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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
1 16-24 Disease denotes Covid-19 MESH:C000657245
4 1183-1188 Species denotes human Tax:9606
5 1192-1197 Species denotes human Tax:9606
8 1690-1701 Species denotes coronavirus Tax:11118
9 1740-1746 Species denotes people Tax:9606
14 2231-2237 Species denotes people Tax:9606
15 2266-2272 Species denotes people Tax:9606
16 2146-2152 Disease denotes deaths MESH:D003643
17 2215-2223 Disease denotes infected MESH:D007239
23 2663-2668 Species denotes Ebola Tax:1570291
24 2557-2561 Disease denotes AIDs
25 2575-2583 Disease denotes infected MESH:D007239
26 2669-2686 Disease denotes hemorrhagic fever MESH:D006480
27 2833-2841 Disease denotes infected MESH:D007239
29 3312-3323 Species denotes coronavirus Tax:11118
33 4117-4120 Gene denotes sea Gene:6395
34 3657-3662 Species denotes bleak Tax:54556
35 3979-3985 Species denotes people Tax:9606
38 4354-4360 Species denotes people Tax:9606
39 4583-4589 Species denotes people Tax:9606
41 4843-4851 Disease denotes sea rise MESH:D009041
43 5935-5943 Disease denotes sea rise MESH:D009041
49 5176-5179 Gene denotes sea Gene:6395
50 5093-5099 Species denotes people Tax:9606
51 5446-5452 Species denotes people Tax:9606
52 5611-5617 Species denotes people Tax:9606
53 5057-5065 Disease denotes sea rise MESH:D009041
56 6035-6041 Species denotes people Tax:9606
57 6266-6271 Species denotes human Tax:9606
61 6642-6648 Species denotes people Tax:9606
62 6658-6664 Species denotes people Tax:9606
63 6680-6686 Species denotes people Tax:9606
68 7485-7493 Species denotes children Tax:9606
69 7640-7648 Species denotes children Tax:9606
70 7669-7675 Species denotes People Tax:9606
71 7761-7769 Species denotes children Tax:9606
76 8318-8322 Gene denotes JAMA Gene:50848
77 8556-8565 Disease denotes mortality MESH:D003643
78 8594-8608 Disease denotes drug overdoses MESH:D062787
79 8626-8641 Disease denotes system diseases MESH:D034721
84 9259-9265 Species denotes people Tax:9606
85 9497-9500 Species denotes men Tax:9606
86 9502-9507 Species denotes women Tax:9606
87 9513-9521 Species denotes children Tax:9606
89 10058-10066 Disease denotes Covid-19 MESH:C000657245
91 11722-11731 Disease denotes inability MESH:D007319
96 11986-11989 Species denotes men Tax:9606
97 11991-11996 Species denotes women Tax:9606
98 12001-12009 Species denotes children Tax:9606
99 12367-12375 Disease denotes diabetes MESH:D003920
105 12486-12494 Disease denotes diabetes MESH:D003920
106 12498-12509 Disease denotes prediabetes MESH:D011236
107 12608-12616 Disease denotes diabetic MESH:D003920
108 12643-12654 Disease denotes prediabetes MESH:D011236
109 12710-12718 Disease denotes diabetes MESH:D003920
117 13423-13430 Gene denotes insulin Gene:3630
118 13196-13199 Species denotes men Tax:9606
119 13201-13206 Species denotes women Tax:9606
120 13212-13220 Species denotes children Tax:9606
121 13268-13275 Gene denotes insulin Gene:3630
122 12852-12860 Disease denotes diabetic MESH:D003920
123 13058-13066 Disease denotes diabetes MESH:D003920
126 13667-13674 Gene denotes Insulin Gene:3630
127 13658-13665 Gene denotes insulin Gene:3630
132 13841-13847 Species denotes people Tax:9606
133 13828-13836 Disease denotes diabetes MESH:D003920
134 13942-13963 Disease denotes cardiovascular events MESH:D002318
135 13968-13982 Disease denotes kidney disease MESH:D007674
138 14395-14400 Chemical denotes water MESH:D014867
139 14124-14132 Disease denotes diabetes MESH:D003920
141 15144-15149 Species denotes Human Tax:9606
143 15427-15433 Species denotes people Tax:9606

LitCovid-PMC-OGER-BB

Id Subject Object Predicate Lexical cue
T56 1183-1188 SP_6;NCBITaxon:9606 denotes human
T55 1192-1197 SP_6;NCBITaxon:9606 denotes human
T54 1218-1223 NCBITaxon:10239 denotes virus
T53 1254-1257 NCBITaxon:9606 denotes man
T52 1690-1701 NCBITaxon:11118 denotes coronavirus
T51 1740-1746 NCBITaxon:9606 denotes people
T50 2004-2011 GO:0065007 denotes control
T49 2146-2152 GO:0016265 denotes deaths
T48 2179-2184 NCBITaxon:10239 denotes virus
T47 2231-2237 NCBITaxon:9606 denotes people
T46 2266-2272 NCBITaxon:9606 denotes people
T45 2456-2461 NCBITaxon:10239 denotes virus
T44 3312-3323 NCBITaxon:11118 denotes coronavirus
T43 3979-3985 NCBITaxon:9606 denotes people
T42 4354-4360 NCBITaxon:9606 denotes people
T41 4583-4589 NCBITaxon:9606 denotes people
T40 5093-5099 NCBITaxon:9606 denotes people
T39 5446-5452 NCBITaxon:9606 denotes people
T38 5611-5617 NCBITaxon:9606 denotes people
T37 6010-6019 GO:0046959 denotes habitable
T36 6035-6041 NCBITaxon:9606 denotes people
T35 6115-6119 CHEBI:33290;CHEBI:33290 denotes food
T34 6266-6271 SP_6;NCBITaxon:9606 denotes human
T33 6525-6529 GO:0001837 denotes EMTs
T32 6642-6648 NCBITaxon:9606 denotes people
T31 6658-6664 NCBITaxon:9606 denotes people
T30 6680-6686 NCBITaxon:9606 denotes people
T29 6744-6748 CHEBI:33290;CHEBI:33290 denotes food
T28 7291-7296 GO:0007568 denotes aging
T27 7619-7625 UBERON:0007023 denotes adults
T26 7884-7892 UBERON:0000104 denotes lifespan
T25 8273-8277 UBERON:0000104 denotes life
T24 8371-8375 UBERON:0000104 denotes life
T23 8474-8478 UBERON:0000104 denotes life
T22 8594-8598 CHEBI:23888;CHEBI:23888 denotes drug
T21 8620-8632 UBERON:0000467 denotes organ system
T20 8671-8677 UBERON:0007023 denotes adults
T19 9259-9265 NCBITaxon:9606 denotes people
T18 11203-11213 CHEBI:52217;CHEBI:52217 denotes pharmacies
T17 11293-11304 CHEBI:52217;CHEBI:52217 denotes pharmacists
T16 11917-11928 CHEBI:52217;CHEBI:52217 denotes pharmacists
T15 11965-11972 GO:0040007 denotes growers
T14 12459-12465 UBERON:0007023 denotes adults
T13 13268-13275 PR:000009054 denotes insulin
T12 13423-13430 PR:000009054 denotes insulin
T11 13658-13665 PR:000009054 denotes insulin
T10 13667-13674 PR:000009054 denotes Insulin
T9 13841-13847 NCBITaxon:9606 denotes people
T8 13942-13956 UBERON:0004535 denotes cardiovascular
T7 13968-13974 UBERON:0002113 denotes kidney
T6 14323-14327 UBERON:0000104 denotes life
T5 14351-14355 CHEBI:33290;CHEBI:33290 denotes food
T4 14395-14400 CHEBI:15377;CHEBI:15377 denotes water
T3 15144-15149 SP_6;NCBITaxon:9606 denotes Human
T2 15427-15433 NCBITaxon:9606 denotes people
T1 16031-16039 CHEBI:75958;CHEBI:75958 denotes solution
T57 887-891 CHEBI:33290;CHEBI:33290 denotes food

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 8620-8632 Body_part denotes organ system http://purl.org/sig/ont/fma/fma7149
T2 13268-13275 Body_part denotes insulin http://purl.org/sig/ont/fma/fma83365
T3 13423-13430 Body_part denotes insulin http://purl.org/sig/ont/fma/fma83365
T4 13658-13665 Body_part denotes insulin http://purl.org/sig/ont/fma/fma83365
T5 13667-13674 Body_part denotes Insulin http://purl.org/sig/ont/fma/fma83365
T6 13800-13804 Body_part denotes hand http://purl.org/sig/ont/fma/fma9712
T7 13968-13974 Body_part denotes kidney http://purl.org/sig/ont/fma/fma7203

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T1 5717-5721 Body_part denotes feet http://purl.obolibrary.org/obo/UBERON_0002387
T2 8620-8625 Body_part denotes organ http://purl.obolibrary.org/obo/UBERON_0000062
T3 13800-13804 Body_part denotes hand http://purl.obolibrary.org/obo/UBERON_0002398
T4 13968-13974 Body_part denotes kidney http://purl.obolibrary.org/obo/UBERON_0002113

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T1 2663-2686 Disease denotes Ebola hemorrhagic fever http://purl.obolibrary.org/obo/MONDO_0005737
T2 12367-12375 Disease denotes diabetes http://purl.obolibrary.org/obo/MONDO_0005015
T3 12486-12494 Disease denotes diabetes http://purl.obolibrary.org/obo/MONDO_0005015
T4 12498-12509 Disease denotes prediabetes http://purl.obolibrary.org/obo/MONDO_0006920
T5 12643-12654 Disease denotes prediabetes http://purl.obolibrary.org/obo/MONDO_0006920
T6 12703-12718 Disease denotes type 2 diabetes http://purl.obolibrary.org/obo/MONDO_0005148
T7 12710-12718 Disease denotes diabetes http://purl.obolibrary.org/obo/MONDO_0005015
T8 13058-13066 Disease denotes diabetes http://purl.obolibrary.org/obo/MONDO_0005015
T9 13828-13836 Disease denotes diabetes http://purl.obolibrary.org/obo/MONDO_0005015
T10 13968-13982 Disease denotes kidney disease http://purl.obolibrary.org/obo/MONDO_0001343|http://purl.obolibrary.org/obo/MONDO_0005240
T12 14124-14132 Disease denotes diabetes http://purl.obolibrary.org/obo/MONDO_0005015
T13 16378-16380 Disease denotes he http://purl.obolibrary.org/obo/MONDO_0017319
T14 16468-16470 Disease denotes he http://purl.obolibrary.org/obo/MONDO_0017319
T15 16791-16793 Disease denotes he http://purl.obolibrary.org/obo/MONDO_0017319
T16 16920-16922 Disease denotes he http://purl.obolibrary.org/obo/MONDO_0017319

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1 176-183 http://purl.obolibrary.org/obo/CLO_0009985 denotes focuses
T2 527-529 http://purl.obolibrary.org/obo/CLO_0007653 denotes me
T3 822-823 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T4 1007-1008 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T5 1119-1120 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T6 1183-1188 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T7 1192-1197 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T8 1218-1223 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T9 1240-1241 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T10 1316-1317 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T11 1351-1363 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T12 1401-1402 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T13 1429-1430 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T14 1716-1719 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T15 1760-1761 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T16 1896-1897 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T17 2031-2032 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T18 2179-2184 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T19 2456-2461 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T20 2518-2521 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T21 2571-2574 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T22 2748-2749 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T23 2886-2887 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T24 3052-3053 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T25 3085-3088 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T26 3218-3220 http://purl.obolibrary.org/obo/CLO_0050475 denotes my
T27 3270-3271 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T28 3689-3701 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T29 4677-4682 http://purl.obolibrary.org/obo/CLO_0009985 denotes focus
T30 4853-4854 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T31 5526-5527 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T32 5586-5587 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T33 5706-5707 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T34 6192-6199 http://www.ebi.ac.uk/efo/EFO_0000876 denotes extreme
T35 6266-6271 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T36 6480-6483 http://purl.obolibrary.org/obo/CLO_0001755 denotes Ask
T37 6551-6553 http://purl.obolibrary.org/obo/CLO_0050475 denotes my
T38 6808-6809 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T39 6821-6827 http://purl.obolibrary.org/obo/UBERON_0000033 denotes headed
T40 6821-6827 http://www.ebi.ac.uk/efo/EFO_0000964 denotes headed
T41 6831-6832 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T42 6845-6846 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T43 7032-7033 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T44 7173-7184 http://purl.obolibrary.org/obo/BFO_0000030 denotes objectively
T45 7522-7523 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T46 7780-7782 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T47 7835-7837 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T48 7904-7907 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T49 7970-7971 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T50 8333-8334 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T51 8512-8513 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T52 8532-8535 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T53 8620-8632 http://purl.obolibrary.org/obo/UBERON_0000467 denotes organ system
T54 8978-8979 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T55 9062-9074 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T56 9076-9077 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T57 9232-9235 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T58 9321-9322 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T59 10108-10109 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T60 10168-10170 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T61 10214-10215 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T62 10655-10660 http://purl.obolibrary.org/obo/UBERON_0001456 denotes faced
T63 10808-10809 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T64 10961-10962 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T65 11377-11379 http://purl.obolibrary.org/obo/CLO_0007622 denotes MD
T66 11436-11437 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T67 11459-11466 http://purl.obolibrary.org/obo/SO_0000418 denotes signals
T68 11797-11798 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T69 12656-12657 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T70 12737-12739 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T71 13186-13187 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T72 13268-13275 http://purl.obolibrary.org/obo/PR_000009054 denotes insulin
T73 13423-13430 http://purl.obolibrary.org/obo/PR_000009054 denotes insulin
T74 13487-13488 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T75 13497-13498 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T76 13520-13521 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T77 13658-13665 http://purl.obolibrary.org/obo/PR_000009054 denotes insulin
T78 13667-13674 http://purl.obolibrary.org/obo/PR_000009054 denotes Insulin
T79 13888-13889 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T80 13968-13974 http://purl.obolibrary.org/obo/UBERON_0002113 denotes kidney
T81 13968-13974 http://www.ebi.ac.uk/efo/EFO_0000927 denotes kidney
T82 13968-13974 http://www.ebi.ac.uk/efo/EFO_0000929 denotes kidney
T83 14077-14085 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes humanity
T84 14086-14091 http://purl.obolibrary.org/obo/UBERON_0001456 denotes faces
T85 14146-14147 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T86 14255-14262 http://www.ebi.ac.uk/efo/EFO_0000876 denotes extreme
T87 14432-14433 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T88 14458-14466 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes humanity
T89 14734-14735 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T90 15063-15064 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T91 15144-15149 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes Human
T92 15163-15171 http://purl.obolibrary.org/obo/UBERON_0001456 denotes be faced
T93 15691-15692 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T94 15794-15795 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T95 15877-15878 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T96 15904-15905 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T97 15933-15934 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T98 16110-16111 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T99 16126-16127 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T100 16189-16190 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T101 16471-16474 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T102 16923-16926 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T103 17273-17277 http://purl.obolibrary.org/obo/CLO_0001185 denotes 2018

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 3156-3164 Chemical denotes medicine http://purl.obolibrary.org/obo/CHEBI_23888
T2 8594-8598 Chemical denotes drug http://purl.obolibrary.org/obo/CHEBI_23888
T3 11141-11146 Chemical denotes sales http://purl.obolibrary.org/obo/CHEBI_24866
T4 11377-11379 Chemical denotes MD http://purl.obolibrary.org/obo/CHEBI_74699
T5 13268-13275 Chemical denotes insulin http://purl.obolibrary.org/obo/CHEBI_145810
T6 13423-13430 Chemical denotes insulin http://purl.obolibrary.org/obo/CHEBI_145810
T7 13658-13665 Chemical denotes insulin http://purl.obolibrary.org/obo/CHEBI_145810
T8 13667-13674 Chemical denotes Insulin http://purl.obolibrary.org/obo/CHEBI_5931
T9 14395-14400 Chemical denotes water http://purl.obolibrary.org/obo/CHEBI_15377
T10 15316-15321 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433
T11 16031-16039 Chemical denotes solution http://purl.obolibrary.org/obo/CHEBI_75958
T12 16604-16609 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T1 4503-4516 http://purl.obolibrary.org/obo/GO_0045851 denotes acidification
T2 5370-5376 http://purl.obolibrary.org/obo/GO_0040007 denotes growth
T3 7291-7296 http://purl.obolibrary.org/obo/GO_0007568 denotes aging

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T1 2681-2686 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T2 12703-12718 Phenotype denotes type 2 diabetes http://purl.obolibrary.org/obo/HP_0005978
T3 13968-13982 Phenotype denotes kidney disease http://purl.obolibrary.org/obo/HP_0000112

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T1 0-57 Sentence denotes Climate change, Covid-19, preparedness, and consciousness
T2 59-160 Sentence denotes The Schwartzreport tracks emerging trends that will affect the world, particularly the United States.
T3 161-382 Sentence denotes For EXPLORE it focuses on matters of health in the broadest sense of that term, including medical issues, changes in the biosphere, technology, and policy considerations, all of which will shape our culture and our lives.
T4 383-453 Sentence denotes Perhaps it is because I research and publish the daily Schwartzreport.
T5 454-551 Sentence denotes The many stories I have done on climate change have certainly sensitized me to what is happening.
T6 552-598 Sentence denotes Maybe it's just curiosity, or maybe it's fear.
T7 599-739 Sentence denotes Whatever the reason, as I travel now I find myself looking around and thinking: what will be the impact of climate change on this community?
T8 740-875 Sentence denotes I notice how they are dealing with the homeless, because migration is going to be a big deal, so this trend is only going to get worse.
T9 876-907 Sentence denotes What's the food situation like?
T10 908-933 Sentence denotes How good are the bridges?
T11 934-988 Sentence denotes How do they handle sanitation demands at large events?
T12 989-1022 Sentence denotes It is going to be a huge problem.
T13 1023-1077 Sentence denotes And all of it impacts, most particularly, health care.
T14 1078-1428 Sentence denotes In the United States on 30 January 2020, a Thursday, the Centers for Disease Control confirmed the first human-to-human transmission of the virus in the country, a 60 year old man returning from Wuhan, China, the center of the outbreak.1 A few hours later The World Health Organization declared the fast-spreading outbreak a global health emergency.2
T15 1429-1573 Sentence denotes A few hours later, President Trump closed the borders, quarantined hundreds of travelers who had just arrived in the U.S. and gave an interview.
T16 1574-1802 Sentence denotes As quoted from CNBC: “President Donald Trump said the U.S. government was working closely with China to contain the coronavirus outbreak that has killed at least 171 people, predicting “a very good ending” for the United States.
T17 1803-2071 Sentence denotes “We are working very closely with China and other countries, and we think it's going to have a very good ending for us, that I can assure you,” Trump added U.S. officials believe “we have it all under control,” adding that it's a “very small problem in this country.”3
T18 2072-2153 Sentence denotes Four days later 17,438 cases had been identified and there were 362 known deaths.
T19 2154-2284 Sentence denotes Four days after that the virus, still centered in China, had infected 34,546 people by that time and killed 720 people worldwide.4
T20 2285-2379 Sentence denotes You will be reading this several months after I write it, and so will know how this plays out.
T21 2380-2439 Sentence denotes But the numbers alone aren't the point I am trying to make.
T22 2440-2544 Sentence denotes It is that this virus in spite of all medical advances arose very quickly and has had worldwide effects.
T23 2545-2724 Sentence denotes Just as the AIDs pandemic has infected 75 million and killed 32 million as of 2019; 5 or the much smaller (worldwide) Ebola hemorrhagic fever African epidemic which killed 11,000.
T24 2725-2993 Sentence denotes Certainly we have come a long way the Spanish Flu pandemic of 1918, the deadliest pandemic on record, which infected an estimated 500 million worldwide, roughly a third of the world's population, and killed 20 to 50 million, including and estimated 675,000 Americans.6
T25 2994-3192 Sentence denotes What I am trying to show with these illustrations is that a century of experience and data has taught us these afflictions appear in spite of all the advances of medicine, and cannot be anticipated.
T26 3193-3437 Sentence denotes The question that haunts my mind is, how would the United States handle such a pandemic outbreak if it occurred as the coronavirus did in China, just as some kind of major climate change crisis was also stressing the American healthcare system.
T27 3438-3454 Sentence denotes Are we prepared?
T28 3455-3480 Sentence denotes I don't think so, do you?
T29 3481-3670 Sentence denotes The reality is that not only America but the world is utterly unprepared for these outbreaks, and when one adds the migrations that climate change will compel things look very bleak indeed.
T30 3671-3846 Sentence denotes The International Organization for Migration in Geneva is generally considered the best source on information on this issue, and their source is Oxford professor Norman Myers.
T31 3847-4155 Sentence denotes He says that by 2050, which is to say just 30 years from now, “When global warming takes hold there could be as many as 200 million people overtaken by disruptions of monsoon systems and other rainfall regimes, by droughts of unprecedented severity and duration, and by sea-level rise and coastal flooding.”7
T32 4156-4205 Sentence denotes This rise in migration trend is already underway.
T33 4206-4455 Sentence denotes The United Nations reports, “The climate crisis is already having an effect: according to the Internal Displacement Monitoring centre, 17.2 million people had to leave their homes last year, because of disasters that negatively affected their lives.
T34 4456-4662 Sentence denotes Slow changes in the environment, such as ocean acidification, desertification and coastal erosion, are also directly impacting people's livelihoods and their capacity to survive in their places of origin.”8
T35 4663-4733 Sentence denotes But I want to focus on the America's internal migrations particularly.
T36 4734-4852 Sentence denotes Just consider the internal migrants projected to abandon coastal cities and towns because of flooding due to sea rise.
T37 4853-5221 Sentence denotes A multi-university re. search team led by Caleb Robinson of Georgia Institute of Technology's School Computational Science and Engineering Department did the calculations (See Fig. 1 ) and projected that sea rise alone will make 13 million people internal migrants.9 The team's commentary is chilling, “The impacts of SLR (sea level rise) are potentially catastrophic.
T38 5222-5403 Sentence denotes About 30% of the urban land on earth was located in high-frequency flood zones in 2000, and it is projected to increase to 40% by 2030 taking urban growth and SLR into account [14].
T39 5404-5567 Sentence denotes In the United States alone, 123.3 million people, or 39% of the total population, lived in coastal counties in 2010, with a predicted 8% increase by the year 2020.
T40 5568-5730 Sentence denotes By the year 2100, a projected 13.1 million people in the United States alone would be living on land that will be considered flooded with a SLR of 6 feet (1.8 m).
T41 5731-5962 Sentence denotes Fig. 1 Shows all counties that experience flooding under 1.8 m of SLR by 2100 in blue and colors the remaining counties based on the number of additional incoming migrants per county that there caused by sea rise over the baseline.
T42 5963-6352 Sentence denotes “As oceans expand and encroach into previously habitable land, affected people—climate migrants—will move towards locations further inland, looking for food and shelter in areas that are less susceptible to increased flooding or extreme weather events….we argue that the comprehensive impacts of SLR on human populations, when considering migration, expand far beyond the coastal areas.”10
T43 6353-6441 Sentence denotes Climate change, migration, and epidemics; what lessons should we draw from those trends?
T44 6442-6479 Sentence denotes How prepared is America to deal them?
T45 6480-6493 Sentence denotes Ask yourself:
T46 6494-6627 Sentence denotes Where I practice how would the EMTs, clinics, hospitals, my practice itself, handle the stresses to come over the next three decades?
T47 6628-6780 Sentence denotes Whether it is people fleeing, people in transit, or people arriving, how would sanitation, housing, healthcare, and food support be done where you live?
T48 6781-6902 Sentence denotes I want to argue that we as a nation are headed to a disaster of a proportion nationwide never experienced in our history.
T49 6903-7023 Sentence denotes And it is occurring at the same time that the Illness Profit System that passes for healthcare in America is collapsing.
T50 7024-7054 Sentence denotes Is this a political statement?
T51 7055-7122 Sentence denotes Only in the sense that it is going to require politics to solve it.
T52 7123-7280 Sentence denotes Let's put partisanship aside and just look at the objectively verifiable data starting with the demographic which is going to live through what is occurring.
T53 7281-7308 Sentence denotes We are an aging population.
T54 7309-7330 Sentence denotes According to the U.S.
T55 7331-7435 Sentence denotes Census Bureau in less that 20 years the old will outnumber the young for the first time in U.S. history.
T56 7436-7564 Sentence denotes They report, “Already, the middle-aged outnumber children, but the country will reach a new milestone in 2034 (previously 2035).
T57 7565-7584 Sentence denotes That year, the U.S.
T58 7585-7668 Sentence denotes Census Bureau projects that older adults will edge out children in population size:
T59 7669-7877 Sentence denotes People age 65 and over are expected to number 77.0 million (previously 78.0 million), while children under age 18 will number 76.5 million (previously 76.7 million).”11 So we are getting older and less vital.
T60 7878-8003 Sentence denotes Also, lifespan in America has been going downward for the last three years, after more than a century of increasing steadily.
T61 8004-8349 Sentence denotes Steven Wolf of Center on Society and Health, Department of Family Medicine and Population Health, Virginia Commonwealth University School of Medicine, Richmond, and Heidi Schoonmaker of Eastern Virginia Medical School, Norfolk, teamed up to really climb inside of this life expectancy decline, and their report in JAMA should be a clock stopper.
T62 8350-8511 Sentence denotes They found that, “US life expectancy increased for most of the past 60 years, but the rate of increase slowed over time and life expectancy decreased after 2014.
T63 8512-8821 Sentence denotes A major contributor has been an increase in mortality from specific causes (e.g., drug overdoses, suicides, organ system diseases) among young and middle-aged adults of all racial groups, with an onset as early as the 1990s and with the largest relative increases occurring in the Ohio Valley and New England.
T64 8822-8945 Sentence denotes The implications for public health and the economy are substantial, making it vital to understand the underlying causes.”12
T65 8946-9102 Sentence denotes And all of this is occurring in a nation whose healthcare system currently ranks, according the to the World Health Organization, a lowly 37th in the world.
T66 9103-9236 Sentence denotes Far from preparing for climate change and what it means, the United States is going backwards, dismantling the fragile system it has.
T67 9237-9334 Sentence denotes Twenty percent of the people living in the United States live in what is defined as a rural area.
T68 9335-9407 Sentence denotes Rural counties constitute approximately 97% of the land mass of America.
T69 9408-9727 Sentence denotes About 20% of the population live in one of these counties – that's just under 66 million men, women, and children, although this population is skewed older; 17.5% are older than 65, compared to urban areas where that percentage is 13.8% In some states more than 50% of the older population lives in these rural areas.13
T70 9728-9898 Sentence denotes So we have climate change coming on in rural areas where there is an older population that already requires more healthcare that average.14 So what is actually happening?
T71 9899-10128 Sentence denotes Since the U.S. healthcare system places profit above health, hospitals are closing right and left (see Fig. 2 ) because they aren't profitable enough, and the Covid-19 crisis will show us what happens in such a healthcare system.
T72 10129-10153 Sentence denotes Fig. 2 Credit: navigant.
T73 10154-10297 Sentence denotes In 2016 about 41% of rural hospitals nationally operated at a negative margin, meaning they lost more money than they produced from operations.
T74 10298-10523 Sentence denotes Texas and Mississippi had the highest number of economically vulnerable facilities, that year.15 Three years later, in 2019, more than 20% of our nation's rural hospitals, or 430 hospitals across 43 states were near collapse.
T75 10524-10578 Sentence denotes At least 155 rural hospitals have closed since 2005.16
T76 10579-10634 Sentence denotes I have been documenting this in these pages since 2005.
T77 10635-10788 Sentence denotes Once the reality is faced that healthcare is calibrated to profit not wellbeing, it is easy to see why hospital corporations are closing rural hospitals.
T78 10789-10913 Sentence denotes At present we have a situation where the healthcare system is disintegrating at the very time it is going to be most needed.
T79 10914-10950 Sentence denotes Think about those hospitals closing.
T80 10951-11065 Sentence denotes Each time a rural hospital closes, there are tragic consequences for the local community and surrounding counties.
T81 11066-11226 Sentence denotes While the medical consequences are the most obvious, there is also loss of sales tax revenue, reduction in supporting businesses such as pharmacies and clinics.
T82 11227-11342 Sentence denotes There are also fewer professionals, including doctors, nurses and pharmacists, and fewer students in local schools.
T83 11343-11556 Sentence denotes David Mosley and Daniel DeBehnke, MD, studied this exact issue and reported: “The closing of a rural hospital often signals the beginning of progressive decline and deterioration of small rural towns and counties.
T84 11557-11674 Sentence denotes Hospitals often serve as financial and professional anchors as well as source of pride for its small rural community.
T85 11675-11791 Sentence denotes It also often means loss of other employers or inability to recruit new employers due to lack of nearby health care.
T86 11792-11886 Sentence denotes When a rural hospital closes its doors, unemployment often rises, and average income drops.”17
T87 11887-12070 Sentence denotes There are no nurses, doctors, pharmacists or ERs for local farmers, ranchers, growers and assorted men, women and children who love living and working in America's vast rural regions.
T88 12071-12198 Sentence denotes Rural communities and rural citizens are often left with no options for routine primary care, maternity care or emergency care.
T89 12199-12250 Sentence denotes Even basic medical supplies are often hard to find.
T90 12251-12357 Sentence denotes Just think about one example of what would happen if 13 million Americans were on the move in desperation.
T91 12358-12376 Sentence denotes Consider diabetes.
T92 12377-12617 Sentence denotes According to the Centers for Disease Control, in 2017 “More than 100 million U.S. adults are now living with diabetes or prediabetes.” The report found that in 2015, 30.3 million Americans – 9.4 percent of the U.S. population were diabetic.
T93 12618-12807 Sentence denotes Another 84.1 million had prediabetes, a condition that if not treated often leads to type 2 diabetes within five years.18 And the numbers in 2020 are larger because they have been going up.
T94 12808-12950 Sentence denotes Assume for the moment equal distribution of diabetic sufferers amongst the internal migrants, although in actuality that will not be the case.
T95 12951-13087 Sentence denotes Coastal Southern states, where climate change will particularly cause internal migration, have the highest diabetes rate in the country.
T96 13088-13123 Sentence denotes But just assume equal distribution.
T97 13124-13243 Sentence denotes If there are 13 million internal migrants, 9.4% would be over a million men, women, and children, 1222,000 to be exact.
T98 13244-13441 Sentence denotes If you have been taking insulin for more than 10 years without it you probably wouldn't live no more than 10 days.19 Do you think all those migrants will be well stocked with the insulin they need?
T99 13442-13458 Sentence denotes No neither do I.
T100 13459-13666 Sentence denotes If you live and practice in a city of a hundred thousand, or a town of 50,000, could your emergency rooms handle 10,000 or 5000 additional diabetics desperate, probably unable to pay for their daily insulin?
T101 13667-13691 Sentence denotes Insulin is not optional.
T102 13692-13762 Sentence denotes How would your city or town even set up the system to meet the demand?
T103 13763-13805 Sentence denotes Would your pharmacies have enough on hand?
T104 13806-14011 Sentence denotes And it isn't just the diabetes; if people weren't getting their dosages regularly a whole range of serious health complications such as cardiovascular events, or kidney disease will arise and require care.
T105 14012-14133 Sentence denotes In this essay I have just touched on three aspects of the crisis humanity faces, pandemics, climate change, and diabetes.
T106 14134-14166 Sentence denotes But that is a very partial list.
T107 14167-14401 Sentence denotes To really get the full picture would require more than an essay; one would have to add: extreme weather events from hurricanes to heatwaves, the decline of life-sustaining ecosystems, food security and dwindling stores of fresh water.
T108 14402-14487 Sentence denotes Each one of these alone poses a monumental challenge to humanity in the 21st century.
T109 14488-14560 Sentence denotes Taken together as is likely to happen the situation becomes cataclysmic.
T110 14561-14617 Sentence denotes America is not prepared for any of this, not even close.
T111 14618-14639 Sentence denotes How bad could it get.
T112 14640-14811 Sentence denotes At the University of Massachusetts in Boston, at the Center for Governance and Sustainability a team led by the center's director Professor Maria Ivanova as that question.
T113 14812-14833 Sentence denotes And their conclusion?
T114 14834-15047 Sentence denotes Looking at the combination of variables they see affecting the world they said these factors, “have the potential to impact and amplify one another in ways that might cascade to create global systemic collapse.”20
T115 15048-15250 Sentence denotes Erik Franklin, a researcher at the University of Hawaii's Institute of Marine Biology concurs, “Human society will be faced with the devastating combined impacts of multiple interacting climate hazards.
T116 15251-15308 Sentence denotes They are happening now and will continue to get worse.”21
T117 15309-15455 Sentence denotes If any group must lead the preparation fight to prepare us I think it must be America's healthcare professionals; the people actually on the line.
T118 15456-15485 Sentence denotes However, comfortable you are.
T119 15486-15613 Sentence denotes No matter how convinced you are that this chain of crises won't touch you, or that you can handle it, you won't, and you can't.
T120 15614-15682 Sentence denotes Not with the infrastructure and illness profit system we have today.
T121 15683-15853 Sentence denotes I think a significant part of the budget now going to the military should be redirected into the rebuilding of a new system based on universality and fostering wellbeing.
T122 15854-15903 Sentence denotes It is going to require a different consciousness.
T123 15904-15932 Sentence denotes A different way of thinking.
T124 15933-15955 Sentence denotes A different worldview.
T125 15956-16040 Sentence denotes And just as they say, you either become part of the problem or part of the solution.
T126 16043-16112 Sentence denotes Scientist, futurist, and award-winning author and novelist Stephan A.
T127 16113-16203 Sentence denotes Schwartz, is a Distinguished Consulting Faculty of Saybrook University, and a BIAL Fellow.
T128 16204-16425 Sentence denotes He is an award winning author of both fiction and non-fiction, columnist for the journal EXPLORE, and editor of the daily web publication Schwartzreport.net in both of which he covers trends that are affecting the future.
T129 16426-16573 Sentence denotes For over 40 years, as an experimentalist, he has been studying the nature of consciousness, particularly that aspect independent of space and time.
T130 16574-16737 Sentence denotes Schwartz is part of the small group that founded modern Remote Viewing research, and is the principal researcher studying the use of Remote Viewing in archaeology.
T131 16738-16879 Sentence denotes In addition to his own non-fiction works and novels, he is the author of more than 200 technical reports, papers, and academic book chapters.
T132 16880-17105 Sentence denotes In addition to his experimental studies he has written numerous magazine articles for Smithsonian, OMNI, American History, American Heritage, The Washington Post, The New York Times, as well as other magazines and newspapers.
T133 17106-17336 Sentence denotes He is the recipient of the Parapsychological Association Outstanding Contribution Award, OOOM Magazine (Germany) 100 Most Inspiring People in the World award, and the 2018 Albert Nelson Marquis Award for Outstanding Contributions.