Difference between revisions of "Covid"

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! colspan="3" style="text-align:center; font-size:15px; font-family:'Arial Black', Gadget, sans-serif !important;; background-color:#dae8fc;" | COVID-19 Forecast and Prediction - May 15th -16th, 2020<br />
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! 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
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|- style="background-color:#ffffc7;"
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| #
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| Lecturer Name
 +
| Lecture Title
 +
|- style="font-size:12px;"
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| 1
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| Victoria Lopez, Madrit University<br />
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| A COVID-19 mathematical model based on Flow Networks and SIR<br />
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|- style="font-size:12px;"
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| 2
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| Axel Branderburg, KTH Stockholm
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| Piecewise quadratic growth during the 2019 novel coronavirus epidemic<br />
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|- style="font-size:12px;"
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| 3
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| Alessio Muscillo, University of Sienna<br />
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| Disease spreading in social networks and unintended consequences of weak social distancing<br />
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|- style="font-size:12px;"
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| 4
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| Marco Paggi, IMT School, Lucca
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| Simulation of Covid-19 epidemic evolution: are compartmental models really predictive?<br />
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|- style="font-size:12px;"
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| 5
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| Venkatesha Prasad, Delft University<br />
 +
| A simple Stochastic SIR model for COVID-19<br />
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|- style="font-size:12px;"
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| 6
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| Ali Nasseri, British Columbia University<br />
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| Planning as Inference in Epidemiological Dynamic Models<br />
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|-
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| 7
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| style="font-size:12px;" | Anand Sahasranaman,  Imperial College London<br />
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| style="font-size:12px;" | Data and models of COVID-19 in India<br />
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|- style="font-size:12px;"
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| 8
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| V. K. Jindal, Penjab University
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| COVID-19 – a realistic model for saturation, growth and decay of the India specific disease<br />
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|- style="font-size:12px;"
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| 9
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| Sebastian Gonçalves, Physics Institute<br />
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| Trends and Urban scaling in the COVID-19 pandemic<br />
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|- style="font-size:12px;"
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| 10
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| 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
+
| 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 />
+
| 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