Multistate Model Research Articles

Frailty transitions and associated factors in older cancer survivors in the USA: using a multi-state modeling.

Frailty is a major concern in the aging cancer population. It can progress to severe frailty or death or improve to pre-frail or non-frail states. However, frailty transitions in older cancer survivors are not well understood. This study aimed to explore frailty transitions and associated factors in older cancer survivors. We analyzed data from the National Health and Aging Trends Study (NHATS) in 2017-2022, focusing on older adults aged ≥ 65 who have been diagnosed with cancer. Frailty was assessed annually using the Fried Frailty Phenotype. Multi-state Markov models were used to explore transitions between frailty states (non-frail, pre-frail, frail, and death) and examine the association with sociodemographic factors, comorbidities, and inflammatory biomarkers (IL-6 and CRP). Among 1219 survivors, 25.27% were non-frail, 52.34% pre-frail, and 22.40% frail at baseline. Over 5years, there were 1396 transitions: 950 (68.05%) progressed or deceased, and 446 (31.95%) reversed. Pre-frail individuals transitioned to frailty slightly more than they reversed to non-frailty (0.25 vs. 0.21). Frail individuals were more likely to decease than to reverse (0.30 vs. 0.28). Factors associated with frailty progression included older age, lower education, more comorbidities, and higher IL-6 and CRP levels. Being female and obese were protective against the frailty-to-death transition. The results showed dynamic frailty transitions in older cancer survivors and identified key sociodemographic and physiological factors. These findings can guide targeted interventions, highlighting the importance of early identification and tailored approaches to prevent frailty progression in older cancer survivors.

Competing risks multi-state model for time-to-event data analysis of HIV/AIDS: a retrospective cohort national datasets, Ethiopia

IntroductionTuberculosis (TB) remains the most common opportunistic infection and leading cause of death among individuals living with HIV/AIDS in Ethiopia. Its significant impact on morbidity and mortality underscores the crucial link between these two diseases. While the advent of antiretroviral therapy (ART) has led to a dramatic decline in mortality rates among HIV/AIDS patients, TB continues to pose a substantial threat. This study aims to estimate the probability of death due to TB among HIV/AIDS patients on ART, considering the presence of various competing risks, including diarrhea, other infections, and unknown/unspecified causes. Also we have assessed the effects of prognostic factors on HIV/AIDS cause specific deaths, compared with the death from other competing risks, and exploring leading cause of death among HIV/AIDS patients on Antiretroviral Therapy.MethodsData from a retrospective research examining the effectiveness of antiretroviral therapy (ART) in Ethiopia were used in this investigation. The data came from medical records of patients who were part of the national ART program. A total of 39,590 records were gathered between October 2019 and March 2020 from all regions of Ethiopia as well as the administration cities of Addis Ababa and Dire Dawa. The study facilities were grouped using a multi-stage sample technique and simple random selection was used to select health facility and a person record from medical records. In the presence of the competing causes of death, Cause specific hazard, subdistribution hazard model and flexible parametric proportional hazard model have been used to assess the effect of covariates on the risk of death, with the cmprisk package in R4.3.2 software.ResultsOut of the total 1212 deaths, 542(44.7%) died competing with other opportunistic infection (TE-Esophageal Candidiasis, TO-oral, CT-CNS Toxoplasmosis, CM-Crypotococcal Meningitis…), 421 (34.7%) died due to tuberculosis and the remaining death were unknown/Not specified infection 222(18.3%) and diarrhea 27(2.2%). Rates of mortality caused by tuberculosis, competing with other opportunistic infection, diarrhea and unknown/Not specified were 3.5, 4.5, 0.2 and 1.8 per 1000 person-months, respectively. Having a higher CD4 count at diagnosis, responding to combination antiretroviral treatment (cART) six months after start, and having prophylactic treatment for pneumocystis pneumonia (PCP) decreased the risk of tuberculosis, other opportunistic infections, and unidentified and diarrheal causes of death. However, older age, late HIV.AIDS diagnosis, and the last HIV/AIDS WHO clinical stages increased the hazard of tuberculosis and other opportunistic disease mortality. Additionally, male gender, older age and last HIV clinical stages increased the mortality HIV/AIDS patients.ConclusionThe findings of this study demonstrated that TB, an opportunistic infection, was the primary cause of death in HIV/AIDS patients, despite the presence of several competing risks, such as diarrhea, other infections, and an undetermined or unclear cause. It's important to use effective techniques to quickly detect those who have HIV or AIDS and provide them with care and treatment to increase their chances of surviving.

Camera trapping of forest mammals in Bükk Mountain, Hungary

AbstractThe link between large- and middle-sized mammals in forest habitat is understudied in Central Europe; meanwhile these animals could have important effects on their habitats. In our study, we analysed camera trapping data obtained from May 2015 to September 2021 on 29 different sites in a temperate forest at the Bükk Mountain, Hungary. We investigated the temporal activity of ungulates (red deer, roe deer, wild boar) and predators (red fox and grey wolf), together with their response to human disturbance. We calculated temporal overlap value (Δ4) and occurrence dynamics with multi-state modelling (msm). The results suggest that human activity was higher at daytime, while the mammals were more active at night. Multi-state modelling (msm) grouped animals and humans separately. Ungulates chose nighttime, when predators were also active, while they avoided daytime and human disturbance. Grey wolf were mostly co-occurred with its main food source, the red deer. Red fox overlapped the most with roe deer, suggesting that fox prey upon deer fawns. We found that human disturbance has a significant impact on the activity of forest mammals, whereas the expected avoidance of predators by ungulates does not appear to be evident. To better understand the effect of prey–predator behavioural responses in the presence of human disturbance, more field studies are needed in the region.

A windowed mean trajectory approximation for condensed phase dynamics.

We propose a trajectory-based quasi-classical method for approximating dynamics in condensed phase systems. Building upon the previously developed optimized mean trajectory approximation that has been used to compute linear and nonlinear spectra, we borrow some ideas from filtering trajectory methods to obtain a novel semiclassical method for the dynamical propagation of density matrices. This new approximation is tested rigorously against standard multistate electronic models, spin-boson models, and models of the Fenna-Matthews-Olson complex. For dissipative systems, the current method is significantly better or as good as many other semiclassical methods available, especially at low temperatures and for off-diagonal density matrix elements, whereas for scattering models, the current method bears similar limitations as mean-field propagation schemes. All results are tested against the numerically exact hierarchical equations of motion method. The new method shows excellent agreement across various parameter regimes with numerically exact results, highlighting the robustness and accuracy of our approach.

Modeling Disability-Free Life Expectancy With Duration Dependence: A Research Note on the Bias in the Markov Assumption.

Demographic studies on healthy life expectancy often rely on the Markov assumption, which fails to consider the duration of exposure to risk. To address this limitation, models like the duration-dependent multistate life table (DDMSLT) have been developed. However, these models cannot be directly applied to left-censored survey data, as they require knowledge of the time spent in the initial state, which is rarely known because of survey design. This research note presents a flexible approach for utilizing this type of survey data within the DDMSLT framework to estimate multistate life expectancies. The approach involves partially dropping left-censored observations and truncating the duration length after which duration dependence is assumed to be minimal. Utilizing the U.S. Health and Retirement Study, we apply this approach to compute disability-free/healthy life expectancy (HLE) among older adults in the United States and compare duration-dependent models to the typical multistate model with the Markov assumption. Findings suggest that while duration dependence is present in transition probabilities, its effect on HLE is averaged out. As a result, the bias in this case is minimal, and the Markov assumption provides a plausible and parsimonious estimate of HLE.

Weighted reverse counting process (WRCP): A novel approach to quantify the overall treatment effect with multiple time-to-event outcomes by adaptive weighting.

In a longitudinal randomized study where multiple time-to-event outcomes are collected, the overall treatment effect may be quantified by a composite endpoint defined as the time to the first occurrence of any of the selected events including death. The reverse counting process (RCP) was recently proposed to extend the restricted mean survival time (RMST) approach with an advantage of utilizing observations of events beyond the "first-occurrence" endpoint. However, the interpretation may be questionable because RCP treats all events equally without considering their different associations with the overall survival. In this work, we propose a novel approach, the weighted reverse counting process (WRCP), to construct a weighted composite endpoint to evaluate the overall treatment effect. A multi-state transition model is used to model the association between events, and an adaptive weighting algorithm is developed to determine the weight for individual endpoints based on the association between the nonfatal endpoints and death using the trial data. Simulation studies are presented to compare the performance of WRCP with RCP, log-rank test and RMST approach. The results show that WRCP is a powerful and robust method to detect the overall treatment effect while controlling the clinically false positive rate well across different simulation scenarios.

Individual claims reserving using the Aalen–Johansen estimator

Abstract We propose an individual claims reserving model based on the conditional Aalen–Johansen estimator, as developed in Bladt and Furrer ((2023a) arXiv:2303.02119.). In our approach, we formulate a multi-state problem, where the underlying variable is the individual claim size, rather than time. The states in this model represent development periods, and we estimate the cumulative density function of individual claim sizes using the conditional Aalen–Johansen method as transition probabilities to an absorbing state. Our methodology reinterprets the concept of multi-state models and offers a strategy for modeling the complete curve of individual claim sizes. To illustrate our approach, we apply our model to both simulated and real datasets. Having access to the entire dataset enables us to support the use of our approach by comparing the predicted total final cost with the actual amount, as well as evaluating it in terms of the continuously ranked probability score.

Long-term tagging reveals variable escapement of stocked Muskellunge among four Ohio reservoirs: Consequences for managing reservoir fisheries

Muskellunge Esox masquinongy are stocked by the Ohio Department of Natural Resources, Division of Wildlife (ODNR-DOW) into nine reservoirs to create trophy fisheries. Escapement is recognized as a potential impediment to maintaining quality fisheries in these reservoirs. We evaluated the escapement of Muskellunge at four reservoirs using mark-recapture methods during 2013–2022. At each reservoir, all juvenile Muskellunge (254–305 mm) stocked during 2013–2018 were implanted with passive-integrated-transponder (PIT) tags prior to release. In addition, adult mark-recapture sampling events were conducted by the ODNR-DOW during 2019–2022 to check for tagged fish and implant untagged fish. Muskellunge anglers were also outfitted with handheld PIT readers to scan and report tagged fish during the study. Escapement was monitored continuously with PIT tag detection systems installed within dam spillways. We used multi-state (in-reservoir vs escaped) mark-recapture models to estimate annual escapement for juvenile (≤ age 1) and adult Muskellunge. A total of 51,826 fish were tagged (51,052 juveniles, 774 adults), resulting in 3428 detections (2316 individuals). The number of Muskellunge escaping varied widely among reservoirs (0–481). Most escapement (85 %) occurred during the spring (March–May). Nearly all (96 %) known age fish that escaped were age 3 or greater. Modelling revealed that annual probability of juvenile escapement (≤ 0.02) was likely inconsequential at all reservoirs. However, adult escapement was highly variable among reservoirs (mean = 0–0.34). Escapement was lowest at reservoirs where water levels are managed via offshore sluice-gate tower structures, and greatest at locations where surface water is discharged from along-shore structures (i.e., crest gates and unregulated spillway). Where escapement occurred, there was a negative relationship between the annual probability of escapement and fishing success. Results will be useful for informing stocking strategies, mitigating fish loss, and managing fishery expectations.

A Multistate Model Incorporating Relative Survival Extrapolation and Mixed Time Scales for Health Technology Assessment.

Multistate models have been widely applied in health technology assessment. However, extrapolating survival in a multistate model setting presents challenges in terms of precision and bias. In this article, we develop an individual-level continuous-time multistate model that integrates relative survival extrapolation and mixed time scales. We illustrate our proposed model using an illness-death model. We model the transition rates using flexible parametric models. We update the hesim package and the microsimulation package in R to simulate event times from models with mixed time scales. This feature allows us to incorporate relative survival extrapolation in a multistate setting. We compare several multistate settings with different parametric models (standard vs. flexible parametric models), and survival frameworks (all-cause vs. relative survival framework) using a previous clinical trial as an illustrative example. Our proposed approach allows relative survival extrapolation to be carried out in a multistate model. In the example case study, the results agreed better with the observed data than did the commonly applied approach using standard parametric models within an all-cause survival framework. We introduce a multistate model that uses flexible parametric models and integrates relative survival extrapolation with mixed time scales. It provides an alternative to combine short-term trial data with long-term external data within a multistate model context in health technology assessment.

Effects of sodium-glucose cotransporter-2 inhibitors on chronic kidney disease progression: a multi-state survival model

BackgroundCurrent guidelines recommend good glycemic control in patients with type 2 diabetes (T2D) to limit the progression of associated complications with combination therapies. This study aimed to compare the rate of chronic kidney disease (CKD) progression between patients who did or did not receive sodium-glucose cotransporter-2 inhibitors (SGLT2i) using a multistate model with two intermediate states (i.e., CKD stage 4 (CKD4) and 5 (CKD5)) and one absorbing state (i.e., death).MethodsData from patients with T2D and CKD stage 3 (CKD3) were retrieved for analysis. Patients treated with SGLT2i were matched 1:2 by prescription date with non-SGLT2i patients. The multistate model was constructed from Cox survival regression models specific to each transition stage. Cumulative failure and transition probabilities were estimated from bootstrapping.ResultsData from 6582 patients (2194 and 4388 patients in the SGLT2i and non-SGLT2i groups, respectively) were analyzed. At 10-year follow-up, patients in the SGLT2i group were more likely to remain at CKD3 compared to the non-SGLT2i group: 82.3% (95% CI 79.9%, 84.6%) vs 60.4% (57.6%, 63.4%). Transition probabilities to CKD4, CKD5, and death were lower in the SGLT2i group than non-SGLT2i group: 11.3% (9.5%, 13.3%) vs 19.8% (17.4%, 22.2%), 2.4% (1.5%, 3.4%) vs 7.4% (5.8%, 9.0%), and 4.1% (2.9%, 5.3%) vs 12.4% (10.3%, 14.6%), respectively.ConclusionSGLT2i may delay the decline in renal function and slow CKD progression compared to standard care without SGLT2i.

The joint distribution of years lived in good and poor health

BackgroundIncidence-based multistate models of population health are commonly applied to calculate state expectancies, such as a healthy life expectancy (HLE), or unhealthy life expectancy (UHE). These models also allow the computation of other summary indices, such as the distributions of healthy or unhealthy lifespans.ObjectiveWe aim to show how a multistate health model implies a multistate death distribution, giving joint information on years lived in good and poor health. We also propose three aggregate indices of joint health and mortality inequality.MethodsWe propose a double-accounting approach to increment-decrement life table methods to intuitively derive a multistate health distribution over age and cumulative duration spent in each state. We then define a variety of summary lifespan inequality indices based on different distance metrics, namely Euclidean, Chebyshev, and Manhattan distances.ResultsWe apply the method to multistate transition probabilities between health states based on the activities of daily living index for Italian women from the Survey of Health, Ageing and Retirement in Europe in 2015-2017. We demonstrate the added value of accounting for joint years lived in health states in multistate models for our understanding of the period health and mortality conditions from the perspective of health-specific lifespans of individuals.ConclusionsMultivariate state distributions and summary indices derived from them give a holistic representation of population health inequality. We offer selected summary indices of the multivariate distribution with different demographic interpretations from the measures derived from univariate distributions. Although more theoretical and methodological work is required to motivate a single comprehensive population health inequality index, this direction is a promising path for a better understanding of population health dynamics and relationships between univariate statistics.

Understanding demographic events and migration patterns in two urban slums of Nairobi City in Kenya

Understanding the dynamics of movements between different demographic events is essential for informing effective population management strategies. This study aims to characterize the trajectories of demographic and other vital events within the Nairobi Urban Health and Demographic Surveillance System (NUHDSS). Thus, it intends to unravel patterns and trends that can guide the development of targeted policies and interventions to address the population’s evolving needs. Using a continuous-time homogeneous multi-state Markov model, longitudinal data from 223,350 individuals in Korogocho and Viwandani urban slums, we study the enumeration, births, deaths, and migrations among urban poor in Nairobi, shedding light on population dynamics and movements over time, disaggregated by gender. Findings indicate a positive net migration in population per thousand in 2002, dropping in 2004, with Viwandani consistently showing higher birth rates than Korogocho. Males generally have higher death rates than females. Females from Viwandani are 39.0% more likely to exit after enumeration compared to Korogocho, while males are 35.6% more likely to move from enumeration to exit compared to males from Korogocho. Both genders from Viwandani have a decreased likelihood of moving from birth to death compared to Korogocho. Our findings provide unique insights into migration in urban Kenya, the frequency and movement to different demographic events and any gender differences that warrant strategic policies for effective population and health planning in Africa. These findings can inform the design of effective health interventions that are often affected by migration and population growth.

Cost-utility of cochlear implantation in single-sided deafness and asymmetric hearing loss: results of a randomized controlled trial.

To determine the Incremental Cost-Utility Ratio (ICUR) of cochlear implantation in the treatment of adult patients with single-sided deafness (SSD) and asymmetric hearing loss (AHL). This prospective multicenter pragmatic study including a randomized controlled trial (RCT) enrolled 155 subjects with SSD or AHL. Subjects chose a treatment option between: abstention, Contralateral Routing Of the Signal hearing aids, Bone Conduction Device or Cochlear Implant (CI). Participants who opted for CI were then randomized between two arms: "immediate CI" where the cochlear implantation was performed within one month and "initial observation" where subjects were first observed. The ICUR of CI was determined at 6 months follow-up by comparing the two arms. Utility was measured using EuroQoL- 5 dimensions (EQ-5D), to calculate the gain in Quality-Adjusted Life Years (QALY). Individual costs were extracted from the French National Health Insurance database. A Markovian MultiState (MMS) model assessed the ICUR evolution over the lifetime horizon. Among the 155 included participants, 51 opted for a CI and were randomized. For a 6 months follow-up period, the ICUR was €422,279/QALY gained after CI. Using the MMS model, the ICUR of CI decreased to €57,561/QALY at 10 years follow-up, €38,006/QALY at 20 years, and dropped to €26,715 at 50 years. In the participants with severe tinnitus, mean ICUR was €31,105/QALY at 10 years. CI can be considered as an efficient treatment in SSD and AHL from 20 years follow-up in the global population, and before 10 years follow-up in patients with severe associated tinnitus.

Evolution of institutional long-term care costs based on health factors

As many developed countries face the challenges of an aging population, the need to efficiently plan and finance long-term care (LTC) becomes increasingly important. Understanding the dynamics of care requirements and their associated costs is essential for sustainable healthcare systems. In this study, we employ a multi-state Markov model to analyze the transitions between care states of elderly individuals within institutional LTC in the canton of Geneva, Switzerland. Utilizing a comprehensive dataset of 21494 elderly residents, we grouped care levels into four broader categories reflecting the range from quasi-autonomy to severe dependency. Our model considers fixed covariates at admission, such as demographic details, medical diagnoses, and levels of dependence, to forecast transitions and associated costs. The main results illustrate significant variations in care trajectories and LTC costs across different health profiles, notably influenced by gender and initial care state. Females generally require longer periods with less intensive care, while conditions like severe and nervous diseases show quicker progression to more intensive care and higher initial costs. These transitions and expected length of stay in each state directly impact LTC costs, highlighting the necessity of advanced strategies to manage the financial burden. Our findings offer insights that can be utilized to optimize LTC services in response to the specific needs of institutionalized elderly people. These findings can be applied to enhance healthcare planning, the preparedness of infrastructure, and the design of insurance products.

Two-layer multi-state SPH modelling of momentum growth and its feedback in viscous debris flow on wet bed sediment

Flow-momentum growth and resultant feedback from bed-sediment entrainment significantly influence the mobility of debris flows and valley topography. Existing models inadequately capture the mass and momentum growth regulated by scale-sensitive, time-dependent pore water pressure in erodible beds, which exhibit pronounced anisotropy and nonlinearity. In this study, we propose a three-dimensional, two-layer, multi-state smooth particle hydrodynamics (TLMS-SPH) model to assess the flow-momentum growth of debris flows on wet beds. Herein, an enhanced Drucker-Prager (DP) yield criterion is integrated into the Herschel-Bulkley-Papanastasiou (HBP) rheology to mitigate particle collapse induced by gravitational perturbations in steep terrains. Particularly, an efficient hydro-poro-mechanics-based pore water pressure algorithm is presented and embedded in the SPH scheme to simulate the pore pressure response. To address the size effect, we rigorously tested the method through a series of full-scale, well-documented entrainment experiments. The results demonstrate that the model effectively captures and reproduces the complex dynamics of flow-momentum growth, manifesting in erosion-induced excessive volume and mobility changes. Our method establishes a clear link between volumetric water content and pore pressure response, further underscoring its capability to delineate levee-channel and deposition morphology. This study represents the first attempt to model debris flow on beds of varying wetness from a particulate perspective.

Multistate Markov chain modeling for child undernutrition transitions in Ethiopia: a longitudinal data analysis, 2002–2016

BackgroundThe use of the multistate Markov chain model is a valuable tool for studying child undernutrition. This allows us to examine the trends of children's transitions from one state to multiple states of undernutrition.ObjectivesIn this study, our objective was to estimate the median duration for a child to first transition from one state of undernutrition to another as well as their first recurrence of undernutrition and also to analyze the typical duration of undernourishment. This involves understanding the central tendency of these transitions and durations in the context of longitudinal data.MethodsWe used a longitudinal dataset from the Young Lives cohort study (YLCS), which included approximately 1997 Ethiopian children aged 1–15 years. These children were selected from five regions and followed through five survey rounds between 2002 and 2016. The surveys provide comprehensive health and nutrition data and are designed to assess childhood poverty. To analyze this dataset, we employed a Markov chain regression model. The dataset constitutes a cohort with repeated measurements, allowing us to track the transitions of individual children across different states of undernutrition over time.ResultsThe findings of our study indicate that 46% of children experienced concurrent underweight, stunting, and wasting (referred to as USW). The prevalence of underweight and stunted concurrent condition (US) was 18.7% at baseline, higher among males. The incidence density of undernutrition was calculated at 22.5% per year. On average, it took 3.02 months for a child in a wasting state to transition back to a normal state for the first time, followed by approximately 3.05 months for stunting and 3.89 months for underweight. It is noteworthy that the median duration of undernourishment among children in the US (underweight and stunted concurrently) state was 48.8 months, whereas those concurrently underweight and wasting experienced a median of 45.4 months in this state. Additionally, rural children (HR = 1.75; 95% CI: 1.53–1.97), those with illiterate fathers (HR = 1.50; 95% CI: 1.38–1.62) and mothers (HR = 1.45; 95% CI: 1.02–3.29), and those in households lacking safe drinking water (HR = 1.70; 95% CI: 1.26–2.14) or access to cooking fuel (HR = 1.95; 95% CI: 1.75–2.17) exhibited a higher risk of undernutrition and a slower recovery rate.ConclusionsThis study revealed that rural children, especially those with illiterate parents and households lacking safe drinking water but cooking fuels, face an increased risk of undernutrition and slower recovery.

Temporal sequence of incident mild cognitive impairment, incident parkinsonism, and risk of death in unimpaired community-dwelling older adults.

Mild cognitive impairment (MCI) and parkinsonism affect many older adults. The objective of this study was to determine the sequence of their occurrence and associated risk of death. 1,255 community-dwelling unimpaired participants from two epidemiological cohorts were examined annually. MCI was based on neuropsychological testing, and parkinsonism was based on the motor portion of the modified Unified Parkinson's Disease Rating Scale. A multi-state Cox proportional hazards model simultaneously examined incidences of MCI, parkinsonism, and death. Average age at baseline was 76.5 years (SD = 7.2) and 73% were female. Incident MCI occurred almost as commonly as incident parkinsonism, yet compared to no impairment, risk of death was higher for MCI (HR = 1.82, 95%CI=1.34, 2.47), but it was not different for parkinsonism (HR = 1.29; 95%CI = 0.95, 1.75). Risk of death for participants with incident MCI who progressed to parkinsonism (40%) was not significantly different from those with MCI alone (HR = 1.25, 95%CI = 0.93, 1.69). However, risk of death for participants with incident parkinsonism who progressed to MCI (51%) was significantly higher than those who did not progress (HR = 1.67, 95%CI = 1.27, 2.18), indicating that risk of death is highest with incidence of MCI. The varied patterns of sequential occurrence of cognitive and motor impairment and associated risk of death suggests much greater heterogeneity than previously recognized. Further work is needed to determine the biology underlying the temporal evolution of these phenotypes, and if identification of the various subtypes improves risk stratification.

Reduced density matrix dynamics in multistate harmonic models via time-convolution and time-convolutionless quantum master equations with quantum-mechanical and semiclassical kernels.

In this work, we explore the electronic reduced density matrix (RDM) dynamics using time-convolution (TC) and time-convolutionless (TCL) quantum master equations (QMEs) that are based on perturbative electronic couplings within the framework of multistate harmonic (MSH) models. The MSH model Hamiltonian consistently incorporates the electronic-vibrational correlations between all pairs of states by satisfying the pairwise reorganization energies directly obtained from all-atom simulations, representing the globally heterogeneous environments that couple to the multiple states differently. We derive the exact quantum-mechanical and a hierarchy of semiclassical approximate expressions for the kernels in TC and TCL QMEs that project the full RDM for general shifted harmonic systems, including the MSH model. These QMEs are applied to simulate RDM dynamics of photoinduced charge transfer (PICT) in organic photovoltaic carotenoid-porphyrin-fullerene triad solvated in tetrahydrofuran solution and the excitation energy transfer (EET) dynamics in photosynthetic Fenna-Matthews-Olson complexes from C. tepidum and P. aestuarii. Our results show that while both TC and TCL QMEs capture similar phenomena in PICT and EET processes, TC QME generally provides more accurate results than TCL QME, particularly in the initial oscillation of EET population dynamics. This study highlights the effectiveness of the TC and TCL QMEs in modeling RDM dynamics of nonadiabatic processes, offering insights for realistic condensed phase systems.

Impact of Respiratory Syncytial Virus (RSV) in Adults 60 Years and Older in Spain.

Background/Objectives: Respiratory illnesses frequently lead to hospitalization in adults aged 60 and older, especially due to respiratory viral infectious (RVI). This study investigates hospitalization patterns and characteristics of RVI at HM Hospitals from October 2023 to March 2024; Methods: We retrospectively explored hospitalizations of patients aged 60 years and older with RVIs, gathering data on demographics, clinical profiles, comorbidities, and treatments. Outcomes included hospitalization, ICU admissions, and mortality, and independent factors associated with outcomes were identified using a multi-state model; Results: From October 2023 to March 2024, from a total of 3258 hospitalizations, 1933 (59.3%) were identified as positive for RVIs. Overall, SARS-CoV-2 was the most prevalent (52.6%), followed by influenza (32.7%), and RSV (11.8%). Most RVI involved single infections (88.2%). Hospitalization rates increased with age for SARS-CoV-2 (333.4 [95% CI: 295.0-375.2] to 651.6 [95% CI: 532.1-788.4]), influenza (169.8 [95% CI: 142.6-200.7] to 518.6 [95% CI: 412.1-643.1]), and RSV (69.2 [95% CI: 52.2-90.0] to 246.0 [95% CI: 173.8-337.5]), with SARS-CoV-2 showing the highest rate, followed by influenza and RSV. In the multi-state model, RSV infection significantly increased ICU admission risk (HR: 2.1, 95%, p = 0.037). Age on admission (HR: 1.1, 95%, p < 0.001) and Charlson score (HR: 1.4, 95%, p = 0.001) were associated with transitioning from admission to death. ICU to death risks included age at admission (HR: 1.7, 95%, p < 0.001); Conclusions: RVI in adults 60 years and older are associated with high hospitalization and mortality rates, primarily driven by influenza and SARS-CoV-2, followed by RSV. Age and comorbidities significantly impact disease severity, emphasizing the need for targeted prevention and management strategies for RSV in this vulnerable population.

Joint association of air pollutants on cardiometabolic multimorbidity

We estimated the association between combined exposure to air pollutants and the development of cardiometabolic multimorbidity (CM) and all-cause mortality. An air pollution score was calculated to determine the combined exposure to five air pollutants. CM was defined as the instance of at least two types of diseases. A genetic risk score (GRS) was calculated for each individual. A multistate regression model was used to investigate the effect of the combined associations of air pollutants on each stage of CM progression. After multivariable adjustment, the air pollution score was related with greater susceptibility of CM and all-cause mortality, and those with a high GRS for cardiovascular disease (CVD) or coronary heart disease (CHD) and a high air pollution score had a greater susceptibility of incident CM and all-cause mortality. The multistate model revealed that the greater air pollution score was connected with the susceptibility of progressing from disease-free baseline to having one cardiometabolic disease, and next to CM, and eventually to death. Combined exposure to five air pollutants were related with greater susceptibility of CM and all-cause mortality in a dose-dependent style and is related with the progression of CM and with all-cause mortality.