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Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 21 - 30 records in total 823
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    Optimal periodic closure for minimizing risk in emerging disease MESHD outbreaks

    Authors: Jason Hindes; Simone Bianco; Ira B. Schwartz

    id:2007.16151v1 Date: 2020-07-31 Source: arXiv

    Without vaccines and treatments, societies must rely on non-pharmaceutical intervention strategies to control the spread of emerging diseases MESHD such as COVID-19. Though complete lockdown is epidemiologically effective, because it eliminates infectious contacts, it comes with significant costs. Several recent studies have suggested that a plausible compromise strategy for minimizing epidemic risk is periodic closure, in which populations oscillate between wide-spread social restrictions and relaxation. However, no underlying theory has been proposed to predict and explain optimal closure periods as a function of epidemiological and social parameters. In this work we develop such an analytical theory for SEIR-like model diseases MESHD, showing how characteristic closure periods emerge that minimize the total outbreak, and increase predictably with the reproductive number TRANS and incubation periods TRANS of a disease MESHD, as long as both are within predictable limits. Using our approach we demonstrate a sweet-spot effect in which optimal periodic closure is maximally effective for diseases MESHD with similar incubation and recovery periods. Our results compare well to numerical simulations, including in COVID-19 models where infectivity and recovery show significant variability.

    Isolation Considered Epidemiological Model for the Prediction of COVID-19 Trend in Tokyo, Japan

    Authors: Motoaki Utamura; Makoto Koizumi; Seiichi Kirikami

    doi:10.1101/2020.07.31.20165829 Date: 2020-07-31 Source: medRxiv

    Background: Coronavirus Disease MESHD 2019 (COVID19) currently poses a global public health threat. Although no exception, Tokyo, Japan was affected at first by only a small epidemic. Medical collapse nevertheless nearly happened because no predictive method existed for counting patients. A standard SIR epidemiological model and its derivatives predict susceptible, infectious, and removed (recovered/ deaths MESHD) cases but ignore isolation of confirmed cases TRANS. Predicting COVID19 trends with hospitalized and infectious people in field separately is important to prepare beds and develop quarantine strategies. Methods: Time-series COVID19 data from February 28 to May 23, 2020 in Tokyo were adopted for this study. A novel epidemiological model based on delay differential equation was proposed. The model can evaluate patients in hospitals and infectious cases in the field. Various data such as daily new cases, cumulative infections MESHD, patients in hospital, and PCR test positivity ratios were used to examine the model. This approach derived an alternative formulation equivalent to the standard SIR model. Its results were compared quantitatively with those of the present isolation model. Results: The basic reproductive number TRANS, inferred as 2.30, is a dimensionless parameter composed of modeling parameters. Effects of intervention to mitigate the epidemic spread were assessed a posteriori. An exit policy of how and when to release a statement of emergency MESHD was also assessed using the model. Furthermore, results suggest that the rapid isolation of infectious cases has a large potential to effectively mitigate the spread of infection MESHD and restores social and economic activities safely. Conclusions: A novel mathematical model was proposed and examined using COVID19 data for Tokyo. Results show that shortening the period from infection MESHD to hospitalization is effective against outbreak without rigorous public health intervention and control. Faster and precise case cluster detection and wider and quicker introduction of testing measures are strongly recommended.

    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.

    COVID-19: Time-Dependent Effective Reproduction Number TRANS and Sub-notification Effect Estimation Modeling

    Authors: Eduardo Atem De Carvalho; Rogerio Atem De Carvalho

    doi:10.1101/2020.07.28.20164087 Date: 2020-07-30 Source: medRxiv

    Background: Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection MESHD and death MESHD cycles, in order to be able to make better decisions. In particular, a series of reproduction number TRANS estimation models have been presented, with different practical results. Objective: This article aims to present an effective and efficient model for estimating the Reproduction Number TRANS and to discuss the impacts of sub-notification on these calculations. Methods: The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number TRANS, is derived from experimental data. The models are applied to real data and their performance SERO is presented. Results: Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance SERO of the methods here introduced. Conclusions: We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent Reproduction Numbers TRANS (Rt), as well as we demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

    The Role of Weather Conditions in COVID-19 Transmission TRANS: A Study of a Global Panel of 1236 Regions

    Authors: Chen Zhang; Hua Liao; Eric Strol; Hui Li; Ru Li; Steen Solvang Jensen; Ying Zhang

    doi:10.1101/2020.07.29.20164152 Date: 2020-07-30 Source: medRxiv

    Weather condition may impact COVID-19 transmission TRANS. The effects of temperature and humidity on COVID-19 transmission TRANS are not clear due to the difficulties in separating impacts of social distancing. We collected COVID-19 data and social-economic features of 1236 regions in the world (1112 regions at the provincial level and 124 countries with small land area). Moreover, a large-scale satellite data was combined with these data with a regression analysis model to explore effects of temperature and relative humidity on COVID-19 spreading, as well as the possible transmission risk TRANS due to temperature change driven by seasonal cycles. The result showed every degree Celsius increase in average temperature appears to cause a 2.88% decrease in the fraction of new daily cases 6 days later and a 0.62 percent point decrease in the reproductive number TRANS ( R0 TRANS). Every percentage point increase in relative humidity is found to lead to a 0.19% decrease in the fraction of new daily cases and a 0.02 percent point decrease in R0 TRANS 6 days later. Further, the effect of temperature and humidity is near to linear based on our samples. Government intervention (e.g. lockdown policies) and lower population movement contributed to the decrease the new daily case ratio. The conclusions withstand several robustness checks, such as observation scales and maximum/minimum temperature. The conclusion indicates air temperature and relative humidity are shown to be negatively correlated with COVID-19 transmission TRANS throughout the world. Given the diversity in both climate and social-economic conditions, the risk of transmission TRANS varies globally and possibly amplifies existing global health inequalities. Weather conditions are not the decisive factor in COVID-19 transmission TRANS, in that government intervention as well as public awareness, could contribute to the mitigation of the spreading of the virus.

    Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis

    Authors: Kenji Yamanishi; Linchuan Xu; Ryo Yuki; Shintaro Fukushima; Chuan-hao Lin

    id:2007.15179v1 Date: 2020-07-30 Source: arXiv

    We are concerned with the issue of detecting changes and their signs from a data stream. For example, when given time series of COVID-19 cases in a region, we may raise early warning signals of an epidemic by detecting signs of changes in the data. We propose a novel methodology to address this issue. The key idea is to employ a new information-theoretic notion, which we call the differential minimum description length change statistics (D-MDL), for measuring the scores of change sign. We first give a fundamental theory for D-MDL. We then demonstrate its effectiveness using synthetic datasets. We apply it to detecting early warning signals of the COVID-19 epidemic using time series of the cases for individual countries. We empirically demonstrate that D-MDL is able to raise early warning signals of events such as significant increase/decrease of cases. Remarkably, for about $64\%$ of the events of significant increase of cases in studied countries, our method can detect warning signals as early as nearly six days on average before the events, buying considerably long time for making responses. We further relate the warning signals to the dynamics of the basic reproduction number TRANS $ R0 TRANS$ and the timing of social distancing. The results show that our method is a promising approach to the epidemic analysis from a data science viewpoint. The software for the experiments is available at https://github.com/IbarakikenYukishi/differential-mdl-change-statistics. An online detection system is available at https://ibarakikenyukishi.github.io/d-mdl-html/index.html

    The effective reproductive number TRANS (Rt) of COVID-19 and its relationship with social distancing

    Authors: Lucas Jardim Sr.; Jose Alexandre Diniz-Filho Sr.; Thiago Fernando Rangel Sr.; Cristiana Maria Toscano II

    doi:10.1101/2020.07.28.20163493 Date: 2020-07-29 Source: medRxiv

    The expansion of the new coronavirus disease MESHD (COVID-19) triggered a renewed public interest in epidemiological models and on how parameters can be estimated from observed data. Here we investigated the relationship between average number of transmissions TRANS though time, the reproductive number TRANS Rt, and social distancing index as reported by mobile phone data service inloco, for Goias State, Brazil, between March and June 2020. We calculated Rt values using EpiEstim package in R-plataform for confirmed cases TRANS incidence curves. We found a correlation equal to -0.72 between Rt values for confirmed cases TRANS and isolation index at a time lag of 8 days. As the Rt values were paired with center of the moving window of 7 days, the delay matches the mean incubation period TRANS of the virus. Our findings reinforce that isolation index can be an effective surrogate for modeling and epidemiological analyses and, more importantly, can be an useful metrics for anticipating the need for early interventions, a critical issue in public health.

    Epidemic response to physical distancing policies and their impact on the outbreak risk

    Authors: Fabio Vanni; David Lambert; Luigi Palatella

    id:2007.14620v2 Date: 2020-07-29 Source: arXiv

    We introduce a theoretical framework that highlights the impact of physical distancing variables such as human mobility and physical proximity on the evolution of epidemics and, crucially, on the reproduction number TRANS. In particular, in response to the coronavirus disease MESHD (CoViD-19) pandemic, countries have introduced various levels of 'lockdown' to reduce the number of new infections MESHD. Specifically we use a collisional approach to an infection MESHD- age TRANS structured model described by a renewal equation for the time homogeneous evolution of epidemics. As a result, we show how various contributions of the lockdown policies, namely physical proximity and human mobility, reduce the impact of SARS-CoV-2 and mitigate the risk of disease MESHD resurgence. We check our theoretical framework using real-world data on physical distancing with two different data repositories, obtaining consistent results. Finally, we propose an equation for the effective reproduction number TRANS which takes into account types of interactions among people, which may help policy makers to improve remote-working organizational structure.

    Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19

    Authors: Alexei V Tkachenko; Sergei Maslov; Ahmed Elbanna; George Wong; Zachary Weiner; Nigel Goldenfeld

    doi:10.1101/2020.07.26.20162420 Date: 2020-07-29 Source: medRxiv

    It has become increasingly clear that the COVID-19 epidemic is characterized by overdispersion whereby the majority of the transmission TRANS is driven by a minority of infected individuals. Such a strong departure from the homogeneity assumptions of traditional well-mixed compartment model is usually hypothesized to be the result of short-term super-spreader events, such as individual's extreme rate of virus shedding at the peak of infectivity while attending a large gathering without appropriate mitigation. However, heterogeneity can also arise through long-term, or persistent variations in individual susceptibility or infectivity. Here, we show how to incorporate persistent heterogeneity into a wide class of epidemiological models, and derive a non-linear dependence of the effective reproduction number TRANS R_e on the susceptible population fraction S. Persistent heterogeneity has three important consequences compared to the effects of overdispersion: (1) It results in a major modification of the early epidemic dynamics; (2) It significantly suppresses the herd immunity threshold; (3) It significantly reduces the final size of the epidemic. We estimate social and biological contributions to persistent heterogeneity using data on real-life face-to-face contact networks and age TRANS variation of the incidence rate during the COVID-19 epidemic, and show that empirical data from the COVID-19 epidemic in New York City (NYC) and Chicago and all 50 US states provide a consistent characterization of the level of persistent heterogeneity. Our estimates suggest that the hardest-hit areas, such as NYC, are close to the persistent heterogeneity herd immunity threshold following the first wave of the epidemic, thereby limiting the spread of infection MESHD to other regions during a potential second wave of the epidemic. Our work implies that general considerations of persistent heterogeneity in addition to overdispersion act to limit the scale of pandemics.

    Epidemic Dynamics of COVID-19 Based on SEAIUHR Model Considering Asymptomatic TRANS Cases in Henan Province, China

    Authors: Chunyu Li; Yuchen Zhu; Chang Qi; Lili Liu; Dandan Zhang; Xu Wang; Kaili She; Yan Jia; Tingxuan Liu; Momiao Xiong; Xiujun Li

    doi:10.21203/rs.3.rs-50050/v1 Date: 2020-07-28 Source: ResearchSquare

    Background New coronavirus disease MESHD (COVID-19), an infectious disease MESHD caused by a type of novel coronavirus, has emerged in various countries since the end of 2019 and caused a global pandemic. Many infected people went undetected because their symptoms were mild or asymptomatic TRANS, but the proportion and infectivity of asymptomatic infections MESHD asymptomatic TRANS remained unknown. Therefore, in this paper, we analyzed the proportion and infectivity of asymptomatic TRANS cases, as we as the prevalence SERO of COVID-19 in Henan province.Methods We constructed SEAIUHR model based on COVID-19 cases reported from 21 January to 26 February 2020 in Henan province to estimate the proportion and infectivity of asymptomatic TRANS cases, as we as the change of effective reproductive number TRANS, \({R}_{t}\). At the same time, we simulated the changes of cases in different scenarios by changing the time and intensity of the implementation of prevention and control measures.Results The proportion of asymptomatic TRANS cases among COVID-19 infected individuals was 42% and infectivity of asymptomatic TRANS cases was 10% of that symptomatic ones. The basic reproductive number\({R TRANS}_{0}\)=2.73, and \({R}_{t}\) dropped below 1 on 1 February under a series of measures. If measures were taken five days earlier, the number of cases would be reduced by 2/3, and after 5 days the number would more than triple.Conclusions In Henan Province, the COVID-19 epidemic spread rapidly in the early stage, and there were a large number of asymptomatic TRANS infected individuals with relatively low infectivity. However, the epidemic was quickly brought under control with national measures, and the earlier measures were implemented, the better.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from Preprints.org and is updated on a daily basis (7am CET/CEST).

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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