This is a table of type bigram and their frequencies. Use it to search & browse the list to learn more about your study carrel.
bigram | frequency |
---|---|
contact tracing | 1462 |
public health | 274 |
granted medrxiv | 132 |
copyright holder | 132 |
author funder | 132 |
reproduction number | 128 |
infectious diseases | 125 |
tracing apps | 124 |
made available | 124 |
digital contact | 119 |
social distancing | 117 |
international license | 116 |
infectious disease | 113 |
version posted | 108 |
contact patterns | 106 |
physical distancing | 103 |
control measures | 83 |
novel coronavirus | 77 |
close contacts | 76 |
social contacts | 74 |
social contact | 74 |
index case | 73 |
contact rate | 72 |
contact network | 70 |
average number | 68 |
household contacts | 67 |
manual contact | 65 |
close contact | 64 |
mixing patterns | 63 |
doc id | 63 |
distancing measures | 63 |
location data | 63 |
cord uid | 63 |
contact rates | 63 |
exposure notification | 63 |
ct apps | 62 |
medrxiv preprint | 61 |
contact lens | 60 |
contact data | 57 |
total number | 57 |
effective contact | 56 |
per day | 56 |
mobile phone | 54 |
tracing app | 54 |
tracing system | 53 |
united states | 53 |
posted may | 52 |
infected individuals | 51 |
symptom onset | 51 |
infected person | 51 |
age group | 49 |
peer review | 49 |
contacts per | 49 |
contact matrices | 49 |
incubation period | 47 |
coronavirus disease | 46 |
age groups | 46 |
social mixing | 45 |
contact networks | 45 |
contact events | 43 |
data collection | 43 |
case isolation | 43 |
health care | 43 |
infectious period | 42 |
health authorities | 42 |
based contact | 42 |
epidemic control | 41 |
disease transmission | 41 |
transmission rate | 40 |
respiratory syndrome | 39 |
healthcare workers | 38 |
south korea | 37 |
trefoil knot | 36 |
world health | 36 |
infection rate | 36 |
confirmed cases | 36 |
tracing applications | 36 |
leprosy patients | 34 |
infected individual | 34 |
marginal infections | 34 |
secondary cases | 34 |
acute respiratory | 34 |
infected persons | 33 |
health organization | 33 |
tracing solutions | 33 |
signal strength | 32 |
household size | 32 |
bluetooth le | 32 |
contact sensing | 32 |
contact surveys | 32 |
human activity | 32 |
many countries | 32 |
bluetooth low | 31 |
basic reproduction | 31 |
large number | 31 |
disease control | 31 |
physical contacts | 31 |
severe acute | 30 |
low energy | 30 |
proximity sensing | 30 |
personal information | 30 |
symptomatic cases | 30 |
gcg app | 30 |
epidemic threshold | 30 |
device id | 29 |
influenza pandemic | 29 |
population density | 29 |
contact lenses | 29 |
data collected | 28 |
privacy concerns | 28 |
health officials | 28 |
secondary infections | 28 |
digital exposure | 28 |
close proximity | 28 |
pandemic influenza | 28 |
attack rate | 28 |
least one | 27 |
based model | 27 |
contact matrix | 27 |
collected data | 27 |
infection control | 27 |
based approach | 27 |
transmission dynamics | 26 |
challenge appraisal | 26 |
effective reproduction | 26 |
systematic review | 26 |
human activities | 26 |
general population | 26 |
digital tracing | 25 |
amino acids | 25 |
tracing technology | 25 |
nan doi | 25 |
contract tracing | 25 |
casual contacts | 25 |
mean number | 25 |
closed trefoil | 25 |
disease spread | 25 |
contact details | 25 |
bcg vaccination | 25 |
activity recognition | 25 |
disease outbreaks | 24 |
may also | 24 |
posted september | 24 |
proximity detection | 24 |
individual contact | 24 |
reported contacts | 24 |
infectious individuals | 24 |
contacts within | 23 |
qr code | 23 |
wifi sensing | 23 |
unit clerks | 23 |
lens wear | 23 |
data protection | 23 |
central server | 23 |
human contact | 23 |
active surveillance | 23 |
lockdown measures | 22 |
many people | 22 |
school closings | 22 |
cross infection | 22 |
confirmed covid | 22 |
modelling study | 22 |
data set | 22 |
physical contact | 22 |
infected people | 22 |
travel restrictions | 21 |
contact ring | 21 |
preserving contact | 21 |
distancing survey | 21 |
health system | 21 |
app users | 21 |
infection rates | 21 |
attack rates | 21 |
exposure prophylaxis | 21 |
new york | 21 |
tracing systems | 21 |
contact survey | 20 |
family members | 20 |
leprosy control | 20 |
contact information | 20 |
mixing matrices | 20 |
dynamic contact | 20 |
contact interactions | 20 |
even though | 20 |
ring vaccination | 20 |
gps data | 20 |
available data | 20 |
focused coping | 20 |
protective effect | 20 |
lens case | 20 |
traditional contact | 20 |
magnetometer traces | 20 |
maximum number | 19 |
ill persons | 19 |
coping behavior | 19 |
group contact | 19 |
machine learning | 19 |
mobile apps | 19 |
health code | 19 |
last accessed | 19 |
diagnosed carriers | 19 |
ebola virus | 19 |
tracing application | 19 |
seir model | 19 |
household members | 18 |
order contacts | 18 |
false positives | 18 |
care workers | 18 |
susceptible population | 18 |
proximity tracing | 18 |
washington state | 18 |
privacy infringement | 18 |
confidential computing | 18 |
protein folding | 18 |
exposure risk | 18 |
primary contact | 18 |
total population | 18 |
baseline survey | 17 |
ct app | 17 |
pharmaceutical interventions | 17 |
mathematical models | 17 |
infections generated | 17 |
wireless sensing | 17 |
secondary case | 17 |
contact tracking | 17 |
traced contacts | 17 |
mobile phones | 17 |
patterns relevant | 17 |
transmission rates | 17 |
staff physicians | 17 |
control strategies | 17 |
tracing process | 17 |
school closures | 17 |
differential equations | 17 |
manual tracing | 17 |
home contacts | 17 |
tracing efforts | 17 |
casual contact | 17 |
hospital beds | 17 |
health workforce | 16 |
phone apps | 16 |
exposed individuals | 16 |
specific social | 16 |
school contacts | 16 |
health professionals | 16 |
contact tracers | 16 |
homogeneous mixing | 16 |
centric approach | 16 |
based models | 16 |
contacts made | 16 |
health workers | 16 |
social media | 16 |
worker groups | 16 |
smartphone magnetometer | 16 |
phone number | 16 |
index cases | 16 |
wearable sensors | 16 |
suggests epidemic | 15 |
mac address | 15 |
two different | 15 |
social networks | 15 |
quantifying sars | 15 |
vaccination coverage | 15 |
total duration | 15 |
user privacy | 15 |
tracing methods | 15 |
personal data | 15 |
highly effective | 15 |
new cases | 15 |
social interactions | 15 |
diagnosed carrier | 15 |
literature review | 15 |
publicly available | 15 |
compartment model | 15 |
test result | 15 |
transmission suggests | 15 |
serial interval | 15 |
using contact | 15 |
virus disease | 15 |
virus transmission | 15 |
different scenarios | 15 |
health status | 15 |
widely used | 15 |
contacts may | 15 |
posted july | 15 |
magnetic field | 15 |
per participant | 15 |
may lead | 15 |
proximity data | 15 |
expected number | 14 |
herd immunity | 14 |
degree distribution | 14 |
patient contacts | 14 |
middle east | 14 |
dose rifampicin | 14 |
current pandemic | 14 |
greater risk | 14 |
infected users | 14 |
infected user | 14 |
case detection | 14 |
risk assessment | 14 |
initial cases | 14 |
influenza vaccination | 14 |
sensing platform | 14 |
real time | 14 |
two individuals | 14 |
ideal knot | 14 |
take place | 14 |
sensitivity analysis | 14 |
age structure | 14 |
become infected | 14 |
social network | 14 |
united kingdom | 14 |
census data | 14 |
entire population | 14 |
contacts traced | 14 |
pandemic management | 14 |
small number | 14 |
ground truth | 14 |
become infectious | 13 |
registered users | 13 |
case scenario | 13 |
will depend | 13 |
preventive measures | 13 |
source code | 13 |
initial number | 13 |
potential impact | 13 |
contact trace | 13 |
proportionate mixing | 13 |
access points | 13 |
results show | 13 |
potential exposure | 13 |
nan sha | 13 |
uptake rate | 13 |
reproductive ratio | 13 |
locations visited | 13 |
average infections | 13 |
secondary attack | 13 |
health conditions | 13 |
informal settlements | 13 |
early diagnosis | 13 |
deep learning | 13 |
different types | 13 |
tracing technologies | 13 |
tracing using | 13 |
will need | 13 |
data points | 13 |
specific mixing | 13 |
reproductive number | 13 |
physical distance | 13 |
many contacts | 13 |
social deprivation | 13 |
fi signals | 13 |
gps location | 13 |
within days | 13 |
cohort study | 13 |
household sizes | 13 |
informed consent | 13 |
control measure | 13 |
per contact | 13 |
per case | 13 |
one another | 13 |
controlled trial | 13 |
new leprosy | 13 |
controlling covid | 13 |
seasonal influenza | 13 |
hospital worker | 13 |
time spent | 12 |
epidemic outbreak | 12 |
health systems | 12 |
different age | 12 |
single dose | 12 |
important role | 12 |
high risk | 12 |
contacts will | 12 |
repeated contacts | 12 |
location information | 12 |
mass quarantine | 12 |
seek medical | 12 |
lpep program | 12 |
susceptible individuals | 12 |
time period | 12 |
branching process | 12 |
health measures | 12 |
hong kong | 12 |
wireless sensors | 12 |
trefoil knots | 12 |
mathematical modelling | 12 |
global positioning | 12 |
mobile app | 12 |
arc length | 12 |
study period | 12 |
early stages | 12 |
epidemic model | 12 |
mobile devices | 12 |
colep study | 12 |
healthcare worker | 12 |
syndrome coronavirus | 12 |
user may | 12 |
infected cases | 12 |
per person | 12 |
transmission probability | 12 |
tracing strategies | 12 |
east respiratory | 12 |
human body | 12 |
contact traced | 12 |
community contacts | 12 |
privacy protection | 12 |
passive wifi | 12 |
respondents reported | 12 |
latent period | 12 |
different settings | 12 |
mobility reports | 12 |
primary contacts | 12 |
window size | 12 |
daily contacts | 12 |
one day | 12 |
previous work | 12 |
real world | 12 |
times greater | 12 |
parameter values | 12 |
model parameters | 12 |
lens wearers | 12 |
received signal | 12 |
position information | 11 |
using bluetooth | 11 |
epidemiological models | 11 |
million people | 11 |
high levels | 11 |
will also | 11 |
new zealand | 11 |
exposed persons | 11 |
new infections | 11 |
tests positive | 11 |
posted october | 11 |
european countries | 11 |
safe paths | 11 |
lens care | 11 |
decision making | 11 |
community mobility | 11 |
beds will | 11 |
coronavirus contact | 11 |
index patient | 11 |
respiratory disease | 11 |
virus spread | 11 |
two people | 11 |
location tracking | 11 |
conversational contacts | 11 |
automated contact | 11 |
specific contact | 11 |
recorded contacts | 11 |
flight passengers | 11 |
containment measures | 11 |
rfid tags | 11 |
tracing data | 11 |
much larger | 11 |
potential benefits | 11 |
total contacts | 11 |
health departments | 11 |
people will | 11 |
also provide | 11 |
tracing contacts | 11 |
public trust | 11 |
slum population | 11 |
aarogya setu | 11 |
individual level | 11 |
time intervals | 11 |
onward transmission | 11 |
system uses | 11 |
folding initiation | 11 |
location history | 11 |
axis shows | 11 |
new case | 11 |
open trefoil | 11 |
randomly selected | 11 |
intensive care | 11 |
diagnostic test | 11 |
working ages | 11 |
epidemic models | 11 |
commercial wi | 11 |
location trail | 10 |
social encounters | 10 |
data security | 10 |
early detection | 10 |
centralized system | 10 |
successfully traced | 10 |
binomial distribution | 10 |
disease prevention | 10 |
compartmental models | 10 |
proximity sensors | 10 |
containment zones | 10 |
apple google | 10 |
general public | 10 |
creative commons | 10 |
authors declare | 10 |
preserving proximity | 10 |
relatively small | 10 |
mobility behaviors | 10 |
baseline scenario | 10 |
passenger lists | 10 |
protection app | 10 |
direct contacts | 10 |
health interventions | 10 |
individual contacts | 10 |
randomized controlled | 10 |
person transmission | 10 |
lockdown period | 10 |
unique id | 10 |
mobility patterns | 10 |
severe symptoms | 10 |
based data | 10 |
among contacts | 10 |
quarantine period | 10 |
negative binomial | 10 |
contact distribution | 10 |
large scale | 10 |
waiting room | 10 |
per shift | 10 |
contacts reported | 10 |
bbc pandemic | 10 |
becomes infected | 10 |
daily life | 10 |
proximity report | 10 |
electronic contact | 10 |
mitigation strategies | 10 |
contact event | 10 |
per vaccination | 10 |
university hospital | 10 |
flight arrival | 10 |
tracing may | 10 |
coping theory | 10 |
positive test | 10 |
bluetooth technology | 10 |
test results | 10 |
health authority | 10 |
safety protection | 10 |
recursive tracing | 10 |
app user | 10 |
keep track | 10 |
contact surface | 10 |
mathematical theory | 10 |
death rate | 10 |
participants reported | 10 |
transparent reporting | 10 |
high number | 10 |
contact screening | 10 |
administrative staff | 10 |
side chains | 10 |
emergency department | 10 |
health response | 10 |
health center | 10 |
wide range | 10 |
critical mass | 10 |
users may | 10 |
quarantine safety | 10 |
pandemic response | 10 |
ethical considerations | 10 |
code app | 10 |
outbreak control | 9 |
sexual contact | 9 |
different contact | 9 |
tested positive | 9 |
individual heterogeneity | 9 |
healthcare system | 9 |
exposure notifications | 9 |
sensing platforms | 9 |
get tested | 9 |
recent years | 9 |
smartphone users | 9 |
mathematical modeling | 9 |
individuals will | 9 |
trace pairs | 9 |
hand hygiene | 9 |
next section | 9 |
identifiable information | 9 |
great britain | 9 |
current contact | 9 |
near future | 9 |
years old | 9 |
strict lockdown | 9 |
achieving control | 9 |
may still | 9 |
standard deviation | 9 |
tracing approach | 9 |
countries around | 9 |
contact pressure | 9 |
entropic cost | 9 |
human mobility | 9 |
trace contacts | 9 |
case finding | 9 |
leprosy prevention | 9 |
recovery rate | 9 |
phone data | 9 |
app adoption | 9 |
main text | 9 |
proposed approach | 9 |
school closure | 9 |
online survey | 9 |
transmission models | 9 |
big data | 9 |
infected area | 9 |
contact structure | 9 |
simulation model | 9 |
people infected | 9 |
high population | 9 |
network data | 9 |
factsheet template | 9 |
global health | 9 |
population level | 9 |
device ids | 9 |
confirmed case | 9 |
ideal shape | 9 |
mobility data | 9 |
prevent leprosy | 9 |
raw data | 9 |
leprosy chemoprophylaxis | 9 |
contact manner | 9 |
rights reserved | 9 |
group i | 9 |
outbreak size | 9 |
contact investigations | 9 |
data will | 9 |
hydrogen peroxide | 9 |
tracing will | 9 |
bcg vaccine | 9 |
healthcare providers | 9 |
epidemic outbreaks | 9 |
social encounter | 9 |
network position | 9 |
disease dynamics | 9 |
health monitoring | 9 |
limited capacity | 9 |
see table | 9 |
adoption rates | 9 |
higher risk | 9 |
existing contact | 9 |
better understand | 9 |
spike protein | 9 |
disease propagation | 9 |
cases will | 9 |
location trails | 9 |
contact set | 9 |
adoption rate | 9 |
infectious individual | 9 |
third party | 9 |
health management | 9 |
using wifi | 9 |
mass surveillance | 9 |
advertising packet | 9 |
node i | 9 |
contact behaviors | 9 |
fi devices | 9 |
apps may | 9 |
current study | 9 |
high school | 8 |
future work | 8 |
dominant eigenvalue | 8 |
first case | 8 |
data sets | 8 |
infectious contact | 8 |
among men | 8 |
bluetooth signal | 8 |
identify people | 8 |
open source | 8 |
among flight | 8 |
push notification | 8 |
sensitive data | 8 |
different levels | 8 |
ideal closed | 8 |
much lower | 8 |
among others | 8 |
took place | 8 |
contact type | 8 |
rssi values | 8 |
positioning system | 8 |
means clustering | 8 |
increased risk | 8 |
long term | 8 |
sensitive personal | 8 |
age bands | 8 |
percentage reduction | 8 |
sir model | 8 |
contact duration | 8 |
two users | 8 |
gcg backend | 8 |
close physical | 8 |
rfid tag | 8 |
next generation | 8 |
detailed survey | 8 |
detection system | 8 |
prediction model | 8 |
asymptomatic close | 8 |
epidemic spread | 8 |
densely populated | 8 |
disease outbreak | 8 |
population structure | 8 |
using mobile | 8 |
york times | 8 |
key role | 8 |
case fatality | 8 |
high accuracy | 8 |
wearable wireless | 8 |
gps devices | 8 |
research model | 8 |
lens compliance | 8 |
respiratory infections | 8 |
two main | 8 |
vaccination strategies | 8 |
binding domain | 8 |
implementing sdr | 8 |
mobile applications | 8 |
available beds | 8 |
policy makers | 8 |
overall population | 8 |
individual privacy | 8 |
respiratory droplets | 8 |
positive covid | 8 |
untraced cases | 8 |
pep administration | 8 |
clinical hcws | 8 |
trace data | 8 |
one study | 8 |
covid safe | 8 |
contacts among | 8 |
fatality rate | 8 |
african countries | 8 |
epidemic prevention | 8 |
may help | 8 |
two groups | 8 |
may provide | 8 |
dawn curfew | 8 |
polymod study | 8 |
identified contacts | 8 |
surgical mask | 8 |
medical advice | 8 |
laboratory confirmation | 8 |
sleep disorder | 8 |
th percentiles | 8 |
tracing model | 8 |
centralized contact | 8 |
economic crisis | 8 |
composite group | 8 |
wifi network | 8 |
infected patients | 8 |
qr codes | 8 |
data management | 8 |
additional file | 8 |
risk factors | 8 |
digital tools | 8 |
field strength | 8 |
assortative mixing | 8 |
epidemic peak | 8 |
universal shelter | 8 |
incubation time | 8 |
initial phase | 8 |
epidemiological model | 8 |
demographic data | 8 |
imported cases | 8 |
ongoing transmission | 8 |
university campuses | 8 |
face proximity | 8 |
increasing number | 8 |
instantaneous contact | 8 |
notification app | 8 |
random variable | 8 |
cumulative number | 8 |
community transmission | 8 |
less effective | 8 |
day period | 8 |
provide information | 8 |
population size | 8 |
symptomatic individuals | 8 |
time duration | 8 |
large numbers | 8 |
floor nurses | 8 |
epidemiological parameters | 8 |
second scenario | 8 |
user adoption | 8 |
magnetometer readings | 8 |
stochastic simulation | 8 |
pandemic control | 8 |
contact durations | 8 |
confidence interval | 8 |
privacy issues | 8 |
time interval | 8 |
infections created | 8 |
contacts increased | 8 |
size distribution | 8 |
leprosy post | 8 |
tracing scenario | 8 |
tti model | 8 |
gesture recognition | 8 |
high probability | 8 |
tracing alone | 7 |
future research | 7 |
leprosy research | 7 |
health agencies | 7 |
false negatives | 7 |
section iv | 7 |
dutch airlines | 7 |
purely geometric | 7 |
paramedical staff | 7 |
health data | 7 |
disease progression | 7 |
digital technologies | 7 |
graph algorithm | 7 |
elastic knots | 7 |
structural equation | 7 |
without symptoms | 7 |
contacts varied | 7 |
mixing data | 7 |
first scenario | 7 |
mean age | 7 |
signal processing | 7 |
time consuming | 7 |
direct patient | 7 |
cumulative duration | 7 |
individual i | 7 |
previous day | 7 |
distance measures | 7 |
surveillance system | 7 |
respiratory protection | 7 |
unit clerk | 7 |
disease surveillance | 7 |
table shows | 7 |
without contact | 7 |
reported confirmed | 7 |
pearson correlation | 7 |
stq strategy | 7 |
demographic information | 7 |
seed case | 7 |
mobile device | 7 |
apps like | 7 |
previous study | 7 |
infectious person | 7 |
secondary schools | 7 |
privacy risks | 7 |
physical knots | 7 |
smartphone app | 7 |
information technology | 7 |
quarantine efficacy | 7 |
days mitigation | 7 |
age mixing | 7 |
using gps | 7 |
alert dialog | 7 |
face contact | 7 |
study participants | 7 |
possible contacts | 7 |
folding process | 7 |
limited number | 7 |
staff physician | 7 |
probability per | 7 |
wearable devices | 7 |
among women | 7 |
contact behavior | 7 |
effective number | 7 |
observation period | 7 |
world data | 7 |
case studies | 7 |
perform contact | 7 |
ethics committee | 7 |
emerging infectious | 7 |
testing capacity | 7 |
amino acid | 7 |
early transmission | 7 |
european privacy | 7 |
reproduction numbers | 7 |
smartphone magnetometers | 7 |
heart rate | 7 |
peptide drugs | 7 |
section iii | 7 |
best possible | 7 |
apps will | 7 |
demographic structure | 7 |
several factors | 7 |
research hypothesis | 7 |
crystal structure | 7 |
tracing tools | 7 |
information security | 7 |
phone app | 7 |
quarantine measures | 7 |
index patients | 7 |
personnel use | 7 |
mitigation measures | 7 |
interim guidance | 7 |
user stress | 7 |
like illness | 7 |
network structure | 7 |
interactions among | 7 |
modeling approach | 7 |
correlation coefficient | 7 |
health emergency | 7 |
protective equipment | 7 |
based proximity | 7 |
accuracy achieved | 7 |
contact chords | 7 |
gps coordinates | 7 |
coronavirus sars | 7 |
potentially infected | 7 |
scale contact | 7 |
death rates | 7 |
linear correlation | 7 |
covid positive | 7 |
air travel | 7 |
system used | 7 |
also used | 7 |
section will | 7 |
initial infected | 7 |
vertical axis | 7 |
th grade | 7 |
distributed random | 7 |
secondary contacts | 7 |
infected pneumonia | 7 |
tracing solution | 7 |
snohomish counties | 7 |
based modeling | 7 |
existing research | 7 |
highly infectious | 7 |
may vary | 7 |
federated states | 7 |
social settings | 7 |
knot shapes | 7 |
health experts | 7 |
publicly reported | 7 |
washington post | 7 |
determine whether | 7 |
ideal trefoil | 7 |
health service | 7 |
mediated contact | 7 |
influenza transmission | 7 |
infected case | 7 |
infection probability | 7 |
infections among | 7 |
may require | 7 |
mathematical model | 7 |
york city | 7 |
mobile application | 7 |
contain covid | 7 |
uses wi | 7 |
reducing transmission | 7 |
false sense | 7 |
infected contacts | 7 |
weekly cases | 7 |
population contact | 7 |
people may | 7 |
coronavirus cases | 7 |
zika virus | 7 |
contact numbers | 7 |
countries like | 7 |
different values | 7 |
exposed people | 7 |
inner segments | 7 |
main difference | 7 |
digital ariadne | 7 |
reported contact | 7 |
emergency response | 7 |
folding pathway | 7 |
control programs | 7 |
intel sgx | 7 |
reduces transmission | 7 |
sensitive information | 7 |
staff members | 7 |
infectious agents | 7 |
privacy preserving | 7 |
means algorithm | 7 |
data processing | 7 |
becoming infectious | 7 |
peak number | 7 |
encounter networks | 7 |
ga ctc | 7 |
central authority | 7 |
horizontal axis | 7 |
device mac | 7 |
lockdown area | 7 |
data analysis | 7 |
inspection window | 7 |
contacts outside | 7 |
active infections | 6 |
exponential growth | 6 |
potential contacts | 6 |
operating system | 6 |
possible outcomes | 6 |
outbreak response | 6 |
infections prevented | 6 |
leprosy incidence | 6 |
network models | 6 |
control transmission | 6 |
radio frequency | 6 |
pandemic project | 6 |
hiv aids | 6 |
phone based | 6 |
five users | 6 |
policy decisions | 6 |
low probability | 6 |
population using | 6 |
posted april | 6 |
wireless signals | 6 |
uk population | 6 |
long time | 6 |
social distance | 6 |
lockdown management | 6 |
ebola epidemic | 6 |
without permission | 6 |
also observed | 6 |
good agreement | 6 |
cork kerry | 6 |
drug development | 6 |
risk contacts | 6 |
infections per | 6 |
infectious people | 6 |
emerging epidemics | 6 |
work school | 6 |
vaccination strategy | 6 |
one way | 6 |
leprosy cases | 6 |
may differ | 6 |
high proportion | 6 |
subclinical infection | 6 |
uses bluetooth | 6 |
pediatric ward | 6 |
initiation event | 6 |
existing literature | 6 |
regular intervals | 6 |
commons licence | 6 |
sample size | 6 |
tracing strategy | 6 |
sexually transmitted | 6 |
patterns shape | 6 |
distributed system | 6 |
causes covid | 6 |
contacts occurred | 6 |
various countries | 6 |
recognition using | 6 |
prevented per | 6 |
device key | 6 |
classification performance | 6 |
coping behaviors | 6 |
ethical questions | 6 |
person interactions | 6 |
data sources | 6 |
will describe | 6 |
three months | 6 |
quickly identify | 6 |
leprosy patient | 6 |
primary school | 6 |
working group | 6 |
infect dis | 6 |
high level | 6 |
mean outbreak | 6 |
health research | 6 |
tracing team | 6 |
tracing programs | 6 |
age distribution | 6 |
connectable advertising | 6 |
epidemic spreading | 6 |
clustering algorithm | 6 |
heterogeneous contacts | 6 |
contacts recorded | 6 |
complete contact | 6 |
sexual behavior | 6 |
data mining | 6 |
initial reproductive | 6 |
previous section | 6 |
distancing score | 6 |
combat covid | 6 |
immune system | 6 |
two smartwatches | 6 |
supply chains | 6 |
severe covid | 6 |
response rates | 6 |
correlation coefficients | 6 |
cumulative infections | 6 |
allows users | 6 |
containment policies | 6 |
uptake rates | 6 |
using wearable | 6 |
transmission potential | 6 |
pandemic date | 6 |
longer time | 6 |
vaccinations performed | 6 |
primary focus | 6 |
ebola outbreak | 6 |
hiv testing | 6 |
based sensing | 6 |
antiviral agents | 6 |
mw vaccine | 6 |
statistically significant | 6 |
infectious state | 6 |
infected agent | 6 |
mixing groups | 6 |
confidence intervals | 6 |
proposed framework | 6 |
curvature profile | 6 |
personal protective | 6 |
containment strategies | 6 |
early stage | 6 |
online questionnaire | 6 |
upper bound | 6 |
different areas | 6 |
tracetogether app | 6 |
ap locations | 6 |
tracing capacity | 6 |
vary across | 6 |
fatality numbers | 6 |
use respiratory | 6 |
detailed information | 6 |
baseline rate | 6 |
based apps | 6 |
supplemental materials | 6 |
south korean | 6 |
countries using | 6 |
first two | 6 |
infection among | 6 |
online questionnaires | 6 |
survey data | 6 |
sensor networks | 6 |
indian inst | 6 |
daily disposable | 6 |
digital system | 6 |
randomly chosen | 6 |
surveillance data | 6 |
individuals belonging | 6 |
across different | 6 |
allows us | 6 |
effective reproductive | 6 |
post lockdown | 6 |
patient care | 6 |
epidemic growth | 6 |
personal privacy | 6 |
schiphol airport | 6 |
known locations | 6 |
contact time | 6 |
csi data | 6 |
combined effect | 6 |
specific contacts | 6 |
government officials | 6 |
two scenarios | 6 |
food security | 6 |
face masks | 6 |
primary case | 6 |
emergency management | 6 |
inflow restrictions | 6 |
power consumption | 6 |
results suggest | 6 |
develop symptoms | 6 |
population uptake | 6 |
gets infected | 6 |
sgx tee | 6 |
allowed without | 6 |
full lockdown | 6 |
case numbers | 6 |
duration contacts | 6 |
mac addresses | 6 |
state i | 6 |
tropical medicine | 6 |
attack size | 6 |
classification model | 6 |
many infectious | 6 |
traditional methods | 6 |
true positives | 6 |
least two | 6 |
fall detection | 6 |
study design | 6 |
input features | 6 |
healthcare systems | 6 |
survey participants | 6 |
reuse allowed | 6 |
strategy based | 6 |
contagious disease | 6 |
unsupervised machine | 6 |
may go | 6 |
readily available | 6 |
using data | 6 |
retrospective cohort | 6 |
computer science | 6 |
two large | 6 |
tracking model | 6 |
indoor localization | 6 |
tracing method | 6 |
much higher | 6 |
access point | 6 |
samples observed | 6 |
statistical data | 6 |
diagnostic odds | 6 |
one year | 6 |
measure social | 6 |
android devices | 6 |
significantly higher | 6 |
information systems | 6 |
important groups | 6 |
large population | 6 |
four different | 6 |
two methods | 6 |
hazard function | 6 |
saharan africa | 6 |
operating systems | 6 |
public database | 6 |
undetected contacts | 6 |
tracing probabilities | 6 |
disease containment | 6 |
keeping track | 6 |
first step | 6 |
important step | 6 |
ideal shapes | 6 |
pandemic virus | 6 |
population densities | 6 |
lancet public | 6 |
research studies | 6 |
commonly used | 6 |
curvature profiles | 6 |
ed staff | 6 |
leprosy transmission | 6 |
transmission paths | 6 |
high precision | 6 |
private cloud | 6 |
next step | 6 |
smartphone apps | 6 |
network analysis | 6 |
sex ratios | 6 |
higher among | 6 |
contact wireless | 6 |
stochastic model | 6 |
increased testing | 6 |
new infectious | 6 |
located users | 6 |
test positive | 6 |
open access | 6 |
telephone number | 6 |
first reported | 6 |
moving average | 6 |
using commercial | 6 |
bluetooth protocol | 6 |
cases isolated | 6 |
just one | 6 |
larger numbers | 6 |
transmission model | 6 |
projecting social | 6 |
bacillus calmette | 6 |
time needed | 6 |
selection bias | 6 |
full potential | 6 |
isolation measures | 6 |
study proposes | 5 |
invite code | 5 |
inform transmission | 5 |
geometric model | 5 |
data preprocessing | 5 |
available hospital | 5 |
system based | 5 |
fast spreading | 5 |
two cases | 5 |
population will | 5 |
control outbreaks | 5 |
initial exposure | 5 |
health policy | 5 |
use contact | 5 |
may well | 5 |
authors acknowledge | 5 |
large university | 5 |
different users | 5 |
smartwatch will | 5 |
another device | 5 |
staff member | 5 |
safe start | 5 |
rod centerline | 5 |
contact characteristics | 5 |
based test | 5 |
enable contact | 5 |
prospective study | 5 |
distancing restrictions | 5 |
quarantine events | 5 |
many jurisdictions | 5 |
gown overall | 5 |
text messaging | 5 |
computational cost | 5 |
long enough | 5 |
design principles | 5 |
virus release | 5 |
among traced | 5 |
simple model | 5 |
medical professionals | 5 |
user location | 5 |
lens related | 5 |
sensor deployment | 5 |
containment strategy | 5 |
transition rates | 5 |
face behavioral | 5 |
testing rate | 5 |
peak height | 5 |
automatic contact | 5 |
offline questionnaire | 5 |
social workers | 5 |
modeling study | 5 |
early symptoms | 5 |
vaccination programmes | 5 |
positive cases | 5 |
band wireless | 5 |
year olds | 5 |
zero leprosy | 5 |
less likely | 5 |
microbial keratitis | 5 |
kurdistan region | 5 |
sensing technologies | 5 |
social gatherings | 5 |
individual variation | 5 |
hiv infection | 5 |
contacts need | 5 |
user consent | 5 |
users will | 5 |
adverse events | 5 |
model describing | 5 |
world networks | 5 |
ltcf residents | 5 |
driven contact | 5 |
individuals infected | 5 |
disease status | 5 |
app uptake | 5 |
corresponding rfid | 5 |
cloud providers | 5 |
health services | 5 |
contact pairs | 5 |
superspreading events | 5 |
may cause | 5 |
around nairobi | 5 |
risk reduction | 5 |
immunoprophylactic agents | 5 |
effective quarantine | 5 |
global pandemic | 5 |
estimate age | 5 |
backend service | 5 |
must also | 5 |
classic seir | 5 |
first index | 5 |
symptomatic transmission | 5 |
time periods | 5 |
one person | 5 |
elastic rod | 5 |
knotted filaments | 5 |
ha server | 5 |
conduct contact | 5 |
one rfid | 5 |
rssi value | 5 |
residual immunity | 5 |
temporary contact | 5 |
completely susceptible | 5 |
seeking medical | 5 |
disease exposure | 5 |
time delayed | 5 |
specific locations | 5 |
anonymous id | 5 |
hand washing | 5 |
contact history | 5 |
much less | 5 |
illness rate | 5 |
wifi networks | 5 |
transmission occurred | 5 |
asymptomatic contacts | 5 |
people per | 5 |
time window | 5 |
order contact | 5 |
airline companies | 5 |
ambient signature | 5 |
suspected cases | 5 |
location report | 5 |
central database | 5 |
might also | 5 |
tracing needs | 5 |
care system | 5 |
highly correlated | 5 |
additional infections | 5 |
one case | 5 |
radiofrequency identification | 5 |
may impact | 5 |
undetected infections | 5 |
digital proximity | 5 |
kenyan government | 5 |
getting tested | 5 |
hospital bed | 5 |
reduce contact | 5 |
emory university | 5 |
resolution human | 5 |
reported case | 5 |
two weeks | 5 |
vol xxx | 5 |
present study | 5 |
dutch population | 5 |
will require | 5 |
epidemic containment | 5 |
avian influenza | 5 |
clinical features | 5 |
decentralized approach | 5 |
service executive | 5 |
model allows | 5 |
large amounts | 5 |
overall infection | 5 |
proposed system | 5 |
detection rate | 5 |
campus contact | 5 |
present work | 5 |
highly contagious | 5 |
technical details | 5 |
implemented using | 5 |
kenya population | 5 |
diagnosed leprosy | 5 |
dependent effects | 5 |
distance measurements | 5 |
three weeks | 5 |
app will | 5 |
swine flu | 5 |
contact definition | 5 |
model based | 5 |
using passive | 5 |
transmission among | 5 |
sensing using | 5 |
current physical | 5 |
viral proteins | 5 |
wireless communication | 5 |
term care | 5 |
contacts without | 5 |
simulation studies | 5 |
significant contribution | 5 |
current covid | 5 |
care systems | 5 |
show results | 5 |
qualitatively similar | 5 |
influenza vaccine | 5 |
one group | 5 |
cutoff threshold | 5 |
among patients | 5 |
disease burden | 5 |
contact map | 5 |
dis doi | 5 |
diamond princess | 5 |
network logs | 5 |
baseline contact | 5 |
plos one | 5 |
becoming infected | 5 |
allow us | 5 |
will help | 5 |
indoor location | 5 |
significant risk | 5 |
physical activities | 5 |
explicit list | 5 |
crucial role | 5 |
elastic rods | 5 |
national level | 5 |
pathogen transmission | 5 |
body movements | 5 |
will result | 5 |
high uptake | 5 |
study conducted | 5 |
invitation code | 5 |
signature generation | 5 |
using hydrogen | 5 |
wifi logs | 5 |
will use | 5 |
starting point | 5 |
risk individuals | 5 |
behavioral networks | 5 |
will generate | 5 |
survey contacts | 5 |
may occur | 5 |
distancing strategies | 5 |
controlling infectious | 5 |
similar results | 5 |
initial attack | 5 |
time series | 5 |
radio signals | 5 |
traced digitally | 5 |
centric contact | 5 |
diagnostic tests | 5 |
coronavirus outbreak | 5 |
possible contact | 5 |
gexf format | 5 |
based picture | 5 |
smartphone contact | 5 |
generation matrix | 5 |
required hospitalizations | 5 |
respondents admitted | 5 |
section ii | 5 |
people might | 5 |
demonstration purposes | 5 |
closing schools | 5 |
epidemic curve | 5 |
rss value | 5 |
step contact | 5 |
airborne infection | 5 |
maximum rss | 5 |
will increase | 5 |
recent past | 5 |
interaction distance | 5 |
hospital workers | 5 |
system will | 5 |
smart grid | 5 |
based human | 5 |
close encounters | 5 |
different approaches | 5 |
two magnetometer | 5 |
wcsi data | 5 |
bad actors | 5 |
scenario relative | 5 |
two years | 5 |
end time | 5 |
like pathogen | 5 |
app store | 5 |
directional antennas | 5 |
floor nurse | 5 |
correlation computation | 5 |
two phones | 5 |
different countries | 5 |
digital solutions | 5 |
income countries | 5 |
infection status | 5 |
materials appendix | 5 |
ap node | 5 |
especially important | 5 |
ribose phosphatase | 5 |
past years | 5 |
ideal knots | 5 |
quarantine strategy | 5 |
model structure | 5 |
simulation models | 5 |
personal devices | 5 |
basic reproductive | 5 |
lessons learned | 5 |
sore throat | 5 |
second wave | 5 |
control group | 5 |
control covid | 5 |
crossed paths | 5 |
potential contact | 5 |
computational models | 5 |
odds ratio | 5 |
artificial intelligence | 5 |
tracing tool | 5 |
least three | 5 |
continuous monitoring | 5 |
phase information | 5 |
leprosy vaccine | 5 |
aged children | 5 |
many secondary | 5 |
sensing system | 5 |
ble signals | 5 |
equation model | 5 |
communicable diseases | 5 |
network science | 5 |
data exchange | 5 |
automatic methods | 5 |
epidemiological characteristics | 5 |
data entry | 5 |
rss range | 5 |
study protocol | 5 |
rapid spread | 5 |
expanded testing | 5 |
reduce social | 5 |
law enforcement | 5 |
case replacement | 5 |
knots tied | 5 |
informal settlement | 5 |
tracing among | 5 |
disease model | 5 |
diagnostic accuracy | 5 |
previous days | 5 |
computing backend | 5 |
infection may | 5 |
move around | 5 |
hospital staff | 5 |
additional information | 5 |
manage covid | 5 |
false positive | 5 |
personally identifiable | 5 |
fully effective | 5 |
reference value | 5 |
scenario will | 5 |
transmission routes | 5 |
cumulative contacts | 5 |
crystal structures | 5 |
allowed us | 5 |
operational research | 5 |
isolation rates | 5 |
mixing matrix | 5 |
also developed | 5 |
traced manually | 5 |
contact pair | 5 |
receptor binding | 5 |
primary schools | 5 |
influenza epidemics | 5 |
medical institution | 5 |
research team | 5 |
xxx journal | 5 |
opening schools | 5 |
medical doctor | 5 |
two days | 5 |
surveillance systems | 5 |
data privacy | 5 |
epidemiological investigation | 5 |
school setting | 5 |
competing interests | 5 |
contact reduction | 5 |
digital health | 5 |
information collected | 5 |
quarantine authorities | 5 |
individual wearing | 5 |
multilayer network | 5 |
stakeholder groups | 5 |
splitting rule | 5 |
mass vaccination | 5 |
university campus | 5 |
worst case | 5 |
technical implementation | 5 |
findings suggest | 5 |
leprosy contacts | 5 |
network effects | 5 |
short duration | 5 |
hospital contact | 5 |
technology companies | 5 |
transmission risk | 5 |
nonlocal contacts | 5 |
close enough | 5 |
simulation results | 5 |
many years | 5 |
significantly reduce | 5 |
present results | 5 |
android app | 5 |
safe contact | 5 |
including school | 5 |
initiation events | 5 |
compartmental model | 5 |
frequency response | 5 |
new vaccines | 5 |
coronavirus pneumonia | 5 |
bernoulli distributed | 5 |
missing data | 5 |
march th | 5 |
early phase | 5 |
minimum rss | 5 |
law distribution | 5 |
effective vaccine | 5 |
control authority | 5 |
finite element | 5 |
systematic reviews | 5 |
takes place | 5 |
unlimited capacity | 5 |
location services | 5 |
node corresponds | 5 |
movement restriction | 5 |
contact detection | 5 |
ordinary differential | 5 |
complex networks | 5 |
ambulance staff | 5 |
health doi | 5 |
risk factor | 5 |
demographic characteristics | 5 |
double contact | 5 |
contact infections | 5 |
van der | 5 |
influenza outbreak | 5 |
diseases transmitted | 5 |
travel company | 5 |
every day | 5 |
sequential collapse | 5 |
epidemic size | 5 |
every mins | 5 |
longer duration | 5 |
larger number | 5 |
small changes | 5 |
coronavirus apps | 5 |
base case | 5 |
session duration | 5 |
expert meeting | 5 |
level contact | 5 |
hospital population | 4 |
two factors | 4 |
van den | 4 |
differ across | 4 |
longer term | 4 |
contact location | 4 |
positional information | 4 |
tap water | 4 |
health information | 4 |
national data | 4 |
human interactions | 4 |
ambient sound | 4 |
modest impact | 4 |
send push | 4 |
measurement bias | 4 |
identifying contacts | 4 |
large fraction | 4 |
global partnership | 4 |
incidental contacts | 4 |
implement contact | 4 |
slum dwellers | 4 |
also tracks | 4 |
health disparities | 4 |
providing awareness | 4 |
bbc data | 4 |
new infected | 4 |
previous vaccination | 4 |
related work | 4 |
core specification | 4 |
cell tower | 4 |
rate increases | 4 |
use case | 4 |
experimental results | 4 |
european union | 4 |
per infected | 4 |
stochastic epidemic | 4 |
long periods | 4 |
transmission likelihood | 4 |
performed using | 4 |
toilet facilities | 4 |
data used | 4 |
contacts involving | 4 |
personal details | 4 |
contact test | 4 |
contact curve | 4 |
solutions may | 4 |
wireless technology | 4 |
potential effectiveness | 4 |
term effects | 4 |
system capacity | 4 |
approach creates | 4 |
respiratory tract | 4 |
shaded region | 4 |
widely trace | 4 |
prodromal phase | 4 |
using deep | 4 |
first symptoms | 4 |
australian government | 4 |
age ranges | 4 |
decision threshold | 4 |
one week | 4 |
orange curve | 4 |
municipal infection | 4 |
arc lengths | 4 |
wifi signals | 4 |
future pandemics | 4 |
either recover | 4 |
specific transmission | 4 |
social behavior | 4 |
risk level | 4 |
infected patient | 4 |
physical closed | 4 |
pm location | 4 |
centroid position | 4 |
also shown | 4 |
wearable proximity | 4 |
icu beds | 4 |
different time | 4 |
tracing might | 4 |
measuring face | 4 |
empirical data | 4 |
additional data | 4 |
wifi data | 4 |
encounter data | 4 |
transmission process | 4 |
prolonged contact | 4 |
left hand | 4 |
effective public | 4 |
trusted authority | 4 |
effectiveness analysis | 4 |
messaging system | 4 |
data sharing | 4 |
surveillance technologies | 4 |
invitation codes | 4 |
nearby devices | 4 |
postexposure prophylaxis | 4 |
wifi devices | 4 |
aspen area | 4 |
prevention strategies | 4 |
mean cluster | 4 |
sensing technology | 4 |
largest eigenvalue | 4 |
several countries | 4 |
staphylococcus aureus | 4 |
performing contact | 4 |
therefore consider | 4 |
cases detected | 4 |
security monitoring | 4 |
model assumptions | 4 |
will still | 4 |
technological approaches | 4 |
long incubation | 4 |
rate among | 4 |
carrier transmission | 4 |
rfid system | 4 |
recent study | 4 |
descriptive meta | 4 |
tracing mobile | 4 |
includes two | 4 |
physical proximity | 4 |
remains neutral | 4 |
people within | 4 |
public places | 4 |
data sent | 4 |
take time | 4 |
apps gone | 4 |
effective method | 4 |
spatial location | 4 |
mean household | 4 |
detected cases | 4 |
stay home | 4 |
longer contact | 4 |
manual contacttracing | 4 |
getting sick | 4 |
ble packet | 4 |
infected state | 4 |
one secondary | 4 |
time frame | 4 |
bluetooth devices | 4 |
household quarantine | 4 |
many areas | 4 |
individual tracking | 4 |
mycobacterium tuberculosis | 4 |
two types | 4 |
centralized approach | 4 |
patients may | 4 |
distance traveled | 4 |
important ethical | 4 |
continued spread | 4 |
also possible | 4 |
data may | 4 |
gps tracking | 4 |
manual tracking | 4 |
internal services | 4 |
effective covid | 4 |
privacy concern | 4 |
measures will | 4 |
survey explored | 4 |
tracing requires | 4 |
session durations | 4 |
hospitalization rate | 4 |
published maps | 4 |
gcg user | 4 |
different encounter | 4 |
loop length | 4 |
lenses whilst | 4 |
institutional affiliations | 4 |
static group | 4 |
mitigate disease | 4 |
classification accuracy | 4 |
single infected | 4 |
relatively large | 4 |
potential transmission | 4 |
asymptomatic individuals | 4 |
preserving protocol | 4 |
right panel | 4 |
unassociated devices | 4 |
maintaining personal | 4 |
early estimation | 4 |
pandemic situation | 4 |
acquired infections | 4 |
temporal resolution | 4 |
dynamic time | 4 |
health benefit | 4 |
learning algorithms | 4 |
lockdown mass | 4 |
bluetooth apps | 4 |
first time | 4 |
total delay | 4 |
much smaller | 4 |
unique sensor | 4 |
reported number | 4 |
age category | 4 |
smartphone holders | 4 |
selective broadcasting | 4 |
case monthly | 4 |
symptoms occur | 4 |
human coronavirus | 4 |
transmission chains | 4 |
year age | 4 |
first cases | 4 |
body motions | 4 |
computed tomography | 4 |
application programming | 4 |
may become | 4 |
recognize human | 4 |
service assigned | 4 |
desktop pc | 4 |
based applications | 4 |
scenario analysis | 4 |
include testing | 4 |
three counties | 4 |
valuable tool | 4 |
citizen empowerment | 4 |
current location | 4 |
low risk | 4 |
calculated using | 4 |
regarding contact | 4 |
contacts using | 4 |
first factor | 4 |
bluetooth rssi | 4 |
tp fn | 4 |
gps locations | 4 |
population may | 4 |
vaccination problem | 4 |
clinical cases | 4 |
one contact | 4 |
temporal contact | 4 |
additional contacts | 4 |
two columns | 4 |
increased contacts | 4 |
wearing contact | 4 |
communicable disease | 4 |
sars cov | 4 |
entrance exit | 4 |
different population | 4 |
average contacts | 4 |
privacy implications | 4 |
international air | 4 |
among users | 4 |
tracing procedure | 4 |
new technology | 4 |
use mobile | 4 |
physical activity | 4 |
transmission via | 4 |
last scenario | 4 |
simulation using | 4 |
reduce covid | 4 |
ct requests | 4 |
transmitted infections | 4 |
staff interactions | 4 |
health medicine | 4 |
significant differences | 4 |
duplex mode | 4 |
open knots | 4 |
participants reporting | 4 |
signature information | 4 |
population screening | 4 |
closed loop | 4 |
commons attribution | 4 |
contact region | 4 |
make informed | 4 |
use bluetooth | 4 |
personal contact | 4 |
positioning systems | 4 |
ble technology | 4 |
epidemiological data | 4 |
infectious patients | 4 |
care facilities | 4 |
every seconds | 4 |
ncov outbreak | 4 |
optimistic assumption | 4 |
reported cases | 4 |
support trust | 4 |
quarantine reduces | 4 |
average incubation | 4 |
living conditions | 4 |
support wearers | 4 |
user data | 4 |
proposed solutions | 4 |
strength indicator | 4 |
one doi | 4 |
recent advances | 4 |
without intervention | 4 |
service number | 4 |
overall illness | 4 |
asymptomatic transmission | 4 |
research assistants | 4 |
total cases | 4 |
one key | 4 |
distance estimation | 4 |
widely available | 4 |
elastic deformation | 4 |
individual mobility | 4 |
wearing time | 4 |
backend services | 4 |
also help | 4 |
every infected | 4 |
hence tackling | 4 |
work related | 4 |
disease transmissions | 4 |
cases per | 4 |
also found | 4 |
efficient vaccination | 4 |
mean rss | 4 |
interquartile range | 4 |
coronavirus infection | 4 |
social stigma | 4 |
system using | 4 |
proximity estimation | 4 |
two rows | 4 |
security aspects | 4 |
visited area | 4 |
private companies | 4 |
broadcasting range | 4 |
research study | 4 |
also provides | 4 |
sufficiently large | 4 |
time data | 4 |
containment margin | 4 |
rapid response | 4 |
centrality measure | 4 |
elastomeric rods | 4 |
government agencies | 4 |
stakeholder group | 4 |
interaction patterns | 4 |
contact hours | 4 |
subsequent untraced | 4 |
periodically according | 4 |
evidence suggests | 4 |
time taken | 4 |
secondary analysis | 4 |
support system | 4 |
information regarding | 4 |
travel logs | 4 |
graph algorithms | 4 |
avian flu | 4 |
wifi access | 4 |
varying infection | 4 |
worker group | 4 |
ml dl | 4 |
infection prevention | 4 |
high adherence | 4 |
vaccinated contacts | 4 |
older adults | 4 |
food service | 4 |
antibiotic resistance | 4 |
peroxide users | 4 |
matrices based | 4 |
human lives | 4 |
currently available | 4 |
step estimation | 4 |
china cdc | 4 |
drug administration | 4 |
therapeutic drugs | 4 |
negative impact | 4 |
time delays | 4 |
springer nature | 4 |
adp ribose | 4 |
infections based | 4 |
transmission speed | 4 |
hospital together | 4 |
daily distance | 4 |
high rate | 4 |
digital contacttracing | 4 |
human rights | 4 |
italian districts | 4 |
infection risk | 4 |
population census | 4 |
specific infection | 4 |
time warping | 4 |
within months | 4 |
distributed across | 4 |
random daily | 4 |
small outbreaks | 4 |
data extraction | 4 |
predictive power | 4 |
results section | 4 |
influenza epidemic | 4 |
years follow | 4 |
service provider | 4 |
reference run | 4 |
will notify | 4 |
random sample | 4 |
whether two | 4 |
characterizing great | 4 |
compartment modeling | 4 |
recovered state | 4 |
hiv epidemic | 4 |
automated text | 4 |
patients infected | 4 |
reusable lenses | 4 |
healthcare demand | 4 |
fatality rates | 4 |
provide additional | 4 |
vulnerable population | 4 |
case counts | 4 |
west africa | 4 |
tracing via | 4 |
early control | 4 |
occupation networks | 4 |
cumulative distribution | 4 |
carrier might | 4 |
staff participants | 4 |
emotionfocused coping | 4 |
among individuals | 4 |
portuguese nationality | 4 |
exposed states | 4 |
people move | 4 |
betweenness centrality | 4 |
also called | 4 |
rss values | 4 |
demographic factors | 4 |
based device | 4 |
signature protocol | 4 |
within hours | 4 |
european centre | 4 |
different assumptions | 4 |
will allow | 4 |
limited testing | 4 |
will reach | 4 |
different groups | 4 |
reusable lens | 4 |
see section | 4 |
collapse model | 4 |
soft contact | 4 |
systematic literature | 4 |
open data | 4 |
high contact | 4 |
tracing across | 4 |
emergency measures | 4 |
average filter | 4 |
contacts throughout | 4 |
one needs | 4 |
given disease | 4 |
also increases | 4 |
text message | 4 |
success rate | 4 |
go untraced | 4 |
illness rates | 4 |
baseline values | 4 |
human behavior | 4 |
le protocol | 4 |
unpublished report | 4 |
night shifts | 4 |
knots exhibit | 4 |
survey information | 4 |
per week | 4 |
contacts also | 4 |
channel state | 4 |
risks associated | 4 |
tracing must | 4 |
credit card | 4 |
kayhan zrar | 4 |
respiratory virus | 4 |
two approaches | 4 |
two reasons | 4 |
scatter plot | 4 |
intervention strategies | 4 |
assisted location | 4 |
wide lockdown | 4 |
statistical analysis | 4 |
economic impact | 4 |
pep implementation | 4 |
agents will | 4 |
scale population | 4 |
fair information | 4 |
newly collected | 4 |
science project | 4 |
surge capacity | 4 |
care must | 4 |
privacy issue | 4 |
android phones | 4 |
economic damage | 4 |
recent contacts | 4 |
three days | 4 |
dl algorithms | 4 |
model assumes | 4 |
infections spread | 4 |
modeling framework | 4 |
rifampicin resistance | 4 |
may come | 4 |
fi router | 4 |
pandemic containment | 4 |
specific population | 4 |
safely lifted | 4 |
face contacts | 4 |
location accuracy | 4 |
dl model | 4 |
google partner | 4 |
three quarters | 4 |
bluetooth data | 4 |
curvature peaks | 4 |
armbruster brandeau | 4 |
contact isolation | 4 |
five informal | 4 |
notifying contacts | 4 |
contact graph | 4 |
different transmission | 4 |
model using | 4 |
capacity constraints | 4 |
specialized hardware | 4 |
exhibit high | 4 |
tensor deconvolution | 4 |
identifying information | 4 |
phosphatase domain | 4 |
total contact | 4 |
information will | 4 |
log files | 4 |
isolate infected | 4 |
user tests | 4 |
one important | 4 |
google play | 4 |
ultimate success | 4 |
several parameters | 4 |
vaccination rates | 4 |
effective use | 4 |
intensive task | 4 |
survey respondents | 4 |
short term | 4 |
low number | 4 |
assessing disease | 4 |
final version | 4 |
widespread testing | 4 |
provide transparency | 4 |
fewer contacts | 4 |
collect data | 4 |
will reduce | 4 |
contact identification | 4 |
three scenarios | 4 |
interval iii | 4 |
using smartphone | 4 |
infection state | 4 |
hypopnea syndrome | 4 |
blanket approach | 4 |
notification model | 4 |
particularly important | 4 |
state information | 4 |
first year | 4 |
efficient graph | 4 |
high cost | 4 |
grade i | 4 |
sectional survey | 4 |
leisure contacts | 4 |
within weeks | 4 |
medical care | 4 |
will affect | 4 |
current epidemic | 4 |
became symptomatic | 4 |
two months | 4 |
ble beacon | 4 |
randomised controlled | 4 |
brief contact | 4 |
contacts exposed | 4 |
privacy considerations | 4 |
smallpox epidemic | 4 |
unmitigated scenario | 4 |
growth rate | 4 |
may share | 4 |
relatively low | 4 |
fi signal | 4 |
previous studies | 4 |
epidemic contact | 4 |
hardware setup | 4 |
like symptoms | 4 |
direct contact | 4 |
gamma distributed | 4 |
household contact | 4 |
measures including | 4 |
different days | 4 |
establish contact | 4 |
tracing protocol | 4 |
maghdid ghafoor | 4 |
clinical health | 4 |
privacy policies | 4 |
municipal emergency | 4 |
laboratory confirmed | 4 |
probability distribution | 4 |
critical transmissibility | 4 |
therapeutic drug | 4 |
human motion | 4 |
bluetooth core | 4 |
unique contacts | 4 |
polymod dataset | 4 |
based approaches | 4 |
urgent need | 4 |
achieve control | 4 |
new coronavirus | 4 |
worker vaccinations | 4 |
mg kg | 4 |
scale setting | 4 |
higher cutoff | 4 |
unique device | 4 |
bbc dataset | 4 |
asymptomatic carrier | 4 |
newly diagnosed | 4 |
mortality rates | 4 |
location sensing | 4 |
elastic knot | 4 |
face coverings | 4 |
taking recent | 4 |
ai systems | 4 |
related information | 4 |
results reported | 4 |
platform consists | 4 |
will see | 4 |
recent estimates | 4 |
zhejiang province | 4 |
decentralized approaches | 4 |
advertising channels | 4 |
division duplex | 4 |
segments involved | 4 |
many different | 4 |
southeast asia | 4 |
two traces | 4 |
user study | 4 |
smart lockdown | 4 |
contact structures | 4 |
incubation periods | 4 |
accuracy concerns | 4 |
highly sensitive | 4 |
mixing expectations | 4 |
alternative approach | 4 |
communication traces | 4 |
getting infected | 4 |
informatics systems | 4 |
detection probability | 4 |
relatively limited | 4 |
socioeconomic status | 4 |
individuals within | 4 |
hospital wards | 4 |
hospitalization rates | 4 |
large impact | 4 |
internet users | 4 |
strict isolation | 4 |
total infections | 4 |
traced per | 4 |
trained public | 4 |
fi sensing | 4 |
data generated | 4 |
bluetooth based | 4 |
school closing | 4 |
nature remains | 4 |
many scenarios | 4 |
logistical burden | 4 |
app needs | 4 |
far less | 4 |
case cleaning | 4 |
governments around | 4 |
computing consortium | 4 |
small outbreak | 4 |
passenger list | 4 |
ode system | 4 |
testing rates | 4 |
based systems | 4 |
state surveillance | 4 |
free human | 4 |
ideal case | 4 |
various non | 4 |
global scale | 4 |
research project | 4 |
proximity sensor | 4 |
centerline curve | 4 |
proposed model | 4 |
features extraction | 4 |
section presents | 4 |
historical data | 4 |
cutoff thresholds | 4 |
smart wearable | 4 |
register device | 4 |
predictive models | 4 |
us school | 4 |
control doctor | 4 |
following sections | 4 |
settlements around | 4 |
approach uses | 4 |
disease emergence | 4 |
whole population | 4 |
team members | 4 |
high logistical | 4 |
google map | 4 |
location visits | 4 |
health practitioners | 4 |
every user | 4 |
social interaction | 4 |
less infectious | 4 |
hospitalized patients | 4 |
first day | 4 |
likely efficacy | 4 |
disease symptoms | 4 |
singular increases | 4 |
susceptible persons | 4 |
fast person | 4 |
viral shedding | 4 |
will continue | 4 |
indoor positioning | 4 |
critical cases | 4 |
seir models | 4 |
sectional deformation | 4 |
ode model | 4 |
low numbers | 4 |
interval i | 4 |
university health | 4 |
reopening scenarios | 4 |
com scientificreports | 4 |
closed knot | 4 |
combined effects | 4 |
prevent onward | 4 |
disease contact | 4 |
random interactions | 4 |
activity classification | 4 |
jurisdictional claims | 4 |
average effective | 4 |
band sensing | 4 |
advisory board | 4 |
recall bias | 4 |
reduce transmission | 4 |
among staff | 4 |
may increase | 4 |
whilst showering | 4 |
security concerns | 4 |
facilitate contact | 4 |
major functional | 4 |
south africa | 4 |
results may | 4 |
contact line | 4 |
short supply | 4 |
health worker | 4 |
id gla | 4 |
modified seir | 4 |
common method | 4 |
heterogeneous contact | 4 |
review board | 4 |
local public | 4 |
survey conducted | 4 |
gone rogue | 4 |
standard seir | 4 |
infections produced | 4 |
data storage | 4 |
human services | 4 |
case returns | 4 |
average secondary | 4 |
bacillus anthracis | 4 |
observed contacts | 4 |
enterprise wifi | 4 |
real life | 4 |
leprosy case | 4 |
approach will | 4 |
uk definition | 4 |
opening primary | 4 |
google mobility | 4 |
various kinds | 4 |
will make | 4 |
theoretical approach | 4 |
urban social | 4 |
response group | 4 |
input parameters | 4 |
across age | 4 |
overall transmission | 4 |
containment efforts | 4 |
measures may | 4 |
systems based | 4 |
right hand | 4 |
power law | 4 |
epidemic predictions | 4 |
nearby users | 4 |
ad hoc | 4 |
columns show | 4 |
power level | 4 |
contacts carriers | 4 |
presumed asymptomatic | 4 |
person becomes | 4 |
makes use | 4 |
clinical characteristics | 4 |
model predicts | 4 |
single day | 4 |
positions information | 4 |
app may | 4 |
physical fiber | 4 |
rapid contact | 4 |
environmental conditions | 4 |
risk populations | 4 |
bayesian network | 4 |
knot theory | 4 |
respiratory pathogens | 4 |
temporal graph | 4 |
registration process | 4 |
denver area | 4 |
public transport | 4 |
natural disaster | 3 |
tracing supported | 3 |
average latent | 3 |
mean serial | 3 |
location details | 3 |
low power | 3 |
data accuracy | 3 |
located devices | 3 |
spectacle wearers | 3 |
additional interventions | 3 |
define pr | 3 |
der waals | 3 |
particularly relevant | 3 |
full prototype | 3 |
data show | 3 |
macroscopic level | 3 |
social worker | 3 |
distributed query | 3 |
enables us | 3 |
physical interaction | 3 |
per ward | 3 |
treatment options | 3 |
normal conditions | 3 |
shortest paths | 3 |
weak spots | 3 |
research ethics | 3 |
triage protocols | 3 |
modeling covid | 3 |
network using | 3 |
first weeks | 3 |
sustained ongoing | 3 |
likely due | 3 |
typical staff | 3 |
high mortality | 3 |
available contact | 3 |
many cities | 3 |
using multi | 3 |
infectious cases | 3 |
diffusion process | 3 |
modelling studies | 3 |