Corpus overview


MeSH Disease

Human Phenotype


    displaying 501 - 510 records in total 827
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    Social Distancing Has Merely Stabilized COVID-19 in the US

    Authors: Aaron B. Wagner; Elaine L. Hill; Sean E. Ryan; Ziteng Sun; Grace Deng; Sourbh Bhadane; Victor Hernandez Martinez; Peter Wu; Dongmei Li; Ajay Anand; Jayadev Acharya; David S. Matteson

    doi:10.1101/2020.04.27.20081836 Date: 2020-04-30 Source: medRxiv

    Social distancing measures, with varying degrees of restriction, have been imposed around the world in order to stem the spread of COVID-19. In this work we analyze the effect of current social distancing measures in the United States. We quantify the reduction in doubling rate, by state, that is associated with social distancing. We find that social distancing is associated with a statistically-significant reduction in the doubling rate for all but three states. At the same time, we do not find significant evidence that social distancing has resulted in a reduction in the number of daily confirmed cases TRANS. Instead, social distancing has merely stabilized the spread of the disease TRANS disease MESHD. We provide an illustration of our findings for each state, including point estimates of the effective reproduction number TRANS, R, both with and without social distancing. We also discuss the policy implications of our findings.

    Real-time estimation of R_0 TRANS for supporting public-health policies against COVID-19

    Authors: Sebastian Contreras; H. Andres Villavicencio; David Medina-Ortiz; Claudia P Saavedra; Alvaro Olivera-Nappa

    doi:10.1101/2020.04.23.20076984 Date: 2020-04-29 Source: medRxiv

    Background: In the absence of a consensus protocol to slow down the current SARS- CoV2 spread, policy makers are in need of real-time indicators to support decisions in public health matters. The Basic Reproduction Number TRANS ( R_0 TRANS) represents viral spread rate and can be dramatically modified by the application of effective public control measures. However, current methodologies to calculate R_0 TRANS from data remain cumbersome and unusable during an outbreak. Objective: To provide a simple mathematical formulation for obtaining R_0 TRANS in Real-Time, and apply it to assess the effectiveness of public-health policies in different iconic countries. Study design: By modifying the equations describing the spread of the virus, we derived a real-time $ R_0 TRANS$ estimator that can be readily calculated from daily official case reports. Results: We show the application of a time trend analysis of the R_0 TRANS estimator to assess the efficacy and promptness of public health measures that impacted on the development of the COVID-19 epidemic in iconic countries. Conclusions: We propose our simple estimator and method as useful tools to follow and assess in real time the effectiveness of public health policies on COVID-19 evolution.

    COVID-19 data analysis and modeling in Palestine

    Authors: Ines Abdeljaoued-Tej

    doi:10.1101/2020.04.24.20078279 Date: 2020-04-29 Source: medRxiv

    We estimate an actual number of infected cases in Palestine based on the 18-day effect from infection MESHD to death MESHD. We find that the number of cases in April 22 varies between 506 and 2 026 infected cases. We also focus on the reproductive number TRANS in Palestine based on population dynamics with two SEIR models. Dataset is from 5 March to 22 April 2020. With a transmission TRANS rate equal to 4.55 106, on May 22, the simulations predict 11 014 total infected cases in the optimistic scenario and 113 171 in the worst one. The crest of the pandemic is from 22 to 27 May 2020. The reproductive number TRANS R0 TRANS is equal to 1.54 for a fixed fraction of 0.6 of symptomatic cases that are reported and for a removal rate of 7. Palestinian COVID-19 mortality number is equal to 6 per million. It is small compared to countries neighboring Palestine. The infected number is equal to 88.4 per million, which is less than most of its neighbors. The basic reproduction number TRANS is still greater than 1. Changes to the transmission TRANS rate (over time) would be advisable, to fall HP R0 TRANS below the critical threshold.

    A new design of an adaptive model of infectious diseases MESHD based on artificial intelligence approach: monitoring and forecasting of COVID-19 epidemic cases

    Authors: Bachir Nail; Abdelaziz Rabehi; Belkacem Bekhiti; Taha Arbaoui

    doi:10.1101/2020.04.23.20077677 Date: 2020-04-29 Source: medRxiv

    Background: Mathematical infectious disease MESHD models available in literature, mostly take in their design that the parameters of basic reproduction number TRANS R_0 TRANS and interval serial TRANS S_I as constant values during tracking the outbreak cases. In this report a new intelligent model called HH-COVID-19 is proposed, with simple design and adaptive parameters. Methods: The parameters R_0 TRANS and S_I are adapted by adding three new weighting factors , {beta} and {gamma} and two free parameters {sigma}_1 and {sigma}_2 in function of time t, thus the HH-COVID-19 become time-variant model. The parameters R_0 TRANS, S_I, , {beta}, {gamma}, {sigma}_1 and {sigma}_2 are estimated optimally based on a recent algorithm of artificial intelligence (AI), inspired from nature called Harris Hawks Optimizer (HHO), using the data of the confirmed infected cases in Algeria country in the first t=55 days. Results: Parameters estimated optimally: R_0= 1.341, S_I= 5.991, = 2.987, {beta}= 1.566, {gamma}= 4.998 {sigma}_1= -0.133 and {sigma}_2= 0.0324. R_0 TRANS starts on 1.341 and ends to 2.677, and S_I starts on 5.991 and ends to 6.692. The estimated results are identically to the actual infected incidence in Algeria, HH-COVID-19 proved its superiority in comparison study. HH-COVID-19 predicts that in 1 May, the infected cases exceed 50 000, during May, to reach quickly the herd immunity stage at beginning of July. Conclusion: HH-COVID-19 can be used for tracking any COVID-19 outbreak cases around the world, just should updating its new parameters to fitting the area to be studied, especially when the population is directly vulnerable to COVID-19 infection MESHD.

    A prototype for decision support tool to help decision-makers with the strategy of handling the COVID-19 UK epidemic

    Authors: Anatoly Zhigljavsky; Ivan Fesenko; Henry Wynn; Kobi Kremnitzer; Jack Noonan; Jonathan Gillard; Roger Whitaker

    doi:10.1101/2020.04.24.20077818 Date: 2020-04-29 Source: medRxiv

    The primary objective of this work is to model and compare different exit scenarios from the lock-down for the COVID-19 UK epidemic. In doing so we provide an additional modelling basis for laying out the strategy options for the decision-makers. The main results are illustrated and discussed in Part I. In Part II, we describe the stochastic model that we have developed for modelling this epidemic. As argued in Part II, the developed model is more flexible than the SEIR/SEIRS models and can be used for modelling the scenarios which may be difficult or impossible to model with the SEIR/SEIRS models. To compare different scenarios for exiting from the lock-down, in Part III we provide our previous report on the same topic where similar (although not as detailed) scenarios were considered. As the possible exit dates, we have chosen May 4, May 11, May 18 and May 25. We model differently the regions with high initial reproductive number TRANS chosen to be R0=2.5, medium R0=2.3 and low R0=2.The numbers for the whole of the UK can be obtained by appropriate averaging of the numbers given in the report. Typical figures are given in Section 4. For each scenario considered, we plot the expected proportion of infected at time t and the expected number of deaths MESHD at time t. To compute the expected numbers of deaths MESHD we used the total mortality rate 0.66%. Many recent studies suggest lower values and therefore the numbers in our projections should be considered as rather pessimistic. Our analysis suggests a value around 0.5% for the mortality rate. In the model, we assume that the isolation of older and vulnerable people continues and the public carries on certain level of isolation until the end of 2020; also we assume that immunity is kept for at least a year and there is no international travel TRANS influence. Our main conclusions are: In regions with higher initial reproductive number TRANS 2.5 the proportion of susceptible at the start of the lock-down should be not smaller than 0.95, the epidemic curve in such regions is in the fast monotonic decline irrespectively of the date of the lock-down lift; In regions with lower initial reproductive number TRANS 2.0 the second mild wave can be expected, the difference between the expected mortality rates is very small for all May 2020 lifting lock-down dates; In regions with initial reproductive number TRANS 2.3, a mild second wave can be expected in the case of large proportion of susceptible at the start of the lock-down, but its severity and resulting mortality depend very little on the date of lifting the lock-down; For the overall UK epidemic, even for rather pessimistic scenarios considered, the second wave is much less pronounced (in terms of the expected mortality rate) than the first one, and the total numbers of expected deaths MESHD are within 2% for all May 2020 dates of lifting the lock-down. Moreover, by keeping R0 TRANS-value after lifting the lock-down below 1.75 is likely to lead to the avoidance of a UK-wide second wave, see Section 4. We believe that the model build in this work can be considered as an important decision support tool to help decision-makers with the strategy of handling the epidemic. We invite other scholars to participate in an open discussion of the strategy options. We feel that this kind of models should be used in the short and long term management of the disease MESHD. We recommend the development of a permanent and modularised modelling suite for COVID-19 management to which additional modules can be added as anti-viral drugs and vaccination are introduced, extending the options. We trust that this work makes a start in that direction and demonstrates the advantages of a heterogeneous demographic refinement, which can only improve targeting role out of treatments.

    Forecast analysis of the epidemics trend of COVID-19 in the United States by a generalized fractional-order SEIR model

    Authors: Conghui Xu; Yongguang Yu; YangQuan Chen; Zhenzhen Lu

    doi:10.1101/2020.04.24.20078493 Date: 2020-04-29 Source: medRxiv

    Abstract In this paper, a generalized fractional-order SEIR model is proposed, denoted by SEIQRP model, which has a basic guiding significance for the prediction of the possible outbreak of infectious diseases MESHD like COVID-19 and other insect diseases MESHD in the future. Firstly, some qualitative properties of the model are analyzed. The basic reproduction number TRANS R0 TRANS is derived. When R0 TRANS < 1, the disease MESHD-free equilibrium point is unique and locally asymptotically stable. When R0 TRANS > 1, the endemic equilibrium point is also unique. Furthermore, some conditions are established to ensure the local asymptotic TRANS stability of disease MESHD-free and endemic equilibrium points. The trend of COVID-19 spread in the United States is predicted. Considering the influence of the individual behavior and government mitigation measurement, a modified SEIQRP model is proposed, defined as SEIQRPD model. According to the real data of the United States, it is found that our improved model has a better prediction ability for the epidemic trend in the next two weeks. Hence, the epidemic trend of the United States in the next two weeks is investigated, and the peak of isolated cases are predicted. The modified SEIQRP model successfully capture the development process of COVID-19, which provides an important reference for understanding the trend of the outbreak.

    Epidemiological and clinical characteristics of the early phase of the COVID-19 epidemic in Brazil

    Authors: William Marciel de Souza; Lewis Fletcher Buss; Darlan da Silva Candido; Jean Paul Carrera; Sabrina Li; Alexander Zarebski; Maria Vincenti-Gonzalez; Janey Messina; Flavia Cristina da Silva Sales; Pamela dos Santos Andrade; Carlos A Prete Jr.; Vitor Heloiz Nascimento; Fabio Ghilardi; Rafael Henrique Moraes Pereira; Andreza Aruska de Souza Santos; Leandro Abade; Bernardo Gutierrez; Moritz U. G. Kraemer; Renato Santana Aguiar; Neal Alexander; Philippe Mayaud; Oliver J Brady; Izabel Oliva Marcilio de Souza; Nelson Gouveia; Guangdi Li; Adriana Tami; Silvano Barbosa Oliveira; Victor Bertollo Gomes Porto; Fabiana Ganem; Walquiria Ferreira Almeida; Francieli Fontana Sutile Tardetti Fantinato; Eduardo Marques Macario; Wanderson Kleber Oliveira; Oliver Pybus; Chieh-Hsi Wu; Julio Croda; Ester Cerdeira Sabino; Nuno R. Faria

    doi:10.1101/2020.04.25.20077396 Date: 2020-04-29 Source: medRxiv

    Background: The first case of COVID-19 was detected in Brazil on February 25, 2020. We report the epidemiological, demographic, and clinical findings for confirmed COVID-19 cases during the first month of the epidemic in Brazil. Methods: Individual-level and aggregated COVID-19 data were analysed to investigate demographic profiles, socioeconomic drivers and age TRANS-sex structure of COVID-19 tested cases. Basic reproduction numbers TRANS ( R0 TRANS) were investigated for Sao Paulo and Rio de Janeiro. Multivariate logistic regression analyses were used to identify symptoms associated with confirmed cases TRANS and risk factors associated with hospitalization. Laboratory diagnosis for eight respiratory viruses were obtained for 2,429 cases. Findings: By March 25, 1,468 confirmed cases TRANS were notified in Brazil, of whom 10% (147 of 1,468) were hospitalised. Of the cases acquired locally (77.8%), two thirds (66.9% of 5,746) were confirmed in private laboratories. Overall, positive association between higher per capita income and COVID-19 diagnosis was identified. The median age TRANS of detected cases was 39 years (IQR 30-53). The median R0 TRANS was 2.9 for Sao Paulo and Rio de Janeiro. Cardiovascular disease MESHD/ hypertension MESHD hypertension HP were associated with hospitalization. Co-circulation of six respiratory viruses, including influenza A and B and human rhinovirus was detected in low levels. Interpretation: Socioeconomic disparity determines access to SARS-CoV-2 testing in Brazil. The lower median age TRANS of infection MESHD and hospitalization compared to other countries is expected due to a younger population structure. Enhanced surveillance of respiratory pathogens across socioeconomic statuses is essential to better understand and halt SARS-CoV-2 transmission TRANS.

    Instantaneous R calculation for COVID-19 epidemic in Brazil

    Authors: Francisco H. C. Felix; Juvenia B. Fontenele

    doi:10.1101/2020.04.23.20077172 Date: 2020-04-29 Source: medRxiv

    COVID-19 pandemic represents a major challenge to health systems of all countries. Brazilian regions habe been showing marked di[ff]erences in onset and number of cases. Health authorities instituted widespread social distancing and lockdown measures but their implementation has also varied. The authors used data on con[fi]rmed cases of COVID-19 in Brazil and its states to calculate the value of instantaneous reproduction number TRANS at these regions. The results show a reduction of instantaneous reproduction number TRANS with time, probably due to social distancing measures put in place in the last weeks by brazillian authorities. It seems logical to maintain restrictions to social contact until the epidemic peak has occurred in Brazil.

    Unraveling the Myths of R0 TRANS in Controlling the Dynamics of COVID-19 Outbreak: a Modelling Perspective

    Authors: Mohd Hafiz Mohd; Fatima Sulayman

    doi:10.1101/2020.04.25.20079319 Date: 2020-04-29 Source: medRxiv

    COVID-19 is an emerging and rapidly evolving pandemic around the world, which causes severe acute respiratory syndrome MESHD and results in substantial morbidity and mortality. To examine the transmission TRANS dynamics of COVID-19 and its interactions with some exogenous factors such as limited medical resources and false detection problems, we employ a simple epidemiological model and analyse this system using modelling and dynamical systems techniques. We discover some contrasting findings with respect to the observations of basic reproduction number TRANS, and we investigate how the issues of limited medical resources and false detection problems affect the COVID-19 pandemic outbreak.

    A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects

    Authors: Zhenzhen Lu; Yongguang Yu; YangQuan Chen; Guojian Ren; Conghui Xu; Shuhui Lu; Zhe Yin

    doi:10.1101/2020.04.25.20079806 Date: 2020-04-29 Source: medRxiv

    A novel coronavirus, designated as COVID-19, e-merged in Wuhan, China, at the end of 2019. In this paper, a mathematical model is proposed to analyze the dynamic behavior of COVID-19. Based on inter-city networked cou-pling effects, a fractional-order SEIHDR system with the real-data from 23 January to 18 March, 2020 of COVID-19 is discussed. Meanwhile, hospitalized individuals and the mortality rates of three types of individuals (exposed, in-fected and hospitalized) are firstly taken into account in the proposed model. And infectivity of individuals during in-cubation is also considered in this paper. By applying least squares method and predictor-correctors scheme, the numer-ical solutions of the proposed system in the absence of the inter-city network and with the inter-city network are stim-ulated by using the real-data from 23 January to 18 - m March, 2020 where m is equal to the number of predic-tion days. Compared with integer-order system ( = 0), the fractional-order model without network is validated to have a better fitting of the data on Beijing, Shanghai, Wuhan, Huanggang and other cities. In contrast to the case with-out network, the results indicate that the inter-city network system may be not a significant case to virus spreading for China because of the lock down and quarantine measures, however, it may have an impact on cities that have not adopted city closure. Meanwhile, the proposed model better fits the data from 24 February to 31, March in Italy, and the peak number of confirmed people is also predicted by this fraction-order model. Furthermore, the existence and unique-ness of a bounded solution under the initial condition are considered in the proposed system. Afterwards, the basic re-production number R0 TRANS is analyzed and it is found to hold a threshold: the disease MESHD-free equilibrium point is locally asymp-totically stable when R0 TRANS [≤] 1, which provides a theoretical basis for whether COVID-19 will become a pandemic in the future.

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MeSH Disease
Human Phenotype

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