Accommodating informative dropout and death: a joint modelling approach for longitudinal and semi-competing risks data.

Both dropout and death can truncate observation of a longitudinal outcome. Since extrapolation beyond death is often not appropriate, it is desirable to obtain the longitudinal outcome profile of a population given being alive. We propose a new likelihood-based approach to accommodating informative dropout and death by jointly modelling the longitudinal outcome and semi-competing event times of dropout and death, with an important feature that the conditional longitudinal profile of being alive can be conveniently obtained in a closed form. We use proposed methods to estimate different longitudinal profiles of CD4 count for patients from the HIV Epidemiology Research Study

Plug-and-play inference for disease dynamics: measles in large and small populations as a case study

Statistical inference for mechanistic models of partially observed dynamic systems is an active area of research. Most existing inference methods place substantial restrictions upon the form of models that can be fitted and hence upon the nature of the scientific hypotheses that can be entertained and the data that can be used to evaluate them. In contrast, the so-called plug-and-play methods require only simulations from a model and are thus free of such restrictions. We show the utility of the plug-and-play approach in the context of an investigation of measles transmission dynamics. Our novel methodology enables us to ask and answer questions that previous analyses have been unable to address. Specifically, we demonstrate that plug-and-play methods permit the development of a modelling and inference framework applicable to data from both large and small populations. We thereby obtain novel insights into the nature of heterogeneity in mixing and comment on the importance of including extra-demographic stochasticity as a means of dealing with environmental stochasticity and model misspecification. Our approach is readily applicable to many other epidemiological and ecological systems

Evaluating consumptive and nonconsumptive predator effects on prey density using field time‐series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time‐series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor can they provide parameters for predictive models. State‐space models (SSMs) applied to time‐series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in an SSM framework to seasonal time series (1994–2012) using a recently developed, maximum‐likelihood–based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g., nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios, such as climate change.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148243/1/ecy2583-sup-0001-AppendixS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148243/2/ecy2583_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148243/3/ecy2583.pd

Remediation of the protein data bank archive

The Worldwide Protein Data Bank (wwPDB; wwpdb.org) is the international collaboration that manages the deposition, processing and distribution of the PDB archive. The online PDB archive at ftp://ftp.wwpdb.org is the repository for the coordinates and related information for more than 47 000 structures, including proteins, nucleic acids and large macromolecular complexes that have been determined using X-ray crystallography, NMR and electron microscopy techniques. The members of the wwPDB–RCSB PDB (USA), MSD-EBI (Europe), PDBj (Japan) and BMRB (USA)–have remediated this archive to address inconsistencies that have been introduced over the years. The scope and methods used in this project are presented

Ecological Complex Systems

Main aim of this topical issue is to report recent advances in noisy nonequilibrium processes useful to describe the dynamics of ecological systems and to address the mechanisms of spatio-temporal pattern formation in ecology both from the experimental and theoretical points of view. This is in order to understand the dynamical behaviour of ecological complex systems through the interplay between nonlinearity, noise, random and periodic environmental interactions. Discovering the microscopic rules and the local interactions which lead to the emergence of specific global patterns or global dynamical behaviour and the noises role in the nonlinear dynamics is an important, key aspect to understand and then to model ecological complex systems.Comment: 13 pages, Editorial of a topical issue on Ecological Complex System to appear in EPJ B, Vol. 65 (2008

Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing

Planning southern Iraq: placing the progressive theories of Max Lock in Um Qasr, Margil, and Basra in the context of Iraqi national development, 1954–1956

Between 1954 and 1956, the architect, educator, and planner, Max Lock (1909–1988) produced a trilogy of plans to modernize the historical city of Basra and create new areas at Margil and Um Qasr in the south of Iraq. The New Basrah Plan was heavily inspired by the works of Patrick Geddes and aligned with contemporaries such as Lewis Mumford, Lock’s planning was progressive in scope and looked to differ from the planning of post-war principles in Britain through his notions of ‘civic surgery’. Contrary to this, his plans for Um Qasr and Margil focussed on infrastructure and the creation of more industrial areas not prioritizing people and place as highly as he did in the New Basrah Plan. Lock’s ‘Civic Surgery’ offered an alternative to mainstream thought by attempting to create usable, humanistic spaces, which hampered by politics and legislation, resulted in the plan’s shelving and were contradicted by his other works’ philosophies. New retrospective analysis of his underappreciated career reveals the complexities of his planning which this article demonstrates through the ‘failure’ of the New Basrah Plan and his plans at Um Qasr and Margil