This is a table of type proper and their frequencies. Use it to search & browse the list to learn more about your study carrel.
| proper | frequency |
|---|---|
| COVID-19 | 409 |
| TB | 150 |
| March | 143 |
| India | 138 |
| UK | 125 |
| Beijing | 110 |
| Fig | 104 |
| SARS | 97 |
| China | 97 |
| Health | 85 |
| CoV-2 | 82 |
| Table | 78 |
| PM2.5 | 74 |
| Bangladesh | 71 |
| April | 71 |
| May | 70 |
| ORVal | 69 |
| England | 66 |
| CC | 59 |
| 58 | |
| June | 54 |
| January | 53 |
| National | 52 |
| Lockdown | 51 |
| US | 48 |
| GDP | 48 |
| Italy | 47 |
| Coronavirus | 46 |
| COPD | 46 |
| Covid-19 | 45 |
| February | 44 |
| CI | 41 |
| Pakistan | 41 |
| ED | 39 |
| ND | 38 |
| BY | 37 |
| • | 36 |
| LGBT | 35 |
| World | 32 |
| France | 32 |
| CERFB | 32 |
| sha | 31 |
| DOI | 31 |
| University | 30 |
| Government | 30 |
| GRES | 30 |
| Appendix | 29 |
| medRxiv | 29 |
| ICU | 28 |
| Online | 27 |
| NOx | 27 |
| Data | 27 |
| COVID | 27 |
| October | 26 |
| New | 26 |
| Wuhan | 22 |
| T | 22 |
| Spain | 22 |
| Singapore | 22 |
| Research | 22 |
| LSOA | 22 |
| Global | 22 |
| Impact | 21 |
| Air | 21 |
| USA | 21 |
| WRF | 20 |
| United | 20 |
| S1 | 20 |
| O3 | 20 |
| French | 20 |
| AJS | 20 |
| μg | 20 |
| Spring | 19 |
| SI | 19 |
| HIV | 19 |
| Festival | 18 |
| AECOPD | 18 |
| Figure | 18 |
| PM | 18 |
| States | 18 |
| m3 | 18 |
| Supplementary | 17 |
| Pearson | 17 |
| PHQ-9 | 17 |
| M | 17 |
| July | 17 |
| J | 17 |
| Institute | 17 |
| Control | 17 |
| CMAQ | 17 |
| Social | 17 |
| GAD-7 | 16 |
| Center | 16 |
| DAS | 16 |
| Graz | 16 |
| Nigeria | 16 |
| Model | 15 |
| Bank | 15 |
| Care | 15 |
| Greece | 15 |
| series | 15 |
| Organization | 15 |
| T1DM | 15 |
| Pandemic | 15 |
| Sec | 14 |
| Department | 14 |
| Disease | 14 |
| Hubei | 14 |
| North | 14 |
| Lagos | 14 |
| South | 14 |
| Times | 14 |
| U.S. | 14 |
| Urban | 14 |
| covid-19 | 14 |
| nan | 14 |
| School | 13 |
| NO2 | 13 |
| Linares | 13 |
| Family | 13 |
| East | 13 |
| Cronbach | 12 |
| Eq | 12 |
| Economic | 12 |
| GPAQ | 12 |
| Anxiety | 12 |
| Addictovigilance | 12 |
| Europe | 12 |
| Sweden | 12 |
| Kenya | 12 |
| SEIR | 12 |
| Society | 12 |
| Statistics | 12 |
| Tulika | 12 |
| NHS | 12 |
| Lancet | 11 |
| Germany | 11 |
| Hospital | 11 |
| Hz | 11 |
| IMF | 11 |
| International | 11 |
| Korea | 11 |
| KPK | 11 |
| Network | 11 |
| PSD | 11 |
| Punjab | 11 |
| September | 11 |
| Sindh | 11 |
| Ukraine | 11 |
| greenspace | 11 |
| PCA | 11 |
| Emergency | 10 |
| MW | 10 |
| ISAM | 10 |
| General | 10 |
| Analysis | 10 |
| Committee | 10 |
| CO | 10 |
| C | 10 |
| Mg | 10 |
| Mental | 10 |
| Questionnaire | 10 |
| Ministry | 10 |
| NC | 10 |
| Plan | 10 |
| Public | 10 |
| a1111111111 | 10 |
| R | 10 |
| R0 | 10 |
| VOC | 10 |
| Zealand | 10 |
| Mobility | 10 |
| Creative | 9 |
| HDT | 9 |
| F | 9 |
| Emission | 9 |
| Daily | 9 |
| BDI | 9 |
| Commons | 9 |
| COVID‐19 | 9 |
| Belgium | 9 |
| Austria | 9 |
| Likert | 9 |
| Life | 9 |
| Khan | 9 |
| ML | 9 |
| STAI | 9 |
| Transport | 9 |
| State | 9 |
| Sect | 9 |
| Scikit | 9 |
| Scale | 9 |
| Manchester | 9 |
| SD | 9 |
| QALY | 9 |
| OSIAP | 9 |
| ONS | 9 |
| Quality | 9 |
| Education | 8 |
| NH3 | 8 |
| N | 8 |
| Labrague | 8 |
| Fable | 8 |
| Ethics | 8 |
| Environmental | 8 |
| Denmark | 8 |
| EC | 8 |
| Development | 8 |
| Class | 8 |
| City | 8 |
| C. | 8 |
| Resilience | 8 |
| AJK | 8 |
| Brooks | 8 |
| Prevention | 8 |
| Response | 8 |
| WHO | 8 |
| SDG | 8 |
| preprint | 8 |
| https | 8 |
| York | 8 |
| Y | 8 |
| Wang | 8 |
| st | 8 |
| Vietnam | 8 |
| Trieste | 8 |
| System | 8 |
| Survey | 8 |
| Statistical | 8 |
| Smith | 8 |
| VOCs | 8 |
| December | 7 |
| Inventory | 7 |
| ICT | 7 |
| HbA1c | 7 |
| HC | 7 |
| 7 | |
| Beltekian | 7 |
| D. | 7 |
| Central | 7 |
| California | 7 |
| Agency | 7 |
| Action | 7 |
| Minister | 7 |
| London | 7 |
| Tuberculosis | 7 |
| News | 7 |
| SIR | 7 |
| OBR | 7 |
| VSL | 7 |
| Sharma | 7 |
| SPSS | 7 |
| SLOVE | 7 |
| Transition | 7 |
| S4 | 7 |
| S2 | 7 |
| Philippines | 7 |
| Patient | 7 |
| Office | 7 |
| OECD | 7 |
| Depression | 6 |
| Iran | 6 |
| Intensive | 6 |
| Indian | 6 |
| GB | 6 |
| Factors | 6 |
| Evaluation | 6 |
| Environment | 6 |
| Ebola | 6 |
| Dr. | 6 |
| Beck | 6 |
| Delhi | 6 |
| Day | 6 |
| Community | 6 |
| Centers | 6 |
| Carlo | 6 |
| CareLink | 6 |
| Li | 6 |
| Balochistan | 6 |
| BCG | 6 |
| < | 6 |
| Kaur | 6 |
| Chinese | 6 |
| License | 6 |
| Science | 6 |
| Lockdowns | 6 |
| × | 6 |
| du | 6 |
| doc_id | 6 |
| Time | 6 |
| Study | 6 |
| Stress | 6 |
| Singh | 6 |
| Seismic | 6 |
| https://doi.org/10 | 6 |
| SO2 | 6 |
| Prime | 6 |
| SNAO | 6 |
| Nature | 6 |
| Northern | 6 |
| Pollution | 6 |
| Monte | 6 |
| Review | 6 |
| S. | 6 |
| SNA | 6 |
| Islamabad | 5 |
| Federation | 5 |
| Flaxman | 5 |
| Fourier | 5 |
| G | 5 |
| EPA | 5 |
| H | 5 |
| Iceland | 5 |
| Environ | 5 |
| Key | 5 |
| Japan | 5 |
| Jones | 5 |
| KMO | 5 |
| L. | 5 |
| Leicester | 5 |
| Lin | 5 |
| M. | 5 |
| Director | 5 |
| MENE | 5 |
| E | 5 |
| CT | 5 |
| De | 5 |
| David | 5 |
| Management | 5 |
| -28 | 5 |
| 8) | 5 |
| Abstract | 5 |
| Africa | 5 |
| America | 5 |
| Asia | 5 |
| Asian | 5 |
| Atmospheric | 5 |
| Australia | 5 |
| B. | 5 |
| CTT | 5 |
| Cambridge | 5 |
| Centre | 5 |
| Chronic | 5 |
| Climate | 5 |
| Commission | 5 |
| Council | 5 |
| Cuestionario | 5 |
| MR | 5 |
| Kumar | 5 |
| McNemar | 5 |
| Salma | 5 |
| Simulation | 5 |
| Stop | 5 |
| Texas | 5 |
| Toronto | 5 |
| TrackATruck | 5 |
| Van | 5 |
| West | 5 |
| addictovigilance | 5 |
| azithromycin | 5 |
| del | 5 |
| https://doi.org/10.1101/2020.05 | 5 |
| https://doi.org/10.1101/2020.06.25.20140442 | 5 |
| los | 5 |
| mg | 5 |
| mid | 5 |
| | | 5 |
| ̃ | 5 |
| ≤ | 5 |
| MetS | 5 |
| Sendai | 5 |
| pane | 5 |
| S7 | 5 |
| PC1 | 5 |
| Metropolitan | 5 |
| Rumi | 5 |
| Michael | 5 |
| Modeling | 5 |
| N2O | 5 |
| NHPP | 5 |
| Notes | 5 |
| Novel | 5 |
| Milano | 5 |
| Partnership | 5 |
| Population | 5 |
| Psychometric | 5 |
| Q | 5 |
| Reports | 5 |
| RC | 5 |
| Random | 5 |
| Pharmacology | 5 |
| Regional | 5 |
| Financial | 4 |
| GoB | 4 |
| Glasgow | 4 |
| Ghosh | 4 |
| G. | 4 |
| Framework | 4 |
| Fisher | 4 |
| Familiares | 4 |
| Figs | 4 |
| Fatigue | 4 |
| Excellence | 4 |
| Evaluación | 4 |
| European | 4 |
| Engineering | 4 |
| Hale | 4 |
| Energy | 4 |
| Guardian | 4 |
| LS2S1 | 4 |
| Healthcare | 4 |
| Infected | 4 |
| Effect | 4 |
| Measures | 4 |
| Markov | 4 |
| Majumdar | 4 |
| MILN | 4 |
| MAS | 4 |
| Liu | 4 |
| Layer | 4 |
| Laboratory | 4 |
| L | 4 |
| Kochhar | 4 |
| Joint | 4 |
| Jeong | 4 |
| Island | 4 |
| Institutional | 4 |
| Effectiveness | 4 |
| Bayes | 4 |
| EEG | 4 |
| Duty | 4 |
| Bartlett | 4 |
| BTH | 4 |
| BSD | 4 |
| BRAC | 4 |
| B | 4 |
| August | 4 |
| Association | 4 |
| Ashish | 4 |
| Article | 4 |
| Annan | 4 |
| Accepted | 4 |
| AOR | 4 |
| ANOVA | 4 |
| A | 4 |
| Medicine | 4 |
| Bhasin | 4 |
| Blavatnik | 4 |
| Bonferroni | 4 |
| Coping | 4 |
| Dutheil | 4 |
| Don | 4 |
| Dhaka | 4 |
| Death | 4 |
| DT | 4 |
| D | 4 |
| Containment | 4 |
| Bosco | 4 |
| Chen | 4 |
| Census | 4 |
| CV | 4 |
| COVID19 | 4 |
| CMAQv5.2 | 4 |
| Básicas | 4 |
| Medical | 4 |
| Anurag | 4 |
| Meyer | 4 |
| Western | 4 |
| Vijay | 4 |
| Venter | 4 |
| Vehicle | 4 |
| Value | 4 |
| VAS | 4 |
| Use | 4 |
| Umer | 4 |
| UNDP | 4 |
| Tribune | 4 |
| Tracker | 4 |
| Taiwan | 4 |
| TBS | 4 |
| T. | 4 |
| Support | 4 |
| Sujoy | 4 |
| Weather | 4 |
| _ | 4 |
| Shammi | 4 |
| appendix | 4 |
| Microsoft | 4 |
| ± | 4 |
| reat | 4 |
| pandemic | 4 |
| p<0.1 | 4 |
| national | 4 |
| −1 | 4 |
| min | 4 |
| ij | 4 |
| https://doi.org/10.1101/2020.05.16.20104075 | 4 |
| https://doi.org/10.1101/2020.04.29.20084517 | 4 |
| eng | 4 |
| el | 4 |
| dl | 4 |
| b. | 4 |
| Springer | 4 |
| key | 4 |
| Services | 4 |
| Park | 4 |
| PED | 4 |
| PC2 | 4 |
| P. | 4 |
| Oslo | 4 |
| OMT | 4 |
| Norway | 4 |
| Nitschke | 4 |
| NYC | 4 |
| NPIs | 4 |
| NO3 | 4 |
| NCore | 4 |
| Monitoring | 4 |
| Models | 4 |
| Minority | 4 |
| Self | 4 |
| PLoS | 4 |
| NHPPs | 4 |
| Physical | 4 |
| S | 4 |
| Sciences | 4 |
| Santos | 4 |
| Pre | 4 |
| SVM | 4 |
| SLUCM | 4 |
| SA | 4 |
| S6 | 4 |
| SOM | 4 |
| Recovery | 4 |
| Road | 4 |
| Protection | 4 |
| Respiratory | 4 |
| Relaciones | 4 |
| RT | 4 |
| Roy | 4 |
| IM | 3 |
| HMRC | 3 |
| HPP | 3 |
| Hargreaves | 3 |
| Hawryluck | 3 |
| Hebei | 3 |
| Heavy | 3 |
| Hopkins | 3 |
| I.G. | 3 |
| ICMR | 3 |
| HCA | 3 |
| ILAE | 3 |
| HDV | 3 |
| GD | 3 |
| H. | 3 |
| Guidelines | 3 |
| Group | 3 |
| Gross | 3 |
| Great | 3 |
| Giannopoulou | 3 |
| G&A | 3 |
| Fu | 3 |
| Federal | 3 |
| FVG | 3 |
| FBG | 3 |
| Indians | 3 |
| F(1 | 3 |
| IQR | 3 |
| Low | 3 |
| Information | 3 |
| Lee | 3 |
| Estimation | 3 |
| Mortality | 3 |
| Mihashi | 3 |
| Middle | 3 |
| Mexico | 3 |
| Meta | 3 |
| Medtronic | 3 |
| Mean | 3 |
| Md. | 3 |
| Matlab | 3 |
| Machine | 3 |
| Liverpool | 3 |
| Kingdom | 3 |
| Innovation | 3 |
| Kaiser | 3 |
| K. | 3 |
| Joya | 3 |
| Journal | 3 |
| Johns | 3 |
| JHU | 3 |
| J. | 3 |
| Italian | 3 |
| Issues | 3 |
| Islam | 3 |
| Investigation | 3 |
| Interrupted | 3 |
| Express | 3 |
| Bourquin | 3 |
| Epidemiology | 3 |
| Audit | 3 |
| Bureau | 3 |
| Buela | 3 |
| Britain | 3 |
| Brief | 3 |
| Brazil | 3 |
| Municipal | 3 |
| Bolton | 3 |
| Blendon | 3 |
| Binomial | 3 |
| Balmford | 3 |
| BMI | 3 |
| Australian | 3 |
| Attribution | 3 |
| English | 3 |
| Areas | 3 |
| Application | 3 |
| Anupam | 3 |
| Andersen | 3 |
| Americans | 3 |
| Adolescent | 3 |
| Adjustment | 3 |
| Acute | 3 |
| ANSM | 3 |
| AMap | 3 |
| AM | 3 |
| = | 3 |
| CSSE | 3 |
| Caerphilly | 3 |
| Canopy | 3 |
| Canyon | 3 |
| Elmer | 3 |
| Economist | 3 |
| Econ | 3 |
| EDs | 3 |
| Dynamics | 3 |
| Dyadic | 3 |
| Domestic | 3 |
| Distress | 3 |
| Distancing | 3 |
| Digital | 3 |
| Diagnosis | 3 |
| Departments | 3 |
| Declaration | 3 |
| Database | 3 |
| Critical | 3 |
| Covid | 3 |
| Countries | 3 |
| Corona | 3 |
| Computer | 3 |
| Clinical | 3 |
| Clin | 3 |
| Chronopoulos | 3 |
| Chi | 3 |
| Chain | 3 |
| Casal | 3 |
| Multiscale | 3 |
| Af | 3 |
| nan | 3 |
| USAID | 3 |
| Wikipedia | 3 |
| 3 | |
| Welfare | 3 |
| Washington | 3 |
| Wales | 3 |
| WEF | 3 |
| Vilaregut | 3 |
| Variation | 3 |
| V.E. | 3 |
| V | 3 |
| Utah | 3 |
| Units | 3 |
| Transmission | 3 |
| Wilk | 3 |
| Trait | 3 |
| Tianjin | 3 |
| Therapeutics | 3 |
| Testing | 3 |
| Technology | 3 |
| Systems | 3 |
| Systematic | 3 |
| Syndrome | 3 |
| Switzerland | 3 |
| Surg | 3 |
| Strategy | 3 |
| Star | 3 |
| Wilcoxon | 3 |
| Wolverhampton | 3 |
| Spielberger | 3 |
| source/ | 3 |
| NCDC | 3 |
| � | 3 |
| − | 3 |
| ∑ | 3 |
| ∆NO | 3 |
| ݇ | 3 |
| ρ | 3 |
| γ | 3 |
| yellow | 3 |
| united | 3 |
| time | 3 |
| states | 3 |
| ses | 3 |
| Worldometer | 3 |
| re)connection | 3 |
| non‐lockdown | 3 |
| mars | 3 |
| las | 3 |
| ijqt | 3 |
| i0 | 3 |
| https://doi.org/10.1101 | 3 |
| glycemic | 3 |
| di | 3 |
| data | 3 |
| bing | 3 |
| Ying | 3 |
| Spread | 3 |
| des | 3 |
| Source | 3 |
| PHQ | 3 |
| Pornography | 3 |
| Poisson | 3 |
| Pharmacovigilance | 3 |
| Peak | 3 |
| Paulo | 3 |
| Paris | 3 |
| Panel | 3 |
| Pan | 3 |
| Package | 3 |
| PPE | 3 |
| PPBG | 3 |
| PHQ-9-Modified | 3 |
| PCR | 3 |
| Practice | 3 |
| P1 | 3 |
| Oxford | 3 |
| Outbreak | 3 |
| November | 3 |
| Newcastle | 3 |
| Nevada | 3 |
| Nazionale | 3 |
| Natural | 3 |
| NVT | 3 |
| NO(2 | 3 |
| Software | 3 |
| NK | 3 |
| Post | 3 |
| PCC | 3 |
| Pradesh | 3 |
| SL | 3 |
| Sky | 3 |
| Single | 3 |
| Prediction | 3 |
| Shapiro | 3 |
| Series | 3 |
| Sensor | 3 |
| Second | 3 |
| Satyaki | 3 |
| Sars | 3 |
| Sanz | 3 |
| STATA | 3 |
| SS | 3 |
| Screeners | 3 |
| SGD | 3 |
| R. | 3 |
| President | 3 |
| Product | 3 |
| Psychological | 3 |
| Preston | 3 |
| Python | 3 |
| RH | 3 |
| Relations | 3 |
| Republic | 3 |
| S3 | 3 |
| S5 | 3 |
| Gogo | 2 |
| Glycemic | 2 |
| Glucose | 2 |
| GitHub | 2 |
| Gilgit | 2 |
| Georgia | 2 |
| Geofisica | 2 |
| Gasoline | 2 |
| Generic | 2 |
| Gauteng | 2 |
| GCT | 2 |
| Gautam | 2 |
| GEV | 2 |
| Galanakis | 2 |
| GPS | 2 |
| Govt | 2 |
| Goldsztejn | 2 |
| Himanshu | 2 |
| Greater | 2 |
| High | 2 |
| Hydroxychloroquine | 2 |
| G.T. | 2 |
| Huang | 2 |
| Household | 2 |
| Horizon | 2 |
| Hindu | 2 |
| Helsinki | 2 |
| Green | 2 |
| Heat | 2 |
| HSE | 2 |
| HF | 2 |
| H1N1 | 2 |
| Gulsheen | 2 |
| Guidance | 2 |
| GAD | 2 |
| Edomah | 2 |
| Frédéric | 2 |
| Franco | 2 |
| Engagement | 2 |
| Emissions | 2 |
| Emilie | 2 |
| Emilia | 2 |
| Elimination | 2 |
| Electronic | 2 |
| El | 2 |
| Economics | 2 |
| Earth | 2 |
| EXP-20 | 2 |
| EU | 2 |
| EM | 2 |
| ELECTRONIC | 2 |
| EDRM | 2 |
| ICNARC | 2 |
| Enlite | 2 |
| Epidemic | 2 |
| Exacerbation | 2 |
| Fernandes | 2 |
| Forest | 2 |
| Forecasting | 2 |
| Food | 2 |
| Florence | 2 |
| Finland | 2 |
| File | 2 |
| Ferguson | 2 |
| Exacerbations | 2 |
| Farrell | 2 |
| FDA | 2 |
| FBCCI | 2 |
| F. | 2 |
| Exposure | 2 |
| Executive | 2 |
| I.k<-rowSums(I.matr | 2 |
| Lake | 2 |
| IEC | 2 |
| Jiao | 2 |
| LS3S3 | 2 |
| LS3S10 | 2 |
| LS3M6 | 2 |
| LS2S10 | 2 |
| LMI | 2 |
| LDV | 2 |
| LC | 2 |
| LANWPC | 2 |
| Kurmann | 2 |
| Krueger | 2 |
| Kong | 2 |
| Khyber | 2 |
| Kermack | 2 |
| Kashmir | 2 |
| K | 2 |
| LS3S4 | 2 |
| LSOAs | 2 |
| La | 2 |
| Light | 2 |
| MB | 2 |
| Luhar | 2 |
| Lovrić | 2 |
| Lombardy | 2 |
| Lodi | 2 |
| Living | 2 |
| Liberia | 2 |
| Drug | 2 |
| Lerman | 2 |
| Legislation | 2 |
| Learning | 2 |
| Land | 2 |
| Lancker | 2 |
| Lanarkshire | 2 |
| Joel | 2 |
| Jean | 2 |
| IEDCR | 2 |
| Jammu | 2 |
| Infectious | 2 |
| Infections | 2 |
| Infection | 2 |
| Inf | 2 |
| Industries | 2 |
| Indonesia | 2 |
| Index | 2 |
| Income | 2 |
| Impacts | 2 |
| Illness | 2 |
| Ibáñez | 2 |
| Ibid | 2 |
| Ian | 2 |
| IPT | 2 |
| INR | 2 |
| Inference | 2 |
| Insights | 2 |
| 2 | |
| Ireland | 2 |
| James | 2 |
| JRK | 2 |
| JOBSTRESS | 2 |
| Item | 2 |
| Istituto | 2 |
| Israel | 2 |
| Interventions | 2 |
| Insulin | 2 |
| Interpretation | 2 |
| Intermediates | 2 |
| Interface | 2 |
| Interest | 2 |
| Integrated | 2 |
| Int | 2 |
| E. | 2 |
| Ccovid-19 | 2 |
| Doza | 2 |
| Applied | 2 |
| Baker | 2 |
| Bai | 2 |
| Background | 2 |
| BMCT | 2 |
| BLD | 2 |
| BJMEMC | 2 |
| BASE | 2 |
| Azad | 2 |
| Authorities | 2 |
| Atlantic | 2 |
| Athanasios | 2 |
| Associated | 2 |
| Arabia | 2 |
| Approach | 2 |
| Appraisal | 2 |
| Baltistan | 2 |
| Basic | 2 |
| Bayesian | 2 |
| Book | 2 |
| Business | 2 |
| Burki | 2 |
| Building | 2 |
| Budget | 2 |
| Braun | 2 |
| Branley | 2 |
| Bolker | 2 |
| Bell | 2 |
| Bodrud | 2 |
| Board | 2 |
| Bloomfield | 2 |
| Birmingham | 2 |
| Bhutan | 2 |
| Ben | 2 |
| Apportionment | 2 |
| Anuraj | 2 |
| Dowd | 2 |
| Annex | 2 |
| ARC | 2 |
| AQI | 2 |
| API | 2 |
| ACC | 2 |
| ABSTRACT | 2 |
| A1 | 2 |
| 3fsn7awq | 2 |
| 0.01˚ | 2 |
| -Part | 2 |
| -11 | 2 |
| -0.548 | 2 |
| -0.362 | 2 |
| -0.314 | 2 |
| -0.110 | 2 |
| MEIC | 2 |
| Aberdeen | 2 |
| Academy | 2 |
| Access | 2 |
| Alexander | 2 |
| Anna | 2 |
| Andant | 2 |
| Amphan | 2 |
| American | 2 |
| Amap | 2 |
| Almaty | 2 |
| Alarm | 2 |
| Activity | 2 |
| Al | 2 |
| Affairs | 2 |
| Aerde | 2 |
| Advanced | 2 |
| Administrative | 2 |
| Adaptation | 2 |
| C1 | 2 |
| C2 | 2 |
| C2-A | 2 |
| C3 | 2 |
| Dashboard | 2 |
| Dadlani | 2 |
| DRAMES | 2 |
| DD | 2 |
| Cross | 2 |
| Criegee | 2 |
| CrI | 2 |
| Country | 2 |
| Counties | 2 |
| Coordination | 2 |
| Cooper | 2 |
| Contact | 2 |
| Consumption | 2 |
| Conger | 2 |
| Conditions | 2 |
| Dataset | 2 |
| Deaths | 2 |
| Deb | 2 |
| Disorder | 2 |
| Dordr | 2 |
| Document | 2 |
| Doctoral | 2 |
| Division | 2 |
| Distribution | 2 |
| Dissertation | 2 |
| Diamond | 2 |
| Delta | 2 |
| Diabetes | 2 |
| DiGiovanni | 2 |
| Dev | 2 |
| Design | 2 |
| Desclaux | 2 |
| Demographic | 2 |
| Computing | 2 |
| Compulsive | 2 |
| Complex | 2 |
| CPC | 2 |
| Cava | 2 |
| Cash | 2 |
| Case | 2 |
| Capital | 2 |
| Cao | 2 |
| CRediT | 2 |
| CP | 2 |
| Change | 2 |
| COVID-2019 | 2 |
| CI:2.34 | 2 |
| CI:0.36 | 2 |
| CERVEAU | 2 |
| CDC | 2 |
| C5 | 2 |
| Chaix | 2 |
| Charanpreet | 2 |
| Company | 2 |
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| UN | 2 |
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| Ville | 2 |
| Version | 2 |
| Verma | 2 |
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| Validación | 2 |
| VJL | 2 |
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| Uttar | 2 |
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| Urrego | 2 |
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| WS | 2 |
| WD | 2 |
| W | 2 |
| Underwood | 2 |
| 2 | |
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| Total | 2 |
| Tools | 2 |
| Tobías | 2 |
| Theory | 2 |
| Test | 2 |
| Territory | 2 |
| Zhou | 2 |
| association | 2 |
| Statement | 2 |
| p=0.008 | 2 |
| u.s | 2 |
| terapia | 2 |
| ter | 2 |
| tc | 2 |
| tau | 2 |
| squared | 2 |
| social | 2 |
| satunr | 2 |
| remdesivir | 2 |
| radical | 2 |
| post | 2 |
| portant | 2 |
| p=0.061 | 2 |
| p=0.019 | 2 |
| p=0.018 | 2 |
| uk | 2 |
| und | 2 |
| us | 2 |
| ΔHbA1c | 2 |
| MFE | 2 |
| ≥20 | 2 |
| ∀i | 2 |
| ݐ | 2 |
| ൌ | 2 |
| δ | 2 |
| ΔGDP | 2 |
| veh | 2 |
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| ±0.5 | 2 |
| west | 2 |
| p=0.013 | 2 |
| p<0.5 | 2 |
| author(s | 2 |
| ordonnances | 2 |
| gmd | 2 |
| forest | 2 |
| figures)-https | 2 |
| feature(s | 2 |
| fbcli | 2 |
| der | 2 |
| covid | 2 |
| contre | 2 |
| clínica | 2 |
| clinicaltrials.gov | 2 |
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| http://covid.gov.pk/stats/pakistan | 2 |
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| https://sfpt-fr.org/covid19 | 2 |
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| I.k<-I.k+(I0-sum(I.k))*P | 1 |
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| Jersey | 1 |
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| Independent | 1 |
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| Introduction | 1 |
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| Kerala | 1 |
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| LS2S12 | 1 |
| LS2S1-S3 | 1 |
| LS2M6 | 1 |
| LS2M5 | 1 |
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| LS1S6 | 1 |
| LS1S4-S9 | 1 |
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| LS1S15 | 1 |
| LS3M1-M5 | 1 |
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| LS1S12-LS1S15 | 1 |
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| Kristina | 1 |
| Kruskal | 1 |
| LS1S10 | 1 |
| Kuitunen | 1 |
| LS1S1 | 1 |
| LS1M3 | 1 |
| LS1M1-M3 | 1 |
| LR | 1 |
| LOT | 1 |
| LOCKDOWN | 1 |
| LMICs | 1 |
| LMIC | 1 |
| LFS | 1 |
| LDTs | 1 |
| LDT | 1 |
| L.-W. | 1 |
| Kutta | 1 |
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| Efstathiou | 1 |
| Corporation | 1 |
| Efficiency | 1 |
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| Assoc | 1 |
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| BGMEA | 1 |
| BEHAVIOURS | 1 |
| BDT12,744 | 1 |
| Ayudas | 1 |
| Ayres | 1 |
| Autumn | 1 |
| Aum | 1 |
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| Athens | 1 |
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| Bergamo | 1 |
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