Biology subjects

Dushoff, J.

Publications and source records attributed to Dushoff, J..

14 recordsLinked to original sources

bioRxiv2026

A simple method of estimating rabies outbreak sizes from phylogenies

The ability to estimate the size of a disease outbreak is beneficial both for coordinating an outbreak response and for retrospectively evaluating the effectiveness of response measures and surveillance. Methods such as seroprevalence surveys and epidemiological modelling can be used for this purpose, but are not suitable for every outbreak. We develop a simple formula to estimate the proportion of outbreak cases sequenced, using only the per-generation substitution rate and the length of a phylogenetic tree. This proportion can then be used to estimate the outbreak size. We validate this method using subsampled data from fully observed simulated outbreaks, and then apply it to an ongoing rabies outbreak in the Philippines. We find that this method produces accurate estimates of outbreak size and can be applied to outbreaks with substitution rates and R0 values within the estimated range for rabies. We estimated that approximately 19% of cases from the outbreak in the Philippines had been sequenced, suggesting better than average case detection, with a resulting outbreak size estimate consistent with previous analyses. With this method and the associated R package POSER (https://github.com/RowanDurrant/poser), we aim to make rabies outbreak size estimation more accessible, but further work is required to improve its applicability to other diseases.

genetics↗

bioRxiv2026

Differences in codon usage between host-species-specific rabies virus clades are driven by UpA and purine content

Viral genes sometimes use certain codons more than others due to their nucleotide content, translational efficiency, and selection pressure from the host immune system. The rabies virus (RABV) is a negative strand RNA virus which can infect a broad range of mammalian hosts, with many of its clades circulating predominantly in specific host species. Previous work on codon usage in RABV has focused only on broader viral clades. We use publicly available RABV nucleoprotein gene sequences to investigate how dinucleotide content and codon usage biases differ between host-associated clades, and what drives these differences. We found that codon usage varies most between bat- and carnivore-associated RABV clades, and more subtly between host-species-specific minor clades within these groups. C1, GA3 and GT3 content were found to have a strong influence over codon usage patterns, and CpG content was higher in carnivore-associated RABV clades than in bat-associated clades. This, along with lower numbers of zinc-finger antiviral protein binding motifs than would be expected based on (di)nucleotide composition in bat-associated RABV sequences, suggests that bat-associated RABV clades may be under higher selection pressure from the hosts zinc-finger antiviral protein than carnivore-associated clades are, warranting further investigation of the mechanism underpinning this change.

microbiology↗

bioRxiv2024

Reducing spatial heterogeneity in coverage improves the effectiveness of dog vaccination against rabies

Vaccination programs are the mainstay of control for many infectious diseases. Heterogeneous coverage is hypothesised to reduce vaccination programme effectiveness, but this impact has not been quantified in real systems. We address this gap using fine-scale data from two decades of rabies contact tracing and dog vaccination campaigns in Serengeti district, Tanzania. We also aimed to identify drivers of continued circulation of rabies in the district despite annual vaccination campaigns. Using generalised linear mixed models, we find that current focal (village-level) dog rabies incidence decreases with increasing recent focal vaccination coverage. However, current focal incidence depends most on recent incidence, both focally and in the wider district, consistent with high population connectivity. Removing the masking effects of prior non-focal incidence shows that, for the same average prior non-focal (wider-district) vaccination coverage, increased heterogeneity in coverage among the non-focal villages leads to increased focal incidence. These effects led to outbreaks following years when vaccination campaigns missed many villages, whereas when heterogeneity in coverage was reduced, incidence declined to low levels (<0.4 cases/1,000 dogs annually and no human deaths) and short vaccination lapses thereafter did not lead to resurgence. Through transmission-tree reconstruction, we inferred frequent incursions into the district each year (mean of 7). Inferred incursions substantially increased as a percentage of all cases in recent years, reaching 50% in 2022, suggesting regional connectivity is driving residual transmission. Overall, we empirically demonstrate how population connectivity and spatial heterogeneity in vaccination can impact disease outcomes, highlighting the importance of fine-scale monitoring in managing vaccination programs.

ecology↗

bioRxiv2024

Reassessing global historical R0 estimates of canine rabies

Rabies spread by domestic dogs continues to cause tens of thousands of human deaths every year in low- and middle-income countries. Nevertheless rabies is often neglected, perhaps because it has already been eliminated from high-income countries through dog vaccination. Estimates of canine rabiess intrinsic reproductive number ([R]0), a metric of disease spread, from a wide range of times and locations are relatively low (values < 2), with narrow confidence intervals. Given rabiess persistence, this consistently low and narrow range of estimates is surprising. We combined incidence data from historical outbreaks of canine rabies from around the world with in-depth contact-tracing data from Tanzania to investigate initial growth rates (r0), generation-interval distributions (G), and reproductive numbers ([R]0). We improved on earlier estimates by choosing outbreak windows algorithmically; fitting r0 using a more appropriate statistical method that accounts for decreases through time; and incorporating uncertainty from both r0 and G in our confidence intervals on[R] 0. Our[R] 0 estimates are larger than previous estimates, with wider confidence intervals. These revised[R] 0 estimates suggest that a greater level of vaccination effort will be required to eliminate rabies than previously thought, but that the level of coverage required remains feasible. Our hybrid approach for estimating[R] 0 and its uncertainty is applicable to other disease systems where researchers estimate[R] 0 by combining data-based estimates of r0 and G.

ecology↗

bioRxiv2023

Examining the molecular clock hypothesis for the contemporary evolution of the rabies virus

The molecular clock hypothesis assumes that mutations accumulate on an organisms genome at a constant rate over time, but this assumption does not always hold true. While modelling approaches exist to accommodate deviations from a strict molecular clock, assumptions about rate variation may not fully represent the underlying evolutionary processes. There is considerable variability in rabies virus (RABV) incubation periods, ranging from days to over a year, during which viral replication may be reduced. This prompts the question of whether modelling RABV on a per infection generation basis might be more appropriate. We investigate how variable incubation periods affect root-to-tip divergence under per-unit time and per-generation models of mutation. Additionally, we assess how well these models represent root-to-tip divergence in time-stamped RABV sequences. We find that at low substitution rates (<1 substitution per genome per generation) divergence patterns between these models are difficult to distinguish, while above this threshold differences become apparent across a range of sampling rates. Using a Tanzanian RABV dataset, we calculate the mean substitution rate to be 0.17 substitutions per genome per generation. At RABVs substitution rate, the per-generation substitution model is unlikely to represent rabies evolution substantially differently than the molecular clock model when examining contemporary outbreaks; over enough generations for any divergence to accumulate, extreme incubation periods average out. However, measuring substitution rates per-generation holds potential in applications such as inferring transmission trees and predicting lineage emergence. Author SummaryRabies is a neglected disease that kills around 60,000 people each year. After entering the body, the incubation period of the virus is usually less than one month, but can sometimes span months to years. While we normally assume a virus accumulates mutations at a constant rate, it is possible that rabies occasional long incubation periods mean that mutations accumulate at varying rates if the virus replicates (and thus mutates) more slowly during the incubation period. We compared how the rabies virus evolves over time using two simulation models where mutations either occur per unit time or per infection generation. We also calculated the mean substitution rate per infection generation, which can be useful for inferring linkage between related rabies cases. We found that at realistic substitution rates for the rabies virus, we could not distinguish between the two models. Our calculations show that in most generations no mutations are expected to occur. Thus, over a time period long enough to observe genetic divergence, occasional long incubation periods would be "cancelled out" by shorter than average incubation periods, meaning that the two models are almost equivalent. However our work suggests that modelling substitution rates per generation may be useful for epidemiological inference.

microbiology↗

bioRxiv2020

Speed and strength of an epidemic intervention

An epidemic can be characterized by its speed (i.e., the exponential growth rate r) and strength (i.e., the reproductive number [R]). Disease modelers have historically placed much more emphasis on strength, in part because the effectiveness of an intervention strategy is typically evaluated on this scale. Here, we develop a mathematical framework for this classic, strength-based paradigm and show that there is a corresponding speed-based paradigm which can provide complementary insights. In particular, we note that r = 0 is a threshold for disease spread, just like [R] = 1, and show that we can measure the speed and strength of an intervention on the same scale as the speed and strength of an epidemic, respectively. We argue that, just as the strength-based paradigm provides the clearest insight into certain questions, the speed-based paradigm provides the clearest view in other cases. As an example, we show that evaluating the prospects of "test-and-treat" interventions against the human immunodeficiency virus (HIV) can be done more clearly on the speed than strength scale, given uncertainty in the proportion of HIV spread that happens early in the course of infection. We suggest that disease modelers should avoid over-emphasizing the reproductive number at the expense of the exponential growth rate, but instead look at these as complementary measures.

ecology↗

bioRxiv2019

Inferring generation-interval distributions from contact-tracing data

Generation intervals, defined as the time between when an individual is infected and when that individual infects another person, link two key quantities that describe an epidemic: the reproductive number, [Formula], and the rate of exponential growth, r. Generation intervals are often measured through contact tracing by identifying who infected whom. We study how observed intervals differ from \"intrinsic\" intervals that could be estimated by tracing individual-level infectiousness, and identify both spatial and temporal effects, including censoring (due to observation time), and the effects of susceptible depletion at various spatial scales. Early in an epidemic, we expect the variation in the observed generation intervals to be mainly driven by the censoring and the population structure near the source of disease spread; therefore, we predict that correcting observed intervals for the effect of temporal censoring but not for spatial effects will provide a spatially informed \"effective\" generation-interval distribution, which will correctly link r and [Formula]. We develop and test statistical methods for temporal corrections of generation intervals, and confirm our prediction using individual-based simulations on an empirical network.

ecology↗

bioRxiv2018

Male and female bees show large differences in floral preference

O_LIIntraspecific variation in foraging niche can drive food web dynamics and ecosystem processes. Field studies and theoretical analysis of plant-pollinator interaction networks typically focus on the partitioning of the floral community between pollinator species, with little attention paid to intraspecific variation among plants or foraging bees. In other systems, male and female animals exhibit different, cascading, impacts on interaction partners. Although the foraging ecology of male bees is little known, we expect foraging preferences to differ between male and female bees, which could strongly impact plant-pollinator interaction outcomes.\nC_LIO_LIWe designed an observational study to evaluate the strength and prevalence of sexually dimorphic foraging preferences in bees.\nC_LIO_LIWe observed bees visiting flowers in semi-natural meadows in New Jersey, USA. To detect differences in flower use against a shared background resource availability, we maximized the number of interactions observed within narrow spatio-temporal windows. To distinguish observed differences in bee use of flower species, which can reflect abundance patterns and sampling effects, from underlying differences in bee preferences, we analyzed our data with both a permutation-based null model and random effects models.\nC_LIO_LIWe found that the diets of male and female bees of the same species were often as dissimilar as the diets of bees of different species. Furthermore, we demonstrate differences in preference between male and female bees, and identify plant species that are particularly attractive to each sex. We show that intraspecific differences in preference can be robustly identified within interactions between hundreds of species, without precisely quantifying resource availability, and despite high phenological turnover.\nC_LIO_LIGiven the large differences in flower use and preference between male and female bees, ecological sex differences should be integrated into studies of bee demography, plant pollination, and coevolutionary relationships between flowers and insects.\nC_LI

ecology↗

bioRxiv2018

Equivalence of the Erlang SEIR epidemic model and the renewal equation

Most compartmental epidemic models can be represented using the Euler-Lotka renewal equation (RE). The value of the RE is not widely appreciated in the epidemiological modelling community, perhaps because its equivalence to standard models has not been presented rigorously in non-trivial cases. Here, we provide analytical expressions for the intrinsic generation interval distribution that must be used in the RE in order to yield epidemic dynamics that are identical to those of the susceptible-exposed-infectious-recovered (SEIR) compartmental model with Erlang-distributed latent and infectious periods. This class of models includes the standard (exponentially-distributed) SIR and SEIR models as special cases.

epidemiology↗

bioRxiv2018

Exploring how generation intervals link strength and speed of epidemics

Infectious-disease outbreaks are often characterized by the reproductive number and exponential rate of growth r. provides information about out-break control and predicted final size. Directly estimating is difficult, while r can often be estimated from incidence data. These quantities are linked by the generation interval - the time between when an individual is infected by an infector, and when that infector was infected. It is often infeasible to ob-tain the exact shape of a generation-interval distribution, and to understand how this shape affects estimates of . We show that estimating generation interval mean and variance provides insight into the relationship between and r. We use examples based on Ebola, rabies and measles to explore approximations based on gamma-distributed generation intervals, and find that use of these simple approximations are often sufficient to capture the r- relationship and provide robust estimates of .

epidemiology↗

bioRxiv2017

Quantifying ethical tradeoffs for vaccine efficacy trials during severe epidemics

BackgroundDuring emerging epidemics of highly fatal diseases, rapid development and testing of new vaccines may be critical to curbing transmission and saving lives. However, the design of vaccine efficacy trials in such contexts may face considerable logistical, epidemiological, or ethical impediments. Three different vaccine efficacy trials were conducted during the 2014-2016 Ebola virus epidemic in West Africa, each with different designs. At the time, there was vigorous debate on the tradeoff between a trials ability to yield information of scientific and societal value versus the perceived ethical dilemma of withholding potentially life-saving vaccines from control participants. Whereas the scientific value of a trial is often estimated in terms of statistical power, speed, and rigor, we lack similar metrics for the ethical costs of withholding interventions.\n\nMethods and FindingsHere, we introduce a conceptual framework that fills this gap and allows quantitative assessment of both the scientific value of a study and the risks incurred by trial participants. We show that even untested vaccines against severe diseases may be probabilistically beneficial--i.e. after accounting for realistic uncertainty in their safety and efficacy, trial participants are expected to be better off vaccinated than not. While accounting for this uncertainty, we estimate trial participant risk under a hypothetical, idealized vaccine rollout scenario and compare it to risk under various candidate trial designs, in order to elucidate specific quantitative tradeoffs between cumulative risk to trial participants and information gained. Through an illustrative simulation example, we highlight specific trial-design modifications that allow for conscientious balance between minimizing participant risk and acquiring information of societal value. These include modifications that affect the speed with which a trial would detect an efficacious vaccine (greater sample size or enrollment rate, interim analyses, or risk-prioritized vaccine rollout), which leads to earlier vaccination of control participants should the vaccine be efficacious, and those that systematically limit the risk \"spent\" by unvaccinated individuals (e.g., providing vaccination to controls after a delay, or presumptive vaccination of subjects above a risk threshold).\n\nConclusionWe advocate this conceptual approach as a means of clarifying the tensions between opposing viewpoints and facilitating transparent discussion to aid ethical and efficient responses to future emerging epidemics.

epidemiology↗

bioRxiv2017

Fitting mechanistic epidemic models to data: a comparison of simple Markov chain Monte Carlo approaches

BackgroundSimple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques. We use fits to simulated data, where parameters (and future behaviour) are known to explore the limitations of different platforms and quantify parameter estimation accuracy, forecasting accuracy, and computational efficiency across combinations of modeling decisions (e.g. discrete vs. continuous latent states, levels of stochasticity) and computational platforms (JAGS, NIMBLE, Stan).\n\nResultsModels incorporating at least one source of population-level variation (i.e., dispersion in either the transmission process or the observation process) provide reasonably good forecasts and parameter estimates, while models that incorporate only individual-level variation can lead to inaccurate (or overconfident) results. Models using continuous approximations to the transmission process showed improved computational efficiency without loss of accuracy.\n\nConclusionSimple models of disease transmission and observation can be fitted reliably to simple simulations, as long as population-level variation is taken into account. Continuous approximations can improve computational efficiency using more advanced MCMC techniques.

epidemiology↗

bioRxiv2016

Surveillance to Establish Elimination of Transmission and Freedom from Dog-mediated Rabies

BackgroundWith a global target set for zero human deaths from dog-mediated rabies by 2030 and some regional programmes close to eliminating canine rabies, there is an urgent need for enhanced surveillance strategies suitable for declaring freedom from disease and elimination of transmission with known confidence.\n\nMethodsUsing exhaustive contact tracing across settings in Tanzania we generated detailed data on rabies incidence, rabid dog biting behaviour and health-seeking behaviour of bite victims. Using these data we compared case detection of sampling-based and enhanced surveillance methodologies and investigated elimination verification procedures.\n\nFindingsWe demonstrate that patients presenting to clinics with bite injuries are sensitive sentinels for identifying dog rabies cases. Triage of patients based on bite history criteria and investigation of suspicious incidents can confirm >10% of dog rabies cases and is an affordable approach that will enable validation of disease freedom following two years without case detection. Approaches based on sampling the dog population without using bite-injury follow-up were found to be neither sensitive nor cost-effective.\n\nInterpretationThe low prevalence of rabies, and short window in which disease can be detected, preclude sampling-based surveillance. Instead, active case finding guided by bite-patient triage is needed as elimination is approached. Our proposed methodology is affordable, practical and supports the goal of eliminating human rabies deaths by improving administration of lifesaving post-exposure prophylaxis for genuinely exposed but untreated contacts. Moreover, joint investigations by public health and veterinary workers will strengthen intersectoral partnerships and capacity for control of emerging zoonoses.

epidemiology↗

bioRxiv2016

Eco-evolutionary theory and insect outbreaks

Eco-evolutionary theory argues that population cycles in consumer-resource interactions are partly driven by natural selection, such that changes in densities and changes in trait values are mutually reinforcing. Evidence that this theory explains cycles in nature, however, is almost nonexistent. Experimental tests of model predictions are almost always impossible because of the long time scales over which cycles occur, but for most organisms, even tests of model assumptions are logistically impractical. For insect baculoviruses in contrast, tests of model assumptions are straightforward, and baculoviruses often drive outbreaks of forest-defoliating insects, as in the gypsy moth that we study here. We therefore used field experiments with the gypsy moth baculovirus to test two key assumptions of eco-evolutionary models of host-pathogen population cycles, that reduced host infection risk is heritable and costly. Our experiments confirm the two assumptions, and inserting parameters estimated from our data into the models gives cycles closely resembling gypsy moth outbreak cycles in North America, whereas standard models predict unrealistic stable equilibria. Our work shows that eco-evolutionary models are useful for explaining outbreaks of forest insect defoliators, while widespread observations of intense selection imposed by natural enemies on defoliators, and frequent laboratory observations of heritable and costly resistance in defoliators, suggest that eco-evolutionary dynamics may play a general role in defoliator outbreaks.

ecology↗