Publications by authors named "Leah R Johnson"

28 Publications

  • Page 1 of 1

Predicting temperature-dependent transmission suitability of bluetongue virus in livestock.

Parasit Vectors 2021 Jul 30;14(1):382. Epub 2021 Jul 30.

Department of Biological Sciences, Virginia Tech, Blacksburg, VA, 24061, USA.

The transmission of vector-borne diseases is governed by complex factors including pathogen characteristics, vector-host interactions, and environmental conditions. Temperature is a major driver for many vector-borne diseases including Bluetongue viral (BTV) disease, a midge-borne febrile disease of ruminants, notably livestock, whose etiology ranges from mild or asymptomatic to rapidly fatal, thus threatening animal agriculture and the economy of affected countries. Using modeling tools, we seek to predict where the transmission can occur based on suitable temperatures for BTV. We fit thermal performance curves to temperature-sensitive midge life-history traits, using a Bayesian approach. We incorporate these curves into S(T), a transmission suitability metric derived from the disease's basic reproductive number, [Formula: see text] This suitability metric encompasses all components that are known to be temperature-dependent. We use trait responses for two species of key midge vectors, Culicoides sonorensis and Culicoides variipennis present in North America. Our results show that outbreaks of BTV are more likely between 15[Formula: see text] C and [Formula: see text], with predicted peak transmission risk at 26 [Formula: see text] C. The greatest uncertainty in S(T) is associated with the following: the uncertainty in mortality and fecundity of midges near optimal temperature for transmission; midges' probability of becoming infectious post-infection at the lower edge of the thermal range; and the biting rate together with vector competence at the higher edge of the thermal range. We compare three model formulations and show that incorporating thermal curves into all three leads to similar BTV risk predictions. To demonstrate the utility of this modeling approach, we created global suitability maps indicating the areas at high and long-term risk of BTV transmission, to assess risk and to anticipate potential locations of disease establishment.
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http://dx.doi.org/10.1186/s13071-021-04826-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323090PMC
July 2021

Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050.

Glob Chang Biol 2021 Jan 28;27(1):84-93. Epub 2020 Oct 28.

Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, USA.

In the aftermath of the 2015 pandemic of Zika virus (ZIKV), concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature-dependent transmission model for ZIKV to project climate change impacts on transmission suitability risk by mid-century (a generation into the future). Based on these model predictions, in the worst-case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.
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http://dx.doi.org/10.1111/gcb.15384DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756632PMC
January 2021

Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23°C and 26°C.

Elife 2020 09 15;9. Epub 2020 Sep 15.

Department of Biology, Stanford University, Stanford, United States.

The temperature-dependence of many important mosquito-borne diseases has never been quantified. These relationships are critical for understanding current distributions and predicting future shifts from climate change. We used trait-based models to characterize temperature-dependent transmission of 10 vector-pathogen pairs of mosquitoes (, , , and others) and viruses (West Nile, Eastern and Western Equine Encephalitis, St. Louis Encephalitis, Sindbis, and Rift Valley Fever viruses), most with substantial transmission in temperate regions. Transmission is optimized at intermediate temperatures (23-26°C) and often has wider thermal breadths (due to cooler lower thermal limits) compared to pathogens with predominately tropical distributions (in previous studies). The incidence of human West Nile virus cases across US counties responded unimodally to average summer temperature and peaked at 24°C, matching model-predicted optima (24-25°C). Climate warming will likely shift transmission of these diseases, increasing it in cooler locations while decreasing it in warmer locations.
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http://dx.doi.org/10.7554/eLife.58511DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492091PMC
September 2020

The Role of Vector Trait Variation in Vector-Borne Disease Dynamics.

Front Ecol Evol 2020 Jul 10;8. Epub 2020 Jul 10.

Department of Life Sciences, Imperial College London, Ascot, United Kingdom.

Many important endemic and emerging diseases are transmitted by vectors that are biting arthropods. The functional traits of vectors can affect pathogen transmission rates directly and also through their effect on vector population dynamics. Increasing empirical evidence shows that vector traits vary significantly across individuals, populations, and environmental conditions, and at time scales relevant to disease transmission dynamics. Here, we review empirical evidence for variation in vector traits and how this trait variation is currently incorporated into mathematical models of vector-borne disease transmission. We argue that mechanistically incorporating trait variation into these models, by explicitly capturing its effects on vector fitness and abundance, can improve the reliability of their predictions in a changing world. We provide a conceptual framework for incorporating trait variation into vector-borne disease transmission models, and highlight key empirical and theoretical challenges. This framework provides a means to conceptualize how traits can be incorporated in vector borne disease systems, and identifies key areas in which trait variation can be explored. Determining when and to what extent it is important to incorporate trait variation into vector borne disease models remains an important, outstanding question.
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http://dx.doi.org/10.3389/fevo.2020.00189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7409824PMC
July 2020

Predicting the fundamental thermal niche of crop pests and diseases in a changing world: A case study on citrus greening.

J Appl Ecol 2019 Aug 1;56(8):2057-2068. Epub 2019 Jul 1.

Department of Statistics, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, Virginia.

Predicting where crop pests and diseases can occur, both now and in the future under different climate change scenarios, is a major challenge for crop management. One solution is to estimate the fundamental thermal niche of the pest/disease to indicate where establishment is possible. Here, we develop methods for estimating and displaying the fundamental thermal niche of pests and pathogens and apply these methods to Huanglongbing (HLB), a vector-borne disease that is currently threatening the citrus industry worldwide.We derive a suitability metric based on a mathematical model of HLB transmission between tree hosts and its vector , and incorporate the effect of temperature on vectortraits using data from laboratory experiments performed at different temperatures. We validate the model using data on the historical range of HLB.Our model predicts that transmission of HLB is possible between 16 and 33°C with peak transmission at ~25°C. The greatest uncertainty in our suitability metric is associated with the mortality of the vectors at peak transmission, and fecundity at the edges of the thermal range, indicating that these parameters need further experimental work.We produce global thermal niche maps by plotting how many months each location is suitable for establishment of the pest/disease. This analysis reveals that the highest suitability for HLB occurs near the equator in large citrus-producing regions, such as Brazil and South-East Asia. Within the Northern Hemisphere, the Iberian peninsula and California are HLB suitable for up to 7 months of the year and are free of HLB currently. We create a thermal niche map which indicates the places at greatest risk of establishment should a crop disease or pest enter these regions. This indicates where surveillance should be focused to prevent establishment. Our mechanistic method can be used to predict new areas for Huanglongbing transmission under different climate change scenarios and is easily adapted to other vector-borne diseases and crop pests.
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http://dx.doi.org/10.1111/1365-2664.13455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367095PMC
August 2019

An open challenge to advance probabilistic forecasting for dengue epidemics.

Proc Natl Acad Sci U S A 2019 11 11;116(48):24268-24274. Epub 2019 Nov 11.

College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, United Kingdom.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.
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http://dx.doi.org/10.1073/pnas.1909865116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883829PMC
November 2019

Modeling Temperature Effects on Population Density of the Dengue Mosquito .

Insects 2019 Nov 7;10(11). Epub 2019 Nov 7.

Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, USA.

Mosquito density plays an important role in the spread of mosquito-borne diseases such as dengue and Zika. While it remains very challenging to estimate the density of mosquitoes, modelers have tried different methods to represent it in mathematical models. The goal of this paper is to investigate the various ways mosquito density has been quantified, as well as to propose a dynamical system model that includes the details of mosquito life stages leading to the adult population. We first discuss the mosquito traits involved in determining mosquito density, focusing on those that are temperature dependent. We evaluate different forms of models for mosquito densities based on these traits and explore their dynamics as temperature varies. Finally, we compare the predictions of the models to observations of abundances over time in Vitòria, Brazil. Our results indicate that the four models exhibit qualitatively and quantitatively different behaviors when forced by temperature, but that all seem reasonably consistent with observed abundance data.
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http://dx.doi.org/10.3390/insects10110393DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920917PMC
November 2019

Thermal biology of mosquito-borne disease.

Ecol Lett 2019 Oct 8;22(10):1690-1708. Epub 2019 Jul 8.

Department of Statistics, Virginia Polytechnic and State University, 250 Drillfield Drive, Blacksburg, VA, USA.

Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species - including globally important diseases like malaria, dengue, and Zika - synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23-29ºC and declining to zero below 9-23ºC and above 32-38ºC. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25-26ºC) while dengue and Zika viruses had the highest (29ºC) thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration.
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http://dx.doi.org/10.1111/ele.13335DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6744319PMC
October 2019

Linked within-host and between-host models and data for infectious diseases: a systematic review.

PeerJ 2019 19;7:e7057. Epub 2019 Jun 19.

Department of Biological Sciences, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA.

The observed dynamics of infectious diseases are driven by processes across multiple scales. Here we focus on two: within-host, that is, how an infection progresses inside a single individual (for instance viral and immune dynamics), and between-host, that is, how the infection is transmitted between multiple individuals of a host population. The dynamics of each of these may be influenced by the other, particularly across evolutionary time. Thus understanding each of these scales, and the links between them, is necessary for a holistic understanding of the spread of infectious diseases. One approach to combining these scales is through mathematical modeling. We conducted a systematic review of the published literature on multi-scale mathematical models of disease transmission (as defined by combining within-host and between-host scales) to determine the extent to which mathematical models are being used to understand across-scale transmission, and the extent to which these models are being confronted with data. Following the PRISMA guidelines for systematic reviews, we identified 24 of 197 qualifying papers across 30 years that include both linked models at the within and between host scales and that used data to parameterize/calibrate models. We find that the approach that incorporates both modeling with data is under-utilized, if increasing. This highlights the need for better communication and collaboration between modelers and empiricists to build well-calibrated models that both improve understanding and may be used for prediction.
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http://dx.doi.org/10.7717/peerj.7057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589080PMC
June 2019

Global expansion and redistribution of Aedes-borne virus transmission risk with climate change.

PLoS Negl Trop Dis 2019 03 28;13(3):e0007213. Epub 2019 Mar 28.

Department of Statistics, Virginia Polytechnic and State University, Blacksburg, Virginia, United States of America.

Forecasting the impacts of climate change on Aedes-borne viruses-especially dengue, chikungunya, and Zika-is a key component of public health preparedness. We apply an empirically parameterized model of viral transmission by the vectors Aedes aegypti and Ae. albopictus, as a function of temperature, to predict cumulative monthly global transmission risk in current climates, and compare them with projected risk in 2050 and 2080 based on general circulation models (GCMs). Our results show that if mosquito range shifts track optimal temperature ranges for transmission (21.3-34.0°C for Ae. aegypti; 19.9-29.4°C for Ae. albopictus), we can expect poleward shifts in Aedes-borne virus distributions. However, the differing thermal niches of the two vectors produce different patterns of shifts under climate change. More severe climate change scenarios produce larger population exposures to transmission by Ae. aegypti, but not by Ae. albopictus in the most extreme cases. Climate-driven risk of transmission from both mosquitoes will increase substantially, even in the short term, for most of Europe. In contrast, significant reductions in climate suitability are expected for Ae. albopictus, most noticeably in southeast Asia and west Africa. Within the next century, nearly a billion people are threatened with new exposure to virus transmission by both Aedes spp. in the worst-case scenario. As major net losses in year-round transmission risk are predicted for Ae. albopictus, we project a global shift towards more seasonal risk across regions. Many other complicating factors (like mosquito range limits and viral evolution) exist, but overall our results indicate that while climate change will lead to increased net and new exposures to Aedes-borne viruses, the most extreme increases in Ae. albopictus transmission are predicted to occur at intermediate climate change scenarios.
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http://dx.doi.org/10.1371/journal.pntd.0007213DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438455PMC
March 2019

Plasmodium vivax readiness to transmit: implication for malaria eradication.

BMC Syst Biol 2019 01 11;13(1). Epub 2019 Jan 11.

Department of Global Health (GH) & Center for Drug Discovery and Innovation (CDDI), College of Public Health, University of South Florida, Tampa, FL, 33612, USA.

Background: The lack of a continuous long-term in vitro culture system for Plasmodium vivax severely limits our knowledge of pathophysiology of the most widespread malaria parasite. To gain direct understanding of P. vivax human infections, we used Next Generation Sequencing data mining to unravel parasite in vivo expression profiles for P. vivax, and P. falciparum as comparison.

Results: We performed cloud and local computing to extract parasite transcriptomes from publicly available raw data of human blood samples. We developed a Poisson Modelling (PM) method to confidently identify parasite derived transcripts in mixed RNAseq signals of infected host tissues. We successfully retrieved and reconstructed parasite transcriptomes from infected patient blood as early as the first blood stage cycle; and the same methodology did not recover any significant signal from controls. Surprisingly, these first generation blood parasites already show strong signature of transmission, which indicates the commitment from asexual-to-sexual stages. Further, we place the results within the context of P. vivax's complex life cycle, by developing mathematical models for P. vivax and P. falciparum and using sensitivity analysis assess the relative epidemiological impact of possible early stage transmission.

Conclusion: The study uncovers the earliest onset of P. vivax blood pathogenesis and highlights the challenges of P. vivax eradication programs.
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http://dx.doi.org/10.1186/s12918-018-0669-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330404PMC
January 2019

How Individual Variation in Host Tolerance Affects Competence to Transmit Parasites.

Physiol Biochem Zool 2019 Jan/Feb;92(1):49-57

Tolerance, or the maintenance of host health or fitness at a given parasite burden, has often been studied in evolutionary and medical contexts, particularly with respect to effects on the evolution of parasite virulence and individual patient outcomes. These bodies of work have provided insight about tolerance for evolutionary phenomena (e.g., virulence) and individual health (e.g., recovering from an infection). However, due to the specific motivations of that work, few studies have considered the ecological ramifications of variation in tolerance, namely, how variation in forms of tolerance could mediate parasite movement through populations and even community-level disease dynamics. Tolerance is most commonly regarded as the relationship between host fitness and parasite burden. However, few if any studies have actually quantified host fitness, instead utilizing proxies of fitness as the response variables to be regressed against parasite burden. Here, we address how attention to the effects of parasite burden on traits that are relevant to host competence (i.e., the ability to amplify parasites to levels transmissible to other hosts/vectors) will enhance our understanding of disease dynamics in nature. We also provide several forms of guidance for how to overcome the challenges of quantifying tolerance in wild organisms.
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http://dx.doi.org/10.1086/701169DOI Listing
February 2019

Bioenergetic theory predicts infection dynamics of human schistosomes in intermediate host snails across ecological gradients.

Ecol Lett 2018 05 12;21(5):692-701. Epub 2018 Mar 12.

Department of Integrative Biology, University of South Florida, 4202, East Fowler Ave., 33620, Tampa, FL, USA.

Epidemiological dynamics depend on the traits of hosts and parasites, but hosts and parasites are heterogeneous entities that exist in dynamic environments. Resource availability is a particularly dynamic and potent environmental driver of within-host infection dynamics (temporal patterns of growth, reproduction, parasite production and survival). We developed, parameterised and validated a model for resource-explicit infection dynamics by incorporating a parasitism module into dynamic energy budget theory. The model mechanistically explained the dynamic multivariate responses of the human parasite Schistosoma mansoni and its intermediate host snail to variation in resources and host density. At the population level, feedbacks mediated by resource competition could create a unimodal relationship between snail density and human risk of exposure to schistosomes. Consequently, weak snail control could backfire if reductions in snail density release remaining hosts from resource competition. If resource competition is strong and relevant to schistosome production in nature, it could inform control strategies.
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http://dx.doi.org/10.1111/ele.12937DOI Listing
May 2018

Changing measurements or changing movements? Sampling scale and movement model identifiability across generations of biologging technology.

Ecol Evol 2017 11 3;7(22):9257-9266. Epub 2017 Oct 3.

Department of Geography University of Florida Gainesville FL USA.

Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. Over time, sensor technology for measuring movement patterns has improved. Although older technologies may be rendered obsolete, the existing data are still valuable, especially if new and old data can be compared to test whether a behavior has changed over time. We used simulated data to assess the ability to quantify and correctly identify patterns of seabird flight lengths under observational regimes used in successive generations of wet/dry logging technology. Care must be taken when comparing data collected at differing timescales, even when using inference procedures that incorporate the observational process, as model selection and parameter estimation may be biased. In practice, comparisons may only be valid when degrading all data to match the lowest resolution in a set. Changes in tracking technology, such as the wet/dry loggers explored here, that lead to aggregation of measurements at different temporal scales make comparisons challenging. We therefore urge ecologists to use synthetic data to assess whether accurate parameter estimation is possible for models comparing disparate data sets before planning experiments and conducting analyses such as responses to environmental changes or the assessment of management actions.
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http://dx.doi.org/10.1002/ece3.3461DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696428PMC
November 2017

Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models.

PLoS Negl Trop Dis 2017 04 27;11(4):e0005568. Epub 2017 Apr 27.

Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, United States of America.

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.
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http://dx.doi.org/10.1371/journal.pntd.0005568DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423694PMC
April 2017

Diversity in growth patterns among strains of the lethal fungal pathogen Batrachochytrium dendrobatidis across extended thermal optima.

Oecologia 2017 06 19;184(2):363-373. Epub 2017 Apr 19.

Department of Environmental Science, Policy and Management, University of California- Berkeley, Berkeley, CA, 94720-3144, USA.

The thermal sensitivities of organisms regulate a wide range of ecological interactions, including host-parasite dynamics. The effect of temperature on disease ecology can be remarkably complex in disease systems where the hosts are ectothermic and where thermal conditions constrain pathogen reproductive rates. Amphibian chytridiomycosis, caused by the pathogen Batrachochytrium dendrobatidis (Bd), is a lethal fungal disease that is influenced by temperature. However, recent temperature studies have produced contradictory findings, suggesting that our current understanding of thermal effects on Bd may be incomplete. We investigated how temperature affects three different Bd strains to evaluate diversity in thermal responses. We quantified growth across the entire thermal range of Bd, and beyond the known thermal limits (T and T ). Our results show that all Bd strains remained viable and grew following 24 h freeze (-12 °C) and heat shock (28 °C) treatments. Additionally, we found that two Bd strains had higher logistic growth rates (r) and carrying capacities (K) at the upper and lower extremities of the temperature range, and especially in low temperature conditions (2-3 °C). In contrast, a third strain exhibited relatively lower growth rates and carrying capacities at these same thermal extremes. Overall, our results suggest that there is considerable variation among Bd strains in thermal tolerance, and they establish a new thermal sensitivity profile for Bd. More generally, our findings point toward important questions concerning the mechanisms that dictate fungal thermal tolerances and temperature-dependent pathogenesis in other fungal disease systems.
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http://dx.doi.org/10.1007/s00442-017-3866-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5487841PMC
June 2017

Mathematical models are a powerful method to understand and control the spread of Huanglongbing.

PeerJ 2016 3;4:e2642. Epub 2016 Nov 3.

Department of Integrative Biology, University of South Florida, Tampa, Florida, United States; Department of Statistics, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, Virginia, United States.

Huanglongbing (HLB), or citrus greening, is a global citrus disease occurring in almost all citrus growing regions. It causes substantial economic burdens to individual growers, citrus industries and governments. Successful management strategies to reduce disease burden are desperately needed but with so many possible interventions and combinations thereof it is difficult to know which are worthwhile or cost-effective. We review how mathematical models have yielded useful insights into controlling disease spread for other vector-borne plant diseases, and the small number of mathematical models of HLB. We adapt a malaria model to HLB, by including temperature-dependent psyllid traits, "flushing" of trees, and economic costs, to show how models can be used to highlight the parameters that require more data collection or that should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We find that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. Also, the best strategy for insecticide intervention is to spray for more days rather than pay extra for a more efficient spray. We conclude that mathematical models are able to provide useful recommendations for managing HLB spread.
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http://dx.doi.org/10.7717/peerj.2642DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101597PMC
November 2016

Hunting, food subsidies, and mesopredator release: the dynamics of crop-raiding baboons in a managed landscape.

Ecology 2016 Apr;97(4):951-60

The establishment of protected areas or parks has become an important tool for wildlife conservation. However, frequent occurrences of human-wildlife conflict at the edges of these parks can undermine their conservation goals. Many African protected areas have experienced concurrent declines of apex predators alongside increases in both baboon abundance and the density of humans living near the park boundary. Baboons then take excursions outside of the park to raid crops for food, conflicting with the human population. We model the interactions of mesopredators (baboons), apex predators, and shared prey in the park to analyze how four components affect the proportion of time that mesopredators choose to crop-raid: (1) the presence of apex predators; (2) nutritional quality of the crops; (3) mesopredator "shyness" about leaving the park; and (4) human hunting of mesopredators. We predict that the presence of apex predators in the park is the most effective method for controlling mesopredator abundance, and hence significantly reduces their impact on crops. Human hunting of mesopredators is less effective as it only occurs during crop-raiding excursions. Furthermore, making crops less attractive, for instance by planting crops further from the park boundary or farming less nutritional crops, can reduce the amount of time mesopredators crop-raid.
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http://dx.doi.org/10.1890/15-0885.1DOI Listing
April 2016

Mapping Physiological Suitability Limits for Malaria in Africa Under Climate Change.

Vector Borne Zoonotic Dis 2015 Dec 18;15(12):718-25. Epub 2015 Nov 18.

10 Western Ecological Research Center, US Geological Survey, Marine Science Institute, University of California , Santa Barbara, California.

We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control.
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http://dx.doi.org/10.1089/vbz.2015.1822DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4700390PMC
December 2015

Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach.

Ecology 2015 Jan;96(1):203-13

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number R0. However, understanding the mechanisms linking R0 and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this, we show how a Bayesian approach can help identify critical uncertainties in components of R0 and how this uncertainty is propagated into the estimate of R0. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15 degrees C to 25 degrees C; fecundity across all temperatures, but especially approximately 25-32 degrees C; mortality from 20 degrees C to 30 degrees C; parasite development rate at degrees 15-16 degrees C and again at approximately 33-35 degrees C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of R0. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.
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http://dx.doi.org/10.1890/13-1964.1DOI Listing
January 2015

Experimental evolution alters the rate and temporal pattern of population growth in Batrachochytrium dendrobatidis, a lethal fungal pathogen of amphibians.

Ecol Evol 2014 Sep 3;4(18):3633-41. Epub 2014 Sep 3.

Department of Environmental Science, Policy and Management, University of California- Berkeley Berkeley, California, 94720-3144.

Virulence of infectious pathogens can be unstable and evolve rapidly depending on the evolutionary dynamics of the organism. Experimental evolution can be used to characterize pathogen evolution, often with the underlying objective of understanding evolution of virulence. We used experimental evolution techniques (serial transfer experiments) to investigate differential growth and virulence of Batrachochytrium dendrobatidis (Bd), a fungal pathogen that causes amphibian chytridiomycosis. We tested two lineages of Bd that were derived from a single cryo-archived isolate; one lineage (P10) was passaged 10 times, whereas the second lineage (P50) was passaged 50 times. We quantified time to zoospore release, maximum zoospore densities, and timing of zoospore activity and then modeled population growth rates. We also conducted exposure experiments with a susceptible amphibian species, the common green tree frog (Litoria caerulea) to test the differential pathogenicity. We found that the P50 lineage had shorter time to zoospore production (T min ), faster rate of sporangia death (d s ), and an overall greater intrinsic population growth rate (λ). These patterns of population growth in vitro corresponded with higher prevalence and intensities of infection in exposed Litoria caerulea, although the differences were not significant. Our results corroborate studies that suggest that Bd may be able to evolve relatively rapidly. Our findings also challenge the general assumption that pathogens will always attenuate in culture because shifts in Bd virulence may depend on laboratory culturing practices. These findings have practical implications for the laboratory maintenance of Bd isolates and underscore the importance of understanding the evolution of virulence in amphibian chytridiomycosis.
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http://dx.doi.org/10.1002/ece3.1199DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224537PMC
September 2014

Temperature alters reproductive life history patterns in Batrachochytrium dendrobatidis, a lethal pathogen associated with the global loss of amphibians.

Ecol Evol 2012 Sep 4;2(9):2241-9. Epub 2012 Aug 4.

Department of Environmental Science, Policy and Management, University of California- Berkeley Berkeley, California, 94720-3144, USA ; School of Public Health, Tropical Medicine and Rehabilitation Sciences, Amphibian Disease Ecology Group, James Cook University Townsville, Queensland, 4811, Australia.

Understanding how pathogens respond to changing environmental conditions is a central challenge in disease ecology. The environmentally sensitive fungal pathogen Batrachochytrium dendrobatidis (Bd), which causes the amphibian disease chytridiomycosis, has spread globally causing amphibian extirpations in a wide variety of climatic regions. To gain an in-depth understanding of Bd's responses to temperature, we used an integrative approach, combining empirical laboratory experiments with mathematical modeling. First, we selected a single Bd isolate and serially propagated two lineages of the isolate for multiple generations in two stable thermal conditions: 4°C (cold-adapted lineage) and 23°C (warm-adapted lineage). We quantified the production of infectious zoospores (fecundity), the timing of zoospore release, and zoospore activity in reciprocal temperature transplant experiments in which both Bd lineages were grown in either high or low temperature conditions. We then developed population growth models for the Bd lineages under each set of temperature conditions. We found that Bd had lower population growth rates, but longer periods of zoospore activity in the low temperature treatment (4°C) compared to the high temperature treatment (23°C). This effect was more pronounced in Bd lineages that were propagated in the low temperature treatment (4°C), suggesting a shift in Bd's response to low temperature conditions. Our results provide novel insights into the mechanisms by which Bd can thrive in a wide variety of temperature conditions, potentially altering the dynamics of chytridiomycosis and thus, the propensity for Bd to cause amphibian population collapse. We also suggest that the adaptive responses of Bd to thermal conditions warrant further investigation, especially in the face of global climate change.
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http://dx.doi.org/10.1002/ece3.334DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3488674PMC
September 2012

Optimal temperature for malaria transmission is dramatically lower than previously predicted.

Ecol Lett 2013 Jan 11;16(1):22-30. Epub 2012 Oct 11.

Ecology, Evolution, and Marine Biology Department, University of California, Santa Barbara, CA 93106, USA.

The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission.
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http://dx.doi.org/10.1111/ele.12015DOI Listing
January 2013

Parameter inference for an individual based model of chytridiomycosis in frogs.

J Theor Biol 2011 May 17;277(1):90-8. Epub 2011 Feb 17.

Department of Ecology, Evolution, and Marine Biology, University of California Santa Barbara, Santa Barbara, CA 93106, United States.

Individual based models (IBMs) and Agent based models (ABMs) have become widely used tools to understand complex biological systems. However, general methods of parameter inference for IBMs are not available. In this paper we show that it is possible to address this problem with a traditional likelihood-based approach, using an example of an IBM developed to describe the spread of chytridiomycosis in a population of frogs as a case study. We show that if the IBM satisfies certain criteria we can find the likelihood (or posterior) analytically, and use standard computational techniques, such as MCMC, for parameter inference.
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http://dx.doi.org/10.1016/j.jtbi.2011.02.010DOI Listing
May 2011

Dynamic energy budget theory and population ecology: lessons from Daphnia.

Philos Trans R Soc Lond B Biol Sci 2010 Nov;365(1557):3541-52

Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA 93106, USA.

Dynamic energy budget (DEB) theory offers a perspective on population ecology whose starting point is energy utilization by, and homeostasis within, individual organisms. It is natural to ask what it adds to the existing large body of individual-based ecological theory. We approach this question pragmatically--through detailed study of the individual physiology and population dynamics of the zooplankter Daphnia and its algal food. Standard DEB theory uses several state variables to characterize the state of an individual organism, thereby making the transition to population dynamics technically challenging, while ecologists demand maximally simple models that can be used in multi-scale modelling. We demonstrate that simpler representations of individual bioenergetics with a single state variable (size), and two life stages (juveniles and adults), contain sufficient detail on mass and energy budgets to yield good fits to data on growth, maturation and reproduction of individual Daphnia in response to food availability. The same simple representations of bioenergetics describe some features of Daphnia mortality, including enhanced mortality at low food that is not explicitly incorporated in the standard DEB model. Size-structured, population models incorporating this additional mortality component resolve some long-standing questions on stability and population cycles in Daphnia. We conclude that a bioenergetic model serving solely as a 'regression' connecting organismal performance to the history of its environment can rest on simpler representations than those of standard DEB. But there are associated costs with such pragmatism, notably loss of connection to theory describing interspecific variation in physiological rates. The latter is an important issue, as the type of detailed study reported here can only be performed for a handful of species.
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http://dx.doi.org/10.1098/rstb.2010.0167DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2981978PMC
November 2010

A statistical framework for the adaptive management of epidemiological interventions.

PLoS One 2009 Jun 5;4(6):e5807. Epub 2009 Jun 5.

Department of Statistical Science, Duke University, Durham, North Carolina, United States of America.

Background: Epidemiological interventions aim to control the spread of infectious disease through various mechanisms, each carrying a different associated cost.

Methodology: We describe a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic while simultaneously propagating uncertainty regarding the underlying disease model parameters through to the decision process. The strategies produced through this framework are adaptive: vaccination schedules are iteratively adjusted to reflect the anticipated trajectory of the epidemic given the current population state and updated parameter estimates.

Conclusions: Using simulation studies based on a classic influenza outbreak, we demonstrate the advantages of adaptive interventions over non-adaptive ones, in terms of cost and resource efficiency, and robustness to model misspecification.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0005807PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2688756PMC
June 2009

Microcolony and biofilm formation as a survival strategy for bacteria.

Authors:
Leah R Johnson

J Theor Biol 2008 Mar 5;251(1):24-34. Epub 2007 Nov 5.

Department of Physics, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.

Bacterial communities such as biofilms are widely recognized as being important for survival and persistence of bacteria in harsh environments. Mechanistic models of biofilm growth indicate that the way in which the surface is seeded can effect the morphology of simulated biofilms. Experimental studies indicate that genes which are important for chemotaxis also influence biofilm formation, perhaps by influencing aggregation on a surface. Understanding aggregation and microcolony formation could therefore help clarify factors influencing biofilm formation and illuminate how groups influence the fitness of bacteria. In this paper I develop an individual based model to examine how different behaviors involved in microcolony formation on a surface determine patterns of group sizes and link patterns to bacterial fitness.
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http://dx.doi.org/10.1016/j.jtbi.2007.10.039DOI Listing
March 2008

Life histories and the evolution of aging in bacteria and other single-celled organisms.

Mech Ageing Dev 2006 Oct 8;127(10):786-93. Epub 2006 Aug 8.

Department of Physics, University of California, 1156 High St., Santa Cruz, CA 95064, USA.

The disposable soma theory of aging was developed to explore how differences in lifespans and aging rates could be linked to life history trade-offs. Although generally applied for multicellular organisms, it is also useful for exploring life history strategies of single-celled organisms such as bacteria. Motivated by recent research of aging in E. coli, we explore the effects of aging on the fitness of simple single-celled organisms. Starting from the Euler-Lotka equation, we propose a mathematical model to explore how a finite reproductive lifespan affects fitness and resource allocation in simple organisms. This model provides quantitative predictions that have the potential for direct comparison with experiment, providing an opportunity to test the disposable soma theory more directly.
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http://dx.doi.org/10.1016/j.mad.2006.07.004DOI Listing
October 2006
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