Recent decades have seen substantial expansions in the global air travel network and rapid increases in traffic volumes. The effects of this are well studied in terms of the spread of directly transmitted infections, but the role of air travel in the movement of vector-borne diseases is less well understood. Increasingly however, wider reaching surveillance for vector-borne diseases and our improving abilities to map the distributions of vectors and the diseases they carry, are providing opportunities to better our understanding of the impact of increasing air travel. Here we examine global trends in the continued expansion of air transport and its impact upon epidemiology. Novel malaria and chikungunya examples are presented, detailing how geospatial data in combination with information on air traffic can be used to predict the risks of vector-borne disease importation and establishment. Finally, we describe the development of an online tool, the Vector-Borne Disease Airline Importation Risk (VBD-Air) tool, which brings together spatial data on air traffic and vector-borne disease distributions to quantify the seasonally changing risks for importation to non-endemic regions. Such a framework provides the first steps towards an ultimate goal of adaptive management based on near real time flight data and vector-borne disease surveillance.

In the last decade, mobile technology offered new opportunities and challenges in animal health surveillance. It began with the use of basic mobile phones and short message service (SMS) for disease reporting, and the development of smartphones and other mobile tools has expanded the possibilities for data collection. These tools assist in the collection of data as well as geo-referenced mapping of diseases, and mapping, visualization and identification of vectors such as ticks. In this article we share our findings about new technologies in the domain of animal health surveillance, based on several projects using a wide range of mobile tools, each with their specific applicability and limitations. For each of the tools used, a comprehensive overview is given about its applicability, limitations, technical requirements, cost and also the perception of the users.The evaluation of the tools clearly shows the importance of selecting the appropriate tool depending on the envisaged data to be collected. Accessibility, visualization and cost related to data collection differ significantly among the tools tested. This paper can thus be seen as a practical guide to the currently available tools.

Novel technologies have prompted a new paradigm in disease surveillance. Advances in computation, communications and materials enable new technologies such as mobile phones and microfluidic chips. In this paper we illustrate examples of new technologies that can augment disease detection. We describe technologies harnessing the internet, mobile phones, point of care diagnostic tools and methods that facilitate detection from passively collected unstructured data. We demonstrate how these can all assist in quicker detection, investigation and response to emerging infectious events. Novel technologies enable collection and dissemination of epidemic intelligence data to both public health practitioners and the general public, enabling finer temporal and spatial resolution of disease monitoring than through traditional public health processes.

Existing algorithms for predicting species' distributions sit on a continuum between purely statistical and purely biological approaches. Most of the existing algorithms are aspatial because they do not consider the spatial context, the occurrence of the species or conditions conducive to the species' existence, in neighbouring areas. The geostatistical techniques of kriging and cokriging are presented in an attempt to encourage biologists more frequently to consider them. Unlike deterministic spatial techniques they provide estimates of prediction errors. The assumptions and applications of common geostatistical techniques are presented with worked examples drawn from a dataset of the bluetongue outbreak in northwest Europe in 2006. Emphasis is placed on the importance and interpretation of weights in geostatistical calculations. Covarying environmental data may be used to improve predictions of species’ distributions, but only if their sampling frequency is greater than that of the species’ or disease data. Cokriging techniques are unable to determine the biological significance or importance of such environmental data, because they are not designed to do so.

The distributions of parasitic diseases are determined by complex factors, including many that are distributed in space. A variety of statistical methods are now readily accessible to researchers providing opportunities for describing and ultimately understanding and predicting spatial distributions. This review provides an overview of the spatial statistical methods available to parasitologists, ecologists and epidemiologists and discusses how such methods have yielded new insights into the ecology and epidemiology of infection and disease. The review is structured according to the three major branches of spatial statistics: continuous spatial variation; discrete spatial variation; and spatial point processes.

Many of the fundamental concepts in studying infectious diseases are rooted in population ecology. We describe the importance of population ecology in exploring central issues in infectious disease research including identifying the drivers and dynamics of host-pathogen interactions and pathogen persistence, and evaluating the success of public health policies. The use of ecological concepts in infectious disease research is demonstrated with simple theoretical examples in addition to an analysis of case notification data of pertussis, a childhood respiratory disease, in Thailand as a case study. We stress that further integration of these fields will have significant impacts in infectious diseases research.

Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

The first UK epizootic of highly pathogenic (HP) H5N1 influenza in wild birds occurred in 2008, in a population of mute swans that had been the subject of ornithological study for decades. Here we use an innovative combination of ornithological, phylogenetic and immunological approaches to investigate the ecology and age structure of HP H5N1 in nature. We screened samples from swans and waterbirds using PCR and sequenced HP H5N1-positive samples. The outbreak's origin was investigated by linking bird count data with a molecular clock analysis of sampled virus sequences. We used ringing records to reconstruct the age-structure of outbreak mortality, and we estimated the age distribution of prior exposure to avian influenza. Outbreak mortality was low and all HP H5N1-positive mute swans in the affected population were <3 years old. Only the youngest age classes contained an appreciable number of individuals with no detectable antibody responses to viral nucleoprotein. Phylogenetic analysis indicated that the outbreak strain circulated locally for ∼1 month before detection and arrived when the immigration rate of migrant waterbirds was highest. Our data are consistent with the hypothesis that HP H5N1 epizootics in wild swans exhibit limited mortality due to immune protection arising from previous exposure. Our study population may represent a valuable resource for investigating the natural ecology and epidemiology of avian influenza.

Molecular phylogeography has revolutionised our ability to infer past biogeographic events from cross-sectional data on current parasite populations. In ecological parasitology, this approach has been used to address fundamental questions concerning host-parasite co-evolution and geographic patterns of spread, and has raised many technical issues and problems of interpretation. For applied parasitologists, the added complexity inherent in adding population genetic structure to perceived parasite distributions can sometimes seem to cloud rather than clarify approaches to control. In this paper, we use case studies firstly to illustrate the potential extent of cryptic diversity in parasite and parasitoid populations, secondly to consider how anthropogenic influences including movement of domestic animals affect the geographic distribution and host associations of parasite genotypes, and thirdly to explore the applied relevance of these processes to parasites of socio-economic importance. The contribution of phylogeographic approaches to deeper understanding of parasite biology in these cases is assessed. Thus, molecular data on the emerging parasites Angiostrongylus vasorum in dogs and wild canids, and the myiasis-causing flies Lucilia spp. in sheep and Cochliomyia hominovorax in humans, lead to clear implications for control efforts to limit global spread. Broader applications of molecular phylogeography to understanding parasite distributions in an era of rapid global change are also discussed.

The rate of new emerging infectious diseases entering the human population has increased over the past century, with pathogens originating from animals or from products of animal origin accounting for the vast majority. Primary risk factors for the emergence and spread of emerging zoonoses include expansion and intensification of animal agriculture and long-distance live animal transport, live animal markets, bushmeat consumption and habitat destruction. Developing effective control strategies is contingent upon the ability to test causative hypotheses of disease transmission within a statistical framework. Broadly speaking, molecular phylogeography offers a framework in which specific hypotheses regarding pathogen gene flow and dispersal within an ecological context can be compared. A number of different methods has been developed for this application. Here, our intent is firstly to discuss the application of a wide variety of statistically based methods (including Bayesian reconstruction, network parsimony analysis and regression) to specific viruses (influenza, salmon anaemia virus, foot and mouth disease and Rift Valley Fever) that have been associated with animal farming/movements; and secondly to place them in the larger framework of the threat of potential zoonotic events as well as the economic and biosecurity implications of pathogen outbreaks among our animal food sources.

Multilocus sequence typing (MLST) and multilocus sequence analysis (MLSA) have revolutionized understanding the global epidemiology of many medically relevant bacteria utilizing a number, mostly seven, of housekeeping genes. A more recent introduction, single nucleotide polymorphisms (SNPs), constitutes an even more powerful tool for bacterial typing, population genetic studies and phylogeography. The introduction of massive parallel sequencing has made genome re-sequencing and SNP discovery more economical for investigations of microbial organisms. In this paper we review phylogeographic studies on Lyme borreliosis (LB)-group spirochetes and methicillin-resistant Staphylococcus aureus (MRSA). Members of the LB-group spirochetes are tick-transmitted zoonotic bacteria that have many hosts and differ in their degree of host specialism, constituting a highly complex system. MRSA is a directly transmitted pathogen that may be acquired by contact with infected people, animals or MRSA-contaminated objects. For the LB-group spirochetes, MLSA has proved a powerful tool for species assignment and phylogeographic investigations while for S. aureus, genome-wide SNP data have been used to study the very short-term evolution of two important MRSA lineages, ST239 and ST225. These data are detailed in this review.

Phylogeography of parasites and microbes is a recent field. Phylogeographic studies have been performed mostly to test three major hypotheses that are not mutually exclusive on the origins and distributions of human parasites and microbes: (1) the “out of Africa” pattern where parasites are supposed to have followed the dispersal and expansion of modern humans in and out of Africa, (2) the “domestication” pattern where parasites were captured in the domestication centres and dispersed through them and (3) the “globalization” pattern, in relation to historical and more recent trade routes. With some exceptions, such studies of human protozoans, helminths and ectoparasites are quite limited. The conclusion emphasizes the need to acquire more phylogeographic data in non-Occidental countries, and particularly in Asia where all the animal domestications took place.