Hazards Model Research Articles

Firm Characteristics and Financial Distress among Manufacturing Firms Listed at Nairobi Securities Exchange Kenya

Businesses including companies listed on stock markets strive to predict financial distress to ensure they manage the factors that could potentially lead to such distress. It is however not clear how the various factors affect financial distress particularly firm size; firm activity levels; firm financial leverage; and profitability given that these are some of the biggest determinants of the financial condition of a business. The lack of clarity results from the fact that there are numerous models of financial distress with each providing varying factors some often contradicting each other. It is therefore critical to evaluate how these affects financial distress among manufacturing firms listed at Nairobi Security Exchange (NSE). This study aims to evaluate how firm size, turnover, leverage and profitability influence financial distress as measured by the B-Ratio. This census survey with a population of 13 companies covers the period 2013 to 2022. Three companies however did not meet the data criteria and were therefore excluded from the analysis. This left 100 firm-year observations. The study utilized four theories of financial distress that include neoclassical theory of investment; liquidity preference theory; pecking order theory; and Wreckers theory of financial distress. The study used panel regression analysis to test the hypotheses that firm size, turnover, leverage and profitability have no significant influence on financial distress. Hausman model specification test revealed that the fixed effects panel regression model was the most appropriate for analysis and it was subsequently used in arriving at the inferential findings. T-test and p-value at 95% confidence interval were used in hypotheses testing. All the four hypotheses set for the study were rejected and it was concluded that size, activity, leverage and financial performance are significant determinants of financial distress. The findings reveal that whereas firm size (as shown by firm capitalization ratio), firm activity level (as shown by total asset turnover) and firm profitability (as shown by return on equity) all had a negative effect on B-ratio, financial leverage had a direct positive effect on financial distress. The study was limited to the 10 qualifying companies at the NSE and has suggested that similar studies could be expanded to non-listed companies, listed nonmanufacturing companies as well as with the use of different models such as hazard models.

Comparison of Cox and Extended Cox Models on Age at First Marriage among Nigerian Women

Cox model is widely used for analysis of factor effects on censored survival time such as age at first marriage. In most practical situations, the fundamental assumption of the proportionality of hazard in Cox model, which implies that the covariates whose effects are to be investigated have a constant impact on the hazard ratio over the time is not always feasible. For example, the values of some of the covariates for individuals may be different over time and these may cause a break-down of proportionality assumption in the hazard model. Ignoring such violation may result in misleading effects of estimates. In this study therefore, Extended Cox models have been used to analyze data on age at first marriage among Nigerian women between 2013 and 2018 waves of Nigerian Demographic and Health Surveys (NDHS). The standard Cox model as well as Extended Cox models under four distinct time functions, namely, t, t2 , log(t) and Heaviside were considered in the analysis and compared using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The standard Cox model was found to perform worst among all the models considered and Extended model with log(t) time function was best fit for the data.

A New Distribution for Modeling both Blood Cancer Data and Median Effective Dose (ED50) of Artemether-Lumefantrine against P. falciparum

In this paper, a novel distribution was proposed for modeling data on Leukemia and median effective dose (ED50) of Artemether-Lumefantrine against Plasmodium falciparum. Plasmodium falciparum or P. falciparum is one of the protozoan species that causes malaria. In the treatment of malaria, especially in sub-Saharan Africa Artemether-Lumefantrine dominates the hospitals. The ED50 (median effective dose) is the dose of a medication that produces a specific effect in 50\% of the population that takes that dose. The new distribution has three parameters that make it both flexible and tractable. The distribution is called the Gompertz-Lindley distribution. The model's hazard function behavior was presented together with the properties of the proposed distribution. The parameters were estimated using the method of maximum likelihood. From the analysis, the Gompertz-Lindley distribution is better than the competing standard distribution in the instances of the two data sets deployed.

Can atmospheric reanalysis datasets reproduce flood inundation at regional scales? A systematic analysis with ERA5 over Mahanadi River Basin, India.

The prime challenges limiting efficient flood management, especially over large regions, are concurrently related to limited hydro-meteorological observations and exorbitant economics with computational modeling. Reanalysis datasets are a valuable alternative, as they furnish relevant variables at high spatiotemporal resolutions. In recent times, ERA5 has gained significant recognition for its applications in hydrological modeling; however, its efficacy at the inundation scale needs to be understood. The advent of "global flood models" has ensured flood inundation and hazard modeling over large regions, otherwise obscure with regional models. For the first time, the present study explores the fidelity of ERA5 reanalysis at the inundation scale over the Mahanadi River basin, a severely flood-prone region in India. The biases in the discharges within ERA5 are ascertained by comparing them with station-level data at the nascent and extreme levels (i.e., 95th and 99th percentiles). Later, ERA5 is fed to LISFLOOD-FP, an acclaimed global flood model, to reenact the 2006, 2008, 2011, and 2014 flood events. Hit rates exceeding 0.8 compared to MODIS satellite imageries affirm the suitability of ERA5 in accurately capturing flood inundation. Distributed design discharges for 50yr and 100yr are derived using a set of extreme value distributions and fed to LISFLOOD-FP to derive design flood inundation and hazards in terms of both "depth" and "product of depth and velocity" of flood waters. Results derived from the study provide vital lessons for efficient land-use planning and adaptation strategies linked to flood protection and resilience.

Hazard Model with Random Treatment Time-Lag Effect

Hazard Model with Random Treatment Time-Lag Effect

Multi-institutional Characterization of Outcomes for Pediatric and Young Adult Patients With High-Risk Myxopapillary Ependymoma After Radiation Therapy

Myxopapillary ependymoma (MPE) is a rare, typically slow-growing subtype of spinal ependymomas. There are no standard guidelines for radiotherapy and long-term outcomes after radiation, particularly patterns of relapse, for pediatric and young adult (YA) patients with MPE remain under-characterized. This is an Institutional Review Board-approved multi-institutional retrospective cohort study of 60 pediatric and YA patients diagnosed with MPE and received radiotherapy between 2000-2020. Clinical and treatment characteristics, and long-term outcomes were recorded. Site(s) of progression was compared to radiation fields. Survival outcomes were analyzed using Kaplan-Meier method. Cumulative incidence of local in-field progression (CILP) after initial radiotherapy was analyzed using Gray's method with out-of-field-only progression as a competing risk. Univariate analyses were performed using Cox proportional hazard's model. The median age at radiation was 14.8 years (range: 7.1-26.5). At time of radiotherapy, 45 (75.0%) and 35 (58.3%) patients had gross residual and multifocal disease, respectively. Forty-eight (80.0%), seven (11.7%) and five (8.3%) patients received involved field radiotherapy, craniospinal irradiation, and whole spine radiation, respectively. Median follow-up from end of radiotherapy was 6.2 years (range: 0.6-21.0). Five-year overall survival, progression-free survival, and CILP were 100%, 60.8% and 4.1%, respectively. Both local recurrences were at sites of gross residual disease. Of the eighteen out-of-field first recurrences after radiotherapy, all were superior to the initial treatment field and nine had intracranial relapse. On univariate analyses, distant-only recurrence before radiation (HR: 4.00, 95% CI: 1.54-10.43, p=0.005) was significantly associated with shorter time to progression. While the risk of recurrence within the radiation field is low, pediatric and YA patients with high-risk MPE remain at risk for recurrences in the spine above the radiation field and intracranially after radiotherapy. Future prospective studies are needed to investigate the appropriate radiation field and dose based on the extent of metastases.

Advancements in Disaster Management: Insights into Risk Assessment, Mitigation, and Funding Strategies

This edition showcases a diverse range of research articles that offer valuable insights into various aspects of disaster management. The articles included in this issue address crucial topics in the field. For instance, Lendra et al. present a study on occupational safety and health risk management in the construction industry during the COVID-19 pandemic, proposing control solutions to ensure worker safety. Arrisaldi et al. focus on landslide risk assessment using Geographic Information System (GIS) in Kulon Progo, Indonesia, providing a comprehensive landslide risk map for disaster preparedness and community resilience. Indira and Manessa explore the generation of effective tsunami evacuation routes based on hazard models in Sukabumi, West Java, emphasizing the importance of revising hazard maps and identifying optimal routes to enhance the safety and preparedness of coastal communities. Irsyadillah investigates the concept of disaster capitalism and its impact on safety culture within the aviation industry. Other topics covered in this issue include spatio-temporal analysis of ground movement using unmanned aerial vehicles (UAV) photogrammetry by Amalia et al., analysis of hydraulic jumps for dam safety, examination of changes in mobility patterns and CO2 emissions during the pandemic by Fatimah et al. and Darma et al., understanding socio-ecological differences and risks faced by indigenous communities by Sunarti et al., exploring funding strategies through the Land Value Capture (LVC) scheme by Handayani et al., and conducting a bibliometric study on disaster management agencies and public policy by Kurniawati et al. These research articles significantly contribute to advancing knowledge in disaster management and provide practical insights for researchers, policymakers, and practitioners. We encourage readers to delve into these articles and participate in further discussions on the vital field of disaster management.

Seismic risk scenarios for the residential buildings in the Sabana Centro province in Colombia

Abstract. Colombia is in one of the most active seismic zones on Earth, where the Nazca, Caribbean, and South American plates converge. Approximately 83 % of the national population lives in intermediate to high seismic hazard zones, and a significant part of the country's building inventory dates from before the nation's first seismic design code (1984). At present, seismic risk scenarios are available for the major cities of the country, but there is still a need to undertake such studies in other regions. This paper presents a seismic risk scenario for the Sabana Centro province, an intermediate hazard zone located close to the country's capital. An exposure model was created combining information from the Global Earthquake Model (GEM) Foundation, surveys, and the national census. Fragility and vulnerability curves were assigned to the building types of the region. A hazard model was developed for the region and 18 earthquake scenarios with a return period of 475 years were simulated using the OpenQuake (OQ) hazard and risk assessment tool to estimate damage and economic losses. In addition, a social vulnerability index (SVI) based on demographic information was used to assess the direct economic loss in terms of replacement costs. The results show that 10 % of all buildings considered in the region would experience collapse, and 7 % would suffer severe damage. Losses account for 14 % of the total replacement cost of the buildings and represent 21 % of the annual gross domestic product (GDP) of the region.

Age-dependent risk of respiratory syncytial virus infection: A systematic review and hazard modeling from serological data.

There is no immunization campaign that currently exist for respiratory syncytial virus (RSV). Seroprevalence studies are critical for assessing epidemiological dynamics before and during an immunization program. A systematic literature review was conducted to summarize the evidence from seroprevalence studies on RSV. A systematic search of age-dependent RSV seroprevalence was conducted using the PubMed database and EMBASE. Age-dependent force of infections (FoI) and the decay rate of immunity were estimated. A mixture finite model was employed, estimating the age-dependent disease state and the antibody concentrations in susceptible and infected/recovered populations. Twenty-one studies were identified from 15 countries, with studies using ELISA being the most represented. Employing a catalytic model, the age-dependent force of infection was estimated to be the lowest in infants aged 6 months to 1 year and increased in older age groups. The proportion ever-infected/recovered was estimated to be above 90% by 3 years of age. The number of seroprevalence studies covering a broad range of ages are limited. The age-dependent FoI indicated that the risk of infection was greatest among those aged >5 years. Additional empirical data that use valid assays are required to fully describe the transmission dynamics of RSV infection.

A Lucas Critique of Mortgage Lending: Theory, Evidence, and Implications

AbstractMortgage risk assessment is based on hazard models using data on “seasoned” mortgages, endorsed in previous years. These models assume that the lender’s pricing decision has no effect on the parameters of the hazard function. This paper argues that, when indicators of creditworthiness that can be influenced by applicants have a significant effect on credit cost, applicants behave strategically to influence the information disclosed to lenders. This gives rise to a Lucas Critique in which models generally perform well but occasionally fail because applicants are able and motivated to behave strategically.

IMPACT OF LEARNING SET AND SAMPLING FOR SNOW AVALANCHE SUSCEPTIBILITY MAPPING WITH RANDOM FOREST

Abstract. Snow avalanche refers to rapid snow mass movement under the influence of gravity and is a frequently observed natural phenomenon in mountainous regions. An area affected by a snow avalanche consists of starting, track (or transition) and runout (or deposition) zones, which have different geomorphologic characteristics that need to be considered in hazard modelling. This study attempted to analyze the impact of the different zones in producing snow avalanche susceptibility maps (ASMs) with data-driven methods. The random forest (RF) method was applied to the data from Gross Spannort Mountain region (Switzerland) for this purpose. Avalanche inventories from two dates were manually delineated to separate the three zones and two RF models were trained with learning datasets; i.e. Inventory-A which includes all snow avalanche zones (original inventory), and Inventory-B with starting and track zones. The conditioning factors were defined based on the literature, data availability and study area characteristics. The trained models (Model-A with Inventory-A and Model-B with Inventory-B) were evaluated with the area under the receiver operating characteristic (ROC), precision, recall and F1 score. The results show that Model-A has AUC of 0.97, precision of 0.89, recall of 0.95 and F1 score of 0.92 and the Model-B has AUC of 0.98, precision of 0.90, recall of 0.94 and F1 score of 0.92 that indicate high prediction performances for both cases. Furthermore, feature importance values were calculated by the Mean Decrease in Impurity (MDI) method, and elevation, aspect and valley depth were found the most influencing conditioning factors.

Association of pathogen-specific clinical mastitis in the first 100 days of first lactation with productive lifetime: An observational study comparing competing risks models for death and sale with the Cox model.

The objective of this observational study was to study the association between clinical mastitis (CM) (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., cases with other treated or other not treated organisms, CM without growth) occurring in a dairy cow's first 100 days (d) of her first lactation and her total productive lifetime, ending in death or sale (for slaughter). Data were collected from 24,831 cows in 5 New York Holstein herds from 2004 to 2014. Two analytical approaches were compared. First, removals (death, sale) were treated as competing events in separate survival analyses, in proportional subdistribution hazards models. In one, death was coded as the event of interest and sale as the competing event; in another, sale was the event of interest and death the competing event. Second, traditional survival analysis (Cox proportional hazards) was conducted. In all models, the time variable was number of days from date of first calving until event (death or sale) date; if the cow was alive at study end, she was censored. Models were stratified by herd. Ten percent of cows died; 48.4 % were sold. In the competing risks analysis, E. coli and CM without growth were associated with death; the former with an increased hazard rate of death, the latter with a lower one. Streptococcus spp., Staph. aureus, Klebsiella spp., cases with other treated or untreated organisms, and CM without growth were associated with higher hazard rates of sale. The Cox proportional hazards model's hazard rates were higher than those in the competing risks model in which death was the event of interest, and resembled those in the model in which sale was the event of interest. Four additional Cox models, omitting dead or sold cows, or censoring each, were also fitted; hazard ratios were similar to the above models. Proportional subdistribution hazards models were appropriate due to competing risks (death, sale); they produce less-biased estimates. A study limitation is that while proportional subdistribution hazards models were appropriate, they have the illogical feature of keeping subjects at risk for the event of interest even after experiencing the competing event. This is, however, necessary in estimating cumulative incidence functions. Another limitation concerns pathogen variability among study farms, implying that CM decisions are farm-specific. Misclassification of 'dead' vs. 'sold' cows was also possible. Nevertheless, the findings may help in optimizing management of cows contracting specific types of CM early in productive lifetime.

Short to medium range impact based forecasting of heavy rainfall in India

There have been major advances in the last few decades in our understanding of heavy rainfall during monsoon season due to substantial progress in both observation and numerical modelling of monsoon. All these resulted in more accurate forecast of heavy rainfall in short to medium range, (upto five days) with 40% improvement in accuracy of heavy rainfall forecast in recent five years (2018-2022) as compared to previous five years. However, improvement of forecast and warning skill is not sufficient to minimize damage to lives and property. It is essential to extend to hazard forecast systems (hazard models) and then to impact and risk assessment with stakeholder interaction for risk based warning (RBW) and response action to protect lives and livelihoods Considering all these, India Meteorological Department (IMD) has introduced impact based forecast (IBF) for heavy rainfall at meteorological sub-division level since July 2013 and at district and city scale in August, 2019 in its short to medium range forecasts and nowcasts indicating the likely impact of the heavy rainfall in different sectors and required response actions. Thereafter the IBF of heavy rainfall has undergone several changes over the years. Currently, the IBF being implemented by IMD includes all the four components, viz., (i) meteorological hazards, (ii) geophysical hazards, (iii) geospatial applications and (iv) socio-economic conditions and it utilises a web-GIS based decision support system (DSS). In this study we have reviewed various approaches and stages of development of IBF of heavy rainfall in India. The success of IBF of heavy rainfall will enhance the management of critical resources like agriculture, water & power and support urban and disaster management sectors among others while reducing loss of life and property.

Tumor Volume Is a Better Prognostic Factor than Greatest Tumor Diameter in Operated Stage I-III Non–Small-Cell Lung Cancer

IntroductionThe aim of this study was to investigate the prognostic impact of tumor volume (TV, recorded from surgical specimens) on patients with stage I-III non–small-cell lung cancer (NSCLC) after complete resection. Materials and MethodsA total of 129 patients with stage I-III NSCLC diagnosed and underwent curative resection from 2007 to 2014 in our center were included in the study. Their clinico-pathological factors were retrospectively reviewed. Overall survival (OS) and disease-free survival (DFS) analyses were performed with the Kaplan-Meier method and Cox's hazard model. According to the ROC analysis, patients were divided into 2 groups (Group 1: 58 patients <30.3 cm3 and Group 2: 71 patients ≥30.3 cm3) and the OS and DFS values were compared. ResultsMedian TVs and greatest tumor diameter were 12 cm3 (0.1-30) / 3 cm (0.4-6.5) in Group 1 and 98 cm3 (30.6-1521) / 6 cm (3.5-21) in Group 2. Median OS was 53 (5-177) months in Group 1 and 38 (2-200) months in Group 2 (P < .001). DFS was similar in both group (28 [1-140] vs. 24 [1-155] months, Introduction P = .489). Kaplan-Meier curves showed significantly higher OS rates in Group 1 than Group 2 (P = .04). In multivariable analysis (TV, tumor T stage, tumor N stage, receiving adjuvant radiotherapy) showed that TV (HR: 0.293, 95% CI: 0.121-0.707, P = .006) and tumor N stage (HR: 0.013, 95% CI: 0.001-0.191, P = .02) were independent factors associated with OS. ConclusionTumor volume, not considered in the routine TNM classification, may improve prediction accuracy of overall OS in operated Stage I-III NSCLC.

Bottom-up multilevel flood hazard mapping by integrated inundation modelling in data scarce cities

With increasing urban flood risk due to urbanisation and climate change, flood hazard prediction is ever more crucial for flood risk management and emergency response. However, when sufficient high-quality data are lacking, a standard flood inundation modelling approach has significant uncertainties. Therefore, this study develops a bottom-up approach for urban flood hazard mapping at multiple levels (grid-kilometre-district), built upon the integration of grid-based flood modelling with data acquisition from open sources. This reduces the adverse effects of data scarcity and quality on hazard modelling. In the paper, we first set out an integrated approach for gridded inundation mapping in an urban basin using a hydrodynamic model supported by crowd-sourced social media data. Then, applying the model to flooding in Chengdu in August 2020, we articulate how input data bias and parameter uncertainty both affect urban inundation modelling. The results show that the choice of terrain data and the quantification of urban drainage flows significantly influence the modelled urban inundation extent, depth and duration. This indicates the potential for large variation when using urban inundation mapping merely relying on a single-scale flood hydrodynamic modelling even when supported by crowd-sourced data. The multilevel hazard mapping approach developed here presents multi-layered and comprehensive inundation mapping; thus the effects of data bias or availability are reduced and the coarser hazard mapping shows less sensitivity to the data input quality and model uncertainty, indicating relatively higher reliability at this higher spatial scale. The grid-kilometre-district three level approach provides more reliable flood hazard mapping, which can support rainstorm-induced flood management in data scarce cities.

Modelling hydrological factors from DEM using GIS

Hydrological modelling is a precondition for many scientific researches such as species distribution models, ecological models, agricultural suitability models, climatological models, hydrological models, flood and flash flood models, landslide models etc. Even the topographic control over many hydrological factors has also been studied. Over time different hydrological models have been developed and extensively used. Recently, these models have been used to prepare different types of conditional factors that are widely used in hazard modelling such as floods, flash floods, landslides etc. Quantitative analysis of the Digital Elevation Model (DEM) according to different models by engaging Geographic Information Systems (GIS) supports users to extract various types of information about landscapes where hydrological and topographic information are most important. Methods to prepare hydrological factors namely TWI, TRI, SPI, STI, TPI, stream density and distance to stream by processing DEM in GIS are discussed in this paper. These common hydrological factors are extensively used in many scientific research papers either for modelling or to measure their relationship with other environmental factors.•Hydrological factors have great importance in understanding the landscape and are widely used in scientific research, especially geo-environmental hazard mapping.•Physically based hydrological methods are engaged in ArcMap 10.5 software.•Commonly used hydrological factors are processed using freely available DEM and ArcMap 10.5 software.

The assessment of earthquake hazard in Italy: a review

We present a review of the assessment of earthquake hazard in Italy, with special reference to the relationships between hazard models and building codes. After early attempts at hazard assessment in the 19th century, the 28 December 1908, Messina Straits earthquake prompted the inception of the first national seismic legislation, passed in early 1909. Nevertheless, the official building code started to be based on a truly scientific background only after 1980, when the catastrophic Irpinia (southern Italy) earthquake forced the qualified authority to accept a science-based assessment (statistics on the earthquake catalogue data) to support the implementation of the new national seismic zonation. Later on, between 1985 and 2000, the two basic components of seismic hazard assessment, namely the earthquake record and the distribution of earthquake sources, were greatly developed through investigations carried out by the Gruppo Nazionale Difesa dai Terremoti and by the Istituto Nazionale di Geofisica. Along with the improvement of basic data, the Italian seismological community started developing a new hazard model (PS4), based on the concept of seismotectonic probabilism, aimed at supplying the Italian Government with a solid reference frame for updating the seismic zonation and building code. Nevertheless, this goal was achieved only two decades later: on 31 October 2002 a moderate-size earthquake caused the death of 27 children and a teacher in a collapsed school of southern Italy, forcing the qualified authority to take a major step of modernization for the second time in 22 years. The entire Italian territory, including areas of rare and sparse seismicity, was subdivided into four seismic zones, mainly on the basis of PS4 results. In 2004, the Italian seismological community developed MPS04, a fully updated hazard model that was initially conceived only in view of updating the seismic zonation. In 2007, MPS04 was extended to provide design spectra for a new building code, which was finally adopted in 2009, following the disastrous L’Aquila (central Italy) earthquake. The experience of the European project for seismic hazard assessment named SHARE, completed in 2013, represented a step forward and put the basis for a new project, termed MPS19, designed specifically to provide a sound basis for updating the Italian building code.

New-onset diabetes mellitus risk associated with concurrent autonomous cortisol secretion in patients with primary aldosteronism.

Concurrent autonomous cortisol secretion (ACS) in patients with primary aldosteronism (PA patients) is not uncommon. This work aimed to determine the effect of cortisol levels on incident new-onset type 2 diabetes mellitus (NODM) in PA patients. Using the prospectively designed observational TAIPAI cohort, the PA patients were grouped by cortisol level after an overnight low-dose dexamethasone suppression test (1-mg DST). Of the 476 PA patients, 387 (43.7% men; mean age 52.8 years) did not have baseline DM. After a mean follow-up of 4.3 ± 2.9 years, 32 patients (8.3%) developed NODM. The cutoff value obtained via a generalized additive model showed that a serum cortisol level ≥ 2.65 µg/dL after 1-mg DST was a risk factor for developing NODM (HR, 3.5, p = 0.031) by Cox proportional- hazards model.. In PA patients with a higher body mass index (>25 kg/m2; HR, 3.16), lower estimated glomerular filtration rate (<90 ml/min/1.73 m2; HR, 3.18), longer hypertension duration (>7 years; HR, 3.34), and higher waist-to-hip ratio (>0.9; HR, 3.07), a concomitant cortisol level ≥ 2.65 μg/dL after 1-mg DST were more likely to develop NODM. The high-cortisol group of patients with aldosterone-producing adenoma (APA) using mineralocorticoid receptor antagonist (MRA) was associated with an increased risk of NODM (HR, 5.72). Our results showed that PA patients with a concomitant cortisol level ≥ 2.65 µg/dL after 1-mg DST, independent of the aldosterone level, had a higher incidence of NODM. Such PA patients should be carefully evaluated and managed to achieve better glucose control and prevent metabolic syndrome.

The molecular features of chronic lung allograft dysfunction in lung transplant airway mucosa.

Many lung transplants fail due to chronic lung allograft dysfunction (CLAD). We recently showed that transbronchial biopsies (TBBs) from CLAD patients manifest severe parenchymal injury and dedifferentiation, distinct from time-dependent changes. The present study explored time-selective and CLAD-selective transcripts in mucosal biopsies from the third bronchial bifurcation (3BMBs), compared to those in TBBs. We used genome-wide microarray measurements in 324 3BMBs to identify CLAD-selective changes as well as time-dependent changes and develop a CLAD classifier. CLAD-selective transcripts were identified with linear models for microarray data (limma) and were used to build an ensemble of 12 classifiers to predict CLAD. Hazard models and random forests were then used to predict the risk of graft loss using the CLAD classifier, transcript sets associated with rejection, injury, and time. T cell-mediated rejection and donor-specific antibody were increased in CLAD 3BMBs but most had no rejection. Like TBBs, 3BMBs showed a time-dependent increase in transcripts expressed in inflammatory cells that was not associated with CLAD or survival. Also like TBBs, the CLAD-selective transcripts in 3BMBs reflected severe parenchymal injury and dedifferentiation, not inflammation or rejection. While 3BMBs and TBBs did not overlap in their top 20 CLAD-selective transcripts, many CLAD-selective transcripts were significantly increased in both for example LOXL1, an enzyme controlling matrix remodeling. In Cox models for one-year survival, the 3BMB CLAD-selective transcripts and CLAD classifier predicted graft loss and correlated with CLAD stage. Many 3BMB CLAD-selective transcripts were also increased by injury in kidney transplants and correlated with decreased kidney survival, including LOXL1. Mucosal and transbronchial biopsies from CLAD patients reveal a diffuse molecular injury and dedifferentiation state that impacts prognosis and correlates with the physiologic disturbances. CLAD state in lung transplants shares features with failing kidney transplants, indicating elements shared by the injury responses of distressed organs.

Comparison of Dose-Response Relationships for Two Isolates of SARS-CoV-2 in a Nonhuman Primate Model of Inhalational COVID-19.

Background: As the COVID-19 pandemic has progressed, numerous variants of SARS-CoV-2 have arisen, with several displaying increased transmissibility. Methods: The present study compared dose-response relationships and disease presentation in nonhuman primates infected with aerosols containing an isolate of the Gamma variant of SARS-CoV-2 to the results of our previous study with the earlier WA-1 isolate of SARS-CoV-2. Results: Disease in Gamma-infected animals was mild, characterized by dose-dependent fever and oronasal shedding of virus. Differences were observed in shedding in the upper respiratory tract between Gamma- and WA-1-infected animals that have the potential to influence disease transmission. Specifically, the estimated median doses for shedding of viral RNA or infectious virus in nasal swabs were approximately 10-fold lower for the Gamma variant than the WA-1 isolate. Given that the median doses for fever were similar, this suggests that there is a greater difference between the median doses for viral shedding and fever for Gamma than for WA-1 and potentially an increased range of doses for Gamma over which asymptomatic shedding and disease transmission are possible. Conclusions: These results complement those of previous studies, which suggested that differences in exposure dose may help to explain the range of clinical disease presentations observed in individuals with COVID-19, highlighting the importance of public health measures designed to limit exposure dose, such as masking and social distancing. The dose-response data provided by this study are important to inform disease transmission and hazard modeling, as well as to inform dose selection in future studies examining the efficacy of therapeutics and vaccines in animal models of inhalational COVID-19.