Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 1 - 10 records in total 353
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    Genomic epidemiology reveals transmission TRANS patterns and dynamics of SARS-CoV-2 in Aotearoa New Zealand

    Authors: Jemma L Geoghegan; Xiaoyun Ren; Matthew Storey; James Hadfield; Lauren Jelley; Sarah Jefferies; Jill Sherwood; Shevaun Paine; Sue Huang; Jordan Douglas; Fabio K L Mendes; Andrew Sporle; Michael G Baker; David R Murdoch; Nigel French; Colin R Simpson; David Welch; Alexei J Drummond; Edward C Holmes; Sebastian Duchene; Joep de Ligt

    doi:10.1101/2020.08.05.20168930 Date: 2020-08-06 Source: medRxiv

    New Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nation-wide lockdown of all non-essential services to curb the spread of COVID-19. New Zealand has now effectively eliminated the virus, with low numbers of new cases limited to new arrivals in managed quarantine facilities at the border. Here, we generated 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected between 26 February and 22 May 2020, representing 56% of all confirmed cases TRANS in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. The proportion of D614G variants in the virus spike protein increased over time due to an increase in their importation frequency, rather than selection within New Zealand. These data also helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number TRANS, Re, of New Zealand's largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in a transmission TRANS lineage of more than one additional case. Most of the cases that resulted in a transmission TRANS lineage originated from North America, rather than from Asia where the virus first emerged or from the nearest geographical neighbour, Australia. Genomic data also helped link more infections MESHD to a major transmission TRANS cluster than through epidemiological data alone, providing probable sources of infections MESHD for cases in which the source was unclear. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease MESHD mitigation.

    Analysis of COVID-19 and comorbidity co- infection MESHD Model with Optimal Control

    Authors: Dr. Andrew Omame; Nometa Ikenna

    doi:10.1101/2020.08.04.20168013 Date: 2020-08-04 Source: medRxiv

    The new coronavirus disease MESHD 2019 (COVID-19) infection MESHD is a double challenge for people infected with comorbidities such as cardiovascular and cerebrovascular diseases MESHD and diabetes. Comorbidities have been reported to be risk factors for the complications of COVID-19. In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 infection MESHD in order to assess the impacts of prior comorbidity on COVID-19 complications and COVID-19 re- infection MESHD. The model is simulated using data relevant to the dynamics of the diseases MESHD in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection MESHD by comorbid susceptibles as well as the rate of re- infection MESHD by those who have recovered from a previous COVID-19 infection MESHD. Sensitivity SERO analysis of the model when the population of individuals co-infected with COVID-19 and comorbidity is used as response function revealed that the top ranked parameters that drive the dynamics of the co- infection MESHD model are the effective contact rate for COVID-19 transmission TRANS, $\beta\sst{cv}$, the parameter accounting for increased susceptibility to COVID-19 by comorbid susceptibles, $\chi\sst{cm}$, the comorbidity development rate, $\theta\sst{cm}$, the detection rate for singly infected and co-infected individuals, $\eta_1$ and $\eta_2$, as well as the recovery rate from COVID-19 for co-infected individuals, $\varphi\sst{i2}$. Simulations of the model reveal that the cumulative confirmed cases TRANS (without comorbidity) may get up to 180,000 after 200 days, if the hyper susceptibility rate of comorbid susceptibles is as high as 1.2 per day. Also, the cumulative confirmed cases TRANS (including those co-infected with comorbidity) may be as high as 1000,000 cases by the end of November, 2020 if the re- infection MESHD rates for COVID-19 is 0.1 per day. It may be worse than this if the re- infection MESHD rates increase higher. Moreover, if policies are strictly put in place to step down the probability of COVID-19 infection MESHD by comorbid susceptibles to as low as 0.4 per day and step up the detection rate for singly infected individuals to 0.7 per day, then the reproduction number TRANS can be brought very low below one, and COVID-19 infection MESHD eliminated from the population. In addition, optimal control and cost-effectiveness analysis of the model reveal that the the strategy that prevents COVID-19 infection MESHD by comorbid susceptibles has the least ICER and is the most cost-effective of all the control strategies for the prevention of COVID-19.

    Waves of COVID-19 pandemic. Detection and SIR simulations

    Authors: Igor Nesteruk

    doi:10.1101/2020.08.03.20167098 Date: 2020-08-04 Source: medRxiv

    Background. Unfortunately, the COVID-19 pandemic is still far from stabilizing. Of particular concern is the sharp increase in the number of diseases MESHD in June-July 2020. The causes and consequences of this sharp increase in the number of cases are still waiting for their researchers, but there is already an urgent need to assess the possible duration of the pandemic, the expected number of patients and deaths MESHD. The resumption of international passenger traffic needs the information for deciding which countries' citizens are welcome guests. Correct simulation of the infectious disease MESHD dynamics needs complicated mathematical models and many efforts for unknown parameters identification. Constant changes in the pandemic conditions (in particular, the peculiarities of quarantine and its violation, situations with testing and isolation of patients) cause various epidemic waves, lead to changes in the parameter values of the mathematical models. Objective. In this article, pandemic waves in Ukraine and in the world will be detected, calculated and discussed. The estimations for hidden periods, epidemic durations and final numbers of cases will be presented. The probabilities of meeting a person spreading the infection MESHD and reproduction numbers TRANS will be calculated for different countries and regions. Methods. We propose a simple method for the epidemic waves detection based on the differentiation of the smoothed number of cases. We use the known SIR (susceptible-infected-removed) model for the dynamics of the epidemic waves. The known exact solution of the SIR differential equations and statistical approach were modified and used. Results. The optimal values of the SIR model parameters were identified for four waves of pandemic dynamics in Ukraine and five waves in the world. The number of cases and the number of patients spreading the infection MESHD versus time were calculated. In particular, the pandemic probably began in August 2019. If current trends continue, the end of the pandemic should be expected no earlier than in March 2021 both in Ukraine and in the world, the global number of cases will exceed 20 million. The probabilities of meeting a person spreading the infection MESHD and reproduction numbers TRANS were calculated for different countries and regions. Conclusions. The SIR model and statistical approach to the parameter identification are helpful to make some reliable estimations of the epidemic waves. The number of persons spreading the infection MESHD versus time was calculated during all the epidemic waves. The obtained information will be useful to regulate the quarantine activities, to predict the medical and economic consequences of the pandemic and to decide which countries' citizens are welcome guests.

    Modified SIR-model applied to covid-19, similarity solutions and projections to further development

    Authors: Eckhard Rebhan

    doi:10.1101/2020.07.30.20165035 Date: 2020-08-03 Source: medRxiv

    The SIR-model is adapted to the covid-19 pandemic through a modification that consists in making the basic reproduction number TRANS variable. Independent of it, another reproduction number TRANS is introduced, which is defined similarly to the usual net reproduction number TRANS. Due to its simple analytic form, it enables a clear interpretation for all values. A further parameter, provisionally called acceleration parameter, is introduced and applied, which enables a more differentiated characterization of the infection MESHD number dynamics. By a variable transformation the 3 equations of the modified SIR-model can be reduced to 2. The latter are solved up to ordinary integrations. The solutions are evaluated for current situations, yielding a pretty good match with the data reported. Encouraged by this, a variety of possible future developments is examined, including linear and exponential growth of the infection MESHD numbers as well as sub- and super-exponential growth. In particular, the behavior of the two reproduction numbers TRANS and the acceleration parameter is studied, which in some cases leads to surprising results. With regard to the number of unreported infections MESHD it is shown, that from the solution for a special one solutions for others can be derived by similarity transformations.

    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.

    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.

    Forecasting COVID-19 Pandemic in Mozambique and Estimating Possible Scenarios

    Authors: Cláudio Moisés Paulo; Felipe Nunes Fontinele; Pedro Henrique Pinheiro Cintra

    id:2007.13933v1 Date: 2020-07-28 Source: arXiv

    COVID-19 is now the largest pandemic crisis of this century, with over 16 million registered cases worldwide. African countries have now begun registering an increasing number of cases, yet, not many models developed focus in specific African countries. In our study we use a simple SEIR model to evaluate and predict future scenarios regarding the pandemic crisis in Mozambique. We compare the effect of different policies on the infection MESHD curve and estimate epidemiological parameters such as the current infection MESHD reproduction number TRANS Rt and the growth rate g. We have found a low value for Rt, ranging from 1.11 to 1.48 and a positive growth rate, between g = 0.22 to 0.27. Our simulations also suggest that a lockdown shows potential for reducing the infection MESHD peak height in 28%, on average, ranging from 20 to 36%.

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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