Wildlife susceptibility to infectious diseases at global scales.

Disease transmission prediction across wildlife is crucial for risk assessment of emerging infectious diseases. Susceptibility of host species to pathogens is influenced by the geographic, environmental, and phylogenetic context of the specific system under study. We used machine learning to analyze how such variables influence pathogen incidence for multihost pathogen assemblages, including one of direct transmission (coronaviruses and bats) and two vector-borne systems (West Nile Virus [WNV] and birds, and malaria and birds). Here we show that this methodology is able to provide reliable global spatial susceptibility predictions for the studied host-pathogen systems, even when using a small amount of incidence information (i.e., [Formula: see text] of information in a database). We found that avian malaria was mostly affected by environmental factors and by an interaction between phylogeny and geography, and WNV susceptibility was mostly influenced by phylogeny and by the interaction between geographic and environmental distances, whereas coronavirus susceptibility was mostly affected by geography. This approach will help to direct surveillance and field efforts providing cost-effective decisions on where to invest limited resources.

Recent advances in biomedical, biosensor and clinical measurement devices for use in humans and the potential application of these technologies for the study of physiology and disease in wild animals.

The goal of achieving enhanced diagnosis and continuous monitoring of human health has led to a vibrant, dynamic and well-funded field of research in medical sensing and biosensor technologies. The field has many sub-disciplines which focus on different aspects of sensor science; engaging engineers, chemists, biochemists and clinicians, often in interdisciplinary teams. The trends which dominate include the efforts to develop effective point of care tests and implantable/wearable technologies for early diagnosis and continuous monitoring. This review will outline the current state of the art in a number of relevant fields, including device engineering, chemistry, nanoscience and biomolecular detection, and suggest how these advances might be employed to develop effective systems for measuring physiology, detecting infection and monitoring biomarker status in wild animals. Special consideration is also given to the emerging threat of antimicrobial resistance and in the light of the current SARS-CoV-2 outbreak, zoonotic infections. Both of these areas involve significant crossover between animal and human health and are therefore well placed to seed technological developments with applicability to both human and animal health and, more generally, the reviewed technologies have significant potential to find use in the measurement of physiology in wild animals. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.