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Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
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    A variational model for computing the effective reproduction number TRANS of SARS-CoV-2

    Authors: Luis Alvarez; Miguel Colom; Jean-Michel Morel

    doi:10.1101/2020.08.01.20165142 Date: 2020-08-04 Source: medRxiv

    We propose a variational model for computing the effective reproduction number TRANS (ERN) of SARS-CoV-2 from the daily count of incident cases. This computation only requires the knowledge of the serial interval TRANS. The ERN estimate is made through the minimization of a functional that includes: (i) the adjustment of the incidence curve using an epidemiological model, (ii) the regularity of the estimation of the ERN and, (iii) the adjustment of the initial value to an initial estimate of R_0 TRANS obtained from the initial exponential growth of the epidemic. The model does not assume any statistical distribution for the ERN and, more importantly, does not require truncating the serial interval TRANS when its distribution contains negative days. A comparative study has been carried out with the standard EpiEstim method. For a particular choice of the parameters of the variational model and of the serial interval TRANS, a good agreement has been obtained between the estimate provided by the variational model and a 7 days shifted estimate obtained by EpiEstim. This backward shift suggests that our estimate is closer to present than that of EpiEstim. We also examine how to forecast the value of the ERN and the number of infected in the short term by two different extrapolation techniques. An implementation of the model is available online at www.ipol.im/ern.

    Epidemiological characteristics of SARS-COV-2 in Myanmar

    Authors: Aung Min Thway; Htun Tayza; Tun Tun Win; Ye Minn Tun; Moe Myint Aung; Yan Naung Win; Kyaw M Tun

    doi:10.1101/2020.08.02.20166504 Date: 2020-08-04 Source: medRxiv

    Coronavirus disease MESHD (COVID-19) is an infectious disease MESHD caused by a newly discovered severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2). In Myanmar, first COVID-19 reported cases were identified on 23rd March 2020. There were 336 reported confirmed cases TRANS, 261 recovered and 6 deaths MESHD through 13th July 2020. The study was a retrospective case series and all COVID-19 confirmed cases TRANS from 23rd March to 13th July 2020 were included. The data series of COVID-19 cases were extracted from the daily official reports of the Ministry of Health and Sports (MOHS), Myanmar and Centers for Disease MESHD Control and Prevention (CDC), Myanmar. Among 336 confirmed cases TRANS, there were 169 cases with reported transmission TRANS events. The median serial interval TRANS was 4 days (IQR 3, 2-5) with the range of 0 - 26 days. The mean of the reproduction number TRANS was 1.44 with (95% CI = 1.30-1.60) by exponential growth method and 1.32 with (95% CI = 0.98-1.73) confident interval by maximum likelihood method. This study outlined the epidemiological characteristics and epidemic parameters of COVID-19 in Myanmar. The estimation parameters in this study can be comparable with other studies and variability of these parameters can be considered when implementing disease MESHD control strategy in Myanmar.

    Estimating the reproductive number TRANS R0 TRANS of SARS-CoV-2 in the United States and eight European countries and implications for vaccination

    Authors: Ruian Ke; Ethan Obie Romero-Severson; Steven Sanche; Nick Hengartner

    doi:10.1101/2020.07.31.20166298 Date: 2020-08-04 Source: medRxiv

    SARS-CoV-2 rapidly spread from a regional outbreak to a global pandemic in just a few months. Global research efforts have focused on developing effective vaccines against SARS-CoV-2 and the disease MESHD it causes, COVID-19. However, some of the basic epidemiological parameters, such as the exponential epidemic growth rate and the basic reproductive number TRANS, R0 TRANS, across geographic areas are still not well quantified. Here, we developed and fit a mathematical model to case and death MESHD count data collected from the United States and eight European countries during the early epidemic period before broad control measures were implemented. Results show that the early epidemic grew exponentially at rates between 0.19-0.29/day (epidemic doubling times between 2.4-3.6 days). We discuss the current estimates of the mean serial interval TRANS, and argue that existing evidence suggests that the interval is between 6-8 days in the absence of active isolation efforts. Using parameters consistent with this range, we estimated the median R0 TRANS value to be 5.8 (confidence interval: 4.7-7.3) in the United States and between 3.6 and 6.1 in the eight European countries. This translates to herd immunity thresholds needed to stop transmission TRANS to be between 73% and 84%. We further analyze how vaccination schedules depends on R0 TRANS, the duration of vaccine-induced immunity to SARS-CoV-2, and show that individual-level heterogeneity in vaccine induced immunity can significantly affect vaccination schedules.

    The basic reproduction number TRANS of SARS-CoV-2: a scoping review of available evidence

    Authors: Ann Barber; John M Griffin; Miriam Casey; Aine Collins; Elizabeth A Lane; Quirine Ten Bosch; Mart De Jong; David Mc Evoy; Andrew W Byrne; Conor G McAloon; Francis Butler; Kevin Hunt; Simon J More

    doi:10.1101/2020.07.28.20163535 Date: 2020-07-30 Source: medRxiv

    Background: The transmissibility TRANS of SARS-CoV-2 determines both the ability of the virus to invade a population and the strength of intervention that would be required to contain or eliminate the spread of infection MESHD. The basic reproduction number TRANS, R0 TRANS, provides a quantitative measure of the transmission TRANS potential of a pathogen. Objective: Conduct a scoping review of the available literature providing estimates of R0 TRANS for SARS-CoV-2, provide an overview of the drivers of variation in R0 TRANS estimates and the considerations taken in the calculation of the parameter. Design: Scoping review of available literature between the 01 December 2019 and 07 May 2020. Data sources: Both peer-reviewed and pre-print articles were searched for on PubMed, Google Scholar, MedRxiv and BioRxiv. Selection criteria: Studies were selected for review if (i) the estimation of R0 TRANS represented either the initial stages of the outbreak or the initial stages of the outbreak prior to the onset of widespread population restriction (lockdown), (ii) the exact dates of the study period were provided and (iii) the study provided primary estimates of R0 TRANS. Results: A total of 20 R0 TRANS estimates were extracted from 15 studies. There was substantial variation in the estimates reported. Estimates derived from mathematical models fell HP within a wider range of 1.94-6.94 than statistical models which fell HP between the range of 2.2 to 4.4. Several studies made assumptions about the length of the infectious period TRANS which ranged from 5.8-20 days and the serial interval TRANS which ranged from 4.41-14 days. For a given set of parameters a longer duration of infectiousness or a longer serial interval TRANS equates to a higher R0 TRANS. Several studies took measures to minimise bias in early case reporting, to account for the potential occurrence of super-spreading events, and to account for early sub-exponential epidemic growth. Conclusions: The variation in reported estimates of R0 TRANS reflects the complex nature of the parameter itself, including the context (i.e. social/spatial structure), the methodology used to estimate the parameter, and model assumptions. R0 TRANS is a fundamental parameter in the study of infectious disease MESHD dynamics however it provides limited practical applicability outside of the context in which it was estimated, and should be calculated and interpreted with this in mind.

    Infectivity, susceptibility, and risk factors associated with SARS-CoV-2 transmission TRANS under intensive contact tracing TRANS in Hunan, China

    Authors: Shixiong Hu; Wei Wang; Yan Wang; Maria Litvinova; Kaiwei Luo; Lingshuang Ren; Qianlai Sun; Xinghui Chen; Ge Zeng; Jing Li; Lu Liang; Zhihong Deng; Wen Zheng; Mei Li; Hao Yang; Jinxin Guo; Kai Wang; Xinhua Chen; Ziyan Liu; Han Yan; Huilin Shi; Zhiyuan Chen; Yonghong Zhou; Kaiyuan Sun; Alessandro Vespignani; Cécile Viboud; Lidong Gao; Marco Ajelli; Hongjie Yu

    doi:10.1101/2020.07.23.20160317 Date: 2020-07-24 Source: medRxiv

    Abstract Importance Several parameters driving the transmission TRANS of severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) remain unclear, including age TRANS-specific differences in infectivity and susceptibility, and the contribution of inapparent infections MESHD to transmission TRANS. Robust estimates of key time-to-event distributions remain scarce as well. Objective Illustrate SARS-CoV-2 transmission TRANS patterns and risk factors, and estimate key time-to-event distributions. Design, Setting, and Participants Individual-based data on 1,178 SARS-CoV-2 infected individuals and their 15,648 contacts identified by contact tracing TRANS monitoring over the period from January 13-April 02, 2020 were extracted from the notifiable infectious diseases MESHD reporting system in Hunan Province, China. Demographic characteristics, severity classification, exposure and travel TRANS history, and key clinical timelines were retrieved. Exposures Confirmed SARS-CoV-2 infection MESHD by positive polymerase chain reaction test result of respiratory samples, and exposure to SARS-CoV-2 infected individuals via household, relative, social, and other types of contacts. Main Outcomes and Measures The relative contribution of pre-symptomatic and asymptomatic TRANS transmission TRANS, key time-to-event parameters, and the effect of biological, demographic, and behavioral factors on SARS-CoV-2 infectivity and susceptibility were quantified. Results Among SARS-CoV-2 infected individuals, the estimated mean serial interval TRANS was 5.5 days (95%CI -5.0, 19.9) and the mean generation time was 5.5 days (95%CI 1.7, 11.6). Infectiousness was estimated to peak 1.8 days before symptom onset TRANS, with 95% of transmission TRANS events occurring between -7.6 days and 7.3 days from the date of symptom onset TRANS. The proportion of pre-symptomatic transmission TRANS was estimated at 62.5%, while a lower bound for the proportion of asymptomatic TRANS transmission TRANS was 3.5%. Infectiousness of SARS-CoV-2 was not significantly different between working- age TRANS adults TRANS (15-59 years old) and other age groups TRANS (0-14 years old: p-value=0.16; 60 years and over: p-value=0.33), whilst susceptibility to SARS-CoV-2 infection MESHD was estimated to increase with age TRANS (p-value=0.03). In addition, transmission risk TRANS was higher for household contacts TRANS (p-value<0.001), but decreased in later generations of a cluster (second generation: OR=0.13, p-value<0.001; generations 3-4: OR=0.05, p-value<0.001, relative to generation 1) and for those exposed to infectors with a larger number of contacts (p-value=0.04). Conclusions and Relevance These findings support the contribution of children TRANS to transmission TRANS and the importance of pre-symptomatic transmission TRANS, in turn highlighting the importance of large-scale testing, contact tracing TRANS activities, and the use of personnel protective equipment during the COVID-19 pandemic.

    Model-free estimation of COVID-19 transmission TRANS dynamics from a complete outbreak

    Authors: Alex James; Michael J Plank; Shaun Hendy; Rachelle N Binny; Audrey Lustig; Nic Steyn

    doi:10.1101/2020.07.21.20159335 Date: 2020-07-24 Source: medRxiv

    Background New Zealand had 1499 cases of COVID-19 before eliminating transmission TRANS of the virus. Extensive contract tracing TRANS during the outbreak has resulted in a dataset of epidemiologically linked cases. This data contains useful information about the transmission TRANS dynamics of the virus, its dependence on factors such as age TRANS, and its response to different control measures. Method We use Monte-Carlo network construction techniques to provide an estimate of the number of secondary cases TRANS for every individual infected during the outbreak. We then apply standard statistical techniques to quantify differences between groups of individuals. Findings Children TRANS under 10 years old are significantly under-represented in the case data. Children TRANS infected fewer people on average and had a lower secondary attack rate TRANS in comparison to adults TRANS and the elderly TRANS. Imported cases infected fewer people on average and had a lower secondary attack rate TRANS than domestically acquired cases. Superspreading is a significant contributor to the epidemic dynamics, with 20% of cases among adults TRANS responsible for 65-85% of transmission TRANS. Asymptomatic TRANS cases infected fewer individuals than clinical cases. Serial intervals TRANS are approximately normally distributed (=5.0 days, {sigma}=5.7 days). Early isolation and quarantine of cases reduced secondary transmission TRANS rates. Interpretation Border controls and strong social distancing measures, particularly when targeted at superspreading, play a significant role in reducing the spread of COVID-19. Funding Te P[u]naha Matatini, the New Zealand Centre of Research Excellence in complex systems. New Zealand Ministry of Business, Innovation and Employment.

    Regional variability in time-varying transmission TRANS potential of COVID-19 in South Korea

    Authors: Eunha Shim; Gerardo Chowell

    doi:10.1101/2020.07.21.20158923 Date: 2020-07-22 Source: medRxiv

    In South Korea, the total number of the 2019 novel coronavirus disease MESHD (COVID-19) cases is 13,711 including 293 deaths MESHD as of July 18, 2020. To examine the change of the growth rate of the outbreak, we present estimates of the transmissibility TRANS of COVID-19 in the four most affected regions in the country: Seoul, Gyeonggi Province, Gyeongbuk Province, and Daegu. The daily confirmed COVID-19 cases in these regions were extracted from publicly available sources. We estimated the time-varying reproduction numbers TRANS in these regions by using the renewable equation determined by the serial interval TRANS of COVID-19. In Seoul and Gyeonggi Province, the first major peak of COVID-19 occurred in early March, with the estimated reproduction number TRANS in February being as high as 4.24 and 8.86, respectively. In Gyeongbuk Province, the reproduction number TRANS reached 3.49 in February 8 and declined to a value below 1.00 on March 10, 2020, and similarly in Daegu, it decreased from 4.38 to 1.00 between February 5 and March 5. However, the loosening of the restrictions imposed by the government has triggered a resurgence of new cases in all regions considered, resulting in a reproduction number TRANS in May 2020 estimated at 3.04 and 4.78 in Seoul and Gyeonggi Province, repectively. Even though our findings indicate the effectiveness of the control measures against COVID-19 in Korea, they also indicate the potential resurgence and sustained transmission TRANS of COVID-19, supporting the continuous implementation of social distancing measures to control the outbreak.

    Estimation of Effective Reproduction Numbers TRANS for COVID-19 using Real-Time Bayesian Method for India and its States

    Authors: Rishabh Tyagi; Laxmi Kant Dwivedi; Ashutosh Sanzgiri

    doi:10.21203/rs.3.rs-45937/v1 Date: 2020-07-20 Source: ResearchSquare

    WHO declared the outbreak of the novel Coronavirus, COVID-19, as a pandemic on 11th March. On 24th March, a three-week nation-wide lockdown has been announced, which is now extended till 31st May. Effective Reproduction Number TRANS (Rt) helps in understanding how effective preventive measures have been in controlling an outbreak. This study assesses the impact of nation-wide lockdown in slowing down the spread of the COVID-19 at the national and state level. An attempt has also been made to examine the important state-level factors responsible for the uneven distribution of Rt of COVID-19 across different states of India. Bayesian approach based on the probabilistic formulation of standard SIR disease MESHD transmission TRANS models have been employed assuming serial interval TRANS of 4 days and basic reproduction number TRANS ( R0 TRANS) of three. India’s Rt has declined from 1.81 (90% HDI: 1.64, 2.00) on 1st April to Rt =1.04 (90% HDI: 0.96, 1.13) on 9th May, after that it started increasing, and Rt =1.14 (90% HDI: 1.06, 1.21) was observed on 17th May. The value of Rt at the state level has shown significant variations. The testing rate had a significant impact in reducing the Rt at the state-level. The strategy of lockdown has contributed to containing the spread of the virus to some extent, but India still has a long way to go. Testing Rate is the most significant factor at state-level, as Testing and isolating patients sooner significantly reduces the disease MESHD disease spread TRANS spread.

    Epidemiological Profile and Transmission TRANS Dynamics of COVID-19 in the Philippines

    Authors: Nel Jason Ladiao Haw; Jhanna Uy; Karla Therese L. Sy

    doi:10.1101/2020.07.15.20154336 Date: 2020-07-20 Source: medRxiv

    The Philippines confirmed local transmission TRANS of COVID-19 on 7 March 2020. We described the characteristics and epidemiological time-to-event distributions for laboratory- confirmed cases TRANS in the Philippines. The median age TRANS of 8,212 cases was 46 years (IQR: 32-61), with 46.2% being female TRANS and 68.8% living in the National Capital Region. Health care workers represented 24.7% of all detected infections MESHD. Mean length of hospitalization for those who were discharged or died were 16.00 days (95% CI: 15.48, 16.54) and 7.27 days (95% CI: 6.59, 8.24). Mean duration of illness was 26.66 days (95% CI: 26.06, 27.28) and 12.61 days (95% CI: 11.88, 13.37) for those who recovered or died. Mean serial interval TRANS was 6.90 days (95% CI: 5.81, 8.41). Epidemic doubling time pre-quarantine (11 February and 19 March) was 4.86 days (95% CI: 4.67, 5.07) and the reproductive number TRANS was 2.41 (95% CI: 2.33, 2.48). During quarantine (March 20 to April 9), doubling time was 12.97 days (95% CI: 12.57, 13.39) and the reproductive number TRANS was 0.89 (95% CI: 0.78, 1.02).

    Time-dependent dynamic transmission TRANS potential and instantaneous reproduction number TRANS of COVID-19 pandemic in India.

    Authors: Gurpreet Singh; Seema Patrikar; PS Sarma; Biju Soman

    doi:10.1101/2020.07.15.20154971 Date: 2020-07-16 Source: medRxiv

    Introduction: Dynamic tools and methods to assess the ongoing transmission TRANS potential of COVID-19 in India are required. We aim to estimate time-dependent transmissibility TRANS of COVID-19 for India using a reproducible framework. Methods: Daily COVID-19 case incidence time series for India and its states were obtained from https://api.covid19india.org/ and pre-processed. The Bayesian approach was adopted to quantify transmissibility TRANS at a given location and time, as indicated by the instantaneous reproduction number TRANS (Reff). The analysis was carried out in R version 4.0.2 using -EpiEstim_2.2-3- package. Serial interval TRANS distribution was estimated using -uncertain_si- algorithm with inputs of mean, standard deviation, minimum and maximum of mean serial intervals TRANS as 5.1, 1.2, 3.9 and 7.5 days respectively; and mean, standard deviation, minimum, and maximum of standard deviations of the serial interval TRANS as 3.7, 0.9, 2.3, and 4.7 respectively with 100 simulations and moving average of seven days. Results. A total of 9,07,544 cumulative incident cases till July 13th, 2020 were analysed. Daily COVID-19 incidence in the country was seen on the rise; however, transmissibility TRANS showed a decline from the initial phases of COVID-19 pandemic in India. The maximum Reff reached at the national level during the study period was 2.57 (sliding week ending April 4th, 2020). Reff on July 13th, 2020 for India was 1.16 with a range from 0.59 to 2.98 across various states/UTs. Conclusion. Reff provides critical feedback for assessment of transmissibility TRANS of COVID-19 and thus is a potential dynamic decision support tool for on-ground public health decision making

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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