Difference between revisions of "Covid"
From Nanopedia
| Line 8: | Line 8: | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 1 | | 1 | ||
| − | | Victoria Lopez, Madrit University<br /> | + | | '''Victoria Lopez''', Madrit University<br /> |
| A COVID-19 mathematical model based on Flow Networks and SIR.[https://www.youtube.com/watch?v=wIG7R0OMpWY&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=1]<br /> | | A COVID-19 mathematical model based on Flow Networks and SIR.[https://www.youtube.com/watch?v=wIG7R0OMpWY&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=1]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 2 | | 2 | ||
| − | | Axel Branderburg, KTH Stockholm | + | | '''Axel Branderburg''', KTH Stockholm |
| Piecewise quadratic growth during the 2019 novel coronavirus epidemic.[https://www.youtube.com/watch?v=1E_ugYzl-q4&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=2]<br /> | | Piecewise quadratic growth during the 2019 novel coronavirus epidemic.[https://www.youtube.com/watch?v=1E_ugYzl-q4&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=2]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 3 | | 3 | ||
| − | | Alessio Muscillo, University of Sienna<br /> | + | | '''Alessio Muscillo''', University of Sienna<br /> |
| Disease spreading in social networks and unintended consequences of weak social distancing.[https://www.youtube.com/watch?v=7tqBR3QqsmI&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=3]<br /> | | Disease spreading in social networks and unintended consequences of weak social distancing.[https://www.youtube.com/watch?v=7tqBR3QqsmI&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=3]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 4 | | 4 | ||
| − | | Marco Paggi, IMT School, Lucca | + | | '''Marco Paggi''', IMT School, Lucca |
| Simulation of Covid-19 epidemic evolution: are compartmental models really predictive?[https://www.youtube.com/watch?v=81ZCQyjvIKo&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=4]<br /> | | Simulation of Covid-19 epidemic evolution: are compartmental models really predictive?[https://www.youtube.com/watch?v=81ZCQyjvIKo&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=4]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 5 | | 5 | ||
| − | | Venkatesha Prasad, Delft University<br /> | + | | '''Venkatesha Prasad''', Delft University<br /> |
| A simple Stochastic SIR model for COVID-19.[https://www.youtube.com/watch?v=iO89rYkdE90&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=5]<br /> | | A simple Stochastic SIR model for COVID-19.[https://www.youtube.com/watch?v=iO89rYkdE90&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=5]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 6 | | 6 | ||
| − | | Ali Nasseri, British Columbia University<br /> | + | | '''Ali Nasseri''', British Columbia University<br /> |
| Planning as Inference in Epidemiological Dynamic Models.[https://www.youtube.com/watch?v=cqqrdvVta_Q&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=6]<br /> | | Planning as Inference in Epidemiological Dynamic Models.[https://www.youtube.com/watch?v=cqqrdvVta_Q&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=6]<br /> | ||
|- | |- | ||
| 7 | | 7 | ||
| − | | style="font-size:12px;" | Anand Sahasranaman, Imperial College London<br /> | + | | style="font-size:12px;" | '''Anand Sahasranaman''', Imperial College London<br /> |
| style="font-size:12px;" | Data and models of COVID-19 in India.[https://www.youtube.com/watch?v=1JAqpxhk8No&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=7]<br /> | | style="font-size:12px;" | Data and models of COVID-19 in India.[https://www.youtube.com/watch?v=1JAqpxhk8No&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=7]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 8 | | 8 | ||
| − | | V. K. Jindal, Penjab University | + | | '''V. K. Jindal''', Penjab University |
| COVID-19 – a realistic model for saturation, growth and decay of the India specific disease.[https://www.youtube.com/watch?v=_Gxw-wZA05Q&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=8]<br /> | | COVID-19 – a realistic model for saturation, growth and decay of the India specific disease.[https://www.youtube.com/watch?v=_Gxw-wZA05Q&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=8]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 9 | | 9 | ||
| − | | Sebastian Gonçalves, Physics Institute<br /> | + | | '''Sebastian Gonçalves''', Physics Institute<br /> |
| Trends and Urban scaling in the COVID-19 pandemic.[https://www.youtube.com/watch?v=aVXyxByBecQ&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=9]<br /> | | Trends and Urban scaling in the COVID-19 pandemic.[https://www.youtube.com/watch?v=aVXyxByBecQ&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=9]<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| 10 | | 10 | ||
| − | | Josimar Chire, ICMC Brasil<br /> | + | | '''Josimar Chire''', ICMC Brasil<br /> |
| Social Sensors to Monitor COVID-19 South American Countries.[https://www.youtube.com/watch?v=Mbqs-zmnxvs&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=10]<br /> | | Social Sensors to Monitor COVID-19 South American Countries.[https://www.youtube.com/watch?v=Mbqs-zmnxvs&list=PL_2_Wdyw43YN7MjG33OlWgsLGV1LxhvcF&index=10]<br /> | ||
|- | |- | ||
| Line 54: | Line 54: | ||
|- 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;" | ||
| style="text-align:center;" | 3 | | style="text-align:center;" | 3 | ||
| − | | Gaetano Perone, University of Bergamo | + | | '''Gaetano Perone''', University of Bergamo |
| An Arima Model to Forecast the Spread and the final size of COVID-2019 Epidemic in Italy | | An Arima Model to Forecast the Spread and the final size of COVID-2019 Epidemic in Italy | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 4 | | style="text-align:center;" | 4 | ||
| − | | Keno Krewer, Max Planck Institute<br /> | + | | '''Keno Krewer''', Max Planck Institute<br /> |
| Time-resolving an ongoing outbreak with Fourier analysis | | Time-resolving an ongoing outbreak with Fourier analysis | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 5 | | style="text-align:center;" | 5 | ||
| − | | Gerry Killeen, University College Cork<br /> | + | | '''Gerry Killeen''', University College Cork<br /> |
| Pushing past the tipping points in containment trajectories of Severe Acute Respiratory Syndrome <br />Coronavirus 2 (SARS-CoV-2) epidemics: A simple arithmetic rationale for crushing the curve instead of merely flattening it.<br /> | | Pushing past the tipping points in containment trajectories of Severe Acute Respiratory Syndrome <br />Coronavirus 2 (SARS-CoV-2) epidemics: A simple arithmetic rationale for crushing the curve instead of merely flattening it.<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 6 | | style="text-align:center;" | 6 | ||
| − | | Michael Li, University of Alberta | + | | '''Michael Li''', University of Alberta |
| Why it is difficulty to make accurate predictions of COVID-19 epidemics? | | Why it is difficulty to make accurate predictions of COVID-19 epidemics? | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 7 | | style="text-align:center;" | 7 | ||
| − | | V.K. Jindal, Panjab University<br /> | + | | '''V.K. Jindal''', Panjab University<br /> |
| COVID-19 Primary and secondary infection as order parameter – a unifying global model.<br /> | | COVID-19 Primary and secondary infection as order parameter – a unifying global model.<br /> | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 8 | | style="text-align:center;" | 8 | ||
| − | | Ashis Das, World Bank<br /> | + | | '''Ashis Das''', World Bank<br /> |
| Rapid development of an open-access artificial intelligence decision support tool for CoVID-19 mortality prediction | | Rapid development of an open-access artificial intelligence decision support tool for CoVID-19 mortality prediction | ||
|- style="font-size:12px;" | |- style="font-size:12px;" | ||
| style="text-align:center;" | 9 | | style="text-align:center;" | 9 | ||
| − | | Fulgensia Mbabazi, Busitema University<br /> | + | | '''Fulgensia Mbabazi''', Busitema University<br /> |
| A Mathematical Model Approach for Prevention and Intervention Measures of the COVID-19 Pandemic in Uganda<br /> | | A Mathematical Model Approach for Prevention and Intervention Measures of the COVID-19 Pandemic in Uganda<br /> | ||
|} | |} | ||
Latest revision as of 08:18, 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.[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 |
