Projected climate and land use change alter western blacklegged tick phenology,seasonal host‐seeking suitability and human encounter risk in California

Global environmental change is having profound effects on the ecology of infectious disease systems, which are widely anticipated to become more pronounced under future climate and land use change. Arthropod vectors of disease are particularly sensitive to changes in abiotic conditions such as temperature and moisture availability. Recent research has focused on shifting environmental suitability for, and geographic distribution of, vector species under projected climate change scenarios. However, shifts in seasonal activity patterns, or phenology, may also have dramatic consequences for human exposure risk, local vector abundance and pathogen transmission dynamics. Moreover, changes in land use are likely to alter human–vector contact rates in ways that models of changing climate suitability are unlikely to capture. Here we used climate and land use projections for California coupled with seasonal species distribution models to explore the response of the western blacklegged tick (Ixodes pacificus), the primary Lyme disease vector in western North America, to projected climate and land use change. Specifically, we investigated how environmental suitability for tick host‐seeking changes seasonally, how the magnitude and direction of changing seasonal suitability differs regionally across California, and how land use change shifts human tick‐encounter risk across the state. We found vector responses to changing climate and land use vary regionally within California under different future scenarios. Under a hotter, drier scenario and more extreme land use change, the duration and extent of seasonal host‐seeking activity increases in northern California, but declines in the south. In contrast, under a hotter, wetter scenario seasonal host‐seeking declines in northern California, but increases in the south. Notably, regardless of future scenario, projected increases in developed land adjacent to current human population centers substantially increase potential human–vector encounter risk across the state. These results highlight regional variability and potential nonlinearity in the response of disease vectors to environmental change.     

Seasonality and the dynamics of infectious diseases

Seasonal variations in temperature, rainfall and resource availability are ubiquitous and can exert strong pressures on population dynamics. Infectious diseases provide some of the best-studied examples of the role of seasonality in shaping population fluctuations. In this paper, we review examples from human and wildlife disease systems to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers. Empirical evidence points to several biologically distinct mechanisms by which seasonality can impact host–pathogen interactions, including seasonal changes in host social behaviour and contact rates, variation in encounters with infective stages in the environment, annual pulses of host births and deaths and changes in host immune defences. Mathematical models and field observations show that the strength and mechanisms of seasonality can alter the spread and persistence of infectious diseases, and that population-level responses can range from simple annual cycles to more complex multiyear fluctuations. From an applied perspective, understanding the timing and causes of seasonality offers important insights into how parasite–host systems operate, how and when parasite control measures should be applied, and how disease risks will respond to anthropogenic climate change and altered patterns of seasonality. Finally, by focusing on well-studied examples of infectious diseases, we hope to highlight general insights that are relevant to other ecological interactions.     

Mechanisms underlying host persistence following amphibian disease emergence determine appropriate management strategies

Emerging infectious diseases have caused many species declines, changes in communities and even extinctions. There are also many species that persist following devastating declines due to disease. The broad mechanisms that enable host persistence following declines include evolution of resistance or tolerance, changes in immunity and behaviour, compensatory recruitment, pathogen attenuation, environmental refugia, density‐dependent transmission and changes in community composition. Here we examine the case of chytridiomycosis, the most important wildlife disease of the past century. We review the full breadth of mechanisms allowing host persistence, and synthesise research on host, pathogen, environmental and community factors driving persistence following chytridiomycosis‐related declines and overview the current evidence and the information required to support each mechanism. We found that for most species the mechanisms facilitating persistence have not been identified. We illustrate how the mechanisms that drive long‐term host population dynamics determine the most effective conservation management strategies. Therefore, understanding mechanisms of host persistence is important because many species continue to be threatened by disease, some of which will require intervention. The conceptual framework we describe is broadly applicable to other novel disease systems.     

Linking community and disease ecology: the impact of biodiversity on pathogen transmission

The increasing number of zoonotic diseases spilling over from a range of wild animal species represents a particular concern for public health, especially in light of the current dramatic trend of biodiversity loss. To understand the ecology of these multi-host pathogens and their response to environmental degradation and species extinctions, it is necessary to develop a theoretical framework that takes into account realistic community assemblages. Here, we present a multi-host species epidemiological model that includes empirically determined patterns of diversity and composition derived from community ecology studies. We use this framework to study the interaction between wildlife diversity and directly transmitted pathogen dynamics. First, we demonstrate that variability in community composition does not affect significantly the intensity of pathogen transmission. We also show that the consequences of community diversity can differentially impact the prevalence of pathogens and the number of infectious individuals. Finally, we show that ecological interactions among host species have a weaker influence on pathogen circulation than inter-species transmission rates. We conclude that integration of a community perspective to study wildlife pathogens is crucial, especially in the context of understanding and predicting infectious disease emergence events.     

Metabolic approaches to understanding climate change impacts on seasonal host‐macroparasite dynamics

Climate change is expected to alter the dynamics of infectious diseases around the globe. Predictive models remain elusive due to the complexity of host–parasite systems and insufficient data describing how environmental conditions affect various system components. Here, we link host–macroparasite models with the Metabolic Theory of Ecology, providing a mechanistic framework that allows integrating multiple nonlinear environmental effects to estimate parasite fitness under novel conditions. The models allow determining the fundamental thermal niche of a parasite, and thus, whether climate change leads to range contraction or may permit a range expansion. Applying the models to seasonal environments, and using an arctic nematode with an endotherm host for illustration, we show that climate warming can split a continuous spring‐to‐fall transmission season into two separate transmission seasons with altered timings. Although the models are strategic and most suitable to evaluate broad‐scale patterns of climate change impacts, close correspondence between model predictions and empirical data indicates model applicability also at the species level. As the application of Metabolic Theory considerably aids the a priori estimation of model parameters, even in data‐sparse systems, we suggest that the presented approach could provide a framework for understanding and predicting climatic impacts for many host–parasite systems worldwide.     

Disentangling extrinsic from intrinsic factors in disease dynamics: a nonlinear time series approach with an application to cholera

Alternative explanations for disease and other population cycles typically include extrinsic environmental drivers, such as climate variability, and intrinsic nonlinear dynamics resulting from feedbacks within the system, such as species interactions and density dependence. Because these different factors can interact in nonlinear systems and can give rise to oscillations whose frequencies differ from those of extrinsic drivers, it is difficult to identify their respective contributions from temporal population patterns. In the case of disease, immunity is an important intrinsic factor. However, for many diseases, such as cholera, for which immunity is temporary, the duration and decay pattern of immunity is not well known. We present a nonlinear time series model with two related objectives: the reconstruction of immunity patterns from data on cases and population sizes and the identification of the respective roles of extrinsic and intrinsic factors in the dynamics. Extrinsic factors here include both seasonality and long-term changes or interannual variability in forcing. Results with simulated data show that this semiparametric method successfully recovers the decay of immunity and identifies the origin of interannual variability. An application to historical cholera data indicates that temporary immunity can be long-lasting and decays in approximately 9 yr. Extrinsic forcing of transmissibility is identified to have a strong seasonal component along with a long-term decrease. Furthermore, noise appears to sustain the multiple frequencies in the long-term dynamics. Similar semiparametric models should apply to population data other than for disease.     

Parasitic and Infectious Disease Responses to Changing Global Nutrient Cycles

Parasitic and infectious diseases (PIDs) are a significant threat to human, livestock, and wildlife health and are changing dramatically in the face of human-induced environmental changes such as those in climate and land use. In this article we explore the little-studied but potentially important response of PIDs to another major environmental change, that in the global nutrient cycles. Humans have now altered the nitrogen (N) cycle to an astonishing degree, and those changes are causing a remarkable diversity of environmental and ecological responses. Since most PIDs are strongly regulated by ecological interactions, changes in nutrients are likely to affect their dynamics in a diversity of environments. We show that while direct tests of the links between nutrients and disease are rare, there is mounting evidence that higher nutrient levels frequently lead to an increased risk of disease. This trend occurs across multiple pathogen types, including helminths, insect-vectored diseases, myxozoa, and bacterial and fungal diseases. The mechanistic responses to increased nutrients are often complex and frequently involve indirect responses that are regulated by intermediate or vector hosts involved in disease transmission. We also show that rapid changes in the N cycle of tropical regions combined with the high diversity of human PIDs in these regions will markedly increase the potential for N to alter the dynamics of disease. Finally, we stress that progress on understanding the effects of nutrients on disease ecology requires a sustained effort to conduct manipulative experiments that can reveal underlying mechanisms on a species-specific basis.     

Disease evolution across a range of spatio-temporal scales

Traditional explorations of infectious disease evolution have considered the competition between two cross-reactive strains within the standard framework of disease models. Such techniques predict that diseases should evolve to be highly transmissible, benign to the host and possess a long infectious period: in general, diseases do not conform to this ideal. Here we consider a more holistic approach, suggesting that evolution is a trade-off between adaptive pressures at different scales: within host, between hosts and at the population level. We present a model combining within-host pathogen dynamics and transmission between individuals governed by an explicit contact network, where transmission dynamics between hosts are a function of the interaction between the pathogen and the hosts' immune system, though ultimately constrained by the contacts each infected host possesses. Our results show how each of the scales places constraints on the evolutionary behavior, and that complex dynamics may emerge due to the feedbacks between epidemiological and evolutionary dynamics. In particular, multiple stable states can occur with switching between them stochastically driven.     

Human mobility patterns predict divergent epidemic dynamics among cities

The epidemic dynamics of infectious diseases vary among cities, but it is unclear how this is caused by patterns of infectious contact among individuals. Here, we ask whether systematic differences in human mobility patterns are sufficient to cause inter-city variation in epidemic dynamics for infectious diseases spread by casual contact between hosts. We analyse census data on the mobility patterns of every full-time worker in 48 Canadian cities, finding a power-law relationship between population size and the level of organization in mobility patterns, where in larger cities, a greater fraction of workers travel to work in a few focal locations. Similarly sized cities also vary in the level of organization in their mobility patterns, equivalent on average to the variation expected from a 2.64-fold change in population size. Systematic variation in mobility patterns is sufficient to cause significant differences among cities in infectious disease dynamics—even among cities of the same size—according to an individual-based model of airborne pathogen transmission parametrized with the mobility data. This suggests that differences among cities in host contact patterns are sufficient to drive differences in infectious disease dynamics and provides a framework for testing the effects of host mobility patterns in city-level disease data.     

Cholera and Shigellosis: Different Epidemiology but Similar Responses to Climate Variability

Background

Comparative studies of the associations between different infectious diseases and climate variability, such as the El Niño-Southern Oscillation, are lacking. Diarrheal illnesses, particularly cholera and shigellosis, provide an important opportunity to apply a comparative approach. Cholera and shigellosis have significant global mortality and morbidity burden, pronounced differences in transmission pathways and pathogen ecologies, and there is an established climate link with cholera. In particular, the specific ecology of Vibrio cholerae is often invoked to explain the sensitivity of that disease to climate.

Methods and Findings

The extensive surveillance data of the International Center for Diarrheal Disease Research, Bangladesh are used here to revisit the known associations between cholera and climate, and to address their similarity to previously unexplored patterns for shigellosis. Monthly case data for both the city of Dhaka and a rural area known as Matlab are analyzed with respect to their association with El Niño and flooding. Linear correlations are examined between flooding and cumulative cases, as well as for flooding and El Niño. Rank-correlation maps are also computed between disease cases in the post-monsoon epidemic season and sea surface temperatures in the Pacific. Similar climate associations are found for both diseases and both locations. Increased cases follow increased monsoon flooding and increased sea surface temperatures in the preceding winter corresponding to an El Niño event.

Conclusions

The similarity in association patterns suggests a systemic breakdown in population health with changing environmental conditions, in which climate variability acts primarily through increasing the exposure risk of the human population. We discuss these results in the context of the on-going debate on the relative importance of the environmental reservoir vs. secondary transmission, as well as the implications for the use of El Niño as an early indicator of flooding and enteric disease risk.     

Emerging and Reemerging Infectious Diseases: Biocomplexity as an Interdisciplinary Paradigm

Understanding factors responsible for reemergence of diseases believed to have been controlled and outbreaks of previously unknown infectious diseases is one of the most difficult scientific problems facing society today. Significant knowledge gaps exist for even the most studied emerging infectious diseases. Coupled with failures in the response to the resurgence of infectious diseases, this lack of information is embedded in a simplistic view of pathogens and disconnected from a social and ecological context, and assumes a linear response of pathogens to environmental change. In fact, the natural reservoirs and transmission rates of most emerging infectious diseases primarily are affected by environmental factors, such as seasonality or meteorological events, typically producing nonlinear responses that are inherently unpredictable. A more realistic view of emerging infectious diseases requires a holistic perspective that incorporates social as well as physical, chemical, and biological dimensions of our planet’s systems. The notion of biocomplexity captures this depth and richness, and most importantly, the interactions of human and natural systems. This article provides a brief review and a synthesis of interdisciplinary approaches and insights employing the biocomplexity paradigm and offers a social–ecological approach for addressing and garnering an improved understanding of emerging infectious diseases. Drawing on findings from studies of cholera and other examples of emerging waterborne, zoonotic, and vectorborne diseases, a “blueprint” for the proposed interdisciplinary research framework is offered which integrates biological processes from the molecular level to that of communities and regional systems, incorporating public health infrastructure and climate aspects.     

'SEEDY' (Simulation of Evolutionary and Epidemiological Dynamics): An R Package to Follow Accumulation of Within-Host Mutation in Pathogens

Genome sequencing is an increasingly common component of infectious disease outbreak investigations. However, the relationship between pathogen transmission and observed genetic data is complex, and dependent on several uncertain factors. As such, simulation of pathogen dynamics is an important tool for interpreting observed genomic data in an infectious disease outbreak setting, in order to test hypotheses and to explore the range of outcomes consistent with a given set of parameters. We introduce ‘seedy’, an R package for the simulation of evolutionary and epidemiological dynamics (http://cran.r-project.org/web/packages/seedy/). Our software implements stochastic models for the accumulation of mutations within hosts, as well as individual-level disease transmission. By allowing variables such as the transmission bottleneck size, within-host effective population size and population mixing rates to be specified by the user, our package offers a flexible framework to investigate evolutionary dynamics during disease outbreaks. Furthermore, our software provides theoretical pairwise genetic distance distributions to provide a likelihood of person-to-person transmission based on genomic observations, and using this framework, implements transmission route assessment for genomic data collected during an outbreak. Our open source software provides an accessible platform for users to explore pathogen evolution and outbreak dynamics via simulation, and offers tools to assess observed genomic data in this context.     

How seasonal variations in birth and transmission rates impact population dynamics in a basic SIR model

The changing climate is expected to alter the timings of key events in species life-histories. These shifts are likely to have important consequences for infectious disease dynamics, as the distribution and abundance of host species will lead to a different environment for parasites. Previous work has shown how seasonality in single host traits - most commonly the reproduction rate or transmission rate - can lead to an array of complex epidemiological dynamics, including chaos and multiple-stable states, with changes to the timing and amplitude of the seasonal peaks often driving drastic changes in behaviour. However, more than one life-history trait is likely to be seasonal, and changing environmental conditions may impact each of them in different ways, yet there have been few studies of host-parasite dynamics that include more than one seasonal trait. Here we examine a Susceptible-Infected-Recovered epidemiological model in which both reproduction and transmission exhibit seasonal fluctuations. We examine how the amplitude and timing of these seasonal peaks impact disease dynamics. We show that the relative timing of the two events is key, with the most stable dynamics when births peak a few months before transmission. We also show that chaotic dynamics become more likely when transmission in particular has a high amplitude, and when baseline transmission and virulence are high. Our results emphasise the importance of seasonality and timing of host life-history events to disease dynamics.     

Role of environmental persistence in pathogen transmission: a mathematical modeling approach

Although diseases such as influenza, tuberculosis and SARS are transmitted through an environmentally mediated mechanism, most modeling work on these topics is based on the concepts of infectious contact and direct transmission. In this paper we use a paradigm model to show that environmental transmission appears like direct transmission in the case where the pathogen persists little time in the environment. Furthermore, we formulate conditions for the validity of this modeling approximation and we illustrate them numerically for the cases of cholera and influenza. According to our results based on recently published parameter estimates, the direct transmission approximation fails for both cholera and influenza. While environmental transmission is typically chosen over direct transmission in modeling cholera, this is not the case for influenza.     

Linking anthropogenic resources to wildlife–pathogen dynamics: a review and meta‐analysis

Urbanisation and agriculture cause declines for many wildlife, but some species benefit from novel resources, especially food, provided in human‐dominated habitats. Resulting shifts in wildlife ecology can alter infectious disease dynamics and create opportunities for cross‐species transmission, yet predicting host–pathogen responses to resource provisioning is challenging. Factors enhancing transmission, such as increased aggregation, could be offset by better host immunity due to improved nutrition. Here, we conduct a review and meta‐analysis to show that food provisioning results in highly heterogeneous infection outcomes that depend on pathogen type and anthropogenic food source. We also find empirical support for behavioural and immune mechanisms through which human‐provided resources alter host exposure and tolerance to pathogens. A review of recent theoretical models of resource provisioning and infection dynamics shows that changes in host contact rates and immunity produce strong non‐linear responses in pathogen invasion and prevalence. By integrating results of our meta‐analysis back into a theoretical framework, we find provisioning amplifies pathogen invasion under increased host aggregation and tolerance, but reduces transmission if provisioned food decreases dietary exposure to parasites. These results carry implications for wildlife disease management and highlight areas for future work, such as how resource shifts might affect virulence evolution.     

Cholera Threat to Humans in Ghana Is Influenced by Both Global and Regional Climatic Variability

Cholera, an acute diarrheal illness, is caused by infection of the intestine with the bacterium Vibrio cholerae after ingestion of contaminated water or food. The disease had disappeared from most of the developed countries in the last 50 years, but cholera epidemics remain a major public health problem in many developing countries, most often localized in tropical areas. Cholera is an infectious disease for which a relationship between disease temporal patterns and climate has been demonstrated, but only in an endemic context and for local areas of Asia and South America. Until now, similar studies have not been done in an epidemic context, on the African continent, although the largest number of cholera cases has been reported for those countries by the World Health Organization. The wavelet method was used in order to explore periodicity in (i) a long-time monthly cholera incidence in Ghana, West Africa, (ii) proxy environmental variables, and (iii) climatic indices time series, from 1975 to 1995. Cross-analysis were done to explore links between these time series, i.e., between cholera and climate. Results showed strong statistical association (coherency) from the end of the 1980s, between cholera outbreak resurgences in Ghana and the climatic/environmental parameters under scrutiny. Further examination of the existence of common spatial and temporal patterns in infectious diseases on the continent of Africa will permit development of more effective treatment of disease.     

Seasonality and wildlife disease: how seasonal birth, aggregation and variation in immunity affect the dynamics of Mycoplasma gallisepticum in house finches

We examine the role of host seasonal breeding, host seasonal social aggregation and partial immunity in affecting wildlife disease dynamics, focusing on the dynamics of house finch conjunctivitis (Mycoplasma gallisepticum (MG) in Carpodacus mexicanus). This case study of an unmanaged emerging infectious disease provides useful insight into the important role of seasonal factors in driving ongoing disease dynamics. Seasonal breeding can force recurrent epidemics through the input of fresh susceptibles, which will clearly affect a wide variety of wildlife disease dynamics. Seasonal patterns of social aggregation and foraging behaviour could change transmission dynamics. We use latitudinal variation in the timing of breeding, and social systems to model seasonal dynamics of house finch conjunctivitis across eastern North America. We quantify the patterns of seasonal breeding, and social aggregation across a latitudinal gradient in the eastern range of the house finch, supplemented with known field and laboratory information on immunity to MG in finches. We then examine the interactions of these factors in a theoretical model of disease dynamics. We find that both forms of seasonality could explain the dynamics of the house finch-MG system, and that these factors could have important effects on the dynamics of wildlife diseases generally. In particular, while either alone is sufficient to create recurrent cycles of prevalence in a population with an endemic disease, both are required to produce the specific semi-annual pattern of disease prevalence seen in the house finch conjunctivitis system.     

Molecular evolutionary signatures reveal the role of host ecological dynamics in viral disease emergence and spread

RNA viruses account for numerous emerging and perennial infectious diseases, and are characterized by rapid rates of molecular evolution. The ecological dynamics of most emerging RNA viruses are still poorly understood and difficult to ascertain. The availability of genome sequence data for many RNA viruses, in principle, could be used to infer ecological dynamics if changes in population numbers produced a lasting signature within the pattern of genome evolution. As a result, the rapidly emerging phylogeographic structure of a pathogen, shaped by the rise and fall in the number of infections and their spatial distribution, could be used as a surrogate for direct ecological assessments. Based on rabies virus as our example, we use a model combining ecological and evolutionary processes to test whether variation in the rate of host movement results in predictive diagnostic patterns of pathogen genetic structure. We identify several linearizable relationships between host dispersal rate and measures of phylogenetic structure suggesting genetic information can be used to directly infer ecological process. We also find phylogenetic structure may be more revealing than demography for certain ecological processes. Our approach extends the reach of current analytic frameworks for infectious disease dynamics by linking phylogeography back to underlying ecological processes.     

Seasonality in human zoonotic enteric diseases: a systematic review

Background

Although seasonality is a defining characteristic of many infectious diseases, few studies have described and compared seasonal patterns across diseases globally, impeding our understanding of putative mechanisms. Here, we review seasonal patterns across five enteric zoonotic diseases: campylobacteriosis, salmonellosis, vero-cytotoxigenic Escherichia coli (VTEC), cryptosporidiosis and giardiasis in the context of two primary drivers of seasonality: (i) environmental effects on pathogen occurrence and pathogen-host associations and (ii) population characteristics/behaviour.

Methodology/Principal Findings

We systematically reviewed published literature from 1960–2010, resulting in the review of 86 studies across the five diseases. The Gini coefficient compared temporal variations in incidence across diseases and the monthly seasonality index characterised timing of seasonal peaks. Consistent seasonal patterns across transnational boundaries, albeit with regional variations was observed. The bacterial diseases all had a distinct summer peak, with identical Gini values for campylobacteriosis and salmonellosis (0.22) and a higher index for VTEC (Gini = 0.36). Cryptosporidiosis displayed a bi-modal peak with spring and summer highs and the most marked temporal variation (Gini = 0.39). Giardiasis showed a relatively small summer increase and was the least variable (Gini = 0.18).

Conclusions/Significance

Seasonal variation in enteric zoonotic diseases is ubiquitous, with regional variations highlighting complex environment-pathogen-host interactions. Results suggest that proximal environmental influences and host population dynamics, together with distal, longer-term climatic variability could have important direct and indirect consequences for future enteric disease risk. Additional understanding of the concerted influence of these factors on disease patterns may improve assessment and prediction of enteric disease burden in temperate, developed countries.     

Impact of Climate Variability on Infectious Disease in West Africa

The importance of infectious disease as a determinant (as well as an outcome) of poverty has recently become a prominent argument for international and national investment in the control of infectious disease, as can be seen in the recently articulated United Nations (UN) Millennium Development Goals (MDGs). Climate variability and land use change have an enormous impact on health in West Africa, and may yet undermine the potential for achieving the MDGs, in certain economic-ecological zones. However, their underlying role in determining the burden of disease in the region on a yearly or decadal basis has never been systematically studied. In order to improve our understanding of the future impacts of climate change, it may be more effective to start by investigating the impact of inter-annual climate variability, and short-term shifts in climate (e.g., decadal), on disease transmission dynamics. This information may inform both current and future policy decisions with regard to prediction, prevention, and management of adverse climate-related health outcomes. This article reviews current knowledge of changes in the epidemiology of infectious diseases associated with climate variability in West Africa over the last 40 years. Selected examples are considered from bacterial (meningococcal meningitis), protozoan (malaria), and filarial (onchocerciasis and lymphatic filariasis) infections where spatial and temporal disease patterns have been directly influenced by seasonal, inter-annual, or decadal changes in climate.The views expressed herein are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration (NOAA) or any of its sub-agencies.