The potential distribution of Bacillus anthracis suitability across Uganda using INLA.

To reduce the veterinary, public health, environmental, and economic burden associated with anthrax outbreaks, it is vital to identify the spatial distribution of areas suitable for Bacillus anthracis, the causative agent of the disease. Bayesian approaches have previously been applied to estimate uncertainty around detected areas of B. anthracis suitability. However, conventional simulation-based techniques are often computationally demanding. To solve this computational problem, we use Integrated Nested Laplace Approximation (INLA) which can adjust for spatially structured random effects, to predict the suitability of B. anthracis across Uganda. We apply a Generalized Additive Model (GAM) within the INLA Bayesian framework to quantify the relationships between B. anthracis occurrence and the environment. We consolidate a national database of wildlife, livestock, and human anthrax case records across Uganda built across multiple sectors bridging human and animal partners using a One Health approach. The INLA framework successfully identified known areas of species suitability in Uganda, as well as suggested unknown hotspots across Northern, Eastern, and Central Uganda, which have not been previously identified by other niche models. The major risk factors for B. anthracis suitability were proximity to water bodies (0-0.3 km), increasing soil calcium (between 10 and 25 cmolc/kg), and elevation of 140-190 m. The sensitivity of the final model against the withheld evaluation dataset was 90% (181 out of 202 = 89.6%; rounded up to 90%). The prediction maps generated using this model can guide future anthrax prevention and surveillance plans by the relevant stakeholders in Uganda.

Integrative modelling for One Health: pattern, process and participation.

This paper argues for an integrative modelling approach for understanding zoonoses disease dynamics, combining process, pattern and participatory models. Each type of modelling provides important insights, but all are limited. Combining these in a '3P' approach offers the opportunity for a productive conversation between modelling efforts, contributing to a 'One Health' agenda. The aim is not to come up with a composite model, but seek synergies between perspectives, encouraging cross-disciplinary interactions. We illustrate our argument with cases from Africa, and in particular from our work on Ebola virus and Lassa fever virus. Combining process-based compartmental models with macroecological data offers a spatial perspective on potential disease impacts. However, without insights from the ground, the 'black box' of transmission dynamics, so crucial to model assumptions, may not be fully understood. We show how participatory modelling and ethnographic research of Ebola and Lassa fever can reveal social roles, unsafe practices, mobility and movement and temporal changes in livelihoods. Together with longer-term dynamics of change in societies and ecologies, all can be important in explaining disease transmission, and provide important complementary insights to other modelling efforts. An integrative modelling approach therefore can offer help to improve disease control efforts and public health responses.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'.

The development of critical thinking among students in baccalaureate nursing education.

Students entering nursing education present with a range of critical-thinking skills and dispositions that are affected by genetic influences, modeling by others, and formal learning experiences. The experience of higher education further contributes, positively or negatively, to the development of those skills and dispositions over time. A conceptual framework is presented as a model to explain the relationship between variables contributing to critical thinking as it is manifested in clinical judgment. A developmental model is presented to align the development of cognitive capabilities and the application of those capabilities in the subprocesses of the nursing process. Implications for nurse educators related to the understanding of critical-thinking development of students are discussed.

Calculation of diffraction effects on the average phase of an optical field.

We report on algorithms for the computation of the average phase of a beam over a detector in the near field. The basic idea is to reconstruct the optical field numerically and then use a quadrature algorithm to evaluate the quantity of interest. The various algorithms that employ discrete Fourier transform techniques for the computation of the field are described, and numerical tests that assess the accuracy of these algorithms are presented. No particular algorithm delivers the desired accuracy over the entire range of Fresnel numbers of interest, but each can produce satisfactory results within a particular range. Finally, new methods to evaluate the average phase are introduced, and their efficiency is assessed.

Hubble Space Telescope prescription retrieval.

Prescription retrieval is a technique for directly estimating optical prescription parameters from images. We apply it to estimate the value of the Hubble Space Telescope primary mirror conic constant. Our results agree with other studies that examined primary-mirror test fixtures and results. In addition they show that small aberrations exist on the planetary-camera repeater optics.