Forecasting Hepatitis C Virus Status for Children in the United States: A Modeling Study

BACKGROUND

Virtually all cases of hepatitis C virus (HCV) infection in children in the United States occur through vertical transmission, but it is unknown how many children are infected. Cases of maternal HCV infection have increased in the United States, which may increase the number of children vertically infected with HCV. Infection has long-term consequences for a child's health, but treatment options are now available for children ≥3 years old. Reducing HCV infections in adults could decrease HCV infections in children.

METHODS

Using a stochastic compartmental model, we forecasted incidence of HCV infections in children in the United States from 2022 through 2027. The model considered vertical transmission to children <13 years old and horizontal transmission among individuals 13-49 years old. We obtained model parameters and initial conditions from the literature and the Centers for Disease Control and Prevention's 2021 Viral Hepatitis Surveillance Report.

RESULTS

Model simulations assuming direct-acting antiviral treatment for children forecasted that the number of acutely infected children would decrease slightly and the number of chronically infected children would decrease even more. Alone, treatment and early screening in individuals 13-49 years old reduced the number of forecasted cases in children and, together, these policy interventions were even more effective.

CONCLUSIONS

Based on our simulations, acute and chronic cases of HCV infection are remaining constant or slightly decreasing in the United States. Improving early screening and increasing access to treatment in adults may be an effective strategy for reducing the number of HCV infected children in the United States.

Characterizing the seasonal abundance and reproductive activity of overwintering Anopheles (Diptera: Culicidae) mosquitoes

In temperate regions of the United States, female Anopheles mosquitoes respond to low temperatures and short photoperiods by entering an overwintering dormancy or diapause. Diapause in Anopheles results in reduced frequency of blood-feeding and reproductive arrest, indicating a period when pathogen transmission by these mosquitoes is unlikely. However, it is unclear precisely how late into the fall and how early in the spring these mosquitoes are biting, reproducing, and potentially transmitting pathogens. This is further complicated by the lack of clear markers of diapause in Anopheles (e.g., changes in egg follicle length). Our goal was to characterize the seasonal reproductive activity of female Anopheles in central Ohio, United States and evaluate egg follicle length as an indicator of Anopheles diapause. We used traditional mosquito traps and aspirators to collect Anopheles from urban woodlots and culverts, respectively, from late September 2021 through mid-May 2022 in central Ohio. By measuring their egg follicle length, reproductive status, and blood-feeding status, we found that egg follicle length is not a reliable indicator of Anopheles diapause. We also found that a small proportion of An. punctipennis (Say), An. perplexens (Ludlow), and An. quadrimaculatus (Say) continued to bite and reproduce into early November 2021 and that females of these species terminated reproductive dormancy and began biting by mid-March 2022. This period of reproductive activity extends beyond current mosquito surveillance and control in Ohio. Our findings suggest that within temperate regions of North America, Anopheles have the capacity to transmit pathogens throughout the spring, summer, and fall.

Mumps epidemic dynamics in the United States before vaccination (1923-1932)

Mumps is a vaccine-preventable, reemerging, and highly transmissible infectious disease. Widespread vaccination dramatically reduced cases; however, case counts have been increasing over the past 20 years. To provide a quantitative overview of historical mumps dynamics that can act as baseline information to help identify causes of mumps reemergence, we analyzed timeseries of cases reported from 1923 to 1932 in the United States. During that time, 239,230 mumps cases were reported in 70 cities. Larger cities reported annual epidemics and smaller cities reported intermittent, sporadic outbreaks. The critical community size above which transmission continuously occurred was likely between 365,583 and 781,188 individuals but could range as high as 3,376,438 individuals. Mumps cases increased as city size increased, suggesting density-dependent transmission. Using a density-dependent SEIR model, we calculated a mean effective reproductive number (Re) of 1.2. Re varied by city and over time, with periodic high values that could characterize short periods of very high transmission known as superspreading events. Case counts most often peaked in March, with higher-than-average transmission from December through April and showed a correlation with weekly births. While certain city pairs in Midwestern states had synchronous outbreaks, most outbreaks were less synchronous and not driven by distance between cities. This work demonstrates the importance of long-term infectious disease surveillance data and will inform future studies on mumps reemergence and control.

Characterizing seasonal changes in the reproductive activity of Culex mosquitoes throughout the fall, winter, and spring in Ohio

BACKGROUND

Culex mosquitoes are the primary vectors of West Nile virus (WNV) across the USA. Understanding when these vectors are active indicates times when WNV transmission can occur. This study determined the proportion of female Culex mosquitoes that were in diapause during the fall and winter and when they terminated diapause and began blood feeding in the spring.

METHODS

Mosquitoes were collected from parks using various traps and/or aspirated from culverts in Franklin County, Ohio, from October to mid-May from 2019 to 2022. Culex mosquitoes were morphologically identified to species, and the ovaries of females were dissected to determine their diapause and parity statuses.

RESULTS

By early October 2021, roughly 95% of Culex pipiens collected in culverts were in diapause and 98% of Cx. erraticus were in diapause. Furthermore, gravid and blood-fed Culex salinarius, Cx. pipiens, and Cx. restuans were collected in late November in 2019 and 2021 in standard mosquito traps. In the winter of 2021, the proportions of non-diapausing Culex decreased within culverts. The last non-diapausing Cx. erraticus was collected in late December 2021 while the final non-diapausing Cx. pipiens was collected in mid-January 2022, both in culverts. Roughly 50% of Cx. pipiens terminated diapause by mid-March 2022, further supported by our collections of gravid females in late March in all 3 years of mosquito collection. In fact, male mosquitoes of Cx. pipiens, Cx. restuans, and Cx. territans were collected by the 1st week of May in 2022, indicating that multiple species of Culex produced a second generation that reached adulthood by this time.

CONCLUSIONS

We collected blood-fed and gravid Culex females into late November in 2 of the 3 years of our collections, indicating that it might be possible for WNV transmission to occur in late fall in temperate climates like Ohio. The persistence of non-diapausing Cx. pipiens and Cx. erraticus throughout December has important implications for the winter survival of WNV vectors and our overall understanding of diapause. Finally, determining when Culex terminate diapause in the spring may allow us to optimize mosquito management programs and reduce the spread of WNV before it is transmitted to humans.

Quantifying intra- and inter-species contact rates at supplemental feeding sites in Ethiopia to inform rabies maintenance potential of multiple host species

Rabies, a multi-host pathogen responsible for the loss of roughly 59,000 human lives each year worldwide, continues to impose a significant burden of disease despite control efforts, especially in Ethiopia. However, how species other than dogs contribute to rabies transmission throughout Ethiopia remains largely unknown. In this study, we quantified interactions among wildlife species in Ethiopia with the greatest potential for contributing to rabies maintenance. We observed wildlife at supplemental scavenging sites across multiple landscape types and quantified transmission potential. More specifically, we used camera trap data to quantify species abundance, species distribution, and intra- and inter-species contacts per trapping night over time and by location. We derived a mathematical expression for the basic reproductive number (R₀ ) based on within- and between-species contract rates by applying the next generation method to the susceptible, exposed, infectious, removed model. We calculated R₀ for transmission within each species and between each pair of species using camera trap data in order to identify pairwise interactions that contributed the most to transmission in an ecological community. We estimated which species, or species pairs, could maintain transmission ( R 0 > 1 ${R_0} &gt; 1$ ) and which species, or species pairs, had contact rates too low for maintenance ( R 0 < 1 ${R_0} &lt; 1$ ). Our results identified multiple urban carnivores as candidate species for rabies maintenance throughout Ethiopia, with hyenas exhibiting the greatest risk for rabies maintenance through intra-species transmission. Hyenas and cats had the greatest risk for rabies maintenance through inter-species transmission. Urban and peri-urban sites posed the greatest risk for rabies transmission. The night-time hours presented the greatest risk for a contact event that could result in rabies transmission. Overall, both intra- and inter-species contacts posed risk for rabies maintenance. Our results can be used to target future studies and inform population management decisions.

Critical Photoperiod and Its Potential to Predict Mosquito Distributions and Control Medically Important Pests

Diapause, a period of arrested development that allows mosquitoes to survive inhospitable conditions, is triggered by short daylengths in temperate mosquitoes. Different populations of mosquitoes initiate diapause in response to a specific photoperiod, or daylength, resulting in population-specific differences in annual cycles of abundance. The photoperiod that causes approximately 50% of a population to initiate diapause is known as the critical photoperiod (CPP). The autumn daylength corresponding to the CPP in the field likely marks the day beyond which the photoperiods would trigger and maintain 50% or more diapause incidence in a population, although temperature, diet, and other factors can impact diapause initiation. In the Northern Hemisphere, northern populations of mosquitoes experience lower temperatures earlier in the year and must be triggered into diapause by longer daylengths than southern populations. CPP is genetically based, but also adapts over time responding to the population's environment. Therefore, CPP has been shown to lengthen with increasing latitude and altitude. While the positive correlation between CPP and latitude/altitude has been established in a few mosquito species, including Aedes albopictus (Skuse, Diptera: Culicidae), Aedes triseriatus, Aedes sierrensis, and Wyeomyia smithii (Coquillett, Diptera: Culicidae), we do not know when most other species initiate their seasonal responses. As several of these species transmit important diseases, characterizing the CPP of arthropod vectors could improve existing control by ensuring that surveillance efforts align with the vector's seasonally active period. Additionally, better understanding when mosquitoes and other vectors initiate diapause can reduce the frequency of chemical applications, thereby ameliorating the negative impacts to nontarget insects.

Multiple urban stressors drive fish-based ecological networks in streams of Columbus, Ohio, USA

Integrating a network perspective into multiple-stressor research can reveal indirect stressor effects and simultaneously estimate both taxonomic and functional community characteristics, thus representing a novel approach to stressor paradigms in rivers. Using six years of data from twelve streams of Columbus, Ohio, USA, the effects of nutrients (N:P), impervious surface (%IS), and sedimentation on network properties were quantified. Variability in the strength and distribution of trophic interactions was assessed by incorporating biomass into networks. All stressors impacted some properties of network topology - linkage density (average number of links per species), connectance (fraction of all possible links realized in a network), and compartmentalization (degree to which networks contain discrete sub-webs), including synergistic interactive effects between sedimentation and stream size. We also found support for antagonistic effects between (1) sedimentation and %IS and between %IS and N:P on the weighted index mean link weight, which represents the magnitude of trophic interactions among species in a network, and (2) %IS and stream size on strength standard deviation, a measure of the distribution of total magnitude of all trophic interactions per species in a network. Overall, our results point to the potential for urban stressors such as impervious surfaces and sedimentation - alone and as interactions - to decrease network complexity, compartmentalization, and stability, likely through homogenizing habitat and limiting food resources. The observation that larger streams often buffered the negative effects of these stressors suggests that restoration and other management approaches might be most beneficial in smaller headwater streams of urban catchments.

Network analyses to quantify effects of host movement in multilevel disease transmission models using foot and mouth disease in Cameroon as a case study

The dynamics of infectious diseases are greatly influenced by the movement of both susceptible and infected hosts. To accurately represent disease dynamics among a mobile host population, detailed movement models have been coupled with disease transmission models. However, a number of different host movement models have been proposed, each with their own set of assumptions and results that differ from the other models. Here, we compare two movement models coupled to the same disease transmission model using network analyses. This application of network analysis allows us to evaluate the fit and accuracy of the movement model in a multilevel modeling framework with more detail than established statistical modeling fitting methods. We used data that detailed mobile pastoralists’ movements as input for 100 stochastic simulations of a Spatio-Temporal Movement (STM) model and 100 stochastic simulations of an Individual Movement Model (IMM). Both models represent dynamic movement and subsequent contacts. We generated networks in which nodes represent camps and edges represent the distance between camps. We simulated pathogen transmission over these networks and tested five network metrics–strength, betweenness centrality, three-step reach, density, and transitivity–to determine which could predict disease simulation outcomes and thereby be used to correlate model simulation results with disease transmission simulations. We found that strength, network density, and three-step reach of movement model results correlated with the final epidemic size of outbreak simulations. Betweenness centrality only weakly correlated for the IMM model. Transitivity only weakly correlated for the STM model and time-varying IMM model metrics. We conclude that movement models coupled with disease transmission models can affect disease transmission results and should be carefully considered and vetted when modeling pathogen spread in mobile host populations. Strength, network density, and three-step reach can be used to evaluate movement models before disease simulations to predict final outbreak sizes. These findings can contribute to the analysis of multilevel models across systems.

Epidemics of infectious disease vary geographically and vary through time. A large part of this variation is caused by movement of individuals who are susceptible to the disease or infected with the disease. To study how movement affects epidemics, researchers often combine movement models with transmission models. However, multiple movement models have been proposed, and their effect on infectious disease model output is not well understood. Here, we combine two different movement models that we developed to represent mobile pastoralists in the Far North Region, Cameroon, with the same disease transmission model. We use network metrics to test how different movement models can affect the output of the disease transmission model. We found that three metrics could be applied to movement model output in order to predict epidemic model output. We conclude that movement models coupled with disease transmission models can affect disease transmission results and should be carefully considered and vetted when modeling epidemics.

Modeling the role of carrier and mobile herds on foot-and-mouth disease virus endemicity in the Far North Region of Cameroon

Foot and mouth disease virus (FMDV) is an RNA virus that infects cloven-hoofed animals, often produces either epidemic or endemic conditions, and negatively affects agricultural economies worldwide. FMDV epidemic dynamics have been extensively studied, but understanding of drivers of disease persistence in areas in which FMDV is endemic, such as most of sub-Saharan Africa, is lacking. We present a spatial stochastic model of disease dynamics that incorporates a spatial transmission kernel in a modified Gillespie algorithm, and use it to evaluate two hypothesized drivers of endemicity: asymptomatic carriers and the movement of mobile herds. The model is parameterized using data from the pastoral systems in the Far North Region of Cameroon. Our computational study provides evidence in support of the hypothesis that asymptomatic carriers, but not mobile herds, are a driver of endemicity.

Network analyses of transhumance movements and simulations of foot-and-mouth disease virus transmission among mobile livestock in Cameroon

Foot-and-mouth disease (FMD) affects cloven-hoofed livestock and agricultural economies worldwide. Analyses of the 2001 FMD outbreak in the United Kingdom informed how livestock movement contributed to disease spread. However, livestock reared in other locations use different production systems that might also influence disease dynamics. Here, we investigate a livestock production system known as transhumance, which is the practice of moving livestock between seasonal grazing areas. We built mechanistic models using livestock movement data from the Far North Region of Cameroon. We represented these data as a dynamic network over which we simulated disease transmission and examined three questions. First, we asked what were characteristics of simulated FMDV transmission across a transhumant pastoralist system. Second, we asked how simulated FMDV transmission across a transhumant pastoralist system differed from transmission across this same population held artificially stationary, thereby revealing the effect of movement on disease dynamics. Third, we asked if disease simulations on well-studied theoretical networks are similar to disease simulations on this empirical dynamic network. The results show that the empirical dynamic network was sparsely connected except for an eight-week period in September and October when pastoralists move from rainy season to dry season grazing areas. The mean epidemic size across all 3,744 simulations was 99.9% and the mean epidemic duration was 1.45 years. Disease simulations across the static network showed a smaller mean epidemic size (27.6%) and a similar epidemic duration (1.5 years). Epidemics simulated on theoretical networks showed similar final epidemic sizes (100%) and different mean durations. Our simulations indicate that transhumant livestock systems have the potential to host FMDV outbreaks that affect almost all livestock and last longer than a year. Furthermore, our comparison of empirical and theoretical networks underscores the importance of using empirical data to understand the role of mobility in the transmission of infectious diseases.

Host species heterogeneity in the epidemiology of Nesopora caninum

Pathogen transmission across species drives disease emergence; however, mechanisms by which multi-host pathogens cross species boundaries are not well identified. This knowledge gap prevents integrated and targeted control in an epidemiologically continuous ecosystem. Our goal is to describe the impact of host species heterogeneity on the epidemiology of Neospora caninum circulating between livestock and wildlife in southeastern Ohio. We collected biological samples from Père David’s deer (Elaphurus davidianus) located at an outdoor wildlife conservation center; from cattle raised at farms adjacent to the center; and from wild white-tailed deer that roamed across farm and center boundaries. We designed nested infectious disease models of competing hypotheses about transmission and used collected data to fit the models, thereby estimating important immunological and transmission quantities which describe the species-specific contribution to the persistence of this pathogen in the community. We applied these data and models to suggest appropriate species-specific disease control methods. Results show that immunity in cattle and Pére David’s deer wanes over time, while in white-tailed deer immunity appears to be lifelong. Transmission quantities for cattle were estimated at values below the threshold for an outbreak (R_t < 1), meaning that chains of transmission are not maintained within this population and infections must occur due to reintroduction from an outside source. Pére David’s deer and white-tailed deer both could maintain continuous chains of transmission within their group (R_t > 1). Therefore, we propose that control of contact with outside sources will be useful for disease control in cattle; boosting immunity with vaccines might be an avenue to prevent infection in cattle and Père David’s deer. White-tailed deer are a potential maintenance host for infection and require further study to determine optimal control methods. Community-level investigations like this allow us to better evaluate heterogeneities in transmission processes that ultimately guide targeted control.

Data-Driven Models of Foot-and-Mouth Disease Dynamics: A Review

Foot-and-mouth disease virus (FMDV) threatens animal health and leads to considerable economic losses worldwide. Progress towards minimizing both veterinary and financial impact of the disease will be made with targeted disease control policies. To move towards targeted control, specific targets and detailed control strategies must be defined. One approach for identifying targets is to use mathematical and simulation models quantified with accurate and fine-scale data to design and evaluate alternative control policies. Nevertheless, published models of FMDV vary in modelling techniques and resolution of data incorporated. In order to determine which models and data sources contain enough detail to represent realistic control policy alternatives, we performed a systematic literature review of all FMDV dynamical models that use host data, disease data or both data types. For the purpose of evaluating modelling methodology, we classified models by control strategy represented, resolution of models and data, and location modelled. We found that modelling methodology has been well developed to the point where multiple methods are available to represent detailed and contact-specific transmission and targeted control. However, detailed host and disease data needed to quantify these models are only available from a few outbreaks. To address existing challenges in data collection, novel data sources should be considered and integrated into models of FMDV transmission and control. We suggest modelling multiple endemic areas to advance local control and global control and better understand FMDV transmission dynamics. With incorporation of additional data, models can assist with both the design of targeted control and identification of transmission drivers across geographic boundaries.

Serotype-Specific Transmission and Waning Immunity of Endemic Foot-and-Mouth Disease Virus in Cameroon

Foot-and-mouth disease virus (FMDV) causes morbidity and mortality in a range of animals and threatens local economies by acting as a barrier to international trade. The outbreak in the United Kingdom in 2001 that cost billions to control highlighted the risk that the pathogen poses to agriculture. In response, several mathematical models have been developed to parameterize and predict both transmission dynamics and optimal disease control. However, a lack of understanding of the multi-strain etiology prevents characterization of multi-strain dynamics. Here, we use data from FMDV serology in an endemic setting to probe strain-specific transmission and immunodynamics. Five serotypes of FMDV affect cattle in the Far North Region of Cameroon. We fit both catalytic and reverse catalytic models to serological data to estimate the force of infection and the rate of waning immunity, and to detect periods of sustained transmission. For serotypes SAT2, SAT3, and type A, a model assuming life-long immunity fit better. For serotypes SAT1 and type O, the better-fit model suggests that immunity may wane over time. Our analysis further indicates that type O has the greatest force of infection and the longest duration of immunity. Estimates for the force of infection were time-varying and indicated that serotypes SAT1 and O displayed endemic dynamics, serotype A displayed epidemic dynamics, and SAT2 and SAT3 did not sustain local chains of transmission. Since these results were obtained from the same population at the same time, they highlight important differences in transmission specific to each serotype. They also show that immunity wanes at rates specific to each serotype, which influences patterns of local persistence. Overall, this work shows that viral serotypes can differ significantly in their epidemiological and immunological characteristics. Patterns and processes that drive transmission in endemic settings must consider complex viral dynamics for accurate representation and interpretation.

Spatial and Temporal Characteristics of Pastoral Mobility in the Far North Region, Cameroon: Data Analysis and Modeling

Modeling the movements of humans and animals is critical to understanding the transmission of infectious diseases in complex social and ecological systems. In this paper, we focus on the movements of pastoralists in the Far North Region of Cameroon, who follow an annual transhumance by moving between rainy and dry season pastures. Describing, summarizing, and modeling the transhumance movements in the region are important steps for understanding the role these movements may play in the transmission of infectious diseases affecting humans and animals. We collected data on this transhumance system for four years using a combination of surveys and GPS mapping. An analysis on the spatial and temporal characteristics of pastoral mobility suggests four transhumance modes, each with its own properties. Modes M1 and M2 represent the type of transhumance movements where pastoralists settle in a campsite for a relatively long period of time (≥20 days) and then move around the area without specific directions within a seasonal grazing area. Modes M3 and M4 on the other hand are the situations when pastoralists stay in a campsite for a relatively short period of time (<20 days) when moving between seasonal grazing areas. These four modes are used to develop a spatial-temporal mobility (STM) model that can be used to estimate the probability of a mobile pastoralist residing at a location at any time. We compare the STM model with two reference models and the experiments suggest that the STM model can effectively capture and predict the space-time dynamics of pastoral mobility in our study area.

Analysis and visualization of H7 influenza using genomic, evolutionary and geographic information in a modular web service

We have reported previously on use of a web-based application, Supramap (http://supramap.org) for the study of biogeographic, genotypic, and phenotypic evolution. Using Supramap we have developed maps of the spread of drug-resistant influenza and host shifts in H1N1 and H5N1 influenza and coronaviruses such as SARS. Here we report on another zoonotic pathogen, H7 influenza, and provide an update on the implementation of Supramap as a web service. We find that the emergence of pathogenic strains of H7 is labile with many transitions from high to low pathogenicity, and from low to high pathogenicity. We use Supramap to put these events in a temporal and geospatial context. We identify several lineages of H7 influenza with biomarkers of high pathogenicity in regions that have not been reported in the scientific literature. The original implementation of Supramap was built with tightly coupled client and server software. Now we have decoupled the components to provide a modular web service for POY (http://poyws.org) that can be consumed by a data provider to create a novel application. To demonstrate the web service, we have produced an application, Geogenes (http://geogenes.org). Unlike in Supramap, in which the user is required to create and upload data files, in Geogenes the user works from a graphical interface to query an underlying dataset. Geogenes demonstrates how the web service can provide underlying processing for any sequence and metadata database. © The Willi Hennig Society 2012.

Reassortment Networks and the evolution of pandemic H1N1 swine-origin influenza

Prior research developed Reassortment Networks to reconstruct the evolution of segmented viruses under both reassortment and mutation. We report their application to the swine-origin pandemic H1N1 virus (S-OIV). A database of all influenza A viruses, for which complete genome sequences were available in Genbank by October 2009, was created and dynamic programming was used to compute distances between all corresponding segments. A reassortment network was created to obtain the minimum cost evolutionary paths from all viruses to the exemplar S-OIV A/California/04/2009. This analysis took 35 hours on the Cray Extreme Multithreading (XMT) supercomputer, which has special hardware to permit efficient parallelization. Six specific H1N1/H1N2 bottleneck viruses were identified that almost always lie on minimum cost paths to S-OIV. We conjecture that these viruses are crucial to S-OIV evolution and worthy of careful study from a molecular biology viewpoint. In phylogenetics, ancestors are typically medians that have no functional constraints. In our method, ancestors are not inferred, but rather chosen from previously observed viruses along a path of mutation and reassortment leading to the target virus. This specificity and functional constraint render our results actionable for further experiments in vitro and in vivo.

Stage-structured transmission of phocine distemper virus in the Dutch 2002 outbreak

Heterogeneities in transmission among hosts can be very important in shaping infectious disease dynamics. In mammals with strong social organization, such heterogeneities are often structured by functional stage: juveniles, subadults and adults. We investigate the importance of such stage-related heterogeneities in shaping the 2002 phocine distemper virus (PDV) outbreak in the Dutch Wadden Sea, when more than 40 per cent of the harbour seals were killed. We do this by comparing the statistical fit of a hierarchy of models with varying transmission complexity: homogeneous versus heterogeneous mixing and density- versus frequency-dependent transmission. We use the stranding data as a proxy for incidence and use Poisson likelihoods to estimate the 'who acquires infection from whom' (WAIFW) matrix. Statistically, the model with strong heterogeneous mixing and density-dependent transmission was found to best describe the transmission dynamics. However, patterns of incidence support a model of frequency-dependent transmission among adults and juveniles. Based on the maximum-likelihood WAIFW matrix estimates, we use the next-generation formalism to calculate an R(0) between 2 and 2.5 for the Dutch 2002 PDV epidemic.

The evolutionary and epidemiological dynamics of the paramyxoviridae

Paramyxoviruses are responsible for considerable disease burden in human and wildlife populations: measles and mumps continue to affect the health of children worldwide, while canine distemper virus causes serious morbidity and mortality in a wide range of mammalian species. Although these viruses have been studied extensively at both the epidemiological and the phylogenetic scales, little has been done to integrate these two types of data. Using a Bayesian coalescent approach, we infer the evolutionary and epidemiological dynamics of measles, mumps and canine distemper viruses. Our analysis yielded data on viral substitution rates, the time to common ancestry, and elements of their demographic history. Estimates of rates of evolutionary change were similar to those observed in other RNA viruses, ranging from 6.585 to 11.350 x 10(-4 )nucleotide substitutions per site, per year. Strikingly, the mean Time to the Most Recent Common Ancestor (TMRCA) was both similar and very recent among the viruses studied, ranging from only 58 to 91 years (1908 to 1943). Worldwide, the paramyxoviruses studied here have maintained a relatively constant level of genetic diversity. However, detailed heterchronous samples illustrate more complex dynamics in some epidemic populations, and the relatively low levels of genetic diversity (population size) in all three viruses is likely to reflect the population bottlenecks that follow recurrent outbreaks.