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Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014–16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD’s incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.

Background. Human immunodeficiency virus (HIV) may influence the outcome and natural history of hepatitis C virus (HCV) infection through an impact on acute HCV-specific T cell responses. Methods. Fifty-five HIV-positive males with acute HCV infection were identified; monoinfected individuals (n = 8) were used for peripheral blood mononuclear cell comparison. In 14 coinfected and 8 HCV-monoinfected patients, HCV-specific T cell responses against a range of HCV antigens were assessed using interferon (IFN)—γ enzyme-linked immunospot (ELISpot) and proliferation assays. E1/E2 region genetic diversity and the selection pressure on the virus were measured in 8 coinfected patients by use of cloned sequences over time. Results. HCV persisted in 52 (95%) coinfected individuals. HCV/HIV coinfection significantly reduced IFN-γ ELISpot responses versus those in HCV-monoinfected individuals, especially against nonstructural proteins (1/10 vs. 5/8; P = .008). In coinfected patients, increasedHCVgenetic diversity was observed between the first and subsequent time points, with no evidence for positive selection in the E1/E2 region sequenced. Conclusion. HIV coinfection is associated with increased rates ofHCVpersistence and a lack of criticalCD4T cell responses, with no evidence of immune selection pressure during early HCV infection. Loss of key cellular immune responses against HCV during acute disease may contribute to the failure of early host control of HCV in HCV/HIV-coinfected patients.

Phylogenies reconstructed from gene sequences can be used to investigate the tempo and mode of species diversification. Here we develop and use new statistical methods to infer past patterns of speciation and extinction from molecular phylogenies. Specifically, we test the null hypothesis that per-lineage speciation and extinction rates have remained constant through time. Rejection of this hypothesis may provide evidence for evolutionary events such as adaptive radiations or key adaptations. In contrast to previous approaches, our methods are robust to incomplete taxon sampling and are conservative with respect to extinction. Using simulation we investigate, first, the adverse effects of failing to take incomplete sampling into account and, second, the power and reliability of our tests. When applied to published phylogenies our tests suggest that, in some cases, speciation rates have decreased through time.

Zika virus (ZIKV) transmission in the Americas was first confirmed in May 2015 in Northeast Brazil1. Brazil has the highest number of reported ZIKV cases worldwide (>200,000 by 24 Dec 2016) as well as the greatest number of cases associated with microcephaly and other birth defects (2,366 confirmed cases by 31 Dec 2016). Following the initial detection of ZIKV in Brazil, 47 countries and territories in the Americas have reported local ZIKV transmission, with 24 of these reporting ZIKV-associated severe disease. Yet the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of such information for interpreting past and future trends in reported microcephaly. To address this we generated 54 complete or partial ZIKV genomes, mostly from Brazil, and report data generated by the ZiBRA project - a mobile genomics lab that travelled across Northeast (NE) Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Joint analyses of viral genomes with ecological and epidemiological data estimate that ZIKV epidemic was present in NE Brazil by March 2014 and likely disseminated from there, both nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates of the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. NE Brazil's role in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the virus' basic reproduction number.

Dengue is an emerging tropical disease infecting tens of millions of people annually. A febrile illness with potentially severe hemorrhagic manifestations, dengue is caused by mosquito-borne viruses (DENV-1 to -4) that are maintained in endemic transmission in large urban centers of the tropics with periodic epidemic cycles at 3- to 5-year intervals. Puerto Rico (PR), a major population center in the Caribbean, has experienced increasingly severe epidemics since multiple dengue serotypes were introduced beginning in the late 1970s. We document the phylodynamics of DENV-4 between 1981 and 1998, a period of dramatic ecological expansion during which evolutionary change also occurs. The timescale of viral evolution is sufficiently short that viral transmission dynamics can be elucidated from genetic diversity data. Specifically, by combining virus sequence data with confirmed case counts in PR over these two decades, we show that the pattern of cyclic epidemics is strongly correlated with coalescent estimates of effective population size that have been estimated from sampled virus sequences using Bayesian Markov Chain Monte Carlo methods. Thus, we show that the observed epidemiologic dynamics are correlated with similar fluctuations in diversity, including severe interepidemic reductions in genetic diversity compatible with population bottlenecks that may greatly impact DENV evolutionary dynamics. Mean effective population sizes based on genetic data appear to increase prior to isolation counts, suggesting a potential bias in the latter and justifying more active surveillance of DENV activity. Our analysis explicitly integrates epidemiologic and sequence data in a joint model that could be used to further explore transmission models of infectious disease.

The yellow fever virus (YFV) epidemic in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes species mosquitos highlights a need to monitor the risk of reestablishment of urban YFV transmission in the Americas. We use a suite of epidemiological, spatial, and genomic approaches to characterize YFV transmission. We show that the age and sex distribution of human cases is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally reveals an early phase of sylvatic YFV transmission and spatial expansion toward previously YFV-free areas, followed by a rise in viral spillover to humans in late 2016. Our results establish a framework for monitoring YFV transmission in real time that will contribute to a global strategy to eliminate future YFV epidemics.

Hepatitis C virus (HCV) is a leading worldwide cause of liver disease. Here, we use a new model of HCV spread to investigate the epidemic behavior of the virus and to estimate its basic reproductive number from gene sequence data. We find significant differences in epidemic behavior among HCV subtypes and suggest that these differences are largely the result of subtype-specific transmission patterns. Our model builds a bridge between the disciplines of population genetics and mathematical epidemiology by using pathogen gene sequences to infer the population dynamic history of an infectious disease.

The evolution of the human immunodeficiency virus (HIV-1) during chronic infection involves the rapid, continuous turnover of genetic diversity. However, the role of natural selection, relative to random genetic drift, in governing this process is unclear. We tested a stochastic model of genetic drift using partial envelope sequences sampled longitudinally in 28 infected children. In each case the Bayesian posterior (empirical) distribution of coalescent genealogies was estimated using Markov chain Monte Carlo methods. Posterior predictive simulation was then used to generate a null distribution of genealogies assuming neutrality, with the null and empirical distributions compared using four genealogy-based summary statistics sensitive to nonneutral evolution. Because both null and empirical distributions were generated within a coalescent framework, we were able to explicitly account for the confounding influence of demography. From the distribution of corrected P-values across patients, we conclude that empirical genealogies are more asymmetric than expected if evolution is driven by mutation and genetic drift only, with an excess of low-frequency polymorphisms in the population. This indicates that although drift may still play an important role, natural selection has a strong influence on the evolution of HIV-1 envelope. A negative relationship between effective population size and substitution rate indicates that as the efficacy of selection increases, a smaller proportion of mutations approach fixation in the population. This suggests the presence of deleterious mutations. We therefore conclude that intrahost HIV-1 evolution in envelope is dominated by purifying selection against low-frequency deleterious mutations that do not reach fixation.

We compare the historical demographies of two Müllerian comimetic butterfly species: Heliconius erato and Heliconius melpomene. These species show an extensive parallel geographic divergence in their aposematic wing phenotypes. Recent studies suggest that this coincident mosaic results from simultaneous demographic processes shaped by extrinsic forces over Pleistocene climate fluctuations. However, DNA sequence variation at two rapidly evolving unlinked nuclear loci, Mannose phosphate isomerase (Mpi) and Triose phosphate isomerase (Tpi), show that the comimetic species have quite different quaternary demographies. In H. erato, despite ongoing lineage sorting across the Andes, nuclear genealogical estimates showed little geographical structure, suggesting high historical gene flow. Coalescent-based demographic analysis revealed population growth since the Pliocene period. Although these patterns suggest vicariant population sub-division associated with the Andean orogeny, they are not consistent with hypotheses of Pleistocene population fragmentation facilitating allopatric wing phenotype radiation in H. erato. In contrast, nuclear genetic diversity, θ, in H. melpomene was reduced relative to its comimic and revealed three phylogeographical clades. The pattern of coalescent events within regional clades was most consistent with population growth in relatively isolated populations after a recent period of restricted population size. These different demographic histories suggest that the wing-pattern radiations were not coincident in the two species. Instead, larger effective population size (Ne) in H. erato, together with profound population change in H. melpomene, supports an earlier hypothesis that H. erato diversified first as the model species of this remarkable mimetic association.