COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv

30,891 Articles (22,568 medRxiv, 8,323 bioRxiv)

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Population simulations of COVID-19 outbreaks provide tools for risk assessment and continuity planning
Peng, B., Amos, C. I.
10.1101/2020.04.13.20064253 — Posted: 2020-04-17
Lymphocytopaenia is associated with severe SARS-CoV-2 disease: A Systematic Review and Meta-Analysis of Clinical Data
Brown, R. A. C., Barnard, J., Harris-Skillman, E., Harbinson, B., Dunne, B., Drake, J., Roche, S., Harris, E., Gunnel, J., Frost, J., Angus, B., Hodgson, S.
10.1101/2020.04.14.20064659 — Posted: 2020-04-17
Importance of untested infectious individuals for the suppression of COVID-19 epidemics
Perez-Reche, F., Strachan, N.
10.1101/2020.04.13.20064022 — Posted: 2020-04-17
Do Weather Temperature and Median-age affect COVID-19 Transmission?
Kassem, A. Z. E.
10.1101/2020.04.16.20067355 — Posted: 2020-04-17
REGIONAL DETERMINANTS OF THE EXPANSION OF COVID-19 IN BRAZIL
Rodrigues, W., Prata, D. N., Camargo, W.
10.1101/2020.04.13.20063925 — Posted: 2020-04-17
Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans
He, X., Yang, X., Zhang, S., Zhao, J., Zhang, Y., Xing, E., Xie, P.
10.1101/2020.04.13.20063941 — Posted: 2020-04-17
Accurate Prediction of COVID-19 using Chest X-Ray Images through Deep Feature Learning model with SMOTE and Machine Learning Classifiers
Kumar, R., Arora, R., Bansal, V., Sahayasheela, V. J., Buckchash, H., Imran, J., Narayanan, N., Pandian, G. N., Raman, B.
10.1101/2020.04.13.20063461 — Posted: 2020-04-17 Discussion: Onsite
Machine Learning Analysis of Chest CT Scan Images as a Complementary Digital Test of Coronavirus (COVID-19) Patients
Al-karawi, D., Al-Zaidi, S., Polus, N., Jassim, S.
10.1101/2020.04.13.20063479 — Posted: 2020-04-17
Nowcasting and Forecasting the Spread of COVID-19 and Healthcare Demand In Turkey, A Modelling Study
Ucar, A., Arslan, S., Ozdemir, M. Y.
10.1101/2020.04.13.20063305 — Posted: 2020-04-17
The Potential role of Particulate Matter in the Spreading of COVID-19 in Northern Italy: First Evidence-based Research Hypotheses
Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M. G., Piazzalunga, A., Borelli, M., Palmisani, J., Di Gilio, A., PISCITELLI, P., Miani, A.
10.1101/2020.04.11.20061713 — Posted: 2020-04-17 Discussion: Onsite

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* The Clinical Trials and Epidemiology subject categories are now closed to new submissions following the completion of bioRxiv's clinical research pilot project and launch of the dedicated health sciences server medRxiv (submit.medrxiv.org). New papers that report results of Clinical Trials must now be submitted to medRxiv. Most new Epidemiology papers also should be submitted to medRxiv, but if a paper contains no health-related information, authors may choose to submit it to another bioRxiv subject category (e.g., Genetics or Microbiology).