Corpus overview


Overview

MeSH Disease

Human Phenotype

Falls (10)

Pneumonia (6)

Hypertension (1)

Fever (1)


Transmission

Seroprevalence
    displaying 31 - 40 records in total 149
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    COVID-19 Transmission TRANS Dynamics and Final Epidemic Size

    Authors: Daifeng Duan; Cuiping Wang; Yuan Yuan

    doi:10.21203/rs.3.rs-40695/v1 Date: 2020-07-08 Source: ResearchSquare

    We propose two kinds of compartment models to study the transmission TRANS dynamics of COVID-19 virus and to explore the potential impact of the interventions, to disentangle how transmission TRANS is affected in different age group TRANS. Starting with an SEAIQR model by combining the effect from exposure, asymptomatic TRANS and quarantine, then extending the model to an two groups with ages TRANS below and above 65 years old, and classify the infectious individuals according to their severity, we focus our analysis on each model with and without vital dynamics. In the models with vital dynamics, we study the dynamical properties including the global stability of the disease free equilibrium and the existence of endemic equilibrium, with respect to the basic reproduction number TRANS. Whereas in the models without vital dynamics, we address the final epidemic size rigorously, which is one of the common but difficult questions regarding an epidemic. Finally, using the data of COVID-19 confirmed cases TRANS in Canada and Newfoundland & Labrador province, we can parameterize the models to estimate the basic reproduction number TRANS and the final epidemic size of disease transmission TRANS.

    An Agent Based Modeling of COVID-19: Validation, Analysis, and Recommendations

    Authors: Md. Salman Shamil; Farhanaz Farheen; Nabil Ibtehaz; Irtesam Mahmud Khan; M. Sohel Rahman

    doi:10.1101/2020.07.05.20146977 Date: 2020-07-08 Source: medRxiv

    The Coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted Non-pharmaceutical Interventions (NPI) to slow down the spread. This study proposes an Agent Based Model that simulates the spread of COVID-19 among the inhabitants of a city. The Agent Based Model can be accommodated for any location by integrating parameters specific to the city. The simulation gives the number of daily confirmed cases TRANS. Considering each person as an agent susceptible to COVID-19, the model causes infected individuals to transmit the disease via various actions performed every hour. The model is validated by comparing the simulation to the real data of Ford county, Kansas, USA. Different interventions including contact tracing TRANS are applied on a scaled down version of New York city, USA and the parameters that lead to a controlled epidemic are determined. Our experiments suggest that contact tracing TRANS via smartphones with more than 60% of the population owning a smartphone combined with a city-wide lock-down results in the effective reproduction number TRANS (Rt) to fall HP below 1 within three weeks of intervention. In the case of 75% or more smartphone users, new infections are eliminated and the spread is contained within three months of intervention. Contact tracing TRANS accompanied with early lock-down can suppress the epidemic growth of COVID-19 completely with sufficient smartphone owners. In places where it is difficult to ensure a high percentage of smartphone ownership, tracing TRANS only emergency service providers during a lock-down can go a long way to contain the spread. No particular funding was available for this project.

    Reopening universities during the COVID-19 pandemic: A testing strategy to minimize active cases and delay outbreaks

    Authors: Lior Rennert; Corey Andrew Kalbaugh; Lu Shi; Christopher McMahan

    doi:10.1101/2020.07.06.20147272 Date: 2020-07-07 Source: medRxiv

    Background: University campuses present an ideal environment for viral spread and are therefore at extreme risk of serving as a hotbed for a COVID-19 outbreak. While active surveillance throughout the semester such as widespread testing, contact tracing TRANS, and case isolation, may assist in detecting and preventing early outbreaks, these strategies will not be sufficient should a larger outbreak occur. It is therefore necessary to limit the initial number of active cases at the start of the semester. We examine the impact of pre-semester NAT testing on disease spread TRANS in a university setting. Methods: We implement simple dynamic transmission TRANS models of SARS-CoV-2 infection MESHD to explore the effects of pre-semester testing strategies on the number of active infections MESHD and occupied isolation beds throughout the semester. We assume an infectious period TRANS of 3 days and vary R0 TRANS to represent the effectiveness of disease mitigation strategies throughout the semester. We assume the prevalence SERO of active cases at the beginning of the semester is 5%. The sensitivity SERO of the NAT test is set at 90%. Results: If no pre-semester screening is mandated, the peak number of active infections occurs in under 10 days and the size of the peak is substantial, ranging from 5,000 active infections when effective mitigation strategies ( R0 TRANS = 1.25) are implemented to over 15,000 active infections for less effective strategies ( R0 TRANS = 3). When one NAT test is mandated within one week of campus arrival, effective ( R0 TRANS = 1.25) and less effective ( R0 TRANS = 3) mitigation strategies delay the onset of the peak to 40 days and 17 days, respectively, and result in peak size ranging from 1,000 to over 15,000 active infections. When two NAT tests are mandated, effective ( R0 TRANS = 1.25) and less effective ( R0 TRANS = 3) mitigation strategies delay the onset of the peak through the end of fall HP semester and 20 days, respectively, and result in peak size ranging from less than 1,000 to over 15,000 active infections. If maximum occupancy of isolation beds is set to 2% of the student population, then isolation beds would only be available for a range of 1 in 2 confirmed cases TRANS ( R0 TRANS = 1.25) to 1 in 40 confirmed cases TRANS ( R0 TRANS = 3) before maximum occupancy is reached. Conclusion: Even with highly effective mitigation strategies throughout the semester, inadequate pre-semester testing will lead to early and large surges of the disease and result in universities quickly reaching their isolation bed capacity. We therefore recommend NAT testing within one week of campus return. While this strategy is sufficient for delaying the timing of the outbreak, pre-semester testing would need to be implemented in conjunction with effective mitigation strategies to reduce the outbreak size.

    The reproduction number TRANS R for COVID-19 in England: Why hasn't ''lockdown'' been more effective?

    Authors: Alastair Grant

    doi:10.1101/2020.07.02.20144840 Date: 2020-07-05 Source: medRxiv

    The reproduction number TRANS R, the average number of people that a single individual with a contagious disease infects MESHD, is central to understanding the dynamics of the COVID-19 epidemic. Values greater than one correspond to increasing rates of infection MESHD, and values less than one indicate that control measures are being effective. Here, we summarise how changes in the behaviour of individuals alter the value of R TRANS. We also use matrix models that correctly recreate distributions of times that individuals spend incubating the disease and being infective to demonstrate the accuracy of a simple approximation to estimate R directly from time series of case numbers, hospital admissions or deaths. The largest uncertainty is that the generation time of the infection is not precisely known, but this challenge also affects most of the more complex methods of calculating R. We use this approximation to examine changes in R in response to the introduction of lockdown restrictions in England. This suggests that there was a substantial reduction in R before large scale compulsory restrictions on economic and social activity were imposed on 23rd March 2020. From mid-April to mid-June decline of the epidemic at national and regional level has been relatively slow, despite these restrictions ( R values TRANS clustered around 0.81). However, these estimates of R are consistent with the relatively high average numbers of close contacts TRANS reported by confirmed cases TRANS combined with directly measured attack rates TRANS via close interactions. This implies that a significant portion of transmission TRANS is occurring in workplaces; overcrowded housing or through close contacts TRANS that are not currently lawful, routes on which nationwide lockdown will have limited impact.

    COVID-19 in China: Risk Factors and R0 TRANS Revisited

    Authors: Irtesam Mahmud Khan; Wenyi Zhang; Sumaira Zafar; Yong Wang; Junyu He; Hailong Sun; Jailos Lubinda; Ubydul Haque; M Sohel Rahman

    doi:10.21203/rs.3.rs-39209/v1 Date: 2020-06-30 Source: ResearchSquare

    Background: The COVID-19 epidemic had spread rapidly through China and subsequently has proliferated globally leading to a pandemic situation around the globe. Human-to-human transmissions TRANS, as well as asymptomatic TRANS transmissions TRANS of the infection, have been confirmed TRANS infection, have been confirmed MESHD. As of April 3rd, public health crisis in China due to COVID-19 is potentially under control. Methods: We compiled a daily dataset of case counts, mortality, recovery, temperature, population density, and demographic information for each prefecture during the period of January 11 to April 07, 2020 (excluding Wuhan from our analysis due to missing data). Understanding the characteristics of spatiotemporal clustering of the COVID-19 epidemic and R0 TRANS is critical in effectively preventing and controlling the ongoing global pandemic. The prefectures were grouped based on several relevant features using unsupervised machine learning techniques. We performed a computational analysis utilizing the reported cases in China to estimate the revised R0 TRANS among different regions for prevention planning in an ongoing global pandemic. Results: Finally, our results indicate that the impact of temperature and demographic (different age group TRANS percentage compared to the total population) factors on virus transmission TRANS may be characterized using a stochastic transmission TRANS model. Conclusions: Such predictions will help prioritize segments of a given community/ region for action and provide a visual aid in designing prevention strategies for a specific geographic region. Furthermore, revised estimation and our methodology will aid in improving the human health consequences of COVID-19 elsewhere.

    Superspreading in Early Transmissions TRANS of COVID-19 in Indonesia

    Authors: Agus Hasan; Hadi Susanto; Muhammad Kasim; Nuning Nuraini; Bony Lestari; Dessy Triany; Widyastuti Widyastuti

    doi:10.1101/2020.06.28.20142133 Date: 2020-06-29 Source: medRxiv

    We estimate the basic reproduction number TRANS R0 TRANS and the overdispersion parameter K at two regions in Indonesia: Jakarta-Depok and Batam. Based on the first 1288 confirmed cases TRANS in both regions, we find a high degree of individual-level variation in the transmission TRANS. The basic reproduction number TRANS R0 TRANS is estimated at 6.79 and 2.47, while the overdispersion parameter K of a negative-binomial distribution is estimated at 0.06 and 0.2 for Jakarta-Depok and Batam, respectively. This suggests that superspreading events played a key role in the early stage of the outbreak, i.e., a small number of infected MESHD individuals are responsible for large amounts of COVID-19 transmission TRANS.

    Data presented by the UK government as lockdown was eased shows the transmission TRANS of COVID-19 had already increased.

    Authors: Mike Lonergan

    doi:10.1101/2020.06.28.20141960 Date: 2020-06-29 Source: medRxiv

    Background: Coronavirus disease 2019 (COVID-19) is an international emergency that has been addressed in many countries by changes in and restrictions on behaviour. These are often collectively labelled social distancing and lockdown. On the 23rd June 2020, Boris Johnson, the Prime Minister of the United Kingdom announced substantial easings of restrictions. This paper examines some of the data he presented. Methods: Generalised additive models, with negative binomial errors and cyclic term representing day-of-week effects, were fitted to data on the daily numbers of new confirmed cases TRANS of COVID-19. Exponential rates for the epidemic were estimated for different periods, and then used to calculate R, the reproduction number TRANS, for the disease in different periods. Results: After an initial stabilisation, the lockdown reduced R to around 0.81 (95% CI: 0.79, 0.82). This value increased to around 0.94 (95% CI 0.89, 0.996) for the fortnight from the 9th June 2020. Conclusions: Official UK data, presented as the easing of the lockdown was announced, shows that R was already more than half way back to 1 at that point. That suggests there was little scope for the announced changes to be implemented without restarting the spread of the disease TRANS.

    Contact Tracing TRANS Evaluation for COVID-19 Transmission TRANS during the Reopening Phase in a Rural College Town

    Authors: Sifat afroj Moon; Caterina Scoglio

    doi:10.1101/2020.06.24.20139204 Date: 2020-06-26 Source: medRxiv

    Contact tracing TRANS can play a vital role in controlling human-to-human transmission TRANS of a highly contagious disease such as COVID-19. To investigate the benefits and costs of contact tracing TRANS, we develop an individual- based contact TRANS-network model and a susceptible-exposed-infected-confirmed (SEIC) epidemic model for the stochastic simulations of COVID-19 transmission TRANS. We estimate the unknown parameters (reproductive ratio R0 TRANS and confirmed rate {delta}2) by using observed confirmed case TRANS data. After a two month-lockdown, states in the USA have started the reopening process. We provide simulations for four different reopening situations: under "stay-at-home" order or no reopening, 25% reopening, 50% reopening, and 75% reopening. We model contact tracing TRANS in a two-layer network by modifying the basic SEIC epidemic model. The two-layer network is composed by the contact network in the first layer and the tracing TRANS network in the second layer. Since the full contact list of an infected individual patient can be hard to obtain, then we consider different fractions of contacts from 60% to 5%. The goal of this paper is to assess the effectiveness of contact tracing TRANS to control the COVID-19 spreading in the reopening process. In terms of benefits, simulation results show that increasing the fraction of traced contacts TRANS decreases the size of the epidemic. For example, tracing TRANS 20% of the contacts is enough for all four reopening scenarios to reduce the epidemic size by half. Considering the act of quarantining susceptible households as the contact TRANS tracing TRANS cost, we have observed an interesting phenomenon. When we increase the fraction of traced contacts TRANS from 5% to 20%, the number of quarantined susceptible people increases because each individual confirmed case TRANS is mentioning more contacts. However, when we increase the fraction of traced contacts TRANS from 20% to 60%, the number of quarantined susceptible people decreases because the increment of the mentioned contacts is balanced by a reduced number of confirmed cases TRANS. The main contribution of this research lies in the investigation of the effectiveness of contact tracing TRANS for the containment of COVID-19 spreading during the initial phase of the reopening process of the USA.

    Bayesian approach for modelling the dynamic of COVID-19 outbreak on the Diamond Princess Cruise Ship

    Authors: Chao-Chih Lai; Chen-Yang Hsu; Hsiao-Hsuan Jen; Ming-Fang Yen; Chang-Chuan Chan; Hsiu-Hsi Chen

    doi:10.1101/2020.06.21.20136465 Date: 2020-06-23 Source: medRxiv

    The outbreaks of acute respiratory infectious disease MESHD with high attack rates TRANS on cruise ships were rarely studied. The outbreak of COVID-19 on the Diamond Princess Cruise Ship provides an unprecedented opportunity to estimate its original transmissibility TRANS with basic reproductive number TRANS ( R0 TRANS) and the effectiveness of containment measures. The traditional deterministic approach for estimating R0 TRANS is based on the outbreak of a large population size rather than that a small cohort of cruise ship. The parameters are therefore fraught with uncertainty. To tackle this problem, we developed a Bayesian Susceptible-Exposed-Infected-Recovery (SEIR) model with ordinary differential equation (ODE) to estimate three parameters, including transmission TRANS coefficients, the latent period, and the recovery rate given the uncertainty implicated the outbreak of COVID-19 on cruise ship with modest population size. Based on the estimated results on these three parameters before the introduction of partial containment measures, the natural epidemic curve after intervention was predicted and compared with the observed curve in order to assess the efficacy of containment measures. With the application of the Bayesian model to the empirical data on COVID-19 outbreak on the Diamond Princess Cruise Ship, the R0 TRANS was estimated as high as 5.71(95% credible interval: 4.08-7.55) because of its aerosols and fomite TRANS transmission TRANS mode. The simulated trajectory shows the entire epidemic period without containment measurements was approximately 47 days and reached the peak one month later after the index case. The partial containment measure reduced 34% (95% credible interval: 31-36%) infected passengers. Such a discovery provides an insight into timely evacuation and early isolation and quarantine with decontamination for containing other cruise ships and warship outbreaks.

    The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial cities

    Authors: Ting Tian; Wenxiang Luo; Yukang Jiang; Minqiong Chen; Wenliang Pan; Jiashu Zhao; Songpan Yang; Heping Zhang; Xueqin Wang

    doi:10.1101/2020.06.22.20137380 Date: 2020-06-23 Source: medRxiv

    Background The outbreak of novel coronavirus disease MESHD (COVID-19) has spread around the world since it was detected in December 2019. As the starting place of COVID-19 pandemic, the Chinese government executed a series of interventions to curb the pandemic. The "battle" against COVID-19 in Shenzhen, China is valuable because populated industrial cities are the epic centers of COVID-19 in many regions. Methods We used synthetic control methods to compare the spread of COVID-19 between Shenzhen and its counterpart regions that didn't implement interventions for the total duration of 16 days starting from the day of the first reported case in compared locations. The hypothetical epidemic situations in Shenzhen were inferred by using time-varying reproduction numbers TRANS, assuming the interventions were delayed by 0 day to 5 days. Results The expected cumulative confirmed cases TRANS would be 1307, is which 4.86 times of 269 observed cumulative confirmed cases TRANS in Shenzhen on February 3, 2020, based on the data from the counterpart counties (mainly from Broward, New York, Santa Clara, Westchester and Orange) in the United States. If the interventions were delayed 5 days from the day when the interventions started, the expected cumulative confirmed cases TRANS of COVID-19 in Shenzhen on February 3, 2020 would be 676 with 95% CI (303,1959). Conclusions Early implementation of mild interventions can subdue the epidemic of COVID-19. The later the interventions were implemented, the more severe the epidemic was in the hard-hit areas. Mild interventions are less damaging to the society but can be effective when implemented early.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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