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 |
---|---|
public health | 1251 |
mental health | 957 |
social media | 818 |
health care | 628 |
physical activity | 497 |
novel coronavirus | 490 |
social distancing | 475 |
coronavirus disease | 438 |
infectious diseases | 434 |
infectious disease | 416 |
social support | 407 |
systematic review | 401 |
health literacy | 347 |
air pollution | 343 |
respiratory syndrome | 329 |
world health | 303 |
united states | 297 |
acute respiratory | 287 |
present study | 270 |
hong kong | 268 |
health organization | 266 |
risk perception | 261 |
risk factors | 258 |
confirmed cases | 257 |
health doi | 255 |
ijerph sha | 255 |
res public | 255 |
doc id | 255 |
cord uid | 255 |
environ res | 255 |
psychological distress | 255 |
climate change | 253 |
saudi arabia | 250 |
severe acute | 233 |
statistically significant | 230 |
cruise ship | 230 |
previous studies | 229 |
food safety | 228 |
health problems | 227 |
health outcomes | 217 |
older adults | 216 |
data collection | 212 |
healthcare workers | 209 |
physical education | 209 |
life satisfaction | 208 |
authors declare | 205 |
emotional intelligence | 200 |
age groups | 180 |
breast cancer | 177 |
healthcare facilities | 174 |
significant differences | 174 |
years old | 174 |
control measures | 167 |
total number | 163 |
older people | 162 |
sleep quality | 159 |
college students | 156 |
middle east | 155 |
age group | 152 |
health services | 151 |
physical health | 149 |
health workers | 148 |
environmental behavior | 148 |
general population | 147 |
case study | 146 |
psychological impact | 146 |
entrepreneurial self | 146 |
new cases | 145 |
ship employees | 143 |
food delivery | 143 |
care workers | 142 |
family members | 141 |
air quality | 140 |
available online | 139 |
depressive symptoms | 139 |
infection control | 139 |
sectional study | 137 |
disease control | 135 |
significantly associated | 135 |
floating population | 134 |
online food | 132 |
food security | 131 |
high risk | 129 |
time series | 128 |
population density | 126 |
online survey | 125 |
hubei province | 123 |
open access | 123 |
infected cases | 123 |
green space | 123 |
syndrome coronavirus | 123 |
young children | 123 |
sample size | 122 |
first day | 122 |
south korea | 121 |
see table | 120 |
university students | 120 |
logistic regression | 119 |
protective equipment | 119 |
relative humidity | 117 |
personal protective | 114 |
creative commons | 114 |
article distributed | 114 |
access article | 114 |
commons attribution | 114 |
psychological health | 113 |
health crisis | 113 |
significantly higher | 112 |
health information | 111 |
disaster response | 110 |
respiratory tract | 110 |
east respiratory | 110 |
randomized controlled | 108 |
per week | 108 |
organic food | 108 |
per day | 108 |
exercise frequency | 106 |
environmental factors | 105 |
delivery service | 104 |
current study | 104 |
tobacco use | 104 |
posttraumatic stress | 103 |
literature review | 103 |
table shows | 103 |
health promotion | 103 |
health status | 101 |
global health | 101 |
gcc countries | 100 |
internal consistency | 100 |
influenza virus | 100 |
young people | 98 |
smartphone use | 97 |
standard deviation | 97 |
future research | 97 |
public voice | 96 |
cohort study | 96 |
regression analysis | 95 |
higher levels | 95 |
health system | 95 |
nursing students | 94 |
perceived social | 94 |
factors associated | 94 |
may also | 94 |
focus group | 94 |
big data | 94 |
food insecurity | 93 |
results show | 93 |
negative emotions | 92 |
significant difference | 91 |
norm perception | 90 |
attitudes toward | 90 |
social frailty | 89 |
socioeconomic status | 88 |
urban areas | 88 |
job satisfaction | 87 |
respiratory infections | 87 |
high school | 87 |
social presence | 86 |
health professionals | 86 |
controlled trial | 85 |
rural areas | 85 |
anxiety disorder | 85 |
game meat | 85 |
likert scale | 85 |
developing countries | 84 |
social determinants | 84 |
even though | 84 |
large number | 84 |
health emergency | 83 |
important role | 83 |
many countries | 83 |
previous research | 83 |
health effects | 83 |
education classes | 83 |
data analysis | 83 |
online physical | 82 |
fresh vegetables | 82 |
healthcare professionals | 82 |
infection prevention | 82 |
linear regression | 82 |
particulate matter | 81 |
point likert | 81 |
confirmed covid | 80 |
dental practice | 79 |
antioxidant activity | 79 |
incubation period | 79 |
structural equation | 79 |
demographic characteristics | 79 |
healthcare services | 79 |
regression models | 79 |
food supply | 79 |
factors influencing | 78 |
positive correlation | 77 |
south africa | 77 |
health promoting | 77 |
health authorities | 77 |
outcome measures | 77 |
impact assessment | 77 |
public sector | 76 |
neural network | 75 |
attitude toward | 75 |
positive effect | 75 |
national health | 75 |
regression model | 75 |
behavioral control | 75 |
traditional media | 74 |
european countries | 74 |
high levels | 74 |
online social | 74 |
higher risk | 74 |
increased risk | 73 |
alcohol consumption | 73 |
th day | 73 |
health measures | 73 |
disaster management | 73 |
education program | 73 |
health perceptions | 72 |
future studies | 72 |
promoting behavior | 72 |
new york | 72 |
sustainable development | 71 |
planned behavior | 71 |
hospitality industry | 71 |
recent years | 70 |
occupational health | 70 |
general public | 70 |
emotional exhaustion | 70 |
pandemic influenza | 70 |
deep learning | 70 |
healthcare system | 69 |
perceived behavioral | 69 |
health behaviors | 69 |
social networks | 69 |
close contact | 69 |
cancer patients | 69 |
correlation coefficient | 69 |
risk assessment | 68 |
hand hygiene | 68 |
machine learning | 68 |
measured using | 68 |
preventive measures | 67 |
local government | 67 |
medical students | 67 |
infection rate | 67 |
entrepreneurial intention | 67 |
imported cases | 67 |
income countries | 67 |
intensive care | 67 |
sleep disturbance | 66 |
resilient community | 66 |
reported cases | 66 |
social isolation | 66 |
crisis management | 66 |
contact tracing | 65 |
medical waste | 65 |
clinical practice | 65 |
medical staff | 64 |
among children | 64 |
infection risk | 64 |
confidence interval | 64 |
informed consent | 64 |
human health | 64 |
also found | 64 |
stress symptoms | 63 |
effect size | 63 |
infected individuals | 63 |
disease prevention | 63 |
online communication | 63 |
dental staff | 63 |
statistical analysis | 63 |
content analysis | 62 |
problematic smartphone | 62 |
longitudinal study | 62 |
turnover intention | 62 |
every day | 62 |
grey verhulst | 62 |
coronavirus pandemic | 62 |
infected people | 62 |
verhulst model | 61 |
different types | 61 |
mood states | 61 |
entrepreneurial intentions | 61 |
care services | 61 |
united nations | 61 |
past days | 61 |
symptom onset | 61 |
results showed | 61 |
health issues | 61 |
high level | 61 |
reproduction number | 61 |
type diabetes | 60 |
stress disorder | 60 |
universal health | 60 |
least one | 60 |
service use | 60 |
carbon footprint | 59 |
perceived risk | 59 |
cruise line | 59 |
ventilation rate | 59 |
social networking | 59 |
descriptive statistics | 59 |
study found | 59 |
food consumption | 59 |
inclusion criteria | 59 |
conceptual model | 59 |
health impact | 59 |
day compared | 59 |
behavioral intention | 58 |
new coronavirus | 58 |
wide range | 58 |
supply chains | 58 |
media data | 58 |
agonistic behaviour | 58 |
disease transmission | 58 |
carbon economy | 58 |
global self | 58 |
social security | 58 |
positive affect | 57 |
surgical smoke | 57 |
data collected | 57 |
respiratory viruses | 57 |
health risk | 57 |
widely used | 57 |
marital status | 57 |
coronavirus outbreak | 57 |
sex life | 57 |
educational level | 57 |
surgical masks | 57 |
highest number | 57 |
airborne transmission | 56 |
sectional survey | 56 |
primary care | 56 |
weibo texts | 56 |
shift work | 56 |
mortality rates | 56 |
health conditions | 56 |
sports participation | 56 |
commonly used | 56 |
health impacts | 55 |
among people | 55 |
two groups | 55 |
cardiovascular disease | 55 |
term exposure | 55 |
independent variables | 55 |
communicable diseases | 55 |
daily life | 55 |
airborne pathogen | 55 |
health interventions | 55 |
previous study | 54 |
results obtained | 54 |
traumatic stress | 54 |
among health | 54 |
many studies | 54 |
risk factor | 54 |
mean age | 54 |
social norms | 54 |
health emergencies | 54 |
fatality rate | 54 |
factor analysis | 54 |
cigarette use | 54 |
emerging infectious | 53 |
study design | 53 |
clinical characteristics | 53 |
per cent | 53 |
protective measures | 53 |
ia reports | 53 |
hospitalized patients | 53 |
elderly people | 53 |
back pain | 53 |
environmental behaviors | 53 |
different countries | 53 |
transmission dynamics | 53 |
associated factors | 53 |
significant association | 53 |
population migration | 53 |
total score | 52 |
disease severity | 52 |
respondents reported | 52 |
scoping review | 52 |
seir model | 52 |
disease outbreak | 52 |
subjective norm | 52 |
exposed controls | 52 |
health coverage | 52 |
higher scores | 52 |
travel medicine | 52 |
per capita | 52 |
dental care | 52 |
control group | 52 |
care facilities | 52 |
negative affect | 51 |
gender differences | 51 |
infected patients | 51 |
united kingdom | 51 |
perceived efficacy | 51 |
rated health | 51 |
review board | 51 |
built environment | 51 |
better understand | 51 |
census tract | 51 |
significant positive | 51 |
disease outbreaks | 51 |
mobile phone | 50 |
mass index | 50 |
psychological effects | 50 |
need satisfaction | 50 |
physical distancing | 50 |
media use | 50 |
local producers | 50 |
cryptosporidium infection | 50 |
one study | 50 |
one month | 50 |
may lead | 50 |
two weeks | 50 |
performed using | 50 |
study used | 50 |
fake news | 50 |
recent study | 49 |
lbp intensity | 49 |
medical care | 49 |
health questionnaire | 49 |
attitudes towards | 49 |
negative impact | 49 |
shs members | 49 |
heart disease | 49 |
another study | 49 |
lower levels | 49 |
higher level | 49 |
scale ranging | 49 |
million people | 49 |
current covid | 49 |
elderly population | 49 |
health opportunity | 49 |
developed countries | 49 |
body mass | 48 |
mortality rate | 48 |
co emissions | 48 |
wp use | 48 |
external funding | 48 |
several studies | 48 |
time period | 48 |
mental disorders | 48 |
response rate | 48 |
recent studies | 48 |
study conducted | 48 |
cumulative incidence | 48 |
media exposure | 48 |
generalized anxiety | 48 |
quality improvement | 48 |
latin america | 47 |
less likely | 47 |
daily new | 47 |
health education | 47 |
child health | 47 |
health systems | 47 |
study aimed | 47 |
fitness apps | 47 |
influenza pandemic | 47 |
low back | 47 |
participants reported | 47 |
conceptual framework | 47 |
qualitative study | 46 |
chinese government | 46 |
seasonal variation | 46 |
hospital beds | 46 |
partner violence | 46 |
search query | 46 |
multiple regression | 46 |
epidemic outbreak | 46 |
significantly lower | 46 |
stock market | 46 |
mainland china | 46 |
air samples | 46 |
sore throat | 46 |
old children | 45 |
situation report | 45 |
study also | 45 |
cases per | 45 |
cssa recipients | 45 |
focus groups | 45 |
distancing measures | 45 |
sars outbreak | 45 |
regression analyses | 45 |
intimate partner | 45 |
current pandemic | 45 |
healthcare providers | 45 |
suicidal thoughts | 45 |
low risk | 45 |
response team | 45 |
pig farmers | 45 |
health benefits | 45 |
systematic reviews | 45 |
social pressure | 45 |
among older | 45 |
demographic variables | 45 |
median age | 45 |
social policy | 44 |
table presents | 44 |
research received | 44 |
positively associated | 44 |
respiratory diseases | 44 |
daily cases | 44 |
young adults | 44 |
contracting covid | 44 |
dental procedures | 44 |
education level | 44 |
kata methodology | 44 |
safety climate | 44 |
based study | 44 |
use among | 44 |
sociodemographic characteristics | 43 |
clinical features | 43 |
coronavirus infection | 43 |
care system | 43 |
one hand | 43 |
exclusion criteria | 43 |
blood pressure | 43 |
smartphone distraction | 43 |
social network | 43 |
institutional review | 43 |
health service | 43 |
public transport | 43 |
risk perceptions | 43 |
living alone | 43 |
early stage | 43 |
public hospitals | 43 |
related events | 43 |
human resources | 42 |
census tracts | 42 |
home confinement | 42 |
health risks | 42 |
public opinion | 42 |
spatial distribution | 42 |
respiratory disease | 42 |
yoghurt sample | 42 |
public engagement | 42 |
case fatality | 42 |
subjective norms | 42 |
medical services | 42 |
psychological well | 42 |
preventive behavior | 42 |
psychological responses | 42 |
three groups | 42 |
prospective cohort | 41 |
study showed | 41 |
health behavior | 41 |
research questions | 41 |
mediating role | 41 |
swimming pool | 41 |
epidemic situation | 41 |
general anxiety | 41 |
total population | 41 |
chronic diseases | 41 |
much higher | 41 |
saharan africa | 41 |
many people | 41 |
nurturing care | 41 |
risk communication | 41 |
response options | 41 |
contact network | 41 |
global pandemic | 41 |
viral infections | 41 |
action plan | 41 |
infectious period | 40 |
transmission rate | 40 |
significant impact | 40 |
correlation analysis | 40 |
current situation | 40 |
using social | 40 |
psychometric properties | 40 |
supplementary materials | 40 |
among others | 40 |
immune system | 40 |
lockdown period | 40 |
economic growth | 40 |
disease response | 40 |
results suggest | 40 |
ethics committee | 40 |
voice behavior | 39 |
care professionals | 39 |
equation modeling | 39 |
author contributions | 39 |
vegetables directly | 39 |
local area | 39 |
related factors | 39 |
news frames | 39 |
public attention | 39 |
national level | 39 |
emergency response | 39 |
per year | 39 |
people living | 39 |
negative effects | 39 |
data sources | 39 |
alcohol use | 39 |
social factors | 39 |
confidence intervals | 39 |
also used | 39 |
patient health | 39 |
health communication | 39 |
three times | 39 |
gray value | 38 |
pathogen concentration | 38 |
dependent variable | 38 |
significantly related | 38 |
positively related | 38 |
bcg vaccine | 38 |
patients infected | 38 |
prevent covid | 38 |
health code | 38 |
direct contact | 38 |
school health | 38 |
statistical significance | 38 |
economic impact | 38 |
school closures | 38 |
positive relationship | 38 |
chronic obstructive | 38 |
hand washing | 38 |
economic development | 38 |
face masks | 38 |
information technology | 38 |
obstructive pulmonary | 37 |
ghg emissions | 37 |
swimming pools | 37 |
new daily | 37 |
six months | 37 |
across different | 37 |
pulmonary disease | 37 |
clinical trials | 37 |
first study | 37 |
community health | 37 |
strongly agree | 37 |
line companies | 37 |
housing mode | 37 |
model based | 37 |
query data | 37 |
least squares | 37 |
strongly disagree | 37 |
basic reproduction | 37 |
human transmission | 37 |
point scale | 37 |
early stages | 37 |
social identity | 37 |
initial stage | 37 |
food outlets | 37 |
recovered period | 37 |
networking sites | 37 |
research team | 37 |
physiological anxiety | 37 |
controlled trials | 37 |
socioeconomic factors | 37 |
research question | 37 |
tai chi | 36 |
personal hygiene | 36 |
care unit | 36 |
also reported | 36 |
disease spread | 36 |
national institute | 36 |
two months | 36 |
care providers | 36 |
ebola outbreak | 36 |
transmission rates | 36 |
health commission | 36 |
social relationships | 36 |
seasonal influenza | 36 |
decision making | 36 |
calculated using | 36 |
environmental protection | 36 |
natural language | 36 |
prepared away | 36 |
one day | 36 |
chronic conditions | 36 |
hydrogen peroxide | 36 |
children aged | 36 |
virus disease | 36 |
positive effects | 36 |
among chinese | 36 |
mediating effect | 36 |
nursing homes | 36 |
greenhouse gas | 36 |
dental practitioners | 35 |
health concern | 35 |
important factor | 35 |
ebola virus | 35 |
close contacts | 35 |
dna methylation | 35 |
lessons learned | 35 |
may help | 35 |
beds per | 35 |
similar results | 35 |
towards covid | 35 |
subjective well | 35 |
later life | 35 |
sexual activity | 35 |
viral load | 35 |
pilot study | 35 |
results indicate | 35 |
positive rate | 35 |
economic status | 35 |
medical information | 35 |
pig buildings | 35 |
first case | 35 |
sars coronavirus | 35 |
upper respiratory | 35 |
companion animals | 35 |
conducted using | 35 |
two different | 35 |
life expectancy | 35 |
data subset | 35 |
st century | 35 |
optical scan | 34 |
cryptosporidium oocysts | 34 |
odds ratio | 34 |
prevalence rates | 34 |
virus transmission | 34 |
mass media | 34 |
vocational college | 34 |
first time | 34 |
studies conducted | 34 |
time spent | 34 |
central government | 34 |
health centers | 34 |
related information | 34 |
immediate psychological | 34 |
isolation period | 34 |
discriminant validity | 34 |
health facilities | 34 |
tourist satisfaction | 34 |
air pollutants | 34 |
aged years | 34 |
death rate | 34 |
particularly important | 34 |
low levels | 34 |
management system | 34 |
remote communications | 34 |
study aims | 34 |
will help | 34 |
coronavirus pneumonia | 34 |
statistical analyses | 34 |
online questionnaire | 34 |
might also | 34 |
sentiment polarity | 34 |
eye care | 34 |
older workers | 34 |
epidemiological data | 34 |
sentiment analysis | 34 |
training needs | 34 |
higher education | 34 |
clinical trial | 34 |
european union | 34 |
factors affecting | 34 |
water resources | 34 |
diabetes mellitus | 34 |
respiratory distress | 34 |
different levels | 34 |
exponential growth | 34 |
farmworker families | 34 |
primary health | 34 |
psychological risk | 34 |
health problem | 34 |
first step | 34 |
among patients | 34 |
significant increase | 34 |
personal identity | 34 |
policy makers | 33 |
washing hands | 33 |
artificial intelligence | 33 |
infections among | 33 |
significant relationship | 33 |
infected population | 33 |
handball players | 33 |
assessed using | 33 |
search engine | 33 |
work community | 33 |
high number | 33 |
data analytics | 33 |
social interaction | 33 |
first two | 33 |
tested positive | 33 |
neck pain | 33 |
rapid spread | 33 |
cellular automata | 33 |
psychological stress | 33 |
better understanding | 33 |
perceived stress | 33 |
oral cavity | 33 |
sociodemographic variables | 33 |
absolute humidity | 33 |
three main | 33 |
epidemic protection | 33 |
two variables | 33 |
respiratory illness | 33 |
media platforms | 33 |
positive sentiment | 33 |
two main | 33 |
license key | 33 |
healthcare systems | 32 |
global burden | 32 |
waste management | 32 |
migration background | 32 |
health disparities | 32 |
exercise behavior | 32 |
mean scores | 32 |
per million | 32 |
resistance training | 32 |
sensitivity analysis | 32 |
precautionary measures | 32 |
surgical mask | 32 |
travel restrictions | 32 |
urban planning | 32 |
based interventions | 32 |
related stress | 32 |
health policy | 32 |
post hoc | 32 |
physical symptoms | 32 |
publicly available | 32 |
confirmed case | 32 |
vast majority | 32 |
food inflation | 32 |
public housing | 32 |
published version | 32 |
crew members | 32 |
included studies | 32 |
indoor environments | 32 |
technology use | 32 |
high prevalence | 32 |
gender roles | 32 |
working conditions | 32 |
supplementary table | 32 |
epidemic curve | 32 |
significant effect | 32 |
first confirmed | 32 |
among adults | 32 |
negative sentiment | 32 |
delivery services | 32 |
much lower | 31 |
selected countries | 31 |
weight loss | 31 |
age categories | 31 |
million population | 31 |
oil encapsulated | 31 |
body temperature | 31 |
precarious employment | 31 |
influencing factors | 31 |
low health | 31 |
drug use | 31 |
provide information | 31 |
study period | 31 |
nsw public | 31 |
information sharing | 31 |
times per | 31 |
rapid review | 31 |
affected countries | 31 |
will increase | 31 |
respiratory droplets | 31 |
ili patients | 31 |
may affect | 31 |
external factors | 31 |
emergency department | 31 |
low level | 31 |
personal outcomes | 31 |
three different | 31 |
tobacco users | 31 |
emotional response | 31 |
neural networks | 31 |
unemployment insurance | 31 |
volatile oils | 31 |
lower respiratory | 31 |
cov infection | 31 |
household income | 31 |
sleep problems | 31 |
gas emissions | 31 |
population size | 31 |
health consequences | 31 |
older age | 31 |
stress levels | 31 |
may increase | 31 |
among participants | 30 |
human beings | 30 |
will continue | 30 |
spatial indicators | 30 |
existing studies | 30 |
social distance | 30 |
prolonged sadness | 30 |
computed tomography | 30 |
first wave | 30 |
distance caregiving | 30 |
enabling factors | 30 |
social assistance | 30 |
preferred pleasantness | 30 |
retrospective cohort | 30 |
proposed model | 30 |
data protection | 30 |
significant role | 30 |
transport station | 30 |
suicide rates | 30 |
prescription drugs | 30 |
collected data | 30 |
epidemic prevention | 30 |
indirect effect | 30 |
since covid | 30 |
work discomfort | 30 |
relationships among | 30 |
factors related | 30 |
treating patients | 30 |
anxiety disorders | 30 |
health determinants | 30 |
psychological interventions | 30 |
positively correlated | 30 |
per population | 30 |
i feel | 30 |
emotional support | 30 |
root mean | 30 |
risk management | 30 |
average age | 29 |
behavior change | 29 |
positive emotions | 29 |
personal control | 29 |
virus infection | 29 |
theoretical framework | 29 |
related health | 29 |
incidence rate | 29 |
positive attitude | 29 |
rural communities | 29 |
new deaths | 29 |
different regions | 29 |
fit index | 29 |
diamond princess | 29 |
short food | 29 |
protective behaviors | 29 |
environmental health | 29 |
health insurance | 29 |
intellectual disability | 29 |
adverse effects | 29 |
observational study | 29 |
among women | 29 |
prediction model | 29 |
susceptible population | 29 |
maladaptive perfectionists | 29 |
receive medical | 29 |
short term | 29 |
occupational safety | 29 |
social protection | 29 |
image registration | 29 |
substance use | 29 |
dental practices | 29 |
several limitations | 29 |
community resilience | 29 |
media usage | 29 |
performance analysis | 29 |
may result | 29 |
ffp respirators | 29 |
mathematical model | 29 |
cluster analysis | 29 |
mental illness | 29 |
food access | 29 |
survey study | 29 |
among adolescents | 29 |
real time | 29 |
sars epidemic | 29 |
carbon emissions | 29 |
travel time | 28 |
river delta | 28 |
social capital | 28 |
perceived loneliness | 28 |
severe covid | 28 |
will also | 28 |
prevention measures | 28 |
health crises | 28 |
rank correlation | 28 |
results revealed | 28 |
medical insurance | 28 |
results also | 28 |
moving mean | 28 |
distress syndrome | 28 |
demographic data | 28 |
among healthcare | 28 |
arima model | 28 |
perceived threat | 28 |
health professional | 28 |
labor market | 28 |
two studies | 28 |
indirect effects | 28 |
digital technologies | 28 |
data obtained | 28 |
prediction models | 28 |
surveillance system | 28 |
local governments | 28 |
pathogen dispersion | 28 |
sedentary behavior | 28 |
twitter data | 28 |
healthy diet | 28 |
control strategies | 28 |
oxidative stress | 28 |
study participants | 28 |
vaccine hesitancy | 28 |
among different | 28 |
prescription drug | 28 |
wearing masks | 28 |
screen use | 28 |
peer support | 28 |
mean score | 28 |
cohort studies | 28 |
significantly different | 28 |
determine whether | 27 |
confirmed patients | 27 |
face recognition | 27 |
dental health | 27 |
online program | 27 |
psychological counseling | 27 |
global public | 27 |
deaths per | 27 |
among young | 27 |
information exchange | 27 |
online classes | 27 |
health management | 27 |
exposure assessment | 27 |
lung cancer | 27 |
mindful attention | 27 |
general health | 27 |
national resilience | 27 |
physical performance | 27 |
average value | 27 |
suspected cases | 27 |
long term | 27 |
average number | 27 |
randomised controlled | 27 |
bed numbers | 27 |
negatively associated | 27 |
three provinces | 27 |
will need | 27 |
operational problems | 27 |
one health | 27 |
online surveys | 27 |
health worker | 27 |
ibm spss | 27 |
development goals | 27 |
actual data | 27 |
three categories | 27 |
metabolic syndrome | 27 |
internet multitasking | 27 |
epidemiological studies | 27 |
second wave | 27 |
cssa system | 27 |
missing data | 27 |
southern hemisphere | 27 |
disease surveillance | 27 |
community identification | 27 |
risk group | 27 |
available data | 27 |
study sample | 27 |
social lives | 27 |
study area | 27 |
west africa | 27 |
air temperature | 27 |
preventive behaviors | 27 |
infection cases | 27 |
coronary heart | 27 |
ibm corp | 27 |
diabetes education | 27 |
city lockdown | 27 |
social interactions | 27 |
attitude towards | 27 |
infectious agents | 27 |
tract infections | 27 |
health research | 26 |
empirical evidence | 26 |
narrative review | 26 |
information acquisition | 26 |
case counts | 26 |
corona virus | 26 |
quit intentions | 26 |
perceived usefulness | 26 |
closely related | 26 |
first reported | 26 |
working group | 26 |
term health | 26 |
el mundo | 26 |
psychological factors | 26 |
findings suggest | 26 |
nursing home | 26 |
relatively high | 26 |
mean values | 26 |
chronic disease | 26 |
viral infection | 26 |
relatively low | 26 |
test results | 26 |
oud sud | 26 |
square test | 26 |
dental treatment | 26 |
community support | 26 |
spring festival | 26 |
intervention group | 26 |
respiratory symptoms | 26 |
dental office | 26 |
year students | 26 |
also observed | 26 |
capstone meeting | 26 |
food prepared | 26 |
new covid | 26 |
highest value | 26 |
took place | 26 |
cancer survivors | 26 |
using spss | 26 |
positive impact | 26 |
results indicated | 26 |
age structure | 26 |
migrant workers | 26 |
positive comments | 26 |
syncytial virus | 26 |
enabling factor | 26 |
working environment | 26 |
first three | 26 |
wuhan city | 26 |
social activities | 26 |
social services | 26 |
mers outbreak | 26 |
normal distribution | 26 |
training programs | 26 |
sina weibo | 26 |
different age | 26 |
also included | 26 |
cruise tourism | 26 |
hospital bed | 26 |
psychological problems | 26 |
airborne particles | 26 |
smartphone addiction | 26 |
academic stress | 26 |
distress among | 26 |
sampling method | 26 |
analyzed using | 26 |
south america | 26 |
family member | 26 |
operating room | 26 |
analysis showed | 26 |
north america | 26 |
dnn model | 26 |
nasopharynx samples | 26 |
healthcare settings | 26 |
realistic threat | 26 |
new zealand | 26 |
pandemic situation | 25 |
death rates | 25 |
based approach | 25 |
sedentary behaviour | 25 |
nasopharyngeal flora | 25 |
lstm models | 25 |
one participant | 25 |
psychological need | 25 |
younger age | 25 |
word categories | 25 |
perceived knowledge | 25 |
avian influenza | 25 |
sir model | 25 |
mco measures | 25 |
correlation coefficients | 25 |
provide medical | 25 |
buying behavior | 25 |
opioid use | 25 |
ipv victims | 25 |
mediterranean diet | 25 |
psychosocial factors | 25 |
dietary diversity | 25 |
also showed | 25 |
people may | 25 |
min per | 25 |
moderating role | 25 |
quarantine measures | 25 |
ssrn electron | 25 |
health sector | 25 |
mean square | 25 |
study results | 25 |
food trade | 25 |
significant decrease | 25 |
early phase | 25 |
prepandemic exercise | 25 |
perceived understanding | 25 |
cow milk | 25 |
internet users | 25 |
subjective knowledge | 25 |
home quarantine | 25 |
greater risk | 25 |
significance level | 25 |
digital ecosystems | 25 |
study population | 25 |
symbolic threat | 25 |
final sample | 25 |
health equity | 25 |
genuine response | 25 |
epidemic model | 25 |
days per | 25 |
short period | 25 |
intermittent fasting | 25 |
health outcome | 25 |
roma children | 25 |
also important | 25 |
epidemiological characteristics | 25 |
traditional gender | 25 |
south texas | 25 |
income economies | 25 |
human coronavirus | 25 |
series analysis | 25 |
included papers | 25 |
sitting time | 25 |
patients suspected | 25 |
unemployment rate | 25 |
current research | 25 |
daily lives | 25 |
online vigilance | 25 |
studies included | 25 |
cancer center | 25 |
poor health | 25 |
use disorder | 25 |
disposable income | 24 |
cooperative governance | 24 |
quit attempt | 24 |
infection curve | 24 |
positive association | 24 |
treat patients | 24 |
adult population | 24 |
female students | 24 |
survey data | 24 |
individual health | 24 |
quarantined area | 24 |
analysis results | 24 |
chain reaction | 24 |
guangdong province | 24 |
effect sizes | 24 |
internet access | 24 |
community pharmacists | 24 |
significant correlation | 24 |
cyber space | 24 |
tourism industry | 24 |
international classification | 24 |
community response | 24 |
anxiety levels | 24 |
work experience | 24 |
pet ownership | 24 |
sodium hypochlorite | 24 |
two items | 24 |
news media | 24 |
growth model | 24 |
team members | 24 |
baidu index | 24 |
sari patients | 24 |
determination theory | 24 |
activation function | 24 |
outcomes among | 24 |
flu period | 24 |
also known | 24 |
modelling study | 24 |
epidemic among | 24 |
drinking water | 24 |
tobacco products | 24 |
cognitive function | 24 |
civic attitudes | 24 |
security system | 24 |
people infected | 24 |
derived model | 24 |
oral health | 24 |
additional information | 24 |
categorical variables | 24 |
important factors | 24 |
influenza viruses | 24 |
medical resources | 24 |
ambient pm | 24 |
remaining teeth | 24 |
personality traits | 24 |
significant correlations | 24 |
containment measures | 24 |
test showed | 24 |
respiratory syncytial | 24 |
coping strategies | 24 |
asymptomatic cases | 24 |
indoor air | 24 |
health perception | 24 |
allow us | 24 |
short time | 24 |
higher rates | 24 |
infection rates | 24 |
statistical computing | 24 |
pearson correlation | 24 |
local level | 24 |
digital transformation | 24 |
null hypothesis | 24 |
executive function | 24 |
statistical software | 24 |
day moving | 24 |
analysis method | 24 |
airborne infection | 24 |
insufficient food | 24 |
related risk | 24 |
systematic literature | 24 |
nonfarmworker families | 24 |
youtube videos | 24 |
health concerns | 24 |
care settings | 24 |
simulation results | 24 |
meteorological parameters | 24 |
selection bias | 24 |
service customers | 24 |
converting enzyme | 24 |
public participation | 24 |
accuracy assessment | 23 |
polymerase chain | 23 |
sexual minority | 23 |
term effects | 23 |
demographic information | 23 |
odds ratios | 23 |
coronavirus cases | 23 |
energy consumption | 23 |
routing problem | 23 |
everyday life | 23 |
vaccine uptake | 23 |
among university | 23 |
timely manner | 23 |
work environment | 23 |
lstm model | 23 |
information system | 23 |
using data | 23 |
network analysis | 23 |
screen time | 23 |
often used | 23 |
comparative study | 23 |
response system | 23 |
employment status | 23 |
forest environment | 23 |
existing literature | 23 |
group membership | 23 |
early childhood | 23 |
rubber dam | 23 |
multicenter distance | 23 |
objective knowledge | 23 |
fitness centers | 23 |
getting infected | 23 |
mathematical models | 23 |
climate migration | 23 |
case reports | 23 |
healthy lifestyle | 23 |
kiggs wave | 23 |
reproductive number | 23 |
influencing disaster | 23 |
next section | 23 |
chinese culture | 23 |
sodium alginates | 23 |
severe symptoms | 23 |
medical treatment | 23 |
total infected | 23 |
direct effect | 23 |
airborne pathogens | 23 |
related quality | 23 |
friendly cities | 23 |
spss statistics | 23 |
depression among | 23 |
information regarding | 23 |
human behavior | 23 |
viral particles | 23 |
pandemic outbreak | 23 |
alcohol abuse | 23 |
consent form | 23 |
results may | 23 |
coronavirus covid | 23 |
become infected | 23 |
secondary school | 23 |
team sports | 23 |
computer vision | 23 |
suicidal ideation | 23 |
lopinavir ritonavir | 23 |
two categories | 23 |
lean methodology | 23 |
immune response | 23 |
tourist destinations | 23 |
statistical power | 23 |
environment information | 23 |
front pages | 23 |
one year | 23 |
operating rooms | 23 |
focused coping | 23 |
work ability | 23 |
health science | 23 |
public awareness | 23 |
autism spectrum | 23 |
positive cases | 23 |
income losses | 23 |
january january | 23 |
sectional design | 23 |
based hand | 23 |
ace receptor | 23 |
observed among | 23 |
code policy | 23 |
social sector | 22 |
policy effectiveness | 22 |
family need | 22 |
moderating effect | 22 |
health organisation | 22 |
high ps | 22 |
psychosocial risks | 22 |
death cases | 22 |
urban agglomerations | 22 |
close proximity | 22 |
environmental quality | 22 |
seriously affected | 22 |
snap participation | 22 |
healthcare facility | 22 |
coping behaviors | 22 |
dental professionals | 22 |
mediation effect | 22 |
dependent variables | 22 |
infected pneumonia | 22 |
differences among | 22 |
stress scores | 22 |
body weight | 22 |
hand sanitizer | 22 |
daily number | 22 |
health symptoms | 22 |
healthcare staff | 22 |
normally distributed | 22 |
healthcare access | 22 |
use disorders | 22 |
knowledge score | 22 |
individual level | 22 |
korean government | 22 |
five studies | 22 |
zhejiang province | 22 |
early life | 22 |
symptoms among | 22 |
respiratory viral | 22 |
directly related | 22 |
final model | 22 |
related weibos | 22 |
environmental impacts | 22 |
traditional chinese | 22 |
exploratory study | 22 |
behavioral intentions | 22 |
factors among | 22 |
group memberships | 22 |
may include | 22 |
spanish government | 22 |
training sessions | 22 |
chinese social | 22 |
sasa scores | 22 |
main reasons | 22 |
google forms | 22 |
hospital admission | 22 |
cruise ships | 22 |
higher number | 22 |
search engines | 22 |
supply chain | 22 |
studies show | 22 |
indirect contact | 22 |
electric scooters | 22 |
great importance | 22 |
chi chuan | 22 |
remote areas | 22 |
pharmaceutical interventions | 22 |
high degree | 22 |
transmission routes | 22 |
problematic usage | 22 |
simulation model | 22 |
improve health | 22 |
variables included | 22 |
community members | 22 |
york city | 22 |
study provides | 22 |
social contact | 22 |
life course | 22 |
environmental conditions | 22 |
via social | 22 |
toward organic | 22 |
various types | 22 |
among students | 22 |
medical institutions | 22 |
pregnant women | 22 |
disease detection | 22 |
ehealth literacy | 22 |
patient safety | 22 |
public concern | 22 |
natural disasters | 22 |
proposed algorithm | 22 |
survey responses | 22 |
health indicators | 21 |
care units | 21 |
severe anxiety | 21 |
viral transmission | 21 |
single case | 21 |
high percentage | 21 |
waiting room | 21 |
control variables | 21 |
may vary | 21 |
health belief | 21 |
onset week | 21 |
dose pm | 21 |
general practitioners | 21 |
elderly care | 21 |
training program | 21 |
principal component | 21 |
scientific literature | 21 |
like illness | 21 |
mediation model | 21 |
perceived ease | 21 |
urgent dental | 21 |
therapeutic outcomes | 21 |
use technology | 21 |
suspected covid | 21 |
northern italy | 21 |
word vector | 21 |
research shows | 21 |
private housing | 21 |
key factors | 21 |
indigenous people | 21 |
best performance | 21 |
workers exposed | 21 |
private sector | 21 |
physical activities | 21 |
younger generations | 21 |
data set | 21 |
psychological impacts | 21 |
severe cases | 21 |
search terms | 21 |
quality index | 21 |
fatality rates | 21 |
food availability | 21 |
behavior among | 21 |
chinese people | 21 |
urban area | 21 |
seven days | 21 |
social connectedness | 21 |
social desirability | 21 |
medical university | 21 |
population flow | 21 |
risk groups | 21 |
social development | 21 |
skin temperature | 21 |
data source | 21 |
wuhan municipal | 21 |
month follow | 21 |
environmental risk | 21 |
significantly correlated | 21 |
component analysis | 21 |
urban green | 21 |
syrian refugees | 21 |
installing partitions | 21 |
four categories | 21 |
may cause | 21 |
life events | 21 |
may contribute | 21 |
first covid | 21 |
water quality | 21 |
new information | 21 |
three items | 21 |
public policy | 21 |
also need | 21 |
showed significant | 21 |
south african | 21 |
model parameters | 21 |
stress scale | 21 |
seafood market | 21 |
large numbers | 21 |
world bank | 21 |
past week | 21 |
new year | 21 |
land use | 21 |
asian countries | 21 |
meteorological factors | 21 |
identity strength | 21 |
zip code | 21 |
assess whether | 21 |
human resource | 21 |
respiratory infection | 21 |
activity levels | 21 |
highest level | 21 |
sustainable urban | 21 |
rolling sequence | 21 |
continuous variables | 21 |
crowded places | 21 |
value areas | 20 |
problematic pornography | 20 |
hiv aids | 20 |
hospital admissions | 20 |
related behaviors | 20 |
psychological consequences | 20 |
numerical value | 20 |
china covid | 20 |
international tourism | 20 |
numerous studies | 20 |
interpersonal relationships | 20 |
host cell | 20 |
four dimensions | 20 |
one week | 20 |
qualitative research | 20 |
travel health | 20 |
eating behavior | 20 |
adaptive perfectionists | 20 |
standard deviations | 20 |
population health | 20 |
representative sample | 20 |
among dentists | 20 |
cumulative number | 20 |
human immunodeficiency | 20 |
health aspects | 20 |
study using | 20 |
person transmission | 20 |
functional interactivity | 20 |
civic engagement | 20 |
outgroup morality | 20 |
may provide | 20 |
local communities | 20 |
different groups | 20 |
study investigated | 20 |
security status | 20 |
becoming infected | 20 |
may influence | 20 |
old age | 20 |
clinical manifestations | 20 |
maximum likelihood | 20 |
long time | 20 |
adverse health | 20 |
vulnerable populations | 20 |
injunctive norms | 20 |
environmental impact | 20 |
root causes | 20 |
three days | 20 |
future directions | 20 |
safety measures | 20 |
personal protection | 20 |
fine particulate | 20 |
poor sleep | 20 |
four items | 20 |
training data | 20 |
high identification | 20 |
second biennium | 20 |
special attention | 20 |
knowledge translation | 20 |
dry cough | 20 |
physical frailty | 20 |
school children | 20 |
based model | 20 |
substance abuse | 20 |
behaviors among | 20 |
table summarizes | 20 |
negative impacts | 20 |
google scholar | 20 |
domestic violence | 20 |
migration attention | 20 |
immunodeficiency virus | 20 |
minority groups | 20 |
employee voice | 20 |
education teachers | 20 |
one another | 20 |
next step | 20 |
psychological needs | 20 |
health personnel | 20 |
active cases | 20 |
randomized clinical | 20 |
nationwide survey | 20 |
wind speed | 20 |
potential risk | 20 |
study group | 20 |
adjusted odds | 20 |
reported physical | 20 |
significant associations | 20 |
toward epidemic | 20 |
infection among | 20 |
chinese version | 20 |
internet use | 20 |
particulate air | 20 |
previous literature | 20 |
large proportion | 20 |
quality care | 20 |
descriptive study | 20 |
health center | 20 |
customer voice | 20 |
chinese cities | 20 |
us states | 20 |
power analysis | 20 |
frontline paramedics | 20 |
target population | 20 |
four types | 20 |
community level | 20 |
total deaths | 20 |
descriptive analysis | 20 |
cov incidence | 19 |
pay attention | 19 |
spanish population | 19 |
limited number | 19 |
high incidence | 19 |
questionnaire survey | 19 |
social participation | 19 |
smoking status | 19 |
kata teams | 19 |
princess cruise | 19 |
healthcare personnel | 19 |
physical disorder | 19 |
mosque closures | 19 |
contact history | 19 |
significant negative | 19 |
volatile oil | 19 |
higher prevalence | 19 |
metropolitan area | 19 |
health sciences | 19 |
significant changes | 19 |
future covid | 19 |
health policies | 19 |
public healthcare | 19 |
negative pressure | 19 |
clinical course | 19 |
breathing difficulties | 19 |
news items | 19 |
emergency management | 19 |
mild symptoms | 19 |
using different | 19 |
worth noting | 19 |
analytic review | 19 |
scooter users | 19 |
currency exchange | 19 |
care systems | 19 |
respiratory system | 19 |
anxiety symptoms | 19 |
moving means | 19 |
widespread covid | 19 |
leading cause | 19 |
street view | 19 |
study may | 19 |
five times | 19 |
sleep duration | 19 |
nucleic acid | 19 |
case studies | 19 |
clinical training | 19 |
natural environment | 19 |
explanatory power | 19 |
information provided | 19 |
bcg vaccination | 19 |
last days | 19 |
total hospital | 19 |
social welfare | 19 |
slirds model | 19 |
occupational exposure | 19 |
studies used | 19 |
factors like | 19 |
clinical data | 19 |
primary prevention | 19 |
physical exercise | 19 |
different cities | 19 |
multiple linear | 19 |
group countries | 19 |
vehicle routing | 19 |
food production | 19 |
information dissemination | 19 |
last year | 19 |
perceived personal | 19 |
take place | 19 |
practices towards | 19 |
new method | 19 |
hoc test | 19 |
will keep | 19 |
psychological support | 19 |
different research | 19 |
path analysis | 19 |
yangtze river | 19 |
critical review | 19 |
social behavior | 19 |
three cities | 19 |
colorectal cancer | 19 |
infected person | 19 |
surgical suite | 19 |
based survey | 19 |
research model | 19 |
mortality due | 19 |
asked participants | 19 |
international concern | 19 |
depression scale | 19 |
child development | 19 |
health organizations | 19 |
early detection | 19 |
migration population | 19 |
longitudinal studies | 19 |
control policies | 19 |
social impact | 19 |
response variable | 19 |
chinese center | 19 |
detailed information | 19 |
thromboembolic diseases | 19 |
service quality | 19 |
negative correlation | 19 |
direct medical | 19 |
open data | 19 |
different health | 19 |
using three | 19 |
confirmatory factor | 19 |
product innovation | 19 |
surface stability | 19 |
economic crisis | 19 |
search radius | 19 |
cancer screening | 19 |
less frequently | 19 |
movement behaviors | 19 |
convergent validity | 19 |
parihs framework | 19 |
volatile basil | 19 |
several factors | 19 |
disease burden | 19 |
side effects | 19 |
empirical study | 19 |
pornography use | 19 |
listening guide | 19 |
wore masks | 19 |
transport stations | 19 |
disabled elderly | 19 |
greater life | 19 |
test data | 19 |
influenza surveillance | 19 |
job opportunities | 19 |
seeking help | 19 |
monitoring stations | 19 |
healthy ageing | 19 |
item scale | 19 |
good health | 19 |
may become | 19 |
ambient air | 19 |
information sources | 19 |
medical facilities | 19 |
empirical studies | 19 |
linear relationship | 19 |
relative risk | 18 |
also investigated | 18 |
training set | 18 |
local food | 18 |
large sample | 18 |
exploratory factor | 18 |
university hospital | 18 |
district office | 18 |
among individuals | 18 |
particle size | 18 |
low self | 18 |
pain management | 18 |
accessible tourism | 18 |
public perceptions | 18 |
virus testing | 18 |
last years | 18 |
composite score | 18 |
independent variable | 18 |
measures taken | 18 |
research areas | 18 |
nutritional status | 18 |
prospective study | 18 |
emotional responses | 18 |
normal weight | 18 |
influencing infectious | 18 |
small number | 18 |
different aspects | 18 |
systems thinking | 18 |
countries around | 18 |
human body | 18 |
direct delivery | 18 |
causality test | 18 |
wuhan pneumonia | 18 |
transmission function | 18 |
policy implementation | 18 |
frequently used | 18 |
higher among | 18 |
compartmental models | 18 |
retrospective study | 18 |
cases reported | 18 |
anxiety among | 18 |
literacy research | 18 |
search queries | 18 |
practiced pa | 18 |
high mortality | 18 |
language processing | 18 |
low compliance | 18 |
task force | 18 |
toward game | 18 |
three years | 18 |
policy evolution | 18 |
epidemic spread | 18 |
statistical methods | 18 |
pandemic perception | 18 |
ophthalmic nurses | 18 |
differential equations | 18 |
latent variables | 18 |
school students | 18 |
younger people | 18 |
disease dynamics | 18 |
vaccine coverage | 18 |
will require | 18 |
different areas | 18 |
last months | 18 |
negatively correlated | 18 |
race ethnicity | 18 |
younger family | 18 |
practical implications | 18 |
spread rapidly | 18 |
isolation measures | 18 |
epidemic peak | 18 |
coronavirus infections | 18 |
spss version | 18 |
two independent | 18 |
disaster risk | 18 |
psychological wellbeing | 18 |
study revealed | 18 |
main reason | 18 |
needs assessment | 18 |
crucial role | 18 |
institution accounts | 18 |
boutique fitness | 18 |
sleep disturbances | 18 |
related weibo | 18 |
sierra leone | 18 |
cross sectional | 18 |
word embedding | 18 |
financial crisis | 18 |
national survey | 18 |
web accessibility | 18 |
logistic growth | 18 |
among medical | 18 |
airport screening | 18 |
largest number | 18 |
tuberculosis infection | 18 |
also associated | 18 |
disease confirmation | 18 |
incidence rates | 18 |
seasonal variations | 18 |
cardiovascular diseases | 18 |
square error | 18 |
scientific community | 18 |
three factors | 18 |
exposed individuals | 18 |
different forms | 18 |
total variance | 18 |
consumer buying | 18 |
similar pandemic | 18 |
low identification | 18 |
public reaction | 18 |
different stages | 18 |
distress symptoms | 18 |
will provide | 18 |
academic performance | 18 |
interpersonal communication | 18 |
study examined | 18 |
variables used | 18 |
social care | 18 |
belief model | 18 |
frontline healthcare | 18 |
facial skin | 18 |
public open | 17 |
basic psychological | 17 |
i will | 17 |
will lead | 17 |
mean value | 17 |
life scale | 17 |
improving health | 17 |
influenza vaccination | 17 |
paper aims | 17 |
first half | 17 |
tobacco smoking | 17 |
mean absolute | 17 |
rabies vaccine | 17 |
stress level | 17 |
sari cases | 17 |
test set | 17 |
made available | 17 |
search keywords | 17 |
support services | 17 |
lived experience | 17 |
social inclusion | 17 |
contact rates | 17 |
many aspects | 17 |
many cases | 17 |
tobacco treatment | 17 |
put forward | 17 |
contact matrix | 17 |
first biennium | 17 |
extended family | 17 |
water samples | 17 |
lower risk | 17 |
relatively small | 17 |
also asked | 17 |
scarlet fever | 17 |
viral respiratory | 17 |
model fit | 17 |
osh professionals | 17 |
three types | 17 |
patient care | 17 |
epidemic dynamics | 17 |
deeper understanding | 17 |
negative effect | 17 |
disease risk | 17 |
direct impact | 17 |
inflammatory markers | 17 |
equation model | 17 |
minimum unit | 17 |
physical environment | 17 |
pandemic crisis | 17 |
work nurses | 17 |
frontline doctors | 17 |
lung injury | 17 |
missing values | 17 |
important risk | 17 |
citation networks | 17 |
food products | 17 |
dog owners | 17 |
high rates | 17 |
increasing number | 17 |
disease information | 17 |
related injuries | 17 |
academic year | 17 |
promotion programs | 17 |
icu beds | 17 |
different scenarios | 17 |
partial least | 17 |
accurate information | 17 |
data used | 17 |
studies using | 17 |
healthcare assistance | 17 |
east area | 17 |
study reported | 17 |
life balance | 17 |
studies investigating | 17 |
many factors | 17 |
dwelling older | 17 |
ill patients | 17 |
sexual orientation | 17 |
rate among | 17 |
outbreak control | 17 |
first cases | 17 |
average bdi | 17 |
risk reduction | 17 |
analysis using | 17 |
among roma | 17 |
moderated mediation | 17 |
five items | 17 |
face mask | 17 |
hand sanitizers | 17 |
epithelial cells | 17 |
vocational colleges | 17 |
wp consumption | 17 |
also provides | 17 |
patient experience | 17 |
digital health | 17 |
spearman correlation | 17 |
diseases related | 17 |
closely linked | 17 |
studies published | 17 |
social connections | 17 |
icu admissions | 17 |
positive correlations | 17 |
behavioral changes | 17 |
last two | 17 |
google street | 17 |
patients admitted | 17 |
directly delivered | 17 |
hwaseong fortress | 17 |
information behavior | 17 |
two nodes | 17 |
policy implications | 17 |
pandemic will | 17 |
perceived health | 17 |
social science | 17 |
sail order | 17 |
starting point | 17 |
dependent risk | 17 |
local disaster | 17 |
instrumental support | 17 |
labour force | 17 |
cases identified | 17 |
first days | 17 |
physical distance | 17 |
deaths due | 17 |
higher self | 17 |
eating habits | 17 |
environmental variables | 17 |
proactive personality | 17 |
front page | 17 |
best practices | 17 |
dry air | 17 |
traumatic events | 17 |
information systems | 17 |
rating scale | 17 |
used data | 17 |
environmental influences | 17 |
using google | 17 |
increased use | 17 |
ethical approval | 17 |
physical inactivity | 17 |
health disorders | 17 |
random sampling | 17 |
entire population | 17 |
pig farmer | 17 |
urban development | 17 |
hubei provincial | 17 |
research priorities | 17 |
health strategies | 17 |
uv radiation | 17 |
survey respondents | 17 |
tb infection | 17 |
social cure | 17 |
less time | 17 |
consumer behavior | 16 |
little influence | 16 |
average variance | 16 |
professional experience | 16 |
surveillance data | 16 |
musculoskeletal pain | 16 |
safety incidents | 16 |
may play | 16 |
measurement items | 16 |
may experience | 16 |
online platforms | 16 |
severe pneumonia | 16 |
social insurance | 16 |
nervous system | 16 |
multivariable logistic | 16 |
pathogen source | 16 |
new south | 16 |
social contacts | 16 |
prejudice towards | 16 |
content validity | 16 |
water supply | 16 |
compartmental model | 16 |
safety issues | 16 |
science research | 16 |
mint oil | 16 |
problematic social | 16 |
nonfarmworker sample | 16 |
relevant studies | 16 |
inflammatory response | 16 |
primary data | 16 |
positive attitudes | 16 |
mental well | 16 |
distance psychological | 16 |
news coverage | 16 |
see appendix | 16 |
pool water | 16 |
electronic health | 16 |
population data | 16 |
common cold | 16 |
study variables | 16 |
open science | 16 |
current evidence | 16 |
cognitive behavioral | 16 |
pandemic risk | 16 |
study shows | 16 |
questions related | 16 |
stress management | 16 |
centred care | 16 |
medical cost | 16 |
tourism destination | 16 |
nighttime light | 16 |
additional infection | 16 |
cases increased | 16 |
human rights | 16 |
like covid | 16 |
healthy life | 16 |
essential services | 16 |
distance caregiver | 16 |
job stress | 16 |
bet index | 16 |
population groups | 16 |
remote communication | 16 |
local community | 16 |
four days | 16 |
taking care | 16 |
negative health | 16 |
explanatory variables | 16 |
specific health | 16 |
intellectual disabilities | 16 |
learning models | 16 |
capacitated vehicle | 16 |
national documents | 16 |
future pandemics | 16 |
reported pa | 16 |
healthcare service | 16 |
findings indicate | 16 |
reported higher | 16 |
safer destinations | 16 |
recent advances | 16 |
highly contagious | 16 |
four studies | 16 |
volatile mint | 16 |
tourism crisis | 16 |
important age | 16 |
analysis revealed | 16 |
usual care | 16 |
significant risk | 16 |
total covid | 16 |
critical care | 16 |
primary outcome | 16 |
public buildings | 16 |
age range | 16 |
meat consumption | 16 |
early diagnosis | 16 |
burkina faso | 16 |
social policies | 16 |
causal relationship | 16 |
comparative analysis | 16 |
collect data | 16 |
necessary measures | 16 |
northern hemisphere | 16 |
mood disorders | 16 |
management strategies | 16 |
pandemic may | 16 |
aerosol transmission | 16 |
thematic analysis | 16 |
international public | 16 |
secondary data | 16 |
economic implications | 16 |
dietary intake | 16 |
tb cases | 16 |
significant influence | 16 |
index return | 16 |
global spread | 16 |
qualitative studies | 16 |
flight shutdowns | 16 |
many participants | 16 |
human subjects | 16 |
least three | 16 |
environmental cleaning | 16 |
working alliance | 16 |
demographic factors | 16 |
italian regions | 16 |
narx neural | 16 |
mental stress | 16 |
sodium alginate | 16 |
middle school | 16 |
adult children | 16 |
virus spread | 16 |
italian government | 16 |
outcome measure | 16 |
viral shedding | 16 |
door openings | 16 |
almost half | 16 |
cent among | 16 |
allows us | 16 |
resilience scale | 16 |
forest therapy | 16 |
protection measures | 16 |
previous findings | 16 |
time step | 16 |
lower level | 16 |
medical workers | 16 |
sf scores | 16 |
spatial analysis | 16 |
education class | 16 |
rest areas | 16 |
government response | 16 |
entrepreneurship education | 16 |
depression symptoms | 16 |
use fitness | 16 |
first aid | 16 |
mask wearing | 16 |
among frontline | 16 |
early lockdown | 16 |
influenza epidemics | 16 |
inclusive research | 16 |
per patient | 16 |
employees stuck | 16 |
see section | 16 |
exposure time | 16 |
spss inc | 15 |
dental team | 15 |
research participants | 15 |
control sample | 15 |
wastewater workers | 15 |
search strategy | 15 |
instrumental social | 15 |
negative attitudes | 15 |
occupational stress | 15 |
study protocol | 15 |
cigarette smoking | 15 |
snowball sampling | 15 |
spatial accessibility | 15 |
greater influence | 15 |
research ethics | 15 |
social sciences | 15 |
hemorrhagic fever | 15 |
resistance genes | 15 |
intestinal parasites | 15 |
drug abuse | 15 |
regional differences | 15 |
making process | 15 |
limited access | 15 |
leisure activities | 15 |
public will | 15 |
developed symptoms | 15 |
daily activities | 15 |
swine flu | 15 |
zika virus | 15 |
among female | 15 |
intermediate hosts | 15 |
chinese new | 15 |
common colds | 15 |
per deaths | 15 |
new section | 15 |
license funding | 15 |
human activities | 15 |
times higher | 15 |
medical research | 15 |
research results | 15 |
primary outcomes | 15 |
respiratory virus | 15 |
moderating effects | 15 |
intergenerational relationships | 15 |
farmworker sample | 15 |
local public | 15 |
also help | 15 |
suicide attempts | 15 |
significant factors | 15 |
rapid increase | 15 |
awareness knowledge | 15 |
study indicated | 15 |
outside hubei | 15 |
prohibitive voice | 15 |
significantly increased | 15 |
air conditioning | 15 |
loved ones | 15 |
key factor | 15 |
first phase | 15 |
disease study | 15 |
linear correlation | 15 |
supplementary section | 15 |
solar radiation | 15 |
ntpc government | 15 |
decision makers | 15 |
lowest rmse | 15 |
infected individual | 15 |
related aspects | 15 |
new technology | 15 |
historical data | 15 |
empirical findings | 15 |
post covid | 15 |
life among | 15 |
source bed | 15 |
pornography usage | 15 |
healthy south | 15 |
charitable organizations | 15 |
least two | 15 |
cases will | 15 |
environmental determinants | 15 |
heart failure | 15 |
conditioning systems | 15 |
among college | 15 |
issues related | 15 |
assessment tool | 15 |
gender difference | 15 |
severe disease | 15 |
percentage error | 15 |
health implications | 15 |
environmental drivers | 15 |
european centre | 15 |
negatively related | 15 |
study will | 15 |
using technology | 15 |
home working | 15 |
cell phone | 15 |
world trade | 15 |
mental distress | 15 |
factors may | 15 |
staff working | 15 |
minimum threshold | 15 |
different models | 15 |
influenza transmission | 15 |
migration reasons | 15 |
ventilation system | 15 |
recovery rate | 15 |
case report | 15 |
social marketing | 15 |
promotive voice | 15 |
international health | 15 |
two decades | 15 |
keep buying | 15 |
take part | 15 |
study included | 15 |
elite soccer | 15 |
human coronaviruses | 15 |
major cities | 15 |
spatial relatedness | 15 |
suspected patients | 15 |
higher lbp | 15 |
two separate | 15 |
cryptosporidium spp | 15 |
internet search | 15 |
social environment | 15 |
public safety | 15 |
communication technologies | 15 |
maximum number | 15 |
related questions | 15 |
population living | 15 |
among nursing | 15 |
two thirds | 15 |
may occur | 15 |
suicide risk | 15 |
considered statistically | 15 |
general characteristics | 15 |
ant colony | 15 |
inanimate surfaces | 15 |
motor vehicles | 15 |
prevention methods | 15 |
lower compared | 15 |
direct exposure | 15 |
crisis communication | 15 |
stress among | 15 |
individual resilience | 15 |
disease caused | 15 |
stochastic approach | 15 |
survey questionnaire | 15 |
also show | 15 |
vice versa | 15 |
locally acquired | 15 |
future work | 15 |
implementation process | 15 |
twitter users | 15 |
food environment | 15 |
inflection point | 15 |
studies focused | 15 |
older generations | 15 |
marketing strategies | 15 |
highly educated | 15 |
climatic conditions | 15 |
central area | 15 |
food handlers | 15 |
victim blaming | 15 |
zip codes | 15 |
causal relationships | 15 |
severe mental | 15 |
forest environments | 15 |
four factors | 15 |
network structure | 15 |
average score | 15 |
higher perceived | 15 |
iddp process | 15 |
contact rate | 15 |
north carolina | 15 |
rolling grey | 15 |
amoebic self | 15 |
several aspects | 15 |
infectious individuals | 15 |
clinical work | 15 |
outlet locations | 15 |
future challenges | 15 |
research methods | 15 |
high perceived | 15 |
injunctive norm | 15 |
financial resources | 15 |
high correlation | 15 |
increased ventilation | 15 |
measures implemented | 15 |
mobile phones | 15 |
economic factors | 15 |
stock markets | 15 |
economic losses | 15 |
physical demands | 15 |
health behaviours | 15 |
emotion regulation | 15 |
sedentary time | 15 |
moving average | 15 |
medical personnel | 15 |
expected number | 15 |
absolute percentage | 15 |
venous thromboembolism | 15 |
wp tobacco | 15 |
south wales | 15 |
identified via | 15 |
pornography viewing | 15 |
protecting health | 15 |
coastal areas | 15 |
regarding covid | 15 |
pittsburgh sleep | 15 |
psychological outcomes | 15 |
child nutrition | 15 |
epidemiological features | 15 |
ship employee | 15 |
predictive validity | 15 |
mean willingness | 15 |
sized enterprises | 15 |
one hospital | 15 |
news reports | 15 |
infection source | 14 |
general hospital | 14 |
regulatory styles | 14 |
income level | 14 |
psychotropic prescription | 14 |
susceptible individuals | 14 |
daily mortality | 14 |
natural resource | 14 |
resource management | 14 |
following section | 14 |
cov outbreak | 14 |
significant predictor | 14 |
four groups | 14 |
cognitive appraisal | 14 |
coronavirus crisis | 14 |
four years | 14 |
full text | 14 |
two cases | 14 |
tce intervention | 14 |
outcomes associated | 14 |
late lockdown | 14 |
contact patterns | 14 |
disease prediction | 14 |
low carbon | 14 |
time points | 14 |