CORD-19-Sentences  

CORD-19:041bae0a6de2b69979d39460b3f2ee8946534ec2 JSONTXT 8 Projects

Annnotations TAB TSV DIC JSON TextAE Lectin_function

Id Subject Object Predicate Lexical cue
TextSentencer_T1 0-107 Sentence denotes Estimation of the final size of the second phase of the coronavirus COVID 19 epidemic by the logistic model
TextSentencer_T1 0-107 Sentence denotes Estimation of the final size of the second phase of the coronavirus COVID 19 epidemic by the logistic model
TextSentencer_T2 109-117 Sentence denotes Abstract
TextSentencer_T2 109-117 Sentence denotes Abstract
TextSentencer_T3 118-308 Sentence denotes In the note, the logistic growth regression model is used for the estimation of the final size and its peak time of the coronavirus epidemic in China, South Korea, and the rest of the World.
TextSentencer_T3 118-308 Sentence denotes In the note, the logistic growth regression model is used for the estimation of the final size and its peak time of the coronavirus epidemic in China, South Korea, and the rest of the World.
TextSentencer_T4 309-447 Sentence denotes In the previous article [1], we try to estimate the final size of the epidemic for the whole World using the logistic model and SIR model.
TextSentencer_T4 309-447 Sentence denotes In the previous article [1], we try to estimate the final size of the epidemic for the whole World using the logistic model and SIR model.
TextSentencer_T5 448-485 Sentence denotes The estimation was about 83000 cases.
TextSentencer_T5 448-485 Sentence denotes The estimation was about 83000 cases.
TextSentencer_T6 486-583 Sentence denotes Both models show that the outbreak is moderating; however, new data showed a linear upward trend.
TextSentencer_T6 486-583 Sentence denotes Both models show that the outbreak is moderating; however, new data showed a linear upward trend.
TextSentencer_T7 584-681 Sentence denotes It turns out that the epidemy in China was slowing but is begin to spread elsewhere in the World.
TextSentencer_T7 584-681 Sentence denotes It turns out that the epidemy in China was slowing but is begin to spread elsewhere in the World.
TextSentencer_T8 682-832 Sentence denotes In this note, we will give forecasting epidemic size for China, South Korea, and the rest of the World and daily predictions using the logistic model.
TextSentencer_T8 682-832 Sentence denotes In this note, we will give forecasting epidemic size for China, South Korea, and the rest of the World and daily predictions using the logistic model.
TextSentencer_T9 833-1004 Sentence denotes Full daily reports and counties outside of China generated are available at https://www.researchgate.net/publication/339912313_Forecasting_of_final_COVID -19_epidemic_size
TextSentencer_T9 833-1004 Sentence denotes Full daily reports and counties outside of China generated are available at https://www.researchgate.net/publication/339912313_Forecasting_of_final_COVID -19_epidemic_size
TextSentencer_T10 1005-1264 Sentence denotes The MATLAB program fitVirus used for calculations is freely available from https://www.mathworks.com/matlabcentral/fileexchange/74411-fitvirus We note that logistic models give similar results as the SIR model (at least for the case of China and South Korea).
TextSentencer_T10 1005-1264 Sentence denotes The MATLAB program fitVirus used for calculations is freely available from https://www.mathworks.com/matlabcentral/fileexchange/74411-fitvirus We note that logistic models give similar results as the SIR model (at least for the case of China and South Korea).
TextSentencer_T11 1265-1492 Sentence denotes However, the logistic model is given by explicit formula and is thus much simpler for regression analysis than the SIR model, where one must on each optimization step solve a system of ordinary differential equations. (One may,
TextSentencer_T11 1265-1492 Sentence denotes However, the logistic model is given by explicit formula and is thus much simpler for regression analysis than the SIR model, where one must on each optimization step solve a system of ordinary differential equations. (One may,
TextSentencer_T12 1494-1613 Sentence denotes however, use approximate solution and thus obtain four-parameter problem which can be very sensitive to initial guess).
TextSentencer_T12 1494-1613 Sentence denotes however, use approximate solution and thus obtain four-parameter problem which can be very sensitive to initial guess).
TextSentencer_T13 1614-1794 Sentence denotes Yet, the logistics model has its drawbacks as the epidemic approaches its final stage: the actual number of cases may be slightly larger than that predicted by the logistics model.
TextSentencer_T13 1614-1794 Sentence denotes Yet, the logistics model has its drawbacks as the epidemic approaches its final stage: the actual number of cases may be slightly larger than that predicted by the logistics model.
TextSentencer_T14 1795-1981 Sentence denotes If the actual number of cases begins to exceed the predicted end-state systematically, then a second phase of the epidemic is likely to occur, and the model will no longer be applicable.
TextSentencer_T14 1795-1981 Sentence denotes If the actual number of cases begins to exceed the predicted end-state systematically, then a second phase of the epidemic is likely to occur, and the model will no longer be applicable.
TextSentencer_T15 1982-2159 Sentence denotes In mathematical epidemiology, when one uses a phenomenological approach, the epidemic dynamics can be described by the following variant of logistic growth model [2] [3] [4] [5]
TextSentencer_T15 1982-2159 Sentence denotes In mathematical epidemiology, when one uses a phenomenological approach, the epidemic dynamics can be described by the following variant of logistic growth model [2] [3] [4] [5]
TextSentencer_T16 2161-2263 Sentence denotes where C is an accumulated number of cases, 0 r  infection rate, and 0 K  is the final epidemic size.
TextSentencer_T16 2161-2263 Sentence denotes where C is an accumulated number of cases, 0 r  infection rate, and 0 K  is the final epidemic size.
TextSentencer_T17 2264-2343 Sentence denotes If   0 0 0 C C   is the initial number of cases then the solution of (1) is
TextSentencer_T17 2264-2343 Sentence denotes If   0 0 0 C C   is the initial number of cases then the solution of (1) is
TextSentencer_T18 2345-2404 Sentence denotes When t   the number of cases follows the Weibull function
TextSentencer_T18 2345-2404 Sentence denotes When t   the number of cases follows the Weibull function
TextSentencer_T19 2405-2451 Sentence denotes The growth rate dC dt reaches its maximum when
TextSentencer_T19 2405-2451 Sentence denotes The growth rate dC dt reaches its maximum when
TextSentencer_T20 2452-2455 Sentence denotes  .
TextSentencer_T20 2452-2455 Sentence denotes  .
TextSentencer_T21 2456-2534 Sentence denotes From this condition, we obtain that the growth rate peak occurs in time time .
TextSentencer_T21 2456-2534 Sentence denotes From this condition, we obtain that the growth rate peak occurs in time time .
TextSentencer_T22 2535-2693 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T22 2535-2693 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T23 2694-2830 Sentence denotes (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T23 2694-2830 Sentence denotes (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T24 2831-2866 Sentence denotes At this time the number of cases is
TextSentencer_T24 2831-2866 Sentence denotes At this time the number of cases is
TextSentencer_T25 2867-2889 Sentence denotes and the growth rate is
TextSentencer_T25 2867-2889 Sentence denotes and the growth rate is
TextSentencer_T26 2890-2973 Sentence denotes To answer the question about doubling time t  , i.e., the time takes to double the
TextSentencer_T26 2890-2973 Sentence denotes To answer the question about doubling time t  , i.e., the time takes to double the
TextSentencer_T27 2974-3054 Sentence denotes The first term represents initial exponential growth, then t  increases with t.
TextSentencer_T27 2974-3054 Sentence denotes The first term represents initial exponential growth, then t  increases with t.
TextSentencer_T28 3055-3061 Sentence denotes When .
TextSentencer_T28 3055-3061 Sentence denotes When .
TextSentencer_T29 3062-3220 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T29 3062-3220 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T30 3221-3532 Sentence denotes (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint Now, if 1 2 , , , n C C C  are the number of cases at times 1 2 , , , n t t t  , then the final size predictions of the epidemic based on these data are 1 2 , , , n K K K 
TextSentencer_T30 3221-3532 Sentence denotes (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint Now, if 1 2 , , , n C C C  are the number of cases at times 1 2 , , , n t t t  , then the final size predictions of the epidemic based on these data are 1 2 , , , n K K K 
TextSentencer_T31 3533-3534 Sentence denotes .
TextSentencer_T31 3533-3534 Sentence denotes .
TextSentencer_T32 3535-3635 Sentence denotes When convergence is achieved, then one may try to predict the final epidemic size by iterated Shanks
TextSentencer_T32 3535-3635 Sentence denotes When convergence is achieved, then one may try to predict the final epidemic size by iterated Shanks
TextSentencer_T33 3636-3741 Sentence denotes There is no natural law or process behind this transformation; therefore, it must be used with some care.
TextSentencer_T33 3636-3741 Sentence denotes There is no natural law or process behind this transformation; therefore, it must be used with some care.
TextSentencer_T34 3742-3837 Sentence denotes In particular, the calculated limit is useless if n K C  , i.e., it is below the current data.
TextSentencer_T34 3742-3837 Sentence denotes In particular, the calculated limit is useless if n K C  , i.e., it is below the current data.
TextSentencer_T35 3838-3951 Sentence denotes The logistic model (2) contains three parameters: K, r, and A, which should be determined by regression analysis.
TextSentencer_T35 3838-3951 Sentence denotes The logistic model (2) contains three parameters: K, r, and A, which should be determined by regression analysis.
TextSentencer_T36 3952-4028 Sentence denotes Because the model is nonlinear, some care should be taken for initial guess.
TextSentencer_T36 3952-4028 Sentence denotes Because the model is nonlinear, some care should be taken for initial guess.
TextSentencer_T37 4029-4173 Sentence denotes First of all, in the early stage, the logistic curve follows an exponential growth curve (3) , so the estimation of K is practically impossible.
TextSentencer_T37 4029-4173 Sentence denotes First of all, in the early stage, the logistic curve follows an exponential growth curve (3) , so the estimation of K is practically impossible.
TextSentencer_T38 4174-4245 Sentence denotes With enough data, the initial guess can be obtain in the following way.
TextSentencer_T38 4174-4245 Sentence denotes With enough data, the initial guess can be obtain in the following way.
TextSentencer_T39 4246-4351 Sentence denotes Expressing t from (2) and use three equidistant data point yield the following system of three equations:
TextSentencer_T39 4246-4351 Sentence denotes Expressing t from (2) and use three equidistant data point yield the following system of three equations:
TextSentencer_T40 4352-4386 Sentence denotes This system has a solution [7]  
TextSentencer_T40 4352-4386 Sentence denotes This system has a solution [7]  
TextSentencer_T41 4387-4449 Sentence denotes The solution is acceptable when all the unknowns are positive.
TextSentencer_T41 4387-4449 Sentence denotes The solution is acceptable when all the unknowns are positive.
TextSentencer_T42 4450-4546 Sentence denotes Formulas (10),(11),(12) are used to calculate the initial approximation in the fitVirus program.
TextSentencer_T42 4450-4546 Sentence denotes Formulas (10),(11),(12) are used to calculate the initial approximation in the fitVirus program.
TextSentencer_T43 4547-4629 Sentence denotes For practical calculation, we take the first, the middle, and the last data point.
TextSentencer_T43 4547-4629 Sentence denotes For practical calculation, we take the first, the middle, and the last data point.
TextSentencer_T44 4630-4705 Sentence denotes If this calculation fails, we consider regression analysis as questionable.
TextSentencer_T44 4630-4705 Sentence denotes If this calculation fails, we consider regression analysis as questionable.
TextSentencer_T45 4706-4713 Sentence denotes Final .
TextSentencer_T45 4706-4713 Sentence denotes Final .
TextSentencer_T46 4714-4872 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T46 4714-4872 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T47 4873-5107 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint values of the parameters K, r, and A are then calculated by least-square fit using the MATLAB functions lsqcurvefit and fitnlm.
TextSentencer_T47 4873-5107 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint values of the parameters K, r, and A are then calculated by least-square fit using the MATLAB functions lsqcurvefit and fitnlm.
TextSentencer_T48 5108-5201 Sentence denotes Before we proceed, we for convenience, introduce the following epidemy phases (see Fig 2) :
TextSentencer_T48 5108-5201 Sentence denotes Before we proceed, we for convenience, introduce the following epidemy phases (see Fig 2) :
TextSentencer_T49 5203-5267 Sentence denotes The duration of the fast-growing period is thus equal to 4 r  
TextSentencer_T49 5203-5267 Sentence denotes The duration of the fast-growing period is thus equal to 4 r  
TextSentencer_T50 5268-5269 Sentence denotes .
TextSentencer_T50 5268-5269 Sentence denotes .
TextSentencer_T51 5270-5352 Sentence denotes We note that the names of the phases are not standard, and are arbitrarily chosen.
TextSentencer_T51 5270-5352 Sentence denotes We note that the names of the phases are not standard, and are arbitrarily chosen.
TextSentencer_T52 5353-5354 Sentence denotes .
TextSentencer_T52 5353-5354 Sentence denotes .
TextSentencer_T53 5355-5513 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T53 5355-5513 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T54 5514-5620 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T54 5514-5620 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T55 5621-5859 Sentence denotes On the base of available data, one can predict that the final size of coronavirus epidemy in China using the logistic model will be approximately 81 000 ± 500 cases (Table 1) and that the peak of the epidemic was on 8 Feb 2020 (Table 2 ).
TextSentencer_T55 5621-5859 Sentence denotes On the base of available data, one can predict that the final size of coronavirus epidemy in China using the logistic model will be approximately 81 000 ± 500 cases (Table 1) and that the peak of the epidemic was on 8 Feb 2020 (Table 2 ).
TextSentencer_T56 5860-5935 Sentence denotes It seems that the epidemic in China is in the ending stage (Fig 3, Fig 4) .
TextSentencer_T56 5860-5935 Sentence denotes It seems that the epidemic in China is in the ending stage (Fig 3, Fig 4) .
TextSentencer_T57 5936-6071 Sentence denotes The short-term forecasting is given in Table 3 where we see that the discrepancy of actual and forecasted number of cases is within 2%.
TextSentencer_T57 5936-6071 Sentence denotes The short-term forecasting is given in Table 3 where we see that the discrepancy of actual and forecasted number of cases is within 2%.
TextSentencer_T58 6072-6161 Sentence denotes However, actual and predicted daily new cases are scattered and vary between 13% to 300%.
TextSentencer_T58 6072-6161 Sentence denotes However, actual and predicted daily new cases are scattered and vary between 13% to 300%.
TextSentencer_T59 6162-6252 Sentence denotes On 7 Mar 2020, the actual number of cases was 80695, and the daily number of cases was 44.
TextSentencer_T59 6162-6252 Sentence denotes On 7 Mar 2020, the actual number of cases was 80695, and the daily number of cases was 44.
TextSentencer_T60 6253-6320 Sentence denotes Prediction in Table 3 is cumulative 80588 cases and 39 daily cases.
TextSentencer_T60 6253-6320 Sentence denotes Prediction in Table 3 is cumulative 80588 cases and 39 daily cases.
TextSentencer_T61 6321-6365 Sentence denotes The errors are 0.1% and 11%, respectively. .
TextSentencer_T61 6321-6365 Sentence denotes The errors are 0.1% and 11%, respectively. .
TextSentencer_T62 6366-6524 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T62 6366-6524 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T63 6525-6726 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T63 6525-6726 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T64 6727-6835 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint .
TextSentencer_T64 6727-6835 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint .
TextSentencer_T65 6836-6994 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T65 6836-6994 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T66 6995-7345 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint On the base of available data, one can predict that the final size of coronavirus epidemy in of South Korea using the logistic model will be approximately 8050 ±70 cases ( Fig 5, Table 4 ) and that the peak of the epidemic was on 1 Mar 2020.
TextSentencer_T66 6995-7345 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint On the base of available data, one can predict that the final size of coronavirus epidemy in of South Korea using the logistic model will be approximately 8050 ±70 cases ( Fig 5, Table 4 ) and that the peak of the epidemic was on 1 Mar 2020.
TextSentencer_T67 7346-7425 Sentence denotes The epidemic in South Korea appears to be in the steady-state transition phase.
TextSentencer_T67 7346-7425 Sentence denotes The epidemic in South Korea appears to be in the steady-state transition phase.
TextSentencer_T68 7426-7468 Sentence denotes These figures were already predicted on 4.
TextSentencer_T68 7426-7468 Sentence denotes These figures were already predicted on 4.
TextSentencer_T69 7469-7533 Sentence denotes Mar 2020 (Table 5) , i.e., the prediction was approximately 7500
TextSentencer_T69 7469-7533 Sentence denotes Mar 2020 (Table 5) , i.e., the prediction was approximately 7500
TextSentencer_T70 7534-7587 Sentence denotes to 8500 cases and that the peak will be around 2 Mar.
TextSentencer_T70 7534-7587 Sentence denotes to 8500 cases and that the peak will be around 2 Mar.
TextSentencer_T71 7588-7678 Sentence denotes On 7 Mar 2020, the actual number of cases was 7134, and the daily number of cases was 367.
TextSentencer_T71 7588-7678 Sentence denotes On 7 Mar 2020, the actual number of cases was 7134, and the daily number of cases was 367.
TextSentencer_T72 7679-7746 Sentence denotes Prediction in Table 5 is cumulative 6572 cases and 259 daily cases.
TextSentencer_T72 7679-7746 Sentence denotes Prediction in Table 5 is cumulative 6572 cases and 259 daily cases.
TextSentencer_T73 7747-7790 Sentence denotes The errors are 8 % and 30%, respectively. .
TextSentencer_T73 7747-7790 Sentence denotes The errors are 8 % and 30%, respectively. .
TextSentencer_T74 7791-7949 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T74 7791-7949 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T75 7950-8058 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint .
TextSentencer_T75 7950-8058 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint .
TextSentencer_T76 8059-8217 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T76 8059-8217 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T77 8218-8324 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T77 8218-8324 Sentence denotes The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T78 8325-8404 Sentence denotes The comparison of the predicted final sizes is shown in the graph in Figure 6 .
TextSentencer_T78 8325-8404 Sentence denotes The comparison of the predicted final sizes is shown in the graph in Figure 6 .
TextSentencer_T79 8405-8431 Sentence denotes Based on the data from 11.
TextSentencer_T79 8405-8431 Sentence denotes Based on the data from 11.
TextSentencer_T80 8432-8542 Sentence denotes Mar 2020, a very rough estimate indicates that the number of cases will be about 90000 (Fig 7) ; data from 13.
TextSentencer_T80 8432-8542 Sentence denotes Mar 2020, a very rough estimate indicates that the number of cases will be about 90000 (Fig 7) ; data from 13.
TextSentencer_T81 8543-8580 Sentence denotes Mar 2020 rise this number to 380 000.
TextSentencer_T81 8543-8580 Sentence denotes Mar 2020 rise this number to 380 000.
TextSentencer_T82 8581-8696 Sentence denotes However, it is an early-stage epidemic, so these estimates are very questionable and will be changed with new data.
TextSentencer_T82 8581-8696 Sentence denotes However, it is an early-stage epidemic, so these estimates are very questionable and will be changed with new data.
TextSentencer_T83 8697-8855 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T83 8697-8855 Sentence denotes CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
TextSentencer_T84 8856-8992 Sentence denotes (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T84 8856-8992 Sentence denotes (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.11.20024901 doi: medRxiv preprint
TextSentencer_T85 8993-9120 Sentence denotes On the base of available data, one can predict that the final size of coronavirus epidemy in China will be around 81 000 cases.
TextSentencer_T85 8993-9120 Sentence denotes On the base of available data, one can predict that the final size of coronavirus epidemy in China will be around 81 000 cases.
TextSentencer_T86 9121-9171 Sentence denotes For South Korea, a prediction is about 8000 cases.
TextSentencer_T86 9121-9171 Sentence denotes For South Korea, a prediction is about 8000 cases.
TextSentencer_T87 9172-9277 Sentence denotes For the rest of the World, the forecasts are still very unreliable in is now approximately 380 000 cases.
TextSentencer_T87 9172-9277 Sentence denotes For the rest of the World, the forecasts are still very unreliable in is now approximately 380 000 cases.
TextSentencer_T88 9278-9357 Sentence denotes We emphasize that the logistics model is a phenomenological, data-driven model.
TextSentencer_T88 9278-9357 Sentence denotes We emphasize that the logistics model is a phenomenological, data-driven model.
TextSentencer_T89 9358-9479 Sentence denotes Thus, its forecasts are as reliable as useful are data and as good as the model can capture the dynamics of the epidemic.
TextSentencer_T89 9358-9479 Sentence denotes Thus, its forecasts are as reliable as useful are data and as good as the model can capture the dynamics of the epidemic.
TextSentencer_T90 9480-9582 Sentence denotes As daily epidemic size forecasts begin to converge, it can be said that the outbreak is under control.
TextSentencer_T90 9480-9582 Sentence denotes As daily epidemic size forecasts begin to converge, it can be said that the outbreak is under control.
TextSentencer_T91 9583-9692 Sentence denotes However, any systematic deviation from the forecast curve may indicate that the epidemic is escaping control.
TextSentencer_T91 9583-9692 Sentence denotes However, any systematic deviation from the forecast curve may indicate that the epidemic is escaping control.
TextSentencer_T92 9693-9713 Sentence denotes An example is China.
TextSentencer_T92 9693-9713 Sentence denotes An example is China.
TextSentencer_T93 9714-9720 Sentence denotes By 25.
TextSentencer_T93 9714-9720 Sentence denotes By 25.
TextSentencer_T94 9721-9796 Sentence denotes Feb., the data follows a logistic curve and then begins to deviate from it.
TextSentencer_T94 9721-9796 Sentence denotes Feb., the data follows a logistic curve and then begins to deviate from it.
TextSentencer_T95 9797-9914 Sentence denotes We now know that this was the beginning of the second stage of the epidemic, which is now spreading around the World.
TextSentencer_T95 9797-9914 Sentence denotes We now know that this was the beginning of the second stage of the epidemic, which is now spreading around the World.
TextSentencer_T96 9915-10078 Sentence denotes A similar linear trend can now be observed for South Korea ( Fig 5) ; we hope this does not mark the beginning of the second stage of the epidemic in this country.
TextSentencer_T96 9915-10078 Sentence denotes A similar linear trend can now be observed for South Korea ( Fig 5) ; we hope this does not mark the beginning of the second stage of the epidemic in this country.