This is a table of named entities, their types, and their frequencies from sentences in your study carrel. Use it to search & browse the list to learn more about your study carrel. Please keep in mind that named-entity extraction is not as accurate as more generic parts-of-speech extraction. Unusual results will appear here.
entity | type | frequency |
---|---|---|
individuals | TAXON | 835 |
infection | DISEASE | 809 |
covid | ORG | 598 |
infectious | DISEASE | 343 |
virus | TAXON | 293 |
covid 19 | ORG | 288 |
sir | ORG | 254 |
infections | DISEASE | 247 |
deaths | DISEASE | 226 |
italy | GPE | 210 |
coronavirus | TAXON | 195 |
sis | ORG | 174 |
china | GPE | 172 |
death | DISEASE | 169 |
infectious disease | DISEASE | 142 |
infectious diseases | DISEASE | 136 |
seir | ORG | 110 |
nodes | CHEMICAL | 109 |
india | GPE | 100 |
human | TAXON | 97 |
cc | CHEMICAL | 82 |
sars | DISEASE | 81 |
epidemic | DISEASE | 77 |
coronavirus | TAXON | 73 |
ppe | ORG | 70 |
outbreaks | TAXON | 65 |
appendix | GPE | 64 |
n | ORG | 62 |
germany | GPE | 62 |
wuhan | GPE | 55 |
us | GPE | 55 |
spain | GPE | 54 |
uk | GPE | 52 |
south korea | GPE | 47 |
coronavirus disease | DISEASE | 44 |
kermack | GPE | 43 |
trauma | DISEASE | 43 |
k | ORG | 42 |
journal | ORG | 38 |
fits | DISEASE | 36 |
usa | GPE | 33 |
padé | GPE | 33 |
japan | GPE | 33 |
viral | TAXON | 32 |
brazil | GPE | 32 |
france | GPE | 31 |
bangladesh | ORG | 30 |
covid19 | ORG | 28 |
johns hopkins | ORG | 28 |
sirs | ORG | 26 |
lymphorrhea | DISEASE | 26 |
max | PERSON | 25 |
sec | PERSON | 24 |
sars cov 2 | ORG | 24 |
fokker | CHEMICAL | 24 |
canada | GPE | 24 |
hmf | ORG | 23 |
the united states | GPE | 23 |
mckendrick | ORG | 23 |
de | GPE | 21 |
mers | DISEASE | 21 |
esir | ORG | 21 |
eq | PERSON | 21 |
h1n1 | GPE | 21 |
hamilton | PERSON | 21 |
china | GPE | 21 |
nam | ORG | 21 |
new york | GPE | 21 |
ORG | 21 | |
bias | CHEMICAL | 21 |
fatalities | DISEASE | 21 |
gamma | CHEMICAL | 20 |
pged | ORG | 20 |
italy | GPE | 19 |
roc | GPE | 19 |
infocas | GPE | 19 |
ddft | GPE | 19 |
ar | ORG | 19 |
texas | GPE | 19 |
ny | ORG | 18 |
amazon | ORG | 18 |
europe | LOC | 18 |
mcmc | ORG | 18 |
sweden | GPE | 18 |
epidemia | TAXON | 18 |
lymphedema | DISEASE | 18 |
un | ORG | 18 |
ncov | ORG | 17 |
complexity | DISEASE | 17 |
toronto | GPE | 17 |
sierra leone | CHEMICAL | 17 |
sfn | ORG | 17 |
humans | TAXON | 17 |
fokker planck | GPE | 17 |
cdc | ORG | 17 |
michigan | GPE | 16 |
markovian | ORG | 16 |
next | ORG | 16 |
monte carlo | PERSON | 16 |
contagion | DISEASE | 16 |
li | PERSON | 15 |
guinea | TAXON | 15 |
kerala | GPE | 15 |
lemma | CHEMICAL | 15 |
anderson | PERSON | 15 |
nd 4 0 international license it | CHEMICAL | 15 |
nhs | ORG | 15 |
pg | CHEMICAL | 15 |
qmf | ORG | 15 |
humans | TAXON | 15 |
inequality | DISEASE | 14 |
switzerland | GPE | 14 |
sf | GPE | 14 |
rrg | ORG | 14 |
death | DISEASE | 14 |
markov | ORG | 13 |
ca | ORG | 13 |
dfe | ORG | 13 |
ifr | CHEMICAL | 13 |
la | GPE | 13 |
infection | DISEASE | 13 |
mathematical | ORG | 13 |
viruses | TAXON | 13 |
txl | ORG | 13 |
curvas | CHEMICAL | 13 |
van kampen | PERSON | 13 |
sin | TAXON | 13 |
iran | GPE | 12 |
coronavirus disease | DISEASE | 12 |
covid 19 | ORG | 12 |
individuals | TAXON | 12 |
dakos | PERSON | 12 |
israel | GPE | 12 |
lst | PERSON | 12 |
bacterial | TAXON | 12 |
burn | DISEASE | 12 |
pneumonia | DISEASE | 12 |
lotka | GPE | 11 |
abc | ORG | 11 |
alemania | GPE | 11 |
algorithm 1 | ORG | 11 |
austria | GPE | 11 |
belgium | GPE | 11 |
bernoulli | ORG | 11 |
cov | CHEMICAL | 11 |
confirmed | ORG | 11 |
coronavirus disease | DISEASE | 11 |
kendall | GPE | 11 |
ode | DISEASE | 11 |
mlp | ORG | 11 |
south africa | GPE | 11 |
después | DISEASE | 11 |
anomalies | DISEASE | 11 |
trauma | ORG | 11 |
supernodes | CHEMICAL | 11 |
sna | ORG | 11 |
poisson | ORG | 11 |
η | DISEASE | 11 |
notice | ORG | 11 |
morocco | TAXON | 11 |
nn | ORG | 10 |
all | DISEASE | 10 |
dde | ORG | 10 |
drc | ORG | 10 |
ebola | TAXON | 10 |
el | GPE | 10 |
human | TAXON | 10 |
ld | GPE | 10 |
lv | ORG | 10 |
mc | PERSON | 10 |
numerical | ORG | 10 |
runge kutta | PERSON | 10 |
russia | GPE | 10 |
table 1 | LOC | 10 |
ui | ORG | 10 |
autofluorescence | CHEMICAL | 10 |
ts | TAXON | 10 |
β | PERSON | 10 |
ocp | ORG | 10 |
enrenew | PERSON | 9 |
mmr | ORG | 9 |
lombardy | GPE | 9 |
lagartococha | PERSON | 9 |
john hopkins university | ORG | 9 |
gabaix | PERSON | 9 |
armenia | GPE | 9 |
cuba | GPE | 9 |
crps | ORG | 9 |
australia | GPE | 9 |
adomian | GPE | 9 |
mitarai | LOC | 9 |
malaria | TAXON | 9 |
anfis | PERSON | 9 |
model | PERSON | 9 |
se | CHEMICAL | 9 |
n s | ORG | 9 |
wuhan | GPE | 9 |
los datos | GPE | 9 |
dspir | CHEMICAL | 9 |
singapore | GPE | 9 |
malaria | DISEASE | 9 |
sse | GPE | 9 |
sivrt | ORG | 9 |
ro | CHEMICAL | 9 |
rrn | PERSON | 9 |
re | ORG | 9 |
new jersey | GPE | 9 |
luxembourg | GPE | 8 |
boltzmann | ORG | 8 |
cfr | ORG | 8 |
formula | ORG | 8 |
harko | ORG | 8 |
heesterbeek 2000 | CHEMICAL | 8 |
hubei | GPE | 8 |
keeling | GPE | 8 |
kermack mckendrick | PERSON | 8 |
legendre | GPE | 8 |
korea | GPE | 8 |
ontario | GPE | 8 |
who | ORG | 8 |
nan doi | PERSON | 8 |
coronavirus covid | DISEASE | 8 |
al 2005 | PERSON | 8 |
infected | DISEASE | 8 |
vm | ORG | 8 |
time | ORG | 8 |
seattle | GPE | 8 |
sars mers | DISEASE | 8 |
eq 4 | ORG | 7 |
maharashtra | ORG | 7 |
lloyd smith | PERSON | 7 |
johns hopkins university | ORG | 7 |
ica | ORG | 7 |
houston | GPE | 7 |
harris county | GPE | 7 |
euler | PERSON | 7 |
beijing | GPE | 7 |
epidemiological | LOC | 7 |
england | GPE | 7 |
eg | ORG | 7 |
borel | PERSON | 7 |
northern italy | LOC | 7 |
becker | DISEASE | 7 |
animals | TAXON | 7 |
ncbi | ORG | 7 |
chaos | DISEASE | 7 |
rct | ORG | 7 |
cow | TAXON | 7 |
rohani | GPE | 7 |
β β | PERSON | 7 |
swine | TAXON | 7 |
skin cancer | DISEASE | 7 |
respiratory syndrome | DISEASE | 7 |
melanoma | DISEASE | 7 |
labor | DISEASE | 7 |
pandemia | DISEASE | 7 |
contagio | CHEMICAL | 7 |
andĪ | ORG | 7 |
acute respiratory syndrome | DISEASE | 7 |
active infections | DISEASE | 7 |
united kingdom | GPE | 7 |
tokyo | GPE | 7 |
taylor | GPE | 7 |
pareto | ORG | 6 |
exposed infected | DISEASE | 6 |
outbreaks | TAXON | 6 |
optimal | ORG | 6 |
np | ORG | 6 |
mh | ORG | 6 |
laplace | ORG | 6 |
hong kong | GPE | 6 |
hamilton jacobi bellman | PERSON | 6 |
auc | ORG | 6 |
ORG | 6 | |
diekmann | PERSON | 6 |
corea | CHEMICAL | 6 |
california | GPE | 6 |
cosir | ORG | 6 |
bapras | ORG | 6 |
asia | LOC | 6 |
sair | ORG | 6 |
pneumonia | GPE | 6 |
tuberculosis | DISEASE | 6 |
sirsim | CHEMICAL | 6 |
confusion | DISEASE | 6 |
sirtype | ORG | 6 |
nucleotides | CHEMICAL | 6 |
max n | ORG | 6 |
fever | DISEASE | 6 |
diseases | DISEASE | 6 |
dengue | DISEASE | 6 |
coronavirus severe acute respiratory syndrome | DISEASE | 6 |
rewritten | CHEMICAL | 6 |
cancer | DISEASE | 6 |
sarcoma | GPE | 6 |
w | ORG | 6 |
turkey | GPE | 6 |
ts | GPE | 6 |
state | ORG | 6 |
social | ORG | 6 |
animals | TAXON | 6 |
hungary | GPE | 5 |
ibr | ORG | 5 |
ihme | CHEMICAL | 5 |
identifying | LOC | 5 |
india australia usa italy | ORG | 5 |
infectious disease | DISEASE | 5 |
kim | PERSON | 5 |
liberia | GPE | 5 |
la county | GPE | 5 |
la | PERSON | 5 |
liu moon | PERSON | 5 |
lloyd smith et | PERSON | 5 |
london | GPE | 5 |
matlab | ORG | 5 |
hethcote | CHEMICAL | 5 |
hubei province | GPE | 5 |
chung | PERSON | 5 |
hastings | PERSON | 5 |
hmf c | ORG | 5 |
gibbs | ORG | 5 |
ferguson | GPE | 5 |
eq 1 | PERSON | 5 |
ebola virus | TAXON | 5 |
doi | CHEMICAL | 5 |
control | ORG | 5 |
china south korea | ORG | 5 |
clt | ORG | 5 |
bryson | PERSON | 5 |
brn | ORG | 5 |
analysis | GPE | 5 |
muraoka | PERSON | 5 |
allen | PERSON | 5 |
mle | ORG | 5 |
tumour | DISEASE | 5 |
north america | LOC | 5 |
hosts | TAXON | 5 |
coronavirus sars | DISEASE | 5 |
coronavirus infected pneumonia | DISEASE | 5 |
coronavirus infection | DISEASE | 5 |
esair | CHEMICAL | 5 |
failure | DISEASE | 5 |
gaps | DISEASE | 5 |
injuries | DISEASE | 5 |
conflict | DISEASE | 5 |
que | PERSON | 5 |
secondary infections | DISEASE | 5 |
shock | DISEASE | 5 |
the laplace adomian decomposition method | ORG | 5 |
β dβ | PERSON | 5 |
pde | ORG | 5 |
cord_uid | ORG | 5 |
loss of generality | DISEASE | 5 |
cholera | GPE | 5 |
van kampen | PERSON | 5 |
schorfheide | CHEMICAL | 5 |
bacterial infection | DISEASE | 5 |
storn | ORG | 5 |
tsconfirmed geo | PERSON | 5 |
time series | ORG | 5 |
touzi | GPE | 5 |
thucydides | GPE | 5 |
vespignani | ORG | 5 |
virus | TAXON | 5 |
walant | ORG | 5 |
yasuni | ORG | 5 |
active infected | DISEASE | 5 |
bacteria | TAXON | 5 |
illinois | GPE | 4 |
mers cov | ORG | 4 |
kmh | GPE | 4 |
kucharski | ORG | 4 |
lva | ORG | 4 |
lagrange | PERSON | 4 |
lambert | GPE | 4 |
lambert w | ORG | 4 |
laplace adomian decomposition methods | ORG | 4 |
liu | PERSON | 4 |
mittag leffler | ORG | 4 |
mlt | ORG | 4 |
mode | ORG | 4 |
mtc | DISEASE | 4 |
makse | PERSON | 4 |
milan | GPE | 4 |
multi | ORG | 4 |
mummert | GPE | 4 |
n β | ORG | 4 |
ind | ORG | 4 |
ibragimov | PERSON | 4 |
covid19 | GPE | 4 |
huang | PERSON | 4 |
hmc | ORG | 4 |
new zealand | GPE | 4 |
6µ | CHEMICAL | 4 |
ai | GPE | 4 |
ames | CHEMICAL | 4 |
barton | GPE | 4 |
chicago | GPE | 4 |
dashboard explorer | PERSON | 4 |
de nadai | PERSON | 4 |
deaths | DISEASE | 4 |
dirichlet | PERSON | 4 |
dynamic | ORG | 4 |
eqs 1 | GPE | 4 |
eubank | GPE | 4 |
examples | PERSON | 4 |
false | ORG | 4 |
fispo | ORG | 4 |
galton watson | PERSON | 4 |
gillespie | GPE | 4 |
godambe | GPE | 4 |
nhs trust | ORG | 4 |
llb | ORG | 4 |
phe | ORG | 4 |
coronavirus sars cov | DISEASE | 4 |
cow disease | DISEASE | 4 |
esperar | DISEASE | 4 |
host | TAXON | 4 |
india | GPE | 4 |
infestation | DISEASE | 4 |
lemma | CHEMICAL | 4 |
livemap | PERSON | 4 |
modelo | PERSON | 4 |
pertussis | DISEASE | 4 |
respiratory disease | DISEASE | 4 |
the center for systems science and engineering csse | ORG | 4 |
the city of toronto | GPE | 4 |
the johns hopkins university | ORG | 4 |
the laplace adomian decomposition methods | ORG | 4 |
the united kingdom | GPE | 4 |
varicella | DISEASE | 4 |
virus disease | DISEASE | 4 |
Á | CHEMICAL | 4 |
Γ | ORG | 4 |
coronavirus outbreaks | TAXON | 4 |
viral disease | DISEASE | 4 |
computational complexity | DISEASE | 4 |
satorras | PERSON | 4 |
carbon | CHEMICAL | 4 |
price 1997 | ORG | 4 |
s n | ORG | 4 |
si | ORG | 4 |
sihrd | ORG | 4 |
sir disease | DISEASE | 4 |
sirit | CHEMICAL | 4 |
sirp | ORG | 4 |
spir | ORG | 4 |
put | CHEMICAL | 4 |
song | PERSON | 4 |
viral | TAXON | 4 |
wang et al 2020 | PERSON | 4 |
animal | TAXON | 4 |
pagerank | ORG | 4 |
bat | TAXON | 4 |
calculus | DISEASE | 4 |
burns | DISEASE | 4 |
susceptibles | CHEMICAL | 4 |
infectious diseases | DISEASE | 3 |
imperial college | ORG | 3 |
infectious diseases of humans dynamics | ORG | 3 |
l s | GPE | 3 |
introduction | ORG | 3 |
johnson | PERSON | 3 |
lle | CHEMICAL | 3 |
houston tx | GPE | 3 |
health | ORG | 3 |
ho 1975 feehery | CHEMICAL | 3 |
heinsberg | ORG | 3 |
healthcare | ORG | 3 |
hamer | ORG | 3 |
html | ORG | 3 |
hiv aids | DISEASE | 3 |
gu | PERSON | 3 |
lvsir | ORG | 3 |
frasca | PERSON | 3 |
llt | CHEMICAL | 3 |
mathematica | GPE | 3 |
las | ORG | 3 |
mckendrick 1927 | ORG | 3 |
feehery | ORG | 3 |
n 1 | ORG | 3 |
multi objective differential evolution mode | ORG | 3 |
middle east | LOC | 3 |
mexico | GPE | 3 |
metropolis hastings | PERSON | 3 |
metropolis | PERSON | 3 |
matlab | GPE | 3 |
lenhart | PERSON | 3 |
markov chain | PERSON | 3 |
malaysia | GPE | 3 |
mop | ORG | 3 |
lymphorrhea | PERSON | 3 |
lotka volterra | ORG | 3 |
lobato | GPE | 3 |
lie | PERSON | 3 |
fourier | PERSON | 3 |
clf | ORG | 3 |
fra | ORG | 3 |
f | ORG | 3 |
ci | ORG | 3 |
ccse | ORG | 3 |
brockmann | PERSON | 3 |
britton | GPE | 3 |
bone | ORG | 3 |
boettiger | PERSON | 3 |
bernstein | PERSON | 3 |
bergamo | GPE | 3 |
beauchemin | PERSON | 3 |
baltimore | GPE | 3 |
austria germany | GPE | 3 |
althaus | ORG | 3 |
allen 2003 | PERSON | 3 |
africa | LOC | 3 |
awt | ORG | 3 |
asps | DISEASE | 3 |
ad | ORG | 3 |
nuts | CHEMICAL | 3 |
cancer | DISEASE | 3 |
cauchy | GPE | 3 |
differential evolution de | ORG | 3 |
exp | ORG | 3 |
esto | ORG | 3 |
eq a4 | ORG | 3 |
eq 9 | LOC | 3 |
ebola virus disease | DISEASE | 3 |
ebov | TAXON | 3 |
dynamical | ORG | 3 |
differential | ORG | 3 |
chikungunya | GPE | 3 |
delays | DISEASE | 3 |
dt | CHEMICAL | 3 |
d m | ORG | 3 |
curves | ORG | 3 |
coronavirus covid | DISEASE | 3 |
continuum | PERSON | 3 |
covstat | PERSON | 3 |
n s i r | CHEMICAL | 3 |
github | ORG | 3 |
ny and nj | ORG | 3 |
overload | DISEASE | 3 |
obesity | DISEASE | 3 |
nonequilibrium | CHEMICAL | 3 |
linear | ORG | 3 |
keloid | DISEASE | 3 |
ksi | PERSON | 3 |
inter county | GPE | 3 |
influenza a h1n1 | DISEASE | 3 |
infectious stage | DISEASE | 3 |
infecteds | CHEMICAL | 3 |
httpd conf | ORG | 3 |
gain | DISEASE | 3 |
france | GPE | 3 |
fracture | DISEASE | 3 |
final infection | DISEASE | 3 |
el segundo | ORG | 3 |
dying | DISEASE | 3 |
disminución | CHEMICAL | 3 |
organism | TAXON | 3 |
pathologies | DISEASE | 3 |
de β | PERSON | 3 |
physreve | CHEMICAL | 3 |
nishiura | PERSON | 3 |
Ω f t | GPE | 3 |
β µ | PERSON | 3 |
Élie hubert | PERSON | 3 |
Élie | CHEMICAL | 3 |
worldometers info coronavirus | DISEASE | 3 |
vital dynamics | ORG | 3 |
virus infection | DISEASE | 3 |
the world health organization | ORG | 3 |
the kingdom of morocco | GPE | 3 |
the basic reproduction number | ORG | 3 |
tabla | DISEASE | 3 |
sarcoma | DISEASE | 3 |
respiratory syndrome coronavirus 2 sars | DISEASE | 3 |
respiratory syndrome coronavirus 2 | DISEASE | 3 |
respiratory syndrome coronavirus | DISEASE | 3 |
pyoverdine | CHEMICAL | 3 |
del número de infectados | PERSON | 3 |
spain | GPE | 3 |
covid19india | CHEMICAL | 3 |
schwartz | PERSON | 3 |
sir n | ORG | 3 |
sif | CHEMICAL | 3 |
si n r | ORG | 3 |
seis | ORG | 3 |
sa | CHEMICAL | 3 |
ross | PERSON | 3 |
respiratory syndrome | DISEASE | 3 |
removed | PERSON | 3 |
rna | ORG | 3 |
python | ORG | 3 |
por lo | PERSON | 3 |
phys rev | GPE | 3 |
peru | GPE | 3 |
posas | ORG | 3 |
ontario quebec | ORG | 3 |
coronavirus pneumonia | DISEASE | 3 |
nonequilibrium | CHEMICAL | 3 |
sra | ORG | 3 |
portugal | GPE | 3 |
scotland | GPE | 3 |
wuhan hubei province | GPE | 3 |
bats | TAXON | 3 |
slovakia | GPE | 3 |
app | ORG | 3 |
allergies | DISEASE | 3 |
alcohol | CHEMICAL | 3 |
al 2013 | PERSON | 3 |
acute respiratory syndrome coronavirus 2 sars cov | DISEASE | 3 |
zika | GPE | 3 |
al 2014 | PERSON | 3 |
watson | PERSON | 3 |
the new york times | ORG | 3 |
u r e | CHEMICAL | 3 |
transmission | GPE | 3 |
thieme | PERSON | 3 |
t00 | ORG | 3 |
washington dc | GPE | 3 |
icu | DISEASE | 2 |
hunan | GPE | 2 |
humans dynamics | ORG | 2 |
hubei province | GPE | 2 |
hu | PERSON | 2 |
ho 1975 | PERSON | 2 |
ho lubik | PERSON | 2 |
hilbert | ORG | 2 |
het00 | CHEMICAL | 2 |
ii | ORG | 2 |
heidelberger | PERSON | 2 |
hellewell | PERSON | 2 |
iedcr | ORG | 2 |
italy a | DISEASE | 2 |
ipc | ORG | 2 |
iqm | ORG | 2 |
iga | ORG | 2 |
josé enrique amaro | PERSON | 2 |
igg | ORG | 2 |
imperial college covid | ORG | 2 |
infectious disease | DISEASE | 2 |
ising | PERSON | 2 |
jh | PERSON | 2 |
jhu s | ORG | 2 |
jpras | GPE | 2 |
jens wittkowski raphael | PERSON | 2 |
harko lobo | ORG | 2 |
johns hopkins data model | ORG | 2 |
harris | PERSON | 2 |
gaps | CHEMICAL | 2 |
haque tasnima | PERSON | 2 |
gelman | PERSON | 2 |
finnoff ashworth | PERSON | 2 |
km | ORG | 2 |
fitzpatrick | GPE | 2 |
flaxman | TAXON | 2 |
friendster | ORG | 2 |
front | ORG | 2 |
fuks | PERSON | 2 |
fynbo | CHEMICAL | 2 |
fðtÞ | CHEMICAL | 2 |
g | ORG | 2 |
ga | ORG | 2 |
gauss newton | PERSON | 2 |
gilbert | PERSON | 2 |
hans fynbo | PERSON | 2 |
gillespie 1977 | PERSON | 2 |
ginzburg landau | PERSON | 2 |
giordano | GPE | 2 |
globalperc | ORG | 2 |
ORG | 2 | |
govt | PERSON | 2 |
gruhl | CHEMICAL | 2 |
gurney 1982 | PERSON | 2 |
hjb | ORG | 2 |
halton | PERSON | 2 |
hamsterster | PERSON | 2 |
hand therapy | ORG | 2 |
k n | ORG | 2 |
medsupplydrive | DISEASE | 2 |
kpp | ORG | 2 |
kandhway | PERSON | 2 |
mf | PERSON | 2 |
ml | PERSON | 2 |
mmr aa | CHEMICAL | 2 |
mainland china | LOC | 2 |
mauritius | GPE | 2 |
mckendric 9 | ORG | 2 |
mckendrick 2 | ORG | 2 |
measles periodicity | ORG | 2 |
n however | ORG | 2 |
melanoma | GPE | 2 |
michael nikolaou | PERSON | 2 |
microsoft | ORG | 2 |
micross | PERSON | 2 |
milroy | ORG | 2 |
mixedgreedy | ORG | 2 |
modellierung von beispielszenarien der sars cov 2 epidemie 2020 | PERSON | 2 |
moleculight | ORG | 2 |
monte carlo planck | PERSON | 2 |
moore | PERSON | 2 |
ms jasmine ho | PERSON | 2 |
n 0 n | ORG | 2 |
n 1 2 σ | ORG | 2 |
n 1 n 2 n γ | CHEMICAL | 2 |
n 2 | ORG | 2 |
n 2 10 7 and ran simulations | CHEMICAL | 2 |
n 2018 | ORG | 2 |
fermi dirac | ORG | 2 |
mcs | ORG | 2 |
mah | ORG | 2 |
lotka volterra lv | PERSON | 2 |
lawniczak 2001 | PERSON | 2 |
keloid | GPE | 2 |
kempe | GPE | 2 |
kilifi | TAXON | 2 |
king county | GPE | 2 |
kolmogorov | PERSON | 2 |
kryscio | PERSON | 2 |
loo | ORG | 2 |
lr | ORG | 2 |
lagebericht | PERSON | 2 |
lambertw | DISEASE | 2 |
lancet | ORG | 2 |
latin america | LOC | 2 |
lebesgue | ORG | 2 |
longstaff schwartz | ORG | 2 |
leclerc | ORG | 2 |
lemma 4 8 | CHEMICAL | 2 |
lemma 4 9 | CHEMICAL | 2 |
lessons | ORG | 2 |
li18 | CHEMICAL | 2 |
limited | PERSON | 2 |
linton | GPE | 2 |
lipschitz | PERSON | 2 |
lithuania | GPE | 2 |
log | PERSON | 2 |
lognormal | ORG | 2 |
lombardy italy | ORG | 2 |
finkenstädt 2006 | PERSON | 2 |
android | PERSON | 2 |
feng | PERSON | 2 |
clostridium difficile infection | DISEASE | 2 |
beispielszenarien | CHEMICAL | 2 |
belfin | GPE | 2 |
bickmann | PERSON | 2 |
biswas | PERSON | 2 |
brasche and bischof 2005 | ORG | 2 |
bulgaria | GPE | 2 |
c n | ORG | 2 |
ca sir | CHEMICAL | 2 |
cdf | ORG | 2 |
cdh | ORG | 2 |
cenew email hamster router condmat | ORG | 2 |
cmd | ORG | 2 |
cran | ORG | 2 |
csse | ORG | 2 |
camilli | ORG | 2 |
canniesburn | CHEMICAL | 2 |
capitalists | CHEMICAL | 2 |
cardoso | ORG | 2 |
carlo mc | PERSON | 2 |
carpenter | PERSON | 2 |
census | PERSON | 2 |
ch | CHEMICAL | 2 |
chad | GPE | 2 |
chen | PERSON | 2 |
chile | GPE | 2 |
classical | ORG | 2 |
clostridium | GPE | 2 |
beare | ORG | 2 |
bayesian | PERSON | 2 |
bayes | ORG | 2 |
ailing a | CHEMICAL | 2 |
n s 0 the | CHEMICAL | 2 |
321984 | CHEMICAL | 2 |
adam | ORG | 2 |
adm | ORG | 2 |
aids | DISEASE | 2 |
ame | CHEMICAL | 2 |
acad sci usa | PERSON | 2 |
accordingly | LOC | 2 |
acemoglu | ORG | 2 |
active brownian | ORG | 2 |
adam | PERSON | 2 |
additionaly | CHEMICAL | 2 |
ajustando | GPE | 2 |
bartlett | PERSON | 2 |
al sheikh 2013 | PERSON | 2 |
alonso | CHEMICAL | 2 |
andalucía | CHEMICAL | 2 |
andersson | PERSON | 2 |
ansatz | PERSON | 2 |
antonopoulos | CHEMICAL | 2 |
appendix a2 | ORG | 2 |
arxiv | GPE | 2 |
ardabili | PERSON | 2 |
athens | GPE | 2 |
autofluorescence | CHEMICAL | 2 |
bcg | ORG | 2 |
clostridium difficile | TAXON | 2 |
cosir | ORG | 2 |
falcone | CHEMICAL | 2 |
colizza | PERSON | 2 |
el segundo | GPE | 2 |
emmanuel clément | PERSON | 2 |
epidemic disease | DISEASE | 2 |
epidemic disease | DISEASE | 2 |
epistulae | PERSON | 2 |
eq 10 | PERSON | 2 |
eq 16 | PERSON | 2 |
eq 26 | ORG | 2 |
eq 39 | ORG | 2 |
eq 6 | PERSON | 2 |
eq 6a | PERSON | 2 |
eq a 2 | ORG | 2 |
eq a1 | GPE | 2 |
eq d 1b | PERSON | 2 |
eqs | PERSON | 2 |
eqs 26 | GPE | 2 |
eqs 4 | GPE | 2 |
erank | CHEMICAL | 2 |
esta | ORG | 2 |
este | PERSON | 2 |
euler bernoulli equation | ORG | 2 |
euler lagrange | ORG | 2 |
europe north america south america | LOC | 2 |
eβ | CHEMICAL | 2 |
fdm | ORG | 2 |
fe | ORG | 2 |
fis2017 85053 c2 1 p | CHEMICAL | 2 |
el geneidy 2009 | ORG | 2 |
earn | LOC | 2 |
ers1572626 | PERSON | 2 |
d 2 fits | CHEMICAL | 2 |
como | PERSON | 2 |
compression | ORG | 2 |
congo | GPE | 2 |
coronavirus epidemic | DISEASE | 2 |
coronavirus sars cov | DISEASE | 2 |
coronavirus sars cov 2 | ORG | 2 |
coronavirus deaths | DISEASE | 2 |
covid | ORG | 2 |
cvitanić | ORG | 2 |
czechia | PERSON | 2 |
d 2 | ORG | 2 |
d 2 2a c the d | CHEMICAL | 2 |
d i k | CHEMICAL | 2 |
download | CHEMICAL | 2 |
d and d | CHEMICAL | 2 |
daisy | ORG | 2 |
deaths | DISEASE | 2 |
diep | ORG | 2 |
darkdrape | ORG | 2 |
deb | ORG | 2 |
dengue chikungunya | ORG | 2 |
denote | PERSON | 2 |
dermatologists | ORG | 2 |
diamond princess | PERSON | 2 |
digg | PERSON | 2 |
dirac | GPE | 2 |
n i0 s0 | ORG | 2 |
gelman rubin | PERSON | 2 |
n s m h c | ORG | 2 |
fxuzd9qf | CHEMICAL | 2 |
host individuals | TAXON | 2 |
human behavior | DISEASE | 2 |
human coronaviruses | TAXON | 2 |
hydroxychloroquine | CHEMICAL | 2 |
individuals r | TAXON | 2 |
infected decreases | DISEASE | 2 |
infectious i | DISEASE | 2 |
infectious diseases a | DISEASE | 2 |
infectious infectious | DISEASE | 2 |
influenza a viral infections | DISEASE | 2 |
influenza dengue fever | ORG | 2 |
italy a | DISEASE | 2 |
la | PERSON | 2 |
las curvas | GPE | 2 |
los recuperados | GPE | 2 |
los valores | ORG | 2 |
malignancy | DISEASE | 2 |
man | TAXON | 2 |
marco | CHEMICAL | 2 |
meanfield | GPE | 2 |
medidas deben | ORG | 2 |
medio de duración de la | PERSON | 2 |
mosquito | TAXON | 2 |
mosquito borne | PERSON | 2 |
mouse | TAXON | 2 |
nanoparticles | CHEMICAL | 2 |
ncbi | CHEMICAL | 2 |
growths | DISEASE | 2 |
flap z | LOC | 2 |
birth death | DISEASE | 2 |
ferromagnetism | DISEASE | 2 |
cada enfermo | PERSON | 2 |
cantidad | CHEMICAL | 2 |
chickenpox | DISEASE | 2 |
chikungunya disease | DISEASE | 2 |
communicable disease | DISEASE | 2 |
como una | ORG | 2 |
coronavirus 2019 ncov spreading | DISEASE | 2 |
coronavirus coronavirus | TAXON | 2 |
coronavirus death | DISEASE | 2 |
coronavirus infections | DISEASE | 2 |
crash | DISEASE | 2 |
crece | CHEMICAL | 2 |
criticality | DISEASE | 2 |
ddl | CHEMICAL | 2 |
de duración de la | PERSON | 2 |
desolve | GPE | 2 |
decay | GPE | 2 |
decrece | CHEMICAL | 2 |
delays | DISEASE | 2 |
deuterium | CHEMICAL | 2 |
differential equation | DISEASE | 2 |
ea20o | DISEASE | 2 |
erosions | DISEASE | 2 |
escenario | DISEASE | 2 |
estimada para | PERSON | 2 |
europe | LOC | 2 |
fatigue | DISEASE | 2 |
necrosis | DISEASE | 2 |
new york | GPE | 2 |
norovirus | TAXON | 2 |
nucleotide | CHEMICAL | 2 |
the national institutes of health | ORG | 2 |
the national science foundation | ORG | 2 |
the people s republic of china | GPE | 2 |
the robert koch institute | ORG | 2 |
the south african national research foundation | ORG | 2 |
the spanish ministerio de economía y competitividad | ORG | 2 |
the u s | GPE | 2 |
the university of maryland | ORG | 2 |
the optimal vaccine administration | ORG | 2 |
tiempos mayores | PERSON | 2 |
tritium | CHEMICAL | 2 |
tumor | DISEASE | 2 |
unpredictability | DISEASE | 2 |
vertex | GPE | 2 |
viral infection | DISEASE | 2 |
wikipedia | DISEASE | 2 |
worm | TAXON | 2 |
y07w2f43 | CHEMICAL | 2 |
Ô z q | PERSON | 2 |
Γ k | CHEMICAL | 2 |
β optimal | PERSON | 2 |
β max | PERSON | 2 |
β γ µ | PERSON | 2 |
β δ | PERSON | 2 |
β σ | PERSON | 2 |
n s t i t r t | CHEMICAL | 2 |
Ω 1 | PERSON | 2 |
the ministry of health and family welfare | ORG | 2 |
the laplace adomian decomposition | ORG | 2 |
the johns hopkins data model | ORG | 2 |
qpcrhttps | PERSON | 2 |
oracle | DISEASE | 2 |
organisms | TAXON | 2 |
pandemic disease | DISEASE | 2 |
panic | DISEASE | 2 |
para tiempos | PERSON | 2 |
permiten | CHEMICAL | 2 |
pipeline | CHEMICAL | 2 |
plants | TAXON | 2 |
porphyrins | CHEMICAL | 2 |
predators | TAXON | 2 |
primary lymphedema | DISEASE | 2 |
propiedad | CHEMICAL | 2 |
que las | PERSON | 2 |
the fermi dirac distribution function | ORG | 2 |
respiratory illness | DISEASE | 2 |
respiratory infections | DISEASE | 2 |
respiratory syndrome mers | DISEASE | 2 |
rhesus macaques | TAXON | 2 |
s max | PERSON | 2 |
skin lesions | DISEASE | 2 |
susceptibleinfected | CHEMICAL | 2 |
the american society of plastic surgeons | ORG | 2 |
the city of los angeles | GPE | 2 |
the confirmed infectious | ORG | 2 |
the coronavirus study group | ORG | 2 |
the european centre for disease prevention | ORG | 2 |
boils | DISEASE | 2 |
the united states of america | GPE | 2 |
bastante | DISEASE | 2 |
parece | PERSON | 2 |
pesco | GPE | 2 |
plague | GPE | 2 |
point c | ORG | 2 |
poisson gaussian fermi | PERSON | 2 |
price | ORG | 2 |
proc natl | PERSON | 2 |
protezione | CHEMICAL | 2 |
provinces | TAXON | 2 |
pubmed | ORG | 2 |
pðkÞ | CHEMICAL | 2 |
pðqÞ | CHEMICAL | 2 |
q j | PERSON | 2 |
quarantined siqrd | PERSON | 2 |
rk | CHEMICAL | 2 |
rvt | ORG | 2 |
ramakrishnan yussouff | GPE | 2 |
re | PERSON | 2 |
remark 1 | PERSON | 2 |
remark 4 | PERSON | 2 |
remark 4 4 notice | ORG | 2 |
respiratory syndrome coronavirus mers | DISEASE | 2 |
ro ro | GPE | 2 |
robert koch institut | PERSON | 2 |
router | ORG | 2 |
s0 i0 r n | ORG | 2 |
s14 | PERSON | 2 |
sars cov | ORG | 2 |
particular | ORG | 2 |
paraíba | ORG | 2 |
sis diseases | DISEASE | 2 |
para que | PERSON | 2 |
n m | ORG | 2 |
n i | ORG | 2 |
avian coronaviruses | TAXON | 2 |
n m n m | ORG | 2 |
n  | ORG | 2 |
n β n | ORG | 2 |
na | CHEMICAL | 2 |
nice | ORG | 2 |
no | CHEMICAL | 2 |
nadini | PERSON | 2 |
naming the coronavirus disease covid | DISEASE | 2 |
neiderud | PERSON | 2 |
netherlands | GPE | 2 |
new york state report | ORG | 2 |
new york times | GPE | 2 |
newman | ORG | 2 |
newman watts small | DISEASE | 2 |
nisbet | GPE | 2 |
norovirus outbreaks consensus | TAXON | 2 |
note | LOC | 2 |
nρ | PERSON | 2 |
ocps | CHEMICAL | 2 |
oic | DISEASE | 2 |
ortiz prado et al 2020 | PERSON | 2 |
otunuga | CHEMICAL | 2 |
oxford | ORG | 2 |
pcr | ORG | 2 |
sis disease | DISEASE | 2 |
neilan | GPE | 2 |
srs | ORG | 2 |
west africa | GPE | 2 |
vista | ORG | 2 |
voterank | ORG | 2 |
wwi | ORG | 2 |
wales | GPE | 2 |
walker | PERSON | 2 |
wall street journal | ORG | 2 |
walsh | PERSON | 2 |
warin | PERSON | 2 |
washington | GPE | 2 |
watsons 1980 | ORG | 2 |
watts | LOC | 2 |
weinstein | PERSON | 2 |
white et al 2007 | PERSON | 2 |
veneto | PERSON | 2 |
woods saxon | ORG | 2 |
working group | ORG | 2 |
working group leclerc | ORG | 2 |
world health organization | ORG | 2 |
youtube tm | PERSON | 2 |
zhou | PERSON | 2 |
zika virus outbreaks | TAXON | 2 |
a susceptible exposed infectious | GPE | 2 |
anxiety | DISEASE | 2 |
stat | ORG | 2 |
al 2016 | PERSON | 2 |
active infection | DISEASE | 2 |
vespignani 2008 | CHEMICAL | 2 |
worldometer | ORG | 2 |
varicella | GPE | 2 |
strategies | PERSON | 2 |
scinet | ORG | 2 |
scalia tomba | PERSON | 2 |
scipy | GPE | 2 |
val borbera | PERSON | 2 |
sannikov | PERSON | 2 |
sec ii | CHEMICAL | 2 |
sec iii | PERSON | 2 |
section iv | ORG | 2 |
shinydashboard | ORG | 2 |
snoeck | PERSON | 2 |
solidification | DISEASE | 2 |
special issue on challenges in modelling infectious disease dynamics modeling | ORG | 2 |
squillante | ORG | 2 |
section | ORG | 2 |
thucydes | PERSON | 2 |
usc | GPE | 2 |
susceptibles infected | PERSON | 2 |
turinici | GPE | 2 |
tornatore | CHEMICAL | 2 |
u | CHEMICAL | 2 |
u s a | CHEMICAL | 2 |
the basic reproduction number | ORG | 2 |
telle | GPE | 2 |
são paulo | GPE | 2 |
systematic | LOC | 2 |
united states | GPE | 2 |
l nn w β γ δ | PERSON | 1 |
l d 2 that | CHEMICAL | 1 |
l bfgs b fortran subroutines | CHEMICAL | 1 |
l 2 l 2 l 2 l 2 with size l 10 and periodic boundary conditions we have solved the equations of the sir | CHEMICAL | 1 |
l 2 | LOC | 1 |
l 1 l | CHEMICAL | 1 |
kurtz | PERSON | 1 |
kuri 61 | PERSON | 1 |
ko 82 | PERSON | 1 |
korteweg de vries | PERSON | 1 |
kuehn | PERSON | 1 |
kronmal | GPE | 1 |
krapivsky | PERSON | 1 |
kotz | ORG | 1 |
korobeinikov | PERSON | 1 |
konno | PERSON | 1 |
kollar | TAXON | 1 |
koji | GPE | 1 |
l w β | PERSON | 1 |
knowledge epidemics and population dynamics models for describing idea diffusion models of science dynamics encounters between complexity theory and information sciences introduction to percolation theory | ORG | 1 |
koenker 2017a | PERSON | 1 |
koczy | CHEMICAL | 1 |
l s of nodes | CHEMICAL | 1 |
lachiany menachem | PERSON | 1 |
la county census | ORG | 1 |
lagartococha callarú | ORG | 1 |
latent | ORG | 1 |
lat | PERSON | 1 |
las curvas | GPE | 1 |
kleiber | PERSON | 1 |
larvae | GPE | 1 |
larson | PERSON | 1 |
laplace adomian | ORG | 1 |
lancet predicting | ORG | 1 |
lancet infectious diseases a | DISEASE | 1 |
lagrangian the | PERSON | 1 |
lagartochocha | LOC | 1 |
la county | ORG | 1 |
laffont | PERSON | 1 |
lack | PERSON | 1 |
lachiany | CHEMICAL | 1 |
la extrapolación | CHEMICAL | 1 |
lv dynamics | ORG | 1 |
lpe sg | CHEMICAL | 1 |
loess | ORG | 1 |
lmt | ORG | 1 |
lhr london | ORG | 1 |
le | GPE | 1 |
knowing | PERSON | 1 |
junling | CHEMICAL | 1 |
kinetic theory | ORG | 1 |
johns hopkins csse epidemiological | ORG | 1 |
jowett | PERSON | 1 |
journal of environmental and public health | ORG | 1 |
journal | ORG | 1 |
josé | CHEMICAL | 1 |
jordan kyrgyzstan | PERSON | 1 |
jones | PERSON | 1 |
johns hopkins university s center for systems science and engineering csse | ORG | 1 |
johns hopkins resource center | ORG | 1 |
johns hopkins cornonavirus resource center | ORG | 1 |
johns hopkins center for systems science and engineering jhu | ORG | 1 |
john r butts carter | PERSON | 1 |
jumping man flap | PERSON | 1 |
john m | PERSON | 1 |
john hopkins dashboard | ORG | 1 |
jo | PERSON | 1 |
jing | GPE | 1 |
jin et al 2013 | PERSON | 1 |
jin dougherty saraf cao ramakrishnan 2013 | ORG | 1 |
jiang yu ji | PERSON | 1 |
lauer | PERSON | 1 |
ji et al 23 | GPE | 1 |
jiang xiaoqian | PERSON | 1 |
julian jeggle | PERSON | 1 |
k 4 | ORG | 1 |
kinetic | PERSON | 1 |
kcut | PERSON | 1 |
killers | CHEMICAL | 1 |
kiamari mehrdad ramachandran | PERSON | 1 |
kharroubi lim | PERSON | 1 |
key node ranking | PERSON | 1 |
kevrekidis 44 | ORG | 1 |
kesten mckay | PERSON | 1 |
kermackmckendrick | ORG | 1 |
kent et al 3 | PERSON | 1 |
kent | ORG | 1 |
keeling rohani | ORG | 1 |
katsoufis | CHEMICAL | 1 |
k n µ k σ 2 k | CHEMICAL | 1 |
katriel 2013 | PERSON | 1 |
karney 2013 | PERSON | 1 |
karnataka | GPE | 1 |
karmisholt | PERSON | 1 |
kahneman | GPE | 1 |
kr08 note | ORG | 1 |
kpp neg | ORG | 1 |
kkt | ORG | 1 |
kap | ORG | 1 |
k note | ORG | 1 |
lattice models monte carlo simulation | ORG | 1 |
lopez martens david | PERSON | 1 |
lauer et al | PERSON | 1 |
law | PERSON | 1 |
m x m t | PERSON | 1 |
m j n j 0 | PERSON | 1 |
m infected fatality rate ifr increase | ORG | 1 |
m furukawa | PERSON | 1 |
lü et al | PERSON | 1 |
lü | DISEASE | 1 |
lymphedema | ORG | 1 |
lurie et al 2020 | PERSON | 1 |
lukáš poláček | PERSON | 1 |
luego después | DISEASE | 1 |
louzoun yoram | PERSON | 1 |
los valores | GPE | 1 |
los tiempos | PERSON | 1 |
los parámetros | LOC | 1 |
los datos | GPE | 1 |
los angeles county | GPE | 1 |
los angeles | GPE | 1 |
los | GPE | 1 |
lorenzo rizzo | PERSON | 1 |
lopez martens | PERSON | 1 |
lopez | PERSON | 1 |
long | PERSON | 1 |
lombardy data | ORG | 1 |
mars | CHEMICAL | 1 |
matlab identifiabilityanalysis | GPE | 1 |
mcmc coda convergence | PERSON | 1 |
madagascar infodemiological | ORG | 1 |
maier | ORG | 1 |
ji 2020 | PERSON | 1 |
mahmudur ahmed asif | PERSON | 1 |
mahmud | ORG | 1 |
mahmoudi | PERSON | 1 |
maheshwari h shetty s bannur n merugu s | PERSON | 1 |
maheshwari 43 | PERSON | 1 |
maharashtra india | ORG | 1 |
maharashtra 10 | GPE | 1 |
magal | CHEMICAL | 1 |
macroeconomic dynamics | ORG | 1 |
mcmc methods | ORG | 1 |
machine learning models | ORG | 1 |
msle | ORG | 1 |
mseir | ORG | 1 |
mse 54 04 | ORG | 1 |
mpl ica | ORG | 1 |
mpl | ORG | 1 |
mohfw coronavirus | PERSON | 1 |
mit lincoln laboratory | ORG | 1 |
mia | CHEMICAL | 1 |
mh mh | CHEMICAL | 1 |
lombardia veneto | PERSON | 1 |
lognormal | PERSON | 1 |
logistic growth models | ORG | 1 |
lemma 9 | CHEMICAL | 1 |
lewis | PERSON | 1 |
levinson | ORG | 1 |
levin et al 2006 | PERSON | 1 |
levenberg | ORG | 1 |
lesniewski andrew | ORG | 1 |
lerman | PERSON | 1 |
lenton | PERSON | 1 |
length | GPE | 1 |
lemmas 4 | ORG | 1 |
lemma 9 let g | CHEMICAL | 1 |
lemma 6 1 for | CHEMICAL | 1 |
liam gaffney | PERSON | 1 |
lemma 6 1 eq | CHEMICAL | 1 |
lekone | CHEMICAL | 1 |
lefèvre 67 | PERSON | 1 |
lefèvre | CHEMICAL | 1 |
left chloropleth | GPE | 1 |
lee duan shin zhu miao | PERSON | 1 |
lee 108 | PERSON | 1 |
lebanon | GPE | 1 |
learning and machine learning | DISEASE | 1 |
learning | GPE | 1 |
lewnard lo | PERSON | 1 |
liangwei chen xiao chen | PERSON | 1 |
logistic growth | ORG | 1 |
lisboa fundação calouste gulbenkian | PERSON | 1 |
lockdowns coronavirus | PERSON | 1 |
loci | PERSON | 1 |
llera | ORG | 1 |
liu et al liu | PERSON | 1 |
liu y et al 2020 | PERSON | 1 |
liu laura moon hyungsik | PERSON | 1 |
liu 2020 | PERSON | 1 |
liu 2009 | PERSON | 1 |
listing 8 | PERSON | 1 |
listeriosis | DISEASE | 1 |
lippi 6 | PERSON | 1 |
libai muller | PERSON | 1 |
lippi | PERSON | 1 |
linton 2020 | PERSON | 1 |
linear regression | ORG | 1 |
linear | ORG | 1 |
lin et al 2020 | PERSON | 1 |
lim | PERSON | 1 |
likert scale 1 | PERSON | 1 |
likelihood | ORG | 1 |
libotte gustavo barbosa lobato fran | ORG | 1 |
liberia sierra leone | PERSON | 1 |
ji el al 67 | GPE | 1 |
hong hyokyoung g li yi | PERSON | 1 |
jeyaseelan l title forecasting | CHEMICAL | 1 |
humanity | ORG | 1 |
heteroscedasticity | ORG | 1 |
herndon | PERSON | 1 |
henry 2020 | PERSON | 1 |
henderson | GPE | 1 |
heffernan | GPE | 1 |
heesterbeek klinkenberg | PERSON | 1 |
heaviside | ORG | 1 |
heathrow lhr | PERSON | 1 |
healthcare facilities | ORG | 1 |
health and safety executive | ORG | 1 |
health system | ORG | 1 |
health social care workers | ORG | 1 |
health organization coronavirus | ORG | 1 |
health education england | ORG | 1 |
head neck tumours | DISEASE | 1 |
head neck | ORG | 1 |
hazem y natarajan | PERSON | 1 |
hawkes | ORG | 1 |
hatchimonji swendiman | PERSON | 1 |
hasegawa takehisa | PERSON | 1 |
hasani tavakkoli | PERSON | 1 |
hasab | PERSON | 1 |
harvesting | ORG | 1 |
hidden | GPE | 1 |
hill | ORG | 1 |
hill levin | PERSON | 1 |
hospital | ORG | 1 |
hubei confbnd | PERSON | 1 |
hubei italy | ORG | 1 |
huang tongtong chu yan shams | PERSON | 1 |
huang peng yin | PERSON | 1 |
hua chen | PERSON | 1 |
hu et al 63 | PERSON | 1 |
hu ren | PERSON | 1 |
hsu et al 2003 | PERSON | 1 |
hsu | PERSON | 1 |
hospital ppe | LOC | 1 |
horn | ORG | 1 |
hinman | PERSON | 1 |
hong kong pathogen | GPE | 1 |
malaysia arifin et al 2020 mahmud | ORG | 1 |
holmström | ORG | 1 |
holmes backward | PERSON | 1 |
holmes | PERSON | 1 |
holm jeanne krishnamachari bhaskar | PERSON | 1 |
hollywood | GPE | 1 |
ho 1975 biegler | PERSON | 1 |
hirschowitz et al 2 | PERSON | 1 |
hinman 2012 simons | DISEASE | 1 |
harvester | PERSON | 1 |
harish c s | GPE | 1 |
haremos | ORG | 1 |
griffiths | PERSON | 1 |
guo chungu yang | PERSON | 1 |
guo | PERSON | 1 |
guinea liberia | GPE | 1 |
guille | PERSON | 1 |
guardian coronavirus | PERSON | 1 |
guan | GPE | 1 |
gruhl guha liben nowell | PERSON | 1 |
growthmodels | CHEMICAL | 1 |
group 1 | ORG | 1 |
grigorieva khailov | PERSON | 1 |
greenstone | CHEMICAL | 1 |
gutenberg | PERSON | 1 |
greenshtein | PERSON | 1 |
green yellow orange | PERSON | 1 |
green | PERSON | 1 |
greedy | PERSON | 1 |
greece | GPE | 1 |
greater houston | LOC | 1 |
greater glasgow | GPE | 1 |
gray greenhalgh hu mao | PERSON | 1 |
graphs | ORG | 1 |
graphpad | ORG | 1 |
gupta | PERSON | 1 |
gutin | PERSON | 1 |
hare jeffrey | PERSON | 1 |
hiv ebola | TAXON | 1 |
hanson 7 zeckhauser | PERSON | 1 |
hand injuries | ORG | 1 |
hamster | ORG | 1 |
hamilton jacob bellman | PERSON | 1 |
haluk | PERSON | 1 |
hall | PERSON | 1 |
hakim | PERSON | 1 |
hst | ORG | 1 |
hmf theory | ORG | 1 |
hmf c ¼ | ORG | 1 |
hiv a | DISEASE | 1 |
gábor | CHEMICAL | 1 |
hiv | TAXON | 1 |
hal | CHEMICAL | 1 |
h1n1v | TAXON | 1 |
h r d | CHEMICAL | 1 |
h n s c | ORG | 1 |
h h x u y z | PERSON | 1 |
h 1 h 1 n i t and 39 the corresponding r 2 coefficient | CHEMICAL | 1 |
göttingen | GPE | 1 |
génois | PERSON | 1 |
gábor stépán | PERSON | 1 |
human coronavirus | TAXON | 1 |
humans data | ORG | 1 |
jewell et al 2020 | PERSON | 1 |
humans and animals human mobility | ORG | 1 |
isingmodel | PERSON | 1 |
ireland safegraph convex optimization exponential | ORG | 1 |
ireland | GPE | 1 |
iraq | GPE | 1 |
iot | CHEMICAL | 1 |
inverse wishart | ORG | 1 |
inverse problem for coefficient identification | ORG | 1 |
inverse gamma | ORG | 1 |
inverse | ORG | 1 |
intervals | TAXON | 1 |
international journal of infectious | ORG | 1 |
interface foundation | ORG | 1 |
interepidemic intervals | ORG | 1 |
intensive care units | ORG | 1 |
intensive care unit | ORG | 1 |
intensive care | ORG | 1 |
integrating eq 13a | PERSON | 1 |
institute of health policy | ORG | 1 |
institute of epidemiology disease control and research iedcr bangladesh | ORG | 1 |
institute for health metrics and | ORG | 1 |
inset | PERSON | 1 |
injury | DISEASE | 1 |
information | ORG | 1 |
islam m z | ORG | 1 |
istanbul | GPE | 1 |
itakura saito | PERSON | 1 |
j h university | ORG | 1 |
jeremy rodrigues | PERSON | 1 |
jensen s | PERSON | 1 |
jeffrey a | PERSON | 1 |
japan singapore | ORG | 1 |
jamaica | GPE | 1 |
jacobin | GPE | 1 |
jhu ccesgis | ORG | 1 |
jhu | ORG | 1 |
jfk | PERSON | 1 |
jcrw | PERSON | 1 |
j denote | ORG | 1 |
italy covid | DISEASE | 1 |
its significance to epidemic prevention | ORG | 1 |
itrend total plot growth rate | ORG | 1 |
italy and usa | GPE | 1 |
italy understanding | ORG | 1 |
italy spain | GPE | 1 |
italy mathematical | ORG | 1 |
italy hubei | GPE | 1 |
italy germany | GPE | 1 |
italy europe | GPE | 1 |
italy centers for disease control and prevention home covid | ORG | 1 |
influential nodes identification | ORG | 1 |
influencing | GPE | 1 |
infectious diseases | DISEASE | 1 |
igf | ORG | 1 |
ilaria capua | ORG | 1 |
ifguis ousama el ghozlani | PERSON | 1 |
ienca | PERSON | 1 |
iceland | GPE | 1 |
ian cooper | PERSON | 1 |
isp | ORG | 1 |
iii observer | ORG | 1 |
iii methodology compartmental | ORG | 1 |
iii | ORG | 1 |
ii ii | CHEMICAL | 1 |
ig | ORG | 1 |
impacts | ORG | 1 |
iedcr 3 | ORG | 1 |
icedr 3 | ORG | 1 |
ic needless | ORG | 1 |
ic | ORG | 1 |
hölder | ORG | 1 |
hébert dufresne et al 2020 | PERSON | 1 |
hypertrophic | PERSON | 1 |
hyman | PERSON | 1 |
huppert | PERSON | 1 |
hunan modeling | PERSON | 1 |
immune | LOC | 1 |
imperial college covid 19 response team | ORG | 1 |
infectious | GPE | 1 |
individual reaction and governmental action hybrid approach for | ORG | 1 |
infections | DISEASE | 1 |
infection dynamics | ORG | 1 |
infected fatality | DISEASE | 1 |
infected deaths | DISEASE | 1 |
inf sci technol | PERSON | 1 |
inequality | DISEASE | 1 |
indoor | ORG | 1 |
indonesia | GPE | 1 |
indocyanine green | CHEMICAL | 1 |
indocyanine | ORG | 1 |
indigenous people articulation regional organization of indigenous peoples of the east | ORG | 1 |
imperial college covid 19 response team 30 | ORG | 1 |
india mathematical | ORG | 1 |
india emerging infectious diseases among indigenous peoples genetic | ORG | 1 |
india australia usa | ORG | 1 |
increase | ORG | 1 |
incentive | ORG | 1 |
inaba | GPE | 1 |
implications for sir models | ORG | 1 |
imperialist | DISEASE | 1 |
imperial college london | ORG | 1 |
imperial college covid19 europe | ORG | 1 |
malavika b | PERSON | 1 |
n 1 n 2 n 3 if n 1 n 2 n γ | CHEMICAL | 1 |
malta | GPE | 1 |
national health commission of | ORG | 1 |
osler | ORG | 1 |
org20a org20b | CHEMICAL | 1 |
orenstein | ORG | 1 |
option c | ORG | 1 |
option b variational | ORG | 1 |
option b epistemic | ORG | 1 |
option a gradient | ORG | 1 |
optimum | ORG | 1 |
operative | ORG | 1 |
ontario italy uruguay | ORG | 1 |
ontario canada italy | ORG | 1 |
online coronavirus covid19 | PERSON | 1 |
online | PERSON | 1 |
on data driven management of the covid 19 outbreak | ORG | 1 |
okumura | ORG | 1 |
off | CHEMICAL | 1 |
oceania | LOC | 1 |
observabilitytest | ORG | 1 |
observability of compartmental models | ORG | 1 |
obadia | GPE | 1 |
overall summary statistical | ORG | 1 |
orig | ORG | 1 |
ode sir | DISEASE | 1 |
osterholm | PERSON | 1 |
ottolino perry et al 4 | PERSON | 1 |
our examples | ORG | 1 |
pmp | CHEMICAL | 1 |
pandemic influenza h1n1 2009 | DISEASE | 1 |
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pan 47 | GPE | 1 |
palo alto | GPE | 1 |
palladino andrea nardelli vincenzo | ORG | 1 |
palau | GPE | 1 |
padé spir | ORG | 1 |
psap | ORG | 1 |
prasad j | PERSON | 1 |
pos | ORG | 1 |
phe health protection scotland public health agency public health wales | ORG | 1 |
output | LOC | 1 |
phe covid | CHEMICAL | 1 |
pged 2 | ORG | 1 |
pek miami mia | ORG | 1 |
pdes murray et al | PERSON | 1 |
pdes | ORG | 1 |
pdc | GPE | 1 |
pbs news | ORG | 1 |
parametro | ORG | 1 |
ovid | PERSON | 1 |
overall selecting θ ed | PERSON | 1 |
o m n | ORG | 1 |
nπz | ORG | 1 |
nåsell 78 79 | ORG | 1 |
neural network | ORG | 1 |
new york city | GPE | 1 |
new world | ORG | 1 |
new multi | ORG | 1 |
new jersey 40 | GPE | 1 |
new delhi ministry of health and family welfare government | ORG | 1 |
new approaches | GPE | 1 |
neves | GPE | 1 |
neuroimaging a systematic literature review dynamic simulation and optimization with inequality path constraints predicting unobserved exposures | ORG | 1 |
neural networks nn | ORG | 1 |
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neural information processing systems | ORG | 1 |
newgreedy | ORG | 1 |
neufeld | PERSON | 1 |
netlogo | ORG | 1 |
netlogo | ORG | 1 |
nest | ORG | 1 |
nes | DISEASE | 1 |
nentries | GPE | 1 |
nekovee | ORG | 1 |
ncol | ORG | 1 |
nbody | LOC | 1 |
naveira | CHEMICAL | 1 |
new york ny | LOC | 1 |
ng | CHEMICAL | 1 |
nvar | ORG | 1 |
nonequilibrium phase transitions | ORG | 1 |
nutz notice | ORG | 1 |
numpy | GPE | 1 |
nullifying spurious data | ORG | 1 |
nr | CHEMICAL | 1 |
notredame | CHEMICAL | 1 |
note n | ORG | 1 |
note thable | ORG | 1 |
northern italy evolution | LOC | 1 |
north london | LOC | 1 |
norovirus | TAXON | 1 |
none none dear sir diver | ORG | 1 |
nicholas lesniewski | PERSON | 1 |
none none | PERSON | 1 |
none letter | ORG | 1 |
nodes | CHEMICAL | 1 |
node 1 | LOC | 1 |
node | ORG | 1 |
no u turn sampler | ORG | 1 |
nimp | ORG | 1 |
nilanjan chatterjee | PERSON | 1 |
nil all | ORG | 1 |
nil | PERSON | 1 |
panels | PERSON | 1 |
papa giovanni xxiii | PERSON | 1 |
para | PERSON | 1 |
preisach | PERSON | 1 |
protopapas pavlos brambilla marco | PERSON | 1 |
proper | GPE | 1 |
proof similarly | ORG | 1 |
proof | PERSON | 1 |
prof jeff kantor | PERSON | 1 |
prof emeritus | PERSON | 1 |
priyanka nandi | ORG | 1 |
prion diseases | DISEASE | 1 |
princeton university | ORG | 1 |
prevalence | ORG | 1 |
predictability | ORG | 1 |
province state | GPE | 1 |
predication of pandemic covid 19 | ORG | 1 |
prado et al 2020 | PERSON | 1 |
prado | GPE | 1 |
practical | GPE | 1 |
posteriormente el mismo modelo | PERSON | 1 |
porfiri maurizio | PERSON | 1 |
por | PERSON | 1 |
population dynamics stability and oscillations in delay differential equations of population dynamics | ORG | 1 |
pontryagin | ORG | 1 |
ponto gutta | ORG | 1 |
province city | GPE | 1 |
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ponce marcelo sandhel amit | ORG | 1 |
python klinger | GPE | 1 |
grant no w911nf | PERSON | 1 |
quasi continuum | PERSON | 1 |
quarantine | PERSON | 1 |
qin | PERSON | 1 |
qatar | GPE | 1 |
qsir | PERSON | 1 |
qaly daly quality and disability adjusted life year | ORG | 1 |
qaly | ORG | 1 |
q eff | PERSON | 1 |
pðw jd | PERSON | 1 |
python 9 data covid 19 | ORG | 1 |
province state ontario | PERSON | 1 |
put δ | LOC | 1 |
put e | CHEMICAL | 1 |
purkayastha | CHEMICAL | 1 |
puerto rico | GPE | 1 |
puede | GPE | 1 |
pubmed https www ncbi nlm nih | PERSON | 1 |
pubmed data element field descriptions | ORG | 1 |
pseudomonas aeruginosa | DISEASE | 1 |
pseudomonas | GPE | 1 |
prussia | PERSON | 1 |
ponto | CHEMICAL | 1 |
points c and c | ORG | 1 |
para aclarar | PERSON | 1 |
paulo | CHEMICAL | 1 |
periodicity | ORG | 1 |
period | CHEMICAL | 1 |
percolation | LOC | 1 |
perceptron mlp | PERSON | 1 |
pensamos que | PERSON | 1 |
peng | PERSON | 1 |
pearson | PERSON | 1 |
pavlos protopapas | ORG | 1 |
pavlos brambilla marco | CHEMICAL | 1 |
pavia | GPE | 1 |
pastor satorras | ORG | 1 |
perra | CHEMICAL | 1 |
pascal | PERSON | 1 |
pasado | PERSON | 1 |
parmet | CHEMICAL | 1 |
park choi | PERSON | 1 |
paris | GPE | 1 |
pareto 1896 | ORG | 1 |
parasites vectors predicting | ORG | 1 |
parasites vectors | TAXON | 1 |
parameters note | ORG | 1 |
parameter | PERSON | 1 |
pernambuco | PERSON | 1 |
perra et al 2012 | PERSON | 1 |
poincaré | CHEMICAL | 1 |
physical processes for studying the spread of civid 19 epidemic polynomial | ORG | 1 |
plummer | PERSON | 1 |
plastics | LOC | 1 |
plastic surgery registrars | ORG | 1 |
plastic surgery nhs trust | ORG | 1 |
plastic surgery department | ORG | 1 |
plastic surgery | ORG | 1 |
piunovskiy | PERSON | 1 |
physics | GPE | 1 |
physically β | PERSON | 1 |
physically | GPE | 1 |
physical meaning of the reproduction number r | ORG | 1 |
personal protective equipment | ORG | 1 |
physreve | DISEASE | 1 |
phys d | PERSON | 1 |
philadelphia | GPE | 1 |
phase iv | GPE | 1 |
pharma north | ORG | 1 |
petrosillo | ORG | 1 |
peter x k | PERSON | 1 |
pescarini s et al | PERSON | 1 |
pescarini | PERSON | 1 |
pertussis | DISEASE | 1 |
navajo | GPE | 1 |
national | ORG | 1 |
maltezos s | ORG | 1 |
narayanam | ORG | 1 |
modelers | CHEMICAL | 1 |
model structure | PERSON | 1 |
model algorithms | PERSON | 1 |
model 6 | PERSON | 1 |
mod | PERSON | 1 |
mitarai o yanagi n title | CHEMICAL | 1 |
mislove adams gummadi 2008 | CHEMICAL | 1 |
miriam beller | PERSON | 1 |
ministry of health family welfare 2020 government | ORG | 1 |
minimal | PERSON | 1 |
mini | GPE | 1 |
miller | ORG | 1 |
mikosch 2006 | CHEMICAL | 1 |
middle east respiratory syndrome coronavirus | LOC | 1 |
middle east respiratory syndrome | LOC | 1 |
micross geitslich | PERSON | 1 |
mexico 1 | GPE | 1 |
mettu | CHEMICAL | 1 |
metropolis hastings mh | PERSON | 1 |
metapopulation biology ecology genetics and evolution matrix analysis | ORG | 1 |
mesri gundoshmian | PERSON | 1 |
meso | PERSON | 1 |
mendelian disorders | DISEASE | 1 |
modeling infectious diseases | ORG | 1 |
modeling institute for health metrics and evaluation | ORG | 1 |
modeling and predictions | ORG | 1 |
moreno et al 8 | PERSON | 1 |
muldowney 1995 | ORG | 1 |
mukhamadiarov ruslan | PERSON | 1 |
ms gillian higgins | PERSON | 1 |
mrs eleanor robertson | PERSON | 1 |
movement control order | ORG | 1 |
mouth disease | DISEASE | 1 |
moutcine | CHEMICAL | 1 |
mosquito borne disease | PERSON | 1 |
mosquito | TAXON | 1 |
mori zwanzig | PERSON | 1 |
moreno et al | PERSON | 1 |
modelling mathematical methods and scientific computation | ORG | 1 |
moon | TAXON | 1 |
montes de title modelos sir modificados para la evoluci on | CHEMICAL | 1 |
monte | GPE | 1 |
molnar tamas | PERSON | 1 |
moleculight | PERSON | 1 |
moleculight toronto canada | ORG | 1 |
mohamed ammou fouzia | PERSON | 1 |
modern numerical analysis theory methods and practice chapman hall crc numerical analysis | ORG | 1 |
models of seirs epidemic | ORG | 1 |
modelos | ORG | 1 |
memory | PERSON | 1 |
medsupplydriveuk | PERSON | 1 |
medicine | GPE | 1 |
martello | ORG | 1 |
mathematical models | ORG | 1 |
mathematical epidemiology of infectious diseases model building transmission | ORG | 1 |
mathematical epidemiology of infectious diseases model building analysis and interpretation analysis | ORG | 1 |
mathematical epidemic dynamics modelling date 2020 | ORG | 1 |
mathworld a wolfram web resource | ORG | 1 |
math model doi | PERSON | 1 |
mastrolia 66 | PERSON | 1 |
massaro | GPE | 1 |
martin lof | PERSON | 1 |
martimort 68 bolton | ORG | 1 |
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mathematical physics | ORG | 1 |
marinov tchavdar | PERSON | 1 |
marginal | ORG | 1 |
marco saldarriaga | PERSON | 1 |
marco | CHEMICAL | 1 |
manual | PERSON | 1 |
mandal et al 20 | PERSON | 1 |
managing counterparty | ORG | 1 |
man kwong | PERSON | 1 |
mammalian | TAXON | 1 |
maltezou | CHEMICAL | 1 |
mathematical models to capture the | ORG | 1 |
mathematical structures of epidemic systems | ORG | 1 |
medical basis for increased susceptibility of covid 19 | ORG | 1 |
mckendrick 64 | ORG | 1 |
med lausanne | PERSON | 1 |
mechanistic | LOC | 1 |
measles outbreaks | ORG | 1 |
mev | PERSON | 1 |
md anwar | PERSON | 1 |
mckenrick 12 | ORG | 1 |
mckendrick s compartmental | ORG | 1 |
mckendrick s | ORG | 1 |
mckendrick 74 | ORG | 1 |
mckendrick 64 mckendrick 75 | ORG | 1 |
mckendrick 4 definition 1 | ORG | 1 |
matthes 2020 | PERSON | 1 |
mckendrick 22 23 24 | ORG | 1 |
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mckendrick 1925 | ORG | 1 |
mckendrick 17 | ORG | 1 |
mckendrick 1 | ORG | 1 |
mckane | ORG | 1 |
mcgeer 2003 | ORG | 1 |
may using | ORG | 1 |
maximum principle | PERSON | 1 |
max | PERSON | 1 |
muller 2001 | DISEASE | 1 |
mulligan | PERSON | 1 |
munich muc | PERSON | 1 |
n dt one gets the system the beauty of | CHEMICAL | 1 |
n of transitions | ORG | 1 |
n nodes | CHEMICAL | 1 |
n n r n | ORG | 1 |
n n | ORG | 1 |
n m mn n n | CHEMICAL | 1 |
n m mn | ORG | 1 |
n k d p | CHEMICAL | 1 |
n i ℜ i 1 2 3 | ORG | 1 |
n elem 2 unknown parameters since the control variable | CHEMICAL | 1 |
n each eq 7 | CHEMICAL | 1 |
n agents | CHEMICAL | 1 |
n t s t i t r t | CHEMICAL | 1 |
n thus when n | ORG | 1 |
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n sin | PERSON | 1 |
n se | LOC | 1 |
n sis | ORG | 1 |
n s t d i t c r t | CHEMICAL | 1 |
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n s max n n where s max n | CHEMICAL | 1 |
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n s sir | CHEMICAL | 1 |
n s t i s | CHEMICAL | 1 |
n t s t i t r t w t the first formulation aims | CHEMICAL | 1 |
n s i r we | CHEMICAL | 1 |
nhs digital | ORG | 1 |
naming the coronavirus disease | DISEASE | 1 |
nadini matthieu | PERSON | 1 |
nadaraya 1964 | PERSON | 1 |
nadaraya | ORG | 1 |
nyc | ORG | 1 |
nsf | ORG | 1 |
nps | CHEMICAL | 1 |
np_fasta | ORG | 1 |
npi | ORG | 1 |
nih | ORG | 1 |
nhs boards and trusts | ORG | 1 |
n β n γ c 1 and e i β c 2 to obtain di dt the solution | CHEMICAL | 1 |
ndtv | CHEMICAL | 1 |
ncbi s | ORG | 1 |
nc | GPE | 1 |
nb | ORG | 1 |
n95 | ORG | 1 |
n ψ s 1 | ORG | 1 |
n λ Σ | CHEMICAL | 1 |
n θ | PERSON | 1 |
n β s β i β r β | CHEMICAL | 1 |
n β s β i β | CHEMICAL | 1 |
n s i r we use s s t i i t r r t | CHEMICAL | 1 |
n s i r the evenly distribution of members of the species s i | CHEMICAL | 1 |
mustafa | GPE | 1 |
n 1 2 van kampen 1981 | CHEMICAL | 1 |
n 2 10 7 | ORG | 1 |
n 150 | ORG | 1 |
n 1000 | CHEMICAL | 1 |
n 100 and assumes n eq s18 gives | CHEMICAL | 1 |
n 100 and assumes n eq s18 | ORG | 1 |
n 100 000 | ORG | 1 |
n 10 | ORG | 1 |
n 1 agents | CHEMICAL | 1 |
n 1 n 2 n γ 2µ | CHEMICAL | 1 |
n 1 2 σ ϕ t to make analytical progress with eq 8 in the main text | CHEMICAL | 1 |
n 1 2 the approximation 10 turns out | CHEMICAL | 1 |
n 2 10 7 and η in fig 6 we | CHEMICAL | 1 |
n 1 2 | CHEMICAL | 1 |
n 0 as zero | ORG | 1 |
n 0 2 u t 0 as such µ λ this then gives | CHEMICAL | 1 |
n 0 | ORG | 1 |
münster the code | DISEASE | 1 |
mysterium | CHEMICAL | 1 |
mvonn | CHEMICAL | 1 |
mustardé s original | CHEMICAL | 1 |
mustardé s | PERSON | 1 |
mustarde | CHEMICAL | 1 |
n 2 10 7 and ran | CHEMICAL | 1 |
n 2 singularities | CHEMICAL | 1 |
n s e i r λ | CHEMICAL | 1 |
n i | ORG | 1 |
n r max n n where r max n | CHEMICAL | 1 |
n r i | CHEMICAL | 1 |
n por | PERSON | 1 |
n n c n r n 1 c n n c n | CHEMICAL | 1 |
n i t n | CHEMICAL | 1 |
n i t | CHEMICAL | 1 |
n i s r in the different | CHEMICAL | 1 |
n i s in the sir | CHEMICAL | 1 |
n i i | CHEMICAL | 1 |
n i equation | CHEMICAL | 1 |
n esta | ORG | 1 |
n 2k | ORG | 1 |
n d 100 | CHEMICAL | 1 |
n assuming c 1 | ORG | 1 |
n assuming | ORG | 1 |
n agents | ORG | 1 |
n active | ORG | 1 |
n 8 5 10 6 for switzerland n 4 7 10 7 for spain and n 6 10 7 for italy figure 3 presents real data color points and predictions solid | CHEMICAL | 1 |
n 6 10 7 it | CHEMICAL | 1 |
n 6 10 7 for | CHEMICAL | 1 |
n 40 3 50 3 60 3 70 3 the number of | CHEMICAL | 1 |
n 33 10 6 | ORG | 1 |
granular | ORG | 1 |
cenew 200th | LOC | 1 |
granovetter 1978 independent | ORG | 1 |
cameroon egypt | GPE | 1 |
quatieri | GPE | 1 |
cdr | ORG | 1 |
cctv | ORG | 1 |
cbs entuk | ORG | 1 |
cara | ORG | 1 |
c b e r of | CHEMICAL | 1 |
c saramäki | ORG | 1 |
c 2 | ORG | 1 |
butler | ORG | 1 |
buscarino et al 2014 | GPE | 1 |
burns plastic surgery and oral and maxillofacial surgery | ORG | 1 |
burks | ORG | 1 |
bulirsch | PERSON | 1 |
brown | PERSON | 1 |
brooks gelman | PERSON | 1 |
brockmann dirk | ORG | 1 |
brock 2011 brock | ORG | 1 |
britton et al 2020 | PERSON | 1 |
britton et al 2019 | PERSON | 1 |
britton 2000 | PERSON | 1 |
british orthopaedic association | ORG | 1 |
british association of plastic reconstructive | ORG | 1 |
britain | GPE | 1 |
ci λ µ τ | PERSON | 1 |
cjl | CHEMICAL | 1 |
classical | CHEMICAL | 1 |
covid quarantinestrength | ORG | 1 |
california usa | ORG | 1 |
currrentdate | ORG | 1 |
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css loading animations | ORG | 1 |
css | ORG | 1 |
csc | CHEMICAL | 1 |
crc | DISEASE | 1 |
cpap | ORG | 1 |
covid infection | DISEASE | 1 |
covid dynamics | ORG | 1 |
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coshh | ORG | 1 |
covid 19 epidemic rare | ORG | 1 |
covid 19 and economic impact inferring | ORG | 1 |
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covid 19 quadratic | ORG | 1 |
covid 19 previous | ORG | 1 |
covid 19 pre | ORG | 1 |
covid 19 pandemic treatment date 2020 | ORG | 1 |
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covid 19 7 8 9 millions | ORG | 1 |
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bertozzi franco mohler short | ORG | 1 |
bernoulli models | ORG | 1 |
berlin | GPE | 1 |
beretta kolmanovskii | PERSON | 1 |
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belarus | PERSON | 1 |
beijing singapore | GPE | 1 |
beijing pek | ORG | 1 |
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becaer 38 | PERSON | 1 |
bavaria | GPE | 1 |
bethune | GPE | 1 |
battiston | ORG | 1 |
bats | TAXON | 1 |
barwolff | CHEMICAL | 1 |
barrier | ORG | 1 |
barrat | PERSON | 1 |
barlow | PERSON | 1 |
barabasi albert | PERSON | 1 |
barabasi | GPE | 1 |
bar yam | PERSON | 1 |
bao | PERSON | 1 |
beta | PERSON | 1 |
bettencourt ribeiro | PERSON | 1 |
brazil mathematical models | ORG | 1 |
bombay | ORG | 1 |
brauer | GPE | 1 |
braha | PERSON | 1 |
box | PERSON | 1 |
bowong | GPE | 1 |
boussinesq | PERSON | 1 |
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boston | GPE | 1 |
boris alexeev | PERSON | 1 |
borgatti 59 | GPE | 1 |
bootstrap4 | ORG | 1 |
body parts3d research organization of information and systems database | ORG | 1 |
bin cao | PERSON | 1 |
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boccara | GPE | 1 |
blue | ORG | 1 |
bloß raus hier article | ORG | 1 |
bjørnstad 2018 | PERSON | 1 |
bizet nana | PERSON | 1 |
biswas et al 2014 | ORG | 1 |
biofuels research engineering | ORG | 1 |
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binary gaussian | PERSON | 1 |
cameroon applied optimal control optimization estimation and | ORG | 1 |
cameroon nguemdjo et | PERSON | 1 |
gramig horan | PERSON | 1 |
campisi | ORG | 1 |
cochrane handbook | PERSON | 1 |
cochrane | PERSON | 1 |
covid | DISEASE | 1 |
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clyde nhs research office | ORG | 1 |
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clinic | ORG | 1 |
clin hand trauma service | ORG | 1 |
clin epidemiol glob health | ORG | 1 |
climate change | ORG | 1 |
cleveland | GPE | 1 |
cleft lip palate | DISEASE | 1 |
clark ellison | PERSON | 1 |
clancy | PERSON | 1 |
city | DISEASE | 1 |
circles | ORG | 1 |
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cintrón arias | PERSON | 1 |
chungu | DISEASE | 1 |
christmas | DISEASE | 1 |
chris g antonopoulos | PERSON | 1 |
choudhary 2020 | PERSON | 1 |
coexistence | DISEASE | 1 |
coexistence of multiple attractors | DISEASE | 1 |
cohen | PERSON | 1 |
compartmental modelling | PERSON | 1 |
considerations | ORG | 1 |
conselho nacional de desenvolvimento científico | ORG | 1 |
confirmed c n c n 1 | ORG | 1 |
conferences | ORG | 1 |
condmat condense matter physics | ORG | 1 |
condense matter physics | ORG | 1 |
computing optimal restrictions determining | ORG | 1 |
complex | GPE | 1 |
compiled | CHEMICAL | 1 |
compartmental models | ORG | 1 |
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coherence | ORG | 1 |
compartment infectious disease | DISEASE | 1 |
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como antes | GPE | 1 |
community | ORG | 1 |
communicating social simulation models to sceptical minds | ORG | 1 |
combined | ORG | 1 |
combinations | PERSON | 1 |
colombia | GPE | 1 |
colaneri di filippo di matteo | PERSON | 1 |
colaneri 44 | PERSON | 1 |
cholera | DISEASE | 1 |
choisy sofonea | PERSON | 1 |
choi | PERSON | 1 |
cases data | ORG | 1 |
centers for disease control and prevention | ORG | 1 |
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cation exchange capacity | ORG | 1 |
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caputo fractional derivative | CHEMICAL | 1 |
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cho ippolito | PERSON | 1 |
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cho | CHEMICAL | 1 |
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abel | PERSON | 1 |
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anfis application of anfis | ORG | 1 |
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allcases | ORG | 1 |
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agg | ORG | 1 |
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ab | ORG | 1 |
a review of multi compartment infectious disease models | ORG | 1 |
a language and environment for statistical computing current | ORG | 1 |
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91646f5019fa32ba6314313991651dc62ad9f65c | DISEASE | 1 |
access | PERSON | 1 |
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aim | PERSON | 1 |
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advancing | ORG | 1 |
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9047 | DISEASE | 1 |
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8664 | CHEMICAL | 1 |
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155015 | DISEASE | 1 |
11 20192229 sha f92c6911f7792e7f65445671900c7e7b6692cee2 | CHEMICAL | 1 |
104158 | DISEASE | 1 |
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1 r e r 0 exactly at the peak of the curve r e 1 because s n r 0 | CHEMICAL | 1 |
1 network | ORG | 1 |
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1 miller | PERSON | 1 |
1 3 nodes | CHEMICAL | 1 |
1 26776 erp021740 erp021740 erp111280 erp111280 | CHEMICAL | 1 |
1 13298 2440 | CHEMICAL | 1 |
1 117619 yp _ 009742608 yp _ 009742609 yp _ 009742610 yp _ 009742611 sra | CHEMICAL | 1 |
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190495 | DISEASE | 1 |
2 cbs entuk | CHEMICAL | 1 |
84 hansen | PERSON | 1 |
339425 | CHEMICAL | 1 |
8 9 figure 4 is the standard plot for sir | CHEMICAL | 1 |
7404 | DISEASE | 1 |
7399 | DISEASE | 1 |
5411 | DISEASE | 1 |
5187 | DISEASE | 1 |
5 5 setσ | CHEMICAL | 1 |
4 study of | ORG | 1 |
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316393 | DISEASE | 1 |
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3 6243 | CHEMICAL | 1 |
2np | CHEMICAL | 1 |
297161 | CHEMICAL | 1 |
280683 | DISEASE | 1 |
277094 | DISEASE | 1 |
259270 | CHEMICAL | 1 |
241596 | DISEASE | 1 |
2144 | DISEASE | 1 |
2050 ritchie | PERSON | 1 |
20049130 | CHEMICAL | 1 |
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also m and n | ORG | 1 |
althaus 2015 total | ORG | 1 |
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avery | ORG | 1 |
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bailey 1975 anderson and watsons 1980 anderson | ORG | 1 |
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angelopoulos et al 2020 | PERSON | 1 |
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arifin | CHEMICAL | 1 |
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antonio jos e da silva | PERSON | 1 |
apple | ORG | 1 |
appendix h | ORG | 1 |
appendix f cc | ORG | 1 |
appendix c proof of | ORG | 1 |
appendix b derivatives | ORG | 1 |
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appendix a algorithm | ORG | 1 |
app | ORG | 1 |
anzum | GPE | 1 |
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erkol | DISEASE | 1 |
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equation 4 2 | CHEMICAL | 1 |
equation 24 | ORG | 1 |
equally | LOC | 1 |
eqs s3 s5 | GPE | 1 |
eqs 8 | PERSON | 1 |
eqs 6 | GPE | 1 |
eqs 5 | GPE | 1 |
eqs 40 | GPE | 1 |
eqs 38 | GPE | 1 |
eqs 16 | GPE | 1 |
eqs 14 | GPE | 1 |
eqs 10 | GPE | 1 |
eqns 4 | ORG | 1 |
eqn 3 | LOC | 1 |
eq v 10 | ORG | 1 |
eq s19 | GPE | 1 |
eq c4 | GPE | 1 |
eq b22 | PERSON | 1 |
este modelo | PERSON | 1 |
estimamos | GPE | 1 |
esto significa | GPE | 1 |
example 1 | ORG | 1 |
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f d i j θ | PERSON | 1 |
f d | PERSON | 1 |
externalities | CHEMICAL | 1 |
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evolving epidemiology and impact of non | ORG | 1 |
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estrada nicolas tombolini antonio | PERSON | 1 |
eq b 2b | PERSON | 1 |
eq a3 | GPE | 1 |
eq a2 | ORG | 1 |
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enrique amaro josé dudouet jérémie nicolás orce josé | ORG | 1 |
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emma wang | PERSON | 1 |
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email enrenew | ORG | 1 |
el valor de la relación k entre el número de infectados observados | PERSON | 1 |
el pico de la | GPE | 1 |
el panel derecho muestra la variación | DISEASE | 1 |
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el modelo | GPE | 1 |
el salvador | GPE | 1 |
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el ghozlani | CHEMICAL | 1 |
eichenbaum et al 20 | PERSON | 1 |
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eiben | CHEMICAL | 1 |
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ecuador genetic | ORG | 1 |
ecuador | GPE | 1 |
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ebolavirus | LOC | 1 |
environmental research modeling | ORG | 1 |
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eq a16 | ORG | 1 |
eq 2 | ORG | 1 |
eq a13 | ORG | 1 |
eq a 1 | GPE | 1 |
eq 70 | GPE | 1 |
eq 7 | LOC | 1 |
eq 54 | PERSON | 1 |
eq 26c | PERSON | 1 |
eq 26a | ORG | 1 |
eq 25 | PERSON | 1 |
eq 22 | LOC | 1 |
eq 21b | LOC | 1 |
eq 19 | LOC | 1 |
epidemic dataset advances | ORG | 1 |
eq 18 | ORG | 1 |
eq 15 | ORG | 1 |
eq 13d | PERSON | 1 |
eq 13 | ORG | 1 |
eq 12 | ORG | 1 |
epidemy | GPE | 1 |
epidemiology early transmission dynamics | ORG | 1 |
epidemiology dynamic | ORG | 1 |
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f β | PERSON | 1 |
f σ sse1 σ | ORG | 1 |
gani | ORG | 1 |
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gao | PERSON | 1 |
gamma_t | PERSON | 1 |
geweke | PERSON | 1 |
gamba simona | PERSON | 1 |
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gp | ORG | 1 |
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g σ probability | ORG | 1 |
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fuzzystochastic fembased | CHEMICAL | 1 |
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