# bib

id: cord-288884-itviia7v
author: Chandra, Vedant
title: Stochastic Compartmental Modelling of SARS-CoV-2 with Approximate Bayesian Computation
date: 2020-04-01
extension: .txt
mime: text/plain
words: 1557
sentence: 88
flesch: 56
cache: cache/cord-288884-itviia7v.txt
txt: txt/cord-288884-itviia7v.txt
summary:
  In this proof-of-concept study, we apply approximate Bayesian computation to fit stochastic epidemic models to real world data. The general goal of ABC is to sample the posterior distributions of simulation parameters such that the simulations match the observed data.


id: cord-159425-fgbruo9l
author: Paticchio, Alessandro
title: Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread
date: 2020-10-10
extension: .txt
mime: text/plain
words: 2531
sentence: 119
flesch: 51
cache: cache/cord-159425-fgbruo9l.txt
txt: txt/cord-159425-fgbruo9l.txt
summary:
  Starting from random z 0 and θ, a solutionẑ(t) is generated, then a gradient descent optimizer adjusts z 0 and θ in order to minimize the loss function: Figure 1 : Semi-supervised neural network architecture. Statistical methods in medical research Solving differential equations using neural network solution bundles Modelling the covid-19 epidemic and implementation of population-wide interventions in italy Multiple epidemic wave model of the covid-19 pandemic: Modeling study The first 100 days: Modeling the evolution of the covid-19 pandemic Early dynamics of transmission and control of covid-19: a mathematical modelling study.


id: cord-187462-fxuzd9qf
author: Palladino, Andrea
title: Modelling the spread of Covid19 in Italy using a revised version of the SIR model
date: 2020-05-18
extension: .txt
mime: text/plain
words: 3210
sentence: 135
flesch: 58
cache: cache/cord-187462-fxuzd9qf.txt
txt: txt/cord-187462-fxuzd9qf.txt
summary:
  The SIR model is based on the assumption of a totally susceptible population at time t 0 , i.e. the beginning of the spreading. Given the lack of reliable and long-term data regarding incubation period, virulence, contagiousness, and other transmission parameters [1] for the novel coronavirus SARS-CoV-2 and the lack of reliable drugs and vaccines [3] , containment measurements, the tracking of infected people and the treatment of patients in the early stage of the illness, remain the only feasible option to face the ongoing outbreak of the virus that is leading to a collapsing health system with thousands of deaths, as seen in hotspots.


id: cord-029725-px209lf0
author: Anand, Nikhil
date: 2020-07-24
extension: .txt
mime: text/plain
words: 3274
sentence: 127
flesch: 53
cache: cache/cord-029725-px209lf0.txt
txt: txt/cord-029725-px209lf0.txt
title:
  Predicting the Spread of COVID-19 Using [Formula: see text] Model Augmented to Incorporate Quarantine and Testing

summary:
  Mathematical modelling using improved SIR model with more realistic assumptions 2020) epidemic landscape and forecasting of SARS-CoV-2 in India Report-9, impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. This assumption is violated in a scenario wherein restrictions such as quarantine and social distancing are enforced, in which case the portion of infected population which is quarantined will not be contributing in the spread of the disease.


id: cord-146213-924ded7t
author: Kiamari, Mehrdad
title: COVID-19 Risk Estimation using a Time-varying SIR-model
date: 2020-08-11
extension: .txt
mime: text/plain
words: 3691
sentence: 132
flesch: 50
cache: cache/cord-146213-924ded7t.txt
txt: txt/cord-146213-924ded7t.txt
summary:
  For discrete-time cases such as daily reporting on number of infected cases, the time-variant effective contact rate β t , which represents the contact rate for time slot t can be derived by solving the following equation: Therefore, the time-variant effective reproduction number would be defined as R t βt σ . In accordance with LA county daily press releases, there is a sharp jump in both R t and risk score around the beginning of July.


id: cord-155015-w3k7r5z9
author: Arazi, R.
title: Discontinuous transitions of social distancing
date: 2020-08-16
extension: .txt
mime: text/plain
words: 3540
sentence: 214
flesch: 61
cache: cache/cord-155015-w3k7r5z9.txt
txt: txt/cord-155015-w3k7r5z9.txt
summary:
  Association of social distancing transitions only with s th is supported by the fit of COVID-19 data. Social distancing changes as pandemic unfolds, reflecting a change in personal and government beliefs in the future.


id: cord-191574-1g38scnj
author: Harko, Tiberiu
date: 2020-08-28
extension: .txt
mime: text/plain
words: 3732
sentence: 154
flesch: 41
cache: cache/cord-191574-1g38scnj.txt
txt: txt/cord-191574-1g38scnj.txt
title:
  Series solution of the Susceptible-Infected-Recovered (SIR) epidemic model with vital dynamics via the Adomian and Laplace-Adomian Decomposition Methods

summary:
  From SIR type models only the model without vital dynamics has an exact analytic solution, which can be obtained in an exact parametric form. Application to the SIR epidemic model Susceptible-Infected-Recovered (SIR) Dynamics of COVID-19 and Economic Impact Inferring change points in the COVID-19 spreading reveals the effectiveness of interventions How to reduce epidemic peaks keeping under control the time-span of the epidemic Forecasting COVID 19 growth in India using Susceptible-Infected-Recovered (SIR) model The challenges of modeling and forecasting the spread of COVID-19 A feedback SIR (fSIR) model highlights advantages and limitations of infection-based social distancing Estimation of COVID-19 spread curves integrating global data and borrowing information Phenomenological dynamics of COVID-19 pandemic: meta-analysis for adjustment parameters On the Emergence of a Power Law in the Distribution of COVID-19 Cases Optimal control of an SIR epidemic through finite-time non-pharmaceutical intervention Understanding the COVID19 infection curves -finding the right numbers Exact analytical solutions of the Susceptible-Infected-Recovered (SIR) epidemic model and of the SIR model with equal death and birth rates A Mathematical Model of Epidemics-A Tutorial for Students, Mathematics 2020 Variational iteration method for solving the epidemic model and the prey and predator problem Solution of the epidemic model by homotopy perturbation method A new method for solving epidemic model A review of the decomposition method in applied mathematics Solving Frontier Problems of Physics: the Decomposition Method A comparison between the variational iteration method and Adomian decomposition method Solving New Fourth-Order Emden-Fowler-Type Equations by the Adomian Decomposition Method A reliable algorithm for positive solutions of nonlinear boundary value problems by the multistage Adomian decomposition method Computation of the general relativistic perihelion precession and of light deflection via the Laplace-Adomian Decomposition Method Analytical and numerical treatment of Falkner-Skan equation via a transformation and Adomian's method Solving the nonlinear biharmonic equation by the Laplace-Adomian and Adomian Decomposition Methods, Surveys in Mathematics and its Applications Vortex solutions in atomic Bose-Einstein condensates via the Adomian Decomposition Method Solution of the epidemic model by Adomian decomposition method A simple computational approach to the Susceptible-Infected-Recovered (SIR) epidemic model via the Laplace-Adomian Decomposition Method On the Integrability of the SIR Epidemic Model with Vital Dynamics


id: cord-140977-mg04drna
author: Maltezos, S.
title: Methodology for Modelling the new COVID-19 Pandemic Spread and Implementation to European Countries
date: 2020-06-27
extension: .txt
mime: text/plain
words: 3987
sentence: 146
flesch: 50
cache: cache/cord-140977-mg04drna.txt
txt: txt/cord-140977-mg04drna.txt
summary:
  Also A is constant while n and τ are model parameters. From the obtained solution for R 0 we can also calculate the parameter a of SIR model, a = βR 0 , where β can be calculated from the peak value of the daily reported recovered individuals by the formula, β = R p /I tot,p , where I tot,p represents the integral of the DRC curve with upper limit the peaking time t p .


id: cord-243070-0b06zk1q
author: Lesniewski, Andrew
title: Epidemic control via stochastic optimal control
date: 2020-04-14
extension: .txt
mime: text/plain
words: 3793
sentence: 199
flesch: 57
cache: cache/cord-243070-0b06zk1q.txt
txt: txt/cord-243070-0b06zk1q.txt
summary:
  Population biology of infectious diseases: Part I Dynamic Programming Time-optimal control strategies in SIR epidemic models Mathematical Models in Epidemiology Stochastic epidemic models: A survey Deterministic and stochastic models for recurrent epidemics Discrete Time Approximation and Monte-Carlo Simulation of Backward Stochastic Differential Equations, Stochastic Processes and their Applications A Scandal in Bohemia, (1891), included in The Adventures of Sherlock Holmes Backward stochastic differential equations in finance Controlled Markov processes and viscosity solutions A stochastic differential equation SIS epidemic model Geometric numerical integration illustrated by the StörmerVerlet method Optimal control of epidemics with limited resources Solving high-dimensional partial differential equations using deep learning A contribution to the mathematical theory of epidemics Stochastic Stability of Differential Equations Simulating Hamiltonian Dynamics Options on infectious diseases Managing counterparty credit risk via backward stochastic differential equations Valuing American Options by Simulation: A Simple Least-Squares Approach Continuous-time Stochastic Control and Optimization with Financial Applications The Mathematical Theory of Optimal Processes Stochastic Controls: Hamiltonian Systems and HJB Equations This leads to the following system of stochastic differential equations (SDE), driven by W t with the initial conditions The third component of the process, X 3 = R, follows the dynamics which implies that the conservation law continues to hold in the stochastic model.


id: cord-007404-s2qnhswe
author: Shu, Panpan
date: 2015-06-04
extension: .txt
mime: text/plain
words: 4289
sentence: 174
flesch: 48
cache: cache/cord-007404-s2qnhswe.txt
txt: txt/cord-007404-s2qnhswe.txt
title:
  Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks

summary:
  Considering that the large fluctuation of the outbreak size occurs near the epidemic threshold, we propose a novel numerical identification method of SIR epidemic threshold by analyzing the peak of the epidemic variability. The numerical method presented can effectively identify SIR epidemic thresholds on various networks, and could be extended to other dynamical processes such as information diffusion and behavior spreading.


id: cord-103598-8umv06ox
author: Ambrosio, Benjamin
title: On a coupled time-dependent SIR models fitting with New York and New-Jersey states COVID-19 data
date: 2020-06-10
extension: .txt
mime: text/plain
words: 4128
sentence: 230
flesch: 69
cache: cache/cord-103598-8umv06ox.txt
txt: txt/cord-103598-8umv06ox.txt
summary:
  SIR models are very classic in literature. Here are also some examples of references for SIR models in other epidemic diseases: Dengue


id: cord-190495-xpfbw7lo
author: Molnar, Tamas G.
title: Safety-Critical Control of Compartmental Epidemiological Models with Measurement Delays
date: 2020-09-22
extension: .txt
mime: text/plain
words: 4206
sentence: 221
flesch: 58
cache: cache/cord-190495-xpfbw7lo.txt
txt: txt/cord-190495-xpfbw7lo.txt
summary:
  SIR model. key: cord-190495-xpfbw7lo authors: Molnar, Tamas G.; Singletary, Andrew W.; Orosz, Gabor; Ames, Aaron D. title: Safety-Critical Control of Compartmental Epidemiological Models with Measurement Delays date: 2020-09-22 journal: nan DOI: nan sha: doc_id: 190495 cord_uid: xpfbw7lo We introduce a methodology to guarantee safety against the spread of infectious diseases by viewing epidemiological models as control systems and by considering human interventions (such as quarantining or social distancing) as control input.


id: cord-167454-ivhqeu01
author: Battiston, Pietro
title: COVID-19: $R_0$ is lower where outbreak is larger
date: 2020-04-16
extension: .txt
mime: text/plain
words: 4527
sentence: 152
flesch: 43
cache: cache/cord-167454-ivhqeu01.txt
txt: txt/cord-167454-ivhqeu01.txt
summary:
  While for a same level of R 0 we expect the predicted time to extinction to increase with the initial outbreak size, the fact that the R 0 is negatively related to initial outbreak size -and that a lower R 0 leads to a quicker extinction -leaves theoretically undetermined the relationship between initial outbreak size and duration of the outbreak. In particular, there is a robust and strongly significant negative correlation between the estimated basic reproduction number ($R_0$) and the initial outbreak size, in contrast with the role of $R_0$ as a emph{predictor} of outbreak size.


id: cord-102966-7vdz661d
author: Nikolaou, M.
title: A Fundamental Inconsistency in the SIR Model Structure and Proposed Remedies
date: 2020-05-01
extension: .txt
mime: text/plain
words: 4493
sentence: 234
flesch: 56
cache: cache/cord-102966-7vdz661d.txt
txt: txt/cord-102966-7vdz661d.txt
summary:
  Comparison of the profiles for the first-order Padé SIR, second-order Padé SIR, dSIR, and SIR models. + 1� (25) Note that the above * , exact for the first-order Padé SIR model and approximate for the second-order Padé SIR and dSIR models, is double the * of the standard SIR model, as confirmed in Figure 8 .


id: cord-152881-k1hx1m61
author: Toda, Alexis Akira
title: Susceptible-Infected-Recovered (SIR) Dynamics of COVID-19 and Economic Impact
date: 2020-03-25
extension: .txt
mime: text/plain
words: 4656
sentence: 269
flesch: 63
cache: cache/cord-152881-k1hx1m61.txt
txt: txt/cord-152881-k1hx1m61.txt
summary:
  Figure 5 shows the dynamics of SIR model when (β, γ) = (0.2, 0.1), y 0 = 10 −6 , 10 −5 , 10 −4 , and z 0 Figure 5 : Dynamics of SIR model when (β, γ) = (0.2, 0.1), y 0


id: cord-010719-90379pjd
author: Saeedian, M.
title: Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model
date: 2017-02-21
extension: .txt
mime: text/plain
words: 4814
sentence: 254
flesch: 56
cache: cache/cord-010719-90379pjd.txt
txt: txt/cord-010719-90379pjd.txt
summary:
  Also in [48] the authors use fractional order differential equations for epidemic models and concentrate on the equilibrium points of the models and their asymptotic stability of differential equations of fractional order. While much effort has been made so far to determine exact epidemic thresholds in Markovian epidemic models [30] [31]


id: cord-273429-dl6z8x9h
author: Dandekar, R.
date: 2020-07-24
extension: .txt
mime: text/plain
words: 5176
sentence: 207
flesch: 46
cache: cache/cord-273429-dl6z8x9h.txt
txt: txt/cord-273429-dl6z8x9h.txt
title:
  A machine learning aided global diagnostic and comparative tool to assess effect of quarantine control in Covid-19 spread

summary:
  This matches the on-ground situation as indicated by a generally strong correlation is seen between the red circles in our study (states with lower quarantine efficiency) and the yellow regions seen in in the Wall Street Journal report 41 (states with reduced imposition of restrictions) and between the blue circles in our study (states with higher quarantine efficiency) and the blue regions seen in the Wall Street Journal report 41 (states with generally higher level of restrictions). [27] [28] Thus, a neural network solution is attractive to approximate quarantine effects in combination with analytical epidemiological models.


id: cord-007399-qbgz7eqt
author: Bilal, Shakir
title: Effects of quasiperiodic forcing in epidemic models
date: 2016-09-22
extension: .txt
mime: text/plain
words: 5177
sentence: 245
flesch: 48
cache: cache/cord-007399-qbgz7eqt.txt
txt: txt/cord-007399-qbgz7eqt.txt
summary:
  The inclusion of seasonality in transmission models has helped in explaining spatiotemporal variations in incidence of infectious diseases such as measles. Consequently, a better understanding of how internal factors (e.g., immunity) of disease dynamics, in association with variable (as opposed to regular/periodic) external forcing, shape up outbreak trajectories is lacking.


id: cord-187700-716af719
author: Lee, Duan-Shin
title: Epidemic Spreading in a Social Network with Facial Masks wearing Individuals
date: 2020-10-31
extension: .txt
mime: text/plain
words: 5590
sentence: 349
flesch: 66
cache: cache/cord-187700-716af719.txt
txt: txt/cord-187700-716af719.txt
summary:
  A randomly selected individual from a population is a type 1 individual with probability p, and is of type 2 with probability 1 − p. A randomly selected node is of type 1 with probability p and is of type 2 with probability 1


id: cord-258018-29vtxz89
author: Cooper, Ian
title: A SIR model assumption for the spread of COVID-19 in different communities
date: 2020-06-28
extension: .txt
mime: text/plain
words: 5817
sentence: 219
flesch: 52
cache: cache/cord-258018-29vtxz89.txt
txt: txt/cord-258018-29vtxz89.txt
summary:
  The Lancet infectious diseases Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions Analysis and forecast of COVID-19 spreading in China, Italy and France A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy Estimation of COVID-19 dynamics on a back-of-envelope: Does the simplest SIR model provide quantitative parameters and predictions Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability Three basic epidemiological models The mathematics of infectious diseases The basic epidemiology models: models, expressions for R0, parameter estimation, and applications The SIR model and the foundations of public health Global analysis of the COVID-19 pandemic using simple epidemiological models A modified sir model for the covid-19 contagion in Italy Mathematical modeling of covid-19 transmission dynamics with a case study of wuhan Mod-370 elling the COVID-19 epidemic and implementation of population-wide interventions in Italy The effectiveness of quarantine of Wuhan city against the Corona Virus Disease 2019 (COVID19): A wellmixed SEIR model analysis ), e0230405. System (1) can be solved numerically to find how the scaled (by f ) susceptible S, infected I and removed R m populations (what we call model solutions) evolve with time, in good agreement with the recorded data.


id: cord-034824-eelqmzdx
author: Guo, Chungu
title: Influential Nodes Identification in Complex Networks via Information Entropy
date: 2020-02-21
extension: .txt
mime: text/plain
words: 5772
sentence: 281
flesch: 49
cache: cache/cord-034824-eelqmzdx.txt
txt: txt/cord-034824-eelqmzdx.txt
summary:
  For example, collaboration networks [1] are used to cover the scientific collaborations between authors, email networks [2] denote the email communications between users, protein-DNA networks [3] help people gain a deep insight on biochemical reaction, railway networks [4] reveal the structure of railway via complex network methods, social networks show interactions between people Greedy method is usually used as the upper bound, but it is not efficient in large networks due to its high time complexity.


id: cord-104158-l7s2utqb
author: Maheshwari, H.
title: CoSIR: Managing an Epidemic via Optimal Adaptive Control of Transmission Policy
date: 2020-11-13
extension: .txt
mime: text/plain
words: 5455
sentence: 263
flesch: 52
cache: cache/cord-104158-l7s2utqb.txt
txt: txt/cord-104158-l7s2utqb.txt
summary:
  In Section 5, we leverage the properties of the LV system to propose strategies for restriction control. The problem of stabilizing infection levels assuming SIR dynamics has a direct analogy with population control in LV predator-prey systems where it is desirable to maintain the predator and prey population at certain target levels suitable for the ecosystem.


id: cord-010715-91fob3ax
author: Hasegawa, Takehisa
title: Outbreaks in susceptible-infected-removed epidemics with multiple seeds
date: 2016-03-30
extension: .txt
mime: text/plain
words: 5810
sentence: 309
flesch: 65
cache: cache/cord-010715-91fob3ax.txt
txt: txt/cord-010715-91fob3ax.txt
summary:
  To consider the connectivity of numerous R components, we use the following procedure: (i) We first calculate the probability, P n , that the size of the R component generated by a single seed is n. (ii) For the case of ρ > 0, the system has numerous R components proportional to ρ. Here we replaced the transmissibility T in [10] with λ as T = λ/(μ + λ) with μ = 1 The susceptibilities χ R and χ S are given as χ R = r =rmax r 2 n R (r) and χ S = s =smax s 2 n S (s) Introduction to Percolation Theory Finite components have no cyclic path in infinite locally treelike networks Let us consider a finite network with N nodes.


id: cord-188958-id9m3mfk
author: Vrugt, Michael te
title: Containing a pandemic: Nonpharmaceutical interventions and the"second wave"
date: 2020-09-30
extension: .txt
mime: text/plain
words: 6305
sentence: 317
flesch: 60
cache: cache/cord-188958-id9m3mfk.txt
txt: txt/cord-188958-id9m3mfk.txt
summary:
  A contribution to the mathematical theory of epidemics Global dynamics of SIR model with switched transmission rate Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory The nature of the liquid-vapour interface and other topics in the statistical mechanics of non-uniform, classical fluids Dynamic density functional theory of fluids Dynamical density functional theory and its application to spinodal decomposition Classical dynamical density functional theory: from fundamentals to applications Dynamics of SIR model with vaccination and heterogeneous behavioral response of individuals modeled by the Preisach operator Memory effects in population dynamics: spread of infectious disease as a case study Ein Plan für den Herbst The basic reproductive number of Ebola and the effects of public health measures: the cases of Congo and Uganda A simple mathematical model for Ebola in Africa SARS-CoV-2 infection protects against rechallenge in rhesus macaques Geographic and temporal development of plagues Face masks against COVID-19: an evidence review Täglicher Lagebericht des RKI zur Coronavirus-Krankheit-2019 (COVID-19 Der Puls steigt Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2) Global stability analysis for a generalized delayed SIR model with vaccination and treatment Mechanism for the stabilization of protein clusters above the solubility curve Controlling the microstructure and phase behavior of confined soft colloids by active interaction switching A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions Binary Gaussian core model: fluid-fluid phase separation and interfacial properties Modellierung von Beispielszenarien der SARS-CoV-2-Epidemie 2020 in Deutschland Rates and probabilities in economic modelling (8) while keeping c constant models a scenario in which (Figs. 2G-2J) .


id: cord-016965-z7a6eoyo
author: Brockmann, Dirk
title: Human Mobility, Networks and Disease Dynamics on a Global Scale
date: 2017-10-23
extension: .txt
mime: text/plain
words: 6793
sentence: 323
flesch: 51
cache: cache/cord-016965-z7a6eoyo.txt
txt: txt/cord-016965-z7a6eoyo.txt
summary:
  Compared to the conventional use of geographic distance effective distance is a much better predictor of epidemic arrival time as is reflected by the linear relationship between arrival time and effective distance, e.g. compare to Fig. Effective distance should therefore decrease with traffic flux.


id: cord-175366-jomeywqr
author: Massonis, Gemma
title: Structural Identifiability and Observability of Compartmental Models of the COVID-19 Pandemic
date: 2020-06-25
extension: .txt
mime: text/plain
words: 6470
sentence: 277
flesch: 38
cache: cache/cord-175366-jomeywqr.txt
txt: txt/cord-175366-jomeywqr.txt
summary:
  However, the accuracy of mechanistic models is constrained by the uncertainties in our knowledge, which creates uncertainties in model parameters and even in the model structure [8] . Figure 1 : Classification of SIR models.


id: cord-279112-ajdkasah
author: Rojas, S.
date: 2020-09-13
extension: .txt
mime: text/plain
words: 1846
sentence: 69
flesch: 47
cache: cache/cord-279112-ajdkasah.txt
txt: txt/cord-279112-ajdkasah.txt
title:
  Comment on “Estimation of COVID-19 dynamics “on a back-of-envelope”: Does the simplest SIR model provide quantitative parameters and predictions?”

summary:
  Thus, the dynamics of the disease, introduced in 1927 by Kermack and McKendrick [2] , is modeled by the set of differential equations: In these equations, the parameters β (the infection rate) and γ (the recovery or removal rate of infectives) are constants: β controls the transition between S and I, equation (1), while γ controls the transition between I and R, equation (3). Then, by a standard Figure 1 : The graph shows the KM approximation R(t) given in equation (7) (with fitting parameters shown in Table 1 , according to equation (11) ) and the full numerical solution of the SIR epidemiological model defined by equations (1)-(3) (with integration parameters compiled in Table 2 ), both with reasonable estimated absolute and relative rmse values are observed to adjust reported cumulative confirmed COVID-19 cases for a number of countries.


id: cord-174036-b3frnfr7
author: Thomas, Loring J.
title: Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity
date: 2020-05-20
extension: .txt
mime: text/plain
words: 6667
sentence: 231
flesch: 40
cache: cache/cord-174036-b3frnfr7.txt
txt: txt/cord-174036-b3frnfr7.txt
summary:
  To model networks of potential contacts at scale, we employ spatial network models (19) , which are both computationally tractable and able to capture the effects of geography and population heterogeneity on network structure (20) . We also present chloropleth maps showing spatial variation in peak infection times, as well as the correlations between the infection trajectory within local areal units and the aggregate infection trajectory for the city as a whole.


id: cord-212912-t5v11gs0
author: Barwolff, Gunter
title: Prospects and limits of SIR-type Mathematical Models to Capture the COVID-19 Pandemic
date: 2020-04-13
extension: .txt
mime: text/plain
words: 1962
sentence: 108
flesch: 65
cache: cache/cord-212912-t5v11gs0.txt
txt: txt/cord-212912-t5v11gs0.txt
summary:
  Thus we can describe the early regime by the equation We are looking for periods in the spreadsheets of infected people per day where the course can be described by a function of type (4 We solved this non-linear minimum problem with the damped Gauss-Newton method (see [4] ). day log(number of infected people)


id: cord-297161-ziwfr9dv
author: Sauter, T.
title: TESTING INFORMED SIR BASED EPIDEMIOLOGICAL MODEL FOR COVID-19 IN LUXEMBOURG
date: 2020-07-25
extension: .txt
mime: text/plain
words: 2247
sentence: 72
flesch: 43
cache: cache/cord-297161-ziwfr9dv.txt
txt: txt/cord-297161-ziwfr9dv.txt
summary:
  Notably, SIR models captured a link between the transmission rate β and the case-infection ratio that was missed by SEIR models. The underestimation of the Infected, Deaths, and Removed, due to not considering country specific testing information, causes SIR models to predict IFR and effective reproduction number (Rt_eff ) values that vary drastically across countries with different testing and might often be overestimated.


id: cord-190296-erpoh5he
author: Schaback, Robert
title: On COVID-19 Modelling
date: 2020-05-11
extension: .txt
mime: text/plain
words: 9450
sentence: 467
flesch: 70
cache: cache/cord-190296-erpoh5he.txt
txt: txt/cord-190296-erpoh5he.txt
summary:
  When mentioning Johns Hopkins data, they provide C, D, and R separately without stating the most important figures, namely I = C − D − R, their change, and the change of their change. Recall that the determination of these variables is done while there are Johns Hopkins data available, following section 4.5, and will be dependent on the data-driven estimations described there.


id: cord-253461-o63ru7nr
author: Tewari, A.
title: Temporal Analysis of COVID-19 Peak Outbreak
date: 2020-09-13
extension: .txt
mime: text/plain
words: 1781
sentence: 85
flesch: 45
cache: cache/cord-253461-o63ru7nr.txt
txt: txt/cord-253461-o63ru7nr.txt
summary:
  With this in mind, SIR model is explored in current research to forecast peak COVID-19 outbreak over a large population in India. This research was conducted to evaluate the feasibility of application of SIR model to predict peak COVID-19 outbreak timeline from the date of first reported case for the 10 largest states in India which together constitute more than 74% or almost 3/4 th of total population in India.


id: cord-222193-0b4o0ccp
author: Saakian, David B.
title: A simple statistical physics model for the epidemic with incubation period
date: 2020-04-13
extension: .txt
mime: text/plain
words: 2072
sentence: 112
flesch: 57
cache: cache/cord-222193-0b4o0ccp.txt
txt: txt/cord-222193-0b4o0ccp.txt
summary:
  Generally, epidemic models have a higher order of non-linearity than evolutionary models, although there are some similarities between these two classes. We use the proposed model to analyze COVID-19 epidemic data in Armenia.


id: cord-277094-2ycmxcuz
author: Ifguis, Ousama
date: 2020-06-02
extension: .txt
mime: text/plain
words: 1223
sentence: 42
flesch: 50
cache: cache/cord-277094-2ycmxcuz.txt
txt: txt/cord-277094-2ycmxcuz.txt
title:
  Simulation of the Final Size of the Evolution Curve of Coronavirus Epidemic in Morocco using the SIR Model

summary:
  Also, as the number of infected cases is increasing, it is necessary for modellers to estimate the severity of the epidemic in terms of the total number of people infected, the total number of confirmed cases, the total number of deaths, and basic reproduction and to predict the duration of the epidemic, the arrival of its peak, and its final size. Figure 3 , based on optimal SIR models, shows that the start of acceleration of the epidemic is around 21 March 2020, the regular growth will begin on 8 April 2020, and the end of the epidemic in Morocco would be around 26 April 2020, with a total of 1,446 infected cases and 366 final number of susceptible cases (Table 2 ).


id: cord-324993-hs66uf1u
author: Adwibowo, A.
title: Flattening the COVID 19 curve in susceptible forest indigenous tribes using SIR model
date: 2020-05-25
extension: .txt
mime: text/plain
words: 3255
sentence: 164
flesch: 49
cache: cache/cord-324993-hs66uf1u.txt
txt: txt/cord-324993-hs66uf1u.txt
summary:
  Using the Susceptible Infectious Recovered (SIR) model, the spread of the COVID 19 under 3 intervention scenarios (low, moderate, high) is simulated and predicted in indigenous tribe populations. The COVID 19 SIR model of indigenous tribe populations living in remote Yasuni rainforest enclaves with simulated 25% (low), 50% (moderate), and 75% (high) interventions (x axis: days, y axis: proportion of total population). .


id: cord-264248-wqkphg2e
author: Hazem, Y.
title: Hasty Reduction of COVID-19 Lockdown Measures Leads to the Second Wave of Infection
date: 2020-05-26
extension: .txt
mime: text/plain
words: 2266
sentence: 95
flesch: 48
cache: cache/cord-264248-wqkphg2e.txt
txt: txt/cord-264248-wqkphg2e.txt
summary:
  The results showed an inevitable second wave of COVID-19 infection following loosening the current measures. Hence, it is important to understand the consequences of easing lockdown measures and refreshing the economy.


id: cord-184685-ho72q46e
author: Huang, Tongtong
date: 2020-08-10
extension: .txt
mime: text/plain
words: 4853
sentence: 202
flesch: 42
cache: cache/cord-184685-ho72q46e.txt
txt: txt/cord-184685-ho72q46e.txt
title:
  Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates

summary:
  Among existing models, the ODE compartment-based models occupy a middle ground between network models at the individual-level and purely count-driven statistical analyses that are disease-dynamics-agnostic, which will be our main interest in this paper. Compartment models, which originated in the early 20th century


id: cord-303030-8unrcb1f
author: Gaeta, Giuseppe
title: Social distancing versus early detection and contacts tracing in epidemic management
date: 2020-07-16
extension: .txt
mime: text/plain
words: 11352
sentence: 385
flesch: 52
cache: cache/cord-303030-8unrcb1f.txt
txt: txt/cord-303030-8unrcb1f.txt
summary:
  SIAM ArXiv: 2003.02062 ; Data Analysis for the COVID-19 early dynamics in Northern Italy A simple SIR model with a large set of asymptomatic infectives A simple SIR model with a large set of asymptomatic infectives How to reduce epidemic peaks keeping under control the time-span of the epidemic Accurate closed-form solution of the SIR epidemic model Asymptomatic transmission, the achilles heel of current strategies to control covid-19 (Editorial) Presumed asymptomatic carrier transmission of COVID-19 Pre-and asymptomatic individuals contribute up to 80% of COVID-19 transmission Evidence supporting transmission of severe acute respiratory syndrome coronavirus 2 while presymptomatic or asymptomatic Temporal dynamics in viral shedding and transmissibility of COVID-19 The rate of underascertainment of novel coronavirus (2019-ncov) infection: estimation using japanese passengers data on evacuation flights Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19) Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the diamond princess cruise ship Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-cov2) We have considered epidemic dynamics as described by mean field models of the SIR type; more specifically, we have first considered the classical Kermack-McKendrick SIR model [1] [2]


id: cord-318525-nc5rtwtd
author: Smeets, Bart
title: Scaling analysis of COVID-19 spreading based on Belgian hospitalization data
date: 2020-03-30
extension: .txt
mime: text/plain
words: 2603
sentence: 118
flesch: 50
cache: cache/cord-318525-nc5rtwtd.txt
txt: txt/cord-318525-nc5rtwtd.txt
summary:
  Data is obtained from publicly available numbers on current hospitalization (H), current number of ICU patients (ICU ), accumulated number of deaths (D) and number of individuals released from the hospital (R). Extrapolation with these parameters predicts a peak in number of ICU patients around April 15th, with the number of ICU patients exceeding the capacity of the Belgian healthcare system of 2650 beds.


id: cord-229937-fy90oebs
author: Amaro, J. E.
title: Global analysis of the COVID-19 pandemic using simple epidemiological models
date: 2020-05-14
extension: .txt
mime: text/plain
words: 4909
sentence: 195
flesch: 51
cache: cache/cord-229937-fy90oebs.txt
txt: txt/cord-229937-fy90oebs.txt
summary:
  Discussion: the Kermack-McKendrick epidemic threshold theorem Stability analysis of SIR model with vaccination Seasonality and the effectiveness of mass vaccination Application of SIR epidemiological model: new trends Epidemic disease in England -the evidence of variability and of persistency of type Report on the Prevention of Malaria in Mauritius An application of the theory of probabilities to the study of a priori pathometry. The Death and extended SIR models are simple enough to provide fast estimations of pandemic evolution by fitting spatial-time average parameters, and present a good first-order approximation to understand secondary effects during the pandemic, such as lockdown and population migrations, which may help to control the disease.


id: cord-194157-ak2gc3nz
author: Clum, Charles
title: Parameter estimation in the SIR model from early infections
date: 2020-08-10
extension: .txt
mime: text/plain
words: 4800
sentence: 271
flesch: 77
cache: cache/cord-194157-ak2gc3nz.txt
txt: txt/cord-194157-ak2gc3nz.txt
summary:
  While the short-term behavior of ι is exponential with rate β − µ, the long-term behavior is instead governed by the quotient R 0 := β/µ, known as the basic reproductive number. − t 0 .


id: cord-153905-qszvwqtj
author: Bizet, Nana Cabo
title: Modelos SIR modificados para la evoluci'on del COVID19
date: 2020-04-23
extension: .txt
mime: text/plain
words: 5535
sentence: 298
flesch: 59
cache: cache/cord-153905-qszvwqtj.txt
txt: txt/cord-153905-qszvwqtj.txt
summary:
  Para aclarar aún más nuestra idea mostraremos las curvas de Alemania y Corea del Sur, esta ultima ya en fase de salida de la epidemia. − γ A continuación discutiremos las soluciones del sistema SIR en los casos de que el número de infectados es mucho más pequeño que la población


id: cord-311183-5blzw9oy
author: Malavika, B.
date: 2020-06-27
extension: .txt
mime: text/plain
words: 2735
sentence: 117
flesch: 50
cache: cache/cord-311183-5blzw9oy.txt
txt: txt/cord-311183-5blzw9oy.txt
title:
  Forecasting COVID-19 epidemic in India and high incidence states using SIR and logistic growth models

summary:
  We forecasted the number of cumulative cases for India and four other high incidence states using logistic growth model which has projected the cumulative cases very closely to the observed cases. As in any other projection using models, the limitation is that each model would behave differently, not merely due to differences in underlying assumptions but differences in population density, existing capacity of the health systems, current level of interventions and socio-demographic and economic situation across and within the states and districts.


id: cord-247144-crmfwjvf
author: Bodova, Katarina
date: 2020-05-14
extension: .txt
mime: text/plain
words: 6862
sentence: 270
flesch: 48
cache: cache/cord-247144-crmfwjvf.txt
txt: txt/cord-247144-crmfwjvf.txt
title:
  Emerging Polynomial Growth Trends in COVID-19 Pandemic Data and Their Reconciliation with Compartment Based Models

summary:
  [18] use the PGED scaling on reported COVID-19 data and claim that public measures and social distancing enforced yield a fractal type contact network on which the epidemic transmission is strongly limited by the network topology. We conducted a systematic survey of COVID-19 pandemic data ([27], the last reporting day May 9, 2020) for all countries where the time series are sufficiently long to display a consistent trend (in total 118 countries).


id: cord-189434-nrkvbdu4
author: Steinmann, Paul
title: Analytical Mechanics Allows Novel Vistas on Mathematical Epidemic Dynamics Modelling
date: 2020-06-06
extension: .txt
mime: text/plain
words: 5590
sentence: 171
flesch: 31
cache: cache/cord-189434-nrkvbdu4.txt
txt: txt/cord-189434-nrkvbdu4.txt
summary:
  The supremum condition identifies I • with the derivative ∂ S H(Z) of the Hamiltonian in minimal phase space coordinates from Eq. 9 with respect to the generalized momentum, and renders Re-solving the above supremum condition for S in terms of I • delivers Based on the Lagrangian in minimal state space coordinates, Hamilton's principle results in the stationarity condition Clearly, the Euler-Lagrange equation in minimal state space coordinates coincides with the single, non-linear ODE formulation of the time re-parameterized SIR model in Eq. 7. Alternatively, extended state space coordinates collectively assembled in the column matrix Q ∈ R 2 , i.e. the generalized coordinates jointly defined as the stock of individuals in the Infected and Susceptible compartments, span the two-dimensional state space Ë, J t = J · Q and J 2 = −I, an additional constraint for the extended phase space coordinates emerges The Hamiltonian H(Q, P ) in extended phase space coordinates thus follows from Legendre transformation by incorporating the constraint via the Lagrange multiplier Λ, i.e. Taking into account the explicit form of the Lagrangian L(Q, Q • ) in extended state space coordinates from Eq. 25 then renders the explicit representation of the Hamiltonian H(Q, P ) in extended phase space coordinates Invoking ∂ Q C(Q, P )


id: cord-310863-jxbw8wl2
author: PRASAD, J.
title: A data first approach to modelling Covid-19
date: 2020-05-26
extension: .txt
mime: text/plain
words: 7181
sentence: 323
flesch: 59
cache: cache/cord-310863-jxbw8wl2.txt
txt: txt/cord-310863-jxbw8wl2.txt
summary:
  In figure (9) we show the reconstruction for β(t), γ(t) and R(t)for Italy with SIR model and in figure (10) the same is shown for β(t), γ(t) and δ(t) in case of SIRD model. From Figure (5) we can conclude that different models can lead to the same amounts of flattening of the curve with a different choice of parameters so there is no preferred model for the suppression.


id: cord-005350-19za0msu
author: O’Regan, Suzanne M.
title: Theory of early warning signals of disease emergenceand leading indicators of elimination
date: 2013-05-31
extension: .txt
mime: text/plain
words: 14420
sentence: 618
flesch: 48
cache: cache/cord-005350-19za0msu.txt
txt: txt/cord-005350-19za0msu.txt
summary:
  (13) enables us to establish the quasi-stationary statistics that potentially could be used as leading indicators of a critical transition in SIS infectious disease systems. We further showed that moving-window estimates of these quantities may be used for anticipating critical transitions in infectious disease systems.


id: cord-248050-apjwnwky
author: Vrugt, Michael te
date: 2020-03-31
extension: .txt
mime: text/plain
words: 5115
sentence: 223
flesch: 46
cache: cache/cord-248050-apjwnwky.txt
txt: txt/cord-248050-apjwnwky.txt
title:
  Effects of social distancing and isolation on epidemic spreading: a dynamical density functional theory model

summary:
  This is crucial here as it allows to model effects of social distancing and selfisolation via a repulsive potential between the different persons. Figure 2 shows the time evolution of the total numbers S(t), I(t), and R(t) of susceptible, infected, and recovered persons, respectively, for the cases without interactions (usual SIR model with diffusion) and with interactions (our model).


id: cord-121428-79wyxedn
author: Dimarco, G.
title: Social contacts and the spread of infectious diseases
date: 2020-09-02
extension: .txt
mime: text/plain
words: 8658
sentence: 301
flesch: 47
cache: cache/cord-121428-79wyxedn.txt
txt: txt/cord-121428-79wyxedn.txt
summary:
  key: cord-121428-79wyxedn authors: Dimarco, G.; Perthame, B.; Toscani, G.; Zanella, M. title: Social contacts and the spread of infectious diseases date: 2020-09-02 journal: nan DOI: nan sha: doc_id: 121428 cord_uid: 79wyxedn Motivated by the COVID-19 pandemic, we introduce a mathematical description of the impact of sociality in the spread of infectious diseases by integrating an epidemiological dynamic with a kinetic modeling of population-based contacts. The kinetic description leads to study the evolution over time of Boltzmann type equations describing the number densities of social contacts of susceptible, infected and recovered individuals, whose proportions are driven by a classical compartmental model in epidemiology.


id: cord-316393-ozl28ztz
author: Enrique Amaro, José
title: Global analysis of the COVID-19 pandemic using simple epidemiological models
date: 2020-10-22
extension: .txt
mime: text/plain
words: 5299
sentence: 213
flesch: 51
cache: cache/cord-316393-ozl28ztz.txt
txt: txt/cord-316393-ozl28ztz.txt
summary:
  Discussion: the Kermack-McKendrick epidemic threshold theorem Stability analysis of SIR model with vaccination Seasonality and the effectiveness of mass vaccination Application of SIR epidemiological model: new trends Epidemic disease in England -the evidence of variability and of persistency of type Report on the Prevention of Malaria in Mauritius An application of the theory of probabilities to the study of a priori pathometry. Similar models are available


id: cord-220116-6i7kg4mj
author: Mukhamadiarov, Ruslan I.
title: Social distancing and epidemic resurgence in agent-based Susceptible-Infectious-Recovered models
date: 2020-06-03
extension: .txt
mime: text/plain
words: 4754
sentence: 160
flesch: 37
cache: cache/cord-220116-6i7kg4mj.txt
txt: txt/cord-220116-6i7kg4mj.txt
summary:
  In this study, we implemented social distancing control measures for simple stochastic SIR epidemic models on regular square lattices with diffusive spreading, two-dimensional Newman-Watts small-world networks that include highly infective long-distance connections, and static contact networks, either with random connectivity or scale-free topology. For each setup, we investigated epidemic outbreaks with model parameters informed by the known COVID-19 data (4).


id: cord-270519-orh8fd1c
author: Oliveira, A. C. S. d.
title: Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases
date: 2020-05-25
extension: .txt
mime: text/plain
words: 4265
sentence: 177
flesch: 50
cache: cache/cord-270519-orh8fd1c.txt
txt: txt/cord-270519-orh8fd1c.txt
summary:
  key: cord-270519-orh8fd1c authors: Oliveira, A. C. S. d.; Morita, L. H. M.; da Silva, E. B.; Granzotto, D. C. T.; Zardo, L. A. R.; Fontes, C. J. F. title: Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases date: 2020-05-25 journal: nan DOI: 10.1101/2020.05.24.20112029 sha: doc_id: 270519 cord_uid: orh8fd1c The novel of COVID-19 disease started in late 2019 making the worldwide governments came across a high number of critical and death cases, beyond constant fear of the collapse in their health systems. To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil.


id: cord-319435-le2eifv8
author: Rahman, Mohammad Mahmudur
date: 2020-04-23
extension: .txt
mime: text/plain
words: 4910
sentence: 248
flesch: 54
cache: cache/cord-319435-le2eifv8.txt
txt: txt/cord-319435-le2eifv8.txt
title:
  Impact of control strategies on COVID-19 pandemic and the SIR model based forecasting in Bangladesh.

summary:
  The prediction results are illustrated in Figure 05 and tabulated in the third column in Table 01 confirmed that by social distancing, COVID-19 infection cases can be controlled and reduced as well as the ending of the outbreak will be rapid. [6] , may help to keep infection number low..


id: cord-326631-7gd3hjc3
author: Ma, Junling
title: Generality of the Final Size Formula for an Epidemic of a Newly Invading Infectious Disease
date: 2006-04-08
extension: .txt
mime: text/plain
words: 7390
sentence: 363
flesch: 58
cache: cache/cord-326631-7gd3hjc3.txt
txt: txt/cord-326631-7gd3hjc3.txt
summary:
  However, noting that the exposed stage can be regarded as an infectious stage during which the transmission rate happens to be zero, we lose no generality by restricting attention to multiple infectious stage models, which we refer to as SI n R models if there are n infectious stages. With the assumption that q = 1 − e −R0 , Von Bahr and Martin-Lof (1980) and Scalia-Tomba (1985) showed that final size distribution for the traditional chain binomial model is asymptotically normal in the limit of large population size.


id: cord-346951-kvh9qt65
author: KUMAR, SUNNY
title: Predication of Pandemic COVID-19 situation in Maharashtra, India
date: 2020-04-11
extension: .txt
mime: text/plain
words: 1071
sentence: 61
flesch: 58
cache: cache/cord-346951-kvh9qt65.txt
txt: txt/cord-346951-kvh9qt65.txt
summary:
  The reproduction ratio is varied from 1.33 to 5 where infected population was increased in the high reproductive ratio. When susceptible are high than infected people will be more as shown in Figure 4 (c)-(d) and corresponding infected people at different reproduction ratio.


id: cord-280683-5572l6bo
author: Liu, Laura
title: Panel forecasts of country-level Covid-19 infections()
date: 2020-10-16
extension: .txt
mime: text/plain
words: 7198
sentence: 365
flesch: 56
cache: cache/cord-280683-5572l6bo.txt
txt: txt/cord-280683-5572l6bo.txt
summary:
  Our model could be generalized by adding additional knots in the deterministic trend component of infection growth rates, but the extension is not pursued in this paper. We specify a panel data model for infection growth rates y


id: cord-332922-2qjae0x7
author: Mbuvha, Rendani
title: Bayesian inference of COVID-19 spreading rates in South Africa
date: 2020-08-05
extension: .txt
mime: text/plain
words: 3225
sentence: 144
flesch: 48
cache: cache/cord-332922-2qjae0x7.txt
txt: txt/cord-332922-2qjae0x7.txt
summary:
  We follow the framework of [6] to perform Bayesian inference for model parameters on the South African COVID-19 data. The posterior inference is governed by Bayes theorem as follows: Where P(W|D, M) is the posterior distribution of a vector of model parameters (W) given the model(M) and observed data(D), P(D|W, M) is the data likelihood and P(D) is the evidence.


id: cord-314725-og0ybfzf
author: Marinov, Tchavdar T.
title: Dynamics of COVID-19 Using Inverse Problem for Coefficient Identification in SIR Epidemic Models
date: 2020-07-15
extension: .txt
mime: text/plain
words: 4764
sentence: 247
flesch: 59
cache: cache/cord-314725-og0ybfzf.txt
txt: txt/cord-314725-og0ybfzf.txt
summary:
  A deterministic model for highly contagious diseases: The case of varicella Classical and Modern Numerical Analysis: Theory, Methods and Practice, Chapman & Hall/CRC Numerical Analysis and Scientific Computing Infectious diseases of humans Numerical modeling and theoretical analysis of a nonlinear advection-reaction epidemic system Interepidemic Intervals in Forced and Unforced SEIR models Modelling Mathematical Methods and Scientific Computation An attempt at a new analysis of the mortality caused by smallpox and of the advantages of inoculation to prevent it Identification of heat-conduction coefficient via method of variational imbedding A note on the existence and stability of an inverse problem for a SIS model Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation Analysis and forecast of COVID-19 spreading in China Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare Qualitative study of a stochastic SIRS epidemic model with information intervention The mathematics of infectious diseases Analysis of SIR epidemic model with information spreading of awareness A contribution to the mathematical theory of epidemics Risk estimation of the SARS-CoV-2 acute respiratory disease outbreak outside China Early dynamics of transmission and control of COVID-19: a mathematical modelling study Global stability of a network-based SIRS epidemic model with nonmonotone incidence rate Dynamical behavior of a stochastic multigroup SIR epidemic model Novel numerical approach to solitary-wave solutions identification of Boussinesq and Korteweg-de Vries equations Coefficient Identification in Euler-Bernoulli Equation from over-posed data Inverse problem for coefficient identification in SIR epidemic models, Computers and Mathematics with Applications Coefficient identification in elliptic partial differential equation Inverse Problem for Coefficient Identification in Euler-Bernoulli Equation Clinical determinants of the severity of Middle East respiratory syndrome (MERS): a systematic review and meta-analysis Mathematical biology. Mathematical modeling and forecasting the spread of epidemic diseases has a long history, see [3] , [5] , [10] , and [31] .


id: cord-131678-rvg1ayp2
author: Ponce, Marcelo
date: 2020-09-02
extension: .txt
mime: text/plain
words: 15209
sentence: 1258
flesch: 66
summary: # retrieve aggregated data data <-covid19 . Date ( 2020 / 4 / 09 ) , days ) # data .
cache: cache/cord-131678-rvg1ayp2.txt
txt: txt/cord-131678-rvg1ayp2.txt
title:
  covid19.analytics: An R Package to Obtain, Analyze and Visualize Data from the Corona Virus Disease Pandemic


id: cord-342855-dvgqouk2
author: Anzum, R.
title: Mathematical Modeling of Coronavirus Reproduction Rate with Policy and Behavioral Effects
date: 2020-06-18
extension: .txt
mime: text/plain
words: 3087
sentence: 144
flesch: 51
cache: cache/cord-342855-dvgqouk2.txt
txt: txt/cord-342855-dvgqouk2.txt
summary:
  https://doi.org/10.1101/2020.06.16.20133330 doi: medRxiv preprint sectors by exploring compartmental models along with standard economic models using econometric techniques. The model estimates the vulnerability of the pandemic with a prediction of new cases by estimating a time-varying R0 to capture changes in the behavior of SIR model implies to new policy taken at different times and different locations of the world.


id: cord-318688-ditadt8l
author: Mitarai, O.
date: 2020-09-20
extension: .txt
mime: text/plain
words: 5908
sentence: 285
flesch: 62
cache: cache/cord-318688-ditadt8l.txt
txt: txt/cord-318688-ditadt8l.txt
title:
  Suppression of COVID-19 infection by isolation time control based on the SIR model and an analogy from nuclear fusion research

summary:
  key: cord-318688-ditadt8l authors: Mitarai, O.; Yanagi, N. title: Suppression of COVID-19 infection by isolation time control based on the SIR model and an analogy from nuclear fusion research date: 2020-09-20 journal: nan DOI: 10.1101/2020.09.18.20197723 sha: doc_id: 318688 cord_uid: ditadt8l The coronavirus disease 2019 (COVID-19) has been damaging our daily life after declaration of pandemic. Required isolation time to terminate the COVID-19 can be estimated by this proposed method.


id: cord-293148-t2dk2syq
author: Nadini, Matthieu
date: 2020-09-22
extension: .txt
mime: text/plain
words: 12287
sentence: 493
flesch: 49
cache: cache/cord-293148-t2dk2syq.txt
txt: txt/cord-293148-t2dk2syq.txt
title:
  A multi-agent model to study epidemic spreading and vaccination strategies in an urban-like environment

summary:
  Agents that exit their base location are likely to jump inside another location and interact with other agents occupying a different portion of the urban environment. In Random, we select the fraction of agents to vaccinate at random; in Center, we vaccinate first the agents that are assigned to central base locations, while in Peripheral, we prioritize vaccination for agents that belongs to the peripheral agents.


id: cord-289325-jhokn5bu
author: Lachiany, Menachem
title: Effects of distribution of infection rate on epidemic models
date: 2016-08-11
extension: .txt
mime: text/plain
words: 6824
sentence: 328
flesch: 53
cache: cache/cord-289325-jhokn5bu.txt
txt: txt/cord-289325-jhokn5bu.txt
summary:
  We propose here that the estimate of the change in the relative infection rate defined as I /I can be a good way to estimate the steady-state number of infected individuals in SIS models, and the total number of removed individuals in SIR models. key: cord-289325-jhokn5bu authors: Lachiany, Menachem; Louzoun, Yoram title: Effects of distribution of infection rate on epidemic models date: 2016-08-11 journal: Phys Rev E DOI: 10.1103/physreve.94.022409 sha: doc_id: 289325 cord_uid: jhokn5bu A goal of many epidemic models is to compute the outcome of the epidemics from the observed infected early dynamics.


id: cord-339789-151d1j4n
author: Hong, Hyokyoung G.
date: 2020-07-21
extension: .txt
mime: text/plain
words: 3939
sentence: 186
flesch: 53
cache: cache/cord-339789-151d1j4n.txt
txt: txt/cord-339789-151d1j4n.txt
title:
  Estimation of time-varying reproduction numbers underlying epidemiological processes: A new statistical tool for the COVID-19 pandemic

summary:
  bðtÞg À 1 ðtÞ < 1 leads to that i(t + 1) < i(t) or the number of infectious cases drops, meaning the spread of virus is controlled; otherwise, the number of infectious cases will keep increasing. We note that (9) is directly based on true numbers of infectious cases and removed cases derived from the discrete SIR model (6) .


id: cord-354627-y07w2f43
author: pinter, g.
title: COVID-19 Pandemic Prediction for Hungary; a Hybrid Machine Learning Approach
date: 2020-05-06
extension: .txt
mime: text/plain
words: 5485
sentence: 261
flesch: 45
cache: cache/cord-354627-y07w2f43.txt
txt: txt/cord-354627-y07w2f43.txt
summary:
  As an alternative to the SIR-based models, this study proposed machine learning as a new trend in advancing outbreak models. Outbreak prediction models have shown to be essential to communicate insights into the likely spread and consequences of COVID-19.


id: cord-186927-b8i85vo7
author: Hubert, Emma
title: Incentives, lockdown, and testing: from Thucydides's analysis to the COVID-19 pandemic
date: 2020-09-01
extension: .txt
mime: text/plain
words: 19294
sentence: 779
flesch: 53
cache: cache/cord-186927-b8i85vo7.txt
txt: txt/cord-186927-b8i85vo7.txt
summary:
  The associated reproduction number R 0 , commonly defined by R 0 := β/(ν + ρ) in the literature on epidemic models, is equal to 2.0, and is thus in the confidence interval of available data, see for example Li et al. This type of model seems in fact well suited to model epidemics related to new viruses, such as the COVID-19, when the immunity of infected persons has not yet been proved.


id: cord-241596-vh90s8vi
author: Libotte, Gustavo Barbosa
date: 2020-04-15
extension: .txt
mime: text/plain
words: 7213
sentence: 302
flesch: 41
cache: cache/cord-241596-vh90s8vi.txt
txt: txt/cord-241596-vh90s8vi.txt
title:
  Determination of an Optimal Control Strategy for Vaccine Administration in COVID-19 Pandemic Treatment

summary:
  Due to the favorable outcome of DE in solving mono-objective optimization problems, for different fields of science and engineering, Lobato and Steffen (2011) proposed the Multi-Objective Differential Evolution (MODE) algorithm to solve multi-objective optimization problems. The most common idea about multi-objective optimization found in the literature was originally proposed by Edgeworth (1881) and further generalized by Pareto (1896) .


id: cord-349898-nvi8h77t
author: Dinh, Ly
title: COVID‐19 pandemic and information diffusion analysis on Twitter
date: 2020-10-22
extension: .txt
mime: text/plain
words: 4779
sentence: 177
flesch: 48
cache: cache/cord-349898-nvi8h77t.txt
txt: txt/cord-349898-nvi8h77t.txt
summary:
  In light of diverse findings on the extent to which SIR models can explain information diffusion on social networks, we examine whether there are similarities in our simulated SIR model (SIRsim), observed SIR model based on actual COVID-19 cases (SIRemp), and observed information cascades on Twitter about the virus (INFOcas). In the context of social networks, information diffusion is formally defined as a process by which a piece of information is passed down from one node to another node through an edge (Gruhl, Guha, Liben-Nowell, & Tomkins, 2004; Guille, Hacid, Favre, & Zighed, 2013) .


id: cord-339425-hdf3blpu
author: Ahmetolan, Semra
date: 2020-09-03
extension: .txt
mime: text/plain
words: 5808
sentence: 244
flesch: 56
cache: cache/cord-339425-hdf3blpu.txt
txt: txt/cord-339425-hdf3blpu.txt
title:
  What Can We Estimate From Fatality and Infectious Case Data Using the Susceptible-Infected-Removed (SIR) Model? A Case Study of Covid-19 Pandemic

summary:
  medRxiv Qualitative analyses of communicable disease models On the uniqueness of epidemic models fitting a normalized curve of removed individuals Modelling the epidemic trend of the 2019 novel coronavirus outbreak in China. medRxiv Preliminary estimation of the basic reproduction number of novel coronavirus Samanlioglu F, Bilge AH, Ergonul O. A susceptible-exposed-infectedremoved (SEIR) model for the 2009-2010 A/H1N1 epidemic in Istanbul On the time shift phenomena in epidemic models Determination of epidemic parameters from early phase fatality data: a case study of the 2009 A (H1N1) pandemic in Europe The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


id: cord-320912-jfeu4tho
author: Fukui, M.
date: 2020-06-12
extension: .txt
mime: text/plain
words: 11778
sentence: 615
flesch: 55
cache: cache/cord-320912-jfeu4tho.txt
txt: txt/cord-320912-jfeu4tho.txt
title:
  Power Laws in Superspreading Events: Evidence from Coronavirus Outbreaks and Implications for SIR Models

summary:
  We then extend an otherwise standard SIR model with estimated power law distributions, and show that idiosyncratic uncertainties in SSEs will lead to large aggregate uncertainties in infection dynamics, even with large populations. Under thin-tailed distributions, such as the estimated negative binomial distribution or power law distribution with α = 2, the epidemiological outcomes will be essentially predictable.


id: cord-321984-qjfkvu6n
author: Tang, Lu
title: A Review of Multi‐Compartment Infectious Disease Models
date: 2020-08-03
extension: .txt
mime: text/plain
words: 21860
sentence: 867
flesch: 43
cache: cache/cord-321984-qjfkvu6n.txt
txt: txt/cord-321984-qjfkvu6n.txt
summary:
  Building sampling variations in infectious disease models makes a statistical modelling approach different from a mathematical modelling approach. Hence, statistical extensions are necessary to incorporate sampling uncertainty in estimation and inference for infectious disease models.


id: cord-335141-ag3j8obh
author: Higgins, G.C.
title: FFP3 reusable respirators for COVID-19; adequate and suitable in the healthcare setting
date: 2020-06-30
extension: .txt
mime: text/plain
words: 22066
sentence: 1026
flesch: 48
cache: cache/cord-335141-ag3j8obh.txt
txt: txt/cord-335141-ag3j8obh.txt
summary:
  When asked Would you think other patients would like to have a similar AR leaflet before surgery and Would you like to see further AR leaflets to be developed in the future? In addition to those directly working in the respiratory, infectious, cardiology, nephrology, psychology, and ICU departments and COVID-19 patients, all members of the general population may encounter the new coronavirus.


# url

id: cord-034824-eelqmzdx
domain: github.com
url:
  https://github.com/yangliangwei/influential-nodes-identification-in-complex-networksvia-information-entropy


# ent

id: cord-153905-qszvwqtj
sid: 30
eid: 4
type: ORG
entity:
  con los datos observados después de divididos por k. los enormes números máximos de enfermos observados se reducen


id: cord-153905-qszvwqtj
sid: 124
eid: 1
type: ORG
entity:
  decrezca en la inmportante región de los bajos valores es imprescindible que el valor en el tiempo de β *


id: cord-153905-qszvwqtj
sid: 162
eid: 3
type: ORG
entity:
  un ejemplo de que la correcta implantación de las medidas de aislamiento puede determinar un decaimiento exponencial de la pandemia


id: cord-153905-qszvwqtj
sid: 206
eid: 2
type: ORG
entity:
  muestra la evolución de infectados totales y observados para el caso de imponer un confinamiento más estricto


id: cord-153905-qszvwqtj
sid: 241
eid: 2
type: ORG
entity:
  y el enfásis de ambos análisis radica en que un control de la epidemia sólo se logra con un confinamiento riguroso


id: cord-153905-qszvwqtj
sid: 258
eid: 2
type: ORG
entity:
  de este trabajo es el hecho de que la dinámica de los parámetros que controlan la evolución de la epidemia es


