A generalized transition model for grouped longitudinal categorical data.

Transition models are an important framework that can be used to model longitudinal categorical data. They are particularly useful when the primary interest is in prediction. The available methods for this class of models are suitable for the cases in which responses are recorded individually over time. However, in many areas, it is common for categorical data to be recorded as groups, that is, different categories with a number of individuals in each. As motivation we consider a study in insect movement and another in pig behaviou. The first study was developed to understand the movement patterns of female adults of Diaphorina citri, a pest of citrus plantations. The second study investigated how hogs behaved under the influence of environmental enrichment. In both studies, the number of individuals in different response categories was observed over time. We propose a new framework for considering the time dependence in the linear predictor of a generalized logit transition model using a quantitative response, corresponding to the number of individuals in each category. We use maximum likelihood estimation and present the results of the fitted models under stationarity and non-stationarity assumptions, and use recently proposed tests to assess non-stationarity. We evaluated the performance of the proposed model using simulation studies under different scenarios, and concluded that our modeling framework represents a flexible alternative to analyze grouped longitudinal categorical data.

Intraguild predation influences oviposition behavior of blow flies (Diptera: Calliphoridae).

The objective of the present study was to determine whether blow flies (Diptera: Calliphoridae) are able to identify larvae of an intraguild predator species in the substrate and avoid laying eggs there. Blow flies oviposited in traps with different treatments: substrate only and substrate with larvae of Chrysomya albiceps (Wiedemann, 1819), Chrysomya megacephala (Fabricius, 1794), or Chrysomya putoria (Wiedemann, 1830). Ch. megacephala, Ch. putoria, and Lucilia eximia (Wiedemann, 1819) avoided laying eggs in the trap containing Ch. albiceps larvae. Cochliomyia macellaria (Fabricius, 1775) did not oviposit differently in each substrate but had overall low abundance. The prevalence of species on corpses may be influenced by the ability of the species to detect the presence of other species, mainly predators. In this sense, intraguild predation may result in misinterpretations of a crime scene and should be considered when assessing the minimum postmortem interval.

DRAG in situ barcoding reveals an increased number of HSPCs contributing to myelopoiesis with age.

Ageing is associated with changes in the cellular composition of the immune system. During ageing, hematopoietic stem and progenitor cells (HSPCs) that produce immune cells are thought to decline in their regenerative capacity. However, HSPC function has been mostly assessed using transplantation assays, and it remains unclear how HSPCs age in the native bone marrow niche. To address this issue, we present an in situ single cell lineage tracing technology to quantify the clonal composition and cell production of single cells in their native niche. Our results demonstrate that a pool of HSPCs with unequal output maintains myelopoiesis through overlapping waves of cell production throughout adult life. During ageing, the increased frequency of myeloid cells is explained by greater numbers of HSPCs contributing to myelopoiesis rather than the increased myeloid output of individual HSPCs. Strikingly, the myeloid output of HSPCs remains constant over time despite accumulating significant transcriptomic changes throughout adulthood. Together, these results show that, unlike emergency myelopoiesis post-transplantation, aged HSPCs in their native microenvironment do not functionally decline in their regenerative capacity.

Disposable face masks and reusable face coverings as non-pharmaceutical interventions (NPIs) to prevent transmission of SARS-CoV-2 variants that cause coronavirus disease (COVID-19): Role of new sustainable NPI design innovations and predictive mathematical modelling.

Best-published evidence supports the combined use of vaccines with non-pharmaceutical interventions (NPIs), to reduce the relative risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes COVID-19; this will enable a safe transition to achieving herd immunity. Albeit complex, the strategic public health goal is to bundle NPIs to keep the basic reproduction number R0 below one. However, validation of these NPIs is conducted using random clinical trials, which is challenging in a swiftly moving pandemic given the need for recruiting large participant cohort over a longitudinal analysis period. This review highlights emerging innovations for potentially improving the design, functionality and improved waste management of disposable face masks such as filtering facepiece (FFPs) respirators, medical masks, and reusable face coverings to help prevent COVID-19. It describes use of different mathematical models under varying scenarios to inform efficacy of single and combined use of NPIs as important counter-measures to break the cycle of COVID-19 infection including new SARS-CoV-2 variants. Demand for face masks during COVID-19 pandemic keeps increasing, especially for FFPs worn by medical workers. Collaborative and well-conducted randomised controlled trials across borders are required to generate robust data to inform common and consistent policies for COVID-19 and future pandemic planning and management; however, current use of systematic reviews of best available evidence can be considered to guide interim policies.

lcc: an R package to estimate the concordance correlation, Pearson correlation and accuracy over time.

BACKGROUND AND OBJECTIVE: Observational studies and experiments in medicine, pharmacology and agronomy are often concerned with assessing whether different methods/raters produce similar values over the time when measuring a quantitative variable. This article aims to describe the statistical package lcc, for are, that can be used to estimate the extent of agreement between two (or more) methods over the time, and illustrate the developed methodology using three real examples. METHODS: The longitudinal concordance correlation, longitudinal Pearson correlation, and longitudinal accuracy functions can be estimated based on fixed effects and variance components of the mixed-effects regression model. Inference is made through bootstrap confidence intervals and diagnostic can be done via plots, and statistical tests. RESULTS: The main features of the package are estimation and inference about the extent of agreement using numerical and graphical summaries. Moreover, our approach accommodates both balanced and unbalanced experimental designs or observational studies, and allows for different within-group error structures, while allowing for the inclusion of covariates in the linear predictor to control systematic variations in the response. All examples show that our methodology is flexible and can be applied to many different data types. CONCLUSIONS: The lcc package, available on the CRAN repository, proved to be a useful tool to describe the agreement between two or more methods over time, allowing the detection of changes in the extent of agreement. The inclusion of different structures for the variance-covariance matrices of random effects and residuals makes the package flexible for working with different types of databases.