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The last two decades have witnessed a complete shift in our perception of the deep sea, from a homogeneous, mostly muddy and unspoiled seafloor to a vast patchwork of diverse and fragile habitats as well as a reservoir of living resources, both energy and mineral. Growing and concomitant awareness of the potential for blue growth and vulnerability of deep-sea ecosystems triggered the implementation of management measures and Marine Spatial Planning (MSP) at national, regional and international levels, which are now cumulating in the UN Decade of Ocean Science for Sustainable Development and the International Conference on Marine Biodiversity of Areas Beyond National Jurisdiction (ABNJ). Based on the best available knowledge collated and produced in the framework of ATLAS, the objective of the present deliverable was to integrate all available data into a common analytical framework for systematic conservation planning at the scale of the North Atlantic. Regional-scale MSP in the deep sea unfortunately suffers from a lack of knowledge on the distribution of species and habitats. Such large-scale endeavours to date have thus been mainly relying on biogeochemical and physiographic proxies to design networks of marine protected areas. In just three years, ATLAS has taken an unprecedented step forward in synthesising the data available for the North Atlantic on the distribution of the most vulnerable deep-sea habitats where fragile and long-lived engineering species, such as corals and sponges, are aggregating. Such a synthesis has been enabled through trans-Atlantic collaboration. The 13 case studies (CS), evenly distributed from north to south and east to west of the northern Atlantic, provided new discoveries of deep-sea vulnerable habitats off Greenland, in the Alboran Sea and the Gulf of Cádiz, as well as on Formigas and Tropic seamounts. Beyond new discoveries, ATLAS CS confirmed and improved knowledge on the distribution, ecology and functionality of those vulnerable habitats in the North Atlantic. For Case Study 1 – LoVe Observatory, 1417 records of Lophelia pertusa coral reefs along the Norwegian coast are included. For Case Study 6 - Bay of Biscay, a total of 450 records of 12 different VME types, including coral reefs, coral rubbles, scleractinians, Antipatharians, gorgonians, seapens or pennatulids, mixed corals, aggregation of actiniarians, sponge community and Xenophyophores, are reported. For Case Study 7, VMEs are reported for two areas: 1) for Seco de los Olivos, in the Alboran Sea, 17 VMEs that include sea pen fields, deep-sea sponge aggregations and diverse coral gardens are reported, and 2) for the Volcano of Gazul, in the Gulf of Cádiz, 16 VMEs are reported, that include diverse coral gardens, mud and sand emergent fauna, cold-water coral reef of Lophelia pertusa / Madrepora oculata and deep-sea sponge aggregations. For Case Study 8, VMEs from different areas of the Azores are included: in the Formigas Seamount, 18 VMEs including diverse coral gardens and deep-sea sponge aggregations are reported. Cavalo Seamount, a ridge on the Mid-Atlantic Ridge, Gigante Seamount, Condor Seamount, Dom João de Castro Seamount, and Mar de Prata Seamount also host various coral gardens; the South of Pico Island hosts a deep-sea sponge aggregation of Pheronema carpenteri. The newly discovered Hydrothermal Vent Luso is also reported as a VME for the Azores. For Case Study 10 – Davis Strait, Eastern Arctic, 8 VME areas of deep-sea sponges, 5 VME areas of large gorgonian corals, 4 of small gorgonian corals and 13 of sea pens are reported. Under Case Study 10, the only known Lophelia pertusa reef in Greenland waters is also reported. For Case Study 11 – Flemish Cap, three VME types were identified by the Northwest Atlantic Fisheries Organization (NAFO) and for each, several VME areas are reported: 13 VME areas for sponges, 6 for sea pens and 7 for large gorgonians. For Case Study 12 - Mid-Atlantic Canyons and SE USA, four VMEs are included: 1) Cape Lookout Coral Banks, dominated by large bioherms built by Lophelia pertusa, 2) Hatteras Middle Slope, a physically and biologically unique area of rugged mini-canyons (composed of consolidated muds), 3) Norfolk Canyon, and 4) Baltimore Canyon and vicinities, two rugged submarine canyons that contain extensive cold-water corals. For Case Study 13 - Tropic Seamount is host to multiple VMEs, including dense patches of reef framework-forming scleractinian, dense aggregations of coral gardens, dense monospecific sponge ground of Poliopogon amadou, mixed deep-sea sponge aggregations, Xenophyophore field, and dense crinoid fields.Knowledge gained from ATLAS CS significantly increases the database of vulnerable marine ecosystem (VME) occurrences in the northern Atlantic but the species that define VMEs have been known about for over a century. In order to get an overview of the distribution of VMEs, data coming from sources as various as historical cruises, by-catch of fisheries surveys and Remotely Operated Vehicle (ROV) surveys must be compiled. The reliability of these data however varies and a confidence index has thus been developed in order to objectively and quantitatively rank the reliability of VME records according to the source of records. The ranking ranges from low, for inferred records, to high, for visually assessed records. In addition, not all VMEs equally meet the criteria of rarity, functional significance, fragility and recovery, which vary according to taxa and the abundance of indicator taxa. A VME index has thus been developed to quantitatively and objectively score the vulnerability of VME records. The VME index and the confidence index have been applied to the records of the VME database created and curated by the joint ICES/NAFO Working Group on Deep-water Ecology (WGDEC). This spatial grid of VME likelihood was completed with the unequivocal VMEs mapped in the ATLAS CS. In general, the VME index provides a simplified, spatially aggregated and weighted estimate of the degree to which an area could be considered to contain VMEs under the Food and Agriculture Organisation of the UN (FAO) definition. The VME index clearly highlights areas where a VME is more likely to occur while the associated estimate of confidence gives an indication of how (un)certain that assessment is. The methodology is transparent, science based and data driven, and the aggregate cells can be explored in greater detail to reveal the individual data points that have contributed to the assessment. It integrates far more information than previous methods and as such, better captures the underlying reasoning for identifying VME areas or benthic deep-sea Ecologically or Biologically Significant Marine Areas (EBSAs). The VME index is expected to be updated each year as new data are submitted and will therefore provide an up to date, repeatable and defensible source upon which to base advice as new information is received. The VME index appears to capture most of the important elements of the VME database. This methodology may be considered as a first step towards a systematic approach for the identification and protection of VMEs and EBSAs in the North Atlantic. Our methodology clearly considered several of the steps proposed by Ardron et al. (2014), namely step 1 on assessing potential VME indicator taxa and habitats in a region, step 3 on considering areas already known for their ecological importance, step 4 on compiling information on the distributions of likely VME indicator species and habitats, step 6 on considering fishing impacts, and step 8 on identify ecologically important areas. However, at least one important aspect of the Ardron et al. (2014) framework is missing in the current VME index which refers to understanding the natural distribution of VMEs before significant impacts occurred. This aspect could be considered in future improvements of the VME index to encompass predicted distribution of VME as discussed in Vierod et al. (2014) and Anderson et al. (2016b). Systematic conservation planning is an explicit, objective-based and quantitative approach for allocating areas for biodiversity conservation, for instance used in Marine Protected Area (MPA) networks design process. It aims to identify priority areas answering specific conservation objectives for each considered species or habitat, whilst minimising the socioeconomic costs of conservation over the study area. For the purpose of systematic conservation planning, data on known or inferred VMEs are still too sparse at the scale of the northern Atlantic. The spatial prioritisation developed here aimed to identify zones of conservation importance for seabed species and habitats associated with VMEs in a comprehensive approach, by complementing the records of unequivocal VMEs and the VME likelihood over the basin resulting from the VME index with supplementary information targeting deep-sea species and habitats. ATLAS modelled the present and future distributions of six coral species indicators of VMEs as well as six exploited fish species (D3.3). Through a collaboration with the H2020 Blue Growth SponGES project, the present and future distribution of one sponge species have also been modelled to provide maps of the distribution of key VME indicator taxa with different environmental requirements, life-history strategies and functional significance. The overlap between the present and future distribution of these species under climate change scenarios furtherallowed the mapping of their future climate refugia, constituting resilient areas that were given a high conservation target in simulations. Although the primary focus of ATLAS is on cold-water corals, there is more at stake in terms of conversation in the northern Atlantic. In order to increase the scope of this systematic conservation planning exercise, chemosynthetic ecosystems that qualify as VMEs as well as large physiographic features known to be functional hotspots such as canyons, seamounts and fracture zones have also been considered. Conservation scenarios integrated current management and human activities aspects over the basin, to combine the conservation and socioeconomic stakes during the prioritisation process. While areas already profiting from conservation designations such as fishing closures, MPAs and EBSAs were favoured, areas situated in major bottom-fishing grounds or within deep-sea mining contracts were penalised. In order to suggest a geographically balanced protection network, conservation objectives were replicated within 13 provinces, which considered the main biogeographic and geographical boundaries over the basin as well as a dissociation between broad shallow (800m) habitats. This regionalisation approach ensured a regional replication and representativity of each conservation feature within the main deep-sea biotopes. Finally, this work addressed benthic connectivity aspects, by using the results of larvae drift models to favour connected networks of conservation as best as possible. Emerging from an incremental scenario complexification process, the final simulation (“all management”, Figure 1) resulted in an ecologically coherent conservation network that gave insight into spatial planning possibilities to better protect seabed vulnerable habitats and species. In particular, continental margin slopes, the Mid-Atlantic Ridge, and shelf areas comporting fishing grounds appeared as crucial zones for preserving deep-sea biodiversity (Figure 1). These identified areas comprised of specific habitats (e.g. canyons, ridges, seamounts), concentrating diverse substrates and representing key areas for nutrient circulation, that sustain VMEs and deep-water fish. Even if their depth range is larger, most of the VME indicator taxa used in this study largely occur between 500 and 2500m depths, which were prioritised here. For some species, including gorgonians (Acanella arbuscula, Acanthogorgia armata), scleratinian coral (Lophelia pertusa) and the sponge species (Geodia barretti), future climate refugia are almost exclusively predicted along margin slopes (ATLAS D3.3), that appeared as the most prioritised areas in conservation scenarios. In addition, the Mid-Atlantic Ridge concentrates sites of hydrothermal activity, giving rise to unique chemosynthetic ecosystems. As all known hydrothermal vents south of the Azores Exclusive Economic Zone (EEZ), but also several other VMEs, are located in areas already pre-empted for massive sulphide exploration, these latter contained substantial conservation potential. Identified conservation areas situated within the International Seabed Authority (ISA) contracts could inform the regional management plan to be implemented for preserving the Mid-Atlantic Ridge biodiversity from adverse mining impacts. Finally, the prioritisation results suggest that conservation objectives, especially for demersal fish species, could not be achieved without including large fished areas situated on shelves. This result may promote the development of conservation measures on fishing grounds, from full closures for the most efficient, to species-based catch limitation or minimum fish size. The implementation of such restrictions in EEZs or Regional Fisheries Management Organisations (RFMOs) regulatory areas in Areas Beyond National Jurisdictions (ABNJs) would also contribute to fisheries’ sustainability objectives.Selecting the most prioritised planning units allowed delineation of the main priority areas for deep-sea conservation (Figure 2). Covering approximatively 17% of the study area, these priority areas would answer a relatively high conservation goal for the deep sea, nonetheless they suffer from poor conservation at the moment (Figure 2). Less than 1% of the study area falls into fishing closures and marine reserves that already protect the priority areas for benthic deep-sea ecosystems. For instance, only a few unequivocal VMEs, species climate refugia or canyons currently benefit from some form of protection. In that respect, our systematic planning exercise has shown that, as important as they are, the sum of all Area-Based Management Tools (ABMTs) of the northern Atlantic still suffer from a lack of conservation efficiency, representativity and viability. Moreover, our results highlighted that a more continuous conservation network, displaying corridors or shorter distances between conservation areas, would lead to a more connected and thus more resilient benthic conservation framework. Ultimately, climate change pressures are likely to largely affect deep-sea oceanography and biodiversity, and the ability of current ABMTs to preserve them. Protecting the priority areas herein identified, which hold substantial resilience potential to future environmental changes through the central place of climate refugia in scenarios, could promote the long-term viability of the deep-sea conservation for the North Atlantic.To our knowledge, this study is the first in systematic conservation planning to address the conservation of deep-sea benthic and demersal biodiversity across a whole oceanic basin. These results contribute to the development of systematic approaches for large scale MSP, such as the conservation management of ABNJs currently the object of ongoing international discussions. Lacking of a coordinated framework as well as efficient, permanent and recognised protection measures, the North-Atlantic high seas conservation network could benefit from the suggestions provided by our scientific evaluation. Finally, this basin scale prioritisation will provide general material for local conservation, through a transfer to the MSP work implemented for ATLAS case studies in ATLAS Work Package 6.&nbsp

1. The rapid growth of species distribution modelling (SDM) as an ecological discipline has resulted in a large and diverse set of methods and software for constructing and evaluating SDMs. The disjointed nature of the current SDM research environment hinders evaluation of new methods, synthesis of current knowledge and the dissemination of new methods to SDM users. 2. The zoon r package aims to overcome these problems by providing a modular framework for constructing reproducible SDM workflows. zoon modules are interoperable snippets of r code, each carrying a SDM method that zoon combines into a single analysis object. 3. Rather than defining these modules, zoon draws modules from an open, version-controlled online repository. zoon makes it easy for SDM researchers to contribute modules to this repository, enabling others to rapidly deploy new methods in their own workflows or to compare alternative methods. 4. Each workflow object created by zoon is a rerunnable record of the data, code and results of an entire SDM analysis. This can then be easily shared, scrutinised, reproduced and extended by the whole SDM research community. 5. We explain how zoon works and demonstrate how it can be used to construct a completely reproducible SDM analyses, create and share a new module, and perform a methodological comparison study.

Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014–16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD’s incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.

Background During the Millennium Development Goal (MDG) era, many countries in Africa achieved marked reductions in under-5 and neonatal mortality. Yet the pace of progress substantially varied at the national level, further demonstrating a vital need to track even more localised trends in child mortality. With the adoption of the Sustainable Development Goals (SDGs) in 2015, which established ambitious targets for improving child survival by 2030, optimal intervention planning and targeting will require understanding past trends and rates of progress at a higher spatial resolution. Methods We assembled 215 geographically-resolved data sources on child deaths to produce 5x5 kilometre (km) estimates of under-5 and neonatal mortality in 46 African countries for 2000, 2005, 2010, and 2015. We used a Bayesian geostatistical analytic framework to generate these estimates, and implemented a predictive validity tests. Last, we aggregated these 5x5 km estimates to two subnational administrative levels to maximise the policy utility of these results. Findings Amid improving child survival in Africa, substantial heterogeneity was found in terms absolute levels of under-5 and neonatal mortality in 2015 and the annualised rates of decline achieved from 2000 to 2015. Subnational areas in countries such as Botswana, Egypt, and Ethiopia recorded some of the largest decreases in child mortality rates since 2000, positioning them well to achieve SDG targets by or prior to 2030. Yet these geographies were the exception for Africa: to achieve SDG 3.2 for under-5 mortality by 2030, most of the continent – particularly in central and western Africa – must at least double the pace at which mortality rates fell between 2000 and 2015. Interpretation In the absence of unprecedented political commitment, financial support, and medical advances, the viability of SDG 3.2 achievement in Africa is precarious at best. By producing child mortality rates at multiple levels of geospatial resolution over time, our study offers decision-makers a powerful set of tools for targeting interventions to populations in the greatest need. In an era where precision public health increasingly has the potential to transform the design, implementation, and impact of health programs, our 5x5 km estimates of child survival in Africa provide a vital baseline against which local, national, and global stakeholders can map the pathways for ending preventable child deaths by 2030.

Background Substantial outbreaks of yellow fever in Angola and Brazil in the past 2 years, combined with global shortages in vaccine stockpiles, highlight a pressing need to assess present control strategies. The aims of this study were to estimate global yellow fever vaccination coverage from 1970 through to 2016 at high spatial resolution and to calculate the number of individuals still requiring vaccination to reach population coverage thresholds for outbreak prevention. Methods For this adjusted retrospective analysis, we compiled data from a range of sources (eg, WHO reports and health-service-provider registeries) reporting on yellow fever vaccination activities between May 1, 1939, and Oct 29, 2016. To account for uncertainty in how vaccine campaigns were targeted, we calculated three population coverage values to encompass alternative scenarios. We combined these data with demographic information and tracked vaccination coverage through time to estimate the proportion of the population who had ever received a yellow fever vaccine for each second level administrative division across countries at risk of yellow fever virus transmission from 1970 to 2016. Findings Overall, substantial increases in vaccine coverage have occurred since 1970, but notable gaps still exist in contemporary coverage within yellow fever risk zones. We estimate that between 393·7 million and 472·9 million people still require vaccination in areas at risk of yellow fever virus transmission to achieve the 80% population coverage threshold recommended by WHO; this represents between 43% and 52% of the population within yellow fever risk zones, compared with between 66% and 76% of the population who would have required vaccination in 1970. Interpretation Our results highlight important gaps in yellow fever vaccination coverage, can contribute to improved quantification of outbreak risk, and help to guide planning of future vaccination efforts and emergency stockpiling.

Cruise JC136 is associated with a NERC joint standard research grant (NE/K011855/1 and NE/K013513/1) entitled “Influence of population connectivity on depth-dependent diversity of deep-sea marine benthic biota”. The aims of this project are to investigate connectivity among deep-sea populations at different depths and spatial scales using: 1) larval dispersal modelling using Lagrangian particle tracking, driven by hydrographic models, 2) population genetics/genomics, and 3) benthic community analysis. The aims of cruise JC136 were then to sample a range of sites and depth bands to: 1. obtain physical samples of 4 model organisms for molecular analysis, 2. gather benthic biological survey data for community level analysis, 3. collect oceanographic data to validate high resolution oceanographic models with which we will model larval dispersal. We visited 5 sites in the NE Atlantic (Rockall Bank, George Bligh Bank, Anton Dohrn Seamount, Wyville-Thomson Ridge, and Rosemary Bank) undertaking 27 ROV dives, 12 AUV missions, 43 CTD casts, 2 mooring deployments and equipment trials. All cruise aims were broadly met. We obtained 3630 biological samples, including sufficient depth and site coverage for molecular analysis of 3 target species. We obtained video transect data with sufficient replication and depth stratification from 3 sites and near complete sampling from a 4th. We obtained sufficient oceanographic data to validate our models. In addition, we gathered 5811.66 km2 of seafloor multibeam to contribute to ongoing efforts to map the North Atlantic, including the first multibeam from the Geike Slide and Hebridean Slope Nature Conservation Marine Protected Area (NCMPA). Poor visitbility at the seabed prevented a planned resurvey of the Darwin Mounds Marine Protected Area (MPA) (see JC60).

Background: Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne infection caused by a virus (CCHFV) from the Bunyaviridae family. Domestic and wild vertebrates are asymptomatic reservoirs for the virus, putting animal handlers, slaughter-house workers and agricultural labourers at highest risk in endemic areas, with secondary transmission possible through contact with infected blood and other bodily fluids. Human infection is characterized by severe symptoms that often result in death. While it is known that CCHFV transmission is limited to Africa, Asia and Europe, definitive global extents and risk patterns within these limits have not been well described. Methods:We used an exhaustive database of human CCHF occurrence records and a niche modeling framework to map the global distribution of risk for human CCHF occurrence. Results: A greater proportion of shrub or grass land cover was the most important contributor to our model, which predicts highest levels of risk around the Black Sea, Turkey, and some parts of central Asia. Sub-Saharan Africa shows more focalized areas of risk throughout the Sahel and the Cape region. Conclusions: These new risk maps provide a valuable starting point for understanding the zoonotic niche of CCHF, its extent and the risk it poses to humans., SCOPUS: ar.j, info:eu-repo/semantics/published

Background: Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination by 2020 and to guide elimination efforts countries have, in recent years, conducted extensive mapping surveys. Documenting the past and present distribution of LF and its environmental limits is important for a number of reasons. Here, we present an initiative to develop a global atlas of LF and present a new global map of the limits of LF transmission. Methods: We undertook a systematic search and assembly of prevalence data worldwide and used a suite of environmental and climatic data and boosted regression trees (BRT) modelling to map the transmission limits of LF. Results: Data were identified for 66 of the 72 countries currently endemic and for a further 17 countries where LF is no longer endemic. Our map highlights a restricted and highly heterogeneous distribution in sub-Saharan Africa, with transmission more widespread in West Africa compared to east, central and southern Africa where pockets of transmission occur. Contemporary transmission occurs across much of south and South-east Asia and the Pacific. Interestingly, the risk map reflects environmental conditions suitable for LF transmission across Central and South America, including the southern States of America, although active transmission is only known in a few isolated foci. In countries that have eliminated LF, our predictions of environmental suitability are consistent with historical distribution. Conclusions: The global distribution of LF is highly heterogeneous and geographically targeted and sustained control will be required to achieve elimination. This first global map can help evaluate the progress of interventions and guide surveillance activities.

Cruise JC136 is associated with a NERC joint standard research grant (NE/K011855/1 and NE/K013513/1) entitled “Influence of population connectivity on depth-dependent diversity of deep-sea marine benthic biota”. The aims of this project are to investigate connectivity among deep-sea populations at different depths and spatial scales using: 1) larval dispersal modelling using Lagrangian particle tracking, driven by hydrographic models, 2) population genetics/genomics, and 3) benthic community analysis. The aims of cruise JC136 were then to sample a range of sites and depth bands to: 1. obtain physical samples of 4 model organisms for molecular analysis, 2. gather benthic biological survey data for community level analysis, 3. collect oceanographic data to validate high resolution oceanographic models with which we will model larval dispersal. We visited 5 sites in the NE Atlantic (Rockall Bank, George Bligh Bank, Anton Dohrn Seamount, Wyville-Thomson Ridge, and Rosemary Bank) undertaking 27 ROV dives, 12 AUV missions, 43 CTD casts, 2 mooring deployments and equipment trials. All cruise aims were broadly met. We obtained 3630 biological samples, including sufficient depth and site coverage for molecular analysis of 3 target species. We obtained video transect data with sufficient replication and depth stratification from 3 sites and near complete sampling from a 4th. We obtained sufficient oceanographic data to validate our models. In addition, we gathered 5811.66 km2 of seafloor multibeam to contribute to ongoing efforts to map the North Atlantic, including the first multibeam from the Geike Slide and Hebridean Slope Nature Conservation Marine Protected Area (NCMPA). Poor visitbility at the seabed prevented a planned resurvey of the Darwin Mounds Marine Protected Area (MPA) (see JC60).

West Nile virus (WNV) is a mosquito borne arbovirus that circulates within avian reservoirs. WNV can spill over into humans and Equidae that are dead-end hosts for WNV but suffer fever, acute morbidity and sometimes death. Outbreaks of WNV are common across Africa and Eastern Europe, and there have also been sporadic outbreaks in Spain and the Camargue Regional Park in France, but never in Great Britain (GB). These areas all fall along a major bird migration route. In this study, we analyse a scenario in which WNV is circulating in the Camargue or in other wetland areas in France and we estimate the risk of northward migrating passerine birds stopping in a WNV hotspot, becoming infected and carrying active infection to GB. If the disease were circulating in the Camargue during a single migratory season, the probability that one or more migrating birds becomes infected and lands in GB whilst still infected is 0.881 with 0.384 birds arriving in areas of suitable vector habitat. However, if WNV became established in the Grand Brière National Park or La Brenne Regional Park wetland areas further to the north, the model predicts that at least one infected bird will continue to GB. Thus, GB is at risk of WNV introduction from the Camargue, but the risk is considerably greater if WNV were to circulate further north than its previous focus in France, but this is highly sensitive to the force of infection in the infected area. However, the risk of establishment and infection of humans in GB is dependent upon a number of additional factors, in particular the vector and epidemiological situation in GB.

BACKGROUND: Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease's contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies. METHODS: We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide. FINDINGS: Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur. INTERPRETATION: Our results provide the evidence base for targeting vaccination campaigns within risk zones, as well as emphasising their high effectiveness. Our study highlights areas where public health authorities should be most vigilant for potential spread or importation events. FUNDING: Bill & Melinda Gates Foundation.

Public health surveillance data are often incomplete, particularly where resources are lacking, but geospatial models can help to fill the gaps by providing estimates where data are sparse. By combining information on locations where diseases have been recorded with geographic data on environmental and socioeconomic covariates known to affect disease transmission using machine-learning models (such as boosted regression trees), niche modelling can generate fine-resolution, evidence-based risk maps for a variety of diseases of public health importance. This thesis investigates the geographical distribution of two vector-borne, zoonotic diseases of public health importance: Plasmodium knowlesi malaria and yellow fever (YF). A number of new methodological approaches to niche modelling are developed for: mapping diseases whose distributions are impacted by multiple host and vector species, ameliorating spatial bias in disease reporting rates, and accounting for human vaccination coverage. Chapter 2 investigates spatial variation in risk of human P. knowlesi infection across Southeast Asia. The infection risk model for P. knowlesi malaria is based on improvements to a standard niche modelling approach, and incorporates a novel joint distribution model to leverage data from a number of host species. Chapter 3 estimates YF vaccination coverage through time across all age cohorts in every district/municipality of countries at risk of YF, globally. These estimates are used to estimate the additional vaccination coverage needed to prevent further YF outbreaks, and they provide information needed to account for population immunity when estimating YF infection risk. Chapter 4 describes the development of a novel Poisson point process niche model, which is then used to predict YF infection risk in humans and demonstrates how vaccination coverage can be efficiently accounted for in disease niche models. The disease risk maps of P. knowlesi malaria and YF produced through this thesis will act as resources to improve the targeting, implementation and evaluation of disease prevention, surveillance and control strategies. Methods developed to account for vaccination coverage, reporting rate biases, and complex transmission systems will be applicable to risk mapping for a range of vector-borne, zoonotic diseases of public health importance.