Corpus overview


MeSH Disease

Human Phenotype


    displaying 491 - 500 records in total 940
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    Empirical Model of Spring 2020 Decrease in Daily Confirmed COVID-19 Cases in King County, Washington

    Authors: Jared C Roach

    doi:10.1101/2020.05.11.20098798 Date: 2020-05-18 Source: medRxiv

    Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number TRANS (R), the two-parameter exponential model should be a standard model - indeed, it has been standard for epidemiological analysis of pandemics for a century but in recent decades has lost popularity to more complex compartmental models. Exponential model should be routinely included in reports describing epidemiological models as a reference, or null hypothesis. Exponential models should be fitted separately for each epidemiologically distinct jurisdiction. They should also be fitted separately to time intervals that differ by any major changes in factors that affect R. Using an exponential model, incidence-count half-life is a better statistic than R. Here an example of the exponential model is applied to King County, Washington during Spring 2020. The parameters and predictions of this model have remained stable for at least 45 days and the accuracy of model predictions has outperformed models with more parameters.

    A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic TRANS isolation compartments reveals unexpected consequences of timing social distancing

    Authors: Jana Gevertz; James Greene; Cynthia Hixahuary Sanchez Tapia; Eduardo D Sontag

    doi:10.1101/2020.05.11.20098335 Date: 2020-05-18 Source: medRxiv

    Motivated by the current COVD-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic TRANS "socially distant" populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission TRANS. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity SERO of the basic reproduction number TRANS to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay MESHD ("CID") in issuing separation mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections MESHD, issuing mandates even slightly after this critical time results in a far greater incidence of infection MESHD. Thus, there is a nontrivial but tight "window of opportunity" for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections --so as to take advantage of potential new therapies and vaccines-- action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule's frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.

    Non-Compulsory Measures Sufficiently Reduced Human Mobility in Tokyo during the COVID-19 Epidemic

    Authors: Takahiro Yabe; Kota Tsubouchi; Naoya Fujiwara; Takayuki Wada; Yoshihide Sekimoto; Satish V. Ukkusuri

    id:2005.09423v2 Date: 2020-05-18 Source: arXiv

    While large scale mobility data has become a popular tool to monitor the mobility patterns during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan on human mobility patterns has been under-studied. Here, we analyze the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility TRANS of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo. The analysis concludes that by April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the effectiveness of non-compulsory measures. Furthermore, the reduction in data-driven human mobility metrics showed correlation with the decrease in estimated effective reproduction number TRANS of COVID-19 in Tokyo. Such empirical insights could inform policy makers on deciding sufficient levels of mobility reduction to contain the disease.

    Spread of the Novel Coronavirus (SARS-CoV-2): Modeling and Simulation of Control Strategies

    Authors: Harishankar Prabhakaran

    doi:10.1101/2020.05.11.20098418 Date: 2020-05-18 Source: medRxiv

    The coronavirus disease MESHD 2019 (COVID-19) is spreading throughout the world and all healthcare systems are loaded beyond its capacity. The virus is named as SARS-CoV-2. In this situation, rational decisions need to be made on how the care is provided for patients with COVID-19. The Incidence report, general symptoms and readily available testing kits, different control strategies, the basic compartmental model, and some of the current research on the epidemiology of the disease are discussed and previously published models are reviewed. Modeling this disease helps in understanding the spread, and predict its future to evaluate different control strategies (Social Distancing, Contact Tracing TRANS and Hospitalization). Compartmental modeling framework is used in this work. The non-linear equations are formulated and fitted to the cumulative case and mortality data. Analytical analysis along with uncertainty analysis and sensitivity SERO analysis is performed, and the conditions to achieve disease free equilibrium is evaluated. Finally, Different control strategies are simulated to show their importance. This paper aims to shows the advantage of mathematical modeling and their simulations in times like now, during which the COVID-19 spreading like wildfire. It also includes Pre-symptomatic and asymptomatic TRANS individuals in the modeling. The simulations are performed for the model fit to Cumulative Case and Mortality data in the United States of America. The Reproduction number TRANS is found to be 2.71914.


    Authors: Khondoker Nazmoon Nabi

    doi:10.1101/2020.05.12.20099192 Date: 2020-05-17 Source: medRxiv

    In this paper, a new Susceptible-Exposed-Symptomatic Infectious- Asymptomatic TRANS Infectious-Quarantined-Hospitalized-Recovered-Dead ( SEIDIUQHRD MESHD) deterministic compartmental model has been proposed and calibrated for describing the transmission TRANS dynamics of the novel coronavirus disease MESHD (COVID-19). A calibration process is executed through the solution of an inverse problem with the help of a Trust-Region-Reflective algorithm, used to determine the best parameter values that would fit the model response. The purpose of this study is to give a tentative prediction of the epidemic peak for Russia, Brazil, India and Bangladesh which could become the next COVID-19 hotspots in no time. Based on the publicly available epidemiological data from late January until 10 May, it has been estimated that the number of daily new symptomatic infectious cases for the above mentioned countries could reach the peak around the beginning of June with the peak size of {approx}15,774 symptomatic infectious cases in Russia, {approx}26,449 cases in Brazil, {approx}9,504 cases in India and {approx}2,209 cases in Bangladesh. Based on our analysis, the estimated value of the basic reproduction number TRANS ( R0 TRANS) as of May 11, 2020 was found to be {approx}4.234 in Russia, {approx}5.347 in Brazil, {approx}5.218 in India, {approx}4.649 in the United Kingdom and {approx}3.5 in Bangladesh. Moreover, with an aim to quantify the uncertainty of our model parameters, Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) which is a global sensitivity SERO analysis (GSA) method is applied which elucidates that, for Russia, the recovery rate of undetected asymptomatic TRANS carriers TRANS, the rate of getting home-quarantined or self-quarantined and the transition rate from quarantined class to susceptible class are the most influential parameters, whereas the rate of getting home-quarantined or self-quarantined and the inverse of the COVID-19 incubation period TRANS are highly sensitive parameters in Brazil, India, Bangladesh and the United Kingdom which could significantly affect the transmission TRANS dynamics of the novel coronavirus. Our analysis also suggests that relaxing social distancing restrictions too quickly could exacerbate the epidemic outbreak in the above mentioned countries.

    Parameter Estimation from ICC curves

    Authors: Joceline Lega

    id:2005.08134v1 Date: 2020-05-17 Source: arXiv

    Incidence - Cumulative Cases (ICC) curves are introduced and shown to provide a simple framework for parameter identification in the case of the most elementary epidemiological model, consisting of susceptible, infected, and removed compartments. This novel methodology is used to estimate the basic reproductive number TRANS of recent outbreaks, including the ongoing COVID-19 epidemic.

    Basic Reproduction Rate and Case Fatality Rate of COVID-19: Application of Meta-analysis


    doi:10.1101/2020.05.13.20100750 Date: 2020-05-16 Source: medRxiv

    Abstract Background: The outbreak of novel coronavirus disease of 2019 (COVID-19) has a wider geographical spread than other previous viruses such as Ebola and H1N1. The onset of disease and its transmission TRANS and severity has become a global concern. The policymakers have a serious concern for containing the spread and minimising the risk of death MESHD. Aim: This study aims to provide the estimates of basic reproduction rate ( R0 TRANS) and case fatality rate (CFR) which applies to a generalised population. Methods: A systematic review was carried out to retrieve the published estimates of reproduction rate and case fatality rate in peer-reviewed articles from PubMed MEDLINE database with defined inclusion and exclusion criteria in the period 15 December 2019 to 3 May 2020. The systematic review led to the selection of 24 articles for R0 TRANS and 17 articles for CFR. These studies used data from China and its provinces, other Asian countries such as Japan, Korea, the Philippines, and countries from other parts of the world such as Nigeria, Iran, Italy, Europe as a whole, France, Latin America, Turkey, the United Kingdom (UK), and the United States of America (USA). These selected articles gave an output of 30 counts of R0 TRANS and 29 counts of CFR which were used in a meta-analysis. A meta-analysis, with the inverse variance method, fixed- and random-effects model and the Forest plot, was performed to estimate the mean effect size or mean value of basic reproduction rate and case fatality rate. The Funnel plot is used to comprehend the publication bias. Results: We estimated the robust estimate of R0 TRANS at 3.11 (2.49-3.71) persons and the robust estimate of CFR at 2.56 (2.06-3.05) per cent after accounting for heterogeneity among studies, using the random-effects model. The regional subgroup analysis in a meta-analysis was significant for R0 TRANS but was not significant for CFR. The R0 TRANS values varied from 1.90 (1.06-2.74) persons to 3.83 (2.44-5.22) persons across the regions. The Funnel plot confirms that the selected studies are significant at one per cent level of significance. Conclusion: We found that one person is likely to infect two to three persons in the absence of any control measures, and around three per cent of the population are at the risk of death within one-and-a-half months from the onset of disease COVID-19 in a generalised population. The emergence of SARS-CoV-2 varies across regions, but the risk of death remains the same. Contribution: The estimates of R0 TRANS and CFR are independent of data from a particular region or time or a homogeneous population. These estimates are applicable to a generalised population. Therefore, the estimates of R0 TRANS and CFR are unequivocally applicable to developing country like India and its states or districts, in ambivalence. The assessments of R0 TRANS and CFR values across the developed nations make all of us aware of consequences of COVID-19, and hence these estimates are of crucial importance for government authorities for the practical implementation of strategies and control measures to contain the disease. Keywords: Covid-19, SARS-CoV-2, Reproduction Rate, Case Fatality Rate, Systematic Review, Meta-analysis

    A comparative analysis of statistical methods to estimate the reproduction number TRANS in emerging epidemics with implications for the current COVID-19 pandemic

    Authors: Megan O'Driscoll; Carole Harry; Christl A. Donnelly; Anne Cori; Ilaria Dorigatti

    doi:10.1101/2020.05.13.20101121 Date: 2020-05-16 Source: medRxiv

    As the SARS-CoV-2 pandemic continues its rapid global spread, quantification of local transmission TRANS patterns has been, and will continue to be, critical for guiding pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the reproduction number TRANS, R0 TRANS, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts. Using simulated epidemic data we assess the performance SERO of 6 commonly-used statistical methods to estimate R0 TRANS as they would be applied in a real-time outbreak analysis scenario - fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean. We find that all methods considered here frequently over-estimate R0 TRANS in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts. We show that true changes in pathogen transmissibility TRANS can be difficult to disentangle from changes in methodological accuracy and precision, particularly for data with significant over-dispersion. As localised epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts.

    Analysis of the COVID-19 Pandemic Spreading in India by an Epidemiological Model and Fractional Differential Operator

    Authors: Amjad S. Shaikh; Vikas S. Jadhav; Munir G. Timol; Kottakkaran S. Nisar; I. Khan

    id:10.20944/preprints202005.0266.v1 Date: 2020-05-16 Source:

    Fractional differential mathematical model unfolding the dynamics of the COVID-19 pandemic in India is presented and explored in this paper. The purpose of this study is to estimate the future outbreak of disease and potential control strategies using mathematical models in India as a whole country as well as in some of the states of the country. This model is calibrated based on reported cases of infections over the month of April 2020 in India. We have used iterative fractional complex transform method to find approximate solutions of the model having modified Riemann Liouville fractional differential operator. We have also carried out a comparative analysis between actual and estimated cumulative cases graphically, moreover, most sensitive parameters for basic reproduction number TRANS$( R_0 TRANS)$ are computed and their effect on transmission TRANS dynamics of COVID-19 pandemic is investigated in detail.

    An epidemiological model for the spread of COVID-19: A South African case study

    Authors: L. E. Olivier; I. K. Craig

    id:2005.08012v2 Date: 2020-05-16 Source: arXiv

    An epidemiological model is developed for the spread of COVID-19 in South Africa. A variant of the classical compartmental SEIR model, called the SEIQRDP model, is used. As South Africa is still in the early phases of the global COVID-19 pandemic with the confirmed infectious cases not having peaked, the SEIQRDP model is first parameterized on data for Germany, Italy, and South Korea - countries for which the number of infectious cases are well past their peaks. Good fits MESHD are achieved with reasonable predictions of where the number of COVID-19 confirmed cases TRANS, deaths MESHD, and recovered cases will end up and by when. South African data for the period from 23 March to 8 May 2020 is then used to obtain SEIQRDP model parameters. It is found that the model fits the initial disease progression well, but that the long-term predictive capability of the model is rather poor. The South African SEIQRDP model is subsequently recalculated with the basic reproduction number TRANS constrained to reported values. The resulting model fits the data well, and long-term predictions appear to be reasonable. The South African SEIQRDP model predicts that the peak in the number of confirmed infectious individuals will occur at the end of October 2020, and that the total number of deaths will range from about 10,000 to 90,000, with a nominal value of about 22,000. All of these predictions are heavily dependent on the disease control measures in place, and the adherence to these measures. These predictions are further shown to be particularly sensitive to parameters used to determine the basic reproduction number TRANS. The future aim is to use a feedback control approach together with the South African SEIQRDP model to determine the epidemiological impact of varying lockdown levels proposed by the South African Government.

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MeSH Disease
Human Phenotype

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