Jonathan Dushoff

Estimating the global burden of endemic canine rabies.

Background Rabies is a notoriously underreported and neglected disease of low-income countries. This study aims to estimate the public health and economic burden of rabies circulating in domestic dog populations, globally and on a country-by-country basis, allowing an objective assessment of how much this preventable disease costs endemic countries. Methodology/Principal Findings We established relationships between rabies mortality and rabies prevention and control measures, which we incorporated into a model framework. We used data derived from extensive literature searches and questionnaires on disease incidence, control interventions and preventative measures within this framework to estimate the disease burden. The burden of rabies impacts on public health sector budgets, local communities and livestock economies, with the highest risk of rabies in the poorest regions of the world. This study estimates that globally canine rabies causes approximately 59,000 (95% Confidence Intervals: 25-159,000) human deaths, over 3.7 million (95% CIs: 1.6-10.4 million) disability-adjusted life years (DALYs) and 8.6 billion USD (95% CIs: 2.9-21.5 billion) economic losses annually. The largest component of the economic burden is due to premature death (55%), followed by direct costs of post-exposure prophylaxis (PEP, 20%) and lost income whilst seeking PEP (15.5%), with only limited costs to the veterinary sector due to dog vaccination (1.5%), and additional costs to communities from livestock losses (6%). Conclusions/Significance This study demonstrates that investment in dog vaccination, the single most effective way of reducing the disease burden, has been inadequate and that the availability and affordability of PEP needs improving. Collaborative investments by medical and veterinary sectors could dramatically reduce the current large, and unnecessary, burden of rabies on affected communities. Improved surveillance is needed to reduce uncertainty in burden estimates and to monitor the impacts of control efforts.

Phenotypic diversity and ecosystem functioning in changing environments: A theoretical framework

Biodiversity plays a vital role for ecosystem functioning in a changing environment. Yet theoretical approaches that incorporate diversity into classical ecosystem theory do not provide a general dynamic theory based on mechanistic principles. In this paper, we suggest that approaches developed for quantitative genetics can be extended to ecosystem functioning by modeling the means and variances of phenotypes within a group of species. We present a framework that suggests that phenotypic variance within functional groups is linearly related to their ability to respond to environmental changes. As a result, the long-term productivity for a group of species with high phenotypic variance may be higher than for the best single species, even though high phenotypic variance decreases productivity in the short term, because suboptimal species are present. In addition, we find that in the case of accelerating environmental change, species succession in a changing environment may become discontinuous. Our work suggests that this phenomenon is related to diversity as well as to the environmental disturbance regime, both of which are affected by anthropogenic activities. By introducing new techniques for modeling the aggregate behavior of groups of species, the present approach may provide a new avenue for ecosystem analysis.

Transmission Dynamics and Prospects for the Elimination of Canine Rabies

Rabies has been eliminated from domestic dog populations in Western Europe and North America, but continues to kill many thousands of people throughout Africa and Asia every year. A quantitative understanding of transmission dynamics in domestic dog populations provides critical information to assess whether global elimination of canine rabies is possible. We report extensive observations of individual rabid animals in Tanzania and generate a uniquely detailed analysis of transmission biology, which explains important epidemiological features, including the level of variation in epidemic trajectories. We found that the basic reproductive number for rabies, R0, is very low in our study area in rural Africa (∼1.2) and throughout its historic global range (<2). This finding provides strong support for the feasibility of controlling endemic canine rabies by vaccination, even near wildlife areas with large wild carnivore populations. However, we show that rapid turnover of domestic dog populations has been a major obstacle to successful control in developing countries, thus regular pulse vaccinations will be required to maintain population-level immunity between campaigns. Nonetheless our analyses suggest that with sustained, international commitment, global elimination of rabies from domestic dog populations, the most dangerous vector to humans, is a realistic goal.

Ecology and evolution of the flu

Influenza (flu) is a common infectious disease, but it is unusual in that the primary timescales for disease dynamics (epidemics) and viral evolution (new variants) are roughly the same. Recently, extraordinarily reliable phylogenetic reconstructions of flu virus evolution have been made using samples from both extant and extinct strains. In addition, because of their public health importance, flu epidemics have been monitored throughout the period over which the phylogenetic trees extend. In parallel with this empirical work, theoretical ecologists have developed mathematical and computational models that elucidate many properties of multistrain systems. In the future, to unravel and interpret the complex interactions between ecological and evolutionary forces on flu dynamics, the documented evolution of the virus must be related to the observed population dynamics of the disease. New theoretical insights are also required to simplify model structures and facilitate predictions that can be tested with accessible data.

Hemagglutinin sequence clusters and the antigenic evolution of influenza A virus

Continual mutations to the hemagglutinin (HA) gene of influenza A virus generate novel antigenic strains that cause annual epidemics. Using a database of 560 viral RNA sequences, we study the structure and tempo of HA evolution over the past two decades. We detect a critical length scale, in amino acid space, at which HA sequences aggregate into clusters, or swarms. We investigate the spatio-temporal distribution of viral swarms and compare it to the time series of the influenza vaccines recommended by the World Health Organization. We introduce a method for predicting future dominant HA amino acid sequences and discuss its potential relevance to vaccine choice. We also investigate the relationship between cluster structure and the primary antibody-combining regions of the HA protein.

The combined effects of pathogens and predators on insect outbreaks.

The economic damage caused by episodic outbreaks of forest-defoliating insects has spurred much research, yet why such outbreaks occur remains unclear. Theoretical biologists argue that outbreaks are driven by specialist pathogens or parasitoids, because host–pathogen and host–parasitoid models show large-amplitude, long-period cycles resembling time series of outbreaks. Field biologists counter that outbreaks occur when generalist predators fail, because predation in low-density defoliator populations is usually high enough to prevent outbreaks. Neither explanation is sufficient, however, because the time between outbreaks in the data is far more variable than in host–pathogen and host–parasitoid models, and far shorter than in generalist-predator models. Here we show that insect outbreaks can be explained by a model that includes both a generalist predator and a specialist pathogen. In this host–pathogen–predator model, stochasticity causes defoliator densities to fluctuate erratically between an equilibrium maintained by the predator, and cycles driven by the pathogen. Outbreaks in this model occur at long but irregular intervals, matching the data. Our results suggest that explanations of insect outbreaks must go beyond classical models to consider interactions among multiple species.

Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager

For species in which group membership frequently changes, it has been a challenge to characterize variation in individual interactions and social structure. Quantifying this variation is necessary to test hypotheses about ecological determinants of social patterns and to make predictions about how group dynamics affect the development of cooperative relationships and transmission processes. Network models have recently become popular for analyzing individual contacts within a population context. We use network metrics to compare populations of Grevy’s zebra (Equus grevyi) and onagers (Equus hemionus khur). These closely related equids, previously described as having the same social system, inhabit environments differing in the distribution of food, water, and predators. Grevy’s zebra and onagers are one example of many sets of coarsely similar fission–fusion species and populations, observed elsewhere in other ungulates, primates, and cetaceans. Our analysis of the population association networks reveals contrasts consistent with their distinctive environments. Grevy’s zebra individuals are more selective in their association choices. Grevy’s zebra form stable cliques, while onager associations are more fluid. We find evidence that females associate assortatively by reproductive state in Grevy’s zebra but not in onagers. The current approach demonstrates the utility of network metrics for identifying fine-grained variation among individuals and populations in association patterns. From our analysis, we can make testable predictions about behavioral mechanisms underlying social structure and its effects on transmission processes.

Codon bias and frequency-dependent selection on the hemagglutinin epitopes of influenza A virus

Although the surface proteins of human influenza A virus evolve rapidly and continually produce antigenic variants, the internal viral genes acquire mutations very gradually. In this paper, we analyze the sequence evolution of three influenza A genes over the past two decades. We study codon usage as a discriminating signature of gene- and even residue-specific diversifying and purifying selection. Nonrandom codon choice can increase or decrease the effective local substitution rate. We demonstrate that the codons of hemagglutinin, particularly those in the antibody-combining regions, are significantly biased toward substitutional point mutations relative to the codons of other influenza virus genes. We discuss the evolutionary interpretation and implications of these biases for hemagglutinins antigenic evolution. We also introduce information-theoretic methods that use sequence data to detect regions of recent positive selection and potential protein conformational changes.

Robust estimation of microbial diversity in theory and in practice.

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao’s estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics (‘Hill diversities’), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao’s estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.

Agricultural intensification, priming for persistence and the emergence of Nipah virus: a lethal bat-borne zoonosis

Emerging zoonoses threaten global health, yet the processes by which they emerge are complex and poorly understood. Nipah virus (NiV) is an important threat owing to its broad host and geographical range, high case fatality, potential for human-to-human transmission and lack of effective prevention or therapies. Here, we investigate the origin of the first identified outbreak of NiV encephalitis in Malaysia and Singapore. We analyse data on livestock production from the index site (a commercial pig farm in Malaysia) prior to and during the outbreak, on Malaysian agricultural production, and from surveys of NiVs wildlife reservoir (flying foxes). Our analyses suggest that repeated introduction of NiV from wildlife changed infection dynamics in pigs. Initial viral introduction produced an explosive epizootic that drove itself to extinction but primed the population for enzootic persistence upon reintroduction of the virus. The resultant within-farm persistence permitted regional spread and increased the number of human infections. This study refutes an earlier hypothesis that anomalous El Niño Southern Oscillation-related climatic conditions drove emergence and suggests that priming for persistence drove the emergence of a novel zoonotic pathogen. Thus, we provide empirical evidence for a causative mechanism previously proposed as a precursor to widespread infection with H5N1 avian influenza and other emerging pathogens.