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COVID-19

This work aims to address and better understand the COVID-19 disease and corresponding pandemic via scenario modeling, forecasting and other support measures.

Amid the current pandemic, our group is using the theoretical and empirical approaches consistently implemented in our projects of focus to assist in the global combative efforts against COVID-19. Our current efforts to aid in response to COVID-19 and to better understand the transmission dynamics of the SARS-CoV-2 coronavirus strain are listed below:

COVID-19 Scenario Modeling Hub

The COVID-19 scenario modeling hub is a collaborative effort between several North American modeling teams that has been developed to meet the need for longer-term projections of COVID-19 burden in the United States. These teams are providing probabilistic projections for each future week, which are then combined into an ensemble for each desired scenario, outcome, week, and location. The goal of these long-term projections is to compare outbreak trajectories under different scenarios, as opposed to offering a specific, unconditional estimate of what “will” happen. The modeling hub was created to build on and complement the COVID 19 Forecast Hub. More information on these projections can be found here.

Contact Tracing Evaluation and Strategic Support Application (ConTESSA)

ConTESSA is a contact tracing application developed for contact tracing program managers. It is meant to indicate the impacts of current programs, as well as emphasize areas in need of greater focus to reduce COVID-19 transmission in identified communities. The scenarios generated by the application are applicable at both the household and community level. This app is in collaboration with Johns Hopkins Bloomberg School of Public Health researchers. The application can be found here.

COVID-19 Scenario Pipeline

This scenario pipeline is a public shared code (via GitHub) used for scenario forecasting and can assist in creating reports for various government entities. The model was designed to be as versatile as possible, allowing for its use with varied parameters (i.e. different spatial scales given the shapefiles, population data and COVID-19 confirmed case data available). The pipeline has been used to support several partners including the state of California and the national US response. Access to the pipeline can be found here.

Health Intervention Tracking (HIT-COVID)

HIT-COVID is a live database focused on the collection of data related to global health COVID-19 intervention policies at the national and first-level administrative units. The intervention policies of interest are believed to have a direct impact on disease transmission. The data is anticipated to assist in the national and subnational governmental determinants of closing or reopening sectors of society. This work is in collaboration with the Boston University School of Public Health. The database can be found here.

2019 Novel Coronavirus Research Compendium (NCRC)

The NCRC is a centralized, curated location for novel research on the SARS-CoV-2 coronavirus strain and the COVID-19 disease. The research is grouped by general topic, with new topic-related reviews continually made available. This is a collaborative effort between the Johns Hopkins School of Public Health and the School of Medicine. The compendium can be found here.

Understanding SARS-COV-2 Transmission with Serologic Data

We are working with multiple collaborators, including those at Massachusetts General Hospital and Hôpitaux universitaires de Genève (Switzerland) to better characterize the human antibody response to SARS-COV-2 infections and to use these data to better understand key aspects of SARS-COV-2 transmission.

SARS-CoV-2 Genomics

We are working with groups across Johns Hopkins University to sequence the SARS-CoV-2 genome from patient samples to better understand the lineages circulating in the National Capital Region. As part of this collaboration, we have published over 100 viral genomes from the region to public databases (including GISAID and NCBI Genbank) and are working to integrate these data with epidemiological models to further characterize transmission dynamics.

COVID-19 Training Initiative

The COVID-19 Training Initiative draws on the resources at the Bloomberg School of Public Health and Johns Hopkins University to provide free online courses and tools, tailored training for public health departments in the US, and additional training for the Baltimore Health Corps. Training materials developed by the Initiative can be found here.

Principal Investigator

Andrew Azman Assistant Scientist

M. Kate Grabowski Assistant Professor

Emily Gurley Associate Scientist

Alison Hill Assistant Professor

Elizabeth C. Lee Research Associate

Kyu Han Lee Research Associate

Justin Lessler Associate Professor

Shaun Truelove Assistant Scientist

Updates #covid19

3 months 5 days ago

We are excited to share that our study looking at how the #COVID19 risk associated with in-person schooling changed… https://t.co/IVzqN6CEYY
7 months 2 weeks ago

RT @JustinLessler: The #COVID19 Scenario Modeling Hub is working on a round devoted to #Omicron. However, the speed and severity of th… https://t.co/KcsFnEUglA
9 months 2 weeks ago

RT @JustinLessler: In spring 2021 the school and #COVID19 situation changed a lot (vaccines, variants and return to inperson classes).… https://t.co/NnaL47gaCl
1 year 2 months ago

RT @JustinLessler: Round 5 results of the #COVID19 Scenario Modeling Hub are live https://t.co/MpOC8UdUk4 Looking good in most scenar… https://t.co/2Lkt3hEj1G
1 year 3 months ago

RT @JustinLessler: Very excited to have the work of the #COVID19 Scenario Modeling Hub featured in the MMWR. This ongoing multi team… https://t.co/xu5Iu74UMq
1 year 3 months ago

RT @JustinLessler: Thrilled our paper on household #COVID19 risk and in person schooling is out in @ScienceMagazine rapid release!… https://t.co/tmzf5iwUAA
1 year 4 months ago

RT @KateGrabowski: #COVID19 #transmission models are ubiquitous and critical to informing policy, but often poorly understood. This p… https://t.co/mwxUOfCKAQ
1 year 8 months ago

RT @LucyStats: 📅🎄 We are officially 14 days, or one #COVID19 quarantine, from Christmas Since folks are likely considering quara… https://t.co/0cDitzMZlL
1 year 8 months ago

RT @JustinLessler: 1,928 US #Covid19 deaths yesterday. Last day with over 1,900 was May 7. The cases to double the current rate are al… https://t.co/6M5o7aOjyp
1 year 8 months ago

RT @JustinLessler: My thoughts on the need for better defining what our goals are in #COVID19 control as we enter a new phase of the p… https://t.co/vNFhlNglRb
1 year 9 months ago

RT @reichlab: Post-doc position for helping with modeling at the #COVID19 Forecast Hub still accepting applications. Come join th… https://t.co/bYSM4bKnVS
1 year 9 months ago

RT @JustinLessler: This is exactly the point. #COVID19 testing is a tool on the way to a solution, not the solution itself. https://t.co/yqzWBWnI07

Funders

Bloomberg Philanthropies

Federal Emergency Management Agency (FEMA)

Johns Hopkins Health System

State of California

Collaborators

Boston University School of Public Health

Hôpitaux Universitaires de Genève (HUG)

Johns Hopkins Applied Physics Laboratory

Johns Hopkins Bloomberg School of Public Health

Johns Hopkins School of Medicine

Publications

12 Apr 2021

Coordinated Strategy for a Model-Based Decision Support Tool for Coronavirus Disease, Utah, USA

Meredith HR, Arehart E, Grantz KH, Beams A, Sheets T, Nelson R, Zhang Y, Vinik RG, Barfuss D, Pettit JC, McCaffrey K, Dunn AC, Good M, Frattaroli S, Samore MH, Lessler J, Lee EC, Keegan LT

Emerg Infect Dis, 2021: 27(5): 10.3201/eid2705.203075

1 May 2021

Serological evidence of human infection with SARS-CoV-2: a systematic review and meta-analysis

Chen X, Chen Z, Azman AS, Deng X, Sun R, Zhao Z, Zheng N, Chen X, Lu W, Zhuang T, Yang J, Viboud C, Ajelli M, Leung DT, Yu H

Lancet Glob Health, 2021: 9(5): e598-e609, 10.1016/S2214-109X(21)00026-7

20 Apr 2021

Markers of Polyfunctional SARS-CoV-2 Antibodies in Convalescent Plasma

Natarajan H, Crowley AR, Butler SE, Xu S, Weiner JA, Bloch EM, Littlefield K, Wieland-Alter W, Connor RI, Wright PF, Benner SE, Bonny TS, Laeyendecker O, Sullivan D, Shoham S, Quinn TC, Larman HB, Casadevall A, Pekosz A, Redd AD, Tobian AAR, Ackerman ME

mBio, 2021: 12(2): e00765-21, 10.1128/mBio.00765-21

26 Apr 2021

Differential Performance of CoronaCHEK SARS-CoV-2 Lateral Flow Antibody Assay by Geographic Origin of Samples

Baker OR, Grabowski MK, Galiwango RM, Nalumansi A, Serwanga J, Clarke W, Hsieh YH, Rothman RE, Fernandez RE, Serwadda D, Kagaayi J, Lutalo T, Reynolds SJ, Kaleebu P, Quinn TC, Laeyendecker O

J Clin Microbiol, 2021: 10.1128/JCM.00837-21

1 Apr 2021

Antibody responses to endemic coronaviruses modulate COVID-19 convalescent plasma functionality

Morgenlander WR, Henson SN, Monaco DR, Chen A, Littlefield K, Bloch EM, Fujimura E, Ruczinski I, Crowley AR, Natarajan H, Butler SE, Weiner JA, Li MZ, Bonny TS, Benner SE, Balagopal A, Sullivan D, Shoham S, Quinn TC, Eshleman SH, Casadevall A, Redd AD, Laeyendecker O, Ackerman ME, Pekosz A, Elledge SJ, Robinson M, Tobian AA, Larman HB

J Clin Invest, 2021: 131(7): e146927, 10.1172/JCI146927

1 Apr 2021

Serology-informed estimates of SARS-CoV-2 infection fatality risk in Geneva, Switzerland

Perez-Saez J, Lauer SA, Kaiser L, Regard S, Delaporte E, Guessous I, Stringhini S, Azman AS

Lancet Infect Dis, 2021: 21(4): e69-e70, 10.1016/S1473-3099(20)30584-3

25 Jan 2021

ABO blood group and SARS-CoV-2 antibody response in a convalescent donor population

Bloch EM, Patel EU, Marshall C, Littlefield K, Goel R, Grossman BJ, Winters JL, Shrestha R, Burgess I, Laeyendecker O, Shoham S, Sullivan D, Gehrie EA, Redd AD, Quinn TC, Casadevall A, Pekosz A, Tobian AAR

Vox Sang, 2021: 10.1111/vox.13070

1 Mar 2021

SARS-CoV-2-specific CD8+ T cell responses in convalescent COVID-19 individuals

Kared H, Redd AD, Bloch EM, Bonny TS, Sumatoh H, Kairi F, Carbajo D, Abel B, Newell EW, Bettinotti MP, Benner SE, Patel EU, Littlefield K, Laeyendecker O, Shoham S, Sullivan D, Casadevall A, Pekosz A, Nardin A, Fehlings M, Tobian AA, Quinn TC

J Clin Invest, 2021: 131(5): e145476, 10.1172/JCI145476

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