Metapopulation Model from Pathogen's Perspective: A Versatile Framework to Quantify Pathogen Transfer and Circulation between Environment and Hosts.

Metapopulation models have been primarily explored in infectious disease epidemiology to study host subpopulation movements and between-host contact structures. They also have the potential to investigate environmental pathogen transferring. In this study, we demonstrate that metapopulation models serve as an ideal modeling framework to characterize and quantify pathogen transfer between environment and hosts. It therefore unifies host, pathogen, and environment, collectively known as the epidemiological triad, a fundamental concept in epidemiology. We develop a customizable and generalized pathogen-transferring model where pathogens dwell in and transferring (via contact) between environment and hosts. We analyze three specific case studies: pure pathogen transferring without pathogen demography, source-sink dynamics, and pathogen control via external disinfection. We demonstrate how pathogens circulate in the system between environment and hosts, as well as evaluate different controlling efforts for healthcare-associated infections (HAIs). For pure pathogen transferring, system equilibria can be derived analytically to explicitly quantify long-term pathogen distribution in the system. For source-sink dynamics and pathogen control via disinfection, we demonstrate that complete eradication of pathogens can be achieved, but the rates of converging to system equilibria differ based on specific model parameterization. Direct host-host pathogen transferring and within-host dynamics can be future directions of this modeling framework by adding specific modules.

Accuracy of the Pediatric End-stage Liver Disease Score in Estimating Pretransplant Mortality Among Pediatric Liver Transplant Candidates.

Importance: Fair allocation of livers between pediatric and adult recipients is critically dependent on the accuracy of mortality estimates afforded by the Pediatric End-stage Liver Disease (PELD) and Model for End-stage Liver Disease, respectively. Widespread reliance on exceptions for pediatric recipients suggests that the 2 systems may not be comparable. Objective: To evaluate the accuracy of the PELD score in estimating 90-day pretransplant mortality among pediatric patients on the United Network for Organ Sharing (UNOS) waiting list. Design, Setting, and Participants: Patients who were listed from February 27, 2002, to March 31, 2014, for primary liver transplant were included in this retrospective analysis and were followed up for at least 2 years through June 17, 2016. The study analyzed 2 cohorts using the UNOS Standard Transplant Analysis and Research data files. The full cohort comprised 4298 patients (<18 years of age) who had chronic liver disease (excluding cancer). The reduced cohort (n = 2421) excluded patients receiving living donor transplantation or PELD exception points. Main Outcomes and Measures: Observed and expected 90-day pretransplant mortality rates evaluated at 10-point interval PELD levels. Results: Among the 4298 patients in the full cohort (mean [SD] age, 2.5 [4.2] years; 2251 [52.4%] female; 2201 [51.2%] white), PELD scores and mortality were concordant (C statistic, 0.8387 [95% CI, 0.8191-0.8584] for the full cohort and 0.8123 [95% CI, 0.7919-0.8327] for the reduced cohort). However, the estimated 90-day mortality using the PELD score underestimated the actual probability of death by as much as 17%. Conclusions and Relevance: With use of the PELD score, the ranking of risk among children was preserved, but direct comparisons between adult and pediatric candidates were not accurate. Children with chronic liver disease who are in need of transplant may be at a disadvantage compared with adults in a similar situation.

Gray's time-varying coefficients model for posttransplant survival of pediatric liver transplant recipients with a diagnosis of cancer.

Transplantation is often the only viable treatment for pediatric patients with end-stage liver disease. Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate effects are time-invariant on right-censored failure time; however, this assumption may not always hold. Gray's piecewise constant time-varying coefficients (PC-TVC) model offers greater flexibility to capture the temporal changes of covariate effects without losing the mathematical simplicity of Cox PH model. In the present work, we examined the Cox PH and Gray PC-TVC models on the posttransplant survival analysis of 288 pediatric liver transplant patients diagnosed with cancer. We obtained potential predictors through univariable (P < 0.15) and multivariable models with forward selection (P < 0.05) for the Cox PH and Gray PC-TVC models, which coincide. While the Cox PH model provided reasonable average results in estimating covariate effects on posttransplant survival, the Gray model using piecewise constant penalized splines showed more details of how those effects change over time.