Word clouds: monthly differences (observed-expected)
> for(j in 1:12){
+ di <- TF[,j+1] - TF[,1]*(S[j+1]/S[1]) # *log(15/P))
+ or <- order(di,decreasing=TRUE)
+ ro <- invPerm(or)
+ names(di) <- N
+ cat("\n",j,":\n")
+ ff <- round(200000/sqrt(1+ro))
+ for(i in 1:50){
+ k <- or[i]
+ cat(i,k,N[k],TF[k,1],TF[k,j+1],P[k],di[k],"\n")
+ }
+ df <- data.frame(N=N[or],f=ff[or])
+ # wc <- wordcloud2(df,size=2,minRotation=-pi/2,maxRotation=-pi/2)
+ wc <- wordcloud2(df,size=0.8,minRotation=0,maxRotation=0)
+ tmp <- paste("wcD",j,".html",sep="")
+ pdf <- paste("wcD",j,".pdf",sep="")
+ png <- paste("wcD",j,".png",sep="")
+ saveWidget(wc,tmp,selfcontained=FALSE)
+ webshot(tmp,pdf,delay=5,vwidth=800,vheight=600)
+ webshot(tmp,png,delay=5,vwidth=800,vheight=600)
+ }
1 :
1 90 virus 17975 104 12 52.30149
2 384 novel 9270 75 12 48.33824
3 324 review 14000 79 12 38.73412
4 12754 ncov 1132 40 11 36.74422
5 401 systematic 6525 50 12 31.23322
6 8696 wuhan 1828 33 12 27.74243
7 31 cell 10223 56 12 26.59728
8 332 china 7114 47 12 26.53918
9 173 analysis 15135 67 12 23.46971
10 7642 2019 13357 61 12 22.58347
11 110 influenza 5329 37 12 21.67308
12 187 human 8882 45 12 19.45418
13 151 infectious 4837 32 12 18.08814
14 137 model 10504 48 12 17.78909
15 614 vaccine 5422 32 12 16.4056
16 849 trial 5012 28 12 13.58481
17 280 development 4727 27 12 13.40451
18 393 outbreak 9294 39 12 12.26921
19 134 control 7836 34 12 11.46261
20 723 meta 3717 22 12 11.30941
21 2224 assist 1573 15 12 10.47584
22 494 respiratory 14443 52 12 10.45999
23 447 identification 2389 17 12 10.12892
24 166 characterization 2163 16 12 9.778922
25 313 among 6847 29 12 9.307109
26 11149 aneurysm 993 12 11 9.143999
27 75 surveillance 2065 15 12 9.060783
28 1386 b 1371 13 12 9.05682
29 850 randomize 2416 16 12 9.05126
30 329 hiv 2087 15 12 8.997508
31 815 via 1785 14 12 8.8661
32 100 function 2211 15 12 8.640867
33 1329 porcine 2247 15 11 8.537326
34 6075 intracranial 568 10 11 8.366356
35 1128 resistance 955 11 12 8.253292
36 1991 antibiotic 621 10 12 8.213921
37 969 injury 3112 17 12 8.04947
38 333 therapeutic 3468 18 12 8.025566
39 239 base 10781 39 12 7.992396
40 2531 rat 1093 11 12 7.856385
41 691 genome 1799 13 12 7.825834
42 11 infection 24401 78 12 7.819447
43 1663 ventilation 1491 12 12 7.711684
44 3843 occlusion 513 9 11 7.524543
45 880 like 2261 14 12 7.49706
46 1872 infant 1228 11 12 7.468107
47 229 factor 6097 25 12 7.464209
48 34 gene 2977 16 12 7.437748
49 2494 pressure 1271 11 12 7.344433
50 582 mouse 2669 15 12 7.323598
2 :
1 2899 coronavirus 31428 546 12 385.2208
2 7642 2019 13357 403 12 334.6683
3 384 novel 9270 355 12 307.5766
4 12754 ncov 1132 193 11 187.2089
5 332 china 7114 170 12 133.6062
6 413 pneumonia 5940 140 12 109.6122
7 393 outbreak 9294 145 12 97.45382
8 450 epidemic 6523 115 12 81.62968
9 8696 wuhan 1828 86 12 76.64833
10 11 infection 24401 195 12 70.16952
11 173 analysis 15135 131 12 53.57247
12 134 control 7836 80 12 39.91264
13 396 transmission 4864 64 12 39.11678
14 121 case 14195 108 12 35.38131
15 90 virus 17975 123 12 31.04361
16 401 systematic 6525 63 12 29.61945
17 3 clinical 14239 102 12 29.15622
18 20 disease 28569 174 12 27.8469
19 239 base 10781 83 12 27.84663
20 777 characteristic 4020 48 12 27.43451
21 1179 infect 2901 42 12 27.15908
22 8501 2020 4992 49 12 23.46196
23 324 review 14000 95 12 23.37889
24 137 model 10504 76 12 22.26371
25 506 spread 3081 36 12 20.23824
26 678 structure 2497 33 12 20.22586
27 330 prevention 3660 38 12 19.2762
28 3244 ct 2514 32 12 19.1389
29 1196 epidemiological 1615 27 12 18.73799
30 614 vaccine 5422 46 12 18.26217
31 7 feature 2310 30 12 18.18252
32 494 respiratory 14443 92 12 18.1126
33 723 meta 3717 37 12 17.9846
34 629 number 1016 23 12 17.80235
35 447 identification 2389 30 12 17.77837
36 631 estimate 1293 24 12 17.38528
37 497 early 5074 43 12 17.04246
38 853 estimation 794 21 12 16.93806
39 2940 coronaviruses 1794 26 12 16.82227
40 187 human 8882 62 12 16.56152
41 206 new 8343 59 12 16.31894
42 566 treatment 11051 72 12 15.46537
43 14329 hubei 311 17 10 15.40899
44 155 emerge 2748 29 12 14.9418
45 481 dynamic 3155 31 12 14.85967
46 1329 porcine 2247 26 11 14.50481
47 417 first 3628 33 12 14.4399
48 649 prediction 1869 24 12 14.43858
49 1054 antiviral 2667 28 12 14.35618
50 2473 province 809 18 12 13.86132
3 :
1 2899 coronavirus 31428 910 12 523.5268
2 7642 2019 13357 517 12 352.7477
3 384 novel 9270 360 12 246.0059
4 393 outbreak 9294 335 12 220.7108
5 332 china 7114 307 12 219.5184
6 20 disease 28569 569 12 217.6842
7 2280 19 147108 1983 12 173.9985
8 8683 covid 149210 1999 12 164.15
9 450 epidemic 6523 236 12 155.786
10 137 model 10504 242 12 112.8313
11 3 clinical 14239 267 12 91.90162
12 413 pneumonia 5940 156 12 82.95524
13 121 case 14195 257 12 82.44269
14 1110 cov 28352 429 12 80.35267
15 8696 wuhan 1828 95 12 72.5209
16 1111 sars 31530 460 12 72.27249
17 871 2 31487 458 12 70.80127
18 8501 2020 4992 130 12 68.61289
19 396 transmission 4864 125 12 65.18691
20 173 analysis 15135 251 12 64.88342
21 506 spread 3081 99 12 61.11264
22 12754 ncov 1132 74 11 60.07968
23 3244 ct 2514 88 12 57.08509
24 7 feature 2310 79 12 50.5937
25 239 base 10781 183 12 50.42498
26 11 infection 24401 350 12 49.9385
27 281 data 5075 111 12 48.59223
28 777 characteristic 4020 95 12 45.56566
29 12491 corona 1812 67 12 44.71766
30 649 prediction 1869 66 12 43.01672
31 497 early 5074 103 12 40.60452
32 60 march 778 49 12 39.43286
33 1196 epidemiological 1615 59 12 39.14019
34 631 estimate 1293 55 12 39.09985
35 742 diagnosis 3889 86 12 38.17658
36 817 italy 2754 68 11 34.13379
37 324 review 14000 206 12 33.84062
38 134 control 7836 130 12 33.63994
39 783 learn 5246 98 12 33.48942
40 401 systematic 6525 113 12 32.76143
41 481 dynamic 3155 71 12 32.20265
42 1179 infect 2901 65 12 29.32612
43 1118 chinese 1878 52 12 28.90605
44 417 first 3628 73 12 28.38613
45 566 treatment 11051 162 12 26.10477
46 575 global 4796 84 12 25.02312
47 2663 deep 1428 41 12 23.43974
48 14329 hubei 311 27 10 23.1756
49 13938 retrieval 171 25 10 22.8972
50 1068 strategy 5138 86 12 22.81751
4 :
1 8683 covid 149210 6570 12 1884.206
2 2280 19 147108 6499 12 1879.217
3 2899 coronavirus 31428 1450 12 463.0344
4 108 pandemic 42664 1778 12 438.1788
5 16281 covid‐19 5103 448 10 287.7453
6 7642 2019 13357 682 12 262.5365
7 393 outbreak 9294 530 12 238.131
8 1110 cov 28352 1096 12 205.6332
9 20 disease 28569 1085 12 187.8185
10 871 2 31487 1175 12 186.1816
11 137 model 10504 508 12 178.1322
12 450 epidemic 6523 380 12 175.1516
13 1111 sars 31530 1153 12 162.8312
14 332 china 7114 373 12 149.5918
15 70 time 9291 419 12 127.2252
16 120 patient 40007 1368 12 111.6193
17 506 spread 3081 206 12 109.2442
18 384 novel 9270 394 12 102.8847
19 817 italy 2754 188 11 101.5133
20 771 “ 2104 151 12 84.92594
21 121 case 14195 525 12 79.21991
22 773 ” 2023 141 12 77.46966
23 1068 strategy 5138 238 12 76.64613
24 906 management 9140 363 12 75.96724
25 3244 ct 2514 153 12 74.05029
26 281 data 5075 231 12 71.62459
27 4385 crisis 4120 196 12 66.61543
28 232 – 2085 132 12 66.52261
29 1400 distance 2073 130 11 64.89946
30 735 measure 2959 156 12 63.0755
31 3 clinical 14239 509 12 61.83813
32 8501 2020 4992 217 12 60.23112
33 18077 sars‐cov‐2 811 85 11 59.53134
34 649 prediction 1869 118 12 59.30588
35 4831 recommendation 2955 152 12 59.20111
36 8696 wuhan 1828 116 12 58.59345
37 631 estimate 1293 99 12 58.3946
38 6995 statement 893 84 12 55.95621
39 413 pneumonia 5940 242 12 55.46011
40 408 test 6690 265 12 54.90709
41 4270 consideration 2173 123 12 54.75906
42 25875 covid19 1143 89 10 53.1052
43 3414 chloroquine 817 77 11 51.34291
44 886 face 2344 123 11 49.38897
45 1235 chest 1920 109 12 48.70428
46 12491 corona 1812 105 12 48.09591
47 56 care 14837 514 12 48.05852
48 106 implication 4029 174 12 47.4732
49 887 mask 1921 104 12 43.67287
50 758 rate 2619 125 12 42.75287
5 :
1 8683 covid 149210 9109 12 2198.225
2 2280 19 147108 8949 12 2135.581
3 16281 covid‐19 5103 1086 10 849.6507
4 108 pandemic 42664 2676 12 699.9843
5 871 2 31487 1787 12 328.6556
6 1110 cov 28352 1629 12 315.8555
7 120 patient 40007 2117 12 264.0453
8 1111 sars 31530 1717 12 256.664
9 137 model 10504 708 12 221.4992
10 70 time 9291 586 12 155.6802
11 7642 2019 13357 763 12 144.3603
12 393 outbreak 9294 567 12 136.5413
13 771 “ 2104 223 12 125.5516
14 773 ” 2023 218 12 124.3032
15 408 test 6690 433 12 123.1475
16 281 data 5075 354 12 118.9475
17 18077 sars‐cov‐2 811 156 11 118.4379
18 906 management 9140 533 12 109.6739
19 121 case 14195 762 12 104.5477
20 169 use 16517 868 12 103.0025
21 239 base 10781 594 12 94.66976
22 232 – 2085 190 12 93.43163
23 783 learn 5246 332 12 89.02751
24 817 italy 2754 214 11 86.44639
25 396 transmission 4864 301 12 75.72013
26 76 system 7703 430 12 73.22967
27 4385 crisis 4120 264 12 73.17905
28 132 network 3081 213 12 70.30113
29 2899 coronavirus 31428 1525 12 69.38819
30 4331 era 4082 257 12 67.93905
31 3 clinical 14239 726 12 66.50985
32 56 care 14837 753 12 65.81302
33 2317 need 3355 220 12 64.61061
34 450 epidemic 6523 366 12 63.88228
35 608 rapid 3629 231 12 62.92009
36 315 risk 10478 547 12 61.70343
37 15332 hydroxychloroquine 1955 152 12 61.45268
38 506 spread 3081 202 12 59.30113
39 4831 recommendation 2955 193 12 56.13692
40 5496 letter 1855 137 12 51.08426
41 1400 distance 2073 147 11 50.98742
42 25875 covid19 1143 103 10 50.06108
43 497 early 5074 285 12 49.99382
44 1293 healthcare 4363 252 12 49.92432
45 1935 italian 1521 120 11 49.55372
46 9857 fuzzy 196 57 9 47.92211
47 20 disease 28569 1371 12 47.80496
48 910 perspective 4830 270 12 46.29486
49 1068 strategy 5138 284 12 46.02961
50 4270 consideration 2173 146 12 45.35585
6 :
1 8683 covid 149210 8579 12 1732.181
2 2280 19 147108 8430 12 1679.636
3 16281 covid‐19 5103 1049 10 814.838
4 108 pandemic 42664 2645 12 687.2713
5 871 2 31487 1816 12 371.1518
6 1110 cov 28352 1668 12 367.008
7 1111 sars 31530 1765 12 318.1787
8 120 patient 40007 2107 12 271.1935
9 18077 sars‐cov‐2 811 161 11 123.7855
10 771 “ 2104 213 12 116.4535
11 56 care 14837 797 12 116.1726
12 773 ” 2023 207 12 114.1703
13 783 learn 5246 343 12 102.2761
14 15214 lockdown 3634 269 11 102.2462
15 515 impact 12012 648 12 96.80375
16 4331 era 4082 284 12 96.68872
17 6974 mental 4050 278 12 92.15711
18 137 model 10504 571 12 89.00155
19 232 – 2085 182 12 86.32533
20 70 time 9291 512 12 85.66264
21 239 base 10781 575 12 80.29082
22 69 health 18487 922 12 73.68457
23 121 case 14195 722 12 70.63214
24 315 risk 10478 550 12 69.19462
25 281 data 5075 299 12 66.1228
26 2004 social 5153 300 12 63.5436
27 3309 india 2550 178 12 60.98781
28 408 test 6690 364 12 57.01508
29 1160 algorithm 714 87 12 54.23659
30 4831 recommendation 2955 189 12 53.40352
31 3017 uk 1874 138 12 52.00751
32 1362 experience 6560 353 12 51.98041
33 129 trace 999 96 11 50.15875
34 7642 2019 13357 663 12 50.08556
35 299 potential 6406 344 12 50.04702
36 385 challenge 5519 302 12 48.74891
37 818 practice 5123 283 12 47.92022
38 59 emergency 5154 284 12 47.49771
39 381 approach 5661 307 12 47.23294
40 132 network 3081 188 12 46.62174
41 15332 hydroxychloroquine 1955 136 12 46.29065
42 1400 distance 2073 141 11 45.87597
43 1063 state 4487 251 12 45.10443
44 1413 medical 5199 283 12 44.43279
45 106 implication 4029 229 12 44.12074
46 4385 crisis 4120 232 12 42.94501
47 371 may 1998 132 12 40.31751
48 7 feature 2310 146 12 40.00072
49 5496 letter 1855 125 12 39.87937
50 817 italy 2754 165 11 38.62683
7 :
1 8683 covid 149210 7978 12 815.5445
2 2280 19 147108 7850 12 788.4458
3 16281 covid‐19 5103 755 10 510.0432
4 871 2 31487 1902 12 390.5448
5 1110 cov 28352 1693 12 332.0326
6 1111 sars 31530 1781 12 267.4806
7 108 pandemic 42664 2248 12 200.0206
8 120 patient 40007 2119 12 198.5633
9 56 care 14837 833 12 120.7867
10 324 review 14000 762 12 89.96476
11 771 “ 2104 186 12 85.0027
12 298 study 19798 1035 12 84.64617
13 1585 mortality 4550 303 12 84.58855
14 773 ” 2023 180 12 82.89091
15 401 systematic 6525 394 12 80.78358
16 2004 social 5153 328 12 80.64303
17 315 risk 10478 575 12 72.02963
18 18077 sars‐cov‐2 811 107 11 68.06996
19 4331 era 4082 263 12 67.05373
20 481 dynamic 3155 214 12 62.55206
21 408 test 6690 383 12 61.86316
22 35 response 11213 598 12 59.74778
23 121 case 14195 741 12 59.60427
24 1472 high 5279 313 12 59.59471
25 326 drug 4988 299 12 59.56345
26 281 data 5075 302 12 58.38723
27 696 report 6902 389 12 57.68663
28 723 meta 3717 236 12 57.57465
29 173 analysis 15135 783 12 56.48191
30 1334 cohort 3167 208 12 55.97603
31 232 – 2085 152 12 51.91475
32 1587 retrospective 2816 186 12 50.82491
33 606 screen 2942 192 12 50.7766
34 1971 protocol 2947 191 12 49.53658
35 239 base 10781 566 12 48.48487
36 515 impact 12012 625 12 48.39377
37 2214 death 2380 162 12 47.75401
38 783 learn 5246 299 12 47.1788
39 15214 lockdown 3634 220 11 45.55885
40 312 population 3968 236 12 45.52601
41 698 future 3034 190 12 44.36036
42 1995 diabetes 2348 156 12 43.29009
43 15332 hydroxychloroquine 1955 135 12 41.15508
44 1493 change 4768 270 12 41.124
45 236 policy 2352 154 12 41.09808
46 8501 2020 4992 279 12 39.37144
47 2649 ace2 1726 122 12 39.14766
48 503 association 3503 206 12 37.84718
49 2175 education 2736 169 12 37.66511
50 299 potential 6406 345 12 37.49588
8 :
1 16281 covid‐19 5103 766 10 536.6321
2 871 2 31487 1701 12 285.7333
3 1110 cov 28352 1519 12 244.6442
4 8683 covid 149210 6903 12 196.3609
5 120 patient 40007 1986 12 187.7793
6 2280 19 147108 6778 12 165.8408
7 1111 sars 31530 1567 12 149.8005
8 515 impact 12012 687 12 147.0888
9 298 study 19798 1018 12 128.1264
10 324 review 14000 739 12 109.7329
11 69 health 18487 938 12 107.0528
12 654 effect 9268 509 12 92.42516
13 18077 sars‐cov‐2 811 123 11 86.54745
14 313 among 6847 394 12 86.24343
15 311 survey 3809 255 12 83.79439
16 169 use 16517 826 12 83.59963
17 108 pandemic 42664 1995 12 77.35338
18 696 report 6902 386 12 75.77131
19 239 base 10781 560 12 75.41937
20 1293 healthcare 4363 269 12 72.89339
21 232 – 2085 164 12 70.28415
22 315 risk 10478 541 12 70.0385
23 1334 cohort 3167 210 12 67.65079
24 771 “ 2104 160 12 65.43014
25 15214 lockdown 3634 228 11 64.66023
26 773 ” 2023 155 12 64.0709
27 56 care 14837 726 12 59.11169
28 137 model 10504 531 12 58.86986
29 401 systematic 6525 351 12 57.71657
30 121 case 14195 693 12 54.96808
31 6974 mental 4050 236 12 53.96201
32 229 factor 6097 327 12 52.95417
33 783 learn 5246 288 12 52.20462
34 1068 strategy 5138 279 12 48.05896
35 1585 mortality 4550 252 12 47.48818
36 705 related 4885 267 12 47.43072
37 314 cancer 7517 385 12 47.1285
38 497 early 5074 275 12 46.93561
39 312 population 3968 225 12 46.64772
40 48 level 2880 176 12 46.55076
41 2358 virtual 1902 132 11 46.50957
42 721 therapy 5786 305 12 44.93289
43 1766 symptom 2663 164 11 44.3044
44 173 analysis 15135 724 12 43.71729
45 1493 change 4768 258 12 43.6896
46 281 data 5075 271 12 42.89067
47 1423 large 2034 132 12 40.57648
48 2004 social 5153 272 12 40.38475
49 218 assessment 3357 191 12 40.11073
50 326 drug 4988 264 12 39.80111
9 :
1 871 2 31487 2033 12 483.2289
2 1110 cov 28352 1843 12 447.5317
3 8683 covid 149210 7781 12 436.9741
4 2280 19 147108 7653 12 412.4333
5 1111 sars 31530 1903 12 351.1125
6 120 patient 40007 2177 12 207.8797
7 298 study 19798 1175 12 200.5544
8 515 impact 12012 759 12 167.7766
9 314 cancer 7517 491 12 121.0178
10 313 among 6847 456 12 118.9948
11 324 review 14000 808 12 118.9285
12 69 health 18487 1018 12 108.0811
13 1585 mortality 4550 329 12 105.0518
14 173 analysis 15135 845 12 100.0645
15 771 “ 2104 191 12 87.44239
16 121 case 14195 786 12 87.33069
17 137 model 10504 604 12 86.99948
18 773 ” 2023 186 12 86.42916
19 772 cross 3197 240 12 82.6456
20 229 factor 6097 381 12 80.90935
21 315 risk 10478 595 12 79.27918
22 696 report 6902 415 12 75.28774
23 2004 social 5153 327 12 73.37246
24 401 systematic 6525 394 12 72.84345
25 654 effect 9268 529 12 72.83465
26 1414 sectional 2086 175 12 72.32834
27 56 care 14837 802 12 71.73184
28 169 use 16517 884 12 71.04326
29 16281 covid‐19 5103 320 10 68.83343
30 299 potential 6406 384 12 68.70056
31 142 stress 2060 166 12 64.60805
32 311 survey 3809 248 12 60.52333
33 723 meta 3717 240 12 57.05151
34 188 adult 4406 272 12 55.13935
35 46 outcome 7173 408 12 54.94928
36 239 base 10781 584 12 53.36571
37 389 old 2892 194 12 51.65751
38 783 learn 5246 309 12 50.79506
39 6974 mental 4050 249 12 49.66145
40 132 network 3081 201 12 49.35505
41 1334 cohort 3167 205 12 49.12218
42 412 associate 8316 457 12 47.69151
43 503 association 3503 220 12 47.58446
44 340 worker 3847 234 12 44.65299
45 15214 lockdown 3634 223 11 44.13672
46 312 population 3968 239 12 43.69744
47 705 related 4885 283 12 42.56326
48 1021 psychological 2224 152 12 42.53607
49 1063 state 4487 263 12 42.15258
50 218 assessment 3357 207 12 41.77049
10 :
1 8683 covid 149210 7390 12 663.8523
2 2280 19 147108 7252 12 620.6071
3 871 2 31487 1874 12 454.6165
4 1110 cov 28352 1696 12 417.9373
5 1111 sars 31530 1764 12 342.6781
6 298 study 19798 1144 12 251.5379
7 16281 covid‐19 5103 476 10 245.9649
8 108 pandemic 42664 2139 12 215.7752
9 120 patient 40007 1967 12 163.5486
10 69 health 18487 982 12 148.6357
11 515 impact 12012 675 12 133.5183
12 313 among 6847 430 12 121.3482
13 1585 mortality 4550 320 12 114.8933
14 8501 2020 4992 335 12 109.9686
15 696 report 6902 420 12 108.8689
16 783 learn 5246 333 12 96.51873
17 281 data 5075 324 12 95.22713
18 169 use 16517 839 12 94.44011
19 311 survey 3809 266 12 94.29638
20 1334 cohort 3167 237 12 94.23672
21 173 analysis 15135 776 12 93.73845
22 46 outcome 7173 415 12 91.65265
23 408 test 6690 387 12 85.42552
24 239 base 10781 571 12 85.0098
25 6974 mental 4050 261 12 78.43249
26 56 care 14837 747 12 78.17182
27 654 effect 9268 494 12 76.21341
28 772 cross 3197 220 12 75.88436
29 121 case 14195 715 12 75.11215
30 15214 lockdown 3634 238 11 74.1851
31 229 factor 6097 347 12 72.15701
32 12 hospital 7047 388 12 70.33253
33 771 “ 2104 165 12 70.15505
34 1414 sectional 2086 164 12 69.96646
35 1411 student 2693 190 12 68.60388
36 324 review 14000 698 12 66.90243
37 773 ” 2023 157 12 65.8064
38 137 model 10504 539 12 65.49651
39 2004 social 5153 290 12 57.71102
40 1816 observational 1660 132 12 57.16986
41 215 quality 2439 167 12 57.05379
42 232 – 2085 151 12 57.01154
43 2023 people 2636 174 12 55.17334
44 5242 online 2156 152 12 54.81097
45 1413 medical 5199 287 12 52.63741
46 1971 protocol 2947 185 12 52.15396
47 358 severity 2458 162 12 51.1973
48 4220 school 1337 111 11 50.73018
49 813 disorder 2572 165 12 49.05836
50 412 associate 8316 423 12 48.12805
11 :
1 8683 covid 149210 6403 12 1128.651
2 2280 19 147108 6297 12 1096.953
3 1110 cov 28352 1620 12 617.7994
4 871 2 31487 1730 12 616.9819
5 1111 sars 31530 1673 12 558.4619
6 298 study 19798 1038 12 338.1705
7 120 patient 40007 1612 12 197.8127
8 515 impact 12012 575 12 150.3939
9 108 pandemic 42664 1638 12 129.8917
10 239 base 10781 507 12 125.9079
11 313 among 6847 358 12 115.9688
12 783 learn 5246 281 12 95.56179
13 408 test 6690 330 12 93.51856
14 173 analysis 15135 627 12 92.00051
15 15214 lockdown 3634 213 11 84.54356
16 69 health 18487 738 12 84.51235
17 1585 mortality 4550 244 12 83.16434
18 1334 cohort 3167 191 12 79.05131
19 1414 sectional 2086 149 12 75.26304
20 311 survey 3809 207 12 72.35758
21 772 cross 3197 185 12 71.99086
22 169 use 16517 649 12 65.14888
23 1971 protocol 2947 169 12 64.82798
24 723 meta 3717 194 12 62.60964
25 503 association 3503 186 12 62.17422
26 12 hospital 7047 308 12 58.89915
27 1433 wave 860 89 12 58.60029
28 46 outcome 7173 310 12 56.44524
29 6974 mental 4050 199 12 55.83859
30 1411 student 2693 151 12 55.8065
31 401 systematic 6525 286 12 55.35106
32 121 case 14195 557 12 55.22809
33 324 review 14000 549 12 54.12105
34 2004 social 5153 235 12 52.8492
35 2663 deep 1428 102 12 51.52235
36 48 level 2880 152 12 50.19633
37 137 model 10504 420 12 48.69939
38 8501 2020 4992 225 12 48.54031
39 888 home 2501 136 12 47.59341
40 56 care 14837 571 12 46.53436
41 312 population 3968 186 12 45.73717
42 1587 retrospective 2816 145 12 45.45863
43 614 vaccine 5422 237 12 45.34045
44 2025 longitudinal 760 72 12 45.13514
45 215 quality 2439 131 12 44.78502
46 8893 der 1380 93 11 44.21907
47 696 report 6902 288 12 44.02468
48 5242 online 2156 120 12 43.78864
49 335 antibody 4869 215 12 42.88817
50 1293 healthcare 4363 197 12 42.77451
12 :
1 8683 covid 149210 830 12 89.47937
2 2280 19 147108 814 12 83.91147
3 871 2 31487 220 12 63.73183
4 1110 cov 28352 203 12 62.29066
5 1111 sars 31530 214 12 57.51843
6 515 impact 12012 94 12 34.38514
7 8501 2020 4992 59 12 34.22499
8 239 base 10781 84 12 30.49452
9 8935 chapter 423 28 8 25.90068
10 298 study 19798 124 12 25.74367
11 445 process 1165 31 12 25.21817
12 408 test 6690 57 12 23.79792
13 7266 manufacturing 211 23 11 21.95282
14 169 use 16517 103 12 21.02708
15 783 learn 5246 47 12 20.9644
16 137 model 10504 73 12 20.86925
17 311 survey 3809 39 12 20.09615
18 6974 mental 4050 38 12 17.90008
19 15214 lockdown 3634 34 11 15.96467
20 1684 de 7340 52 12 15.572
21 8893 der 1380 22 11 15.15114
22 10844 cut 203 16 11 14.99252
23 2721 machine 988 19 12 14.09661
24 313 among 6847 48 12 14.01873
25 69 health 18487 105 12 13.25008
26 1492 energy 791 17 12 13.07431
27 654 effect 9268 59 12 13.00345
28 1411 student 2693 26 12 12.6348
29 3156 national 2295 24 12 12.61005
30 772 cross 3197 27 12 11.13347
31 368 la 4010 31 12 11.0986
32 4386 physical 1621 19 12 10.95507
33 4300 force 615 14 11 10.94779
34 4514 laser 261 12 11 10.70467
35 8905 für 490 13 11 10.56816
36 468 tool 1753 19 12 10.29996
37 1423 large 2034 20 12 9.905375
38 280 development 4727 33 12 9.540171
39 508 country 2553 22 12 9.329608
40 108 pandemic 42664 221 12 9.261027
41 2224 assist 1573 17 12 9.193292
42 484 post 2783 23 12 9.188131
43 608 rapid 3629 27 12 8.989482
44 56933 machining 9 9 1 8.955334
45 464 l 825 13 12 8.905573
46 430 direct 1039 14 12 8.843503
47 631 estimate 1293 15 12 8.582916
48 720 activity 3914 28 12 8.575044
49 1011 pre 1096 14 12 8.560615
50 2103 3d 511 11 11 8.463936
>
January, February
March, April
May, June
July, August
September, October
November, December
