Because infectious diseases often transmit directly or indirectly from person to person, social networks are a powerful tool to understand infectious disease spread. A branch of my work therefore focuses on using networks and EMR data to understand infectious disease spread. This began with a simple question: can we predict infection solely based on being around others suspected of infection? It turns out the answer is: yes! I am now in the process of studying asymptomatic infections, how they affect disease dynamics in a healthcare setting, and how identifying and quarantining them might lead to smaller outbreaks. I have also done simulation work on infectious disease questions when the necessary data are not easily obtainable, which has led to important insights in the absence of empirical data.
Lienert J, Reed-Tsochas F, Marcum CS, and Koehly L. 2020. A passive monitoring tool using hospital administrative data enables earlier specific detection of healthcare-acquired infections. Journal of Hospital Infection. DOI: https://doi.org/10.1016/j.jhin.2020.07.031.
Rewley J. 2020. Specimen pooling conserves additional testing resources when persons’ infection status is correlated: A simulation study. Epidemiology.
Lienert J, Koehly L, Finney J, Marcum CS, Reed-Tsochas F. Detection of patients with asymptomatic infection via electronic medical records.