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SI for From Serological Surveys to Disease Burden: A Modelling Pipeline for Chagas Disease

This work is a collaboration between BioRISC (the Biosecurity Research Initiative at St Catharine’s College, Cambridge), Conservation Evidence based in the Department of Zoology, University of Cambridge and the Centre for the Study of Existential Risk. It was created by documenting our experience of options, consulting guidance, contacting people working in different countries to explore the range of options and crowd-sourcing ideas through social media. We welcome suggestions for options missed (especially those implemented outside of the UK), innovations for novel options or means of improving existing options. Please contact biorisc@caths.cam.ac.uk. You can also view the list of options on the BioRISC website (https://covid-19.biorisc.com/) or customise the list yourself using this app we developed (https://alecchristie888.shinyapps.io/Covid_19_options/).

Additional file 1.

Funder: Alborada Trust, The Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife-human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host-pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread.

This work provides compact representations for single- and multi-robot motion planning in the context of prehensile robot manipulation. This work describes the asymptotic near-optimality and probabilistic near-optimality properties of these planners. Probabilistic near-optimality is leveraged to provide practical and grounded stopping criteria for these methods which probabilistically guarantee the methods return high-quality paths. It is also shown how these methods can be leveraged to produce a compact planning representation, which is a lightweight structure that is quick to query and easy to store. The work also outlines a compact representation for solving multi-arm manipulation tasks, and integrates a scalable, asymptotically optimal multi-robot motion planning method to provide scalable, globally asymptotically optimal task and motion planning in manipulation domains.

Details of models

Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats and (iv) reservoir competence of host species and pathogenicity for humans of different genotypes of Borrelia burgdorferi. Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host–vector-borne zoonotic disease.This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Non-invasive surveys for primate malarias. Raw data from studies that quantified Plasmodium detection from non-invasive samples.

Optimal storage techniques. Data on DNA yield from faecal samples stored with four different protocols that varied in temperature and media.

Citizenship, as a concept, is about the rights and duties of individuals (usually) in a given political territory (e.g., the state). In its participatory guises, it is normally associated with activity in the public sphere, and it may or not entail the cultivation and exercise of certain virtues. It is the specific design of this general architecture that gives us what we might call «adjectival citizenships» -e.g., liberal citizenship, republican citizenship, cosmopolitan citizenship-. Each of these types of citizenship interprets the architecture in different ways. So liberal citizenship tends to focus more on rights than on duties, republican citizenship speaks in the language of duty and of virtue, and cosmopolitan citizenship calls into question the territorial underpinnings of both these types of citizenship. This article explores the way in which ecological citizenship fills out the architecture of citizenship, before outlining the importance of ecological citizenship to the project of achieving sustainable development.La ciudadanía, como concepto, trata de los derechos y los deberes de los individuos (normalmente), y en un territorio político determinado (por ejemplo, un Estado). Bajo su vertiente participativa, la ciudadanía está normalmente asociada con la esfera pública, y puede suponer o no el cultivo y ejercicio de ciertas virtudes. El diseño específico de la arquitectura general del concepto de ciudadanía nos define lo que podríamos llamar «ciudadanías adjetivas» -por ejemplo, la ciudadanía liberal, la ciudadanía republicana o la ciudadanía cosmopolita-. Cada uno de estos tipos de ciudadanía interpreta la arquitectura de diferente manera. Así, la ciudadanía liberal tiende a centrarse más en los derechos que en los deberes, la ciudadanía republicana habla en el lenguaje del deber y la virtud, y la ciudadanía cosmopolita cuestiona los argumentos territoriales de los otros dos tipos de ciudadanía. Este artículo explora el modo en que la ciudadanía ecológica completa la arquitectura general de la ciudadanía, antes de perfilar la importancia de la ciudadanía ecológica para el objetivo de lograr el desarrollo sostenible.

Sampling-based motion planners have proven to be efficient solutions to a variety of high-dimensional, geometrically complex motion planning problems with applications in several domains. The traditional view of these approaches is that they solve challenges efficiently by giving up formal guarantees and instead attain asymptotic properties in terms of completeness and optimality. Recent work has argued based on Monte Carlo experiments that these approaches also exhibit desirable probabilistic properties in terms of completeness and optimality after finite computation. The current paper formalizes these guarantees. It proves a formal bound on the probability that solutions returned by asymptotically optimal roadmap-based methods (e.g., PRM*) are within a bound of the optimal path length I* with clearance {\epsilon} after a finite iteration n. This bound has the form P(|In - I* | {\leq} {\delta}I*) {\leq} Psuccess, where {\delta} is an error term for the length a path in the PRM* graph, In. This bound is proven for general dimension Euclidean spaces and evaluated in simulation. A discussion on how this bound can be used in practice, as well as bounds for sparse roadmaps are also provided., Comment: 17 pages, 5 figures, 3 tables. Submitted to the Eleventh International Workshop on the Algorithmic Foundations of Robotics (WAFR 2014)

Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats and (iv) reservoir competence of host species and pathogenicity for humans of different genotypes of Borrelia burgdorferi. Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host–vector-borne zoonotic disease.This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats and (iv) reservoir competence of host species and pathogenicity for humans of different genotypes of Borrelia burgdorferi. Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host–vector-borne zoonotic disease.This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Conservation takes place within social–ecological systems, and many conservation interventions aim to influence human behaviour in order to push these systems towards sustainability. Predictive models of human behaviour are potentially powerful tools to support these interventions. This is particularly true if the models can link the attributes and behaviour of individuals with the dynamics of the social and environmental systems within which they operate. Here we explore this potential by showing how combining two modelling approaches (social network analysis, SNA, and agent-based modelling, ABM) could lead to more robust insights into a particular type of conservation intervention. We use our simple model, which simulates knowledge of ranger patrols through a hunting community and is based on empirical data from a Cambodian protected area, to highlight the complex, context-dependent nature of outcomes of information-sharing interventions, depending both on the configuration of the network and the attributes of the agents. We conclude by reflecting that both SNA and ABM, and many other modelling tools, are still too compartmentalized in application, either in ecology or social science, despite the strong methodological and conceptual parallels between their uses in different disciplines. Even a greater sharing of methods between disciplines is insufficient, however; given the impact of conservation on both the social and ecological aspects of systems (and vice versa), a fully integrated approach is needed, combining both the modelling approaches and the disciplinary insights of ecology and social science.This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats and (iv) reservoir competence of host species and pathogenicity for humans of different genotypes of Borrelia burgdorferi. Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host–vector-borne zoonotic disease.This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Conservation takes place within social–ecological systems, and many conservation interventions aim to influence human behaviour in order to push these systems towards sustainability. Predictive models of human behaviour are potentially powerful tools to support these interventions. This is particularly true if the models can link the attributes and behaviour of individuals with the dynamics of the social and environmental systems within which they operate. Here we explore this potential by showing how combining two modelling approaches (social network analysis, SNA, and agent-based modelling, ABM) could lead to more robust insights into a particular type of conservation intervention. We use our simple model, which simulates knowledge of ranger patrols through a hunting community and is based on empirical data from a Cambodian protected area, to highlight the complex, context-dependent nature of outcomes of information-sharing interventions, depending both on the configuration of the network and the attributes of the agents. We conclude by reflecting that both SNA and ABM, and many other modelling tools, are still too compartmentalized in application, either in ecology or social science, despite the strong methodological and conceptual parallels between their uses in different disciplines. Even a greater sharing of methods between disciplines is insufficient, however; given the impact of conservation on both the social and ecological aspects of systems (and vice versa), a fully integrated approach is needed, combining both the modelling approaches and the disciplinary insights of ecology and social science.This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

Bats are reservoirs for emerging human pathogens, including Hendra and Nipah henipaviruses and Ebola and Marburg filoviruses. These viruses demonstrate predictable patterns in seasonality and age structure across multiple systems; previous work suggests that they may circulate in Madagascar's endemic fruit bats, which are widely consumed as human food. We aimed to (a) document the extent of henipa- and filovirus exposure among Malagasy fruit bats, (b) explore seasonality in seroprevalence and serostatus in these bat populations and (c) compare mechanistic hypotheses for possible transmission dynamics underlying these data. To this end, we amassed and analysed a unique dataset documenting longitudinal serological henipa- and filovirus dynamics in three Madagascar fruit bat species. We uncovered serological evidence of exposure to Hendra-/Nipah-related henipaviruses in Eidolon dupreanum, Pteropus rufus and Rousettus madagascariensis, to Cedar-related henipaviruses in E. dupreanum and R. madagascariensis and to Ebola-related filoviruses in P. rufus and R. madagascariensis. We demonstrated significant seasonality in population-level seroprevalence and individual serostatus for multiple viruses across these species, linked to the female reproductive calendar. An age-structured subset of the data highlighted evidence of waning maternal antibodies in neonates, increasing seroprevalence in young and decreasing seroprevalence late in life. Comparison of mechanistic epidemiological models fit to these data offered support for transmission hypotheses permitting waning antibodies but retained immunity in adult-age bats. Our findings suggest that bats may seasonally modulate mechanisms of pathogen control, with consequences for population-level transmission. Additionally, we narrow the field of candidate transmission hypotheses by which bats are presumed to host and transmit potentially zoonotic viruses globally.

International audience; Bats are reservoirs for emerging human pathogens, including Hendra and Nipah henipaviruses and Ebola and Marburg filoviruses. These viruses demonstrate predictable patterns in seasonality and age structure across multiple systems; previous work suggests that they may circulate in Madagascar's endemic fruit bats, which are widely consumed as human food. We aimed to (a) document the extent of henipa- and filovirus exposure among Malagasy fruit bats, (b) explore seasonality in seroprevalence and serostatus in these bat populations and (c) compare mechanistic hypotheses for possible transmission dynamics underlying these data. To this end, we amassed and analysed a unique dataset documenting longitudinal serological henipa- and filovirus dynamics in three Madagascar fruit bat species. We uncovered serological evidence of exposure to Hendra-/Nipah-related henipaviruses in Eidolon dupreanum, Pteropus rufus and Rousettus madagascariensis, to Cedar-related henipaviruses in E. dupreanum and R. madagascariensis and to Ebola-related filoviruses in P. rufus and R. madagascariensis. We demonstrated significant seasonality in population-level seroprevalence and individual serostatus for multiple viruses across these species, linked to the female reproductive calendar. An age-structured subset of the data highlighted evidence of waning maternal antibodies in neonates, increasing seroprevalence in young and decreasing seroprevalence late in life. Comparison of mechanistic epidemiological models fit to these data offered support for transmission hypotheses permitting waning antibodies but retained immunity in adult-age bats. Our findings suggest that bats may seasonally modulate mechanisms of pathogen control, with consequences for population-level transmission. Additionally, we narrow the field of candidate transmission hypotheses by which bats are presumed to host and transmit potentially zoonotic viruses globally.