Difference between revisions of "Covid"
From Nanopedia
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{| class="wikitable" | {| class="wikitable" | ||
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− | ! colspan="3" style="text-align:center; font-size: | + | ! colspan="3" style="text-align:center; font-size:18px; font-family:'Arial Black', Gadget, sans-serif !important;; background-color:#dae8fc;" | COVID-19 by the Numbers, Models, Big Data, and Reality - April 24th - 25th, 2020 |
+ | |- style="background-color:#ffffc7;" | ||
+ | | # | ||
+ | | Lecturer Name | ||
+ | | Lecture Title | ||
+ | |- style="font-size:12px;" | ||
+ | | 1 | ||
+ | | Victoria Lopez, Madrit University<br /> | ||
+ | | A COVID-19 mathematical model based on Flow Networks and SIR<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 2 | ||
+ | | Axel Branderburg, KTH Stockholm | ||
+ | | Piecewise quadratic growth during the 2019 novel coronavirus epidemic<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 3 | ||
+ | | Alessio Muscillo, University of Sienna<br /> | ||
+ | | Disease spreading in social networks and unintended consequences of weak social distancing<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 4 | ||
+ | | Marco Paggi, IMT School, Lucca | ||
+ | | Simulation of Covid-19 epidemic evolution: are compartmental models really predictive?<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 5 | ||
+ | | Venkatesha Prasad, Delft University<br /> | ||
+ | | A simple Stochastic SIR model for COVID-19<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 6 | ||
+ | | Ali Nasseri, British Columbia University<br /> | ||
+ | | Planning as Inference in Epidemiological Dynamic Models<br /> | ||
+ | |- | ||
+ | | 7 | ||
+ | | style="font-size:12px;" | Anand Sahasranaman, Imperial College London<br /> | ||
+ | | style="font-size:12px;" | Data and models of COVID-19 in India<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 8 | ||
+ | | V. K. Jindal, Penjab University | ||
+ | | COVID-19 – a realistic model for saturation, growth and decay of the India specific disease<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 9 | ||
+ | | Sebastian Gonçalves, Physics Institute<br /> | ||
+ | | Trends and Urban scaling in the COVID-19 pandemic<br /> | ||
+ | |- style="font-size:12px;" | ||
+ | | 10 | ||
+ | | Josimar Chire, ICMC Brasil<br /> | ||
+ | | Social Sensors to Monitor COVID-19 South American Countries<br /> | ||
+ | |- | ||
+ | | colspan="3" style="text-align:center; font-size:18px; font-family:'Arial Black', Gadget, sans-serif !important;; background-color:#dae8fc;" | COVID-19 Forecast and Prediction - May 15th -16th, 2020<br /> | ||
|- style="text-align:center; font-size:15px; background-color:#ffffc7;" | |- style="text-align:center; font-size:15px; background-color:#ffffc7;" | ||
| # | | # | ||
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|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 1 | | style="text-align:center;" | 1 | ||
− | | | + | | David S. Jones, Harvard University |
| History in a Crisis—Lessons for Covid-19 | | History in a Crisis—Lessons for Covid-19 | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 2 | | style="text-align:center;" | 2 | ||
− | | | + | | Christofer Brandt, Universität Greifswald<br /> |
| Transparent comparison and prediction of corona numbers | | Transparent comparison and prediction of corona numbers | ||
|- style="font-size:12px;" | |- style="font-size:12px;" |
Revision as of 06:43, 27 May 2020
COVID-19 by the Numbers, Models, Big Data, and Reality - April 24th - 25th, 2020 | ||
---|---|---|
# | Lecturer Name | Lecture Title |
1 | Victoria Lopez, Madrit University |
A COVID-19 mathematical model based on Flow Networks and SIR |
2 | Axel Branderburg, KTH Stockholm | Piecewise quadratic growth during the 2019 novel coronavirus epidemic |
3 | Alessio Muscillo, University of Sienna |
Disease spreading in social networks and unintended consequences of weak social distancing |
4 | Marco Paggi, IMT School, Lucca | Simulation of Covid-19 epidemic evolution: are compartmental models really predictive? |
5 | Venkatesha Prasad, Delft University |
A simple Stochastic SIR model for COVID-19 |
6 | Ali Nasseri, British Columbia University |
Planning as Inference in Epidemiological Dynamic Models |
7 | Anand Sahasranaman, Imperial College London |
Data and models of COVID-19 in India |
8 | V. K. Jindal, Penjab University | COVID-19 – a realistic model for saturation, growth and decay of the India specific disease |
9 | Sebastian Gonçalves, Physics Institute |
Trends and Urban scaling in the COVID-19 pandemic |
10 | Josimar Chire, ICMC Brasil |
Social Sensors to Monitor COVID-19 South American Countries |
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 |