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 | 432 |
health care | 431 |
granted medrxiv | 408 |
author funder | 408 |
copyright holder | 391 |
version posted | 349 |
confirmed cases | 348 |
social distancing | 323 |
made available | 311 |
international license | 297 |
novel coronavirus | 279 |
coronavirus disease | 257 |
medrxiv preprint | 211 |
cord uid | 206 |
doc id | 206 |
mental health | 201 |
world health | 197 |
reproduction number | 173 |
health organization | 168 |
peer review | 163 |
new cases | 163 |
active cases | 160 |
united states | 159 |
acute respiratory | 158 |
present study | 156 |
developing countries | 155 |
air quality | 149 |
air pollution | 146 |
infectious diseases | 145 |
total number | 142 |
posted may | 137 |
corona virus | 132 |
lockdown period | 130 |
positive cases | 130 |
respiratory syndrome | 130 |
west bengal | 125 |
per day | 124 |
risk factors | 123 |
growth rate | 122 |
time series | 116 |
monetary policy | 114 |
severe acute | 113 |
social media | 113 |
tamil nadu | 112 |
infected cases | 106 |
th march | 102 |
posted june | 100 |
incubation period | 100 |
hiv aids | 97 |
infectious disease | 92 |
uttar pradesh | 91 |
family welfare | 90 |
fatality rate | 89 |
mortality rate | 87 |
health services | 85 |
per cent | 85 |
large number | 84 |
recovered cases | 83 |
machine learning | 82 |
first case | 81 |
disease control | 80 |
urban areas | 80 |
containment measures | 79 |
avian influenza | 79 |
new delhi | 79 |
th may | 79 |
systematic review | 77 |
indian states | 77 |
recovery rate | 76 |
nationwide lockdown | 76 |
disease transmission | 75 |
healthcare system | 74 |
case fatality | 74 |
population density | 73 |
exponential growth | 72 |
backyard poultry | 72 |
preventive measures | 71 |
doubling time | 71 |
sir model | 71 |
th april | 70 |
food security | 69 |
infection rate | 68 |
reported cases | 68 |
contact tracing | 68 |
transmission dynamics | 68 |
migrant workers | 68 |
basic reproduction | 68 |
care system | 67 |
andhra pradesh | 66 |
income countries | 66 |
private sector | 66 |
susceptible population | 66 |
south korea | 65 |
backyard flocks | 65 |
linear regression | 65 |
syndrome coronavirus | 64 |
best fit | 64 |
control measures | 63 |
natural products | 63 |
hemorrhagic fever | 62 |
questionable content | 62 |
new york | 61 |
mathematical model | 61 |
data set | 61 |
high risk | 60 |
nan doi | 60 |
different states | 60 |
india date | 60 |
rural areas | 60 |
across india | 59 |
many countries | 59 |
diabetes mellitus | 59 |
health system | 58 |
middle east | 57 |
infected individuals | 57 |
madhya pradesh | 57 |
type diabetes | 57 |
glycemic control | 56 |
personal protective | 56 |
global health | 56 |
medical research | 56 |
tb burden | 56 |
health conditions | 56 |
will help | 56 |
will also | 55 |
countries like | 55 |
mortality rates | 54 |
icu beds | 54 |
mathematical models | 54 |
among children | 54 |
transmission rate | 54 |
river ganga | 54 |
allowed without | 54 |
virus infection | 53 |
growth curve | 53 |
seir model | 53 |
protective equipment | 53 |
reuse allowed | 53 |
death rate | 53 |
without permission | 53 |
human health | 52 |
pregnant women | 52 |
healthcare professionals | 52 |
covid pandemic | 52 |
health workers | 52 |
data analysis | 51 |
rights reserved | 51 |
cumulative number | 51 |
till may | 51 |
water quality | 50 |
leaf curl | 50 |
tb incidence | 50 |
general public | 50 |
chandipura virus | 49 |
containment zones | 49 |
relative humidity | 49 |
lockdown relaxation | 49 |
national lockdown | 49 |
age group | 48 |
novel corona | 48 |
per capita | 48 |
posted july | 48 |
indian context | 48 |
infection peak | 48 |
real time | 48 |
developed countries | 48 |
arima model | 47 |
deep learning | 47 |
th june | 47 |
intensive care | 47 |
data collection | 47 |
like india | 46 |
available data | 46 |
essential oils | 46 |
regression model | 45 |
modelling study | 45 |
indian government | 45 |
climate change | 45 |
per million | 45 |
lockdown measures | 45 |
authors declare | 44 |
complete lockdown | 44 |
real data | 44 |
india using | 44 |
infected population | 44 |
primary health | 44 |
psychological impact | 44 |
general population | 44 |
asian countries | 44 |
artificial intelligence | 44 |
may also | 44 |
health systems | 44 |
community transmission | 43 |
million people | 43 |
health facilities | 43 |
coronavirus pandemic | 43 |
health problems | 43 |
will require | 43 |
children aged | 43 |
case study | 43 |
media reports | 43 |
total population | 43 |
infected person | 42 |
tb services | 42 |
amino acid | 42 |
media reporting | 42 |
higher risk | 42 |
effective reproduction | 42 |
respiratory viruses | 42 |
syncytial virus | 42 |
regression analysis | 42 |
cases per | 41 |
th day | 41 |
even though | 41 |
moving average | 41 |
supply chains | 41 |
supply chain | 41 |
lockdown phase | 41 |
neem oil | 41 |
confirmed covid | 41 |
different countries | 41 |
time period | 41 |
drug users | 40 |
see table | 40 |
long term | 40 |
healthcare workers | 40 |
sample size | 40 |
particulate matter | 40 |
zika virus | 40 |
policy makers | 39 |
respiratory syncytial | 39 |
daily new | 39 |
average number | 39 |
congo hemorrhagic | 39 |
blood glucose | 39 |
community health | 39 |
clinical trials | 38 |
united nations | 38 |
health infrastructure | 38 |
national institute | 38 |
sex workers | 38 |
blood pressure | 38 |
risk factor | 38 |
wind speed | 38 |
hospital beds | 37 |
coronavirus cases | 37 |
viral diseases | 37 |
poster sessions | 37 |
doubling rate | 37 |
affected countries | 37 |
neem cake | 37 |
th january | 37 |
chain reaction | 37 |
health status | 37 |
march th | 37 |
indian council | 37 |
respiratory infections | 37 |
polymerase chain | 37 |
major cities | 37 |
state governments | 36 |
indian cities | 36 |
human rights | 36 |
may lead | 36 |
series data | 36 |
standard deviation | 36 |
cases reported | 36 |
south asia | 36 |
confirmed case | 36 |
respiratory tract | 36 |
asymptomatic cases | 36 |
among people | 36 |
important role | 36 |
health emergency | 35 |
influenza virus | 35 |
indoor air | 35 |
logistic growth | 35 |
fever virus | 35 |
herd immunity | 35 |
health centre | 35 |
gut microbiota | 34 |
sird model | 34 |
local governments | 34 |
tertiary care | 34 |
national health | 34 |
total confirmed | 34 |
prime minister | 34 |
statistical analysis | 34 |
plasmodium vivax | 34 |
pandemic influenza | 34 |
case studies | 34 |
age groups | 34 |
infected patients | 34 |
parameter values | 34 |
coronavirus outbreak | 34 |
social security | 34 |
exponential smoothing | 33 |
critical care | 33 |
highly pathogenic | 33 |
different parts | 33 |
early detection | 33 |
epidemiological models | 33 |
pandemic situation | 33 |
pharmaceutical interventions | 33 |
people living | 33 |
east asia | 33 |
supplementary material | 33 |
disease spread | 33 |
primary care | 33 |
confidence interval | 33 |
waste management | 33 |
infection control | 33 |
young children | 33 |
phylogenetic analysis | 33 |
indian population | 33 |
health promotion | 33 |
key informants | 33 |
affected states | 32 |
absolute humidity | 32 |
vivax malaria | 32 |
fake news | 32 |
cases will | 32 |
cohort study | 32 |
strict lockdown | 32 |
infected individual | 32 |
near future | 32 |
respiratory virus | 32 |
viral rna | 32 |
azadirachta indica | 32 |
india covid | 32 |
daily cases | 32 |
publicly available | 31 |
statistically significant | 31 |
short term | 31 |
north india | 31 |
many people | 31 |
backyard birds | 31 |
recovery time | 31 |
first time | 31 |
current situation | 31 |
communicable diseases | 31 |
aged years | 31 |
death cases | 31 |
covid india | 31 |
potential impact | 31 |
genome sequences | 30 |
health interventions | 30 |
infected people | 30 |
health professionals | 30 |
recent years | 30 |
also observed | 30 |
food insecurity | 30 |
serial interval | 30 |
wide range | 30 |
health outcomes | 30 |
also reported | 30 |
study period | 30 |
model parameters | 30 |
differential equations | 30 |
tomato leaf | 30 |
plasmodium falciparum | 30 |
medical care | 30 |
european countries | 30 |
global pandemic | 30 |
immune response | 30 |
contact rate | 30 |
sustainable development | 30 |
physical distancing | 30 |
world bank | 29 |
highest number | 29 |
genomic medicine | 29 |
sequence analysis | 29 |
performed using | 29 |
health needs | 29 |
also used | 29 |
indian state | 29 |
based approach | 29 |
least one | 29 |
india will | 29 |
health policy | 29 |
national level | 29 |
food system | 29 |
community spread | 29 |
care workers | 29 |
respiratory distress | 29 |
symptomatic cases | 29 |
universal health | 29 |
travel history | 29 |
urban health | 29 |
respiratory illness | 28 |
direct cost | 28 |
higher education | 28 |
southeast asia | 28 |
clinical samples | 28 |
food systems | 28 |
central government | 28 |
nipah virus | 28 |
maximum number | 28 |
health issues | 28 |
total cases | 28 |
widely used | 28 |
increased risk | 28 |
current study | 28 |
face masks | 28 |
deceased cases | 28 |
drug use | 28 |
drinking water | 28 |
isolation beds | 28 |
support vector | 28 |
supplementary table | 28 |
neural network | 27 |
socioeconomic status | 27 |
economic growth | 27 |
risk assessment | 27 |
regression models | 27 |
electron microscopy | 27 |
respiratory disease | 27 |
data points | 27 |
various countries | 27 |
health organisation | 27 |
will provide | 27 |
care services | 27 |
air pollutants | 27 |
infected persons | 27 |
cumulative cases | 27 |
also found | 27 |
repo rate | 27 |
clinical features | 27 |
tests per | 27 |
virus disease | 27 |
study also | 27 |
medical students | 27 |
serum samples | 27 |
testing rate | 27 |
th july | 27 |
viral infections | 27 |
well known | 26 |
celebrity suicide | 26 |
social support | 26 |
environmental factors | 26 |
social justice | 26 |
animal health | 26 |
situation report | 26 |
influenza viruses | 26 |
south africa | 26 |
street youth | 26 |
diabetes care | 26 |
severe covid | 26 |
air mass | 26 |
data protection | 26 |
clinical characteristics | 26 |
human society | 26 |
infection spread | 26 |
data collected | 26 |
disease progression | 26 |
local government | 26 |
substance use | 26 |
northern india | 26 |
nucleic acid | 26 |
study will | 26 |
human infection | 26 |
medical education | 26 |
viral genome | 26 |
climatic variables | 26 |
different regions | 26 |
tb deaths | 25 |
sensitivity analysis | 25 |
daily confirmed | 25 |
inner city | 25 |
second wave | 25 |
intervention strategies | 25 |
respiratory symptoms | 25 |
western india | 25 |
coronavirus lockdown | 25 |
urban poor | 25 |
east respiratory | 25 |
service providers | 25 |
travel restrictions | 25 |
increasing number | 25 |
policy rate | 25 |
disease prevention | 25 |
population health | 25 |
health coverage | 25 |
rural india | 25 |
backyard farming | 25 |
decision making | 25 |
proposed model | 25 |
spike protein | 25 |
state government | 25 |
will continue | 25 |
specific primers | 25 |
population size | 25 |
indian subcontinent | 25 |
may th | 25 |
study conducted | 25 |
malaria elimination | 25 |
average daily | 25 |
public sector | 25 |
new zealand | 25 |
coming days | 25 |
parainfluenza virus | 25 |
least square | 24 |
pathogenic avian | 24 |
mortality due | 24 |
eastern india | 24 |
capacity building | 24 |
generation time | 24 |
hong kong | 24 |
age range | 24 |
family members | 24 |
control strategies | 24 |
wide lockdown | 24 |
excess tb | 24 |
emerging infectious | 24 |
high population | 24 |
civil society | 24 |
thematic analysis | 24 |
high levels | 24 |
positive correlation | 24 |
long time | 24 |
health survey | 24 |
health centres | 24 |
years old | 24 |
increased testing | 24 |
policy framework | 24 |
informed consent | 24 |
medical facilities | 24 |
peak infection | 24 |
tb care | 24 |
exchange rate | 24 |
fatality rates | 24 |
tested positive | 23 |
posted april | 23 |
epidemiological data | 23 |
closely related | 23 |
clinical trial | 23 |
first covid | 23 |
human beings | 23 |
york city | 23 |
among patients | 23 |
april th | 23 |
severe disease | 23 |
cumulative confirmed | 23 |
lockdown periods | 23 |
human transmission | 23 |
borne diseases | 23 |
disease outbreaks | 23 |
factors associated | 23 |
disease burden | 23 |
reporting lag | 23 |
vaccine development | 23 |
extended closure | 23 |
mathematical modelling | 23 |
backyard chickens | 23 |
urgent need | 23 |
heart disease | 23 |
first two | 23 |
different types | 23 |
social contact | 23 |
newcastle disease | 22 |
large population | 22 |
lower respiratory | 22 |
methyl bromide | 22 |
day lockdown | 22 |
million population | 22 |
much higher | 22 |
power law | 22 |
india may | 22 |
time point | 22 |
fourth lockdown | 22 |
tb transmission | 22 |
new covid | 22 |
social capital | 22 |
urban fgd | 22 |
chemical composition | 22 |
union territories | 22 |
kidney disease | 22 |
data sets | 22 |
buffalopox virus | 22 |
severe malaria | 22 |
series analysis | 22 |
online learning | 22 |
till th | 22 |
united kingdom | 22 |
current crisis | 22 |
life cycle | 22 |
service delivery | 22 |
reverse transcription | 22 |
deaths due | 22 |
health crisis | 22 |
polynomial regression | 22 |
intellectual property | 22 |
economic impact | 22 |
total infected | 22 |
indirect cost | 22 |
economic burden | 22 |
disease surveillance | 22 |
close contact | 22 |
global burden | 22 |
also known | 22 |
relative risk | 22 |
trade unions | 21 |
essential oil | 21 |
natural environment | 21 |
amid covid | 21 |
first lockdown | 21 |
animal diseases | 21 |
series models | 21 |
conceptual model | 21 |
mental illness | 21 |
economic times | 21 |
future research | 21 |
model based | 21 |
several countries | 21 |
coronavirus infection | 21 |
physical activity | 21 |
densely populated | 21 |
per annum | 21 |
epidemiological model | 21 |
recent study | 21 |
gender equality | 21 |
may result | 21 |
time pcr | 21 |
active case | 21 |
human development | 21 |
hand washing | 21 |
analysis showed | 21 |
may help | 21 |
paraquat poisoning | 21 |
immune system | 21 |
infection growth | 21 |
saudi arabia | 21 |
virus spread | 21 |
distancing measures | 21 |
news reports | 21 |
ethics committee | 21 |
urban centres | 21 |
people will | 21 |
personal data | 21 |
ambient air | 21 |
meningococcal disease | 21 |
epidemiological characteristics | 21 |
healthcare facilities | 21 |
healthcare services | 21 |
presentation will | 21 |
phylogenetic tree | 21 |
health facility | 21 |
based models | 21 |
curve fitting | 20 |
present scenario | 20 |
public policy | 20 |
getting infected | 20 |
health risk | 20 |
early stages | 20 |
virus isolates | 20 |
health insurance | 20 |
post lockdown | 20 |
case numbers | 20 |
viral disease | 20 |
social services | 20 |
i th | 20 |
coronavirus covid | 20 |
time evolution | 20 |
till date | 20 |
commonly used | 20 |
nitrogen dioxide | 20 |
farming systems | 20 |
two different | 20 |
posterior distribution | 20 |
wuhan city | 20 |
fatality ratio | 20 |
local level | 20 |
virus outbreak | 20 |
face shields | 20 |
will need | 20 |
quality infrastructure | 20 |
mitigation strategies | 20 |
nd march | 20 |
symptomatic patients | 20 |
south india | 20 |
mosaic virus | 20 |
atmospheric pollutants | 20 |
hospitalized patients | 20 |
annual report | 20 |
disease virus | 20 |
new infections | 20 |
two countries | 20 |
care systems | 20 |
seasonal influenza | 20 |
hubei province | 20 |
low income | 20 |
contact rates | 20 |
upper ci | 20 |
current pandemic | 20 |
south asian | 20 |
help us | 20 |
significantly higher | 19 |
treatment outcomes | 19 |
lockdown phases | 19 |
reproductive number | 19 |
results suggest | 19 |
joinpoint regression | 19 |
higher rates | 19 |
corona positive | 19 |
homeless people | 19 |
affected people | 19 |
international concern | 19 |
coat protein | 19 |
dead body | 19 |
buffalo milk | 19 |
must also | 19 |
live attenuated | 19 |
family health | 19 |
western countries | 19 |
state level | 19 |
chim studies | 19 |
local health | 19 |
medical services | 19 |
towards covid | 19 |
economic activities | 19 |
bovine viral | 19 |
developing world | 19 |
daily number | 19 |
hiv infection | 19 |
care providers | 19 |
cardiovascular disease | 19 |
aids denial | 19 |
meningococcal meningitis | 19 |
confidence intervals | 19 |
significant increase | 19 |
hopkins university | 19 |
indian express | 19 |
genetic diversity | 19 |
posted august | 19 |
medical imaging | 19 |
literature review | 19 |
table shows | 19 |
medical college | 19 |
quality index | 19 |
previous studies | 19 |
interest rates | 19 |
test results | 19 |
large numbers | 19 |
indian region | 19 |
action plan | 19 |
various states | 19 |
transmission rates | 19 |
growth rates | 19 |
early stage | 19 |
pollution levels | 19 |
health intervention | 19 |
healthcare systems | 19 |
various aspects | 19 |
maximum temperature | 19 |
gut microbiome | 19 |
domestic violence | 19 |
results show | 19 |
average temperature | 19 |
lockdown restrictions | 19 |
research institute | 19 |
poor people | 19 |
india due | 19 |
better understanding | 19 |
life expectancy | 19 |
surveillance system | 19 |
influenza pandemic | 19 |
local transmission | 18 |
sampling locations | 18 |
kerala model | 18 |
severe cases | 18 |
actual data | 18 |
environmental conditions | 18 |
health sector | 18 |
mean temperature | 18 |
several studies | 18 |
power plants | 18 |
southern india | 18 |
conceptual framework | 18 |
health officials | 18 |
disease caused | 18 |
high humidity | 18 |
domestic animals | 18 |
less likely | 18 |
virus infections | 18 |
reported confirmed | 18 |
sars coronavirus | 18 |
risk groups | 18 |
competing interests | 18 |
adverse effects | 18 |
integrated moving | 18 |
health service | 18 |
first reported | 18 |
state income | 18 |
death toll | 18 |
developing country | 18 |
chronic diseases | 18 |
diseases like | 18 |
harm reduction | 18 |
spread across | 18 |
sectional study | 18 |
carrying capacity | 18 |
total infections | 18 |
infection rates | 18 |
high number | 18 |
haemorrhagic fever | 18 |
care facilities | 18 |
first week | 18 |
access control | 18 |
health risks | 18 |
economic activity | 18 |
maintain social | 18 |
information criterion | 18 |
highly contagious | 18 |
fruit bats | 18 |
end tb | 18 |
significantly associated | 18 |
better understand | 18 |
large scale | 18 |
conformity assessment | 18 |
census data | 18 |
recovery rates | 18 |
clinical symptoms | 17 |
development goals | 17 |
national average | 17 |
middle dot | 17 |
time rt | 17 |
focus group | 17 |
healthcare providers | 17 |
tb cases | 17 |
epidemic growth | 17 |
model also | 17 |
contagious disease | 17 |
social networks | 17 |
patients infected | 17 |
mortality risk | 17 |
significant impact | 17 |
economic status | 17 |
positive case | 17 |
distancing policies | 17 |
next days | 17 |
national capital | 17 |
actual number | 17 |
will increase | 17 |
local governance | 17 |
also important | 17 |
detailed analysis | 17 |
initial phase | 17 |
international travel | 17 |
states like | 17 |
vulnerable population | 17 |
young people | 17 |
significant association | 17 |
educational institutions | 17 |
personal relationships | 17 |
capita income | 17 |
human population | 17 |
mean age | 17 |
returning workers | 17 |
indian economy | 17 |
last days | 17 |
pandemic covid | 17 |
care cascade | 17 |
education system | 17 |
early phase | 17 |
analysis revealed | 17 |
minimum temperature | 17 |
disease dynamics | 17 |
reproduction numbers | 17 |
three countries | 17 |
focus groups | 17 |
information flow | 17 |
testing capacity | 17 |
billion people | 17 |
based study | 17 |
igm antibodies | 17 |
urban settings | 17 |
nutritional status | 17 |
san francisco | 17 |
coming months | 17 |
negative impact | 17 |
till now | 17 |
including india | 17 |
data till | 17 |
disease severity | 17 |
springer nature | 17 |
time points | 17 |
burden countries | 17 |
current trend | 17 |
incidence data | 17 |
logistic model | 17 |
phase ii | 17 |
food production | 17 |
research project | 17 |
many cases | 17 |
poverty line | 17 |
low cost | 17 |
sulfuryl fluoride | 17 |
rice tungro | 17 |
cervical cancer | 17 |
findings suggest | 17 |
another study | 17 |
small number | 17 |
data obtained | 16 |
detection rate | 16 |
severe respiratory | 16 |
calculated using | 16 |
disaster management | 16 |
remains neutral | 16 |
health information | 16 |
high mortality | 16 |
last years | 16 |
structured impact | 16 |
initial value | 16 |
second week | 16 |
urban communities | 16 |
study design | 16 |
time taken | 16 |
johns hopkins | 16 |
positive impact | 16 |
tioman virus | 16 |
maximum likelihood | 16 |
five children | 16 |
side effects | 16 |
jurisdictional claims | 16 |
three cases | 16 |
financial interests | 16 |
trec program | 16 |
health impact | 16 |
media platforms | 16 |
controlled human | 16 |
india institute | 16 |
logistic regression | 16 |
green zones | 16 |
economic losses | 16 |
per month | 16 |
disease outbreak | 16 |
reported positive | 16 |
journal pre | 16 |
health problem | 16 |
correlation coefficient | 16 |
mouth disease | 16 |
daily basis | 16 |
reserve bank | 16 |
monsoon season | 16 |
total rna | 16 |
high rates | 16 |
st may | 16 |
health condition | 16 |
full lockdown | 16 |
death rates | 16 |
till april | 16 |
interest rate | 16 |
health research | 16 |
mathematical modeling | 16 |
model using | 16 |
mixed infection | 16 |
case counts | 16 |
i i | 16 |
published maps | 16 |
confirm cases | 16 |
five years | 16 |
medical sciences | 16 |
swine flu | 16 |
tests conducted | 16 |
times higher | 16 |
secondary cases | 16 |
nature remains | 16 |
susceptible individuals | 16 |
health effects | 16 |
institutional affiliations | 16 |
per year | 16 |
supporting information | 16 |
key role | 16 |
peak time | 16 |
quality control | 15 |
note springer | 15 |
age distribution | 15 |
gujarat state | 15 |
early diagnosis | 15 |
drug resistance | 15 |
one health | 15 |
time variation | 15 |
coping strategies | 15 |
kerala economy | 15 |
daily data | 15 |
observed data | 15 |
diagnostic tests | 15 |
ppe kit | 15 |
immune responses | 15 |
community members | 15 |
percent change | 15 |
privacy protection | 15 |
viral transmission | 15 |
collected data | 15 |
high prevalence | 15 |
urban idi | 15 |
crucial role | 15 |
healthcare sector | 15 |
first phase | 15 |
sars cov | 15 |
moderate lockdown | 15 |
one month | 15 |
suspected cases | 15 |
epidemic curve | 15 |
median age | 15 |
airline industry | 15 |
also suggested | 15 |
ibm quantum | 15 |
learning models | 15 |
slum population | 15 |
two main | 15 |
interaction spaces | 15 |
uncontrolled diabetes | 15 |
social mixing | 15 |
positive loading | 15 |
without lockdown | 15 |
previous years | 15 |
human metapneumovirus | 15 |
different geographical | 15 |
hot spots | 15 |
genome sequence | 15 |
direct contact | 15 |
child health | 15 |
rapid spread | 15 |
informal sector | 15 |
york times | 15 |
rabies virus | 15 |
alcohol policy | 15 |
best practices | 15 |
present situation | 15 |
reverse migration | 15 |
circular migrants | 15 |
health measures | 15 |
prediction model | 15 |
essential services | 15 |
human dignity | 15 |
urban area | 15 |
much lower | 15 |
economic development | 15 |
random forest | 15 |
crop residue | 15 |
given time | 15 |
corona viruses | 15 |
red zones | 15 |
inflation targeting | 15 |
corona cases | 15 |
care unit | 15 |
different time | 15 |
raw material | 15 |
japanese encephalitis | 15 |
injecting drug | 15 |
nan sha | 15 |
infection curve | 15 |
healthcare infrastructure | 15 |
endemic areas | 15 |
compartmental models | 15 |
urban agriculture | 15 |
health centers | 15 |
scientific community | 15 |
awareness among | 15 |
pandemic spread | 15 |
mainland china | 15 |
dengue virus | 15 |
neem trees | 14 |
whole country | 14 |
random sample | 14 |
international standards | 14 |
central pollution | 14 |
news media | 14 |
among different | 14 |
host cell | 14 |
children hospitalized | 14 |
contact patterns | 14 |
west nile | 14 |
solid waste | 14 |
alcohol withdrawal | 14 |
mentioned earlier | 14 |
every day | 14 |
daily wage | 14 |
high tb | 14 |
collective victimisation | 14 |
countries around | 14 |
african american | 14 |
accessed april | 14 |
backyard farmers | 14 |
major concern | 14 |
two decades | 14 |
cardiovascular diseases | 14 |
average concentration | 14 |
across different | 14 |
egg production | 14 |
climatic conditions | 14 |
private hospitals | 14 |
face mask | 14 |
supportive care | 14 |
poultry flocks | 14 |
post covid | 14 |
alcohol use | 14 |
covid patients | 14 |
first year | 14 |
may vary | 14 |
confirmed positive | 14 |
cases due | 14 |
high incidence | 14 |
vulnerable populations | 14 |
large proportion | 14 |
district level | 14 |
rural fgd | 14 |
based model | 14 |
cytokine storm | 14 |
takes place | 14 |
comparative analysis | 14 |
cases till | 14 |
global economy | 14 |
different locations | 14 |
infectious period | 14 |
time dependent | 14 |
will lead | 14 |
financial support | 14 |
health inequalities | 14 |
content analysis | 14 |
asymptomatic individuals | 14 |
labour market | 14 |
imported cases | 14 |
analysis using | 14 |
posted october | 14 |
also showed | 14 |
standard operating | 14 |
blood samples | 14 |
ordinary differential | 14 |
first confirmed | 14 |
monoclonal antibody | 14 |
also help | 14 |
national tb | 14 |
zero lockdown | 14 |
sectional survey | 14 |
model predicts | 14 |
mechanical ventilation | 14 |
neem products | 14 |
action research | 14 |
higher levels | 14 |
covid cases | 14 |
public engagement | 14 |
social isolation | 14 |
hospitalized children | 14 |
google trends | 14 |
found positive | 14 |
web portal | 14 |
virtual identity | 14 |
significant number | 14 |
escherichia coli | 14 |
pollution control | 14 |
hindustan times | 14 |
forecasting covid | 14 |
food safety | 14 |
principal component | 14 |
country like | 14 |
expert committee | 14 |
respiratory infection | 14 |
economic crisis | 14 |
virtual identities | 14 |
creative commons | 14 |
current status | 14 |
three different | 14 |
may increase | 14 |
stop tb | 14 |
infection due | 14 |
residue burning | 14 |
home quarantine | 14 |
care hospital | 14 |
training data | 14 |
tb partnership | 14 |
june th | 14 |
viral replication | 14 |
future studies | 14 |
component analysis | 14 |
data science | 14 |
data will | 14 |
biosecurity measures | 14 |
suspected covid | 14 |
poultry production | 14 |
structural proteins | 14 |
lockdown scenario | 14 |
meteorological factors | 14 |
data available | 14 |
epidemiological studies | 14 |
special reference | 14 |
municipal corporation | 14 |
study aimed | 14 |
short period | 14 |
using data | 13 |
done using | 13 |
tract infections | 13 |
help groups | 13 |
previously described | 13 |
public awareness | 13 |
human body | 13 |
using different | 13 |
positive test | 13 |
sample survey | 13 |
private healthcare | 13 |
health consequences | 13 |
epidemic models | 13 |
vaccinia virus | 13 |
get infected | 13 |
quarantine facilities | 13 |
surgical practice | 13 |
developing nations | 13 |
may affect | 13 |
every year | 13 |
middle income | 13 |
will take | 13 |
significant role | 13 |
pandemic confirmed | 13 |
online media | 13 |
heart failure | 13 |
entire country | 13 |
acute phase | 13 |
initial values | 13 |
existing health | 13 |
human mobility | 13 |
contact history | 13 |
viral diarrhoea | 13 |
high level | 13 |
nasopharyngeal swab | 13 |
statistical significance | 13 |
data using | 13 |
international spread | 13 |
cases rise | 13 |
precautionary measures | 13 |
ppe kits | 13 |
wild birds | 13 |
congo haemorrhagic | 13 |
research questions | 13 |
environmental protection | 13 |
study showed | 13 |
high burden | 13 |
every country | 13 |
remote sensing | 13 |
based research | 13 |
health authorities | 13 |
international journal | 13 |
exponential curve | 13 |
took place | 13 |
household survey | 13 |
several factors | 13 |
negative effects | 13 |
injection drug | 13 |
around million | 13 |
clinical presentation | 13 |
supreme court | 13 |
prudent public | 13 |
search volume | 13 |
global supply | 13 |
weather parameters | 13 |
various measures | 13 |
meteorological parameters | 13 |
weather indicators | 13 |
nucleocapsid protein | 13 |
fit parameters | 13 |
reported number | 13 |
local institutions | 13 |
cancer screening | 13 |
transmission potential | 13 |
cell lines | 13 |
demographic characteristics | 13 |
passenger traffic | 13 |
policy measures | 13 |
whole world | 13 |
public transport | 13 |
pilot study | 13 |
quarantine measures | 13 |
care professionals | 13 |
twitter data | 13 |
local community | 13 |
shelf life | 13 |
central india | 13 |
cases may | 13 |
substance abuse | 13 |
pacific region | 13 |
daily growth | 13 |
medical practitioners | 13 |
asian msm | 13 |
psychological distress | 13 |
returnee migrants | 13 |
lessons learned | 13 |
two major | 13 |
hidden markov | 13 |
causal models | 13 |
weighted average | 13 |
daily covid | 13 |
water pollution | 13 |
prevalence rate | 13 |
trend analysis | 13 |
high temperature | 13 |
drug policy | 13 |
diabetic foot | 13 |
gamma distribution | 13 |
within days | 13 |
basis points | 13 |
three years | 13 |
prior information | 13 |
factors affecting | 13 |
patient care | 13 |
present work | 13 |
tract infection | 13 |
worst hit | 13 |
basic reproductive | 13 |
competing financial | 13 |
viral load | 13 |
weight gain | 13 |
human genome | 13 |
health records | 13 |
measures taken | 13 |
modelling analysis | 13 |
control board | 13 |
central bank | 13 |
hand hygiene | 13 |
first step | 13 |
big data | 13 |
weather conditions | 13 |
associated hospitalization | 13 |
study revealed | 12 |
asymptomatic carriers | 12 |
sri lanka | 12 |
years ago | 12 |
electronic health | 12 |
natural product | 12 |
entertainment media | 12 |
health experts | 12 |
adverse events | 12 |
mainly due | 12 |
current scenario | 12 |
mg kg | 12 |
coronavirus diseases | 12 |
native places | 12 |
influenza vaccine | 12 |
newspaper reports | 12 |
social protection | 12 |
international trade | 12 |
two groups | 12 |
lockdown scenarios | 12 |
total environment | 12 |
also shows | 12 |
information technology | 12 |
million cases | 12 |
new normal | 12 |
health education | 12 |
virus isolation | 12 |
leading cause | 12 |
social network | 12 |
critical role | 12 |
cell culture | 12 |
countries across | 12 |
policy decisions | 12 |
travel ban | 12 |
ebola virus | 12 |
require isolation | 12 |
major role | 12 |
prediction models | 12 |
liquor shops | 12 |
data sources | 12 |
government medical | 12 |
urban backyard | 12 |
red blood | 12 |
virus rna | 12 |
growth model | 12 |
genome sequencing | 12 |
mixed infections | 12 |
ncov outbreak | 12 |
specific health | 12 |
significant difference | 12 |
various factors | 12 |
vector regression | 12 |
among women | 12 |
gives us | 12 |
molecular biology | 12 |
genetic material | 12 |
health programs | 12 |
one patient | 12 |
two years | 12 |
one third | 12 |
ethnic minority | 12 |
one hand | 12 |
chikungunya virus | 12 |
case transmission | 12 |
task force | 12 |
average monthly | 12 |
viral diarrhea | 12 |
vivax infection | 12 |
backyard chicken | 12 |
living conditions | 12 |
symptom onset | 12 |
highest positive | 12 |
public services | 12 |
breast cancer | 12 |
reported case | 12 |
private laboratories | 12 |
anonymous credentials | 12 |
peripheral blood | 12 |
drug abuse | 12 |
bcg vaccination | 12 |
developed nations | 12 |
control group | 12 |
will become | 12 |
upper respiratory | 12 |
india reported | 12 |
based analysis | 12 |
total covid | 12 |
many studies | 12 |
animal products | 12 |
working group | 12 |
home delivery | 12 |
sector hospitals | 12 |
online survey | 12 |
high blood | 12 |
also detected | 12 |
year period | 12 |
south indian | 12 |
concerns regarding | 12 |
online version | 12 |
first study | 12 |
akaike information | 12 |
great deal | 12 |
quarantine period | 12 |
tissue culture | 12 |
higher number | 12 |
metab syndr | 12 |
research team | 12 |
important aspect | 12 |
distress syndrome | 12 |
lockdown may | 12 |
legal metrology | 12 |
th lockdown | 12 |
india relative | 12 |
increasing trend | 12 |
throat swabs | 12 |
specific prevalence | 12 |
require icu | 12 |
physical health | 12 |
allows us | 12 |
frontline workers | 12 |
comparative study | 12 |
four different | 12 |
negative association | 12 |
epidemic model | 12 |
provide information | 12 |
transmission mechanism | 12 |
tuberculosis control | 12 |
air travel | 12 |
corresponding author | 12 |
level data | 12 |
tb disease | 12 |
two months | 12 |
neural networks | 12 |
risk state | 12 |
influenza epidemic | 12 |
many years | 12 |
samples collected | 12 |
significant reduction | 12 |
bps maintain | 12 |
human resources | 12 |
severely affected | 12 |
time interval | 12 |
lower mortality | 12 |
indian health | 12 |
climate changes | 12 |
data used | 12 |
like covid | 12 |
government policies | 12 |
india also | 12 |
five major | 12 |
infected pneumonia | 12 |
second lockdown | 12 |
air temperature | 12 |
countries including | 12 |
geographical areas | 11 |
initial lockdown | 11 |
virus transmission | 11 |
initial stages | 11 |
outbreak predictions | 11 |
uncertainty around | 11 |
mental disorders | 11 |
agent orange | 11 |
health indicators | 11 |
google search | 11 |
reported data | 11 |
potential outreach | 11 |
community capacity | 11 |
laboratory investigations | 11 |
term memory | 11 |
personal hygiene | 11 |
pulmonary edema | 11 |
different levels | 11 |
month restoration | 11 |
parameters like | 11 |
currently available | 11 |
controlled trial | 11 |
significantly lower | 11 |
work reported | 11 |
clinical complications | 11 |
rapid growth | 11 |
gulf countries | 11 |
worst affected | 11 |
total deaths | 11 |
unwanted sexual | 11 |
forest disease | 11 |
respective countries | 11 |
call money | 11 |
markov model | 11 |
policy responses | 11 |
tb programs | 11 |
monte carlo | 11 |
second phase | 11 |
st june | 11 |
susceptible pool | 11 |
west africa | 11 |
physical symptoms | 11 |
epidemiological parameters | 11 |
ill patients | 11 |
indian association | 11 |
india since | 11 |
india today | 11 |
data analytics | 11 |
anthropogenic activities | 11 |
multiplex pcr | 11 |
rift valley | 11 |
without diabetes | 11 |
people infected | 11 |
also play | 11 |
higher prevalence | 11 |
language pathologists | 11 |
estimated using | 11 |
indian medical | 11 |
admitted patients | 11 |
vector machine | 11 |
household food | 11 |
two variables | 11 |
swine fever | 11 |
case finding | 11 |
genetic variants | 11 |
cases based | 11 |
antimicrobial activity | 11 |
also provided | 11 |
one hundred | 11 |
renal syndrome | 11 |
vulnerable groups | 11 |
descriptive statistics | 11 |
public domain | 11 |
higher proportion | 11 |
demographic factors | 11 |
ever since | 11 |
based covid | 11 |
world war | 11 |
zoonotic diseases | 11 |
pulmonary disease | 11 |
early dynamics | 11 |
low levels | 11 |
cd monoclonal | 11 |
medium enterprises | 11 |
compartmental model | 11 |
negative impacts | 11 |
early warning | 11 |
reported covid | 11 |
partial lockdown | 11 |
medical staff | 11 |
major cause | 11 |
supplement table | 11 |
linear growth | 11 |
new coronavirus | 11 |
biomedical waste | 11 |
care delivery | 11 |
case management | 11 |
opposition parties | 11 |
important lessons | 11 |
north america | 11 |
local authorities | 11 |
coming time | 11 |
diabetes metab | 11 |
historical data | 11 |
river water | 11 |
healthcare delivery | 11 |
south gujarat | 11 |
total lockdown | 11 |
potential domestic | 11 |
will depend | 11 |
system capacity | 11 |
randomized controlled | 11 |
asymptomatic transmission | 11 |
pandemic response | 11 |
past months | 11 |
since march | 11 |
stochastic mathematical | 11 |
since many | 11 |
next generation | 11 |
first wave | 11 |
empowerment process | 11 |
attack rate | 11 |
zoonotic disease | 11 |
extended lockdown | 11 |
study provides | 11 |
important factor | 11 |
outbreak originating | 11 |
term exposure | 11 |
available online | 11 |
public healthcare | 11 |
learning methods | 11 |
growth regulators | 11 |
tb infection | 11 |
population will | 11 |
criminal justice | 11 |
community based | 11 |
retrospective analysis | 11 |
will happen | 11 |
indian society | 11 |
like virus | 11 |
mg dl | 11 |
acute lower | 11 |
measures like | 11 |
eastern states | 11 |
food borne | 11 |
google scholar | 11 |
known competing | 11 |
first days | 11 |
pandemic period | 11 |
employment opportunities | 11 |
data driven | 11 |
urban centers | 11 |
alcohol prohibition | 11 |
clinical practice | 11 |
health related | 11 |
predicted cumulative | 11 |
source apportionment | 11 |
study population | 11 |
positivity rate | 11 |
asymptomatic patients | 11 |
like illness | 11 |
case detection | 11 |
reduce covid | 11 |
drug treatment | 11 |
model used | 11 |
new patients | 11 |
lower bound | 11 |
daily fatalities | 11 |
future cases | 11 |
com news | 11 |
pandemic will | 11 |
way forward | 11 |
money market | 11 |
early transmission | 11 |
bombay presidency | 11 |
neem tree | 11 |
sodium chlorate | 11 |
also show | 11 |
almost every | 11 |
infection prevention | 11 |
analysis shows | 11 |
four months | 11 |
using epidemiological | 11 |
three types | 11 |
results obtained | 11 |
falciparum malaria | 11 |
days lockdown | 11 |
human life | 11 |
differential equation | 11 |
lockdown continues | 11 |
quantum computer | 11 |
two phases | 11 |
short time | 11 |
attitudes towards | 11 |
death due | 11 |
new virus | 11 |
pivotal role | 11 |
east countries | 11 |
north east | 11 |
monetary transmission | 10 |
conducted using | 10 |
patient management | 10 |
community level | 10 |
daily weather | 10 |
full length | 10 |
transmission reductions | 10 |
publicly reported | 10 |
computer science | 10 |
water supply | 10 |
controlled diabetes | 10 |
higher among | 10 |
ongoing pandemic | 10 |
care units | 10 |
outbreak situation | 10 |
predictive model | 10 |
complete genome | 10 |
seafood market | 10 |
price stability | 10 |
kabasuraneer choornam | 10 |
regressive integrated | 10 |
vaccine strain | 10 |
india i | 10 |
bat borne | 10 |
samples obtained | 10 |
fractal dimension | 10 |
purpose limitation | 10 |
home isolation | 10 |
mean absolute | 10 |
borne viral | 10 |
human immunodeficiency | 10 |
health benefits | 10 |
long distances | 10 |
medical professionals | 10 |
significant effect | 10 |
stranded rna | 10 |
valley fever | 10 |
related mortality | 10 |
covid data | 10 |
domestic product | 10 |
index case | 10 |
human cases | 10 |
current covid | 10 |
different social | 10 |
community spaces | 10 |
values obtained | 10 |
two scenarios | 10 |
family planning | 10 |
one year | 10 |
viral spread | 10 |
analysed using | 10 |
covid epidemic | 10 |
wearing masks | 10 |
significant improvement | 10 |
african countries | 10 |
influenza surveillance | 10 |
grounded theory | 10 |
liver disease | 10 |
nearly half | 10 |
impact categories | 10 |
regarding covid | 10 |
many parts | 10 |
south african | 10 |
term forecasting | 10 |
english language | 10 |
declared covid | 10 |
government securities | 10 |
delhi virus | 10 |
causative agent | 10 |
health impacts | 10 |
chronic obstructive | 10 |
current model | 10 |
new drugs | 10 |
care indicators | 10 |
acute gastroenteritis | 10 |
key factors | 10 |
growth models | 10 |
public places | 10 |
reference genome | 10 |
kolkata municipal | 10 |
crack users | 10 |
cchf virus | 10 |
patients admitted | 10 |
may occur | 10 |
much better | 10 |
body fluids | 10 |
six years | 10 |
severe anemia | 10 |
cases found | 10 |
table i | 10 |
take place | 10 |
public key | 10 |
new immigrants | 10 |
sore throat | 10 |
two weeks | 10 |
national sample | 10 |
study using | 10 |
like maharashtra | 10 |
largest population | 10 |
immunosorbent assay | 10 |
infectious agents | 10 |
rapid transmission | 10 |
health concern | 10 |
assessed using | 10 |
sexual abuse | 10 |
renal failure | 10 |
entire population | 10 |
current analysis | 10 |
latin america | 10 |
global emergency | 10 |
three months | 10 |
also likely | 10 |
july th | 10 |
drug development | 10 |
national family | 10 |
religious event | 10 |
indian isolates | 10 |
protein gene | 10 |
two types | 10 |
prior distribution | 10 |
early days | 10 |
fossil fuel | 10 |
culex quinquefasciatus | 10 |
diarrhea virus | 10 |
older adults | 10 |
water bodies | 10 |
resource allocation | 10 |
underlying health | 10 |
information available | 10 |
daily cumulative | 10 |
media briefing | 10 |
tells us | 10 |
healthcare personnel | 10 |
smoking cessation | 10 |
three phases | 10 |
every individual | 10 |
medical schools | 10 |
village level | 10 |
target population | 10 |
contaminated water | 10 |
dengue fever | 10 |
daily reported | 10 |
major states | 10 |
ethnic groups | 10 |
public hospitals | 10 |
copper sulfate | 10 |
already reported | 10 |
effective contacts | 10 |
transmission process | 10 |
open access | 10 |
sex ratio | 10 |
qualitative research | 10 |
genomic epidemiology | 10 |
different species | 10 |
linked immunosorbent | 10 |
policy development | 10 |
lockdown exit | 10 |
virus detection | 10 |
largest number | 10 |
different stages | 10 |
community mobility | 10 |
second largest | 10 |
within india | 10 |
kyasanur forest | 10 |
incoming cases | 10 |
eastern europe | 10 |
paper will | 10 |
model predictions | 10 |
qualitative study | 10 |
disease study | 10 |
integral part | 10 |
curl new | 10 |
critical cases | 10 |
commercially available | 10 |
decision support | 10 |
will likely | 10 |
malaria transmission | 10 |
recent times | 10 |
anxiety symptoms | 10 |
seeking keywords | 10 |
one day | 10 |
preliminary analysis | 10 |
chim study | 10 |
appendix table | 10 |
also shown | 10 |
antiretroviral therapy | 10 |
different age | 10 |
gradual relaxation | 10 |
feeding practices | 10 |
higher level | 10 |
less severe | 10 |
best fitting | 10 |
critically ill | 10 |
economically important | 10 |
total death | 10 |
risk score | 10 |
world economic | 10 |
mass index | 10 |
economic loss | 10 |
become available | 10 |
rank correlation | 10 |
healthcare demand | 10 |
environmental pollution | 10 |
public good | 10 |
age structure | 10 |
deaths among | 10 |
take care | 10 |
among others | 10 |
analyzed using | 10 |
birth weight | 10 |
prevalence among | 10 |
impact assessment | 10 |
dependent reproduction | 10 |
long short | 10 |
health agencies | 10 |
complete genomes | 10 |
obstructive pulmonary | 10 |
mean pm | 10 |
greater risk | 10 |
lakh crore | 10 |
biosecurity practices | 10 |
scientific research | 10 |
credible intervals | 10 |
deaths worldwide | 10 |
normal distribution | 10 |
infection will | 10 |
seek help | 10 |
immunodeficiency virus | 10 |
higher mortality | 10 |
ward containment | 10 |
household level | 10 |
poor health | 10 |
since th | 10 |
virus strain | 10 |
disease incidence | 10 |
risk category | 10 |
statistical methods | 10 |
political will | 10 |
information related | 10 |
population relative | 10 |
limited access | 10 |
st march | 10 |
will get | 10 |
slum livestock | 10 |
public distribution | 10 |
clinical management | 10 |
human gut | 10 |
also seen | 10 |
flock size | 10 |
invasive meningococcal | 10 |
influenza epidemics | 10 |
exit strategy | 10 |
significant proportion | 10 |
term impact | 10 |
per thousand | 10 |
month lockdown | 10 |
policy transmission | 10 |
supplementary file | 10 |
environmental health | 10 |
information systems | 10 |
heavy metals | 9 |
national schedule | 9 |
social health | 9 |
directorate general | 9 |
bayesian credible | 9 |
tb mortality | 9 |
past two | 9 |
social workers | 9 |
mmr vaccine | 9 |
like symptoms | 9 |
sexual health | 9 |
two days | 9 |
distancing norms | 9 |
pandemic using | 9 |
time distribution | 9 |
holistic approach | 9 |
learning approach | 9 |
molecular characterization | 9 |
future generations | 9 |
environmental impacts | 9 |
nipha virus | 9 |
will remain | 9 |
negatively associated | 9 |
seven days | 9 |
study used | 9 |
south asians | 9 |
significant correlation | 9 |
relationship among | 9 |
coronavirus pneumonia | 9 |
ten days | 9 |
different cities | 9 |
study reveals | 9 |
recent past | 9 |
positive samples | 9 |
online platforms | 9 |
fitting model | 9 |
mitigation measures | 9 |
initial stage | 9 |
family member | 9 |
first report | 9 |
prior studies | 9 |
spread rapidly | 9 |
acute medical | 9 |
policy interventions | 9 |
registered medical | 9 |
root mean | 9 |
epidemic disease | 9 |
yellow vein | 9 |
treating covid | 9 |
protection agency | 9 |
million confirmed | 9 |
outpatient care | 9 |
higher values | 9 |
three times | 9 |
pox virus | 9 |
job losses | 9 |
bordeaux mixture | 9 |
winter months | 9 |
density areas | 9 |
cargo business | 9 |
i will | 9 |
three main | 9 |
lockdown due | 9 |
capital region | 9 |
initial conditions | 9 |
optometry education | 9 |
three weeks | 9 |
management practices | 9 |
also provide | 9 |
patient flow | 9 |
local containment | 9 |
meningococcal infection | 9 |
virus circulation | 9 |
issues related | 9 |
lockdown started | 9 |
reproductive health | 9 |
using google | 9 |
global economic | 9 |
longer period | 9 |
required number | 9 |
expanded testing | 9 |
death counts | 9 |
global spread | 9 |
lancet infectious | 9 |
seek care | 9 |
opening remarks | 9 |
premature mortality | 9 |
agrochemical poisoning | 9 |
law enforcement | 9 |
sample collection | 9 |
blood cells | 9 |
world trade | 9 |
rna polymerase | 9 |
ganga river | 9 |
term circular | 9 |
economic determinants | 9 |
syndr doi | 9 |
positive patients | 9 |
mental space | 9 |
environmental impact | 9 |
deadly virus | 9 |
female sex | 9 |
month period | 9 |
low risk | 9 |
waste disposal | 9 |
fine particulate | 9 |
risk reduction | 9 |
dna vaccine | 9 |
surface water | 9 |
intelligent packaging | 9 |
genetic epidemiology | 9 |
safety net | 9 |
hot spot | 9 |
thermal power | 9 |
reporting guidelines | 9 |
systems science | 9 |
pearson correlation | 9 |
underlying conditions | 9 |
treat covid | 9 |
toxicological analysis | 9 |
aids epidemic | 9 |
untreated tb | 9 |
primary case | 9 |
labour laws | 9 |
india imposed | 9 |
reproduction rate | 9 |
reported deaths | 9 |
demographic information | 9 |
retrospective study | 9 |
significantly reduced | 9 |
old man | 9 |
social development | 9 |
illness among | 9 |
patient data | 9 |
similar results | 9 |
folic acid | 9 |
countries using | 9 |
pcr assay | 9 |
one person | 9 |
rapidly increasing | 9 |
india currently | 9 |
provide insights | 9 |
online consultations | 9 |
kg co | 9 |
incidence rates | 9 |
informal settlements | 9 |
virus specific | 9 |
adversely affected | 9 |
clinical history | 9 |
line workers | 9 |
soft ward | 9 |
highly affected | 9 |
policy repo | 9 |
rural backyard | 9 |
related issues | 9 |
high quality | 9 |
first half | 9 |
daily life | 9 |
risk management | 9 |
deaths per | 9 |
policy committee | 9 |
winters models | 9 |
himachal pradesh | 9 |
human activities | 9 |
operating cost | 9 |
positive results | 9 |
model provides | 9 |
current data | 9 |
two parameters | 9 |
sequence data | 9 |
female gender | 9 |
religious leaders | 9 |
arima models | 9 |
police personnel | 9 |
convalescent plasma | 9 |
especially among | 9 |
east asian | 9 |
lockdown will | 9 |
emergency use | 9 |
predicted values | 9 |
recent studies | 9 |
series forecasting | 9 |
testing strategy | 9 |
modelling approach | 9 |
medical conditions | 9 |
active constituents | 9 |
four cases | 9 |
infection model | 9 |
public service | 9 |
driven analysis | 9 |
second peak | 9 |
vector control | 9 |
janata curfew | 9 |
two studies | 9 |
commonly known | 9 |
survey conducted | 9 |
community leaders | 9 |
dependent variable | 9 |
confirmed corona | 9 |
badly affected | 9 |
adverse impact | 9 |
zoonotic pathogens | 9 |
confidence level | 9 |
isolation wards | 9 |
piecewise linear | 9 |
home affairs | 9 |
disease among | 9 |
protective efficacy | 9 |
daily recovered | 9 |
results indicate | 9 |
pcr assays | 9 |
electronic supplementary | 9 |
total reported | 9 |
tropical countries | 9 |
care needs | 9 |
toxic effects | 9 |
sampling technique | 9 |
contains supplementary | 9 |
multivariate analyses | 9 |
main objective | 9 |
disease risk | 9 |
previous research | 9 |
initial susceptible | 9 |
problem solving | 9 |
give rise | 9 |
across countries | 9 |
co eq | 9 |
unintended consequences | 9 |
like china | 9 |
new case | 9 |
care infrastructure | 9 |
lung cancer | 9 |
many regions | 9 |
wq parameters | 9 |
last two | 9 |
vice versa | 9 |
viral pathogens | 9 |
active infection | 9 |
papua new | 9 |
adverse effect | 9 |
human rhinovirus | 9 |
agrarian distress | 9 |
role played | 9 |
person transmission | 9 |
clinical course | 9 |
study suggests | 9 |
political economy | 9 |
curl disease | 9 |
related deaths | 9 |
lockdown levels | 9 |
manufacturing sector | 9 |
one million | 9 |
demographic data | 9 |
model simulation | 9 |
biomass burning | 9 |
financial markets | 9 |
test positive | 9 |
analysis period | 9 |
organization declares | 9 |
cumulative deceased | 9 |
igg antibodies | 9 |
malaria cases | 9 |
frontline health | 9 |
fight covid | 9 |
commercial poultry | 9 |
india took | 9 |
total remittances | 9 |
borne viruses | 9 |
urban population | 9 |
sexually transmitted | 9 |
authorized users | 9 |
biomedical research | 9 |
may provide | 9 |
disease will | 9 |
economic factors | 9 |
state wise | 9 |
significant change | 9 |
vero ccl | 9 |
first detected | 9 |
world economy | 9 |
high density | 9 |
recent outbreak | 9 |
law growth | 9 |
severe criteria | 9 |
balanced diet | 9 |
distribution system | 9 |
us states | 9 |
slum dwellers | 9 |
rates among | 9 |
recent decades | 9 |
average recovery | 9 |
glucose levels | 9 |
plant species | 9 |
see appendix | 9 |
clean air | 9 |
access health | 9 |
us embassies | 9 |
project management | 9 |
saharan africa | 9 |
various indian | 9 |
similar trend | 9 |
rural population | 9 |
third lockdown | 9 |
cisgender woman | 9 |
current research | 9 |
pteropus giganteus | 9 |
lessons learnt | 9 |
final version | 9 |
vaccine strains | 9 |
combat covid | 9 |
people died | 9 |
healthcare service | 9 |
operating leverage | 9 |
future pandemics | 9 |
indole alkaloids | 9 |
daily count | 9 |
demographic details | 9 |
five different | 9 |
veterinary services | 9 |
hospital bed | 9 |
will focus | 9 |
polynomial growth | 9 |
reviewed articles | 9 |
india till | 9 |
health response | 9 |
print media | 9 |
losses due | 9 |
turning point | 9 |
suicide reporting | 9 |
high school | 9 |
model analysis | 9 |
covid curve | 9 |
will improve | 9 |
mortality among | 9 |
simple model | 9 |
even death | 8 |
analysis indicated | 8 |
containment zone | 8 |
weibull distribution | 8 |
aluminium phosphide | 8 |
bayesian approach | 8 |
clinical manifestations | 8 |
study aims | 8 |
also identified | 8 |
naked dna | 8 |
time dependence | 8 |
huge population | 8 |
dna polymerase | 8 |
infection curves | 8 |
global public | 8 |
model assumes | 8 |
environmentally sound | 8 |
neutralizing antibodies | 8 |
pandemic era | 8 |
small proportion | 8 |
east india | 8 |
observed among | 8 |
government health | 8 |
sir models | 8 |
southeast asian | 8 |
testing data | 8 |
square estimates | 8 |
additive manufacturing | 8 |
vaccine production | 8 |
young adults | 8 |
differentially private | 8 |
positively correlated | 8 |
prospective cohort | 8 |
also helps | 8 |
narendra modi | 8 |
women living | 8 |
also need | 8 |
eastern region | 8 |
community development | 8 |
observational cohort | 8 |
environmental sustainability | 8 |
associated hospitalizations | 8 |
operating procedure | 8 |
quarantine facility | 8 |
community participation | 8 |
mean value | 8 |
existing medical | 8 |
testing laboratories | 8 |
national levels | 8 |
seasonal flu | 8 |
cumulative new | 8 |
financial crisis | 8 |
analysis also | 8 |
homestead gardens | 8 |
sexual experiences | 8 |
kerala emigrants | 8 |
present day | 8 |
cumulative recovered | 8 |
advisory committee | 8 |
food availability | 8 |
heat action | 8 |
aedes albopictus | 8 |
unfavourable meteorology | 8 |
mild symptoms | 8 |
transboundary animal | 8 |
healthy controls | 8 |
vulnerability assessment | 8 |
best fitted | 8 |
health policies | 8 |
estimated parameters | 8 |
liquor stores | 8 |
linear trend | 8 |
income inequality | 8 |
last months | 8 |
following sections | 8 |
first one | 8 |
infection cases | 8 |
food insecure | 8 |
livestock agriculture | 8 |
spatial distribution | 8 |
onset diabetes | 8 |
british columbia | 8 |
abdominal pain | 8 |
till june | 8 |
even within | 8 |
relatively low | 8 |
random testing | 8 |
covid outbreak | 8 |
longer duration | 8 |
factors influencing | 8 |
mobility reports | 8 |
hazard ratios | 8 |
enteric viruses | 8 |
severe illness | 8 |
virus type | 8 |
global level | 8 |
depressive symptoms | 8 |
random sampling | 8 |
low rates | 8 |
india impact | 8 |
severe symptoms | 8 |
stool samples | 8 |
poor air | 8 |
results also | 8 |
change point | 8 |
virus causing | 8 |
moving averages | 8 |
hidden states | 8 |
like social | 8 |
livestock keeping | 8 |
rna viruses | 8 |
different parameters | 8 |
positive covid | 8 |
genomic analysis | 8 |
common cold | 8 |
one infected | 8 |
four states | 8 |
last three | 8 |
negative correlation | 8 |
suspected patients | 8 |
european union | 8 |
younger age | 8 |
community services | 8 |
antenatal care | 8 |
significantly different | 8 |
based diet | 8 |
confirmed deaths | 8 |
vp gene | 8 |
contact matrices | 8 |
states across | 8 |
parainfluenza viruses | 8 |
quality parameters | 8 |
january th | 8 |
five states | 8 |
may require | 8 |
occupancy rate | 8 |
factors like | 8 |
vero cell | 8 |
pacific regions | 8 |
economically disadvantaged | 8 |
large country | 8 |
important factors | 8 |
benefit analysis | 8 |
severity criteria | 8 |
treatment services | 8 |
models using | 8 |
clinical research | 8 |
indian scenario | 8 |
development studies | 8 |
pulmonary tuberculosis | 8 |
medical history | 8 |
longer term | 8 |
growth performance | 8 |
longer time | 8 |
current health | 8 |
past year | 8 |
days prior | 8 |
first day | 8 |
model prediction | 8 |
constructed using | 8 |
private partnership | 8 |
kerala state | 8 |
western pacific | 8 |
bitter gourd | 8 |
administrative units | 8 |
genomic data | 8 |
insect growth | 8 |
medical waste | 8 |
high degree | 8 |
great extent | 8 |
environmental effects | 8 |
covid infection | 8 |
field conditions | 8 |
many asian | 8 |
chronic disease | 8 |
river buffalo | 8 |
lockdown followed | 8 |
third wave | 8 |
generalized fractal | 8 |
human coronavirus | 8 |
functional form | 8 |
poultry sector | 8 |
will reduce | 8 |
absolute percentage | 8 |
high rate | 8 |
term forecasts | 8 |
quality data | 8 |
states uts | 8 |
live poultry | 8 |
management system | 8 |
genotyping initiatives | 8 |
cell line | 8 |
aggressive testing | 8 |
primary objective | 8 |
sanitation workers | 8 |
different scenarios | 8 |
significance level | 8 |
rapid increase | 8 |
findings indicate | 8 |
expected number | 8 |
clinical signs | 8 |
online classes | 8 |
public attention | 8 |
production systems | 8 |
model shows | 8 |
rural women | 8 |
upper bound | 8 |
learning based | 8 |
social determinants | 8 |
extended data | 8 |
monetary targeting | 8 |
section presents | 8 |
total infection | 8 |
emergency services | 8 |
disease covid | 8 |
living organisms | 8 |
mega cities | 8 |
dietary habits | 8 |
genomic sovereignty | 8 |
health ministry | 8 |
also analysed | 8 |
clinical outcomes | 8 |
northern parts | 8 |
rapid rise | 8 |
reverse transcriptase | 8 |
organophosphorus insecticides | 8 |
field isolates | 8 |
lung injury | 8 |
medical colleges | 8 |
present case | 8 |
using real | 8 |