Summary of your 'study carrel' ============================== This is a summary of your Distant Reader 'study carrel'. The Distant Reader harvested & cached your content into a collection/corpus. It then applied sets of natural language processing and text mining against the collection. The results of this process was reduced to a database file -- a 'study carrel'. The study carrel can then be queried, thus bringing light specific characteristics for your collection. These characteristics can help you summarize the collection as well as enumerate things you might want to investigate more closely. This report is a terse narrative report, and when processing is complete you will be linked to a more complete narrative report. Eric Lease Morgan Number of items in the collection; 'How big is my corpus?' ---------------------------------------------------------- 58 Average length of all items measured in words; "More or less, how big is each item?" ------------------------------------------------------------------------------------ 4207 Average readability score of all items (0 = difficult; 100 = easy) ------------------------------------------------------------------ 55 Top 50 statistically significant keywords; "What is my collection about?" ------------------------------------------------------------------------- 21 COVID-19 11 covid-19 10 model 5 Fig 4 fractional 3 epidemic 3 India 2 control 2 case 2 SIR 2 SARS 2 LSTM 2 Italy 2 China 2 Caputo 2 ARIMA 1 vaccine 1 vaccination 1 topic 1 table 1 system 1 spread 1 room 1 rate 1 quarantine 1 player 1 optimal 1 n−1 1 new 1 mutation 1 market 1 logistic 1 individual 1 figure 1 disease 1 death 1 country 1 cluster 1 USA 1 Table 1 São 1 Sars 1 SIRS 1 SIDARTHE 1 Risk 1 Riesz 1 Paulo 1 Pakistan 1 Morocco 1 Legendre Top 50 lemmatized nouns; "What is discussed?" --------------------------------------------- 2304 model 1166 case 1045 disease 1000 time 984 epidemic 915 number 769 rate 724 individual 689 infection 685 system 678 population 673 r 658 datum 648 parameter 561 t 559 control 522 dynamic 500 country 487 equation 450 order 440 value 437 outbreak 427 virus 425 day 420 transmission 404 analysis 403 coronavirus 394 pandemic 371 result 368 spread 364 study 339 p 331 function 323 people 311 contact 310 network 302 equilibrium 279 measure 273 % 272 solution 269 death 263 strategy 258 γ 256 state 255 period 252 condition 234 approach 233 class 229 quarantine 229 effect Top 50 proper nouns; "What are the names of persons or places?" -------------------------------------------------------------- 817 COVID-19 297 Fig 277 China 274 t 236 SIR 234 S 199 SARS 158 al 149 India 139 n 137 Wuhan 136 CoV-2 128 Table 128 . 121 et 119 Coronavirus 112 March 112 Italy 109 Caputo 105 f 104 Eq 101 R 101 April 93 D 89 − 88 HIV 84 USA 83 covid-19 81 Health 80 T 74 u 74 E 72 β 70 SEIR 70 Analysis 68 ARIMA 67 January 67 Chaos 65 j 65 M 64 LSTM 64 COVID 63 Figure 61 Solitons 59 May 58 N 56 sha 56 n−1 55 DOI 54 Lyapunov Top 50 personal pronouns nouns; "To whom are things referred?" ------------------------------------------------------------- 1940 we 875 it 435 i 207 they 88 us 75 them 40 one 26 he 16 themselves 12 itself 6 she 4 you 4 him 4 's 3 u 2 s 2 ourselves 2 m 1 β 1 ŝ 1 theirs 1 oneself 1 herewith 1 her 1 328 Top 50 lemmatized verbs; "What do things do?" --------------------------------------------- 7436 be 1595 have 915 use 487 show 465 give 437 base 436 follow 383 infect 347 consider 311 see 308 propose 287 spread 280 obtain 267 apply 260 take 235 report 221 increase 220 predict 217 confirm 216 describe 212 find 210 do 208 reduce 201 model 196 present 195 estimate 194 assume 189 recover 187 represent 182 become 180 develop 170 provide 161 know 158 study 155 control 148 include 145 observe 144 make 132 define 125 compare 118 expose 114 get 109 change 106 decrease 105 indicate 105 affect 104 lead 103 let 103 analyze 102 solve Top 50 lemmatized adjectives and adverbs; "How are things described?" --------------------------------------------------------------------- 648 fractional 588 not 579 infected 421 also 398 different 392 new 385 infectious 358 more 358 covid-19 349 other 331 susceptible 326 such 319 mathematical 318 then 296 - 286 social 266 first 266 asymptomatic 247 well 239 therefore 239 novel 231 real 231 high 230 thus 219 numerical 214 total 205 most 203 positive 203 however 198 only 193 non 191 optimal 190 initial 183 differential 177 large 177 basic 175 many 163 same 161 as 156 stochastic 155 early 154 further 152 public 145 global 135 possible 135 low 134 various 132 daily 131 here 130 out Top 50 lemmatized superlative adjectives; "How are things described to the extreme?" ------------------------------------------------------------------------- 59 most 58 good 48 least 27 large 21 high 13 simple 11 low 10 Most 8 near 8 great 7 small 7 big 4 late 4 fast 4 bad 4 Least 2 βcS 2 sharp 2 busy 1 new 1 n(t 1 grave 1 deadly 1 cord-320980-srpgcy4b 1 -which Top 50 lemmatized superlative adverbs; "How do things do to the extreme?" ------------------------------------------------------------------------ 146 most 14 least 6 well 2 worst 1 lowest Top 50 Internet domains; "What Webbed places are alluded to in this corpus?" ---------------------------------------------------------------------------- 2 wsjkw.hlj.gov.cn 2 github.com 1 www.icmje.org 1 www.gsdata.cn 1 ourworldindata 1 lishuyan.lzu.edu.cn 1 doi.org 1 ai.baidu.com Top 50 URLs; "What is hyperlinked from this corpus?" ---------------------------------------------------- 2 http://wsjkw.hlj.gov.cn/ 2 http://github.com/indrajitg-r/COVID 1 http://www.icmje.org/recommendations/browse/roles-andresponsibilities/defining-the-role-of-authors-and-contributors.html#two 1 http://www.gsdata.cn/ 1 http://ourworldindata 1 http://lishuyan.lzu.edu.cn/COVID2019_2/ 1 http://doi.org/10.1016/j.chaos.2020.110016 1 http://ai.baidu.com/tech/nlp Top 50 email addresses; "Who are you gonna call?" ------------------------------------------------- 1 vladislav.nenchev@gmail.com 1 sachinraghav522@gmail.com 1 rmarques@fisica.ufpr.br 1 mbeims@fisica.ufpr.br 1 giuseppe.gaeta@unimi.it 1 elb@fisica.ufpr.br 1 danish_pha2007@nitsri.net 1 cesar.manchein@udesc.br Top 50 positive assertions; "What sentences are in the shape of noun-verb-noun?" ------------------------------------------------------------------------------- 10 model based study 5 model is able 5 model is then 4 countries are not 4 covid-19 confirmed cases 4 covid-19 is higher 4 epidemic spreading probability 4 epidemic spreading process 4 individuals are not 4 individuals do not 4 model does not 4 number is less 3 epidemic spreading significantly 3 individuals are equivalent 3 individuals become susceptible 3 model are positive 3 model did not 3 model is also 3 models are not 2 cases are asymptomatic 2 cases is much 2 cases using deep 2 coronavirus infected populations 2 countries have not 2 covid-19 is also 2 covid-19 was first 2 data are available 2 data becomes available 2 disease does not 2 disease spread curbs 2 epidemic be precisely 2 epidemic is not 2 epidemic model sipherd 2 epidemic spreading dynamics 2 individual becomes susceptible 2 individuals are more 2 individuals are very 2 individuals become much 2 individuals do so 2 individuals increase rapidly 2 individuals is often 2 infection is close 2 infection is not 2 infections has not 2 model described above 2 model gives root 2 model is effective 2 model is non 2 model is stable 2 model takes account Top 50 negative assertions; "What sentences are in the shape of noun-verb-no|not-noun?" --------------------------------------------------------------------------------------- 2 individuals are not willing 1 case are not enough 1 case is not conscious 1 cases had no significant 1 cases has not yet 1 control is not effective 1 countries are not alone 1 countries are not ready 1 countries have not yet 1 countries is not too 1 data are not available 1 epidemic is not high 1 individuals have no chance 1 individuals have no chances 1 individuals is not widely 1 infection has not yet 1 infection is not obvious 1 model does not really 1 models are not able 1 models do not always 1 number does not rep-90 1 order has no effect 1 pandemic is not over 1 parameter has no reasonable 1 population is not dramatically 1 r is not sufficient 1 rate does not significantly 1 rate is not just 1 rate is not uniform 1 system is not homogeneous 1 system is not overstretched 1 transmissions are not fully 1 virus is not yet A rudimentary bibliography -------------------------- id = cord-254195-k7e8g0ni author = Akinlar, M.A. title = Solutions of a disease model with fractional white noise date = 2020-04-30 keywords = Brownian; SIRS; fractional summary = There is no SIRS-type model which considers fractional epidemic disease models with fractional white noise or Wick product settings which makes the paper totally a new contribution to the related science. Fractional-stochastic calculus consist of fractional-order derivatives, integral operators or fractional Brownian motion and a noise term representing uncertainty or randomness in modeling. In the modeling of epidemic diseases via compartmental type mathematical models, there exists not any study considering fractional white noise, Wick product and fractional-order operators all together. From this listed contributions, we can say that the present paper is totally a new contribution to mathematical biologists studying compartment models by fractional and stochastic differential equations. The mathematical models describing epidemic diseases are generated by deterministic, stochastic or fractional-order system of ordinary differential equations. To the best of our knowledge, there exists not any mathematical model for a epidemic disease which considers both fractional-order operators and white noise together. doi = 10.1016/j.chaos.2020.109840 id = cord-320980-srpgcy4b author = Aldila, Dipo title = A mathematical study on the spread of COVID-19 considering social distancing and rapid assessment : The case of Jakarta, Indonesia date = 2020-06-28 keywords = COVID-19 summary = title: A mathematical study on the spread of COVID-19 considering social distancing and rapid assessment : The case of Jakarta, Indonesia The aim of this study is to investigate the effects of rapid testing and social distancing in controlling the spread of COVID-19, particularly in the city of Jakarta, Indonesia. The objective of our study is to analyze the effect of rapid testing and self-monitored isolation, and to predict the long-term dynamics of the incidence data of Jakarta, Indonesia. 265 Figure 10 : long-time simulation for prediction of incidence of COVID-19 in Jakarta with easing the social distancing policy combined with more massive rapid test and hospitalization. The model considers many important factors, such as hidden cases, rapid testing to trace hidden cases, limitation of medical resources, social distancing, quarantine/isolation, and parameter estimation for the incidence date from the city of Jakarta, Indonesia. doi = 10.1016/j.chaos.2020.110042 id = cord-308296-43gmzqa6 author = Alkahtani, Badr Saad T. title = A novel mathematics model of covid-19 with fractional derivative. Stability and numerical analysis date = 2020-06-17 keywords = n−1 summary = title: A novel mathematics model of covid-19 with fractional derivative. Uncertainties around the spread of Covid-19 have lead many researchers to understand investigation in many field of technology, science and engineering in the last five months since its appearance in Wuhan-China last December-2019 Many mathematical models were suggested in the last five months with the aim to understand the dynamics spread of the novel deathly disease [10] . with the function f differentiable then, the definition of the new fractional derivative (Atangana-Baleanu derivative in Caputo sense) is given as In this paper, we considered a set of 8 nonlinear ordinary differential equations to model the spread of covid-19 in a given population. We presented the positivity of each class as function of time, for classical and fractional case. New numerical approach for fractional differential equations doi = 10.1016/j.chaos.2020.110006 id = cord-337275-phgfpzbt author = Andrew, Jones title = Is Spread of COVID-19 a Chaotic Epidemic? date = 2020-10-20 keywords = country; covid-19; system summary = Traditional compartmental epidemiological models demonstrated limited ability to predict the scale and dynamics of COVID-19 epidemic in different countries. Our mathematical examination of COVID-19 epidemic data in different countries reveals similarity of this dynamic to the chaotic behavior of many dynamics systems, such as logistic maps. In a previous study, [4] demonstrated that the coronavirus raw data in China''s first two months of the disease suggest chaotic growth, similar to other epidemics like H1N1 and measles. These systems are now termed "chaotic." Unpredictability due to highly-sensitive reliance on initial conditions inspired the term "deterministic chaos." After Poincaré''s studies, the deterministic chaotic behavior was discovered in numerous dynamical systems and confirmed experimentally [15, 6, 2, 20] . Through use of an interactive data map, it was shown that the spread of COVID-19 exhibits the major characteristics of chaotic systems, namely, determinism, high sensitivity, large number of equilibria, and unpredictability. doi = 10.1016/j.chaos.2020.110376 id = cord-320262-9zxgaprl author = Asamoah, Joshua Kiddy K. title = Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment:using data from Ghana date = 2020-07-10 keywords = COVID-19; control summary = title: Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment:using data from Ghana that other optimal control model on COVID-19 have been studied (see for example [27, 28, 29 , 30, 31, The model further assumes that, no exposed individual transmits the disease. It is further inferred from this 310 study that; applying optimal control strategy on the rate at which the virus is released into the system, m 1 311 and m 2 , and also on the relative transmission rate due to human behaviour will considerably strike down 312 COVID-19 pandemic. Early dynamics of transmission and control 376 of COVID-19: a mathematical modelling study A model based study on the dynamics 431 of COVID-19: Prediction and control A model based study on the dynamics 431 of COVID-19: Prediction and control Modeling the impact of non-pharmaceutical interventions on the dynamics of 435 novel coronavirus with optimal control analysis with a case study Modelling of rabies transmission dynamics 477 using optimal control analysis doi = 10.1016/j.chaos.2020.110103 id = cord-308115-bjyr6ehq author = Baba, Isa Abdullah title = Fractional Order Model for the Role of Mild Cases in the Transmission of COVID-19 date = 2020-10-20 keywords = Caputo; model summary = To execute these measures effectively, there is need to have an in depth study about the number of persons that each infected individual can infect, meanwhile a mathematical model describing the transmission dynamics of the disease should be established. [6] developed a mathematical model (for MERS) inform of nonlinear system of differential equations, in which he considered a camel to be the source of infection that spread the virus to infective human population, then human to human transmission, then to clinic center then to care center. However, they constructed the Lyapunov candidate function to investigate the local and global stability analysis of the equilibriums solution and subsequently obtained the basic reproduction number or roughly, a key parameter describing transmission of the infection. A mathematical model for COVID-19 transmission by using the Caputo fractional derivative A fractional differential equation model for the COVID-19 transmission by using the Caputo-Fabrizio derivative doi = 10.1016/j.chaos.2020.110374 id = cord-332618-8al98ya2 author = Barraza, Néstor Ruben title = A non-homogeneous Markov early epidemic growth dynamics model. Application to the SARS-CoV-2 pandemic date = 2020-09-18 keywords = model summary = We propose a functional form of birth rate that depends on the number of individuals in the population and on the elapsed time, allowing us to model a contagion effect. Hence, 35 we propose a different model based on a Pure Birth process with an event rate that, like Polya''s, depends on both the elapsed time and the number of previous events, but with a different functional form. Our main motivation is to obtain a model that describes an epidemic outbreak at its first stage, before it reaches the inflection point in the case incidence curve, which is useful to monitor how contagion is spreading out. Since the mean value function of the Polya-Lundberg process is a linear function of time (see Appendix B), we introduce a modification in the event rate in order to get a mean value function that grows 85 subexponentially with either positive or negative concavity as we observe in the early epidemic growth curves usually reported. doi = 10.1016/j.chaos.2020.110297 id = cord-309758-2rnhrbeq author = Batistela, Cristiane M. title = SIRSi compartmental model for COVID-19 pandemic with immunity loss date = 2020-10-29 keywords = Fig; Paulo; São summary = The proposed Susceptible -Infected -Removed -Sick (SIRSi) model also considers birth and death of individuals in the given population and introduces a feedback from those in the recovered group who did not gain immunity or lost their immunity after a period of time. In this section the parameters of the proposed SIRSi model (1) (see Fig. 1 ) are numerically adjusted to fit the curve of confirmed symptomatic cases of three major cities in the state of São Paulo -Brazil, using publicly available data from the State Data Analysis System -SEADE ( Sistema Estadual de Análise de Dados 2 ) [47] . The proposed model with re-susceptibility feedback adjusted to the confirmed infection data, suggests the possibility that recovered patients may have temporary immunity γ > 0 or even permanent γ = 0 . doi = 10.1016/j.chaos.2020.110388 id = cord-301829-6yrgkx96 author = Bhardwaj, Rashmi title = Data Driven Estimation of Novel COVID-19 Transmission Risks Through Hybrid Soft-Computing Techniques date = 2020-07-25 keywords = COVID-19; China summary = Wavelet-based forecasting model predicts for shorter time span such as five to ten days advanced number of confirmed, death and recovered cases of China, India and USA. Study forecasted impending COVID-19 spread cases for China plus some other regions using mathematical & traditional time-series prediction models [22] . None of the authors have studied the wavelet based neuronal fuzzification hybrid model for the data of countrywise spread of COVID-19 genome. The forecast of 50-60 days ahead varying in every case helps to understand the clear picture of the pandemic spread and the manner in which the transmission rate may change in the following time periods in these three countries India, China and America. Data-based analysis, modelling and forecasting of the COVID-19 outbreak Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis doi = 10.1016/j.chaos.2020.110152 id = cord-334413-h6n36jei author = Bhattacharyya, Suvanjan title = A Novel CFD Analysis to Minimize the Spread of COVID-19 Virus in Hospital Isolation Room date = 2020-09-17 keywords = CFD; COVID-19; room summary = Present study investigates the effectiveness of conditioned air released from air-conditioning machines to mix with aerosol sanitizer to reach every point of the space of the isolation room so as to kill the COVID-19 virus which will help to protect the lives of doctors, nurses and health care workers. It is found from the analysis that high turbulent fields generated inside the isolation room may be an effective way of distributing sanitizer in entire volume of isolation room to kill the COVID-19 virus. As the medical treatments are often inaccurate, besides precautionary measures and supports, it is therefore reasonable to investigate the possibilities to sanitize the confined volume of air to mitigate the spread of COVID-19 virus inside the airborne infection isolation rooms, and ICUs of a hospital. The study has been carried out to investigate the effectiveness of conditioned air released from air-conditioning machines to mix with aerosol sanitizer so as to reach every corner of the isolation room and kill the COVID-19 virus. doi = 10.1016/j.chaos.2020.110294 id = cord-349841-eigcqb1b author = Boukanjime, Brahim title = Dynamics of a stochastic coronavirus (COVID-19) epidemic model with Markovian switching date = 2020-10-16 keywords = COVID-19 summary = title: Dynamics of a stochastic coronavirus (COVID-19) epidemic model with Markovian switching In this paper, we analyze a stochastic coronavirus (COVID-19) epidemic model which is perturbed by both white noise and telegraph noise incorporating general incidence rate. In fact, the COVID-19 epidemic model is unavoidably subjected to the environmental noise, which made the parameters involved in the system often fluctuate randomly around some average values as the surrounding environment fluctuation. In this paper, we propose a stochastic COVID-19 model adopting a generalized incidence function [25, 26] as follows: Note that the COVID-19 epidemic models may be perturbed by telegraph noise which can causes the system to switch from one environmental regime to another [22] . To study the dynamical behaviour of an epidemic model, we firstly need to consider whether the solution is global and positive. This paper investigates a stochastic epidemic model describing COVID-19 dynamics affected 125 by mixture of environmental perturbations modeled by white and telegraph noises. doi = 10.1016/j.chaos.2020.110361 id = cord-283291-lj3k53px author = Brugnago, Eduardo L. title = How relevant is the decision of containment measures against COVID-19 applied ahead of time? date = 2020-08-12 keywords = April; Brazil; Fig summary = The cumulative number of confirmed infected individuals by the new coronavirus outbreak until April 30(th), 2020, is presented for the countries: Belgium, Brazil, United Kingdom (UK), and the United States of America (USA). For Belgium, UK, and USA, countries with a large number of infected people, after the power-law growth, a distinct behavior is obtained when approaching saturation. We study how changing the social distance and the number of daily tests to identify infected asymptomatic individuals can interfere in the number of confirmed cases of COVID-19 when applied in three distinct days, namely April 16(th) (early), April 30(th) (current), and May 14(th) (late). One leading observation was that after an initial time with a low incidence of newly infected people, the growth of the cumulative number of confirmed cases for all studied countries followed a power-law. doi = 10.1016/j.chaos.2020.110164 id = cord-337760-joti9nwg author = Buldú, Javier M. title = The resumption of sports competitions after COVID-19 lockdown: The case of the Spanish football league date = 2020-06-04 keywords = COVID-19; player summary = Our results highlight the influence of the days between matches, the frequency of virus tests and their sensitivity on the number of players infected at the end of the season. The model, whose main parameters were based on the scientific literature concerning the infection and recovery periods of COVID-19, could be easily adapted to describe other kinds of sports competitions just by modifying the number of players and teams participating in the tournament. Table 1: Summary of the main parameters used in the model: Probability of being infected during the training period β train , during a match β match and from the player''s social circle β ext ; latent period σ −1 , infectious period γ −1 and quarantine period γ −1 Q ; probability of being detected as exposed (by virus test) µ E and as infectious (by virus test or by symptoms) µ I ; number of days between virus tests N test and matches N match . doi = 10.1016/j.chaos.2020.109964 id = cord-258235-khdyxiwe author = Chakraborty, Tanujit title = Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis date = 2020-04-30 keywords = ARIMA; CFR; covid-19 summary = To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. In this section, we first briefly discuss these datasets, followed by the development of the proposed hybrid model, and finally, the application of the proposed model to generate short-term forecasts of the future COVID-19 cases for five different countries. Algorithm 1 Proposed Hybrid ARIMA-WBF Model 1 Given a time series of length n, input the in-sample (training) COVID-19 daily cases data. Thus, these real-time short-term forecasts based on the proposed hybrid ARIMA-WBF model for Canada, France, India, South Korea, and the UK will be helpful for government officials and policymakers to allocate adequate health care resources for the coming days. doi = 10.1016/j.chaos.2020.109850 id = cord-295116-eo887olu author = Chimmula, Vinay Kumar Reddy title = Time Series Forecasting of COVID-19 transmission in Canada Using LSTM Networks() date = 2020-05-08 keywords = Canada; LSTM; covid-19; model summary = title: Time Series Forecasting of COVID-19 transmission in Canada Using LSTM Networks() Based on the public datasets provided by John Hopkins university and Canadian health authority, we have developed a forecasting model of COVID-19 outbreak in Canada using state-of-the-art Deep Learning (DL) models. In this novel research, we evaluated the key features to predict the trends and possible stopping time of the current COVID-19 outbreak in Canada and around the world. In this paper we presented the Long short-term memory (LSTM) networks, a deep learning approach to forecast the future COVID-19 cases. Recurrent LSTM networks has capability to address the limitations of traditional time series forecasting techniques by adapting nonlinearities of given COVID-19 dataset and can result state of the art results on temporal data. Accord-COVID-19 forecasting using LSTM Networks ing to this second model within 10 days, Canada is expected to see exponential growth of confirmed cases. doi = 10.1016/j.chaos.2020.109864 id = cord-308069-iydjrmhh author = Contreras, Sebastián title = Statistically-based methodology for revealing real contagion trends and correcting delay-induced errors in the assessment of COVID-19 pandemic date = 2020-07-03 keywords = COVID-19 summary = We address the existence of different delays in the report of new cases, induced by the incubation time of the virus and testing-diagnosis time gaps, and other error sources related to the sensitivity/specificity of the tests used to diagnose COVID-19. In a previous work , we proposed a methodology to obtain real-time estimations of the Effective Reproduction Number R t directly from raw data, which was satisfactorily applied to evaluate the panorama of the COVID-19 spread in different countries and to forecast its evolution (Medina-Ortiz et al., 2020a) . We present an analogous methodology to estimate the number of discharged/recovered individuals, based on the reported evolution of the viral infection, the performance of the different tests for its diagnosis, and the case fatality, which can be easily adapted for a particular country. doi = 10.1016/j.chaos.2020.110087 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 keywords = COVID-19; SIR; model summary = The data in [29] for China, South Korea, India, Australia, USA, Italy and the state of Texas (communities) are organised in the form of time-series where the rows are recordings in time (from January to June, 2020), and the three columns are, the total cases I d tot (first column), number of infected individuals I d (second column) and deaths D d (third column). Assuming the published data are reliable, the SIR model (1) can be applied to assess the spread of the COVID-19 disease and predict the number of infected, removed and recovered populations and deaths in the communities, accommodating at the same time possible surges in the number of susceptible individuals. In this work, we have augmented the classic SIR model with the ability to accommodate surges in the number of susceptible individuals, supplemented by recorded data from China, South Korea, India, Australia, USA and the state of Texas to provide insights into the spread of COVID-19 in communities. doi = 10.1016/j.chaos.2020.110057 id = cord-351343-zdh8ms1z author = Din, Anwarud title = STATIONARY DISTRIBUTION AND EXTINCTION OF STOCHASTIC CORONAVIRUS (COVID-19) EPIDEMIC MODEL date = 2020-06-24 keywords = COVID-19 summary = The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. In the recent study, we proposed a stochastic epidemic model for the transmission dynamics of the COVID-19 with a changing environment considering long term behavior. The present section is devoted to formulation of a model based on stochastic theory for studying the transmissions dynamic of the novel virus i.e., COVID-19 pandemic. This section is about studying the existence and uniqueness of solution of the proposed stochastic COVID-19 model (1). Proof: To prove the theorem, we shall apply direct integration to the proposed stochastic COVID-19 model (1) . With the help of stochastic theory, we developed a model for the novel COVID-19 keeping in view the characteristic of the disease to investigate the transmission dynamics with changing population environment. doi = 10.1016/j.chaos.2020.110036 id = cord-298626-duvzwxv0 author = Džiugys, Algis title = Simplified model of Covid-19 epidemic prognosis under quarantine and estimation of quarantine effectiveness date = 2020-07-29 keywords = case; new; quarantine summary = The model is developed on the basis of collected epidemiological data of Covid19 pandemic, which shows that the daily growth rate of new infections has tendency to decrease linearly when the quarantine is imposed in a country (or a region) until it reaches a constant value, which corresponds to the effectiveness of quarantine measures taken in the country. We propose to build epidemic analysis and model on the dynamics of rate of new infection cases as more reliable epidemiological data together with an assumption of effectiveness to isolate registered infectious during imposed quarantine. In order to predict Covid-19 disease spread in infected country or region with imposed quarantine, a model of the growth rate of new cases needs to be developed. doi = 10.1016/j.chaos.2020.110162 id = cord-344252-6g3zzj0o author = Farooq, Junaid title = A Novel Adaptive Deep Learning Model of Covid-19 with focus on mortality reduction strategies date = 2020-07-21 keywords = Risk; covid-19; death; model summary = We employ deep learning to propose an Artificial Neural Network (ANN) based and data stream guided real-time incremental learning algorithm for parameter estimation of a non-intrusive, intelligent, adaptive and online analytical model of Covid-19 disease. In this work, we employ deep learning to propose an Artificial Neural Network (ANN) based real-time online incremental learning technique to estimate parameters of a data stream guided analytical model of Covid-19 to study the transmission dynamics and prevention mechanism for SARS-Cov-2 novel coronavirus in order to aid in optimal policy formulation, efficient decision making, forecasting and simulation. To the best of our knowledge, this paper develops for the first time a deep learning model of epidemic diseases with data science approach in which parameters are intelligently adapted to the new ground realities with fast evolving infection dynamics. doi = 10.1016/j.chaos.2020.110148 id = cord-355419-8txtk0b3 author = Feng, Liang title = Epidemic in networked population with recurrent mobility pattern date = 2020-06-25 keywords = epidemic summary = In this paper, we utilize a discrete-time Markov chain approach and propose an epidemic model to describe virus propagation in the heterogeneous graph, which is used to represent individuals with intra social connections and mobility between individuals and common locations. Different from commonly used homogeneous mixing approaches [2, 3] , we give an analysis of epidemic spreading in population following a structured network with recurrent mobility pattern in this work. One widely used approach to analyse epidemic spreading in complex networks is metapopulation model, which divides the whole population into several geographical structured parts [13, 18] , and contacts among individuals in the same subpopulation are assumed to be well-mixed. In Section 2 , we give the formulation of epidemic model for virus spreading in networked population with recurrent mobility pattern, along with theoretical results of epidemic threshold. We formulate an epidemic model of virus propagating in networked population with recurrent mobility pattern between individuals and public areas. doi = 10.1016/j.chaos.2020.110016 id = cord-303030-8unrcb1f author = Gaeta, Giuseppe title = Social distancing versus early detection and contacts tracing in epidemic management date = 2020-07-16 keywords = COVID; Italy; SIR; epidemic summary = In this paper we discuss the different effects of these ingredients on the epidemic dynamics; the discussion is conducted with the help of two simple models, i.e. the classical SIR model and the recently introduced variant A-SIR (arXiv:2003.08720) which takes into account the presence of a large set of asymptomatic infectives. In the SIR model [1] [2] [3] [4] [5] , a population of constant size (this means the analysis is valid over a relatively short time-span, or we should consider new births and also deaths not due to the epidemic) is subdivided in three classes: Susceptibles, Infected (and by this also Infectives), and Removed. Acting on α or on β to get the same γ will produce different timescales for the dynamics; see Fig. 1 , in which we have used values of the parameters resulting from our fit of early data for the Northern Italy COVID-19 epidemic [7] . doi = 10.1016/j.chaos.2020.110074 id = cord-354792-6ckgxn9l author = Ghosh, Mousam title = Dynamic Model of Infected Population Due to Spreading of Pandemic COVID-19 Considering Both Intra and Inter Zone Mobilization Factors with Rate of Detection date = 2020-10-19 keywords = COVID-19; Fig summary = title: Dynamic Model of Infected Population Due to Spreading of Pandemic COVID-19 Considering Both Intra and Inter Zone Mobilization Factors with Rate of Detection In this paper a dynamic model of infected population due to spreading of pandemic COVID-19 considering both intra and inter zone mobilization factors with rate of detection has been proposed. In view of these, a dynamic model to predict the pattern and volume of infected population due to the spread of COVID-19 has been proposed in the present paper considering several real life factors such as intra and inter zone mobilization, lockdown on local and global activities before detection, rate of detection and the effects of quarantine after detection. In this paper a dynamic model of infected population due to spreading of pandemic COVID-19 considering both intra and inter zone mobilization factors with rate of detection, have been proposed with various operating procedures. doi = 10.1016/j.chaos.2020.110377 id = cord-327544-7ws2kleo author = Hammoumi, Aayah title = Impact assessment of containment measure against COVID-19 spread in Morocco date = 2020-08-22 keywords = COVID-19; Morocco summary = Since the appearance of the first case of COVID-19 in Morocco on March, 02,2020, the cumulative number of reported infectious cases continues to increase and, up to date, the peak-time of infection is not reached yet. In this study, we propose a Susceptible-Asymptomatic-Infectious deterministic model to evaluate the impact of compulsory containment imposed in Morocco on March, 21 on the spread of COVID-19 epidemic across the country. Since the containment measure started 19 days since the first reported case then the model equations without containment is defined for 0 ≤ t < t 0 := 19 as follows Here, we assume that confined asymptomatic and confined unreported individuals can still spread the virus to their families. We used reported infectious case data, from March 2nd to April 9th, 2020, provided by the Health Ministry of Morocco to parameterize the model. doi = 10.1016/j.chaos.2020.110231 id = cord-342591-6joc2ld1 author = Higazy, M. title = Novel Fractional Order SIDARTHE Mathematical Model of The COVID-19 Pandemic date = 2020-06-13 keywords = SIDARTHE; fractional; model summary = The existence of a stable solution of the fractional order COVID-19 SIDARTHE model is proved and the fractional order necessary conditions of four proposed control strategies are produced. In addition, we study an optimal control plans for the fractional order SIDARTHE model via four control strategies that include the availability of vaccination and existence of treatments for the infected detected three population fraction phases. Applying the fractional order differential equations numerical solver using MATLAB software, we show the dynamics of the state variables of the model and display the effect of changing the fractional derivative order on the system response. We also implement the optimal control strategies numerically for the fractional order SIDARTHE model. Figure 9 displays the phase plane of state variables: total infected ( ) and susceptible cases (S(t)) with different fractional derivative order . doi = 10.1016/j.chaos.2020.110007 id = cord-355689-mo4mvwch author = Huang, Jiechen title = Role of vaccine efficacy in the vaccination behavior under myopic update rule on complex networks date = 2019-09-06 keywords = individual; vaccination; vaccine summary = The results indicate that healthy individuals are often willing to inoculate the vaccine under the myopic update rule, which can stop the infectious disease from being spread, in particular, it is found that the vaccine efficacy influences the fraction of vaccinated individuals much more than the relative cost of vaccination on the regular lattice, Meanwhile, vaccine efficacy is more sensitive on the heterogeneous scale-free network. On the one hand, they classify these models according to source and type of information that individuals base their neighbors on, in which source of information may be local or global and the type of information that individuals change their behaviors are prevalence-based or belief-based; On the other hand, they classify the previous works based on the impact of individual behavior changes on the disease dynamics, which include the following three aspects: (i) the disease state; (ii) model parameters (infection or recovering rate); and (iii) the network contact structure relevant for the spread of epidemics. doi = 10.1016/j.chaos.2019.109425 id = cord-355267-ndzgxk0k author = Kassa, Semu M. title = Analysis of the mitigation strategies for COVID-19: from mathematical modelling perspective date = 2020-06-05 keywords = COVID-19; case; disease; figure summary = Whereas knowledge of the virus dynamics and host response are essential for formulating strategies for antiviral treatment, vaccination, and epidemiological control of COVID-19, estimation of changes in transmission over time can provide insights into the epidemiological situation and help to identify whether public health control measures are having a measurable effect [5, 39] . Applying the above described set of assumptions in the bounds for some of the parameters, we optimized the model output to fit the daily new cases data reported from the Hubei province, China. Analysis of the mitigation strategies for COVID-19 Figure 11 : Dynamics of the disease with at most 10% of the population in the class and at least 50% of the class are detected and quarantined just after Phase 1 period, with strict social distancing rule imposed for 11 weeks. doi = 10.1016/j.chaos.2020.109968 id = cord-299312-asc120pn author = Khoshnaw, Sarbaz H.A. title = A Quantitative and Qualitative Analysis of the COVID–19 Pandemic Model date = 2020-05-25 keywords = covid-19; model summary = Mathematical models with computational simulations are effective tools that help global efforts to estimate key transmission parameters and further improvements for controlling this disease. Interestingly, we identify that transition rates between asymptomatic infected with both reported and unreported symptomatic infected individuals are very sensitive parameters concerning model variables in spreading this disease. Interestingly, we identify that 27 transition rates between asymptomatic infected with both reported and unreported 28 symptomatic infected individuals are very sensitive parameters concerning model variables 29 This helps international efforts to reduce the number of infected 30 individuals from the disease and to prevent the propagation of new coronavirus more 31 widely on the community. This helps international efforts to reduce the number of infected 30 individuals from the disease and to prevent the propagation of new coronavirus more 31 widely on the community. One of the identified key parameters is the transmission rate 515 between asymptomatic infected and reported symptomatic individuals. doi = 10.1016/j.chaos.2020.109932 id = cord-288894-2iaq3ayv author = Kumar, Sachin title = A novel mathematical approach of COVID-19 with non-singular fractional derivative date = 2020-07-01 keywords = Legendre; fractional summary = A new operational matrix of fractional differentiation on domain [0, a], a ≥ 1, a ∈ N by using the extended Legendre polynomial on larger domain has been developed. Finally, we provide numerical evidence and theoretical arguments that our new model can estimate the output of the exposed, infected and asymptotic carrier with higher fidelity than the previous models, thereby motivating the use of the presented model as a standard tool for examining the effect of contact rate and transmissibility multiple on number of infected cases are depicted with graphs. We will present some numerical treatments based on the number of infected people increases with increment in contact rate. The derivation of operational matrix of fractional differentiation based on orthogonal Legendre polynomial on interval [0, a ] is derived in Section 3 . The use of this newly derived matrix with Legendre collocation method is applied to solve a system of fractional ordinary differential equation. doi = 10.1016/j.chaos.2020.110048 id = cord-312120-xt5v3bjh author = Lahmiri, Salim title = The Impact of COVID-19 pandemic upon Stability and Sequential Irregularity of Equity and Cryptocurrency Markets date = 2020-05-28 keywords = LLE; market summary = The measures of Largest Lyapunov Exponent (LLE) based on the Rosenstein''s method and Approximate Entropy (ApEn), which are robust to small samples, are applied to price time series in order to estimate degrees of stability and irregularity in cryptocurrency and international stock markets. During the COVID-19 pandemic period it was found that (a) the level of stability in cryptocurrency markets has significantly diminished while the irregularity level significantly augmented, (b) the level of stability in international equity markets has not changed but gained more irregularity, (c) cryptocurrencies became more volatile, (d) the variability in stability and irregularity in equities has not been affected, (e) cryptocurrency and stock markets exhibit a similar degree of stability in price dynamics, whilst finally (f) cryptocurrency exhibit a low level of regularity compared to international equity markets. Hence, measuring both LLE and approximate entropy in price time series allows to assess divergence/convergence and regularity/irregularity of cryptocurrency and stock time series before and during Covid-19 pandemic. doi = 10.1016/j.chaos.2020.109936 id = cord-316705-3wzurnfp author = Lalmuanawma, Samuel title = Applications of Machine Learning and Artificial Intelligence for Covid-19 (SARS-CoV-2) pandemic: A review date = 2020-06-25 keywords = SARS; covid-19 summary = A new novel model, that forecast and predicting 1-3 to 6 days ahead of total Covid-19 patient of 10 Brazilian states, using stacking-ensemble with support vector regression algorithm on the cumulative positive Covid-19 cases of Brazilian data was proposed, thus augmenting the short-term forecasting process to alert the healthcare expert and the government to tackle the pandemic [38] . A Canadian based forecasting model using time-series was developed employing Deep learning algorithm for the long-short-term-memory network, the studies found out a key factor intended for predicting the course with an ending point estimation of the current SARS-CoV-2 epidemic in Canada and all over the globe [40] . Since the outbreak of the novel SARS-CoV-2, scientists and medical industries around the globe ubiquitously urged to fight against the pandemic, searching alternative method of rapid screening and prediction process, contact tracing, forecasting, and development of vaccine or drugs with the more accurate and reliable operation. doi = 10.1016/j.chaos.2020.110059 id = cord-319804-i5oprni9 author = Mahajan, Ashutosh title = An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India date = 2020-07-28 keywords = COVID-19; India summary = In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. A different compartmental model SEIR [9] predicts the dynamics of the transmission of the COVID-19 for certain countries, and the impact of quarantine of the infected persons are also studied in it. We employ an improved mathematical model SIPHERD [19] for the COVID-19 pandemic embedding the purely asymptomatic infected cases and the transmission of the disease from them. The model simulations bring out the efficacy of different ways for the containment, by predicting the total number of active and confirmed cases, total deaths, and daily new positive cases considering various social distancing/lockdown conditions and the number of tests done per day. An epidemic model sipherd and its application for prediction of the spread of covid-19 infection for india and usa doi = 10.1016/j.chaos.2020.110156 id = cord-333162-gwmvsoru author = Malki, Zohair title = Association between Weather Data and COVID-19 Pandemic Predicting Mortality Rate: Machine Learning Approaches date = 2020-07-17 keywords = COVID-19; spread summary = title: Association between Weather Data and COVID-19 Pandemic Predicting Mortality Rate: Machine Learning Approaches In this work, various regressor machine learning models are proposed to extract the relationship between different factors and the spreading rate of COVID-19. The machine learning algorithms employed in this work estimate the impact of weather variables such as temperature and humidity on the transmission of COVID-19 by extracting the relationship between the number of confirmed cases and the weather variables on certain regions. Thus, from this result, we can conclude that temperature and humidity are important features for predicting COVID-19 mortality rate. For Italy, regions 33 with a temperature higher than 15 degrees Celsius and 34 75% humidity have less spread of COVID-19 cases. Temperature and latitude 554 analysis to predict potential spread and seasonality for COVID-555 19 Temperature, population and longitu-571 dinal analysis to predict potential spread for COVID-19 doi = 10.1016/j.chaos.2020.110137 id = cord-291227-dgjieg7t author = Mandal, Manotosh title = A model based study on the dynamics of COVID-19: Prediction and control date = 2020-05-13 keywords = COVID-19 summary = authors: Mandal, Manotosh; Jana, Soovoojeet; Nandi, Swapan Kumar; Khatua, Anupam; Adak, Sayani; Kar, T.K. title: A model based study on the dynamics of COVID-19: Prediction and control Further, we perform the sensitivity analysis of the essential reproduction number and found that reducing the contact of exposed and susceptible humans is the most critical factor in achieving disease control. Finally, we forecast a short-term trend of COVID-19 for the three highly affected states, Maharashtra, Delhi, and Tamil Nadu, in India, and it suggests that the first two states need further monitoring of control measures to reduce the contact of exposed and susceptible humans. A theoretical study on mathematical modeling of an 578 infectious disease with application of optimal control Early dynamics of transmission and control of COVID-19: a 591 mathematical modelling study. doi = 10.1016/j.chaos.2020.109889 id = cord-299810-e57pwgnx author = Martelloni, Gabriele title = Modelling the downhill of the Sars-Cov-2 in Italy and a universal forecast of the epidemic in the world date = 2020-07-01 keywords = Italy; Sars summary = Finally we study the behavior of the ratio infected over swabs for Italy, Germany and USA, and we show as studying this parameter we recover the generalized Logistic model used in [1] for these three countries. The parameters r 0 represents the rates of growth of epidemic, K is the carrying capacity for the classical logistic model, α is a constant in order to have a power low initial growth before LD, β is the exponent of the second term of equation 1 that represents the influence of asymptomatic; δ,a correction of the quadratic term of logistic, and γ are the constant parameters considering the influence of the government measures 1 , K f is a proportionality constant between deaths and total number of infected, while t d and t r are the delays of deaths and recoveries respect to infected respectively; the constant A represents the contribution of asymptomatic people as introduced in [1] and finally t 0 is the time of LD start. doi = 10.1016/j.chaos.2020.110064 id = cord-288080-rr9e61ay author = Mohadab, Mohamed El title = Bibliometric method for mapping the state of the art of scientific production in Covid-19 date = 2020-06-30 keywords = cluster; covid-19 summary = The latest statistics indicate that there has been an exponential increase in the number of publications since the discovery of the Covid-19 pandemic; the results provide a comprehensive view of interdisciplinary research in medicine, biology, finance and other fields. So the use of bibliometric analysis [2] to identify and analyze the scientific performance of authors, articles, journals, institutions, countries through the analysis of keywords and the number of citations constitutes an essential element which provides researchers with the means to identify avenues and new directions in relation to a theme of scientific research. In order to observe and evaluate the trends in publications in the thematic of Covid-19, the VOSviewer software was used to analyze the academic literature and examine the evolution of published articles, co-authorship, geographic area (country) of authors, co-citation, co-occurrence. Afterwards, a bibliometric analysis method was adopted in order to map the state of the art on the theme of Covid-19, so the three scientific databases (Scopus, Web of Science, Pubmed) were used. doi = 10.1016/j.chaos.2020.110052 id = cord-268630-vu8yyisx author = Mohammad, Mutaz title = Implicit Riesz wavelets based-method for solving singular fractional integro-differential equations with applications to hematopoietic stem cell modeling date = 2020-06-17 keywords = Riesz summary = title: Implicit Riesz wavelets based-method for solving singular fractional integro-differential equations with applications to hematopoietic stem cell modeling In this paper, an effective and accurate technique based on Riesz wavelets is presented for solving weakly singular type of fractional order integro-differential equations with applications to solve system of fractional order model that describe the dynamics of uninfected, infected and free virus carried out by cytotoxic T lymphocytes (CTL). Motivated by the above contributions and properties, that are essential to develop efficient algorithms for the numerical solutions of a given fractional integro-differential equations (FIDEs), the main goal of the proposed work is to develop an efficient algorithm based on Riesz wavelets using the collocation method to solve fractional order of integro-differential equations with weakly singular kernels. In this framework, the collocation method based on Riesz wavelets has been applied to numerically solve fractional order type of integro-differential equations with singular kernel type. doi = 10.1016/j.chaos.2020.109991 id = cord-261599-ddgoxape author = Nabi, Khondoker Nazmoon title = Forecasting of COVID-19 pandemic: From integer derivatives to fractional derivatives date = 2020-09-21 keywords = COVID-19; Caputo; model summary = In a recent study, Nabi [26] has proposed a new Susceptible-Exposed-Symptomatic Infectious-Asymptomatic Infectious-Quarantined-Hospitalized-Recovered-Dead (SEI D I U QHRD) compartmental mathematical model and calibrated model parameters to project the future dynamics of COVID-19 for various COVID-19 hotspots. The advantage of applying Caputo fractional derivatives to solve the proposed COVID-19 model is the dynamics of the model can be observed more deeply using the real-time Cameroon data. The aim of this work is to forecast the probable time and size of the epidemic peaks of the novel coronavirus outbreak in Cameroon by studying a realistic compartmental model using the robust concept of Caputo fractional derivative. Section 3 is devoted to model calibration using real data of reported cases of COVID-19 in Cameroon, global sensitivity analysis of the proposed model, and forecasting of the disease future dynamics. doi = 10.1016/j.chaos.2020.110283 id = cord-352990-0uglwvid author = Nadim, Sk Shahid title = Occurrence of backward bifurcation and prediction of disease transmission with imperfect lockdown: A case study on COVID-19 date = 2020-08-17 keywords = Table summary = title: Occurrence of backward bifurcation and prediction of disease transmission with imperfect lockdown: A case study on COVID-19 In this case, for imperfect lockdown, the basic reproduction number does not rep-90 resent the required elimination effort; rather, the effort at the turning point is described The paper is organized as follows: Our proposed mathematical model which incorporates 108 the lockdown of susceptible individuals and imperfect lockdown efficacy is described in 109 Section 2. backward bifurcation phenomenon, where two stable equilibria, namely the disease-free 387 equilibrium and an endemic equilibrium coexist when the corresponding basic number 388 of reproduction is less than unity. We have 394 seen that the disease-free equilibrium is globally asymptotically stable whenever the as-395 sociated basic reproduction number is less than unity for the perfect lockdown model. doi = 10.1016/j.chaos.2020.110163 id = cord-259846-oxbmtend author = Naik, Parvaiz Ahmad title = Global dynamics of a fractional order model for the transmission of HIV epidemic with optimal control date = 2020-06-18 keywords = AIDS; HIV; fractional summary = Furthermore, for the fractional optimal control problem associated with the control strategies such as condom use for exposed class, treatment for aware infectives, awareness about disease among unaware infectives and behavioral change for susceptibles, we formulated a fractional optimality condition for the proposed model. We incorporate into the model time dependent controls such as condom use for exposed individuals, treatment for infected female sex workers, awareness about the disease among unaware infectives and behavioral change for susceptibles in order to reduce the risk of the spread of HIV/AIDS disease. In order to justify our theoretical findings, we introduced in this section some numerical experiments obtained for different instances of fractional power κ for the HIV epidemic model without control (9) and with control (24) along with adjoint variable systems and the control strategies. We present the numerical results for the model (9) when all control measures are absent and also to examine the role of fractional order κ on the HIV disease spread. doi = 10.1016/j.chaos.2020.109826 id = cord-269363-drjj705k author = Nenchev, Vladislav title = Optimal quarantine control of an infectious outbreak date = 2020-07-28 keywords = control; optimal summary = An issue of practical concern for many disease outbreaks without an available vaccine, such as for SARS-CoV-2 as of June 2020, is minimizing the overall quarantine effort or the final outbreak size, while respecting control and capacity constraints on the current number of infections. Upon an outbreak of a previously unknown disease, better model parameter estimates can be obtained as more data becomes available, and the induced optimization problem can be recomputed in a data-driven receding horizon manner to improve actions. In this work, the goal is to obtain an optimal quarantine control policy u ( t ), t ∈ [0, t f ] for a fixed final time t f , that minimizes a weighted combination of the total number of infections and the overall number of quarantined individuals at time t f . doi = 10.1016/j.chaos.2020.110139 id = cord-328069-a9fi9ssg author = Pathan, Refat Khan title = Time Series Prediction of COVID-19 by Mutation Rate Analysis using Recurrent Neural Network-based LSTM Model date = 2020-06-13 keywords = SARS; mutation; rate summary = title: Time Series Prediction of COVID-19 by Mutation Rate Analysis using Recurrent Neural Network-based LSTM Model This study explores the mutation rate of the whole genomic sequence gathered from the patient''s dataset of different countries. Furthermore, based on the size of the dataset, the determined mutation rate is categorized for four different regions: China, Australia, The United States, and the rest of the World. Using this train and testing process, the nucleotide mutation rate of 400(th) patient in future time has been predicted. The complete genomic sequence (Wuhan-HU1) of this large RNA virus (SARS-CoV-2) was first discovered in the laboratory of China on 10th January [10] and placed in the NCBI GenBank. al have performed Phylogenetic analysis of SARS-CoV-2 virus based on the spike gene of the genomic sequence [17] . An adequate amount of gene dataset is currently available in the NCBI GenBank which has the complete genome sequence of SARS-CoV-2. doi = 10.1016/j.chaos.2020.110018 id = cord-311054-dwns5l64 author = Rafiq, Danish title = Evaluation and prediction of COVID-19 in India: a case study of worst hit states date = 2020-06-19 keywords = COVID-19; India summary = For example, in [12] , a data-driven estimation method like long short-term memory (LSTM) is used for the prediction of total number of COVID-19 cases in India for a 30-days ahead prediction window. The model is then used for the prediction of the total number of cases and deaths in most affected states of India for the next 30 days. To estimate the spread of COVID-19 in India, we used a Predictive Error Minimization (PEM) based system identification technique to identify a discrete-time, single-input, single-output (SISO) model [19] [20] [21] . The models were then verified on the testing data and upon validation, the models were used to predict the total number of cases and deaths for the next 30-days in the 10 worst hit states in India. As per our prediction based on data up to 17 th May 2020, Delhi along with other states would continue to see marginal surge in the number of COVID-19 cases owing to the relaxations in lock-down measures. doi = 10.1016/j.chaos.2020.110014 id = cord-301035-dz8642qx author = Rasheed, Jawad title = A Survey on Artificial Intelligence Approaches in Supporting Frontline Workers and Decision Makers for COVID-19 Pandemic date = 2020-10-10 keywords = COVID-19; Deep; Learning summary = As the pandemic has caused great disruption to normal day-to-day operations and created a sense of unknown amongst the public, many motivated scientists and citizens have tried to assist in the COVID-19 response by developing their own unique AI-based tools to solve a large number of problems, in a variety of applied domains, such as: COIVD-19 disease detection and classification, mortality rate prediction and severity assessment, outbreak forecasting and tracking, biological insight of SARS-Cov-2 strain, and drug discovery. The investigation of this paper reveals several AI-based approaches that have been proposed as potential ways to help, with the COVID-19 pandemic, covering everything from initial diagnoses via image diagnostics up to the presentation of models that help to understand the spread of COVID-19 and identify potential new outbreak areas. Detection of Coronavirus (COVID-19) Associated Pneumonia based on Generative Adversarial Networks and a Fine-Tuned Deep Transfer Learning Model using Chest X-ray Dataset doi = 10.1016/j.chaos.2020.110337 id = cord-301150-41lfsedz author = Sardar, Tridip title = Assessment of Lockdown Effect in Some States and Overall India: A Predictive Mathematical Study on COVID-19 Outbreak date = 2020-07-08 keywords = table summary = title: Assessment of Lockdown Effect in Some States and Overall India: A Predictive Mathematical Study on COVID-19 Outbreak By validating our model to the data on notified cases from five different states and overall India, we estimated several epidemiologically important parameters as well as the basic reproduction number (R(0)). Our result suggests that lockdown will be effective in those locations where a higher percentage of symptomatic infection exists in the population. Furthermore, the trend of the effective reproduction number (R(t)) during the projection period indicates if the lockdown measures are completely removed after May 17, 2020, a high spike in notified cases may be seen in those locations. • Using current estimate of the lockdown rate and different parameters of our mathe-230 matical model (see Table 1 and Therefore, lockdown will be effective in those region where higher 310 percentage of symptomatic infection is found in the population and also larger COVID-19 311 mass testing will be required to isolate the cases. doi = 10.1016/j.chaos.2020.110078 id = cord-280975-9hgtvm6d author = Sarkar, Kankan title = Modeling and forecasting the COVID-19 pandemic in India date = 2020-06-28 keywords = COVID-19; India summary = A sensitivity analysis is conducted to determine the robustness of model predictions to parameter values and the sensitive parameters are estimated from the real data on the COVID-19 pandemic in India. [27] extended the SEIR (susceptible-exposed-infectious-removed) compartment model to study the dynamics of COVID-19 incorporating public perception of risk and the number of cumulative cases. Here, we developed 70 a new epidemiological mathematical model for novel coronavirus or SARS-CoV-2 epidemic in India that extends the standard SEIR compartment model, alike to that studied by Tang et al. We develop here a classical SEIR (susceptible-exposed-infectious-recovered)-type epidemiological model 75 by introducing contact tracing and other interventions such as quarantine, lockdown, social distancing and isolation that can represent the overall dynamics of novel coronavirus or COVID-19 (SARS-CoV-2). The square of sum of 185 the error computed as Σ n i=1 (C(i) − S(i)) 2 , where C(i) represents the observed daily new COVID-19 cases on i-th day, S(i) is the SARII q S q model simulation on i-th day and n is the sample size of the observed data. doi = 10.1016/j.chaos.2020.110049 id = cord-315676-y0qbkszx author = Shahid, Farah title = Predictions for COVID-19 with Deep Learning Models of LSTM, GRU and Bi-LSTM date = 2020-08-19 keywords = ARIMA; LSTM summary = In this paper, proposed forecast models comprising autoregressive integrated moving average (ARIMA), support vector regression (SVR), long shot term memory (LSTM), bidirectional long short term memory (Bi-LSTM) are assessed for time series prediction of confirmed cases, deaths and recoveries in ten major countries affected due to COVID-19.  Statistical models as ARIMA, ML technique of SVR with polynomial and RBF kernels, and DL mechanisms of LSTM, GRU and Bi-LSTM are proposed to predict the COVID-19 three categories, confirmed cases, deaths and recovered cases for ten countries. Parameters with their values of SVR, ARIMA and LSTM is shown in Table 1 , while results of actual and predicted cases in three categories in terms of performance measures are presented in Table 2 .  COVID-19 dataset has been modelled using various regressors including ARIMA, SVR with polynomial and RBF kernels, LSTM, GRU and Bi-LSTM for future predictions on confirmed cases, deaths and recovered case for ten countries across the globe. doi = 10.1016/j.chaos.2020.110212 id = cord-311544-7ihtyiox author = Sun, Tingzhe title = Modeling COVID-19 Epidemic in Heilongjiang Province, China date = 2020-05-29 keywords = Heilongjiang; covid-19 summary = However, massive imported patients especially into Heilongjiang Province in China recently have been an alert for local COVID-19 outbreak. Stochastic simulations further showed that significantly increased local contacts among imported ''escaper'', its epidemiologically associated cases and susceptible populations greatly contributed to the local outbreak of COVID-19. Collectively, our model has characterized the epidemic of COVID-19 in Heilongjiang province and implied that strongly controlled measured should be taken for infected and asymptomatic patients to minimize total infections. Specifically, a recent ''super spreader'' or ''imported escaper'' in Heilongjiang province has led to tens of diagnosed or asymptomatic cases [3] . Using this model, we performed stochastic simulations and found that partial relief in strictly controlled interventions may contribute to the occurrence of diagnosed patients recently (from April 9 to April 19) provided that there is only one imported patient without surveillance [3] . Estimating the Effects of Asymptomatic and Imported Patients on COVID-19 Epidemic Using Mathematical Modeling doi = 10.1016/j.chaos.2020.109949 id = cord-290952-tbsccwgx author = Ullah, Saif title = Modeling the impact of non-pharmaceutical interventions on the dynamics of novel coronavirus with optimal control analysis with a case study date = 2020-07-03 keywords = Pakistan; covid-19; model summary = In this paper, we develop a mathematical model to explore the transmission dynamics and possible control of the COVID-19 pandemic in Pakistan, one of the Asian countries with a high burden of disease with more than 100,000 confirmed infected cases so far. In this paper, we develop a mathematical model to explore the transmission dynamics and possible control of the COVID-19 pandemic in Pakistan, one of the Asian countries with a high burden of disease with more than 100,000 confirmed infected cases so far. The effect of low (or mild), moderate, and comparatively strict control interventions like social-distancing, quarantine rate, (or contact-tracing of suspected people) and hospitalization (or self-isolation) of testing positive COVID-19 cases are shown graphically. The effect of low (or mild), moderate, and comparatively strict control interventions like social-distancing, quarantine rate, (or contact-tracing of suspected people) and hospitalization (or self-isolation) of testing positive COVID-19 cases are shown graphically. doi = 10.1016/j.chaos.2020.110075 id = cord-346185-qmu1mrmx author = Velásquez, Ricardo Manuel Arias title = Forecast and evaluation of COVID-19 spreading in USA with Reduced-space Gaussian process regression date = 2020-05-22 keywords = COVID-19; USA summary = title: Forecast and evaluation of COVID-19 spreading in USA with Reduced-space Gaussian process regression In this report, we analyze historical and forecast infections for COVID-19 death based on Reduced-Space Gaussian Process Regression associated to chaotic Dynamical Systems with information obtained in 82 days with continuous learning, day by day, from January 21(th), 2020 to April 12(th). According last results, COVID-19 could be predicted with Gaussian models mean-field models can be meaningfully used to gather a quantitative picture of the epidemic spreading, with infections, fatality and recovery rate. able on the Center for Systems Science and Engineering at Johns Hopkins University [6] , the available data analyzed is considered between January 21 th 2020 and April 39 12 th 2020, included, with a feedback process in a neural network applied; it allows 40 to examined the information in real time in each state, at Fig. 1 • . doi = 10.1016/j.chaos.2020.109924 id = cord-337256-b3j3kg73 author = Wang, Peipei title = Prediction of Epidemic Trends in COVID-19 with Logistic Model and Machine Learning Technics date = 2020-07-01 keywords = covid-19; logistic summary = title: Prediction of Epidemic Trends in COVID-19 with Logistic Model and Machine Learning Technics We integrate the most updated COVID-19 epidemiological data before June 16, 2020 into the Logistic model to fit the cap of epidemic trend, and then feed the cap value into Fbprophet model, a machine learning based time series prediction model to derive the epidemic curve and predict the trend of the epidemic. Many scholars have developed a number of predicting methods for the trend forecasting of COVID-19, in some severe countries and global [8, 9] , debating 30 about mathematical model, infectious disease model, and artificial intelligence model. The models based on mathematical statistics, machine learning and deep learning have been applied to the prediction of time series of epidemic development [10, 11] . Generalized logistic growth modeling of the covid-19 outbreak in 29 provinces in china and in the rest of the world doi = 10.1016/j.chaos.2020.110058 id = cord-019114-934xczf3 author = Zhan, Xiu-Xiu title = Epidemic dynamics on information-driven adaptive networks date = 2018-02-16 keywords = Fig; epidemic summary = Simulation results and numerical analyses based on the pairwise approach indicate that the information-driven adaptive process can not only slow down the speed of epidemic spreading, but can also diminish the epidemic prevalence at the final state significantly. By depicting preventive measures as the reduction of transmitting probability [20, 21] or particular states of individuals (immune or vaccination) [22] , previous models showed that the disease information diffusion indeed inhibits the epidemic spreading significantly (reduce the epidemic prevalence as well as enhance the epidemic threshold) [15, 23] . In this work, we consider a more complicated case that two dynamical processes (i.e., epidemic spreading and disease information diffusion) are spreading on adaptive networks. Both numerical analyses based on the pairwise approach and simulation results indicate that the information diffusion and the adaptive behavior of the nodes can inhibit the epidemic outbreak significantly. doi = 10.1016/j.chaos.2018.02.010 id = cord-317371-v7hmc9sj author = Zhang, Xiaolei title = Predicting turning point, duration and attack rate of COVID-19 outbreaks in major Western countries date = 2020-04-20 keywords = covid-19 summary = In this paper, we employed a segmented Poisson model to analyze the available daily new cases data of the COVID-19 outbreaks in the six Western countries of the Group of Seven, namely, Canada, France, Germany, Italy, UK and USA. Our analysis allowed us to make a statistical prediction on the turning point (the time that the daily new cases peak), the duration (the period that the outbreak lasts) and the attack rate (the percentage of the total population that will be infected over the course of the outbreak) for these countries. To identify the turning point and predict the further spread of COVID-19 outbreaks while accounting for governments enforcement of stay-at-home advises/orders, social distancing, lockdowns, and quarantines against COVID-19, we combine the power law with the exponential law for daily new cases based on a segmented Poisson model. doi = 10.1016/j.chaos.2020.109829 id = cord-325862-rohhvq4h author = Zhang, Yong title = Applicability of time fractional derivative models for simulating the dynamics and mitigation scenarios of COVID-19 date = 2020-06-04 keywords = COVID-19; China; Fig; model summary = The model results revealed that 1) the transmission, infection and recovery dynamics follow the integral-order SEIR model with significant spatiotemporal variations in the recovery rate, likely due to the continuous improvement of screening techniques and public hospital systems, as well as full city lockdowns in China, and 2) the evolution of number of deaths follows the time FDE, likely due to the time memory in the death toll. The main contributions of this work, therefore, include 1) the first application of FDEs in modeling the evolution of the COVID-19 death toll, 2) an updated SEIR model with a transient recovery rate to better capture the dynamics of COVID-19 pandemic within China and for other countries, and 3) a particle-tracking approach based on stochastic bimolecular reaction theory to evaluate the mitigation of the spread of the COVID-19 outbreak. doi = 10.1016/j.chaos.2020.109959 id = cord-353306-hwwswvi3 author = Zhu, Bangren title = Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics date = 2020-07-17 keywords = February; January; LDA; topic summary = COVID-19 blocked Wuhan in China, which was sealed off on Chinese New Year''s Eve. During this period, the research on the relevant topics of COVID-19 and emotional expressions published on social media can provide decision support for the management and control of large-scale public health events. The research assisted the analysis of microblog text topics with the help of the LDA model, and obtained 8 topics ("origin", "host", "organization", "quarantine measures", "role models", "education", "economic", "rumor") and 28 interactive topics. At the same time, the discussion rate of epidemic topics gradually weakens; (3) The political and economic center is an area where social media is highly concerned. The spatial division of the number of Weibo social media texts has a high correlation with the economic zone division; (4) The existence of the topic of "rumor" will enable people to have more communication and discussion. doi = 10.1016/j.chaos.2020.110123