1. Making Every Test Count: Group Testing
  2. Modeling and Controlling the Spread of COVID-19
  3. Communications Technology & Coronavirus
  4. Engineering Vaccines
  5. Contact Tracing and Virus Tracking
  6. Using Drones to deliver disinfecting UV-light
  7. What About Our Mental Health?
  8. IEEE Standards for secure communications from home

1. Making Every Test Count: Group Testing

Krishna Narayanan and Anoosheh Heidarzadeh, Texas A&M University
Junan Zhu, Kistina Rivera, and Dror Baron, North Carolina State University
Dhruva Kartik and Urbashi Mitra, University of Southern California

There is broad consensus among epidemiologists, economists and policy makers that wide-scale testing of asymptomatic patients is the key for reopening the economy. Wide-scale testing will ensure containment of the disease to a small population and appropriate apportionment of medical resources to different geographic regions. A current challenge is the limited number of tests and the variation of efficacies across different testing methodologies. It is also clear that different populations of individuals have different prior probabilities of being positive for SARS-CoV-2: where one lives, workplace, symptoms, underlying health conditions. To this end, group testing can be used to pool samples from individuals in order to substantially reduce the number of overall tests used to evaluate who in the population is positive for SARS-CoV-2.  If the prevalence is small, the reduction in the number of tests needed to determine infected individuals is high.  Several groups are actively investigating how to apply group testing strategies to reduce the number of needed tests.  Communication theories that are proving useful include approximate message passing which has roots in CDMA and LDPC codes as well as compressed sensing and more general coding theory.

Five People. One test. That is how you get there.  https://www.nytimes.com/2020/05/07/opinion/coronavirus-group-testing.html


M. Aldridge, O. Johnson, J. Scarlett, “Group testing: an information theory perspective,” arXiv, Sep. 2019. Available: arXiv:1902.06002    (https://arxiv.org/abs/1902.06002)

Tapestry: A Single-Round Smart Technique for COVID-19 Testing. https://tapestry-pooling.herokuapp.com

N. Shental, S. Levy, S. Skorniakov, V. Wuvshet, Y. Shemer-Avni, A. Porgador, T. Hertz, “Efficient high throughput SARS-CoV-2 testing to detect asymptomatic carriers,” arXiv, April 2020. Available: medRxiv 2020.04.14.20064618    (https://www.medrxiv.org/content/10.1101/2020.04.14.20064618v1)

J. Zhu, K. Rivera, D. Baron, “Noisy Pooled PCR for Virus Testing,’’ arXiv, April 2020. Available: arXiv:2004.02689   (https://arxiv.org/abs/2004.02689)

K. R. Narayanan, A. Heidarzadeh, R. Laxminarayan, “On Accelerated Testing for COVID-19 Using Group Testing,’’ arXiv, April 2020. Available: arXiv:2004.04785   (https://arxiv.org/abs/2004.04785)

J. Yi, R. Mudumbai, and W. Xu, “Low-cost and high-throughput testing of covid-19 viruses and antibodies via compressed sensing: System concepts and computational experiments,” arXiv, April 2020. Available: arXiv:2004.05759    (https://arxiv.org/abs/2004.05759)

Kartik D, Nayyar A, Mitra U. Fixed-horizon Active Hypothesis Testing. arXiv preprint arXiv:1911.06912. 2019 Nov 15.

Kartik D, Nayyar A, Mitra U. Testing for Anomalies: Active Strategies and Non-asymptotic Analysis. arXiv preprint arXiv:2005.07696. 2020 May 15.

2. Modeling and Controlling the Spread of COVID-19

Vince Poor, Simon Levin (Princeton University), Joshua Plotkin (University of Pennsylvania), Osman Yagan (Carnegie Mellon University)

A key scientific goal concerning COVID-19 is to develop mathematical models that help us to understand and predict its spreading behavior, as well as to provide guidelines on what can be done to limit its spread. With tight restrictions on human mobility and activity already in place in many jurisdictions, an important question will soon arise as to when these restrictions can be safely eliminated. To have educated answers to these questions, we need to

    i) Analyze and predict the spread of COVID-19 through mathematical models incorporating virus mutations,
    ii) Do optimal and robust control of the spread of COVID-19 by carefully-timed interventions.

Fortunately, both these goals are well within our scope of expertise as engineers.

We expect the outcomes of this research to provide authorities an input to better assess the effectiveness of existing or potential countermeasures in limiting the spread of COVID-19. They can also help leaders assess the outcomes of eliminating existing countermeasures. Finally, they will help us better prepare for different mutation scenarios including worst-cases (for the current or a future pandemic).




Proceedings of the National Academy of Sciences Mar 2020, 117 (11) 5664 5670; DOI: 10.1073/pnas.1918529117   (https://www.pnas.org/content/117/11/5664.abstract)

R. Eletreby, Y. Zhuang, K. M. Carley, O. Yagan, and H. V. Poor, “The effects of evolutionary adaptations on spreading processes in complex networks”, Proceedings of the National Academy of Sciences, vol. 117, no. 11, pp. 5664-5670, Mar. 2020. (https://www.pnas.org/content/117/11/5664.abstract)

3. Communications Technology & Coronavirus

Vincent Poor (Princeton University), Petar Popovski (Aalborg University), Fulvio Babich (University of Trieste), Mohamed-Slim Alouini (King Abdullah University of Science and Technology),Robert Heath (University of Texas, Austin) , Hamed Ahmadi (University of York), Konstantinos Katzis (European University Cyprus), Muhammad Zeeshan Shakir (University of the West of Scotland), Mahnaz Arvaneh (University of Sheffield), Alan Gatherer (Futurewei)  

Communications technologies have been essential for us to continue many lines of work from home during the COVID-19 lockdown, in particular, network technologies for low mobility/fixed users have proved useful. These works below include discussions of how current efforts (ultra-reliable, low latency communications, IoT networks) can make an impact as well as the role that communications and signal processing research can play in the future

Concepts in communications and network theories can have valuable areas of application in the re-opening stage, as well. For example, we can form analogies between contact probabilities of humans and MAC protocols to come up with strategies to mitigate the infection risk, or link game theory to stay-at-home behaviors of people.

We also unfortunately saw many misconceptions about SARS-CoV-2 and 5G. The articles and blog posts noted below, highlight the role for communication engineers to play in getting accurate information out to the public.



https://coronavirus.jhu.edu/map.html (last accessed: July 2nd, 2020)

R. W. Heath, “Revisiting Research on Signal Processing for Communications in a Pandemic [From the Editor],” in IEEE Signal Processing Magazine, vol. 37, no. 3, pp. 3-5, May 2020.




“Coronavirus: Derby 5G phone mast set on fire,” Available at https://www.bbc.com/news/uk-england-derbyshire-52790399

“5G protesters sabotage dutch phone towers,” Available at https://www. dw.com/en/5g-protesters-sabotage-dutch-phone-towers/a-53094033, Last Accessed: 26th May 2020.

“5G mast ’on fire’ hours after mayor slams ’bizarre’ coronavirus conspiracy theories,” Available at https://www.liverpoolecho.co.uk/news/liverpool-news/5g-mast-on-fire-hours-18041768

Caulfield, “Pseudoscience and COVID-19-we’ve had enough already.” Available at: https://www.nature.com/articles/ d41586-020-01266-z, Apr. 2020

Chiaraviglio, A. Elzanaty, M.S. Alouini, “Health risks associated with 5G exposure: A view from the communications engineering perspective,’’ arXiv, April 2020. Available: arXiv:2004.02689 (https://arxiv.org/abs/2006.00944)

4. Engineering Vaccines

Matthew McKay – Hong Kong University of Science and Technology

What marks the “end” of the COVID-19 outbreak? What are we waiting for by staying at home? When will the public fear be relieved? If we ask these questions to the general public, the most wide-spread answer would probably be related to the development of a vaccine.

Throughout decades, virologists used a classical vaccine design methodology that aims to induce an immune response in the patient by injecting a weakened form of the virus. This strategy was obviously very successful, mitigating the effects of many dangerous and contagious diseases, even eradicating some. However, the classical approach has unfortunate shortcomings against viruses with rapid evolving natures (e.g. HIV). Furthermore, we may want to take quick and accurate action against rapidly emerging viruses, such as SARS-CoV-2. Prof. Matthew McKay of the Hong Kong University of Science and Technology aims to provide insights on structural properties -and hopefully vulnerabilities- of viruses through data analytics methods on the genetic sequence of viruses. In another article in the Viruses Journal, Prof. McKay’s group addresses the possibility of leveraging existing literature on the initial SARS outbreak of 2003 by characterizing the genetic similarity between SARS-CoV and SARS-CoV-2 viruses. The results of the study hints to promising points that could be exploited from a vaccine design point of view. Information regarding the obtained genetic data for the SARS-CoV-2 virus, alongside the immunological data of the 2003 SARS outbreak can be accessed through the COVIDep web platform developed by the group.


[R1] M. S. Sohail, A. A. Quadeer, and M. R. McKay, “How genetic sequence can guide vaccine design,” IEEE Potentials, vol. 39, no. 3, May 2020. https://ieeexplore.ieee.org/abstract/document/9088164

[R2] S. F. Ahmed, A. A. Quadeer, and M. R. McKay, “Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies,” Viruses 12.3 (2020): 254. https://www.mdpi.com/1999-4915/12/3/254

[R3] S. F. Ahmed, A. A. Quadeer, and M. R. McKay, “COVIDep: a web-based platform for real-time reporting of vaccine target recommendations for SARS-CoV-2”, Nature Protocols, June 2020. (https://doi.org/10.1038/s41596-020-0358-9)


5. Contact Tracing and Virus Tracking

Privacy-sensitive mobile-based contact logging
Bhaskar Krishnamachari, University of Southern California

While the idea of digital mobile-device based contact tracing, using short-range radio signals to determine which individuals  have been close to each other has been around for some time, and clearly useful in the context of the present COVID-19 pandemic, there is still not a wide and uniform acceptance of such tools, particularly in places where people have significant concerns about privacy.  With a goal of establishing privacy-sensitive contact logging and exposure notification, we can invoke our knowledge from network theory and come up with protocols. Two of such protocols, for example, have been proposed by Prof. Krishnamachari at the University of Southern California, and are based on the beaconing and logging of anonymous (either encrypted or randomized) Bluetooth messages. Such endeavors are also in the scope of companies like Google and Apple. Methods based on signal strength and localization are essential in the contact tracing effort.







6. Using Drones to deliver disinfecting UV-light

Tara Javidi, UCSD

Prof. Tara Javidi of UCSD is working to use off-the-shelf drones adapted to carry UV lights to act as remote room disinfectors for the SARS-CoV-2 virus. UV-C light has shown promise in disinfecting viruses; however, a challenge is that such light can be harmful to human skin.  Thus, such systems would need to be used in a remote fashion.  The cleaning strategy is based on a new work by Javidi’s group on active hypothesis testing and decision making.  Her methods have been effective in designing active methods for adapting mmWave antenna apertures to finding objects of interest in a scene.


[1] Y. Kaspi, O. Shayevitz and T. Javidi, “Searching for multiple targets with measurement dependent noise,” 2015 IEEE International Symposium on Information Theory (ISIT), Hong Kong, 2015, pp. 969-973 (https://ieeexplore.ieee.org/abstract/document/7282599)

[2] Sung-En Chiu and Tara Javidi. Low Complexity Sequential Search with Measurement Dependent Noise,arXiv, cs.IT, 2020 (https://arxiv.org/abs/2005.07814)

[3] Y. Kaspi, O. Shayevitz and T. Javidi, “Searching With Measurement Dependent Noise,” in IEEE Transactions on Information Theory, vol. 64, no. 4, pp. 2690-2705, April 2018 (https://ieeexplore.ieee.org/abstract/document/8115301)


7. What About Our Mental Health?

Ashutosh Sabharwal and Ashok Veeraraghavan, Rice University
Nidal Moukaddam, Baylor College of Medicine

For millions affected globally by COVID-19 – patients, caregivers, healthcare professionals and everyone else either stuck at home or having to work in this pandemic – mental wellbeing is now under threat. Rice University and Baylor College of Medicine researchers have joined forces in a citizen science project, CovidSense, to understand COVID’s impact on people’s mental wellbeing. You can join from anywhere in the world to contribute data – no app download needed and no private info will be shared. More than 550 people from 14 countries have already enrolled. The data could influence public health policies, so have your voice heard.https://covidsense.org/

8.  IEEE Standards for secure communications from home

Mohammad Asad Chaudhry – IEEE Standards for Software-Defined and Virtualized Ecosystems (SDN/NFV Performance – IEEE P1916) 

The IEEE Standard Group for software-defined networking and virtualized ecosystems (IEEE P1916.1), are utilizing their expertise in the network engineering domain to develop standards to enhance deployment of COVID-19 solutions. The applications vary from soft-converting a non-HIPAA compliant infrastructure to an HIPAA-compliant one, testing solutions, and many more. This endeavor can be of use for health service providers, the individuals needing these services, the government agencies resourcing the solutions, and other stakeholders.