockdown of Wuhan city, and 2.1 days after the lockdown. The median period from symptom onset to diagnosis is 8.8 days before the lockdown, and 4.8 days after the lockdown. The number of cases in Hubei doubled every 3 days before the lockdown. In other provinces, reproduction number decreased from 1.51 in the first-generation patients to less than 0.21 in later generation patients. Conclusions We parametrized incubation period, and the periods from symptom onset to hospitalization and diagnosis. Some (possibly a majority of) patients were infected before the symptom onset of their sources of infection, causing a low success rate of official (not self) quarantines. Social distancing and self-quarantine greatly reduced the reproduction number, and shorted the periods from symptom onset to hospitalization and diagnosis.

scholarly journals Prevalence and Financial Significance of Bovine Fasciolosis in Oda-Bultum District, West Hararge, Oromia Regional State, Ethiopia

2019 ◽  
Vol 1 (4) ◽  
pp. 103-111
Author(s):  
Kebede Ayele Terefe
Keyword(s):  
Statistical Analysis ◽  
Significant Variation ◽  
Age Groups ◽  
Economic Loss ◽  
Control Measures ◽  
Economic Losses ◽  
Fecal Samples ◽  
Adult Age ◽  
Economic Significance ◽  
Significant Difference

A study was conducted from November 2010 to February 2011 to determine the prevalence and estimate the economic loss of bovine fasciolosis in OdaBultum district based on the carpological examination and abattoir survey. Out of total of 384 fecal samples taken from cattle and examined, 182 (47.39%) were found positive for fasciolosis ,prevalence on months basis revealed higher prevalence rate (48.78%) in January and the lower (43.47%) was observed in November. No statistically significant variation (p>0.05) was observed in the monthly occurrence of the disease. Among the three localities (Godahora, Odaroba and Odabiyyo) from which fecal samples were taken higher infection rate (48.75%) was recorded in Odabiyyo while the lowest (46.27%) was noted at Odaroba. Statistical analysis of the result revealed no significant differences in prevalence among the three localities. Prevalence among the age groups showed 48.32% and 46.75% in young and adult age groups, respectively. No statistically significant difference in prevalence was seen between the two age group (p>0.05). Prevalence on the basis of sexes indicated 50% in male and 45.53 in females but the difference was not statistically significant (p>0.05). A four month post mortem examination of 197 cattle slaughtered at baddessa town municipal abattoir revealed the overall prevalence of 47.68%. Statistical analysis showed that there was no significant variation in monthly prevalence during the study period (p>0.05). Analysis of economic losses associated with liver condemnation in the study abattoir indicated a total of 13,498 ETB has been estimated to be lost each year in the abattoir as a result of fasciolosis. The current study has indicated that disease is of considerable economic significance therefore, calls for implementation of an appropriate control measures.

scholarly journals The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019

2020 ◽  
Vol 5 ◽  
pp. 58 ◽  
Author(s):  
Yang Liu ◽  
Sebastian Funk ◽  
Stefan Flasche ◽  
Keyword(s):  
Incubation Period ◽  
Symptom Onset ◽  
Case Finding ◽  
Mitigation Strategies ◽  
Potential Contribution ◽  
Active Case Finding ◽  
Symptomatic Infection ◽  
Active Case ◽  
Secondary Infections ◽  
Serial Interval

Background: Pre-symptomatic transmission can be a key determinant of the effectiveness of containment and mitigation strategies for infectious diseases, particularly if interventions rely on syndromic case finding. For COVID-19, infections in the absence of apparent symptoms have been reported frequently alongside circumstantial evidence for asymptomatic or pre-symptomatic transmission. We estimated the potential contribution of pre-symptomatic cases to COVID-19 transmission. Methods: Using the probability for symptom onset on a given day inferred from the incubation period, we attributed the serial interval reported from Shenzen, China, into likely pre-symptomatic and symptomatic transmission. We used the serial interval derived for cases isolated more than 6 days after symptom onset as the no active case finding scenario and the unrestricted serial interval as the active case finding scenario. We reported the estimate assuming no correlation between the incubation period and the serial interval alongside a range indicating alternative assumptions of positive and negative correlation. Results: We estimated that 23% (range accounting for correlation: 12 – 28%) of transmissions in Shenzen may have originated from pre-symptomatic infections. Through accelerated case isolation following symptom onset, this percentage increased to 46% (21 – 46%), implying that about 35% of secondary infections among symptomatic cases have been prevented. These results were robust to using reported incubation periods and serial intervals from other settings. Conclusions: Pre-symptomatic transmission may be essential to consider for containment and mitigation strategies for COVID-19.

scholarly journals Assessing asymptomatic, pre-symptomatic and symptomatic transmission risk of SARS-CoV-2

2021 ◽  
Author(s):  
Peng Wu ◽  
Fengfeng Liu ◽  
Zhaorui Chang ◽  
Yun Lin ◽  
Minrui Ren ◽  
...  
Keyword(s):  
Control Measures ◽  
Transmission Risk ◽  
Contact Tracing ◽  
Secondary Infections ◽  
Different Types ◽  
Early Case ◽  
Symptom Status ◽  
Early Case Detection ◽  
Index Cases ◽  
Close Contacts

Abstract Background The relative contributions of asymptomatic, pre-symptomatic and symptomatic transmission of SARS-CoV-2 have not been clearly measured although control measures may differ in response to the risk of spread posed by different types of cases. Methods We collected detailed information on transmission events and symptom status based on laboratory-confirmed patient data and contact tracing data from four provinces and one municipality in China. We estimated the variation in risk of transmission over time, and the severity of secondary infections, by symptomatic status of the infector. Results There were 393 symptomatic index cases with 3136 close contacts and 185 asymptomatic index cases with 1078 close contacts included into the study. The secondary attack rate among close contacts of symptomatic and asymptomatic index cases were 4.1% (128/3136) and 1.1% (12/1078), respectively, corresponding to a higher transmission risk from symptomatic cases than from asymptomatic cases (OR: 3.79, 95% CI: 2.06, 6.95). Approximately 25% (32/128) and 50% (6/12) of the infected close contacts were asymptomatic from symptomatic and asymptomatic index cases, respectively, while more than one third (38%) of the infections in the close contacts of symptomatic cases were attributable to exposure to the index cases before symptom onset. Infected contacts of asymptomatic index cases were more likely to be asymptomatic and less likely to be severe. Conclusions Asymptomatic and pre-symptomatic transmission play an important role in spreading infection, although asymptomatic cases pose a lower risk of transmission than symptomatic cases. Early case detection and effective test-and-trace measures are important to reduce transmission.

Assessment of ST2 for Risk of Death Following Graft-versus-Host Disease in the Pediatric and Adult Age Groups

2019 ◽  
Author(s):  
Courtney Rowan ◽  
Francis Pike ◽  
Kenneth R. Cooke ◽  
Robert Krance ◽  
Paul A. Carpenter ◽  
...  
Keyword(s):  
Graft Versus Host Disease ◽  
Age Groups ◽  
Host Disease ◽  
Adult Age ◽  
Graft Versus Host ◽  
Risk Of Death

An Epidemiological Analysis of COVID-19 Confirmed Cases, Reported at National Institute of Health, Pakistan (Preprint)

2020 ◽  
Author(s):  
Ambreen Chaudhry
Keyword(s):  
Age Groups ◽  
Target Population ◽  
Control Measures ◽  
Contact Tracing ◽  
Bivariate Analysis ◽  
Travel History ◽  
Disease Epidemiology ◽  
Hygiene Practices ◽  
Multi Center Study ◽  
Epidemiological Characteristics

BACKGROUND Coronavirus disease (Covid-19) is a zoonotic disease of novel origin that posed a continuous threat to health worldwide after taking the shape of the pandemic. An understanding of disease epidemiology is supportive in timely preventive and control measures as well as contact tracing and curbing surveillance activities. OBJECTIVE The objective of our study was to determine the epidemiological characteristics of COVID-19 confirmed cases reported at the National Institute of Health Pakistan and elements of its spread in Pakistan. METHODS A retrospective record review was conducted at the National Institute of Health (NIH) Islamabad, Pakistan from January 25 to April 4, 2020. Univariate and bivariate analysis was done with 95% CI and p<0.05. RESULTS A total of 14,422 samples of suspected COVID-19 cases were received with a positivity rate of 9% (n=1348). Among all 70% (n=939) were male. The median age was 41years of age (range: 01-99Years). Among all, 19% were from 30-39 years old followed by 50-59 years old (17%). Children remained the least affected by 3% (n=35). Of the total reported cases, 55% (n=735) have reported the travel history within the last 14 days. Among these travelers’ international travelers were 23% (n=166) and domestic travelers were 77% (n=569). Travel history including both international and domestic remained significantly associated with the different age groups and Young adults remained more vulnerable to COVID-19 (P=0.03). Fever, SOB, and Cough remained the most significantly associated (P<0.05) in all age groups. CONCLUSIONS A higher incidence of COVID-19 among elderly men suggests robust quarantine measures for this target population. An escalating incidence of local transmission needs strict social distancing and hygiene practices to help flatten the curve. An extensive multi-center study is also recommended for a full understanding of disease dynamics.

scholarly journals Predicting COVID-19 mortality with electronic medical records

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hossein Estiri ◽  
Zachary H. Strasser ◽  
Jeffy G. Klann ◽  
Pourandokht Naseri ◽  
Kavishwar B. Wagholikar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Medical Information ◽  
Age Groups ◽  
Prognostic Models ◽  
Smoking History ◽  
Risk Scores ◽  
Gradient Boosting ◽  
Chronic Obstructive ◽  
Clinical Expertise ◽  
History Of

AbstractThis study aims to predict death after COVID-19 using only the past medical information routinely collected in electronic health records (EHRs) and to understand the differences in risk factors across age groups. Combining computational methods and clinical expertise, we curated clusters that represent 46 clinical conditions as potential risk factors for death after a COVID-19 infection. We trained age-stratified generalized linear models (GLMs) with component-wise gradient boosting to predict the probability of death based on what we know from the patients before they contracted the virus. Despite only relying on previously documented demographics and comorbidities, our models demonstrated similar performance to other prognostic models that require an assortment of symptoms, laboratory values, and images at the time of diagnosis or during the course of the illness. In general, we found age as the most important predictor of mortality in COVID-19 patients. A history of pneumonia, which is rarely asked in typical epidemiology studies, was one of the most important risk factors for predicting COVID-19 mortality. A history of diabetes with complications and cancer (breast and prostate) were notable risk factors for patients between the ages of 45 and 65 years. In patients aged 65–85 years, diseases that affect the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and a smoking history, were important for predicting mortality. The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.

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