LitCovid-sentences  

PMC:7175914 / 1488-33370 JSONTXT 11 Projects

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Id Subject Object Predicate Lexical cue
T14 0-12 Sentence denotes Introduction
T15 13-477 Sentence denotes In the past more than fifty days, the Chinese government and all the people in China fought against the COVID-19 disease, and employed extremely and rigorously controlling measures to protect the people avoiding the infection of the COVID-19 virus, such as the lockdown of many cities in Hubei province (e.g. Wuhan city) and initiating a top-level emergency response to rein in the outbreak of the epidemic associated with COVID-19 in the other provinces of China.
T16 478-839 Sentence denotes With these strong and effective strategic policies, the number of the daily new confirmed COVID-19 cases was significantly decreased from the largest value of 3887 at Feb 4, 2020 to the value of 648 at Feb 22, 2020 from the National Health Commission of the People's Republic of China (http://www.nhc.gov.cn/)(excluding more than 140,000 cases at Feb 12, 2020).
T17 840-1568 Sentence denotes Recently, more and more researchers have been paid large attention on the COVID-19 variations in China, such as detecting the clinical characteristics (Guan et al., 2020), estimating the spreading characteristics ([Wu et al., 2020], [Zhao et al., 2020a], [Zhao et al., 2020b]) and exploring the effects of the control strategies ([Chinazzi et al., 2020], [Huang et al., 2020], [Lin et al., 2020], [Tang et al., 2020a], [Tang et al., 2020b]).The individual behavioural reaction and governmental actions played a key role in controlling the spread of the COVID-19 outbreak for the public health in the world, e.g. holiday extension, travel restriction, hospitalisation and quarantine ([Chinazzi et al., 2020], [Lin et al., 2020]).
T18 1569-1724 Sentence denotes Until now, there are only few researches about the effects of different population migration and quarantine strategies on the COVID-19 variations in China.
T19 1725-1823 Sentence denotes Guangdong province has the largest gross domestic product (GDP) than the other provinces in China.
T20 1824-2089 Sentence denotes Moreover, according to the present COVID-19 variations and control strategies, the Guangdong province adjusted the emergency response level of epidemic prevention and control from the first level response to the second level at Feb 24, 2020 (http://www.gd.gov.cn/).
T21 2090-2170 Sentence denotes More and more workers will come back to Guangdong province from other provinces.
T22 2171-2329 Sentence denotes Thereby, we choose Guangdong province as a case study to explore the effects of the population migration and quarantine strategies on the COVID-19 variations.
T23 2330-2464 Sentence denotes Based on the present rigorous and extreme control measures in Hubei province, input population from Hubei province are not considered.
T24 2465-2732 Sentence denotes In this study, we focus on the input population and quarantine strategies influencing on the disease variations, including the peak values of the cumulative confirmed cases, the daily new increased confirmed cases and the confirmed cases, and the corresponding times.
T25 2733-2778 Sentence denotes The organization of this paper is as follows.
T26 2779-2871 Sentence denotes In the next section, the establishment of SEIRQ model, data and methodology are illustrated.
T27 2872-3007 Sentence denotes In “Result” section, the input population and quarantine strategies at different scenarios are investigated which are our main results.
T28 3008-3063 Sentence denotes A brief discussion is provided in “Discussion” section.
T29 3065-3098 Sentence denotes SEIRQ model, data and methodology
T30 3100-3111 Sentence denotes SEIRQ model
T31 3112-3514 Sentence denotes In this study, according to the characteristics of the COVID-19 transmission, the whole population at time t is divided into seven compartments which include the susceptible individuals S(t), exposed individuals E(t), infectious individuals I(t), removed individuals R(t), quarantined susceptible individuals S q(t), quarantined exposed individuals E q(t) and quarantined infectious individuals I q(t).
T32 3515-3665 Sentence denotes The COVID-19 disease is transmitted from I(t) to S(t) with the incidence rate of β, and from E(t) to S(t) with the incidence rate of σβ, respectively.
T33 3666-3745 Sentence denotes The susceptible individuals S(t) is partly quarantined with the rate of q 1(t).
T34 3746-3957 Sentence denotes We assume that exposed individuals E(t) and quarantined exposed individuals E q(t) are transmitted to infectious individuals I(t) and quarantined infectious individuals I q(t) with the same transition rate of ν.
T35 3958-4059 Sentence denotes The quarantined rates of exposed individuals E(t) and infectious individuals I(t) are q 1(t) and q 3.
T36 4060-4364 Sentence denotes The death rate induced by the COVID-19 disease is α in both infectious individuals I(t) and quarantined infectious individuals I q(t) which removed to the removed individuals R(t) . γ(t) is the recovery rate of quarantined infected individuals I q(t) which is the mainly part of removed individuals R(t).
T37 4365-4490 Sentence denotes Moreover, based on the population migration, we assume that the input population and output population have constant numbers.
T38 4491-4841 Sentence denotes Susceptible individuals S(t), exposed individuals E(t) and infectious individuals I(t) have their respective input individuals of p 1(t)A(t), p 2(t)A(t) and p 3(t)A(t), and the parameters p i(t), i  = 1, 2, 3 are the rates of susceptible individuals, exposed individuals, infectious individuals in the total input number of A(t) from other provinces.
T39 4842-4977 Sentence denotes The output population are B 1, B 2 and B 3 for the susceptible individuals S(t), exposed individuals E(t), infectious individuals I(t).
T40 4978-5075 Sentence denotes The COVID-19 disease transmission and population migration are demonstrated by Fig. 1 in details.
T41 5076-5128 Sentence denotes Figure 1 Flowchart of COVID-19 SEIRQ epidemic model.
T42 5129-5460 Sentence denotes The SEIRQ epidemic model can be described by the following system of ordinary differential equations(1) S′=p1(t)A(t)−βSI−σβSE−q1(t)S−B1,E′=p2(t)A(t)+βSI+σβSE−νE−q2(t)E−B2,I′=p3(t)A(t)+νE−q3I−αI−B3,R′=γ(t)Iq+αI+αIq,Sq′=q1(t)SEq′=q2(t)E−νEqIq′=q3I+νEq−γ(t)Iq−αIqwhere the prime (′) denotes the differentiation with respect to time t.
T43 5461-5558 Sentence denotes Here, parameters 0 <  β, ν, γ(t), α  < 1 and the quarantined rates 0 ≤  q 1(t), q 2(t), q 3  ≤ 1.
T44 5559-5678 Sentence denotes All the initial values of different individual groups: S(0), E(0), I(0), R(0), S q(0), E q(0), I q(0) are non-negative.
T45 5680-5684 Sentence denotes Data
T46 5685-6041 Sentence denotes In this study, the COVID-19 cases of Guangdong province, Hubei province and mainland China are obtained from the Health Commission of Guangdong Province (http://wsjkw.gd.gov.cn/), the Health Commission of Hubei Province (http://wjw.hubei.gov.cn/), and the National Health Commission of the People's Republic of China (http://www.nhc.gov.cn/), respectively.
T47 6042-6261 Sentence denotes The data are from Jan 20, 2020 to present which include the number of the cumulative confirmed cases, the number of the confirmed cases, the number of the cumulative cured cases and the number of cumulative death cases.
T48 6262-6453 Sentence denotes The numbers of the total population of Guangdong Province, Hubei Province and mainland China are employed at the end of 2018 from the National Bureau of Statistics (http://www.stats.gov.cn/).
T49 6454-6641 Sentence denotes The numbers of the input and output population from Hubei province and the other provinces of mainland China to Guangdong province are from the Baidu migration (http://qianxi.baidu.com/).
T50 6642-6817 Sentence denotes These data are covering the period of Jan 1, 2020 to Feb 20, 2020 which are employed to display the population migration variations from other provinces to Guangdong province.
T51 6818-7100 Sentence denotes Because the input population from Hubei province to Guangdong province is significantly decreased from 26.86% of the total input population at Jan 26, 2020 to the 6.84% at Jan 27, 2020, for the Guangdong province, the starting date of the COVID-19 disease data is from Jan 27, 2020.
T52 7102-7113 Sentence denotes Methodology
T53 7114-7221 Sentence denotes In this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases.
T54 7222-7348 Sentence denotes The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease.
T55 7349-7454 Sentence denotes The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.
T56 7455-7564 Sentence denotes The initial values and parameters can be obtained from the Text methodology of the supplementary information.
T57 7565-7898 Sentence denotes The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.
T58 7899-8294 Sentence denotes To compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios.
T59 8295-8654 Sentence denotes To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]).
T60 8655-8734 Sentence denotes The details are displayed in Text methodology of the supplementary information.
T61 8736-8742 Sentence denotes Result
T62 8744-8804 Sentence denotes Simulation and prediction of the COVID-19 disease variations
T63 8805-9027 Sentence denotes In this section, the variations of the COVID-19 in Guangdong province are simulated and predicted based on our SEIRQ model only considering the input population from the other provinces of China (excluding Hubei province).
T64 9028-9087 Sentence denotes The simulated period are from Jan 27, 2019 to Feb 19, 2020.
T65 9088-9190 Sentence denotes The parameter values and the initial values of our simulation and prediction are provided in Table 1 .
T66 9191-9346 Sentence denotes The performance is evaluated by the data from Feb 20, 2020 to Feb 23, 2020, and R  *  2, AE, RE, RMSE, MPAE and DISO are employed to quantify the accuracy.
T67 9347-9422 Sentence denotes The simulation and prediction results are displayed in Table 2 and Fig. 2 .
T68 9423-9486 Sentence denotes Table 1 Parameter estimates for COVID-19 in Guangdong province.
T69 9487-9530 Sentence denotes Parameter Definitions Esimated value Source
T70 9531-9582 Sentence denotes β Transmission incidence rate 2.45 × 10−8 Estimated
T71 9583-9667 Sentence denotes σ The fraction of transmission incidence rate for exposed individuals 0.63 Estimated
T72 9668-9714 Sentence denotes α Disease-induced death rate 0.00375 Estimated
T73 9715-9828 Sentence denotes ν Transmission rate of exposed individuals to the infected class 0.183 [Zhao et al., 2020a], [Zhao et al., 2020b]
T74 9829-9887 Sentence denotes γ(t) Recovery rate 0.008+0.19(1+e5.0126−0.1846t) Estimated
T75 9888-9952 Sentence denotes q1(t) Quarantined rate of susceptible individuals 0.28 Estimated
T76 9953-10013 Sentence denotes q2(t) Quarantined rate of exposed individuals 0.76 Estimated
T77 10014-10072 Sentence denotes q3 Quarantined rate of infected individuals 0.89 Estimated
T78 10073-10101 Sentence denotes A(t) Input number 86926 data
T79 10102-10129 Sentence denotes B1 Output number 21356 data
T80 10130-10207 Sentence denotes p1 The fraction of input population into susceptible class 0.9999927 Computed
T81 10208-10281 Sentence denotes p2 The fraction of input population into exposed class 0.0000073 Computed
T82 10282-10347 Sentence denotes p3 The fraction of input population into infected class 0 Assumed
T83 10348-10396 Sentence denotes Initial values Definitions Esimated value Source
T84 10397-10440 Sentence denotes N(0) Initial total population 113460000 GSY
T85 10441-10496 Sentence denotes S(0) Initial susceptible population 113346174 Estimated
T86 10497-10541 Sentence denotes E(0) Initial exposed population 31 Estimated
T87 10542-10587 Sentence denotes I(0) Initial infected population 19 Estimated
T88 10588-10653 Sentence denotes Sq(0) Initial quarantined susceptible population 113460 Estimated
T89 10654-10707 Sentence denotes Eq(0) Initial quarantined exposed population 128 data
T90 10708-10762 Sentence denotes Iq(0) Initial quarantined infected population 184 data
T91 10763-10802 Sentence denotes R(0 Initial recovered population 4 data
T92 10803-10813 Sentence denotes Note: GSY:
T93 10814-10851 Sentence denotes Guangdong Statistical Yearbook, 2019.
T94 10852-10934 Sentence denotes Table 2 Evaluation results of the simulation and prediction in Guangdong province.
T95 10935-10972 Sentence denotes Different cases Simulation Prediction
T96 10973-11015 Sentence denotes R * 2 AE MAPE (%) DISO 20/2 21/2 22/2 23/2
T97 11016-11043 Sentence denotes RE (%) RE (%) RE (%) RE (%)
T98 11044-11117 Sentence denotes Cumulative confirmed cases 0.9973 −5.33 2.54 0.06 −0.38 −0.45 −0.37 −0.37
T99 11118-11176 Sentence denotes Confirmed cases 0.9898 −2.63 3.86 0.11 2.68 1.51 0.81 7.07
T100 11177-11241 Sentence denotes Recovered cases 0.9934 −3.38 43.32 0.17 −2.09 −1.38 −3.75 −10.41
T101 11242-11426 Sentence denotes Figure 2 Simulation and prediction of the COVID-19 in Guangdong province. (A) cumulative confirmed cases; (B) daily new confirmed cases and (C) difference of increased confirmed cases.
T102 11427-11745 Sentence denotes The initial values and parameters are S(0) = 113346174, E(0) = 31, I(0) = 19, R(0) = 4, Sq(0) = 113460, Eq(0) = 128, Iq(0) = 184, A = 86926, B = 21356, p1 = 0.9999927, p2 = 0.0000073, p3 = 0, q1 = 0.28, q2 = 0.76, q3 = 0.89, α = 0.00375, β = 2.45 × 10−8, ν = 0.183, σ = 0.63, γ(t) = 0.008 + 0.19/(1 + e5.0126−0.1846t).
T103 11746-11872 Sentence denotes Our model has the ability to simulate and to predict the COVID-19 variations with the very high accuracy (Table 2 and Fig. 2).
T104 11873-12054 Sentence denotes Particularly, the determinant coefficients R* of the cumulative confirmed cases, confirmed cases and recovered cases are highly to 0.9973, 0.9898 and 0.9934, respectively (Table 2).
T105 12055-12198 Sentence denotes Very small estimations are obtained with the AE values of −5.33, −2.63 and −3.38 for the cumulative cases, confirmed cases and recovered cases.
T106 12199-12382 Sentence denotes The comprehensive accuracies of our model are quantitatively measured by the DISO with the values of 0.06, 0.11 and 0.17 for the cumulative cases, confirmed cases and recovered cases.
T107 12383-12686 Sentence denotes For the validation at Feb 20, Feb 21, Feb 22 and Feb 23, 2020, the very small RE values of the cumulative confirmed cases, confirmed cases and recovered cases indicate that our model also has very high accuracies and it can be employed to predict the future variations of the COVID-19 disease (Table 2).
T108 12687-12891 Sentence denotes Moreover, the largest number of cumulative confirmed cases is 1397 at May 7, 2020 which indicates that the COVID-19 disease will become extinction after 102 days in Guangdong province (Fig. 2A, STable 1).
T109 12892-13030 Sentence denotes The peak value time of daily new confirmed cases is Feb 1, 2020 which is highly agrement with the reported time at Jan 31, 2020 (Fig. 2B).
T110 13031-13232 Sentence denotes For the confirmed cases, the peak value and the corresponding time are both obtained by our model with the simulated values of 1002 at Feb 10, 2020 and reported values of 1007 at Feb 9, 2020 (Fig. 2C).
T111 13233-13374 Sentence denotes The number of the recovered cases will reach about 1400 which is consist with the future changes of the cumulative confirmed cases (Fig. 2D).
T112 13375-13561 Sentence denotes In order to further explore the forecasting accuracy of our model, we have been compared the forecasting result with the observed data prolonged 11 days from Feb 24, 2020 to Mar 4, 2020.
T113 13562-13670 Sentence denotes The absolute values of RE (relative error) of the cumulative confirmed cases are smaller than 1% (Table 3 ).
T114 13671-13838 Sentence denotes The corresponding figures also display that our model can capture the temporal variations in a relative longer period (see SFigure 1 in the supplementary information).
T115 13839-13906 Sentence denotes Table 3 Evaluation results of the prediction in Guangdong province.
T116 13907-13959 Sentence denotes RE (%) 24/2 25/2 26/2 27/2 28/2 29/2 1/3 2/3 3/3 4/3
T117 13960-14038 Sentence denotes Cumulative confirmed cases −2.30 −0.41 0.12 0.20 0.25 0.37 0.40 0.49 0.58 0.66
T118 14039-14124 Sentence denotes Confirmed cases −14.98 −19.21 −24.22 −26.74 −27.64 −30.81 −36.19 −35.94 −33.52 −34.68
T119 14125-14196 Sentence denotes Recovered cases 9.60 11.35 13.09 12.57 10.88 10.67 11.35 9.35 7.08 6.31
T120 14198-14248 Sentence denotes Effects of input population at different scenarios
T121 14249-14523 Sentence denotes The input population variations include the percentage changes p 2 of the exposed individuals and the number changes A of the input population which impact the disease on the peak value of the cumulative confirmed cases and the disease extinction time (Figure 3, Figure 4 ).
T122 14524-14915 Sentence denotes For the first time point t 1  = 10 (i.e. Feb 6, 2020), the days of disease extinction (DDE) are shortened to 78 days (i.e. Apr 13, 2020) and 69 days (i.e. Apr 4, 2020) at Sce 1: (p 2, A) = (p 2  * , 1.5A  *) and Sce 2: (p 2, A) = (p 2  * , 2A  *), and the maximum values of the cumulative confirmed cases (MVCCC) have the numbers of 1396 and 1397 [Fig. 3A, Supplementary table 1 (STable 1)].
T123 14916-15091 Sentence denotes For the confirmed cases, the peak values are nearly close to the baseline value with the number of 1003, and the corresponding times are same as the baseline value (STable 1).
T124 15092-15314 Sentence denotes Moreover, the confirmed cases of Sce 1 and Sce 2 have the same variations as the baseline result with their early disease extinction that are consist with the variations of the cumulative confirmed cases (Fig. 2A and 3 A).
T125 15315-15607 Sentence denotes For Sce 4, Sce 5, Sce 7 and Sce 8, compared with the baseline results, the DDE of these scenarios are 81 days (i.e. Apr 16, 2020), 59 days (i.e. Mar 25, 2020), 83 days (i.e. Apr 18, 2020) and 73 days (i.e. Apr 8, 2020), respectively which indicate the early extinction of COVID-19 (STable 1).
T126 15608-15713 Sentence denotes The MVCCC of the four scenarios are larger than the baseline result with the largest value (1448) in Sce:
T127 15714-15736 Sentence denotes 8 (Fig. 3A, STable 1).
T128 15737-15843 Sentence denotes For the confirmed cases, these scenarios are similar as these of the baseline results (Fig. 4A, STable 1).
T129 15844-16092 Sentence denotes Figure 3 Scenarios results of input population impacting on the cumuletive confirmed COVID-19 cases at four time points: (A) t1 = 10, (B) t1 = 20, (C) t1 = 28 and (D) t1 = 38 corresponding to Feb 6, 2020, Feb 16, 2020, Feb 24, 2020 and Mar 5, 2020.
T130 16093-16330 Sentence denotes Figure 4 Scenarios results of input population impacting on the confirmed COVID-19 cases at four time points: (A) t1 = 10, (B) t1 = 20, (C) t1 = 28 and (D) t1 = 38 corresponding to Feb 6, 2020, Feb 16, 2020, Feb 24, 2020 and Mar 5, 2020.
T131 16331-16674 Sentence denotes For Sce 3: (p 2, A) = (1.5p 2  * , A  *) and Sce 6: (p 2, A) = (2p 2  * , A  *), the increased percentage of the exposed individuals only impacted the number of the cumulative confirmed cases with the values of 1422 and 1447, and the corresponding DDE have only small changes with 105 days for Sce 3 and 107 days for Sce 6 (Fig. 3A, STable 1).
T132 16675-16823 Sentence denotes For the confirmed cases, they have the very similar variations as the baseline result in the peak value and the peak value time (Fig. 4A, STable 1).
T133 16824-16971 Sentence denotes For the other three time points t 1  = 20, t 1  = 28 and t 1  = 38, the differences of the scenarios results are similar as the these of t 1  = 10.
T134 16972-17246 Sentence denotes Moreover, for each scenario, the changes in the input population have the nearly same impacts on the disease variations among the four time points which display that the same input population strategies at different time points have no significant difference on the disease.
T135 17247-17543 Sentence denotes From the above analysis, it can be concluded that the increased numbers of the input population can mainly shorten the disease extinction days and the increased percentages of the exposed individuals of the input population increase the number of cumulative confirmed cases at a small percentage.
T136 17544-17697 Sentence denotes Both the increased input population and the increased exposed individuals have no impacts on the peak values and peak value times of the confirmed cases.
T137 17699-17749 Sentence denotes Effects of quarantine rates at different scenarios
T138 17750-17880 Sentence denotes In this section, the effects of quarantine rates at six scenarios on the COVID-19 variations are displayed in Figure 5, Figure 6 .
T139 17881-18162 Sentence denotes For the first time point t 1  = 10, Feb 6, 2020, Sce 1 (q 1, q 2) = (0q 1  * , 0q 2  *) has significantly negative impacts on the COVID-19 variations with the disease outbreak again which suggest the very high risks appear at the quarantine strategy of Sce 1 (Figure 5, Figure 6A).
T140 18163-18327 Sentence denotes Specifically, the confirmed cases reaches its first peak value as the baseline result at Feb 10, 2020, and then the number is decreased close to 97 at Mar 14, 2020.
T141 18328-18454 Sentence denotes A sharp increase is detected to the second peak value of the confirmed cases with the number of 1016704 at 165 days (Fig. 6A).
T142 18455-18571 Sentence denotes The disease will become extinction after 361 days with the MVCCC dramatically reaching to more than 9 million (Figs.
T143 18572-18589 Sentence denotes 5A and STable 2).
T144 18590-18853 Sentence denotes Sce 2: (q 1, q 2) = (0q 1  * , 0.5q 2  *) and Sce 3: (q 1, q 2) = (0q 1  * , q 2  *) have the similar impacts on the disease variations with the largest cumulative confirmed values of 1444 at 110 days (i.e. May 15, 2020), and 1416 at 105 days (i.e. May 10, 2020).
T145 18854-19057 Sentence denotes The DDE and MVCCC of Sce 4: (q 1, q 2) = (0.5q 1  * , 0.5q 2  *), Sce 5: (q 1, q 2) = (0.5q 1  * , q 2  *) and Sce 6: (q 1, q 2) = (q 1  * , 0.5q 2  *) are agreement with the baseline results (STable 2).
T146 19058-19193 Sentence denotes These three scenarios have very weak influences on the confirmed case variations compared with the baseline result (Fig. 6A, STable 2).
T147 19194-19442 Sentence denotes Figure 5 Scenarios results of quarantine rates impacting on the cumuletive confirmed COVID-19 cases at four time points: (A) t1 = 10, (B) t1 = 20, (C) t1 = 28 and (D) t1 = 38 corresponding to Feb 6, 2020, Feb 16, 2020, Feb 24, 2020 and Mar 5, 2020.
T148 19443-19680 Sentence denotes Figure 6 Scenarios results of quarantine rates impacting on the confirmed COVID-19 cases at four time points: (A) t1 = 10, (B) t1 = 20, (C) t1 = 28 and (D) t1 = 38 corresponding to Feb 6, 2020, Feb 16, 2020, Feb 24, 2020 and Mar 5, 2020.
T149 19681-19942 Sentence denotes For the other three time points, Sce 1: (q 1, q 2) = (0q 1  * , 0q 2  *) increased the MVCCC and prolonged the DDE with the values of 1430 at 123 days (i.e. May 28, 2020), 1416 at 115 days (i.e. May 20, 2020) and 1409 at 112 days (i.e. May 17, 2020) (STable 2).
T150 19943-20101 Sentence denotes The disease variations of the other scenarios are agreement with the baseline results which indicates the weak impacts of these scenarios (Fig. 5A, STable 2).
T151 20102-20394 Sentence denotes Moreover, we also explored that the second outbreak of the disease appears when both the values of q 1 and q 2 are nearly close to zero, such as (q 1, q 2) = (0.01q 1  * , 0.01q 2  *), (0q 1  * , 0.05q 2  *) at t 1  = 10, and (q 1, q 2) = (0q 1  * , 0q 2  *) at t 1  = 11 (Fig. 7 , STable 3).
T152 20395-20604 Sentence denotes This suggests that no quarantine or very weak quarantine on the susceptible individuals and exposed individuals before the days of the peak values of the confirmed cases may lead to the disease outbreak again.
T153 20605-20877 Sentence denotes Figure 7 Cumulative confirmed COVID-19 cases (A) and confirmed COVID-19 cases (B) at the scenarios of aspect 2 with (q1, q2) = (0.01q1 * , 0.01q2 *), (0q1 * , 0.05q2 *) at t1 = 10, and (q1, q2) = (0q1 * , 0q2 *) at t1 = 11, and the other parameters as the baseline values.
T154 20879-20955 Sentence denotes Effects of both input population and quarantine rates at different scenarios
T155 20956-21089 Sentence denotes The impact results of both the input population and quarantine rates on the COVID-19 disease are displayed in Fig. 8, 9 and STable 3.
T156 21090-21344 Sentence denotes According to the results in “Effects of input population at different scenarios” and “Effects of quarantine rates at different scenarios” sections, the second outbreak of the disease are obtained in the scenarios with no or very weak quarantine strategy.
T157 21345-21361 Sentence denotes Therefore, Figs.
T158 21362-21517 Sentence denotes 8 and 9 only provide the COVID-19 disease variations of the scenarios with second outbreak, and the disease variations in other scenarios are not provided.
T159 21518-21569 Sentence denotes STable 4 provides the results of all the scenarios.
T160 21570-21844 Sentence denotes Figure 8 Scenarios results of both input population and quarantine rates impacting on the cumuletive confirmed COVID-19 cases at four time points: (A) t1 = 10, (B) t1 = 20, (C) t1 = 28 and (D) t1 = 38 corresponding to Feb 6, 2020, Feb 16, 2020, Feb 24, 2020 and Mar 5, 2020.
T161 21845-22120 Sentence denotes Figure 9 Scenarios results of both input population and quarantine rates impacting on the cumuletive confirmed COVID-19 cases at four time points: (A) t1 = 10, (B) t1 = 20, (C) t1 = 28 and (D) t1 = 38 corresponding to Feb 6, 2020, Feb 16, 2020, Feb 24, 2020 and Mar 5,  2020.
T162 22121-22513 Sentence denotes For time point t 1  = 10, Sce 1: (p 2, A, q 1, q 2) = (1.5p 2  * , 1.5A  * , 0q 1  * , 0q 2  *), Sce 2: (p 2, A, q 1, q 2) = (1.5p 2  * , 2A  * , 0q 1  * , 0q 2  *), Sce 7: (p 2, A, q 1, q 2) = (2p 2  * , 1.5A  * , 0q 1  * , 0q 2  *) and Sce 8: (p 2, A, q 1, q 2) = (2p 2  * , 2A  * , 0q 1  * , 0q 2  *) have the MVCCC larger than 10 million at 328, 313, 327 and 312 days (Fig. 8A, STable 3).
T163 22514-22819 Sentence denotes In fact, they have the two outbreaks of the disease with the confirmed cases having the first peak value as the baseline result at Feb 10, 2020 and the second peak values larger than 1 million at 142 days, 132 days, 141 days and 130 days for Sce1, Sce 2, Sce 7 and Sce 8, respectively (Fig. 9A, STable 3).
T164 22820-22947 Sentence denotes The magnified figure in the period of Jan 27, 2020-Apr 26, 2020 clearly displays the second outbreak of this disease (Fig. 9A).
T165 22948-23129 Sentence denotes Moreover, the weak changes of the four scenarios in the quarantine rates or around the time point t 1  = 10, the second outbreak also resulted in the second outbreak of the disease.
T166 23130-23425 Sentence denotes If the control measures employed as the four scenarios after the other three time points t 1  = 20, t 1  = 28, and t 1  = 38, the MVCCC are rapidly decreased with still larger than the baseline results, and the DDE are prolonged except the Sce 2 and Sce 8 of t 1  = 28, and t 1  = 38 (STable 4).
T167 23426-23450 Sentence denotes For the other scenarios:
T168 23451-23617 Sentence denotes Sce 3-Sce 6 and Sce 9-Sce 12 of the four time points, the DDE become smaller than the baseline result due to the larger input population and more exposed individuals.
T169 23618-23773 Sentence denotes Moreover, the weaker quarantine rates together with the more input population resulted in the more infected individuals and increased the MVCCC (STable 4).
T170 23775-23785 Sentence denotes Discussion
T171 23786-23968 Sentence denotes Since the COVID-19 disease reported in Wuhan city, Hubei province of China, the Chinese government and all the people have been fighting against the disease for more than two months.
T172 23969-24178 Sentence denotes Now, the daily new confirmed cases have been continuously decreasing, and the latest value is 427 at Feb 28, 2020 from the National Health Commission of the People's Republic of China (http://www.nhc.gov.cn/).
T173 24179-24408 Sentence denotes According to the present COVID-19 disease situation, some provinces have been adjusted the emergency response level of epidemic prevention and control from the first level response to the second level, such as Guangdong province.
T174 24409-24490 Sentence denotes More and more workers are coming back to Guangdong province from other provinces.
T175 24491-24733 Sentence denotes To address the effects of the input population on the disease variations, taking Guangdong province as a case study, the impacts of the input population and quarantine strategies are explored using a dynamical epidemic model at three aspects.
T176 24734-24988 Sentence denotes They include aspect 1: effects of the input population at different scenarios; aspect 2: effects of quarantine rates at different scenarios and the last aspect (i.e. aspect 3): effects of both input population and quarantine rates at different scenarios.
T177 24989-25177 Sentence denotes For the population flow, recent study ([Tang et al., 2020a], [Tang et al., 2020b]) considered the data from the Baidu migration website in a stochastic discrete transmission dynamic model.
T178 25178-25356 Sentence denotes Both our study and [Tang et al., 2020a], [Tang et al., 2020b] obtained the risk of the secondary outbreak when the population flow are changed at a serious input population flow.
T179 25357-25628 Sentence denotes In [Tang et al., 2020a], [Tang et al., 2020b], with more data from the Health Commission of Shananxi Province, they estimated the daily new increased confirmed cases, and the daily new increased infectious individuals from the population flow by the Poisson distribution.
T180 25629-25796 Sentence denotes In our study, constrained by the data policy of the Health Commission of Guangdong Province, the input population is defined as the deterministic and continuous input.
T181 25797-26113 Sentence denotes Moreover, the ratio of the exposed individuals accounting for the input population is defined as the percentages of the exposed individuals in the total population of China excluding Guangdong and Hubei provinces which is derived from the daily new increased confirmed cases according to the 3–7 days latent periods.
T182 26114-26316 Sentence denotes In the development of the COVID-19 model, [Tang et al., 2020a], [Tang et al., 2020b] considered the quarantined susceptible individuals returned back to susceptible individuals after 14 days quarantine.
T183 26317-26410 Sentence denotes While this condition is not included in our study the major reasons are displayed as follows.
T184 26411-26559 Sentence denotes Under the present quarantine strategies in China, the susceptible individuals are quarantined in the forms of home quarantine, community quarantine.
T185 26560-26959 Sentence denotes Although the quarantined susceptible individuals can be returned to susceptible individuals after 14 days, they will certainly employ very strict other controlling strategies against the COVID-19 virus, such as wearing the medical masks and washing their hands frequently, and which result in only very small part of the quarantined susceptible individuals back to the truth susceptible individuals.
T186 26960-27106 Sentence denotes For the simulation and prediction abilities of our model, it displayed that our model can well capture the COVID-19 variations with high accuracy.
T187 27107-27212 Sentence denotes In general, it is very hard to capture the disease variations with high accuracy by the dynamical models.
T188 27213-27325 Sentence denotes We have been compared our forecasting with the observed data prolonged 11 days from Feb 24, 2020 to Mar 4, 2020.
T189 27326-27433 Sentence denotes The absolute values of RE (relative error) of the cumulative confirmed cases are smaller than 1% (Table 2).
T190 27434-27601 Sentence denotes The corresponding figures also display that our model can capture the temporal variations in a relative longer period (see SFigure 1 in the supplementary information).
T191 27602-27796 Sentence denotes The weaker forecasting capabilities from Feb 24, 2020 to Mar 4, 2020 than these from Feb 20, 2020 to Feb 23, 2020 are resulted by the parameter estimation period of Jan 19, 2020 to Feb 19, 2020.
T192 27797-27986 Sentence denotes At the same time, it inspired that if we want to obtain a high accuracy in a relative longer period the dataset used to estimate the parameters should be changed or prolonged with the time.
T193 27987-28259 Sentence denotes Our result indicated that the increased numbers of the input population can mainly shorten the disease extinction days and the increased percentages of the exposed individuals of the input population increase the number of cumulative confirmed cases at a small percentage.
T194 28260-28413 Sentence denotes Both the increased input population and the increased exposed individuals have no impacts on the peak values and peak value times of the confirmed cases.
T195 28414-28633 Sentence denotes For the impacts of aspect 2, no quarantine or very weak quarantine on the susceptible individuals and exposed individuals before the days of the peak values of the confirmed cases may lead to the disease outbreak again.
T196 28634-28717 Sentence denotes This proves the significant role of the quarantine strategy on the disease control.
T197 28718-28927 Sentence denotes If we increase the input population and decrease the quarantine strategy together around the time point of the peak value of the confirmed cases, there will appear second outbreak of the disease exponentially.
T198 28928-29107 Sentence denotes Moreover, the weaker quarantine rates together with the more input population resulted in the more infected individuals and increased the number of the cumulative confirmed cases.
T199 29108-29216 Sentence denotes More information about our simulation and quarantine situation can be explored if more data can be obtained.
T200 29217-29442 Sentence denotes In this study, to address the quarantine situation in Guangdong province, 108 scenarios are listed from the input population and quarantine strategies which may include the present quarantine strategies in Guangdong province.
T201 29443-29619 Sentence denotes The other further analysis of the COVID-19 variations, such as the daily number of people under medical observation, will be explored when more new data are obtained in future.
T202 29620-29840 Sentence denotes Based the above analysis, we have the major conclusions as follows.(1) The COVID-19 disease variations can be simulated by our models with very high accuracy, including the cumulative confirmed cases and confirmed cases.
T203 29841-30023 Sentence denotes (2) Under the present daily input population and quarantine strategy, the COVID-19 disease will become extinction in May 11, 2020, with the cumulative confirmed cases number of 1397.
T204 30024-30250 Sentence denotes (3) In Guangdong province, the adjustment of the emergency response level of epidemic prevention and control from the first level response to the second level at Feb 24, 2020 is reasonable which is also predicted by our model.
T205 30251-30430 Sentence denotes (4) The disease will have a second outbreak risk when the input population is remarkably increased and the present quarantine strategy rapidly decreases to the values around zero.
T206 30432-30474 Sentence denotes Ethics approval and consent to participate
T207 30475-30588 Sentence denotes Because no individual patient's data was employed, the ethical approval or individual consent was not applicable.
T208 30590-30624 Sentence denotes Availability of data and materials
T209 30625-30657 Sentence denotes All data are publicly available.
T210 30659-30666 Sentence denotes Funding
T211 30667-30741 Sentence denotes This research was supported by National Natural Science Foundation of P.R.
T212 30742-30759 Sentence denotes China [11771373].
T213 30761-30771 Sentence denotes Disclaimer
T214 30772-31016 Sentence denotes The funding agencies had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
T215 31018-31039 Sentence denotes Conflict of interests
T216 31040-31183 Sentence denotes We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work.
T217 31185-31207 Sentence denotes Authors’ contributions
T218 31208-31221 Sentence denotes Study design:
T219 31222-31295 Sentence denotes Zengyun Hu, Qianqian Cui, Junmei Han and Zhidong Teng; Conceptualization:
T220 31296-31338 Sentence denotes Zengyun Hu, Qianqian Cui; Data collection:
T221 31339-31394 Sentence denotes Junmei Han, Zengyun Hu and Qianqian Cui; Data analysis:
T222 31395-31435 Sentence denotes Zengyun Hu, Qianqian Cui; Visualization:
T223 31436-31470 Sentence denotes Qianqian Cui, Junmei Han; Writing:
T224 31471-31502 Sentence denotes Zengyun Hu; Review and editing:
T225 31503-31528 Sentence denotes Zhidong Teng, Zengyun Hu.
T226 31529-31565 Sentence denotes In the revised processes, Dr. Wei E.
T227 31566-31568 Sentence denotes I.
T228 31569-31711 Sentence denotes Sha from Zhejiang University provided important suggestions to address the quarantine strategy and improved the manuscript in English grammar.
T229 31712-31882 Sentence denotes Dr. Xia Wang from Shaanxi Normal University addressed the comments on the differences of population flow between our model and [Tang et al., 2020a], [Tang et al., 2020b].