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:
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: https://iddynamics.jhsph.edu/apps/connect/contessa/ .
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: https://github.com/HopkinsIDD/COVIDScenarioPipeline .
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: https://akuko.io/post/covid-intervention-tracking .
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: https://ncrc.jhsph.edu .
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.
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.
The first Coursera course developed under this initiative provides an introduction to COVID-19 and contact tracing: https: //www.coursera.org/learn/covid-19-contact-tracing
The second Coursera course provides contact tracing program managers guidance on important indicators of performance of a contact tracing program, and a tool that can be used to project the likely impact of improvements in specific indicators: https://www.coursera.org/learn/measuring-and-maximizing-impact-of-covid-...