Investigating the relationship between extreme weather and cryptosporidiosis and giardiasis in Colorado: A multi-decade study using distributed-lag nonlinear models.

Environmentally-mediated protozoan diseases like cryptosporidiosis and giardiasis are likely to be highly impacted by extreme weather, as climate-related conditions like temperature and precipitation have been linked to their survival, distribution, and overall transmission success. Our aim was to investigate the relationship between extreme temperature and precipitation and cryptosporidiosis and giardiasis infection using monthly weather data and case reports from Colorado counties over a twenty-one year period. Data on reportable diseases and weather among Colorado counties were collected using the Colorado Electronic Disease Reporting System (CEDRS) and the Daily Surface Weather and Climatological Summaries (Daymet) Version 3 dataset, respectively. We used a conditional Poisson distributed-lag nonlinear modeling approach to estimate the lagged association (between 0 and 12-months) between relative temperature and precipitation extremes and the risk of cryptosporidiosis and giardiasis infection in Colorado counties between 1997 and 2017, relative to the risk found at average values of temperature and precipitation for a given county and month. We found distinctly different patterns in the associations between temperature extremes and cryptosporidiosis, versus temperature extremes and giardiasis. When maximum or minimum temperatures were high (90th percentile) or very high (95th percentile), we found a significant increase in cryptosporidiosis risk, but a significant decrease in giardiasis risk, relative to risk at the county and calendar-month mean. Conversely, we found very similar relationships between precipitation extremes and both cryptosporidiosis and giardiasis, which highlighted the prominent role of long-term (>8 months) lags. Our study presents novel insights on the influence that extreme temperature and precipitation can have on parasitic disease transmission in real-world settings. Additionally, we present preliminary evidence that the standard lag periods that are typically used in epidemiological studies to assess the impacts of extreme weather on cryptosporidiosis and giardiasis may not be capturing the entire relevant period.

Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination.

BACKGROUND: Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence. METHODS: In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data. RESULTS: The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen's kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (an indicator of surface water presence) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways. CONCLUSION: Our results suggest that in low-transmission environments, leveraging open-source environmental data can yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Integrating genomic and epidemiologic data to accelerate progress toward schistosomiasis elimination.

The global community has adopted ambitious goals to eliminate schistosomiasis as a public health problem, and new tools are needed to achieve them. Mass drug administration programs, for example, have reduced the burden of schistosomiasis, but the identification of hotspots of persistent and reemergent transmission threaten progress toward elimination and underscore the need to couple treatment with interventions that reduce transmission. Recent advances in DNA sequencing technologies make whole-genome sequencing a valuable and increasingly feasible option for population-based studies of complex parasites such as schistosomes. Here, we focus on leveraging genomic data to tailor interventions to distinct social and ecological circumstances. We consider two priority questions that can be addressed by integrating epidemiological, ecological, and genomic information: (1) how often do non-human host species contribute to human schistosome infection? and (2) what is the importance of locally acquired versus imported infections in driving transmission at different stages of elimination? These questions address processes that can undermine control programs, especially those that rely heavily on treatment with praziquantel. Until recently, these questions were difficult to answer with sufficient precision to inform public health decision-making. We review the literature related to these questions and discuss how whole-genome approaches can identify the geographic and taxonomic sources of infection, and how such information can inform context-specific efforts that advance schistosomiasis control efforts and minimize the risk of reemergence.

Tick abundance, diversity and pathogen data collected by the National Ecological Observatory Network.

Cases of tick-borne diseases have been steadily increasing in the USA, owing in part to tick range expansion, land cover and associated host population changes, and habitat fragmentation. However, the relative importance of these and other potential drivers remain poorly understood within this complex disease system. Ticks are ectotherms with multi-host lifecycles, which makes them sensitive to changes in the physical environment and the ecological community. Here, we describe data collected by the National Ecological Observatory Network on tick abundance, diversity and pathogen infection. Ticks are collected using drag or flag methods multiple times in a growing season at 46 terrestrial sites across the USA. Ticks are identified and enumerated by a professional taxonomist, and a subset of nymphs are PCR-tested for various tick-borne pathogens. These data will enable multiscale analyses to better understand how drivers of tick dynamics and pathogen prevalence may shift with climate or land-use change.

Aedes-borne disease outbreaks in West Africa: A call for enhanced surveillance.

Arboviruses transmitted by Aedes mosquitoes are a growing global concern; however, there remain large gaps in surveillance of both arboviruses and their vectors in West Africa. We reviewed over 50 years of data including outbreak reports, peer-reviewed literature, and prior data compilations describing Zika, dengue, and chikungunya, and their vectors in West Africa. Large outbreaks of dengue, Zika, and chikungunya have recently occurred in the region with over 27,000 cases of Aedes-borne disease documented since 2007. Recent arboviral outbreaks have become more concentrated in urban areas, and Aedes albopictus, recently documented in the region, has emerged as an important vector in several areas. Seroprevalence surveys suggest reported cases are a gross underestimate of the underlying arboviral disease burden. These findings indicate a shifting epidemiology of arboviral disease in West Africa and highlight a need for increased research and implementation of vector and disease control. Rapid urbanization and climate change may further alter disease patterns, underscoring the need for improved diagnostic capacity, and vector and disease surveillance to address this evolving health challenge.

How Temperature, Pond-Drying, and Nutrients Influence Parasite Infection and Pathology.

The rapid pace of environmental change is driving multi-faceted shifts in abiotic factors that influence parasite transmission. However, cumulative effects of these factors on wildlife diseases remain poorly understood. Here we used an information-theoretic approach to compare the relative influence of abiotic factors (temperature, diurnal temperature range, nutrients and pond-drying), on infection of snail and amphibian hosts by two trematode parasites (Ribeiroia ondatrae and Echinostoma spp.). A temperature shift from 20 to 25 °C was associated with an increase in infected snail prevalence of 10-20%, while overall snail densities declined by a factor of 6. Trematode infection abundance in frogs was best predicted by infected snail density, while Ribeiroia infection specifically also declined by half for each 10% reduction in pond perimeter, despite no effect of perimeter on the per snail release rate of cercariae. Both nutrient concentrations and Ribeiroia infection positively predicted amphibian deformities, potentially owing to reduced host tolerance or increased parasite virulence in more productive environments. For both parasites, temperature, pond-drying, and nutrients were influential at different points in the transmission cycle, highlighting the importance of detailed seasonal field studies that capture the importance of multiple drivers of infection dynamics and the mechanisms through which they operate.

Drought and immunity determine the intensity of West Nile virus epidemics and climate change impacts.

The effect of global climate change on infectious disease remains hotly debated because multiple extrinsic and intrinsic drivers interact to influence transmission dynamics in nonlinear ways. The dominant drivers of widespread pathogens, like West Nile virus, can be challenging to identify due to regional variability in vector and host ecology, with past studies producing disparate findings. Here, we used analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental-scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors. We found that drought was the primary climatic driver of increased West Nile virus epidemics, rather than within-season or winter temperatures, or precipitation independently. Local-scale data from one region suggested drought increased epidemics via changes in mosquito infection prevalence rather than mosquito abundance. In addition, human acquired immunity following regional epidemics limited subsequent transmission in many states. We show that over the next 30 years, increased drought severity from climate change could triple West Nile virus cases, but only in regions with low human immunity. These results illustrate how changes in drought severity can alter the transmission dynamics of vector-borne diseases.

Host and parasite thermal acclimation responses depend on the stage of infection.

Global climate change is expected to alter patterns of temperature variability, which could influence species interactions including parasitism. Species interactions can be difficult to predict in variable-temperature environments because of thermal acclimation responses, i.e. physiological changes that allow organisms to adjust to a new temperature following a temperature shift. The goal of this study was to determine how thermal acclimation influences host resistance to infection and to test for parasite acclimation responses, which might differ from host responses in important ways. We tested predictions of three, non-mutually exclusive hypotheses regarding thermal acclimation effects on infection of green frog tadpoles (Lithobates clamitans) by the trematode parasite Ribeiroia ondatrae with fully replicated controlled-temperature experiments. Trematodes or tadpoles were independently acclimated to a range of 'acclimation temperatures' prior to shifting them to new 'performance temperatures' for experimental infections. Trematodes that were acclimated to intermediate temperatures (19-22 °C) had greater encystment success across temperatures than either cold- or warm-acclimated trematodes. However, host acclimation responses varied depending on the stage of infection (encystment vs. clearance): warm- (22-28 °C) and cold-acclimated (13-19 °C) tadpoles had fewer parasites encyst at warm and cold performance temperatures, respectively, whereas intermediate-acclimated tadpoles (19-25 °C) cleared the greatest proportion of parasites in the week following exposure. These results suggest that tadpoles use different immune mechanisms to resist different stages of trematode infection, and that each set of mechanisms has unique responses to temperature variability. Our results highlight the importance of considering thermal responses of both parasites and hosts when predicting disease patterns in variable-temperature environments.

The scaling of host density with richness affects the direction, shape, and detectability of diversity-disease relationships.

Pathogen transmission responds differently to host richness and abundance, two unique components of host diversity. However, the heated debate around whether biodiversity generally increases or decreases disease has not considered the relationships between host richness and abundance that may exist in natural systems. Here we use a multi-species model to study how the scaling of total host community abundance with species richness mediates diversity-disease relationships. For pathogens with density-dependent transmission, non-monotonic trends emerge between pathogen transmission and host richness when host community abundance saturates with richness. Further, host species identity drives high variability in pathogen transmission in depauperate communities, but this effect diminishes as host richness accumulates. Using simulation we show that high variability in low richness communities and the non-monotonic relationship observed with host community saturation may reduce the detectability of trends in empirical data. Our study emphasizes that understanding the patterns and predictability of host community composition and pathogen transmission mode will be crucial for predicting where and when specific diversity-disease relationships should occur in natural systems.

Experimental warming drives a seasonal shift in the timing of host-parasite dynamics with consequences for disease risk.

Multi-species experiments are critical for identifying the mechanisms through which climate change influences population dynamics and community interactions within ecological systems, including infectious diseases. Using a host-parasite system involving freshwater snails, amphibians and trematode parasites, we conducted a year-long, outdoor experiment to evaluate how warming affected net parasite production, the timing of infection and the resultant pathology. Warming of 3 °C caused snail intermediate hosts to release parasites 9 months earlier and increased infected snail mortality by fourfold, leading to decreased overlap between amphibians and parasites. As a result, warming halved amphibian infection loads and reduced pathology by 67%, despite comparable total parasite production across temperature treatments. These results demonstrate that climate-disease theory should be expanded to account for predicted changes in host and parasite phenology, which may often be more important than changes in total parasite output for predicting climate-driven changes in disease risk.

Does life history mediate changing disease risk when communities disassemble?

Biodiversity loss sometimes increases disease risk or parasite transmission in humans, wildlife and plants. Some have suggested that this pattern can emerge when host species that persist throughout community disassembly show high host competence - the ability to acquire and transmit infections. Here, we briefly assess the current empirical evidence for covariance between host competence and extirpation risk, and evaluate the consequences for disease dynamics in host communities undergoing disassembly. We find evidence for such covariance, but the mechanisms for and variability around this relationship have received limited consideration. This deficit could lead to spurious assumptions about how and why disease dynamics respond to community disassembly. Using a stochastic simulation model, we demonstrate that weak covariance between competence and extirpation risk may account for inconsistent effects of host diversity on disease risk that have been observed empirically. This model highlights the predictive utility of understanding the degree to which host competence relates to extirpation risk, and the need for a better understanding of the mechanisms underlying such relationships.

Using physiology to understand climate-driven changes in disease and their implications for conservation.

Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host-parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host-parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change-disease literature. We stress that much of the work on how climate influences host-parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host-parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host-parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations.

Species diversity reduces parasite infection through cross-generational effects on host abundance.

With growing interest in the effects of biodiversity on disease, there is a critical need for studies that empirically identify the mechanisms underlying the diversity-disease relationship. Here, we combined wetland surveys of host community structure with mechanistic experiments involving a multi-host parasite to evaluate competing explanations for the dilution effect. Sampling of 320 wetlands in California indicated that snail host communities were strongly nested, with competent hosts for the trematode Ribeiroia ondatrae predominating in low-richness assemblages and unsuitable hosts increasingly present in more diverse communities. Moreover, competent host density was negatively associated with increases in snail species richness. These patterns in host community assembly support a key prerequisite underlying the dilution effect. Results of multigenerational mesocosm experiments designed to mimic field-observed community assemblages allowed us to evaluate the relative importance of host density and diversity in influencing parasite infection success. Increases in snail species richness (from one to four species) had sharply negative effects on the density of infected hosts (-90% reduction). However, this effect was indirect; competition associated with non-host species led to a 95% reduction in host density (susceptible host regulation), owing primarily to a reduction in host reproduction. Among susceptible hosts, there were no differences in infection prevalence as a function of community structure, indicating a lack of support for a direct effect of diversity on infection (encounter reduction). In monospecific conditions, higher initial host densities increased infection among adult hosts; however, compensatory reproduction in the low-density treatments equalized the final number of infected hosts by the next generation, underscoring the relevance of multigenerational studies in understanding the dilution effect. These findings highlight the role of interspecific competition in mediating the relationship between species richness and parasite infection and emphasize the importance of field-informed experimental research in understanding mechanisms underlying the diversity-disease relationship.

From superspreaders to disease hotspots: linking transmission across hosts and space.

Since the identification and imprisonment of "Typhoid Mary," a woman who infected at least 47 people with typhoid in the early 1900s, epidemiologists have recognized that 'superspreading' hosts play a key role in disease epidemics. Such variability in transmission also exists among species within a community (amplification hosts) and among habitat patches across a landscape (disease 'hotspots'), underscoring the need for an integrative framework for studying transmission heterogeneity. Here, we synthesize literature on human, plant, and animal diseases to evaluate the relative contributions of host, pathogen, and environmental factors in driving transmission heterogeneity across hosts and space. We show that host and spatial heterogeneity are closely linked and that quantitatively assessing the contribution of infectious individuals, species, or environmental patches to overall transmission can aid management strategies. We conclude by posing hypotheses regarding how pathogen natural history influences transmission heterogeneity and highlight emerging frontiers in the study of transmission heterogeneity.

Frontiers in climate change-disease research.

The notion that climate change will generally increase human and wildlife diseases has garnered considerable public attention, but remains controversial and seems inconsistent with the expectation that climate change will also cause parasite extinctions. In this review, we highlight the frontiers in climate change-infectious disease research by reviewing knowledge gaps that make this controversy difficult to resolve. We suggest that forecasts of climate-change impacts on disease can be improved by more interdisciplinary collaborations, better linking of data and models, addressing confounding variables and context dependencies, and applying metabolic theory to host-parasite systems with consideration of community-level interactions and functional traits. Finally, although we emphasize host-parasite interactions, we also highlight the applicability of these points to climate-change effects on species interactions in general.