@article{yu_andradottir_ayhan_2023, title={Optimal control of supervisors balancing individual and joint responsibilities}, volume={1}, url={http://dx.doi.org/10.1017/s0269964823000013}, DOI={10.1017/s0269964823000013}, abstractNote={Abstract}, journal={Probability in the Engineering and Informational Sciences}, publisher={Cambridge University Press (CUP)}, author={Yu, Zhuoting and Andradottir, Sigrun and Ayhan, Hayriye}, year={2023}, month={Jan}, pages={1–20} }
 @article{yu_keskinocak_magliocca_romero_sokol_2023, title={Split or whole liver transplantation? Utilization and posttransplant survival}, url={https://doi.org/10.1097/HC9.0000000000000225}, DOI={10.1097/HC9.0000000000000225}, abstractNote={
            Background:
            Split liver transplantation (SLT), where a single donor liver is divided for transplantation to 2 recipients, has the potential to increase the availability of size-matched livers for pediatric candidates and expand the supply of donor organs available for adult candidates. Although SLT is a well-established technique, the number of SLTs has remained flat during the past 2 decades, partly due to concerns about the posttransplant survival of SLT recipients compared with whole liver transplantation (WLT) recipients. Prior work on SLT versus WLT survival analysis had limitations because, for pediatric recipients, it did not consider the correlations between donor age/weight and the allograft type, and for adult recipients, it may have included records where the donor livers did not meet the split liver criteria (splittable).
          }, journal={Hepatology Communications}, author={Yu, Zhuoting and Keskinocak, Pinar and Magliocca, Joseph F. and Romero, Rene and Sokol, Joel}, year={2023}, month={Sep} }
 @article{yu_keskinocak_sokol_chen_2022, title={Flexible analytic model to inform multi-stakeholder pediatric vaccine scheduling decisions}, volume={40}, url={http://dx.doi.org/10.1016/j.vaccine.2022.09.076}, DOI={10.1016/j.vaccine.2022.09.076}, abstractNote={Pediatric immunization is important for preventing potentially life-threatening diseases in children. Over time, the number of recommended pediatric vaccines has increased and is likely to increase further as new vaccines are developed. Given the different number of doses for available vaccines and various constraints (e.g., the appropriate age for each dose of a vaccine or the time between doses), it is challenging to develop a recommended vaccination schedule or a catch-up schedule when a child falls behind on one or more vaccinations.We developed an integer programming optimization model, enabled by Python programming and embedded into an Excel-based decision tool, to recommend childhood vaccination schedules or personalized catch-up schedules. The model recommends a vaccination schedule that balances the goal of being as close as possible to the clinically-indicated dosing schedules and the goal of minimizing clinic visits, and gives users the ability to trade off between these two goals. We illustrated the broad applicability of our proposed model with commonly-faced vaccine scheduling challenges in the United States.The illustrative computational case study confirms our model's ability to create personalized schedules based on each child's age and vaccination history, and to adjust appropriately when a new vaccine becomes available.The model presented in this paper fills the need for an easy-to-use tool to recommend vaccination schedules for de novo and catch-up purposes. It provides straightforward recommendations that can be easily used by physicians, is flexible to handle the requirements varying by region, and can be updated as new vaccines are approved for use.}, number={52}, journal={Vaccine}, publisher={Elsevier BV}, author={Yu, Zhuoting and Keskinocak, Pinar and Sokol, Joel and Chen, Yao-Hsuan}, year={2022}, month={Dec}, pages={7631–7639} }
 @article{yu_keskinocak_steimle_yildirim_2022, title={The Impact of Testing Capacity and Compliance With Isolation on COVID-19: A Mathematical Modeling Study}, volume={1}, url={http://dx.doi.org/10.1016/j.focus.2022.100006}, DOI={10.1016/j.focus.2022.100006}, abstractNote={•Starting testing programs early is effective in reducing the infection spread.•Starting testing programs early also leads to less self-isolation in total.•Higher symptomatic isolation compliance is favored if early testing is unavailable.•Delay in the start of testing results in extra testing capacity to make up. IntroductionDiagnostic tests can play an important role in reducing the transmission of infectious respiratory diseases, particularly during a pandemic. The potential benefit of diagnostic testing depends on at least 4 factors: (1) how soon testing becomes available after the beginning of the pandemic and (2) at what capacity; (3) compliance with isolation after testing positive; and (4) compliance with isolation when experiencing symptoms, even in the absence of testing.MethodsTo understand the interplay between these factors and provide further insight into policy decisions for future pandemics, we developed a compartmental model and simulated numerous scenarios using the dynamics of COVID-19 as a case study.ResultsOur results quantified the significant benefits of early start of testing and high compliance with isolation. Early start of testing, even with low testing capacity over time, could significantly slow down the disease spread if compliance with isolation is high. By contrast, when the start of testing was delayed, the benefit of testing on reducing infection spread was limited, even when testing capacity was high; the additional testing capacity required increased superlinearly for each day of delay to achieve a similar infection attack rate as in starting testing earlier.ConclusionsOur study highlighted the importance of the early start of testing and public health messaging to promote isolation compliance when needed for an ongoing effective response to COVID-19 and future pandemics.}, number={1}, journal={AJPM Focus}, publisher={Elsevier BV}, author={Yu, Zhuoting and Keskinocak, Pinar and Steimle, Lauren N. and Yildirim, Inci}, year={2022}, month={Sep}, pages={100006} }