Disease ecology and pathogeography: Changing the focus to better interpret and anticipate complex environment–host–pathogen interactions

Over the past 15 years, disease ecology has become a discipline in its own right. It is fundamentally based on training in ecology and evolution, with solid theoretical foundations and skills in computational biology and statistics, and it differs from a medical approach to the interpretation of disease. It is concerned with how species interactions, including host–pathogen relationships and environmental conditions (e.g. temperature and rainfall), affect patterns and processes of disease presence and spread, how pathogens impact host individuals, populations, communities, and ultimately ecosystem function (Ostfeld et al. 2008). Initially rooted in parasite ecology, particularly among researchers working on transmission cycles and host–disease population dynamics, disease ecology mainly focuses on parasitic and infectious diseases but is not exclusive to them (Ostfeld 2018). A booming subfield currently concerns research linking different areas such as infectious transmission, agriculture development, and development aid policies, notably in the world's poorest countries (Ngonghala et al. 2014). Unlike ecologists, disease ecologists focus on understanding the causes and consequences of the maintenance and transmission of pathogens in animal species, including humans, plants, and communities of species. It has become much more widespread in studies among wild animal species, also in their contacts with domestic species, e.g. livestock, and their interactions with human populations, and much less so in plant diseases and their transmission, which in some respects are the focus of more plant-pathology molecular-orientated research (Guégan et al. 2023a). We cannot say that the development of disease ecology has involved the gradual integration of several distinct lines of inquiry because it is the heir of ecology. It has an ecosystem-based approach and takes into account natural complexity (Johnson et al. 2015, Hassell et al. 2021, Petrone et al. 2023); it develops experimental methods in the laboratory or mesocosms and has an essential background in statistical and mathematical analysis. The spatial scales of disease ecology study are experimental or local and, depending on the questions posed, can extend to the most global scales (Guernier et al. 2004, Jones et al. 2008, Allen et al. 2017, Carlson et al. 2022). In the temporal domain, these can be daily or weekly studies or multi-decadal investigations, such as in disease population dynamics (Keeling and Rohani 2007). By definition, disease ecology is concerned with understanding patterns and processes on large spatial and temporal scales. It integrates different levels of life organization, i.e. from genes to the global ecosystem, which is not the case, or only to a limited extent, of medical and veterinary approaches (Ezenwa et al. 2015). Over the years, however, disease ecology has gained the confidence of other disciplines, particularly the medical and veterinary ones, and is now published in top-leading generalist journals (Mahon et al. 2024, Pfenning-Butterworth et al. 2024, Chevillon et al. 2024). Today, disease ecology is also challenging established dogmas in human and veterinary medicine, reconsidering several aspects of infectious transmission in-depth, raising the question of possible larger host species spectra, and questioning the origin and nature of pathogen virulence (Chevillon et al. 2024). We are happy to present this special issue on disease ecology in the journal Ecography. At least two other contributions recently published in Ecography could have contributed to this special issue in disease ecology. Both constitute remarkable illustrations of macro-scale studies on host–parasite interactions. They are: Latitudinal distributions of the species richness, phylogenetic diversity and functional diversity of fleas and their small mammalian hosts in four geographic quadrants by Krasnov and colleagues (Krasnov et al. 2023); and Continental-scale climatic gradients of pathogenic microbial taxa in birds and bats by Xu and coauthors (Xu et al. 2023). As illustrated in the different sections of this special issue, disease ecology is a highly interdisciplinary field, drawing on molecular biology and population genetics, immunology, epidemiology, time-series and spatial biostatistics, and ecological and epidemiological modeling. It takes an interdisciplinary approach, often questioning disease distribution, transmission, and intensity from another angle, and this with the wish to propose methods of surveillance, control, and research that are innovative sometimes breakthrough, and more in line with the complexity of the observations made. In summary, the papers we present in this issue illustrate diverse scientific work and confirm the significant growth of disease ecology in the international research landscape. Climate change is accepted as an important driver of infectious disease emergence and spread for humans, wildlife, and domestic animals (Mora et al. 2022). However, there is considerable controversy as to whether climate change operates directly on the ecology of host–pathogen interactions (Franklinos et al. 2019, Casadevall 2020) or whether it intervenes more indirectly by exacerbating prevailing environmental, socioeconomic, or political conditions (Guégan et al. 2023b). In a disease–biogeography study based on field observations, entitled Climate change linked to vampire bat expansion and rabies virus spillover, Van de Vuurst and collaborators (Van de Vuurst et al. 2023) report the impacts of global warming on the distributional range and expansion of the common vampire bat, Desmodus rotundus, across the Americas over the last century. Through a cogent correlation-based statistical analysis, the authors document the gradual expansion of vampire-borne rabies virus outbreaks in cattle herds in the last 50 years of the multi-decadal study period. The results presented here confirm the numerous observations of vampire-borne rabies cases in livestock on the continent while situating it in a macroecological dimension and pathogeography research perspective (Murray et al. 2018). Then, Garcia-Carrasco and coauthors in an article, Present and future situation of West Nile virus in the Afro-Palaearctic pathogeographic system (Garcia-Carrasco et al. 2024), analyze the impacts of climate change on West Nile virus transmission and spread, a disease system that is highly sensitive to weather conditions and change. This virus is transmitted by insect vectors, genus Culex, and is also hosted by a wide range of bird species, making this zoonotic disease highly sensitive to climatic conditions. Using an innovative machine learning and fuzzy logic approach to model the effects of climate change scenarios for 2040 and 2070, this study evaluates the risk of West Nile virus outbreaks in two biogeographic regions, the Afrotropical and the Western Paleartic. They report that the Afro-Paleartic land masses could experience significant upsurges of epizootic and epidemic West Nile virus, with central and northern European regions at notable risk of disease expansion beyond the current distribution range. This study also confirms a broader comparative study on spillover risk in the context of climate change and wild species range shifts (Carlson et al. 2022). Next, Aliaga Samanez and colleagues, in their article Climate change is aggravating dengue and yellow fever transmission risk (Aliaga-Samanez et al. 2024), model dengue and yellow fever diseases, two severe human infectious diseases, considering for the first time urban and sylvatic vectors, and non-primate hosts, to identify areas where climatic favourability for the two viral agents could change with global warming. Both viruses spilled over into human transmission and were translocated in many regions, opening a path for spillback onto sylvatic cycles mainly for yellow fever (Santos de Abreu et al. 2022, Tuells et al. 2022) and DENV-2 serotype (Hanley et al. 2024). Using the same methodological framework as for previous studies, they obtain projections of future transmission risk for dengue and yellow fever and show that global favourability could increase by 10% for dengue and 7% for yellow fever, providing details of regions and subregions at particular risk for each disease. Furthermore, pathogeographical patterns of viral transmission are discussed in light of both vector and non-human primates' geographical distribution and potential range shifts. Projections of disease spread scenarios within the current context of climate change become particularly relevant since these changes disrupt ecological equilibria among vectors, host reservoirs, and human populations. These three examples illustrate the application of disease ecology and biogeography tools to assess the risk of infectious diseases and anticipate their future spread. Human activities modify, either directly or indirectly, the environments in which host–pathogen interactions take place (Lindahl and Grace 2015), leading to more encounters with reservoirs (Rhyan and Spraker 2010) or changes in the natural dynamics of complex multi-species systems (Hassell et al. 2017). In this section, contributors to the Special Issue investigate how habitat alterations and loss can reshape the risk of disease transmission or emergence. Among the drivers that disease emergence and biodiversity loss share, land use features prominently. In their contribution, García-Peña and Rubio (2024) investigate how reservoirs of pathogenic and non-pathogenic New World Hantaviruses (NWH) respond to disturbances alongside a continent-wide gradient going from primary forest to agriculture. Through multivariate analysis, their results suggest that the prevalence of hosts is increased in rangelands and agricultural landscapes, corroborating global comparative studies exploring drivers of spillover transmission from rodent hosts (Ecke et al. 2022). Increased chances of encountering NWH reservoirs in agricultural lands suggest that ongoing widespread reconversion of the forest into cropland, such as the Brazilian Amazon (Morton et al. 2006), may increase the burden of infectious disease. Remarkably, this analysis also highlights a potential hotspot for reservoirs of NWH in northern Canada, a prediction that is well-supported in, for example, the case records of infections of humans by Sin Nombre virus since 1993 (Warner et al. 2020). The question of how much habitat degradation will reshape the global risk of zoonotic diseases is, likewise, the core of the contribution by (Heckley et al. 2023). Through a meta-analysis of neotropical bat prevalence and seroprevalence, they examine the consequences of various classes of habitat degradation (including forest loss) on infection dynamics. Although sampling biases led to an over-representation of data on D. rotundus and rabies virus (see also Van de Vuurst et al. 2023 in this issue), they report that the highest prevalences (above 50%) were only observed in regions with the greatest extents of forest loss in the year before sampling. Identifying these potential causal mechanisms linking habitat degradation to zoonotic disease spillover is critical for more accurate prediction (Plowright et al. 2017, Mahon et al. 2024). The strength of the study by Heckley et al. (2023) is to show how diffuse these effects can be, even within relatively well-described systems (bats in the Neotropics). One possible explanation is that seasonal dynamics (Kessler et al. 2018) can profoundly change the landscape hosts experience, and these intra-annual variations can only be captured with a significantly larger amount of data. In their contribution, Teitelbaum et al. (2024) look at how wild waterfowl interact with domestic poultry farms and how variations in these interactions shape the risk of transmission of avian influenza. The data used in this study (GPS data at the individual scale for over 400 individuals of ten species) offer a high-resolution view of space, time, and taxonomy; this allows for developing an appreciation of the risk of avian influenza transmission at a very fine scale. Different species of wild waterfowl used the habitats provided by domestic poultry farms at different rates, both across day/night and seasonal changes. Coupled with changes in abundance and influenza prevalence, the (multiplicative) interactions between these factors led to substantial changes in transmission risk, even within the relatively homogeneous study environment of California's Central Valley. These studies highlight the challenges of understanding how habitat alteration will reshape the risk associated with disease. Because the ecological processes linking species (and species interactions) to their habitats play out over heterogeneous space and time, the amount of data required to draw general conclusions remains the main obstacle. Advances in Earth Observation through, e.g. remote sensing or the increased availability of high-resolution data with GPS collars are likely to provide good data to generalize our understanding of these questions in the coming years. In this section, the authors illustrate the inherent complexity in host–pathogen or host–symbiont interactions. Indeed, a microbe cannot cause disease on its own without a host (Casadevall and Pirofski 2014). Still, this host–pathogen interaction is also mediated by the relationships it may maintain with other host and non-host species and with abiotic and biotic environmental conditions. Disease is one of several possible outcomes of an interaction between a host and a microbe, and this section also proposes research on host–symbiont relationships. A first contribution by Clark and contributors entitled Aggregation of symbionts on hosts depends on interaction type and host traits analyzes aggregation patterns in both barnacle–limpet and gill helminth–poecilid fish associations (Clark et al. 2023). The aggregation of symbionts and parasites among hosts is a near-universal pattern, and it also has important consequences for the stability of host–parasite associations and disease impacts (Morrill et al. 2022). Identifying which potential drivers are contributing to levels of observed aggregation in these systems has always been a pillar of parasitological ecology, the precursor of what would become disease ecology. This research has also contributed to developing high-performance biostatistical methods, another feature of disease ecology (McVinish and Lester 2020, Lester and Blomberg 2021). Using null models to analyze aggregation patterns in the two Clark et al. (2023) show that aggregation of on with observed across depending on across fish were less by with aggregation with host fish The authors that processes can account for the aggregation of symbionts on their hosts but not the levels of aggregation observed in host–parasite interactions for which host traits may to aggregation In a macroecological and colleagues a gradient for a of parasite that not to the of accepted interactions the et al. 2023). 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