Covid
From Nanopedia
COVID-19 by the Numbers, Models, Big Data, and Reality - April 24th - 25th, 2020 | ||
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# | Lecturer Name | Lecture Title |
1 | Victoria Lopez, Madrit University |
A COVID-19 mathematical model based on Flow Networks and SIR.[1] |
2 | Axel Branderburg, KTH Stockholm | Piecewise quadratic growth during the 2019 novel coronavirus epidemic.[2] |
3 | Alessio Muscillo, University of Sienna |
Disease spreading in social networks and unintended consequences of weak social distancing.[3] |
4 | Marco Paggi, IMT School, Lucca | Simulation of Covid-19 epidemic evolution: are compartmental models really predictive?[4] |
5 | Venkatesha Prasad, Delft University |
A simple Stochastic SIR model for COVID-19.[5] |
6 | Ali Nasseri, British Columbia University |
Planning as Inference in Epidemiological Dynamic Models.[6] |
7 | Anand Sahasranaman, Imperial College London |
Data and models of COVID-19 in India.[7] |
8 | V. K. Jindal, Penjab University | COVID-19 – a realistic model for saturation, growth and decay of the India specific disease.[8] |
9 | Sebastian Gonçalves, Physics Institute |
Trends and Urban scaling in the COVID-19 pandemic.[9] |
10 | Josimar Chire, ICMC Brasil |
Social Sensors to Monitor COVID-19 South American Countries.[10] |
COVID-19 Forecast and Prediction - May 15th -16th, 2020 | ||
# | Lecturer Name |
Lecture Title |
1 | David S. Jones, Harvard University | History in a Crisis—Lessons for Covid-19 |
2 | Christofer Brandt, Universität Greifswald |
Transparent comparison and prediction of corona numbers |
3 | Gaetano Perone, University of Bergamo | An Arima Model to Forecast the Spread and the final size of COVID-2019 Epidemic in Italy |
4 | Keno Krewer, Max Planck Institute |
Time-resolving an ongoing outbreak with Fourier analysis |
5 | Gerry Killeen, University College Cork |
Pushing past the tipping points in containment trajectories of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) epidemics: A simple arithmetic rationale for crushing the curve instead of merely flattening it. |
6 | Michael Li, University of Alberta | Why it is difficulty to make accurate predictions of COVID-19 epidemics? |
7 | V.K. Jindal, Panjab University |
COVID-19 Primary and secondary infection as order parameter – a unifying global model. |
8 | Ashis Das, World Bank |
Rapid development of an open-access artificial intelligence decision support tool for CoVID-19 mortality prediction |
9 | Fulgensia Mbabazi, Busitema University |
A Mathematical Model Approach for Prevention and Intervention Measures of the COVID-19 Pandemic in Uganda |