Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks

Radar versus optical: The impact of cloud cover when mapping seasonal surface water for health applications in monsoon-affected India

Surface water plays a vital role in the spread of infectious diseases. Information on the spatial and temporal dynamics of surface water availability is thus critical to understanding, monitoring and forecasting disease outbreaks. Before the launch of Sentinel-1 Synthetic Aperture Radar (SAR) missions, surface water availability has been captured at various spatial scales through approaches based on optical remote sensing data. A critical drawback of the latter is data loss due to cloud cover, however few studies have quantified this. This study evaluated data loss due to clouds in three Western Ghats (India) districts. These forest-agricultural mosaic landscapes, where water-related diseases are prevalent, experience the Indian monsoon. We compared surface water areas mapped by thresholding 10m Sentinel-1A SAR data with the optical 30m Landsat-derived Joint Research Centre (JRC) Global Surface Water product, currently the only globally available long-term monthly surface water data product. Backscatter thresholds were identified manually, and our Bayesian algorithm found these thresholds were very likely (>97%). While the Sentinel-1 SAR-based and JRC's optical-based approach mapped surface water extent with high overall accuracy (> 98%) when the cloud cover was low, the unmapped surface water area was substantial in the JRC product during the monsoon months. Across the districts, the average cloud cover in the July-August period was 92% or 90% for 2017 and 2018 respectively, resulting in 25% or 23% of the surface water area being unmapped. Also, the more detailed 10m resolution of Sentinel-1A SAR helped detect the many small water features missed by 30m JRC. Thus, for predicting water-related disease risks linked to small water features or monsoon rainfall, Sentinel-1A SAR is more effective. Finally, automatic backscatter thresholding for unvegetated surface water mapping can be effective if threshold values are adapted to regional-specific backscatter spatial and temporal variations.

Informing climate-health adaptation options through mapping the needs and potential for integrated climate-driven early warning forecasting systems in South Asia-A scoping review

BACKGROUND

Climate change is widely recognised to threaten human health, wellbeing and livelihoods, including through its effects on the emergence, spread and burdens of climate-and water-sensitive infectious diseases. However, the scale and mechanisms of the impacts are uncertain and it is unclear whether existing forecasting capacities will foster successful local-level adaptation planning, particularly in climate vulnerable regions in developing countries. The purpose of this scoping review was to characterise and map priority climate- and water-sensitive diseases, map existing forecasting and surveillance systems in climate and health sectors and scope out the needs and potential to develop integrated climate-driven early warning forecasting systems for long-term adaptation planning and interventions in the south Asia region.

METHODS

We searched Web of Science Core Collection, Scopus and PubMed using title, abstract and keywords only for papers focussing on climate-and water-sensitive diseases and explicit mention of either forecasting or surveillance systems in south Asia. We conducted further internet search of relevant national climate adaptation plans and health policies affecting disease management. We identified 187 studies reporting on climate-sensitive diseases and information systems in the south Asia context published between 1992 and 2024.

RESULTS

We found very few robust, evidenced-based forecasting systems for climate- and water- sensitive infectious diseases, which suggests limited operationalisation of decision-support tools that could inform actions to reduce disease burdens in the region. Many of the information systems platforms identified focussed on climate-sensitive vector-borne disease systems, with limited tools for water-sensitive diseases. This reveals an opportunity to develop tools for these neglected disease groups. Of the 34 operational platforms identified across the focal countries, only 13 (representing 38.2%) are freely available online and all were developed and implemented by the human health sector. Tools are needed for other south Asian countries (Afghanistan, Sri Lanka, Bhutan) where the risks of infectious diseases are predicted to increase substantially due to climate change, drought and shifts in human demography and use of ecosystems.

CONCLUSION

Altogether, the findings highlight clear opportunities to invest in the co-development and implementation of contextually relevant climate-driven early warning tools and research priorities for disease control and adaptation planning.

Land system governance shapes tick-related public and animal health risks

Land cover and land use have established effects on hazard and exposure to vector-borne diseases. While our understanding of the proximate and distant causes and consequences of land use decisions has evolved, the focus on the proximate effects of landscape on disease ecology remains dominant. We argue that land use governance, viewed through a land system lens, affects tick-borne disease risk. Governance affects land use trajectories and potentially shapes landscapes favourable to ticks or increases contact with ticks by structuring human-land interactions. We illustrate the role of land use legacies, trade-offs in land-use decisions, and social inequities in access to land resources, information and decision-making, with three cases: Kyasanur Forest disease in India, Lyme disease in the Outer Hebrides (Scotland), and tick acaricide resistance in cattle in Ecuador. Land use governance is key to managing the risk of tick-borne diseases, by affecting the hazard and exposure. We propose that land use governance should consider unintended consequences on infectious disease risk.

Producing context specific land cover and land use maps of human-modified tropical forest landscapes for infectious disease applications

Satellite-based land cover mapping plays an important role in understanding changes in ecosystems and biodiversity. There are global land cover products available, however for region specific studies of drivers of infectious disease patterns, these can lack the spatial and thematic detail or accuracy required to capture key ecological processes. To overcome this, we produced our own Landsat derived 30 m maps for three districts in India's Western Ghats (Wayanad, Shivamogga and Sindhudurg). The maps locate natural vegetation types, plantation types, agricultural areas, water bodies and settlements in the landscape, all relevant to functional resource use of species involved in infectious disease dynamics. The maps represent the mode of 50 classification iterations and include a spatial measure of class stability derived from these iterations. Overall accuracies for Wayanad, Shivamogga and Sindhudurg are 94.7 % (SE 1.2 %), 88.9 % (SE 1.2 %) and 88.8 % (SE 2 %) respectively. Class classification stability was high across all three districts and the individual classes that matter for defining key interfaces between human habitation, forests, crop, and plantation cultivation, were generally well separated. A comparison with the 300 m global ESA CCI land cover map highlights lower ESA CCI class accuracies and the importance of increased spatial resolution when dealing with complex landscape mosaics. A comparison with the 30 m Global Forest Change product reveals an accurate mapping of forest loss and different dynamics between districts (i.e., Forests lost to Built-up versus Forests lost to Plantations), demonstrating an interesting complementarity between our maps and the % tree cover Global Forest Change product. When studying infectious disease responses to land use change in tropical forest ecosystems, we recommend using bespoke land cover/use classifications reflecting functional resource use by relevant vectors, reservoirs, and people. Alternatively, global products should be carefully validated with ground reference points representing locally relevant habitats.

Resource selection by New York City deer reveals the effective interface between wildlife, zoonotic hazards and humans

Although the role of host movement in shaping infectious disease dynamics is widely acknowledged, methodological separation between animal movement and disease ecology has prevented researchers from leveraging empirical insights from movement data to advance landscape scale understanding of infectious disease risk. To address this knowledge gap, we examine how movement behaviour and resource utilization by white-tailed deer (Odocoileus virginianus) determines blacklegged tick (Ixodes scapularis) distribution, which depend on deer for dispersal in a highly fragmented New York City borough. Multi-scale hierarchical resource selection analysis and movement modelling provide insight into how deer's movements contribute to the risk landscape for human exposure to the Lyme disease vector-I. scapularis. We find deer select highly vegetated and accessible residential properties which support blacklegged tick survival. We conclude the distribution of tick-borne disease risk results from the individual resource selection by deer across spatial scales in response to habitat fragmentation and anthropogenic disturbances.

Using mechanistic models to highlight research priorities for tick-borne zoonotic diseases: Improving our understanding of the ecology and maintenance of Kyasanur Forest Disease in India

The risk of spillover of zoonotic diseases to humans is changing in response to multiple environmental and societal drivers, particularly in tropical regions where the burden of neglected zoonotic diseases is highest and land use change and forest conversion is occurring most rapidly. Neglected zoonotic diseases can have significant impacts on poor and marginalised populations in low-resource settings but ultimately receive less attention and funding for research and interventions. As such, effective control measures and interventions are often hindered by a limited ecological evidence base, which results in a limited understanding of epidemiologically relevant hosts or vectors and the processes that contribute to the maintenance of pathogens and spillover to humans. Here, we develop a generalisable next generation matrix modelling framework to better understand the transmission processes and hosts that have the greatest contribution to the maintenance of tick-borne diseases with the aim of improving the ecological evidence base and framing future research priorities for tick-borne diseases. Using this model we explore the relative contribution of different host groups and transmission routes to the maintenance of a neglected zoonotic tick-borne disease, Kyasanur Forest Disease Virus (KFD), in multiple habitat types. The results highlight the potential importance of transovarial transmission and small mammals and birds in maintaining this disease. This contradicts previous hypotheses that primates play an important role influencing the distribution of infected ticks. There is also a suggestion that risk could vary across different habitat types but currently more research is needed to evaluate this relationship. In light of these results, we outline the key knowledge gaps for this system and future research priorities that could inform effective interventions and control measures.

The role of invasive alien species in the emergence and spread of zoonoses

The role of invasive alien species in the transmission dynamics of zoonotic pathogens is often overlooked, despite the rapid escalation in biological invasions globally. Here we synthesise available information on the influence of invasive alien species on zoonotic pathogen dynamics in invaded ranges, focussing on Europe, and identify key associated knowledge gaps. We identified 272 documented interactions between alien species and zoonotic pathogens within invaded ranges. The majority of these involved invasive alien mammals followed by birds with only a few occurrences of other taxa documented. A wide range of potential interactions between invasive alien species and zoonotic pathogens were identified but few studies considered transmission to humans and so there was limited evidence of actual impacts on human health. However, there is an urgent need to raise awareness of the potential risks posed to human health by the transmission of zoonotic diseases by invasive alien species; the role of invasive alien species in zoonotic disease transmission may exceed that of native wildlife and occur in a relatively short period following the arrival of an invasive alien species within a new region. Ecological and social mechanisms govern the dynamics of zoonotic disease transmission but wildlife diseases are not consistently included within animal, plant and human policies. Rapid advances in the development of systems frameworks that integrate the ecological, economic and social processes promoting spillover in rapidly changing environments will increase understanding to inform decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10530-022-02978-1.

dynamAedes: a unified modelling framework for invasive Aedes mosquitoes

Mosquito species belonging to the genus Aedes have attracted the interest of scientists and public health officers because of their capacity to transmit viruses that affect humans. Some of these species were brought outside their native range by means of trade and tourism and then colonised new regions thanks to a unique combination of eco-physiological traits. Considering mosquito physiological and behavioural traits to understand and predict their population dynamics is thus a crucial step in developing strategies to mitigate the local densities of invasive Aedes populations. Here, we synthesised the life cycle of four invasive Aedes species (Ae. aegypti, Ae. albopictus, Ae. japonicus and Ae. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R package dynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data. Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on the species' biology which could be applied to the management of invasive Aedes populations as well as to more theoretical ecological inquiries.

Effect of Constant Temperatures on Culicoides sonorensis Midge Physiology and Vesicular Stomatitis Virus Infection

Simple Summary

Culicoides biting midges are nuisance pests of livestock and well-known vectors of veterinary arboviruses, such as vesicular stomatitis virus (VSV). Female midges ingest viruses when feeding on blood to obtain protein for egg-laying. After ingesting a VSV-infected blood meal, the environmental temperature of the resting location mediates the rates at which blood is digested, eggs are laid, and virus particles are replicated inside the midge. VSV transmission will occur if the timing of virus amplification aligns with the next feeding–egg-laying cycle. We evaluated the impact of constant environmental temperatures on midge physiology (lifespan and reproduction), vector competence for VSV (infection and dissemination), and thermal resting preference. Our results indicate that after ingesting a blood meal, most midges prefer to rest in areas that fall within their preferred physiological range regardless of the temperatures at which they were being maintained. These preferred temperatures maximized their survival, the number of egg-laying cycles, and the likelihood of VSV transmission. Our temperature approach shows that in the Culicoides–VSV system, the preferred resting temperature selected by blood-fed midges is beneficial for both insect and virus transmission.

Abstract

Culicoides midges play an important role in vesicular stomatitis virus (VSV) transmission to US livestock. After VSV-blood feeding, blood digestion followed by oviposition occurs while ingested virus particles replicate and disseminate to salivary glands for transmission during subsequent blood-feeding events. Changes to environmental temperature may alter the feeding–oviposition–refeeding cycles, midge survival, VSV infection, and overall vector capacity. However, the heterothermic midge may respond rapidly to environmental changes by adjusting their thermal behavior to resting in areas closer to their physiological range. Here we investigated the effects of four constant environmental temperatures (20, 25, 30, and 35 °C) on C. sonorensis survival, oviposition, and VSV infection, as well as resting thermal preferences after blood-feeding. We found that most midges preferred to rest in areas at 25–30 °C. These two constant temperatures (25 and 30 °C) allowed an intermediate fitness performance, with a 66% survival probability by day 10 and oviposition cycles occurring every 2–3 days. Additionally, VSV infection rates in bodies and heads with salivary glands were higher than in midges held at 20 °C and 35 °C. Our results provide insight into the implications of temperature on VSV–Culicoides interactions and confirm that the range of temperature preferred by midges can benefit both the vector and the arbovirus.

The evolving story of Borrelia burgdorferi sensu lato transmission in Europe

Beside mosquitoes, ticks are well-known vectors of different human pathogens. In the Northern Hemisphere, Lyme borreliosis (Eurasia, LB) or Lyme disease (North America, LD) is the most commonly occurring vector-borne infectious disease caused by bacteria of the genus Borrelia which are transmitted by hard ticks of the genus Ixodes. The reported incidence of LB in Europe is about 22.6 cases per 100,000 inhabitants annually with a broad range depending on the geographical area analyzed. However, the epidemiological data are largely incomplete, because LB is not notifiable in all European countries. Furthermore, not only differ reporting procedures between countries, there is also variation in case definitions and diagnostic procedures. Lyme borreliosis is caused by several species of the Borrelia (B.) burgdorferi sensu lato (s.l.) complex which are maintained in complex networks including ixodid ticks and different reservoir hosts. Vector and host influence each other and are affected by multiple factors including climate that have a major impact on their habitats and ecology. To classify factors that influence the risk of transmission of B. burgdorferi s.l. to their different vertebrate hosts as well as to humans, we briefly summarize the current knowledge about the pathogens including their astonishing ability to overcome various host immune responses, regarding the main vector in Europe Ixodes ricinus, and the disease caused by borreliae. The research shows, that a higher standardization of case definition, diagnostic procedures, and standardized, long-term surveillance systems across Europe is necessary to improve clinical and epidemiological data.

Tick exposure and risk of tick-borne pathogens infection in hunters and hunting dogs: a citizen science approach

Citizen science may be described as a research involving communities and individuals, other than scientists. Following this approach, along with the evidence of a high prevalence of Rickettsia spp. in Dermacentor marginatus from wild boars in hunting areas of southern Italy, this study aimed to assess the occurrence of tick‐borne pathogens (TBPs) in ticks collected from hunters and their hunting dogs. From October 2020 to May 2021, ticks were collected from wild boar hunters (n = 347) and their dogs (n = 422) in regions of southern Italy (i.e., Apulia, Basilicata, Calabria, Campania and Sicily). All ticks were morphologically identified, classified according to gender, feeding status, host, geographic origin, and molecularly screened for zoonotic bacteria. Adult ticks (n = 411) were collected from hunters (i.e., n = 29; 8.4%; mean of 1.6 ticks for person) and dogs (i.e., n = 200; 47.4%; mean of 1.8 ticks for animal) and identified at species level as D. marginatus (n = 240, 58.4%), Rhipicephalus sanguineus sensu lato (n = 135, 32.8%), Rhipicephalus turanicus (n = 27, 6.6%) and Ixodes ricinus (n = 9, 2.2%). Overall, 45 ticks (i.e., 10.9%, 95% CI: 8.3‐14.3) tested positive for at least one tick‐borne agent, being Rickettsia slovaca the most frequent species (n = 37, 9.0%), followed by Rickettsia raoultii, Rickettsia aeschlimannii, Rickettsia monacensis, Coxiella burnetii, Borrelia lusitaniae and Candidatus Midichloria mitochondrii (n = 2, 0.5% each). Data herein presented demonstrate a relevant risk of exposure to TBPs for hunters and hunting dogs during the hunting activities. Therefore, the role of hunters to monitor the circulation of ticks in rural areas may be considered an effective example of the citizen science approach, supporting the cooperation toward private and public health stakeholders.

Environmental determinants of Anaplasma phagocytophilum infection in cattle using a kernel density function

The study of vector-borne zoonotic diseases often relies on partial data, because of the constraints associated with observing various elements of the transmission cycle: the pathogen, the vector, the host - wild or domestic. Each angle comes with its own practical challenges, leading to data reflecting poorly either on spatial or temporal dynamics, or both. In this study, we investigated the effect of landscape on the presence of bovine ehrlichiosis infection in Walloon cattle. This disease is transmitted to cattle through the bite of a tick infected by the bacterium Anaplasma phagocytophilum. The first case of bovine ehrlichiosis in the southern region of Belgium (Wallonia) was detected in 2005 and the high seroprevalence found in herds suggests that the disease is endemic. The presence of antibodies of A. phagocytophilum in one cow selected in each of 1445 herds in 2010 and 2011 was detected using indirect immunofluorescence. Samples were geolocated at the farm. However, the precise location of infection remains uncertain. To account for the data sparsity, we elaborated a spatial index for the intensity of the presence of seropositive animals, based on a non-parametric kernel density estimation. We examined this index with the landscape surrounding the pastures, using multiple regressions. Landscape factors were selected using a conceptual framework based on the ecological resources needed for the transmission cycle of A. phagocytophilum. Results suggest that our spatial index adequately reflected infection presence in cattle in Wallonia, which was highest in central regions, corresponding to more forested and fragmented landscapes. We noticed that the presence of large hosts, wild or domestic, as well as the composition and configuration of the landscape of the pasture, influenced the capacity of the pasture to support the presence of bovine ehrlichiosis in Walloon herds. This is consistent with the ecology of A. phagocytophilum and current knowledge about risk factors of tick-borne diseases in cattle at the regional scale. The nature of the kernel density index, based on uncertainties over the location of cases positive to A. phagocytophilum, reflected the infectiousness profile at the landscape and not at the pasture level. Results also highlighted that the effects of some environmental variables remain, even when considering the different agro-geographic regions of Wallonia, which present contrasted landscapes and different levels of intensity of A. phagocytophilum infection. The kernel density index is a useful tool to help veterinary practitioner to quickly target areas where A. phagocytophilum infection is likely.

Spatio-temporal modelling of Culicoides Latreille (Diptera: Ceratopogonidae) populations on Reunion Island (Indian Ocean)

BACKGROUND

Reunion Island regularly faces outbreaks of bluetongue and epizootic hemorrhagic diseases, two insect-borne orbiviral diseases of ruminants. Hematophagous midges of the genus Culicoides (Diptera: Ceratopogonidae) are the vectors of bluetongue (BTV) and epizootic hemorrhagic disease (EHDV) viruses. In a previous study, statistical models based on environmental and meteorological data were developed for the five Culicoides species present in the island to provide a better understanding of their ecology and predict their presence and abundance. The purpose of this study was to couple these statistical models with a Geographic Information System (GIS) to produce dynamic maps of the distribution of Culicoides throughout the island.

METHODS

Based on meteorological data from ground weather stations and satellite-derived environmental data, the abundance of each of the five Culicoides species was estimated for the 2214 husbandry locations on the island for the period ranging from February 2016 to June 2018. A large-scale Culicoides sampling campaign including 100 farms was carried out in March 2018 to validate the model.

RESULTS

According to the model predictions, no husbandry location was free of Culicoides throughout the study period. The five Culicoides species were present on average in 57.0% of the husbandry locations for C. bolitinos Meiswinkel, 40.7% for C. enderleini Cornet & Brunhes, 26.5% for C. grahamii Austen, 87.1% for C. imicola Kieffer and 91.8% for C. kibatiensis Goetghebuer. The models also showed high seasonal variations in their distribution. During the validation process, predictions were acceptable for C. bolitinos, C. enderleini and C. kibatiensis, with normalized root mean square errors (NRMSE) of 15.4%, 13.6% and 16.5%, respectively. The NRMSE was 27.4% for C. grahamii. For C. imicola, the NRMSE was acceptable (11.9%) considering all husbandry locations except in two specific areas, the Cirque de Salazie-an inner mountainous part of the island-and the sea edge, where the model overestimated its abundance.

CONCLUSIONS

Our model provides, for the first time to our knowledge, an operational tool to better understand and predict the distribution of Culicoides in Reunion Island. As it predicts a wide spatial distribution of the five Culicoides species throughout the year and taking into consideration their vector competence, our results suggest that BTV and EHDV can circulate continuously on the island. As further actions, our model could be coupled with an epidemiological model of BTV and EHDV transmission to improve risk assessment of Culicoides-borne diseases on the island.

Reviewing the ecological evidence base for management of emerging tropical zoonoses: Kyasanur Forest Disease in India as a case study

Zoonoses disproportionately affect tropical communities and are associated with human modification and use of ecosystems. Effective management is hampered by poor ecological understanding of disease transmission and often focuses on human vaccination or treatment. Better ecological understanding of multi-vector and multi-host transmission, social and environmental factors altering human exposure, might enable a broader suite of management options. Options may include "ecological interventions" that target vectors or hosts and require good knowledge of underlying transmission processes, which may be more effective, economical, and long lasting than conventional approaches. New frameworks identify the hierarchical series of barriers that a pathogen needs to overcome before human spillover occurs and demonstrate how ecological interventions may strengthen these barriers and complement human-focused disease control. We extend these frameworks for vector-borne zoonoses, focusing on Kyasanur Forest Disease Virus (KFDV), a tick-borne, neglected zoonosis affecting poor forest communities in India, involving complex communities of tick and host species. We identify the hierarchical barriers to pathogen transmission targeted by existing management. We show that existing interventions mainly focus on human barriers (via personal protection and vaccination) or at barriers relating to Kyasanur Forest Disease (KFD) vectors (tick control on cattle and at the sites of host (monkey) deaths). We review the validity of existing management guidance for KFD through literature review and interviews with disease managers. Efficacy of interventions was difficult to quantify due to poor empirical understanding of KFDV-vector-host ecology, particularly the role of cattle and monkeys in the disease transmission cycle. Cattle are hypothesised to amplify tick populations. Monkeys may act as sentinels of human infection or are hypothesised to act as amplifying hosts for KFDV, but the spatial scale of risk arising from ticks infected via monkeys versus small mammal reservoirs is unclear. We identified 19 urgent research priorities for refinement of current management strategies or development of ecological interventions targeting vectors and host barriers to prevent disease spillover in the future.

Dispersal in heterogeneous environments drives population dynamics and control of tsetse flies

Spatio-temporally heterogeneous environments may lead to unexpected population dynamics. Knowledge is needed on local properties favouring population resilience at large scale. For pathogen vectors, such as tsetse flies transmitting human and animal African trypanosomosis, this is crucial to target management strategies. We developed a mechanistic spatio-temporal model of the age-structured population dynamics of tsetse flies, parametrized with field and laboratory data. It accounts for density- and temperature-dependence. The studied environment is heterogeneous, fragmented and dispersal is suitability-driven. We confirmed that temperature and adult mortality have a strong impact on tsetse populations. When homogeneously increasing adult mortality, control was less effective and induced faster population recovery in the coldest and temperature-stable locations, creating refuges. To optimally select locations to control, we assessed the potential impact of treating them and their contribution to the whole population. This heterogeneous control induced a similar population decrease, with more dispersed individuals. Control efficacy was no longer related to temperature. Dispersal was responsible for refuges at the interface between controlled and uncontrolled zones, where resurgence after control was very high. The early identification of refuges, which could jeopardize control efforts, is crucial. We recommend baseline data collection to characterize the ecosystem before implementing any measures.

Environmental Drivers of Adult Seasonality and Abundance of Biting Midges Culicoides (Diptera: Ceratopogonidae), Bluetongue Vector Species in Spain

Bluetongue is a viral disease affecting wild and domestic ruminants transmitted by several species of biting midges Culicoides Latreille. The phenology of these insects were analyzed in relation to potential environmental drivers. Data from 329 sites in Spain were analyzed using Bayesian Generalized Linear Mixed Model (GLMM) approaches. The effects of environmental factors on adult female seasonality were contrasted. Obsoletus complex species (Diptera: Ceratopogonidae) were the most prevalent across sites, followed by Culicoides newsteadi Austen (Diptera: Ceratopogonidae). Activity of female Obsoletus complex species was longest in sites at low elevation, with warmer spring average temperatures and precipitation, as well as in sites with high abundance of cattle. The length of the Culicoides imicola Kieffer (Diptera: Ceratopogonidae) female adult season was also longest in sites at low elevation with higher coverage of broad-leaved vegetation. Long adult seasons of C. newsteadi were found in sites with warmer autumns and higher precipitation, high abundance of sheep. Culicoides pulicaris (Linnaeus) (Diptera: Ceratopogonidae) had longer adult periods in sites with a greater number of accumulated degree days over 10°C during winter. These results demonstrate the eco-climatic and seasonal differences among these four taxa in Spain, which may contribute to determining sites with suitable environmental circumstances for each particular species to inform assessments of the risk of Bluetongue virus outbreaks in this region.

Geomatics and EO Data to Support Wildlife Diseases Assessment at Landscape Level: A Pilot Experience to Map Infectious Keratoconjunctivitis in Chamois and Phenological Trends in Aosta Valley (NW Italy)

Geomatics and satellite remote sensing offer useful analysis tools for several technical-scientific fields. This work, with reference to a regional case of study, investigates remote sensing potentialities for describing relationships between environment and diseases affecting wildlife at landscape level in the light of climate change effects onto vegetation. Specifically, the infectious keratoconjunctivitis (IKC) of chamois (Rupicapra rupicapra L.) in Aosta Valley (NW Italy) was investigated at the regional level. IKC (Mycoplasma conjunctivae) is a contagious disease for domestic and wild ruminants (Caprinae and Ovinae). Two types of analysis were performed: one aimed at exploring by remotely sensed data phenological metrics (PMs) and evapotranspiration (ET) trends of vegetation in the area; one investigating the correlation between PMs and ET, versus IKC prevalence. The analysis was based on TERRA MODIS image time series ranging from 2000 to 2019. Ground data about IKC were available for a shorter time range: 2009–2019. Consequently, PMs and ET trend investigations were focused on the whole times range (2000–2019); conversely, correlation analysis was achieved with reference to the reduced 2009–2019 period. The whole study was based on freely available data from public archives. MODIS products, namely MOD13Q1 v.6 and MOD16A2, were used to derive PM and ET trends, respectively. Shuttle Radar Topography Mission (SRTM) Digital Terrain Model (DTM) was used to describe local topography; CORINE Land Cover map was adopted to describe land use classes. PMs and ET (as derivable from EO data) proved to significantly changed their values in the last 20 years, with a continuous progressive trend. As far as correlation analysis was concerned, ET and some PMs (specifically, End of Season (EOS) and Length of Season (LOS) proved significantly condition IKC prevalence. According to results, the proposed methodology can be retained as an effective tool for supporting public health and eco-pathological sectors. Specifically, it can be intended for a continuous monitoring of effects that climatic dynamics determine onto wild animals in the Alpine area, included diseases and zoonosis, moving future environmental management and planning towards the One Health perspective.

Local human movement patterns and land use impact exposure to zoonotic malaria in Malaysian Borneo

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement and space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges.

Achieving explanatory depth and spatial breadth in infectious disease modelling: Integrating active and passive case surveillance

Ideally, the data used for robust spatial prediction of disease distribution should be both high-resolution and spatially expansive. However, such in-depth and geographically broad data are rarely available in practice. Instead, researchers usually acquire either detailed epidemiological data with high resolution at a small number of active sampling sites, or more broad-ranging but less precise data from passive case surveillance. We propose a novel inferential framework, capable of simultaneously drawing insights from both passive and active data types. We developed a Bayesian latent point process approach, combining active data collection in a limited set of points, where in-depth covariates are measured, with passive case detection, where error-prone, large-scale disease data are accompanied only by coarse or remotely-sensed covariate layers. Using the example of malaria, we tested our method's efficiency under several hypothetical scenarios of reported incidence in different combinations of imperfect detection and spatial complexity of the environmental variables. We provide a simple solution to a widespread problem in spatial epidemiology, combining latent process modelling and spatially autoregressive modelling. By using active sampling and passive case detection in a complementary way, we achieved the best-of-both-worlds, in effect, a formal calibration of spatially extensive, error-prone data by localised, high-quality data.

Lyme Disease Risks in Europe under Multiple Uncertain Drivers of Change

BACKGROUND

Debates over whether climate change could lead to the amplification of Lyme disease (LD) risk in the future have received much attention. Although recent large-scale disease mapping studies project an overall increase in Lyme disease risk as the climate warms, such conclusions are based on climate-driven models in which other drivers of change, such as land-use/cover and host population distribution, are less considered.

OBJECTIVES

The main objectives were to project the likely future ecological risk patterns of LD in Europe under different assumptions about future socioeconomic and climate conditions and to explore similarity and uncertainty in the projected risks.

METHODS

An integrative, spatially explicit modeling study of the ecological risk patterns of LD in Europe was conducted by applying recent advances in process-based modeling of tick-borne diseases, species distribution mapping, and scenarios of land-use/cover change. We drove the model with stakeholder-driven, integrated scenarios of plausible future socioeconomic and climate change [the Shared Socioeconomic Pathway (SSPs) combined with the Representative Concentration Pathways (RCPs)].

RESULTS

The model projections suggest that future temperature increases may not always amplify LD risk: Low emissions scenarios (RCP2.6) combined with a sustainability socioeconomic scenario (SSP1) resulted in reduced LD risk. The greatest increase in risk was projected under intermediate (RCP4.5) rather than high-end (RCP8.5) climate change scenarios. Climate and land-use change were projected to have different roles in shaping the future regional dynamics of risk, with climate warming being likely to cause risk expansion in northern Europe and conversion of forest to agriculture being likely to limit risk in southern Europe.

CONCLUSIONS

Projected regional differences in LD risk resulted from mixed effects of temperature, land use, and host distributions, suggesting region-specific and cross-sectoral foci for LD risk management policy. The integrated model provides an improved explanatory tool for the system mechanisms of LD pathogen transmission and how pathogen transmission could respond to combined socioeconomic and climate changes. https://doi.org/10.1289/EHP4615.

Livestock host composition rather than land use or climate explains spatial patterns in bluetongue disease in South India

Culicoides-borne arboviruses of livestock impair animal health, livestock production and livelihoods worldwide. As these arboviruses are multi-host, multi-vector systems, predictions to improve targeting of disease control measures require frameworks that quantify the relative impacts of multiple abiotic and biotic factors on disease patterns. We develop such a framework to predict long term (1992-2009) average patterns in bluetongue (BT), caused by bluetongue virus (BTV), in sheep in southern India, where annual BT outbreaks constrain the livelihoods and production of small-holder farmers. In Bayesian spatial general linear mixed models, host factors outperformed landscape and climate factors as predictors of disease patterns, with more BT outbreaks occurring on average in districts with higher densities of susceptible sheep breeds and buffalo. Since buffalo are resistant to clinical signs of BT, this finding suggests they are a source of infection for sympatric susceptible sheep populations. Sero-monitoring is required to understand the role of buffalo in maintaining BTV transmission and whether they must be included in vaccination programs to protect sheep adequately. Landscape factors, namely the coverage of post-flooding, irrigated and rain-fed croplands, had weak positive effects on outbreaks. The intimate links between livestock host, vector composition and agricultural practices in India require further investigation at the landscape scale.

Spatial dynamics of a zoonotic orthohantavirus disease through heterogenous data on rodents, rodent infections, and human disease

Zoonotic diseases are challenging to study from the ecological point of view as, broadly speaking, datasets tend to be either detailed on a small spatial extent, or coarse on a large spatial extent. Also, there are many ways to assess zoonotic disease transmission systems, from pathogens to hosts to humans. We explore the complementarity of datasets considering the pathogen in its host, the host and human cases in the context of Puumala orthohantavirus infection in Germany. We selected relevant environmental predictors using a conceptual framework based on resource-based habitats. This framework assesses the functions, and associated environmental resources of the pathogen and associated host. A resource-based habitat framework supports variable selection and result interpretation. Multiplying ‘keyholes’ to view a zoonotic disease transmission system is valuable, but requires a strong conceptual framework to select and interpret environmental explanatory variables. This study highlights the usefulness of a structured, ecology-based approach to study drivers of zoonotic diseases at the level of virus, host, and human - not only for PUUV but also for other zoonotic pathogens. Our results show that human disease cases are best explained by a combination of variables related to zoonotic pathogen circulation and human exposure.

Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance

BACKGROUND

Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe.

METHODS

We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present.

RESULTS

The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups.

CONCLUSIONS

The duration periods with low or null adult activity can be derived from the associated monthly distribution maps, and it was also possible to identify and map areas with uncertain predictions. In the absence of ongoing vector surveillance, these maps can be used by veterinary authorities to classify areas as likely vector-free or as likely risk areas from southern Spain to northern Sweden with acceptable precision. The maps can also focus costly entomological surveillance to seasons and areas where the predictions and vector-free status remain uncertain.

Ecosystem change and zoonoses in the Anthropocene

Changes in land use, animal populations and climate, primarily due to increasing human populations, drive the emergence of zoonoses. Force of infection (FOI), which for these diseases is a measure of the ease with which a pathogen reaches the human population, can change with specific zoonoses and context. Here, we outline three ecosystem categories-domestic, peridomestic and sylvatic, where disease ecology alters the FOI of specific zoonoses. Human intervention is an overriding effect in the emergence of zoonoses; therefore, we need to understand the disease ecology and other influencing factors of pathogens and parasites that are likely to interact differently within ecological and cultural contexts. Planning for One Health and community ecology, such as an ecological impact assessment, is required to prepare and manage the emergence and impact of zoonoses in the Anthropocene.

Seroprevalence of Borrelia burgdorferi in Belgian forestry workers and associated risk factors

Background

As forest is the preferred environment for ticks, forestry workers are exposed to tick bites and tick-borne diseases. We assessed the seroprevalence of anti-Borrelia burgdorferi (Bb) antibodies and investigated, using an integrated landscape approach, the individual and environmental factors associated with the seroprevalence of Bb in Belgian forestry workers, a high-risk group in Belgium.

Methods

A group of 310 Belgian forest workers was examined to assess the seroprevalence of anti-Borrelia IgG antibodies. Using principal component analysis and binary logistic regression, the joint effects of individual characteristics and environmental characteristics were examined.

Results

Sixty-seven of the 310 workers were seropositive for Lyme disease (LD), leading to a seroprevalence of 21.6%. The seroprevalence was higher among forest workers visiting forests more frequently (P = 0.003) or who reported over 100 tick bites (P-value < 0.001). The intensity of tick bites and the use of protection measures against tick bites have a positive impact on LD seroprevalence while the quantity of shadow from trees at ground level had a negative one.

Conclusions

This study showed that forest workers are a population at risk for LD and, by extension, at risk for various tick-borne diseases. In addition to the role of the environment, our results also showed the importance of considering exposure when predicting the risk of infection by Bb.

Using Landscape Analysis to Test Hypotheses about Drivers of Tick Abundance and Infection Prevalence with Borrelia burgdorferi

Patterns of vector-borne disease risk are changing globally in space and time and elevated disease risk of vector-borne infection can be driven by anthropogenic modification of the environment. Incidence of Lyme disease, caused by the bacterium Borrelia burgdorferi sensu stricto, has risen in a number of locations in North America and this increase may be driven by spatially or numerically expanding populations of the primary tick vector, Ixodes scapularis. We used a model selection approach to identify habitat fragmentation and land-use/land cover variables to test the hypothesis that the amount and configuration of forest cover at spatial scales relevant to deer, the primary hosts of adult ticks, would be the predominant determinants of tick abundance. We expected that land cover heterogeneity and amount of forest edge, a habitat thought to facilitate deer foraging and survival, would be the strongest driver of tick density and that larger spatial scales (5-10 km) would be more important than smaller scales (1 km). We generated metrics of deciduous and mixed forest fragmentation using Fragstats 4.4 implemented in ArcMap 10.3 and found, after adjusting for multicollinearity, that total forest edge within a 5 km buffer had a significant negative effect on tick density and that the proportion of forested land cover within a 10 km buffer was positively associated with density of I. scapularis nymphs. None of the 1 km fragmentation metrics were found to significantly improve the fit of the model. Elevation, previously associated with increased density of I. scapularis nymphs in Virginia, while significantly predictive in univariate analysis, was not an important driver of nymph density relative to fragmentation metrics. Our results suggest that amount of forest cover (i.e., lack of fragmentation) is the most important driver of I. scapularis density in our study system.

Modelling and mapping tick dynamics using volunteered observations

BACKGROUND

Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014.

METHOD

Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT.

RESULTS

We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level.

CONCLUSIONS

This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

Landscape epidemiology in urban environments: The example of rodent-borne Trypanosoma in Niamey, Niger

Trypanosomes are protozoan parasites found worldwide, infecting humans and animals. In the past decade, the number of reports on atypical human cases due to Trypanosoma lewisi or T. lewisi-like has increased urging to investigate the multiple factors driving the disease dynamics, particularly in cities where rodents and humans co-exist at high densities. In the present survey, we used a species distribution model, Maxent, to assess the spatial pattern of Trypanosoma-positive rodents in the city of Niamey. The explanatory variables were landscape metrics describing urban landscape composition and physiognomy computed from 8 land-cover classes. We computed the metrics around each data location using a set of circular buffers of increasing radii (20m, 40m, 60m, 80m and 100m). For each spatial resolution, we determined the optimal combination of feature class and regularization multipliers by fitting Maxent with the full dataset. Since our dataset was small (114 occurrences) we expected an important uncertainty associated to data partitioning into calibration and evaluation datasets. We thus performed 350 independent model runs with a training dataset representing a random subset of 80% of the occurrences and the optimal Maxent parameters. Each model yielded a map of habitat suitability over Niamey, which was transformed into a binary map implementing a threshold maximizing the sensitivity and the specificity. The resulting binary maps were combined to display the proportion of models that indicated a good environmental suitability for Trypanosoma-positive rodents. Maxent performed better with landscape metrics derived from buffers of 80m. Habitat suitability for Trypanosoma-positive rodents exhibited large patches linked to urban features such as patch richness and the proportion of landscape covered by concrete or tarred areas. Such inferences could be helpful in assessing areas at risk, setting of monitoring programs, public and medical staff awareness or even vaccination campaigns.

Integrated epidemiology for vector-borne zoonoses

The development and application of interventions for the control of vector-borne zoonoses requires broad understanding of epidemiological linkages between vector, animal infection and human infection. However, there are significant gaps in our understanding of these linkages and a lack of appropriate data poses a considerable barrier to addressing this issue. A move towards strengthened surveillance of vectors and disease in both animal and human hosts, in combination with linked human-animal surveys, could form the backbone for epidemiological integration, enabling explicit assessment of the animal-human (and vector) interface, and subsequent implications for spill-over to human populations. Currently available data on the spatial distribution of human African trypanosomiasis allow an illustrative example.

Climate-driven longitudinal trends in pasture-borne helminth infections of dairy cattle

Helminth parasites of grazing ruminants are highly prevalent globally and impact negatively on animal productivity and food security. There is a growing concern that climate change increases helminth disease frequency and intensity. In Europe, these concerns stem from case reports and theoretical life cycle models assessing the effects of climate change scenarios on helminth epidemiology. We believe this study is the first to investigate climate-driven trends in helminth infections of cattle on a cohort of randomly selected farms. One thousand, six hundred and eighty dairy farms were monitored over an 8year period for the two major helminth infections in temperate climate regions and climate-driven trends were investigated by multivariable linear mixed models. The general levels of exposure to Fasciola hepatica decreased over the study period while those to Ostertagia ostertagi increased, and this could at least be partially explained by meteorological factors (i.e. the number of rainy (precipitation >1mm) and warm days (average daily temperature >10°C) in a year). The longitudinal trends varied according to the altitude and the agricultural region of the farm. This study shows that longitudinal epidemiological data from sentinel farms combined with meteorological datasets can significantly contribute to understanding the effects of climate on infectious disease dynamics. When local environmental conditions are taken into account, the effects of climate change on disease dynamics can also be understood at more local scales. We recommend setting up a longitudinal sampling strategy across Europe in order to monitor climate-driven changes in helminth disease risk to inform adaptation strategies to promote animal health and productivity.

Plasmodium knowlesi transmission: integrating quantitative approaches from epidemiology and ecology to understand malaria as a zoonosis

The public health threat posed by zoonotic Plasmodium knowlesi appears to be growing: it is increasingly reported across South East Asia, and is the leading cause of malaria in Malaysian Borneo. Plasmodium knowlesi threatens progress towards malaria elimination as aspects of its transmission, such as spillover from wildlife reservoirs and reliance on outdoor-biting vectors, may limit the effectiveness of conventional methods of malaria control. The development of new quantitative approaches that address the ecological complexity of P. knowlesi, particularly through a focus on its primary reservoir hosts, will be required to control it. Here, we review what is known about P. knowlesi transmission, identify key knowledge gaps in the context of current approaches to transmission modelling, and discuss the integration of these approaches with clinical parasitology and geostatistical analysis. We highlight the need to incorporate the influences of fine-scale spatial variation, rapid changes to the landscape, and reservoir population and transmission dynamics. The proposed integrated approach would address the unique challenges posed by malaria as a zoonosis, aid the identification of transmission hotspots, provide insight into the mechanistic links between incidence and land use change and support the design of appropriate interventions.

Forest classes and tree cover gradient: tick habitat in encroached areas of southern Norway

Forest, in particular deciduous forest, is a key element in determining areas with a high probability of tick presence. The way forest is generally monitored may be ill suited to some landscapes where Ixodes ricinus is found, as forest is usually characterised using crisp land cover classes. However, tree vegetation can be found outside of forests and continuous gradations of tree density can be found in a variety of landscapes. In this paper we investigate the probability of tick presence in southern Norway using landscape description based both on land cover classes and continuous data describing the tree cover fraction. Both perspectives on the landscape are significant in the logistic model, indicating that the usual approach based solely on land cover classes may not be comprehensive enough in capturing tick habitat, and characterising the landscape with variables focused on single specific elements may be insufficient.

Prevalence and distribution of exposure to Schmallenberg virus in Irish cattle during October 2012 to November 2013

Background

Schmallenberg virus (SBV) was first identified in November 2011. It is a novel Orthobunyavirus (family Bunyaviridae) whose main ill effect is congenital malformation of the musculoskeletal and central nervous systems. It is borne by Culicoides spp., and has spread extensively in western Europe. The first case of SBV in Ireland was diagnosed in October 2012. It was anticipated that once the virus emerged in Ireland that there would be wide scale or nationwide spread over the course of the 2013 vector season. The objectives of this study were to determine the seroprevalence and distribution of exposure to Schmallenberg virus in Irish cattle from November 2012 to November 2013.

Methods

Samples of brain for the pathology based surveillance were collected from malformed bovine and ovine foetuses submitted for post mortem examination. These samples were tested for SBV using RT-qPCR. Three serological surveys were carried out on sera submitted for the national brucellosis eradicartion programme. A spatial analysis of both sets of data was carried out.

Results

Between October 2012 and 10th May 2013, SBV was confirmed by RT-qPCR in brain tissues from malformed foetuses obtained from 49 cattle herds and 30 sheep flocks in Ireland. In national serosurveys conducted between November 2012 until November 2013 the herd-level and animal-level SBV seroprevalences in cattle were 53 and 36 % respectively for the first survey, 51 and 35 % for the second survey and 53 and 33 % for the third survey. The herd level seroprevalence in counties ranged from 0 to 100 %, with the counties in the south and southeast having the highest seroprevalence (>50 %), the midlands a moderate herd level seroprevalence (10–50 %) while northern and north western counties had a low herd level seroprevalence (0–10 %). There was close spatial agreement between the results of the two different targeted surveillance strategies.

Conclusions

At the end of the 2012 vector season, there was widespread exposure to SBV among herds in southern and south eastern Ireland. During 2013, there was little or no evidence of further outward spread, unlike the situation in several other European countries. Given the lack of evidence for circulation of the virus since 2012, it is likely that the younger age cohort in herds previously exposed to SBV and substantial proportions of animals of all ages on the margins of affected areas are immunologically naïve to SBV, and would be susceptible to infection if the virus were to re-emerge.