| t01 |
coronavirus, disease, respiratory, 2019, health, syndrome, caused, acute, world, china |
209 |
195 |
| t02 |
hubei, province, china, hubei_province, february, epidemic, wuhan, city, cases, 2020 |
107 |
100 |
| t03 |
italy, countries, iran, south, india, korea, south_korea, country, march, growth |
73 |
68 |
| t04 |
patients, %, detection, symptoms, fever, nucleic, clinical, acid, positive, chest |
51 |
50 |
| t05 |
model(s), predict, peak, method, epidemic, april, mathematical, based, prediction |
63 |
57 |
| t06 |
95, CI, interval, estimated, reproduction, exported, travel, mainland_china, estimate(s) |
36 |
36 |
| t07 |
care, patients, experience, hospital, department, cancer, staff, management, COVID-19, dental |
45 |
43 |
| t08 |
fatality, rate, %, cure, mortality_rate, death, case_fatality, CFR, ill, aged |
22 |
21 |
| t09 |
temperature, correlation(s), interest, factors, incidence, humidity, climate, daily, significant |
27 |
27 |
| t10 |
drug(s), cells, immune, cardiovascular, lung, approved, liver, HD, trials |
31 |
31 |
| t11 |
genome(s), sars-cov-2, host, phylogenetic, molecular, pangolin-cov, mutations, sequences, ratg13 |
27 |
27 |
| t12 |
contact, market, seafood, taiwan, united_states, cluster, animal, united, route, close |
17 |
16 |
| t13 |
covid-19, mental, media, social_media, social, public, health, facemask, H7N9, avian |
23 |
22 |
| t14 |
R0, lombardy, total_population, simulations, COVID−19, 95%-CI, SIRD, tccpm, bound, + |
12 |
11 |
| t15 |
de, el, en, children, pediatric, con, casos, gi_symptoms, su, las |
4 |
4 |
