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

31,248 Articles (22,733 medRxiv, 8,515 bioRxiv)

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Age groups that sustain resurging COVID-19 epidemics in the United States
Monod, M., Blenkinsop, A., Xi, X., Hebert, D., Bershan, S., Bradley, V. C., Chen, Y., Coupland, H., Filippi, S., Ish-Horowicz, J., McManus, M., Mellan, T. A., Gandy, A., Hutchinson, M., Unwin, H. J. T., Vollmer, M. A. C., Weber, S., Zhu, H., Bezancon, A., Tietze, S., Ferguson, N. M., Mishra, S., Flaxman, S., Bhatt, S., Ratmann, O., Imperial College London COVID-19 Response Team
10.1101/2020.09.18.20197376 — Posted: 2020-09-22
COVID-19: Risks of Re-emergence, Re-infection, and Control Measures -- A Long Term Modelling Study
Ghosh, S. K., Ghosh, S.
10.1101/2020.09.19.20198051 — Posted: 2020-09-22
Epidemiology of COVID-19 vs. Influenza: Differential Failure of COVID-19 Mitigation among Hispanics
Trick, W. E., Badri, S., Doshi, K., Zhang, H., Rezai, K., Hoffman, M. J., Weinstein, R. A.
10.1101/2020.09.21.20199018 — Posted: 2020-09-22
Estimation and Interactive Visualization of the Time-Varying Reproduction Number Rt and the Time-Delay from Infection to Estimation
Valka, F., Schuler, C.
10.1101/2020.09.19.20197970 — Posted: 2020-09-22
A comparison of five epidemiological models for transmission of SARS-CoV-2 in India
Purkayastha, S., Bhattacharyya, R., Bhaduri, R., Kundu, R., Gu, X., Salvatore, M., Mishra, S., Mukherjee, B.
10.1101/2020.09.19.20198010 — Posted: 2020-09-22
Analysis of geo-temporal evolution and modeling of the COVID-19 epidemic in Libya
Bredan, A., Benamer, H., Bakoush, O.
10.1101/2020.09.19.20197822 — Posted: 2020-09-22
Quantifying the Effects of Social Distancing on theSpread of COVID-19
Daghriri, T., Ozmen, O.
10.1101/2020.09.19.20197996 — Posted: 2020-09-22
An improved method to estimate the effective reproduction number of the COVID-19 pandemic: lessons from its application in Greece
Lytras, T., Sypsa, V., Panagiotakos, D., Tsiodras, S.
10.1101/2020.09.19.20198028 — Posted: 2020-09-22
Vent-Lock: A 3D Printed Ventilator Multiplexer to Enhance the Capacity of Treating Patients with COVID-19
Xun, H., Shallal, C., Unger, J., Tao, R., Torres, A., Vladimirov, M., Frye, J., Singhala, M., Horne, B., Yesantharao, P., Kim, B. S., Burke, B., Montana, M., Talcott, M., Winters, B., Frisella, M., Kushner, B., Sacks, J., Guest, J., Kang, S. H., Caffrey, J.
10.1101/2020.09.16.20195230 — Posted: 2020-09-22
Uncovering clinical risk factors and prediction of severe COVID-19: A machine learning approach based on UK Biobank data
WONG, K. C. Y., So, H.-C.
10.1101/2020.09.18.20197319 — Posted: 2020-09-22 Discussion: Onsite

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