Difference between revisions of "COVID-19"

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|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
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[https://www.youtube.com/results?search_query=COVID+19+corona+virus+novel+coronavirus+ai Youtube search...]
 
[https://www.youtube.com/results?search_query=COVID+19+corona+virus+novel+coronavirus+ai Youtube search...]
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** [[Healthcare]]
 
** [[Healthcare]]
 
** [[Bioinformatics]]
 
** [[Bioinformatics]]
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** [[Risk, Compliance and Regulation]]
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* [[Risk, Compliance and Regulation]] ... [[Ethics]] ... [[Privacy]] ... [[Law]] ... [[AI Governance]] ... [[AI Verification and Validation]]
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*** [[Screening; Passenger, Luggage, & Cargo]]
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* [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
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** [[Personal Relationships]]
 
−
* [[Government Services]]
 
−
** [[National Institute of Standards and Technology (NIST)]]
 
−
** [[U.S. Department of Homeland Security (DHS)]]
 
−
** [[Defense]]
 
 
* [[First Responder]]
 
* [[First Responder]]
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* [[Network Pattern]]
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* [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]]
 +
* [[Contextual Literature-Based Discovery (C-LBD)]]
 
* [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]]  ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ...  [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]]
 
* [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]]  ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ...  [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]]
 +
* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]]
 
* [https://thenextweb.com/neural/2020/07/24/heres-why-ai-didnt-save-us-from-covid-19/ Here’s why AI didn’t save us from COVID-19 | Tristan Greene - TNW]
 
* [https://thenextweb.com/neural/2020/07/24/heres-why-ai-didnt-save-us-from-covid-19/ Here’s why AI didn’t save us from COVID-19 | Tristan Greene - TNW]
 +
* [[Life~Meaning]] ... [[Consciousness]] ... [[Loop#Feedback Loop - Creating Consciousness|Creating Consciousness]] ... [[Quantum#Quantum Biology|Quantum Biology]]  ... [[Orch-OR]] ... [[TAME]] ... [[Protein Folding & Discovery|Proteins]]
 +
* [https://fortune.com/well/2023/10/13/scientists-use-artifical-intelligence-predict-next-big-covid-variants-pandemic-hiv-flu-lassa-nipah-virus/ Scientists are using AI to forecast the future of COVID—and, potentially, to predict the next pandemic | Erin Prater - Fortune]
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<youtube>ehjVRmHqTvA</youtube>
 
<youtube>ehjVRmHqTvA</youtube>
 
<b>Collective and Augmented Intelligence Against COVID-19 (CAIAC) Launch
 
<b>Collective and Augmented Intelligence Against COVID-19 (CAIAC) Launch
−
</b><br>A virtual event hosted by the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and the AI Initiative at The Future Society to officially announce a global alliance on the COVID-19 pandemic response. The alliance will provide an information service not yet available that is vitally important to facing and mitigating the crisis. In parallel with the UN High Level Political Forum, the launch agenda will include details on the partnership and speakers from the private sector, academia, government, and multilateral institutions, including UNESCO, the World Bank, the WHO and UN Global Pulse, offering unique perspectives on the roadblocks and opportunities to addressing the COVID-19 pandemic. Topics covered will include challenges with disparate data and determining meaningful information in the fight against the virus, as well as the importance of building multi-stakeholder collaborations.  [[Creatives#Fei-Fei Li |Fei-Fei Li]]
+
</b><br>A virtual event hosted by the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and the AI Initiative at The Future Society to officially announce a global alliance on the COVID-19 pandemic response. The alliance will provide an information service not yet available that is vitally important to facing and mitigating the crisis. In parallel with the UN High Level Political Forum, the launch agenda will include details on the partnership and speakers from the private sector, academia, government, and multilateral institutions, including UNESCO, the World Bank, the WHO and UN Global Pulse, offering unique [[perspective]]s on the roadblocks and opportunities to addressing the COVID-19 pandemic. Topics covered will include challenges with disparate data and determining meaningful information in the fight against the virus, as well as the importance of building multi-stakeholder collaborations.  [[Creatives#Fei-Fei Li |Fei-Fei Li]]
 
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<youtube>A0uBdY4Crlg</youtube>
 
<youtube>A0uBdY4Crlg</youtube>
 
<b>Analyzing COVID-19: Can the Data Community Help?
 
<b>Analyzing COVID-19: Can the Data Community Help?
−
</b><br>Online Tech Talk hosted by Denny Lee, Developer Advocate @ Databricks My name is Denny Lee and I’m a Developer Advocate at Databricks. But before this, I was a biostatistician working on HIV/AIDS research at the Fred Hutchinson Cancer Research Center and University of Washington Virology Lab in the Seattle-area. Watching my friends and colleagues working the front lines of this current pandemic has inspired me to see if we - as the data scientist community - can potentially help with “flattening the curve”. But before we dive into data science, remember - the most important thing you can do is wash your hands and social distancing! With the current concerns over SARS-Cov-2 and COVID-19, there are now available various COVID-19 datasets on Kaggle and GitHub as well as competitions such as the COVID-19 Open Research Dataset Challenge (CORD-19). Whether you are a student or a professional data scientist, we thought we could help out by providing a primer session with notebooks on how to start analyzing these datasets. For this primer session we will review (and shortly publish thereafter) iPython notebooks working with Apache Spark and/or Pandas (or both) for the following datas sets.  
+
</b><br>Online Tech Talk hosted by Denny Lee, Developer Advocate @ [[Databricks]] My name is Denny Lee and I’m a Developer Advocate at [[Databricks]]. But before this, I was a biostatistician working on HIV/AIDS research at the Fred Hutchinson Cancer Research Center and University of Washington Virology Lab in the Seattle-area. Watching my friends and colleagues working the front lines of this current pandemic has inspired me to see if we - as the data scientist community - can potentially help with “flattening the curve”. But before we dive into data science, remember - the most important thing you can do is wash your hands and social distancing! With the current concerns over SARS-Cov-2 and COVID-19, there are now available various COVID-19 datasets on Kaggle and GitHub as well as competitions such as the COVID-19 Open Research Dataset Challenge (CORD-19). Whether you are a student or a professional data scientist, we thought we could help out by providing a primer session with notebooks on how to start analyzing these datasets. For this primer session we will review (and shortly publish thereafter) iPython notebooks working with Apache Spark and/or Pandas (or both) for the following datas sets.  
 
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<youtube>8dskS7iOZZs</youtube>
 
<youtube>8dskS7iOZZs</youtube>
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<b>Graph Gurus 37: Combining Natural Language Processing with a Graph Database for COVID-19 Dataset
+
<b>[[Graph]] Gurus 37: Combining Natural Language Processing with a [[Graph]] [[Database]] for COVID-19 Dataset
 
</b><br>Learn how to process text and extract entities (words and phrases) as well as classes linking the entities using SciSpacy, a [[Natural Language Processing (NLP)]] tool. Import the output of NLP and semantically link it in TigerGraph  Run advanced analytics queries with TigerGraph to analyze the relationships and deliver insights  
 
</b><br>Learn how to process text and extract entities (words and phrases) as well as classes linking the entities using SciSpacy, a [[Natural Language Processing (NLP)]] tool. Import the output of NLP and semantically link it in TigerGraph  Run advanced analytics queries with TigerGraph to analyze the relationships and deliver insights  
 
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* [[StructBERT]] - Fight Coronavirus
 
* [[StructBERT]] - Fight Coronavirus
  
−
When the Coronavirus outbreak hit [[Government Services#China|China]], Alibaba’s DAMO Academy developed the [[StructBERT]] NLP model. Being deployed in Alibaba’s ecosystem, the model powered not only the search engine on Alibaba’s retail platforms but also anonymous healthcare data analysis. By analyzing the text of medical records and epidemiological investigation, the Centers for Disease Control (CDCs) used [[StructBERT]] for fighting against COVID-19 in [[Government Services#China|China]] cities. Being based on the BERT pre-trained model, StructBert not only understands the context of words in search queries but also leverages the structural information: sentence-level ordering and word-level ordering.
+
When the Coronavirus outbreak hit [[Government Services#China|China]], Alibaba’s DAMO Academy developed the [[StructBERT]] NLP model. Being deployed in Alibaba’s ecosystem, the model powered not only the search engine on Alibaba’s retail platforms but also anonymous healthcare data analysis. By analyzing the text of medical records and epidemiological investigation, the Centers for Disease Control (CDCs) used [[StructBERT]] for fighting against COVID-19 in [[Government Services#China|China]] cities. Being based on the BERT pre-trained model, StructBert not only understands the [[context]] of words in search queries but also leverages the structural information: sentence-level ordering and word-level ordering.
  
 
== [[Kaggle]] ==
 
== [[Kaggle]] ==
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<youtube>Gi-wfXFDK44</youtube>
 
<youtube>Gi-wfXFDK44</youtube>
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<b>Detecting COVID - 19 cases with RPA, #AI and Machine Learning - UiPath
+
<b>Detecting COVID - 19 cases with [[Robotic Process Automation (RPA)]], #AI and Machine Learning - UiPath
 
</b><br>Based on UiPath AI Fabric and with a touch of MachineLearning, Radu Pruna from our Immersion Lab built a model for detecting COVID-19 cases from X-ray chest images in seconds. The model is described in this paper - https://bit.ly/3awDEym.
 
</b><br>Based on UiPath AI Fabric and with a touch of MachineLearning, Radu Pruna from our Immersion Lab built a model for detecting COVID-19 cases from X-ray chest images in seconds. The model is described in this paper - https://bit.ly/3awDEym.
 
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<youtube>pQM-OGfLAX0</youtube>
 
<youtube>pQM-OGfLAX0</youtube>
 
<b>A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment
 
<b>A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment
−
</b><br>Motivated by the current COVID-19 outbreak, we introduce a novel epidemic model based on marked temporal point processes that is specifically designed to make fine-grained spatiotemporal predictions about the course of the disease in a population. Our model can make use and benefit from data gathered by a variety of contact tracing technologies and it can quantify the effects that different testing and tracing strategies, social distancing measures, and business restrictions may have on the course of the disease. Building on our model, we use [[Bayes|Bayesian]] optimization to estimate the risk of exposure of each individual at the sites they visit and the difference in transmission rate between asymptomatic and symptomatic individuals from historical longitudinal testing data. Experiments using real COVID-19 data and mobility patterns from several towns and regions in Germany and Switzerland demonstrate that our model can be used to quantify the effects of tracing, testing, and containment strategies at an unprecedented spatiotemporal resolution. To facilitate research and informed policy-making, particularly in the context of the current COVID-19 outbreak, we are releasing an open-source implementation of our framework at https://github.com/covid19-model. Manuel Gomez Rodriguez is a tenure-track faculty at Max Planck Institute for Software Systems. Manuel develops human-centered machine learning models and algorithms for the analysis, modeling and control of social, information and networked systems.  
+
</b><br>Motivated by the current COVID-19 outbreak, we introduce a novel epidemic model based on marked temporal point processes that is specifically designed to make fine-grained spatiotemporal predictions about the course of the disease in a population. Our model can make use and benefit from data gathered by a variety of contact tracing technologies and it can quantify the effects that different testing and tracing strategies, social distancing measures, and business restrictions may have on the course of the disease. Building on our model, we use [[Bayes|Bayesian]] optimization to estimate the risk of exposure of each individual at the sites they visit and the difference in transmission rate between asymptomatic and symptomatic individuals from historical longitudinal testing data. Experiments using real COVID-19 data and mobility patterns from several towns and regions in Germany and Switzerland demonstrate that our model can be used to quantify the effects of tracing, testing, and containment strategies at an unprecedented spatiotemporal resolution. To facilitate research and informed policy-making, particularly in the [[context]] of the current COVID-19 outbreak, we are releasing an open-source implementation of our framework at https://github.com/covid19-model. Manuel Gomez Rodriguez is a tenure-track faculty at Max Planck Institute for Software Systems. Manuel develops human-centered machine learning models and algorithms for the analysis, modeling and control of social, information and networked systems.  
 
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13:45 - Dr. Eva Lee - Modeling and Evaluating Intervention Options and Strategies for COVID-19 Containment: A Biological-Behavioral-Logistics Computation Decision Framework
 
13:45 - Dr. Eva Lee - Modeling and Evaluating Intervention Options and Strategies for COVID-19 Containment: A Biological-Behavioral-Logistics Computation Decision Framework
 
14:45 - break
 
14:45 - break
−
15:00 - Roger Ng, MD - Ray NG, MD - COVID-19: A Front-Line Physician’s Perspective
+
15:00 - Roger Ng, MD - Ray NG, MD - COVID-19: A Front-Line Physician’s [[Perspective]]
 
15:45 - Dr. Deborah Duong - Modeling COVID-19 Using Simulated [[Agents]] with Intelligence and Culture
 
15:45 - Dr. Deborah Duong - Modeling COVID-19 Using Simulated [[Agents]] with Intelligence and Culture
 
16:30 - Break
 
16:30 - Break
−
16:45 - Vinay Gupta, Dr. Anish Mohammad, Dr. Mircea Davidescu, Dr.Nabarun Dasgupta - Panel: Simulating the Pandemic: Perspectives on COVID-19 Modeling. Moderate by Gina Smith
+
16:45 - Vinay Gupta, Dr. Anish Mohammad, Dr. Mircea Davidescu, Dr.Nabarun Dasgupta - Panel: Simulating the Pandemic: [[Perspectives]] on COVID-19 Modeling. Moderate by Gina Smith
 
17:45 - Break
 
17:45 - Break
 
17:50 - Dr. Ben Goertzel - [[Agents|Agent]]-Based Modeling of COVID-19 -- Next Steps and Broader Implications  
 
17:50 - Dr. Ben Goertzel - [[Agents|Agent]]-Based Modeling of COVID-19 -- Next Steps and Broader Implications  
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<youtube>LQCGeboXZkc</youtube>
 
<youtube>LQCGeboXZkc</youtube>
 
<b>Data Modelling and Analysis of COVID-19 Spread using Python Code: Session by a Data Scientist
 
<b>Data Modelling and Analysis of COVID-19 Spread using Python Code: Session by a Data Scientist
−
</b><br>Currently, there are so many dashboards and statistics around the Coronavirus spread available all over the internet. With so much information and expert opinions, to see different nations adopting different strategies, from complete lockdown to social distancing to herd immunity, one is left thinking as to what the right strategy is for them. Is there any basis to these opinions and advice? This session is an attempt of data modelling and analysing Coronavirus (COVID-19) spread with the help of data science and data analytics in python code. This analysis will help us to find the basis behind common notions about the virus spread from purely a dataset perspective. So, let’s flex some data science muscles and jump right into it.
+
</b><br>Currently, there are so many dashboards and statistics around the Coronavirus spread available all over the internet. With so much information and expert opinions, to see different nations adopting different strategies, from complete lockdown to social distancing to herd immunity, one is left thinking as to what the right strategy is for them. Is there any basis to these opinions and advice? This session is an attempt of data modelling and analysing Coronavirus (COVID-19) spread with the help of data science and data analytics in python code. This analysis will help us to find the basis behind common notions about the virus spread from purely a dataset [[perspective]]. So, let’s flex some data science muscles and jump right into it.
 
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<youtube>q6KW1Q1XyzA</youtube>
 
<youtube>q6KW1Q1XyzA</youtube>
 
<b>Using Artificial Intelligence to Unlock the structure of SARS-COV-2
 
<b>Using Artificial Intelligence to Unlock the structure of SARS-COV-2
−
</b><br>In this video clip, Museum of Science educator Megan Litwhiler discusses how computer scientists are using an artificial neural network called AlphaFold to learn more about the structure of the virus that causes COVID-19.
+
</b><br>In this video clip, Museum of Science educator Megan Litwhiler discusses how computer scientists are using an artificial [[Neural Network]] called AlphaFold to learn more about the structure of the virus that causes COVID-19.
 
This program was supported by the MIT Center for Brains, Minds and Machines NSF award
 
This program was supported by the MIT Center for Brains, Minds and Machines NSF award
 
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<youtube>6l3RxlwEVlE</youtube>
 
<youtube>6l3RxlwEVlE</youtube>
 
<b>Knowledge Graphs for Drug Repurposing  
 
<b>Knowledge Graphs for Drug Repurposing  
−
</b><br>Vassilis Ioannidis presents his team's work at AWS on open-sourcing a biological knowledge graph to fight COVID-19.  The problem of drug repurposing is discussed in the context of knowledge graph representation learning.   
+
</b><br>Vassilis Ioannidis presents his team's work at AWS on open-sourcing a biological knowledge graph to fight COVID-19.  The problem of drug repurposing is discussed in the [[context]] of knowledge graph representation learning.   
 
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<youtube>oKcsMT_A5Q0</youtube>
 
<youtube>oKcsMT_A5Q0</youtube>
 
<b>Graph Technologies - More than just Social (Distancing) Networks
 
<b>Graph Technologies - More than just Social (Distancing) Networks
−
</b><br>Graphs have become a hot topic in the data analytics area, but what can they do for organizations? Graphs excel at analyzing latent relationships in large networks of data – so they’re great for fraud analytics, manufacturing dependency analysis, customer 360 analysis – use cases that relational models struggle with. Oracle provides robust and scalable graph data management, query, and analytics – for free in Oracle Database. Hans Viehmann, Product Manager EMEA, Oracle @SpatialHannes and Gianni Ceresa, Managing Director at DATAlysis, Oracle ACE Director @G_Ceresa will introduce you to what graphs are all about, what problems they solve, and how you can get started using them right in Oracle Database.
+
</b><br>Graphs have become a hot topic in the data analytics area, but what can they do for organizations? Graphs excel at analyzing [[latent]] relationships in large networks of data – so they’re great for fraud analytics, manufacturing dependency analysis, customer 360 analysis – use cases that relational models struggle with. Oracle provides robust and scalable graph data management, query, and analytics – for free in Oracle [[Database]]. Hans Viehmann, Product Manager EMEA, Oracle @SpatialHannes and Gianni Ceresa, Managing Director at DATAlysis, Oracle ACE Director @G_Ceresa will introduce you to what graphs are all about, what problems they solve, and how you can get started using them right in Oracle [[Database]].
 
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<youtube>pvGf_SqOKx8</youtube>
 
<youtube>pvGf_SqOKx8</youtube>
 
<b>Asset Tracking Solutions for COVID-19
 
<b>Asset Tracking Solutions for COVID-19
−
</b><br>In the COVID-19 context, government authorities and commercial companies have been looking at recent technologies such as IoT to find all sorts of solutions to respond to the crisis. Social distancing, people tracking and asset monitoring have become crucial aspects of keeping the situation under control. In this webinar, LoRa Alliance® members will be addressing the following challenges with their LoRaWAN® solutions that currently exist in the market:
+
</b><br>In the COVID-19 [[context]], government authorities and commercial companies have been looking at recent technologies such as IoT to find all sorts of solutions to respond to the crisis. Social distancing, people tracking and asset monitoring have become crucial aspects of keeping the situation under control. In this webinar, LoRa Alliance® members will be addressing the following challenges with their LoRaWAN® solutions that currently exist in the market:
  
 
• How to facilitate social distancing for workers while respecting [[privacy]] regulations?
 
• How to facilitate social distancing for workers while respecting [[privacy]] regulations?

Latest revision as of 08:36, 7 January 2026

Youtube search... ... Quora search ...Google search ...Google News ...Bing News


Machine Learning Projects Against COVID-19
IBM Research is proud to host professor Yoshua Bengio — one of the world’s leading experts in AI — in a discussion of how AI can contribute to the fight against COVID-19. Professor at the Université de Montréal since 1993, Bengio is also the founder and scientific director of Mila–Quebec Artificial Intelligence Institute, the world’s largest university-based research group in deep learning. In this video, he describes two of many projects started at Mila to to contribute to the fight against COVID-19. The first involves searching for antiviral drugs and the second is about predicting contagiousness risk based on data acquired on phones.

How is AI helping to fight the coronavirus COVID-19
In this special video, I give an overview of the possible areas that AI helps us fight the coronavirus and then deep dive a little bit into how data is used with machine learning in that fight. Of course, there are many areas where AI is helping. Also, just AI is not a silver bullet. We need people, experts, processes, tools, governments, health organizations, and many entities to come together in a systematic way to defeat the virus. Here's what I can do to help you. I speak on the topics of architecture and AI, help you integrate AI into your organization, educate your team on what AI can or cannot do, and make things simple enough that you can take action from your new knowledge.

Collective and Augmented Intelligence Against COVID-19 (CAIAC) Launch
A virtual event hosted by the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and the AI Initiative at The Future Society to officially announce a global alliance on the COVID-19 pandemic response. The alliance will provide an information service not yet available that is vitally important to facing and mitigating the crisis. In parallel with the UN High Level Political Forum, the launch agenda will include details on the partnership and speakers from the private sector, academia, government, and multilateral institutions, including UNESCO, the World Bank, the WHO and UN Global Pulse, offering unique perspectives on the roadblocks and opportunities to addressing the COVID-19 pandemic. Topics covered will include challenges with disparate data and determining meaningful information in the fight against the virus, as well as the importance of building multi-stakeholder collaborations. Fei-Fei Li

AI and Data Science against COVID-19: part 1
Starting on 11 May 2020, The Finnish Center for Artificial Intelligence FCAI organises a webinar series together with Helsinki Centre for Data Science HiDATA. The webinar series sheds light on how artificial intelligence-based systems and data science could be of help while fighting against COVID-19. Come and listen to the top researchers at University of Helsinki and Aalto University and other related talks in the field of artificial intelligence and data science. The sessions are chaired by FCAI and HiDATA leading professors.

Covid 19 and Digital Health: Challenges and Opportunities
Hamad bin Khalifa University

Intelligent Detection & Artificial Intelligence Solution for Covid-19
Premiered Jul 1, 2020

Robotics and AI for COVID Resilience
Neil Jacobstein, mediaX Distinguished Visiting Scholar and chair of the Artificial Intelligence and Robotics Track at Singularity University hosted the third webinar in the mediaX series “Thinking Tools for Wicked Problems”. Neil’s webinar covers some of the current uses of AI in addressing COVID-19, focusing on large scale collaborations and many team efforts to develop drugs and vaccines. Included in this are these three takeaways. 1. AI and robotics are already delivering significant value in combating pandemic disease. 2. International collaboration on machine learning datasets and open source robotic designs are accelerating progress. 3. AI and robotics can decrease cost, increase effectiveness, accelerate solutions, and save lives in the current COVID-19 pandemic, and the public health crises to come.

Webinar: Leveraging Artificial Intelligence in a COVID-19 Environment
Get the latest insights on the use of artificial intelligence and machine learning in the fight against COVID-19 through this informative Applied Radiology webinar. You'll hear from industry experts on what role these technologies play in this new era. This program is brought to you through a cooperative effort between New York University School of Professional Studies and the American Board of Artificial Intelligence in Medicine.

MUSC AI effort to address COVID-19
Matthew Turner, Mathew Davis, M.D., Stephane Meystre, M.D., Les Lenert, M.D., Jihad Obeid, M.D. Experts from MUSC share how they leveraged artificial intelligence in response to COVID-19

Stanford HAI - COVID-19 and AI: A Virtual Conference - Session One
Sponsored by the Stanford Institute for Human-Centered Artificial Intelligence (HAI), COVID-19 and AI: A Virtual Conference convened experts from Stanford and beyond to advance the understanding of the virus and its impact on society. The speakers and topics engaged the broad research community, government and international organizations and civil society, uniting a global community toward solutions to benefit all of humanity. Fei-Fei Li


Research

Analyzing COVID-19: Can the Data Community Help?
Online Tech Talk hosted by Denny Lee, Developer Advocate @ Databricks My name is Denny Lee and I’m a Developer Advocate at Databricks. But before this, I was a biostatistician working on HIV/AIDS research at the Fred Hutchinson Cancer Research Center and University of Washington Virology Lab in the Seattle-area. Watching my friends and colleagues working the front lines of this current pandemic has inspired me to see if we - as the data scientist community - can potentially help with “flattening the curve”. But before we dive into data science, remember - the most important thing you can do is wash your hands and social distancing! With the current concerns over SARS-Cov-2 and COVID-19, there are now available various COVID-19 datasets on Kaggle and GitHub as well as competitions such as the COVID-19 Open Research Dataset Challenge (CORD-19). Whether you are a student or a professional data scientist, we thought we could help out by providing a primer session with notebooks on how to start analyzing these datasets. For this primer session we will review (and shortly publish thereafter) iPython notebooks working with Apache Spark and/or Pandas (or both) for the following datas sets.

CORD-19 Search: Using Machine Learning to Explore COVID-19 Scientific Literature | AWS Public Sector
Healthcare providers and researchers face an exponentially increasing volume of information about COVID-19, which makes it difficult to derive trends that can inform treatment. In response, Amazon Web Services (AWS) launched CORD-19 Search, a search website powered by machine learning, to help researchers quickly search for research papers and documents to answer questions like “When is the salivary viral load highest for COVID-19?”

COVID-19 Epidemic Mitigation via Scientific Machine Learning (SciML)
Chris Rackauckas Applied Mathematics Instructor, MIT Senior Research Analyst, University of Maryland, Baltimore School of Pharmacy This was a seminar talk given to the COVID modeling journal club on scientific machine learning for epidemic modeling

Data Analytics Tools for COVID-19 Applications
David Yang - Hamad bin Khalifa University


Research Tools

Research Datasets

Using natural language processing, AI could generate valuable new insights from the published research.

Cleaning and exploring the COVID-19 Open Research Dataset (CORD-19)
I show how to open and explore the CORD-19 dataset of scientific publications related to COVID-19 (coronavirus). This includes parsing json files with jsonlite, rectangling the data with tidyr's hoist and unnest_wider, and doing named entity recognition by combining tidytext with the spacyr package and scispacy models. The CORD-19 dataset was released by a collaboration of government and research organizations, and is hosted by Kaggle

Data and AI For COVID 19(05/09/2020)
As the COVID-19 pandemic sweeps the globe, big data and AI have emerged as crucial tools for everything from diagnosis and epidemiology to therapeutic and vaccine development. Here, we collect and review the latest development in how big data is fighting back against COVID-19. Andrew is a senior data science engineer with IBM. Andrew is a data science and machine learning advocate. His current interests are computer vision, Natural Language Processing (NLP), and scaling machine learning in a hybrid multi-cloud enterprise environment. Before joining IBM, Andrew was an enterprise architect with Novartis Pharmaceuticals. Previously he was a senior tech lead managing large scale news media Internet operations in New York.

Which help to uncover potential patterns across research papers...

COVID-19 Knowledge Graph

Graph Gurus 37: Combining Natural Language Processing with a Graph Database for COVID-19 Dataset
Learn how to process text and extract entities (words and phrases) as well as classes linking the entities using SciSpacy, a Natural Language Processing (NLP) tool. Import the output of NLP and semantically link it in TigerGraph Run advanced analytics queries with TigerGraph to analyze the relationships and deliver insights

The Covid Graph - Neo4j Online MeetUp
Martin Preusse (Kaiser & Preusse) provides an overview of the Covid Graph Knowledge Graph, linking many different data sources, such as genome information and research papers together to aid rapid research on COVID-19. https://covidgraph.org

NLP-Powered Epidemiological Investigation

When the Coronavirus outbreak hit China, Alibaba’s DAMO Academy developed the StructBERT NLP model. Being deployed in Alibaba’s ecosystem, the model powered not only the search engine on Alibaba’s retail platforms but also anonymous healthcare data analysis. By analyzing the text of medical records and epidemiological investigation, the Centers for Disease Control (CDCs) used StructBERT for fighting against COVID-19 in China cities. Being based on the BERT pre-trained model, StructBert not only understands the context of words in search queries but also leverages the structural information: sentence-level ordering and word-level ordering.

Kaggle

The primary goal of Kaggle’s COVID-19 effort is to find factors that impact the transmission of COVID-19 (particularly those that map to the NASEM/WHO open scientific questions). You've already shown great results in producing meaningful insights to help address the pandemic! - Kaggle Team

  • COVID-19 Dataset Challenge: Kagglers will need to find, curate, share -- and join -- useful public datasets. You can review the relevant threads for sharing datasets and discussing dataset ideas to get an idea of the types of things that Kagglers find most useful. For this challenge we are only considering public datasets on Kaggle.

Acknowledgments

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Coronavirus Competition Results (Remdesivir)
I’m pleased to announce the results of our open-source Coronavirus Drug Discovery Competition! In just 2 weeks, hundreds of developers from around the world signed up to join the fight against the novel coronavirus, using publicly available datasets and algorithms to come up with relevant solutions. The top 3 submissions, winning $3500 in prizes, stood out from the rest in terms of their algorithmic and reporting quality.

Coronavirus Deep Learning Competition
The goal is to use deep learning to find a potential cure or treatment, then we'll send samples of the compound to the Wuhan Institute of Virology for further analysis. This is the perfect opportunity to show the world how open-source, community-driven AI can effect positive, relevant change. This is the AI-Human collaborative "Deep Blue" moment, a moment where, given AI tools, a human or group of humans will be able to accomplish an extraordinary feat that they couldn't otherwise.

COVID-19 Data Analysis and Prediction: Part-1: Data Loading from Kaggle
COVID-19 cases (novel corona virus infections) Data Analysis on Kaggle Data. The code for the video is available: https://github.com/theclassofai/COVID_19

Dataset Exploration - CORD-19 - COVID-19 Open Research Dataset Challenge - Kaggle
An overview of the CORD-19 challenge that aims at combating the Coronavirus (Covid-19) by building an AI-powered Literature Review to extract useful information from thousands of research papers made available by Kaggle.

Virus Management & Operations

Virus Testing

Decisions on where to place pop-up COVID-19 testing sites are data-driven
Local health experts are using strategy, skill and data to determine the best places to reach the most people at COVID-19 testing sites during this recent spike in cases.

ESDS AA+ COVID-19 Testing Solution- AI-Enabled Tool That Indicates COVID-19 in JUST 5 Minutes
Amidst the global rise of #COVID19 pandemic, Government and other healthcare organizations from all over the world traditionally take 24-48 hours to determine whether a person is suffering from COVID-19 or not. #ESDS Software Solution Pvt. Ltd, an advanced technologies solutions provider in India, has developed an AI-enabled tool that can indicate COVID-19 in under 5 minutes by following a simple 3-step procedure from Chest X-ray.

Virus Detection


Can deep learning AI help with detecting COVID-19/coronavirus?
Join us live where we will have a live paper discussion session on the recent paper on using deep learning to detect COVID-19 from CT lung scan. The Lancet: Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. JAMA: Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China. Springer: 2019 Novel coronavirus: where we are and what we know. RSNA: Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. MedRXIV: Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study. Discussion leads: Xiyang Chen (CTO of Aggregate Intellect), Shazia Akbar (ML Engineer at Altis Labs), Isha Berry (PhD Candidate at University of Toronto)

Can machine learning help predict severe cases of Covid-19?
In this edition, we tell you how artificial intelligence is assisting scientists not only in developing new drug molecules, but also how it's helping predict the most severe cases of Covid-19. This as it can quickly comb through huge amounts of scientific and medical data looking for connections.

Detecting COVID-19 from X-Ray | Training a Convolutional Neural Network | Deep Learning
In this webinar, we will discuss how you can make your own machine learning to successfully detect COVID-19 from Chest X-Rays by building a Simple Convolution Neural Network. - Dataset Preparation - Understanding the Dataset - Building a CNN - Model Training

Detecting COVID - 19 cases with Robotic Process Automation (RPA), #AI and Machine Learning - UiPath
Based on UiPath AI Fabric and with a touch of MachineLearning, Radu Pruna from our Immersion Lab built a model for detecting COVID-19 cases from X-ray chest images in seconds. The model is described in this paper - https://bit.ly/3awDEym.

LUNG DISEASE CLASSIFICATION AND QUANTIFICATION WITH EXPLAINABLE AI
The world is suffering from the COVID-19 pandemic outbreak. The only way to control the situation is to increase the testing and finding COVID traces. But the problem is the cost of testing which is a big burden on the economy. To overcome this problem, a more widespread solution is through analyzing Chest X-Ray Images for finding traces of COVID-19.

ACG: COVID-19 AI Screening Solutions
ACG: COVID-19 AI Screening Solutions - Protecting Those at Risk During the Pandemic. Recording from August 12, 2020


How is Coronavirus Diagnosed?


COVID-19 | Coronavirus: How is Coronavirus Diagnosed
Join us for our lecture on COVID-19 where Ninja Nerd Science will go into detail on the diagnostics used to diagnose COVID-19. This is our April update on our previous lecture to keep all of our viewers informed on the new research and publications that have been released on COVID-19. Please be aware— This lecture is up to date as of April 17, 2020. Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19. COVID-19 is the infectious disease caused by the most recently discovered coronavirus. This new virus and disease were unknown before the outbreak began in Wuhan, China, in December 2019. The most common symptoms of COVID-19 are fever, tiredness, and dry cough. Some patients may have aches and pains, nasal congestion, runny nose, sore throat or diarrhea. These symptoms are usually mild and begin gradually. Some people become infected but don’t develop any symptoms and don't feel unwell. Most people (about 80%) recover from the disease without needing special treatment. Around 1 out of every 6 people who gets COVID-19 becomes seriously ill and develops difficulty breathing. Older people, and those with underlying medical problems like high blood pressure, heart problems or diabetes, are more likely to develop serious illness. People with fever, cough and difficulty breathing should seek medical attention.

Contact Tracing

Virtual Hearing - Exposure Notification and Contact Tracing: How AI Helps
On Wednesday, July 8, 2020, from 12:00 p.m. (ET) Task Force on Artificial Intelligence Chairman Foster and Ranking Member Loudermilk will host a virtual hearing entitled, “Exposure Notification and Contact Tracing: How AI Helps Localities Reopen Safely and Researchers Find a Cure." Witnesses for this one-panel hearing will be: • Brian McClendon, CEO, Co-founder, CVKey Project • Krutika Kuppalli, M.D., Infectious Diseases Physician • Andre M. Perry, Fellow, Metropolitan Policy Program, Brookings Institute • Ramesh Raskar, Professor, MIT and Founder, PathCheck Foundation The novel coronavirus 2019 (“COVID-19”) pandemic has had a significant public health and economic impact on the United States, including on the financial services sector. As states halt or reverse phased reopening’s because of recent increases in COVID-19 infections, the ability to trace and contain the virus continues to remain a top priority for all aspects of society. Contact tracing and exposure notification have the potential to help isolate coronavirus cases and keep workers, including at financial institutions, safe. Artificial intelligence (“AI”) has been instrumental in helping experts analyze the influx of new research and data related to how COVID-19 continues to evolve. However, some experts have raised concerns about using AI to analyze consumer and financial data related to COVID-19 because doing so may violate consumer privacy laws.

COVID-19 Contact Tracing with Enigma
Launch event for Enigma's SafeTrace, Privacy-Preserving Contact Tracing for COVID-19, plus a demo of APEX, Outlier Ventures' AI-powered analytics platform built on Enigma. Join us for a live demo of privacy-preserving analytics and machine learning for COVID-19 data, as well as a discussion between Outlier Ventures and Enigma on the future of private compute in epidemiology.

Contact Tracing Technology - Computerphile
As we contemplate life after lock-down, what technology could help the health services to work out how viruses can spread? Dr Mike Pound & Dr Steve Bagley chat to Sean. This video was filmed by Mike Pound, Steve Bagley & Sean Riley and edited by Sean Riley. Computer Science at the University of Nottingham: https://bit.ly/nottscomputer

TraceSigma - An open-source contact-tracing device - Hackware v6.1
Speaker: James Yong

A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment
Motivated by the current COVID-19 outbreak, we introduce a novel epidemic model based on marked temporal point processes that is specifically designed to make fine-grained spatiotemporal predictions about the course of the disease in a population. Our model can make use and benefit from data gathered by a variety of contact tracing technologies and it can quantify the effects that different testing and tracing strategies, social distancing measures, and business restrictions may have on the course of the disease. Building on our model, we use Bayesian optimization to estimate the risk of exposure of each individual at the sites they visit and the difference in transmission rate between asymptomatic and symptomatic individuals from historical longitudinal testing data. Experiments using real COVID-19 data and mobility patterns from several towns and regions in Germany and Switzerland demonstrate that our model can be used to quantify the effects of tracing, testing, and containment strategies at an unprecedented spatiotemporal resolution. To facilitate research and informed policy-making, particularly in the context of the current COVID-19 outbreak, we are releasing an open-source implementation of our framework at https://github.com/covid19-model. Manuel Gomez Rodriguez is a tenure-track faculty at Max Planck Institute for Software Systems. Manuel develops human-centered machine learning models and algorithms for the analysis, modeling and control of social, information and networked systems.

Digital Contact Tracing for COVID19
understand various technology solutions that are currently available in the market to implement contact tracing, assess employee risk exposure, and document digital trail for future reference. And, learn about the need for a comprehensive digital contact tracing framework that helps you automate your pandemic response by leveraging data from existing enterprise systems and public data sources. By listening to this webinar, you can find: How to digitize and automate your pandemic response The technology behind digital contact tracing at the workplace The importance of digital screening to assess employee risk To know more, write to us at connect@imaginea.com or visit our website: https://www.imaginea.com/

Tracking

COVID-19 Dashboard Visualizations
Brian Wood takes us through his development work on the COVID-19 Dashboard powered by the Wolfram Cloud. You can access the dashboard yourself here: https://wolfr.am/COVID19Dashboard

Complete Latest Covid-19 Data Analysis Visualization in 4 Hours
May 29, 2020

Visualizing Coronavirus spread using Animated Charts -Part 2
In this video, we will continue with our data science portfolio building. We will be moving into animated custom charts and Dashboard creation using multiple datasets, from social media, john Hopkins repo and news crawling.

Analyze and Visualize the Impact of COVID-19 Pandemic
In this video, the ArcGIS Insights team provides: • Introduction to ArcGIS Insights • Live examples showing the analytics tools to gauge the impact of COVID-19 • Analytic models that help you reuse workflows and improve collaboration • Scripting to connect to any dataset and analyze it with open Python or R libraries • Ready-to-use models, workbooks, trusted data, and tutorials to jumpstart your analysis

ArcGIS Insights fuses traditional data analytics with location analytics, providing you with both capabilities in one place. Perform exploratory and advanced analytics including spatial, predictive, statistical, and link analysis on your data. Share results in the form of interactive maps, charts, and reports that speak to your audience.

Dynamic Mapping of the Progression of COVID-19 using Python Programming
In this tutorial, you will learn how to create a dynamic map using time series data of Coronavirus infections around the world using GeoPandas and Pandas Python libraries. The time series data are acquired from the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE.

COVID-19 Visualizer: Postman live stream on Twitch
Postman COVID-19 API Resource Center, Importing CovidAPI Building the Visualization Running Visualizer Updating the data / Converting object to array Debugging Running updated Visualizer Changing the background color Creating a Fork Adding a variable (Country) Publish Collection Arlemi and Joyce graph time series data using the Postman visualizer.

Reading COVID-19 graphics

How coronavirus charts can mislead us
How to read a popular chart of coronavirus cases by country. Much of the data about the coronavirus epidemic and covid-19 is flawed. It is collected and reported in different ways by different countries, and almost certainly undercounts the number of cases and deaths. But organizations and journalists still need to report the available data to inform the public and help guide policymakers. Much of that data ends up in visualizations, like charts and maps, which can make it easier to understand and analyze. But it's important to know how the process of data visualization can shape our perception of the crisis. In this video, we deconstruct one particularly popular chart of covid-19 cases around the world which uses a logarithmic scale, and explain how to avoid being misled by it.

Data viz experts explain COVID-19 graphs | Things to Know
We’re confronted daily with staggering new data from this unprecedented pandemic. The data, presented in charts, graphs, maps, and animations, can be overwhelming and also hard to grasp. We asked two data visualization researchers for their advice on reading a few of the most common COVID-19 charts. In the video they share what these graphs can and cannot tell us about the pandemic.

Simulations

COVID-19 Simulation Summit
An Online Meeting of the Minds Among Top Global Scientists!

The COVID-19 Simulation Summit is an online event focused on the use of agent-based simulation models for more effective simulation of COVID-19 spread and evaluation of COVID-19 policies. The event will consist of live video talks, Q&A sessions, and panel discussions. The event will gather together scientists with insight and experience in simulation modelling of complex systems (especially but not only agent-based modelling) and complex systems dynamics; along with scientists and physicians with specific insight into COVID-19 and related epidemiological issues. 10:30 - Dr. Ben Goertzel - Opening & Introductory Keynote - 11:15 - Dr. Yaneer Bar-Yam - The Coronavirus and Modeling of its Pandemic 12:00 - Dr. Robin Hanson - Variolation and Vouching as Alternate Pandemic Policies 12:45 - Break 13:00 - Dr.Petronio Candido - agent-Based Simulation of COVID-19 Health and Economical Effects 13:45 - Dr. Eva Lee - Modeling and Evaluating Intervention Options and Strategies for COVID-19 Containment: A Biological-Behavioral-Logistics Computation Decision Framework 14:45 - break 15:00 - Roger Ng, MD - Ray NG, MD - COVID-19: A Front-Line Physician’s Perspective 15:45 - Dr. Deborah Duong - Modeling COVID-19 Using Simulated Agents with Intelligence and Culture 16:30 - Break 16:45 - Vinay Gupta, Dr. Anish Mohammad, Dr. Mircea Davidescu, Dr.Nabarun Dasgupta - Panel: Simulating the Pandemic: Perspectives on COVID-19 Modeling. Moderate by Gina Smith 17:45 - Break 17:50 - Dr. Ben Goertzel - Agent-Based Modeling of COVID-19 -- Next Steps and Broader Implications

Simulating an epidemic
Experiments with toy SIR models Home page: https://www.3blue1brown.com Brought to you by you: https://3b1b.co/sir-thanks

Outbreak Prediction

Epidemic, Endemic, and Eradication Simulations
Thanks to Dr Rohin Francis of Medlife Crisis and Dr Rishi Desai of Osmosis for their feedback. Interactive COVID-19 simulations from Nicky Case and epidemiologist Marcel Salathé: https://ncase.me/covid-19 More on logistic growth - 3Blue1Brown, also regarding disease spread: https://youtu.be/Kas0tIxDvrg - Primer, regarding carrying capacity: https://youtu.be/uRTtlpD_U54

Using Machine Learning to Optimize COVID-19 Predictions
With the current COVID-19 pandemic impacting many aspects of our lives, understanding the data and models around COVID-19 data are ever more crucial. Understanding the potential number of cases impacts the guidance around our policies (needing more hospital ICU beds, when to ease stay at home orders, when to open schools, etc.). In this session, we will focus on some exploratory data analysis to understand the accuracy of these models. We will then use machine learning models to improve them.

Data Modelling and Analysis of COVID-19 Spread using Python Code: Session by a Data Scientist
Currently, there are so many dashboards and statistics around the Coronavirus spread available all over the internet. With so much information and expert opinions, to see different nations adopting different strategies, from complete lockdown to social distancing to herd immunity, one is left thinking as to what the right strategy is for them. Is there any basis to these opinions and advice? This session is an attempt of data modelling and analysing Coronavirus (COVID-19) spread with the help of data science and data analytics in python code. This analysis will help us to find the basis behind common notions about the virus spread from purely a dataset perspective. So, let’s flex some data science muscles and jump right into it.

Covid 19 Global forecasting prediction using Machine Learning Kaggle Kernel
Covid 19 Global forecasting prediction using Machine Learning Kaggle Kernel Kaggle Covid 19: https://www.kaggle.com/covid19 COVID19 Global Forecasting (Week 3): https://bit.ly/2V8SKEw COVID19 Global Forecasting (Week 2): https://bit.ly/2XaeLp4

Covid19 Machine Learning Prediction and Forecasting | Time Series Analysis | Codegnan
In this video you'll learn about Covid19 Machine Learning Prediction and Forecasting with Time Series Analysis with available Covid19 Data Set. You'll also learn Data Science Journey. What is Machine Learning and How to Predict and Forecast Data using Machine learning

Fighting COVID19 with Machine Learning | COVID19 Outbreak Prediction | Intellipaat
Know what is corona, what is machine learning,how machine learning technology can be used to fight corona, corona virus predictions and lot more.

Coronavirus Outbreak Prediction Using Machine Learning | April Update | Simplilearn
The outbreak of Coronavirus has taken the world by storm. It has caused a lot of hardships for people around the globe. This video focuses on the emergence of Coronavirus (Covid-19) and the impact it has created worldwide. You will understand how Coronavirus cases have grown so far, the deaths reported, and the recoveries made. You will look at an analysis using machine learning in Python to predict the number of upcoming cases for the next 20 days. Finally, we'll tell you the safety measure you can take to secure yourself for getting attacked by Coronavirus.

COVID - 19 Outbreak Prediction using Machine Learning | Machine Learning Training | Edureka
This Edureka Session explores and analyses the spread and impact of the novel coronavirus pandemic which has taken the world by storm with its rapid growth. In this session, we shall develop a machine learning model in Python to analyze what has been its impact so far and analyze the outbreak of COVID 19 across various regions, visualize them using charts and tables, and predict the number of upcoming confirmed cases. Finally, we’ll conclude with a few safety measures that you can take to save yourself and your loved ones from getting adversely affected in the hour of crisis.

Vaccines and the Immune Response

Vaccines are among the most powerful weapons we have for preventing infectious disease. In the 1950s, hundreds of thousands of Americans were infected by measles every year. But by 2015, after decades of vaccination, a mere 191 cases were reported. Unfortunately, most vaccines take years to develop, and in the midst of a pandemic, society can’t wait. One promising approach to accelerate this process is to use machine learning, a form of artificial intelligence, to guide vaccine design. What does it mean to design a vaccine? Vaccines work by exposing you to parts of a pathogen with the aim that your immune system will more easily recognize it in the future, mounting a quicker and more robust response. The oldest forms of vaccines were composed of dead viruses that are relatively safe but sometimes ineffective or live, weakened viruses that pose greater safety risks. More recent vaccines tend to contain specific components of a virus (such as the surface protein for hepatitis B vaccines) that are judged to be safe and effective. Future vaccines might even include specific viral protein fragments. Regardless of the way in which a vaccine is composed, the design goal is always to include viral components that are highly immunogenic: visible to your immune system and eliciting an immune response. Can artificial intelligence help us design vaccines? | Ethan Fast and Binbin Chen - Brookings Institution

COVID-19: A chat with Bob Langer on vaccines, nanotech & the future of healthcare
MIT Institute Professor Robert Langer discusses COVID-19 research taking place in his lab, and how advances in nanotechnology and healthcare could enable humanity to address the current pandemic. Science is our best shot at a solution to the ongoing COVID-19 pandemic. Much needed vaccines, novel diagnostic approaches and new therapies all would not be possible without research and scientific innovation. Cue Prof Langer, a renowned chemical engineer, scientist, serial entrepreneur and biomedical inventor. Known for his contributions to cancer treatment, drug delivery systems and regenerated organs, Prof Langer’s innovations have saved countless lives. Today, he runs the largest biomedical engineering lab in the world. Named by Forbes as one of the 25 most important people in biotechnology in the world, Prof. Langer is the academic co-founder of US biotech Moderna, which is leading the effort to find a COVID-19 vaccine and has a candidate in Phase I clinical trials.

How soon can we get a COVID-19 vaccine? AI helps
Will we achieve this breakthrough speed to get one? AI plays a key role. Vaccine R&D has three points: massive data analysis, literature screening and knowledge mapping. That's exactly the strength of artificial intelligence. CGTN reporter Zhou Yiqiu shares more.

How Microsoft Is Using AI to Find Covid-19 Antibodies, Says CTO
Apr.06 -- Kevin Scott, Microsoft chief technology officer, discusses how Microsoft is helping with internet access and in the healthcare arena during the COVID-19 crisis. He speaks with Emily Chang on "Bloomberg Technology."

FIGHTING CORONAVIRUS : with Artificial Intelligence and Data Science
With the onset of the new Coronavirus cases, scientists and researchers are doing all that they can to prevent it and quite possibly come up with a cure. While quite unconventional, many have turned to technology like A.I., Machine Learning & Data Science and their efforts have not been in vain. Technology has always made life easier and now with the ability to predict the spread of diseases and develop new cures, it’s making life safer. In this video, we talk about the Coronavirus disease, how technology like Artificial Intelligence is being used to battle this pandemic and some facts and figures to help you stay informed.

Leveraging big data for intelligent vaccine design | Matthew Mckay
It has so far proved too difficult to develop vaccines for some diseases, such as HIV and Hepatitis C – but that may change. Matthew Mckay explains how his work at Hong Kong University of Science and Technology is using data analytics and machine learning to identify potential vulnerabilities in these viruses.

This AI Created A Flu Vaccine
Need to get your flu shot? If you're in the US, the CDC can help you find the closest place.

FCAI Simulator-based inference: AI-assisted vaccine development
Jukka Corander: FCAI Simulator-based inference: AI-assisted vaccine development Machine Learning Coffee Seminar, 7th October 2019.

The quest for the coronavirus vaccine | Seth Berkley
When will the coronavirus vaccine be ready? Epidemiologist Seth Berkley (head of Gavi, the Vaccine Alliance) takes us inside the effort to create a vaccine for the coronavirus. With clarity and urgency, he explains what makes it so challenging to develop, when we can expect it to be rolled out at scale and why we'll need global collaboration to get it done. (This virtual conversation is part of the TED Connects series, hosted by head of TED Chris Anderson and current affairs curator Whitney Pennington Rodgers. Recorded March 26, 2020)

Coronavirus: Searching for a COVID-19 cure - with the help of AI | Coronavirus vaccine
Scientists are intensively researching for a cure for COVID-19 while the coronavirus keeps the world in suspense. Perhaps AI can help in the search for a vaccine for COVID-19. Scientists all over the world are using AI in their research on the coronavirus. What do you think? Can AI help in the search for a cure for COVID-19?

How AI is helping find a vaccine for COVID-19
An AI expert discusses how close pharmaceutical companies are getting to finding a coronavirus vaccine or treatment and why the use of the technology is helping.

Unlocking the Pathogen Puzzle

COVID-19: Could AI and supercomputers unlock the pathogen puzzle?
Futuris looks at how Artificial Intelligence and High Performance Computing are helping in the fight against COVID-19.

Using Artificial Intelligence to Unlock the structure of SARS-COV-2
In this video clip, Museum of Science educator Megan Litwhiler discusses how computer scientists are using an artificial Neural Network called AlphaFold to learn more about the structure of the virus that causes COVID-19. This program was supported by the MIT Center for Brains, Minds and Machines NSF award

Mutations

How Viruses Like The Coronavirus Mutate
Science Insider Genetic mutations aren’t as scary as they sound. With RNA viruses, like the coronavirus (SARS-CoV-2) that causes COVID-19, they’re happening constantly — basically every time it replicates. But not all mutations stick, and not all the ones that stick are bad. In fact, mutations are actually necessary for tracking and containing COVID-19. Here’s how viruses mutate and why you shouldn’t be worried when you hear about them.

How Yale Genomic Epidemiologists Use Mutations to Track the COVID-19 Pandemic
Learn more about the Yale School of Medicine's response to COVID-19, visit: https://covid.yale.edu. Dr. Nathan Grubaugh is an assistant professor of epidemiology at the Yale School of Public Health and uses genomic epidemiology to study viral outbreaks. His background has led him to studying the mutations in COVID-19 to track the spread of the virus. Faculty across Yale, including at the School of Medicine, School of Nursing, School of Public Health, School of Engineering & Applied Science and Faculty of Arts and Sciences are actively engaged in research, innovation, and clinical efforts to combat COVID-19. Attribution: https://www.videoblocks.com/ https://grubaughlab.com/ https://nextstrain.org/ https://nanoporetech.com/

Knowledge Graphs for Drug Repurposing

Knowledge Graphs for Drug Repurposing
Vassilis Ioannidis presents his team's work at AWS on open-sourcing a biological knowledge graph to fight COVID-19. The problem of drug repurposing is discussed in the context of knowledge graph representation learning.

Drug Discovery Knowledge Graphs - Introduction to Drug Discovery (1/7)
Combinatorial chemistry has produced a huge amount of chemical libraries and data banks which include prospective drugs. Despite all of this progress, the fundamental problem still remains: how do we take advantage of this data to identify the prospective nature of a compound as a vital drug? Traditional methodologies fail to provide a solution to this. Grakn, however, provides the framework which can make drug discovery much more efficient, effective and approachable. This radical advancement in technology can model biological knowledge complexity as it is found at its core. With concepts such as hyper relationships, type hierarchies, automated reasoning and analytics we can finally model, represent, and query biological knowledge at an unprecedented scale.

Drug Discovery

drug_discovery_and_development_process_Slide01.jpg

Cracking COVID-19: How Cyclica is speeding up drug discovery | MaRS Discovery District
Doctors and scientists everywhere are scrambling to produce a coronavirus vaccine, though, many experts here at home question whether that is the right strategy. Startup Cyclica wants to expedite the process, using its AI platform to identify drugs, already functional and approved by the FDA, to unlock proteins that could be effective against COVID-19. The company is working in partnership with renowned Chinese institute Materia Medica on the initiative, bringing some of the most respected international medical minds together under one (virtual) roof. ABOUT MaRS DISCOVERY DISTRICT MaRS is the world's largest innovation hub located in Toronto. We support impact-driven startups in health, cleantech, fintech and enterprise.

COVID Conversations: Nicole Zitzmann on Drug discovery
Professor of Virology and Director of the Glycobiology Institute, Nicole Zitzmann, talks about how her team are working with other groups across the globe to apply chemical principles and techniques to address the important biological questions around COVID-19, and what they’ve already learnt through the development and testing of existing drugs.

Fighting the Virus

Immunology | Antibody Structure & Function
NinjaNerdScience@gmail.com

Immunology | T- Cell Development
Join us in this video where we discuss the thymus gland and T-cell development. We go into detail

Immunology | Adaptive Immunity
Join us in this video where we discuss adaptive immunity. These will include humoral and cell

Vaccines and the Immune Response: How Vaccines Work
This animation provides an overview of vaccines and the immune response, and how influenza vaccines work. Influenza vaccines are able to trigger an immune response by mimicking viral infection. They are usually manufactured using inactivated or killed virus particles taken from various circulating influenza strains.

Society Impacts

Social Distancing

Deep Learning and Video AI for Social Distancing
In this recording, we share SpringML Machine Learning frameworks that allow for rapid deployment of social distancing compliance solutions leveraging Google Cloud Vision AI. Our frameworks allow for rapid detection from any video feed when people are not wearing personal protective equipment (PPE) or complying with social distancing guidelines.

COVID-19 Deep Learning Social Distancing - Explained
In this presentation we explain how deep learning can be applied to social distancing in a regulated post-pandemic period. We will cover challenges business may face to reopen, and use cases and deployment of deep learning models for these challenges. We will then do a technical dive under the hood on how to design social distancing models, using pre-trained components and DIY for those wanting to build from the bottom up.

Track Social Distancing Using Computer Vision - AI Suisse
Michael Gorkow: Due to the current Corona crisis, many governments decided to implement restrictions for social distance. While a lot of people follow these rules, there are still people who ignore them for various reasons. In this session, I will show you a way to track these social distancing rules using Computer Vision on camera images. Manfred Kügel: Businesses are required to guarantee safety of their staff and also customers during the current COVID-19 crisis. Manfred will show how companies can restart their businesses safely following the current strict guidelines including keeping 2m distance between people, wearing masks, closely monitoring symptoms, etc. It will be a competitive advantage for companies and institutions if they can avoid infection among their workforce. AI/Computer Vision can be an instrument to help companies to make sure that people stick to the guidelines and stay healthy. The use cases discussed are meant to serve as an inspiration for how AI and data science can support businesses to overcome the challenges of these times and the step-by-step opening of the economy again. Host: Steffen Konrath

Graph Technologies - More than just Social (Distancing) Networks
Graphs have become a hot topic in the data analytics area, but what can they do for organizations? Graphs excel at analyzing latent relationships in large networks of data – so they’re great for fraud analytics, manufacturing dependency analysis, customer 360 analysis – use cases that relational models struggle with. Oracle provides robust and scalable graph data management, query, and analytics – for free in Oracle Database. Hans Viehmann, Product Manager EMEA, Oracle @SpatialHannes and Gianni Ceresa, Managing Director at DATAlysis, Oracle ACE Director @G_Ceresa will introduce you to what graphs are all about, what problems they solve, and how you can get started using them right in Oracle Database.

Behavioral Health

Funding Virtual Care in a Time of Crisis Unpacking the FCC's COVID 19 Telehealth Program
NeuroFlow COO Adam Pardes and Wipfli Health Care Partner Jeff Bramschrieber will provide an overview of the FCC COVID-19 Telehealth Program, other COVID-19 funding opportunities, and how you can start funding your remote, virtual care efforts to support patients during these uncertain times. www.neuroflowsolution.com/coronavirusresponse

Using Virtual Care To Cope with Coronavirus
Remote and virtual care tools can help support your patients and properly allocate resources during the COVID-19 crisis. This Webinar on "Using Virtual Care to Cope with Coronavirus" offers our insights and support during this critical time.

Logistics

Asset Tracking Solutions for COVID-19
In the COVID-19 context, government authorities and commercial companies have been looking at recent technologies such as IoT to find all sorts of solutions to respond to the crisis. Social distancing, people tracking and asset monitoring have become crucial aspects of keeping the situation under control. In this webinar, LoRa Alliance® members will be addressing the following challenges with their LoRaWAN® solutions that currently exist in the market:

• How to facilitate social distancing for workers while respecting privacy regulations?

• Monitoring population flows in buildings and cities, which has become even more important than before.

• Connecting healthcare devices appears to be really helpful, especially in the most critical phases of the crisis

• In several industries, hygiene standards will evolve and remote monitoring will become necessary to maximize efficiency

• In addition to caring about people, maintenance of facilities, machines, and assets will also become more and more remote in the future.

CORONAVIRUS PANDEMIC PANIC BUYING | EMERGENCY PREPAREDNESS
The recent Coronavirus outbreak has everyone rushing to Costco and Walmart panic buying up all the toilet paper and bottled water and sanitizer and cold medicine. The sudden panic over the rapid spread of the Coronavirus worldwide has emergency and pandemic preparedness on everyone's mind. We put together some survival kits today and talked to the kids about how if you wait for an emergency to stock up on essentials, you're already too late. Then we went to four different grocery stores to find empty shelves and out of stock items as people are selling out of toilet paper and water across the country. So just how serious is the novel Coronavirus? Is it officially a pandemic? Check the latest facts and numbers on the official CDC website to get accurate up to date information about the spreading Coronavirus.

Policy - Data Driven Decisions

Artificial Intelligence | Decision Intelligence | Machine Learning | Global Knowledge
What is the role of data, AI, and analytics in mitigating the risks of COVID-19 to the workplace or public space? COVID-19 represents new risks for organizations as workers return physically to their jobs, and as people return to public spaces. In this webinar, you will learn:” What are AI and DI? Why are they both essential to COVID-19 decision making?” ” How to use AI to see the patterns in data—private and public—that affect risk.”

  • ” How to use agent-based simulations to see how people interact with your facility, in order to inform policies that minimize risk.” About the presenter: Dr. Lorien Pratt has three decades of experience delivering applied AI, ML, and Natural Language Processing (NLP) solutions. She is a celebrated author, has appeared multiple times on NPR, has appeared on two TEDx Talks, and is a respected keynote speaker.

Policy Modelling for COVID-19: Better Data for Better Decision-Making in Low- and Middle-Income Countries
As low- and middle-income countries prepare to be hard hit by the COVID-19 outbreak, policymakers must make tough choices on how to allocate finite resources to respond, especially considering constraints in human resources, infrastructure, and supply chains. Optimizing resource allocation—at all times, but particularly in times of crisis—requires data on what works best and at what cost, but many policymakers currently lack this crucial information. The limited evidence on the comparative cost-effectiveness of potential interventions tends to be proprietary and predominantly shared with, and applicable to, high-income country governments. Further, this data is centered around disease transmission models and rarely incorporates the wider economic and health implications of containment policies beyond their immediate health impacts. As a result, policymakers, especially in low-resource settings, have little visibility into the direct health impacts and costs of COVID-targeted interventions, the indirect health implications of reallocated resources, and the longer-term effects on the economy and human capital more broadly.

Intelligence Community (IC)

COVID-19's Impact on the Intelligence Community
In this era of social distancing and quarantines due to the COVID-19 pandemic, individuals and industries are adapting to new norms in which direct in-person contact may be seriously curtailed for some time to come. How will this affect the intelligence community and espionage? Will human intelligence collection practices be forced to change? Will communications and signals intelligence collection play a more prominent role as face-to-face interactions become less frequent? Join 30-year CIA veteran Carol Rollie Flynn to learn how intelligence agencies are adapting during this unique time.

Intelligence agencies adapt to COVID-19
Former intelligence workers say lockdowns and stay-at-home orders could slow down the pipeline of human intelligence that spies get from new sources.

Understanding the Virus

What is Corona virus? What is COVID-19? Coronaviruses (CoV) are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). Coronavirus disease (COVID-19) caused by SARS-COV2 is a new strain that was discovered in 2019 and has not been previously identified in humans. Coronaviruses are zoonotic, meaning they are transmitted between animals and people. Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from camels to humans. Several known coronaviruses are circulating in animals that have not yet infected humans. It is believed that COVID-19 was transmitted from pangolin to humans (current theory). Common signs of infection include respiratory symptoms, fever, cough, shortness of breath and breathing difficulties. In more severe cases, infection can cause pneumonia, severe acute

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The "Six-Foot Rule" For The Coronavirus Is Based On Science From The 1930s. | Lydia Bourouiba - MIT disease transmission researcher - JAMA

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From email stating the source is The Center for Infectious Diseases at Johns Hopkins...

  • The virus is not a living organism, but a protein molecule (DNA) covered by a protective layer of lipid (fat), which, when absorbed by the cells of the ocular, nasal or buccal mucosa, changes their genetic code. (mutation) and convert them into aggressor and multiplier cells.
  • Since the virus is not a living organism but a protein molecule, it is not killed, but decays on its own. The disintegration time depends on the temperature, humidity and type of material where it lies.
  • The virus is very fragile; the only thing that protects it is a thin outer layer of fat. That is why any soap or detergent is the best remedy, because the foam CUTS the FAT (that is why you have to rub so much: for 20 seconds or more, to make a lot of foam).

By dissolving the fat layer, the protein molecule disperses and breaks down on its own.

  • HEAT melts fat; this is why it is so good to use water above 25 degrees Celsius for washing hands, clothes and everything. In addition, hot water makes more foam and that makes it even more useful.
  • Alcohol or any mixture with alcohol over 65% DISSOLVES ANY FAT, especially the external lipid layer of the virus.
  • Any mix with 1 part bleach and 5 parts water directly dissolves the protein, breaks it down from the inside.
  • Oxygenated water helps long after soap, alcohol and chlorine, because peroxide dissolves the virus protein, but you have to use it pure and it hurts your skin.
  • NO BACTERICIDE OR ANTIBIOTIC SERVES. The virus is not a living organism like bacteria; antibodies cannot kill what is not alive.
  • NEVER shake used or unused clothing, sheets or cloth. While it is glued to a porous surface, it is very inert and disintegrates only
    • between 3 hours (fabric and porous),
    • 4 hours (copper and wood)
    • 24 hours (cardboard),
    • 42 hours (metal) and
    • 72 hours (plastic).

But if you shake it or use a feather duster, the virus molecules float in the air for up to 3 hours, and can lodge in your nose.

  • The virus molecules remain very stable in external cold, or artificial as air conditioners in houses and cars.

They also need moisture to stay stable, and especially darkness. Therefore, dehumidified, dry, warm and bright environments will degrade it faster.

  • UV LIGHT on any object that may contain it breaks down the virus protein. For example, to disinfect and reuse a mask is perfect. Be careful, it also breaks down collagen (which is protein) in the skin.
  • The virus CANNOT go through healthy skin.
  • Vinegar is NOT useful because it does not break down the protective layer of fat.
  • NO SPIRITS, NOR VODKA, serve. The strongest vodka is 40% alcohol, and you need 65%.
  • LISTERINE IF IT SERVES! It is 65% alcohol.
  • The more confined the space, the more concentration of the virus there can be. The more open or naturally ventilated, the less.
  • You have to wash your hands before and after touching mucosa, food, locks, knobs, switches, remote control, cell phone, watches, computers, desks, TV, etc. And when using the bathroom.
  • You have to HUMIDIFY HANDS DRY from so much washing them, because the molecules can hide in the micro cracks. The thicker the moisturizer, the better.
  • Also keep your NAILS SHORT so that the virus does not hide there.

-JOHNS HOPKINS HOSPITAL

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The Exponential Power of Now | Nicholas P. Jewell is Chair of Biostatistics and Epidemiology at the London School of Medicine and Tropical Medicine

COVID-19: The Exponential Power of Now - With Prof. Nicholas Jewell
Where are we with COVID-19, and how are mathematical models and statistics helping us develop strategies to overcome the burden of infections. Nicholas P. Jewell is Chair of Biostatistics and Epidemiology at the London School of Medicine and Tropical Medicine and Professor of the Graduate School (Biostatistics and Statistics) at the University of California, Berkeley.

Epidemiology, Pathophysiology, Diagnostics

Sialic acids are a diverse group of carbohydrates that blossom like leaves from the tips of proteins covering the surfaces of human cells. ...This canopy of sugars is typically the first thing you'd bump into if you were the size of a virus or bacterium, so it's no surprise that these chemicals serve as a security badge, identifying friend from foe."Most coronaviruses infect cells in two steps – first by recognising abundant sialic acids as binding sites to gain a foothold, and then seeking out the higher affinity protein receptors like ACE2," says physician Ajit Varki. Strangely, a human-like elimination of the NeuA5c gene in mice gives them a boost in running ability, and in activating other parts of their immune system. Given the new cognitive and physical talents emerging in humans a couple of million years ago, asthma and cholera might well have been worth the swap. Humans Might Be So Sickly Because We Evolved to Avoid a Single Devastating Disease | Mike Mcrae and Ann Gibbons - Science Alert - Science Magazine

COVID-19 | Coronavirus: Epidemiology, Pathophysiology, Diagnostics
What is Corona virus? What is COVID-19? Coronaviruses (CoV) are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). Coronavirus disease (COVID-19) caused by SARS-COV2 is a new strain that was discovered in 2019 and has not been previously identified in humans. Coronaviruses are zoonotic, meaning they are transmitted between animals and people. Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from camels to humans. Several known coronaviruses are circulating in animals that have not yet infected humans. It is believed that COVID-19 was transmitted from pangolin to humans (current theory). Common signs of infection include respiratory symptoms, fever, cough, shortness of breath and breathing difficulties. In more severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure and even death (WHO, 2020). Ninja Nerd Lectures has compiled the most up to date and recent data on COVID-19 as of March 15, 2020. Please follow along with this lecture to understand the origin and zoonosis of COVID-19, the routes of transmission, epidemiology (current as of 3/15/2020), pathophysiology, and diagnostic tests used to identify COVID-19. As new information and research is published we will continue to provide updates on COVID-19 and ensure all of our viewers are kept up to date on the most recent data.

COVID-19 | Coronavirus: Epidemiology, Pathophysiology
Join us for our lecture on COVID-19 where Ninja Nerd Science will go into detail on the virology, epidemiology, and pathophysiology/pathology of COVID-19. This is our April update on our previous lecture to keep all of our viewers informed on the new research and publications that have been released on COVID-19. Please be aware— This lecture is up to date as of April 17, 2020. Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19. COVID-19 is the infectious disease caused by the most recently discovered coronavirus. This new virus and disease were unknown before the outbreak began in Wuhan, China, in December 2019. The most common symptoms of COVID-19 are fever, tiredness, and dry cough. Some patients may have aches and pains, nasal congestion, runny nose, sore throat or diarrhea. These symptoms are usually mild and begin gradually. Some people become infected but don’t develop any symptoms and don't feel unwell. Most people (about 80%) recover from the disease without needing special treatment. Around 1 out of every 6 people who gets COVID-19 becomes seriously ill and develops difficulty breathing. Older people, and those with underlying medical problems like high blood pressure, heart problems or diabetes, are more likely to develop serious illness. People with fever, cough and difficulty breathing should seek medical attention. World Health Organization (WHO) | 8 April 2020

Treatment, Prognosis, Precautions | Zach Murphy

COVID-19 | Coronavirus: Treatment, Prognosis, Precautions
What is Corona virus? What is COVID-19? Coronaviruses (CoV) are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). Coronavirus disease (COVID-19) caused by SARS-COV2 is a new strain that was discovered in 2019 and has not been previously identified in humans. Coronaviruses are zoonotic, meaning they are transmitted between animals and people. Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from camels to humans. Several known coronaviruses are circulating in animals that have not yet infected humans. It is believed that COVID-19 was transmitted from pangolin to humans (current theory). Common signs of infection include respiratory symptoms, fever, cough, shortness of breath and breathing difficulties. In more severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure and even death (WHO). Ninja Nerd Lectures has compiled the most up to date and recent data on COVID-19 as of March 15, 2020. Please follow along with this lecture to understand the treatment, prognosis, and precautions for COVID-19 (current as of 3/15/2020). As new information and research is published we will continue to provide updates on COVID-19 and ensure all of our viewers are kept up to date on the most recent data. REFERENCES: World Health Organization (WHO), Centers for Disease Control and Prevention (CDC). World Health Organization (WHO), Centers for Disease Control and Prevention (CDC).

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