Nicotiana species from diverse geographic regions and ploidy levels was assessed for resistance to non-coevolved viruses from the genus Nepovirus, family Secoviridae. The heritability of resistance was tested in a panel of synthetic allopolyploids. Leaves of different positions on each inoculated plant were tested for virus presence and a subset of plants was re-inoculated and assessed for systemic recovery.The relationship between allopolyploidy and plant virus resistance is poorly understood. To determine the relationship of plant evolutionary history and basal virus resistance, a panel of Nicotiana species, but this trend did not hold when synthetic allopolyploids were taken into account. Furthermore, a relationship between resistance and geographical origin was observed.Depending on the host-virus combination, plants displayed immunity, susceptibility or intermediate levels of resistance. Synthetic allopolyploids showed an incompletely dominant resistance phenotype and manifested systemic recovery. Plant ploidy was weakly negatively correlated with virus resistance in The gradients of resistance and virulence corresponded to a modified matching allele model of resistance. Intermediate resistance responses of allopolyploids corresponded with a model of multi-allelic additive resistance. The variable virus resistance of extant allopolyploids suggested that selection-based mechanisms surpass ploidy with respect to evolution of basal resistance to viruses. The ‘Red Queen Hypothesis’ suggests that coevolution between hosts and pathogens or pests results in a ‘boom and bust’ cycle where neither host nor its invader can gain lasting supremacy . AllopolNicotiana has been used as a model system for studying plant-virus interactions and for investigating genotypic and phenotypic changes that occur at and after polyploidization , except for GFLV-F13-inoculated 2 × (N. tabacum × N. benthamiana), where 23 plants in an original population of 70 plants was sampled for virus presence in apical leaves in a stratified sampling approach.Twenty-four DAS-ELISA was used to determine virus presence or absence for 2719 GFLV samples and 536 ToRSV samples in 48 plant-virus combinations. DAS-ELISA absorbance values had a bimodal distribution, which allowed a clear delineation of virus-positive from virus-negative samples. Infection frequencies at each leaf position in each virus-host sample group were summed to calculate virus incidence, which was the dependent variable in correlation analyses. The trajectory of virus incidence among leaf positions in given host-virus combinations were evaluated to generate six discrete resistance categories. Based on the spatial distribution of virus in host plants, host-virus interactions were labeled ‘susceptible’, ‘immune’ or one of four categories of recovery , or ‘delayed susceptibility’.N. benthamiana, N. clevelandii, N. goodspeedii and 2 × (N. tabacum × N. benthamiana), and for ToRSV-AP on N. benthamiana and 2 × (N. tabacum × N. benthamiana). GFLV-GHu symptoms on N. benthamiana and N. clevelandii were consistent with those previously described  showed late recovery to ToRSV-AP (Table . 2 × (N. tabacum × N. benthamiana) and 4 ×  showed late recovery to GFLV-F13, and 4x, 4 × (N. sylvestris × N. otophora), 4 × (N. sylvestris × N. tomentosiformis), 4 × (N. glutinosa x N. tabacum), N. glutinosa, N. paniculata and N. setchelii showed late recovery to GFLV-GHu (Table . Intermediate recovery (category 4), characterized by fluctuation of virus incidence over three or more leaf axes  and 2 × (N. tabacum × N. benthamiana), and in GFLV-F13-inoculated 4 × (N. debneyi × N. clevelandii) (Table Late recovery (category 3) was the most frequent host-virus interaction phenomenon observed in this test panel, and was seen for all virus isolates tested. All tested members of section AP Table . 2 ×   were susceptible to ToRSV-AP  was observed only in response to GFLV-GHu inoculation of ) Figure ; Table 2expected , N. goodNicotiana allopolyploids. Whereas N. tabacum showed high resistance to GFLV-GHu, ToRSV-AP and GFLV-F13, and N. benthamiana was fully susceptible to all three virus strains, 2 × (N. tabacum × N. benthamiana) exhibited delayed susceptibility to GFLV-GHu, intermediate recovery to ToRSV-AP, and late recovery to GFLV-F13  exhibited intermediate recovery to GFLV-F13 and delayed susceptibility to GFLV-GHu  response to GFLV-GHu was not categorically different than the response of N. rustica (both category 4), but the synthetic allopolyploid showed consistently lower incidence of infection in apical leaves (23-40%) compared to N. rustica (40-80%), which could reflect the contribution of N. tabacum (category 2) to resistance  and the closest relatives of their known progenitors for GFLV-GHu resistance. The closest extant diploid progenitors of N. clevelandii are N. obtusifolia  and N. attenuata   exhibited high or moderate virus resistance phenotypes for each virus tested  and 4 × (N. sylvestris × N. tomentosiformis) to GFLV-GHu were similar in terms of inoculated leaf infection, but N. tabacum showed early recovery whereas the neoallopolyploids showed late recovery, though the overall apical virus incidence levels were similar  and 4 × (N. debneyi × N. clevelandii) exhibited intermediate resistance phenotypes after inoculation with GFLV-GHu and GFLV-F13 compared to their parents  response to ToRSV-AP (Table N. rustica × N. tabacum) response to GFLV-GHu  showed lower resistance (higher category ratings) to GFLV-GHu than to ToRSV-AP (Table N. tabacum × N. benthamiana), 4 × (N. rustica × N. tabacum), and 4 × (N. debneyi x N. clevelandii) (Table . There was a significant (P < 0.0001) but weak (r = 0.406) correlation between virus composition and infection frequencies across plant genotypes .ToRSV-AP typically produced equal or greater categorical ratings than GFLV-GHu, and GFLV-GHu always produced equal or higher category ratings than GFLV-F13 Table . An exceAP Table . Viruleni) Table . There wχ2 in the contingency table that compared observed and expected virus incidence frequencies for each virus at each leaf position, there is a higher virus incidence in the first apical leaf than expected for ToRSV-AP; conversely, there is less virus incidence in the first apical leaf than expected for GFLV-F13 (data not shown). Expected and observed apical virus incidence values are similar for GFLV-GHu. These results suggest that ToRSV-AP displays higher virulence and GFLV-F13 displays lower virulence than GFLV-GHu in this panel of Nicotiana species.According to individual components of Nicotiana-nepovirus panel. Changes in virus incidence were characterized using DAS-ELISA on multiple leaves of large samples of plants  exhibited early recovery, this phenotype was frequently associated with a high infection frequency (>50%) in inoculated leaves  and delayed susceptibility of the 2 × (N. tabacum × N. benthamiana) responses to ToRSV raises the interesting possibility that N. quadrivalvis and N. benthamiana may possess a dominant ToRSV susceptibility factor in N. tabacum backgrounds. The observation of ringspot symptoms on the GFLV-GHu-inoculated 2 × (N. tabacum x N. benthamiana) amphihaploid suggests that the vein clearing symptomology typical of N. benthamiana infection  was re-inoculated with GFLV-GHu in the fourth leaf position 34 days after the original inoculation. Re-inoculated leaves were tested for GFLV incidence at five dpi by DAS-ELISA. Negative values were interpreted as systemic recovery and positive values were interpreted as a lack of systemic recovery.A subset of the host panel exhibiting recovery from inoculation with GFLV strains F13 or GHu [4r) and contingency tables. Correlation analyses were made for species origin , ploidy (x = 12 to 48), and virus inoculum  with respect to virus incidence at each leaf position. Origin and virus inoculum was considered as categorical variables, ploidy as continuous and virus incidence as ordinal data. A contingency analysis for section was not included due to the limited instances in which multiple species were sampled within a section. Correlation analyses were conducted where synthetic allopolyploids were either included or excluded in the data set.Statistics were computed on JMP version 10.0 . A score of one was assigned for each leaf infected in the first three apical leaf positions, and the sum of these scores among the samples at each leaf position is referred to as virus incidence. Each plant inoculated with a given virus was considered a replicate. Contingency analyses were used to compute Pearson’s correlations  strains F13 and GHu, and Tomato ringspot virus (ToRSV) strain AP. The data set supporting the results of the article is available in the Dryad Digital Repository in a Microsoft Word Document, doi:10.5061/dryad.3543v [Plant responses to ad.3543v .Click here for file


Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation process including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution  Increasing evidence suggests that HIV-1 released from activated latent cells survives in productively infected cells in patient plasma despite competition against better adapted virus variants that have evolved in response to the host immune pressure. Long-term survival requires that latent virus forms adapt to the host immune response so that they are not outcompeted. We simulated the dynamics of HIV-1 envelope sequence evolution in response to host immune pressure to investigate how virus from activated latent cells can survive despite having reduced fitness compared to the more evolved virus variants in patient plasma. The evolutionary trends of our simulated virus populations followed closely those observed in HIV-1 sequence data from 16 patients. Our simulation results suggest that recombination facilitates the survival of genomic fragments originating from virus activated from latent cells. Our model further predicts that sequence diversity increases with the number of latent genomic fragments from different origins that persist in plasma. Patients infected with HIV-1 require lifelong highly active antiretroviral therapy (HAART) to suppress infection. Treatment cessation typically leads to HIV viral rebound to pre-therapy levels; the resurgence is thought to be associated with activation of long-lived, latently HIV-infected cells. A cure for HIV therefore requires either clearance of all cells harboring latent virus, or prevention of virus release from the reservoirs after discontinuation of treatment. Increasing evidence suggests that latency plays an integral role throughout the life cycle of the virus. We recently observed that the majority of HIV-1 plasma sequences in two untreated chronically infected patients had accumulated significantly less mutations than expected, suggesting a period of latency during which no replication occurred in the history of these lineages –4. WhileHIV-1 is subject to selection pressure exerted by the immune system; strains that can avoid the immune response have an advantage within a host. The neutralizing antibody response in patient sera is much stronger against virus circulating in infection earlier than contemporaneous variants, with immunological memory persisting for years –9. VirusIn order to survive, activated latent forms must either have a replicative advantage outweighing immune selection, or quickly acquire escape mutations to evade the immune response. While mutations associated with immune escape decrease the replicative capacity of the virus between 0–24% , compensRecombination provides a mechanism to preserve genomic fragments originating from activated latent cells within contemporaneous virus backbones adapted to the immune response. Further recombination events may propagate latent genomic fragments through the replicating plasma population, enhancing the adaptability potential of the virus. In this paper, we investigate the persistence of latent envelope genomic fragments in the replicating plasma population by developing a detailed model of HIV-1 sequence evolution and the cycling of lineages in and out of the latent reservoir.There has been an increasing focus on modeling the dynamics of the latent reservoir, particularly in the context of delineating the effect of latency on viral blips during treatment, and the re-emergence of infection after treatment failure/interruption –16. A coVijay et al. developed an HIV sequence evolution model of infected patients that incorporates mutation, infection of cells by multiple virions, recombination, fitness selection, and epistatic interactions between multiple loci . Their min vivo, we compare our simulated sequences to sequences from 16 untreated or unsuccessfully treated patients followed longitudinally from seroconversion [We extend the sequence evolution model by incorporating a latent compartment in which no evolution takes place, and by explicitly simulating how the virus population interacts with and adapts to the immune response. To evaluate whether our model captures sequence evolution nversion , 21, 22 We developed an agent-based model to simulate within-host HIV-1 sequence evolution after primary HIV-1 infection (PHI), tracking how long each virus lineage has spent in the latent reservoir throughout its history . The modThe relative fitness of each virus depends on whether it has acquired mutations at invariant sites, which are considered deleterious, and how well it is recognized by the immune system. All virus sequences have multiple epitopes at pre-defined sites, which are presented to the immune system. If an epitope variant reaches a sufficient frequency in the plasma, it elicits an immune response, which remains in memory for the duration of the simulation. The breadth of the immune response is updated each generation by adding any newly recognized epitope variants to immunological memory.While we simulate infections established by a single founder strain, the model can also accommodate multiple founder strains, which are observed in 20% of heterosexual cases . The simNV identical virions, where each virion consists of a string of L nucleotides . While HIV contains two RNA molecules, we considered only a single RNA molecule for each virus to simplify computations. Because recombination between two identical parental strains does not lead to new genetic variants, restricting our simulations to one RNA molecule per virus should have a negligible effect on our simulation results. We chose as the starting sequence the consensus of the first time point sequences, sampled close to seroconversion, of Patient A from the Amsterdam cohort [env, and consists of approximately 700 nucleotides.We initialized the simulation by generating a set of m cohort . The seqNC viruses are chosen to infect NC uninfected cells such that each cell is infected with a single virus. Multiple infection of cells is described below. The probability of selecting a given virus is proportional to its relative fitness, which is a function of the strength of the immune response against it, and the number of deleterious mutations it has acquired. Fitness selection is described in detail below. Upon infection each cell has a small probability η of becoming latent and moving to the latent reservoir. The virus in the infected cells that remain productive undergo reverse transcription, where the viral RNA is copied into proviral DNA. This process includes both recombination and substitution.At each generation, env sequences were over 10 times shorter.To simplify computations, we only considered dual infections that lead to recombination. Based on estimates of Josefsson et al. , we assu−4 per site per generation [NR = 0.1 × 0.5 × 3 × 10−4 × NCL. We incorporated dual infection into the model by sampling NR additional viruses from the virus population with probability proportional to their relative fitness and adding them to randomly chosen infected cells. The dually infected cells then undergo recombination.For a template switching rate of 3 × 10neration , 28, theL − 1} randomly. The sequence of the starting strand is copied until the cross-over position, the strand is then switched, and the second strand is copied to the end of the sequence. The recombinant sequence replaces the two parent strands, so that all infected cells contain a single viral sequence. The sequence is then mutated according to a general-time-reversible substitution model [PAUP*, [P identical virions, which form the current population of virus from which viruses that infect the next generation of cells are selected.We assumed that cross-over events are distributed uniformly across the genome, selecting the starting strand and the cross-over position ∈ {2,on model . We used [PAUP*, ), which NL cells with the same founder virus used to infect the replicating population. During effective antiretroviral treatment, the reservoir’s half-life has been estimated to range from 4 to 44 months [NL, remains constant during untreated chronic infection, we set the probability of an infected cell becoming latent equal to the decay rate of the latent reservoir. Each generation, we randomly select which (if any) infected cells become latent.As the latent reservoir is established early in infection , 32, we 4 months –36. AssuNL after the addition of any newly latent cells and the removal of any activated or dead cells is less than the target size For simplicity, we assumed homogeneous activation and death rates, randomly selecting which cells in the latent compartment die or become activated each generation. Activated latent cells join the population of productively infected cells and produce progeny virus. We assumed that the latent reservoir is maintained through homeostatic proliferation , 13, 37,n generations, we consider the recombinant progeny a latent virus form, with the portion of its genome acquired from the non-latent parent recorded as having been latent for zero generations, and the portion acquired from the latent parent as having been latent n generations. At the end of the simulation, we know the position and age of every latent genomic fragment for each virus sequence. We are interested in the persistence of sequences that contain at least one latent genomic fragment consisting of at least one site originally from a latent ancestor.The model tracks how many generations each cell spends in the latent reservoir before being activated, with progeny viruses retaining the information for the duration of the lineage. Because viruses that have been latent for different amounts of time can recombine, we track latency separately at each site in the genome. If a virus that has never been latent recombines with a virus that has been latent for The immune response against antigens with recognized epitopes consists of two major arms; neutralization of a pathogen via antibodies, and killing of infected cells by cell-mediated immune responses. Because we simulated the viral envelope, we focused primarily on the antibody response, assuming that 1) variants with a recognized epitope are less fit than those able to evade the immune response, and 2) once an epitope is recognized, it is retained in memory for all time. The immune response imposes diversifying selection pressure on the virus population, resulting in sequential escape at each epitope. A virus variant not recognized by the immune system has a fitness advantage, and starts to take over the virus population, eventually eliciting an immune response, and thus selection for new escape variants.NE epitopes randomly in the envelope fragment that we are simulating. Epitopes are approximately 30 nucleotides in length, and may be non-contiguous and overlapping [We chose the location of rlapping . As synoSerum from HIV-1 infected individuals does not neutralize contemporaneous virus, but rather virus that dominated the population 3 to 6 months earlier . To modef, in the plasma, and initiated an immune response against them. The epitopes were stored in immunological memory for the duration of the simulation, and all virus variants containing them had a fitness disadvantage. For simplicity, we assumed that to be recognized the nucleotide sequence of a virus epitope must match perfectly with the sequence of a stored epitope. Note that virus may be recognized at multiple epitopes simultaneously.We began the immune response against the virus after 30 generations. Every generation thereafter, we determined which epitope variants had reached a sufficient frequency, i of variant j increases linearly until it reaches some maximum value i of variant j is given byi of variant j is introduced, d is the time it takes to reach full potency, and δij is the Dirac delta function, where δij = 1 when epitope i of variant j is recognized, and δij = 0 when it is not recognized.Because antibody responses mature over time, we assumed that the fitness cost to the virus imposed by the immune response to epitope The strength of the immune response against a particular epitope depends in part on how accessible it is to antibodies/killer T-cells. While escape mutations appear shortly after seroconversion in HIV-1/SIV infection at some epitopes , 39, it ψ is the reduction in fitness per mutation, and k is the number of mutations. At the beginning of each simulation, we randomly distribute Lpinv invariant sites across the sequence, where pinv is the proportion of invariant sites. Note that the positions of the invariant sites vary between simulations, and may occur in both non-epitope and epitope regions. Following Ganusov et al. [j as Purifying selection conserves sites in the HIV-1 genome where mutations would be deleterious to the virus. We assume that mutations at invariant sites (where no variability is observed across sequences from different time points) are inherently deleterious, and incur a multiplicative fitness cost, v et al. , we defiNC = 15000 infected cells, which is in line with the mean effective population size of HIV-1 in chronic infection [P = 5 [μ = 3.5 × 10 − 5 [We considered a pool of nfection . HIV-1 hnfection , but onlnfection –45. Eachn [P = 5 , 18. Fol× 10 − 5 . We set × 10 − 5 , 22. We NL = 100 [8 productively infected cells [5 to 1.6 × 107 latent cells with replication competent DNA [NL of 16 to 1200 cells; our chosen latent reservoir size is close to the geometric mean of this range.To maintain the ratio of productively infected to latent cells predicted by the homeostatic proliferation model of latency introduced by Kim et al. and Rong et al., we set the size of the latent reservoir to L = 100 , 13. Assed cells  and betwtent DNA , there aη of an infected cell becoming latent upon infection such that the size of the latent reservoir was maintained. Archin et al. recently estimated that the composite parameter βη is on the order of 10−14 [β is the mass-action infection rate constant in ml−1day−1. The latter has been estimated to be approximately β = 1.5 × 10−8 [η = 3.5 × 10−6 is therefore in line with these estimates. We set the death rate of latent cells to dL = 0.004 per generation, corresponding to the estimated death rate of memory cells, which make up the bulk of the latent reservoir [aL ∈  per generation so that between 0.1 and 1 latent cells were activated each generation [We chose a conservative estimate of 44 months for the half life of the latent reservoir , 36, whiof 10−14 , where β5 × 10−8 , 50. Oureservoir , 14. Folneration , 14.de novo infections ranged from 19.6% to 35.2% [Barr et al. estimated that the minimum efficacy of three early neutralizing antibodies at blocking to 35.2% . To accoto 35.2%  that somThe remaining parameters associated with the immune response are not well known. For our default parameter setting, we assumed that there are ten epitopes in the approximately 700 nucleotide region of envelope that we simulate. In subsequent sensitivity analyses, we varied the number of epitopes between 0 and 15. While it is not known how many epitopes there are on the envelope, analysis of escape mutations to SIV in rhesus monkeys suggests that there are several . We assuP = 8 infectious progeny virions [P = 10 to account for viral clearance [in vivo to two days, estimated from the decay dynamics of productively infected cells [−5 [NR, and 10NR.To investigate the robustness of our results, we also considered alternative parameter values proposed in the literature. Recent estimates of the basic reproductive number of HIV-1 during primary infection suggest that an infectious cell generates at least eight new infected cells at the start of infection when target cells are not limiting. Thus, each infected cell produces at least  virions . Followilearance . We set ed cells , and theells [−5 , 55. We d to denote the mean number of differences per position between sequences i and j, divergence and diversity are defined as follows for a collection of k sequences:Estimating sequence divergence and diversity allows us to quantify viral evolution. Divergence is a measure of how far viral genomes have evolved from the founder strain, whereas diversity is a measure of the genomic variation in the viral population at any given time. Every 30 generations, we calculated the divergence and diversity of the HIV-1 sequences in the entire populations of productively infected and latent cells, recording the mean, median, and 5% and 95% quantiles. Furthermore, we randomly sampled 100 productively infected cells and 100 cells from the latent reservoir every 300 generations, storing the HIV-1 sequences for later phylogenetic analysis. Using nr at generation zero. The relative fitness of each latent virus was set to 0.5, while the relative fitness of each non-latent virus was drawn from a uniform distribution between 0.5 and 1. As in our full model, each generation of the simulation consisted of every infected cell producing five progeny virions, and downsampling the virus population to infect the next generation of nr uninfected cells. The expected number of dual infections involving at least one latent virus was then estimated for each simulation run.Stochastic effects dominate at small population sizes—the smaller the population, the larger the probability that stochastic fluctuations lead to extinction. We therefore investigated how the size of the simulated population affects the ability of latent genomic fragments to survive in patient plasma, assuming that recombination is necessary for survival. To this end we determined the expected number of dual infections, a precursor for recombination, involving at least one latent form when the sizes of the replicating and latent populations were increased ten-fold. We ran 100 simulations, tracking the progeny of the activated latent cells for ten generations, introduced into a replicating population of size Simulation results were compared to HIV-1 DNA sequence data from 16 untreated or unsuccessfully treated patients , 21, 22.p = 0.67, cor = 0.15; Pearson’s product-moment correlation). Increasing the activation rate slightly decreased sequence divergence at the end of the simulations . Unsurprisingly, both mean sequence divergence and diversity increased in the latent reservoir at a much slower initial rate than in productively infected cells  generated trees more typically observed in HIV-1 infected patients. Importantly, these intermediate landscapes also showed typical patient diversity trends . InteresThe shape of the landscape is defined by the maximum fitness costs exerted by immune responses against different viral epitopes. The concave landscapes have a higher number of different immune responses exerting similar high fitness costs on the virus than convex or nearly linear landscapes. Escaping the immune response exerting the maximum fitness cost only marginally increases fitness if there are simultaneous immune responses against other epitopes that also impose high fitness costs. Therefore, a more concave fitness landscape exerts a stronger selection pressure on the virus, reducing both the mean and variance of the relative fitness in the virus population. The survival of less adapted latent forms in plasma therefore increases, while the reduction in fitness differences between virus variants in productively infected cells increases diversity.p < 0.05, Wilcoxon rank-sum test), while in simulations where there were more than 5 latent origins, sequence diversity became significantly higher much earlier, after approximately 5 years post-PHI . At 10 years post-PHI, mean sequence diversity was 0.038 substitutions/site when no latent genomic fragments survived, increasing by 16%, when there were between 1 and 5 latent origins, and by 95% when there were more than 15 latent origins. The propagation of genomic fragments that have accumulated fewer mutations than contemporaneous variants should reduce average sequence divergence in the plasma. As expected, when the number of surviving genomic fragments of different latent origins increased, mean sequence divergence decreased . Furthermore, the rate of increase of virus with latent genomic fragments over time in the replicating population was approximately 9 times faster when recombination was involved The proportion of virus with latent genomic fragments was higher when we allowed for recombination than when we ignored it. This distinction is clear from even the first sample time, after 30 generations  were qualitatively and quantitatively similar to those seen previously under the default parameters. The mean sequence divergence and diversity of 100 simulations with the alternative model parameters are shown in , while sequence divergence increased .The sensitivity of the model to the immune system parameters, i.e., the antigen frequency necessary to elicit a new immune response, and the number of epitopes accessible to the immune system, are described in  Tables, When the immune response to a new escape mutant is delayed, the frequency of virus variants carrying the advantageous escape mutation increases. The increase in the number of virus variants that have evolved away from the founder sequence increases divergence but the simultaneous convergence towards the new escape variant reduces diversity. Because the mean relative fitness of virus in productively infected cells increases, the survival probability of virus from activated latent cells decreases. The survival of virus with latent genomic fragments was low in all simulations without recombination.On the other hand, when the number of epitopes was increased, sequence diversity at 10 years post-PHI initially decreased from one epitope to 4 epitopes and then increased from 4 to 15 epitopes . SequencWhen the number of epitopes was zero, no immune pressure was exerted on the virus. This resulted in high diversity (0.081 subst/site) because all virus variants without mutations at invariant sites had equal probability of surviving, and low divergence (0.047 subst/site), because rapid accumulation of escape mutations was not selected for. Virus with latent genomic fragments survived in all simulations, because earlier virus forms were not at a fitness disadvantage compared to more recent variants.When the number of epitopes was increased from 1 to 4, it became increasingly more difficult but not impossible for virus to escape the immune response. When two epitopes had high fitness costs associated with them, it took longer for any virus variant in the population to simultaneously escape both responses, and the significant fitness gain and proliferation due to escape resulted in decreased diversity . Such get = t0, corresponding to the expected number of cells activated each generation from the latent reservoir of 100 cells at the highest activation rate α = 0.01, the expected number of dual infections involving at least one latent virus was 0.1 over 10 generations. However, when 10 latent forms were introduced to a population of 150,000 cells, i.e., at the same proportion but in a ten-fold population, the total expected number of dual infections was 0.94. Thus, when the simulated population size was increased ten-fold, the probability that at least one latent form ended up in a dually infected cell before disappearing from the replicating population increased nearly ten-fold. The long-term behavior in simulations where virus with latent genomic fragments proliferates is expected to be robust to stochastic effects due to the increased number of such viruses, however, the variance observed in the survival of latent virus forms between simulations is overestimated in a smaller population due to early stochastic extinction. The proportion of simulations with persistence of virus with latent genomic fragments is therefore likely an underestimate.Surviving in the replicating population long enough to recombine with a replicating virus forms the bottleneck that largely determines the long-term fate of a latent lineage. When one latent form was introduced into a population of 15,000 cells at generation We developed a within-host HIV-1 evolution model that includes point mutation, recombination, immune (positive) selection, negative selection, and latency. This model quantitatively captures previously observed viral sequence divergence and diversity trends and mechanistically explains these patterns, allowing us to model realistic within-host natural evolution of HIV-1. We used this model to investigate when and how latent forms of HIV-1 can survive in productively infected cells despite not being well adapted to the immune response, therefore having reduced relative fitness. Our simulation results suggest that recombination is a key mechanism facilitating the survival of virus forms with latent genomic fragments. We have previously shown that the majority of phylogenetic lineages in HIV-1 populations of untreated patients display a statistically defined signal of latency [By comparing simulations where the surviving genomic fragments originated from different numbers of latent ancestors, we found that latency reduced mean sequence divergence, but increased mean sequence diversity for reasonable fitness landscapes. This effect may explain how HIV-1 can keep a high adaptation potential without mutating too far away from the infecting strain. High adaptation potential is useful for escaping immune and antiviral drug pressures, while less divergent sequences closer to the infecting form are arguably more fit to infect new hosts .The dynamics of our simulated immune response depend on the number of epitopes and the antigen frequency triggering a new immune response, neither of which are well known. To test the sensitivity of our model, we varied these parameters to the extremes where measures of sequence divergence and diversity became unrealistic. Importantly, the trend of much higher survival of virus with latent genomic fragments in simulations with recombination than in simulations without recombination was robust for the full range of immune system parameters. This suggests that our main result is not sensitive to the exact details of how the immune response was implemented in our model.in vivo HIV-1 viral populations are typically very large, computational considerations limited us to follow instead the relatively small population of 15,000 productively infected cells, which is in line with recent estimates of the effective population size in real HIV-1 populations [While ulations . The varPrevious studies have suggested that escape mutations have a fitness cost , and thuFurthermore, if activated virus from latent cells has similar fitness as contemporaneous variants, recombination may not be as important for survival. However, recombination does not merely facilitate survival, but rather allows latent genomic fragments to propagate through the plasma virus population. In the most extreme case where no selection pressure was exerted by the immune response Click here for additional data file.S1 Fig(A) Typical phylogeny from our simulations. The proportion of surviving lineages from earlier samples is representative of the tree shape (star- to ladder-like). The legend shows samples through time and the surviving proportion of lineages in parentheses. (B) Green dots represent the proportion of surviving lineages between samples at adjacent time points in clinical data, and black dots represent our simulated data. The stronger green color indicates overlapping data points. The phylogenetic trees were generated from 20 sequences sampled every year per simulation.(TIF)Click here for additional data file.S2 FigWe ran 1000 simulations with the concave fitness landscape shown in the insert, and categorized the results based on the number of latent genomic fragments from different origins at 1% or greater frequency at 10 years post-PHI. Increasing the number of latent origins does not increase sequence diversity, which grows linearly regardless of the latent survival.(TIF)Click here for additional data file.S3 FigEnvelope indicates the span of 95% of observations, with the mean given by the white line, and the median given by the green line.(TIF)Click here for additional data file.S4 FigA) The distribution of the number of different latent origins in productively infected cells as a function of activation rate. B) The distribution of the proportion of virus with latent genomic fragments in productively infected cells as a function of activation rate. 95% envelopes with white lines as the mean and green lines as the median.(TIF)Click here for additional data file.S5 FigAfter approximately 2 years post-PHI, diversity starts to grow linearly in the latent reservoir (blue solid line) while it starts to saturate in plasma (green solid line). Divergence in the latent reservoir (blue dashed line) grows at a slightly slower rate than in plasma (green dashed line).(TIF)Click here for additional data file.S6 FigA) Simulations without recombination. B) Simulations with recombination. Grey lines show the proportion of latent lineages in the productively infected cell population of individual simulations, where the bold tan line is the mean proportion of latent lineages and the thin tan lines outline the 95% confidence envelope. Comparing panels A and B clearly shows that recombination facilitates survival of latent forms.(TIF)Click here for additional data file.S7 FigWe compiled the simulation results of varying the number of epitopes between 1 and 15 , and re-(TIF)Click here for additional data file.S1 TableIncreasing the activation rate in simulations with recombination increases the proportion of simulations with persistence (≥ 10%) of virus with latent genomic fragments, and the mean proportion of virus sequences with latent genomic fragments. 100 simulations were performed for each activation rate. In simulations without recombination, latent persistence is rare.(DOC)Click here for additional data file.S2 TableIncreasing the recombination rate increases the proportion of simulations with persistence (≥ 10%) of virus with latent genomic fragments, and the mean proportion of virus sequences with latent genomic fragments. As the recombination rate increases, the mean number of latent fragments per sequence increases, but the mean size of the fragments decreases. 50 simulations were performed for each recombination rate.(DOC)Click here for additional data file.S3 TableIncreasing the antigen frequency required for eliciting a new immune response in simulations with recombination decreases the survival of virus with latent genomic fragments and sequence diversity while sequence divergence increases. In simulations without recombination, latent persistency is rare. 50 simulations were performed for each value of antigen frequency.(DOC)Click here for additional data file.S4 TableWhen the number of epitopes is increased in simulations with recombination, sequence diversity initially decreases, reaching lowest values at 3 and 4 epitopes, and increases thereafter. Sequence divergence follows the reverse trend. Virus with latent genomic fragments rarely survived in simulations without recombination. 50 simulations were performed for each number of epitopes.(DOC)Click here for additional data file.


Three H9N2 avian influenza viruses were isolated from the Dongting Lake wetland, among which one was from fresh egret feces, the other two were from chicken cloacal swabs in poultry markets. Phylogenetic analyses suggested that eight genes of the egret-derived H9N2 virus might come from Korean-like or American-like lineages. The two poultry-derived H9N2 viruses were reassortants between the CK/BJ/94-like and G1-like viruses. Except the PB1 genes (90.6%), the nucleotide sequence of other internal genes of the two viruses exhibited high homology (>95%). In addition, they also exhibited high homology (96–98.3%) with some genes of the H7N9 virus that caused an epidemic in China in 2013. Nucleotide sequence of the poultry-derived and egret-derived H9N2 viruses shared low homology. Infection studies showed that the egret-derived H9N2 virus was non-pathogenic to both mice and chickens, and the virus was unable to infect chickens even through 8 passages continuously in the lung. On the other hand, the chickens infected by poultry-derived viruses showed obvious clinical symptoms and even died; the infected mice showed no noticeable clinical symptoms and weight loss, but viruses could be detected in their lungs. In conclusion, for the egret-derived H9N2 virus, it would take a long adaptation process to achieve cross-species transmission in poultry and mammals. H9N2 viruses isolated at different times from the same host species in the same geographical region presented different evolutionary status, and virus isolated from different hosts in the same geographical region exhibited genetic diversity. Therefore, it is important to continue the H9N2 virus surveillance for understanding their evolutionary trends so as to provide guidance for disease control and prevention. The H9N2 avian influenza virus (AIV) was first isolated from North American waterfowls in 1966 and it has disseminated worldwide since then Epidemiology and phylogenetic studies found that the viruses that caused H9N2 AIV outbreak in Hong Kong live poultry market could be divided into three distinct lineages: A/Chicken/Beijing/1/94 (Ck/BJ/94-like), Quail/Hong Kong/G1/97 (G1-like) and Duck/Hong Kong/Y439/97 (Y439-like or Korean-like) A total of three H9N2 subtype AIV strains were isolated during 2010–2012. Of which one was isolated from fresh egret feces collected in Dongting Lake Egret Nature Reserve, the other two were isolated from chicken cloacal swabs collected in poultry markets. We carried out whole-genome sequencing for the three viruses, constructed phylogenetic trees and investigated the sources of the virus genomes. Pathogenicity tests of these H9N2 viruses were conducted in mice and SPF white Leghorn chickens. The study revealed the evolutionary status and likelihood of cross-species transmission of H9N2 AIVs in wide birds and poultry in Dongting Lake wetland, and contributed data for molecular epidemiology of AIV.All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of Laboratory Animal, Wuhan Institute of Virology, Chinese Academy of Sciences . This study was carried out in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals. All procedures were performed under anesthesia. Animals were closely monitored and observed for development of disease once daily, and all efforts were made to minimize suffering.Fresh migratory bird feces were collected at Dongting Lake Egret Nature Reserve  and no specific permissions were required for these locations. The cloacal swabs collected in poultry markets  and no specific permissions were required for these activities. All field studies did not involve endangered or protected species.Sterile cotton swabs were used to collect fresh migratory bird feces and poultry cloacal samples. The swabs were placed into viral transport media. All the samples were placed in a hand-held portable 4°C refrigerator, transported to the laboratory within 24 hours, and frozen in −80°C immediately for future use.The swabs frozen in the −80°C freezer were transferred to a 4°C refrigerator for thawing. Then the sample was spun at 6000 rpm for 10 min at 4°C, and the supernatant was inoculated into 10-day-old SPF embryonated chicken eggs. The embryonated chicken eggs were cultured at 37°C for 48–72 hours. The embryos that died within the first 24 hours were discarded, for the rest live or dead embryos, allantoic fluid was collected and spun at 3000 rpm for 10 min at 4°C and then tested for hemagglutination. The allantoic fluid positive for hemagglutination was divided into aliquots and frozen at −80°C for further tests.RNA extraction and reverse transcription of virus RNA were performed according to the instructions of the RNA extraction kit (Takara) and mouse reverse transcription kit , respectively. Influenza virus gene fragments were amplified by PCR using a Phusion High-Fidelity PCR Kit (New England Biolabs). The primers used to amplify the eight genes were universal primers designed by Hoffman et al. Phylogenetic analysis was based on nucleotides 94–1,556  of the HA gene, 38–1,371  of NA, 56–2,289  of PB2, 40–2,233  of PB1, 25–2,166  of PA, 39–1,388  of NP, 95–931 (837 bp) of M, and 38–806 (769 bp) of NS. Multiple alignments were constructed by using BioEdit (version 7.0.5.2). Phylogenetic trees were generated by using Maximum Likelihood analysis with 1000 bootstrap replicates in the MEGA program (version 5.2).6EID50 virus in 0.1 ml. Oropharyngeal and cloacal swabs were collected on day 1, 3, 5, 7 p.i.. Viral titration was conducted in 10-day-old SPF embryonated chicken eggs. The chickens were observed for 21 days post-inoculation (p.i) and their symptoms and survival were recorded. The symptoms, virus titration of lungs and death were as results of virus infection.Two routes of virus infection, intravenous (i.v) and intranasal (i.n) injection were used. For each route, 6-week-old SPF white Leghorn chickens were divided into two groups, eight each group. In i.v groups, virus was diluted 10 fold and then injected intravenously to the chickens at a dose of 0.2 ml each. In i.n groups, each chicken was anesthetized via intramuscular injection of ketamine (20 mg/kg) and xylazine (1 mg/kg) and given a dose of 106EID50 virus after being anaesthetized. Three days after infection, the chickens were euthanized with ketamine and xylazine, and the lungs were taken out and homogenized with a total of 2 ml of PBS containing 0.1% BSA. The tissue homogenate was used for virus titration after removing cellular debris by centrifugation. Virus titration was performed as above. The remaining five chickens were observed for symptoms and survival for 21 days and post-recovery sera were collected for hemagglutination inhibition (HI) test. The same procedure was performed from Passage 0 (P0) to 8 (P8).For lung passage experiment in SPF white Leghorn chickens, eight chickens were infected intranasally with each virus in a volume of 0.1 ml of 106 EID50 virus in 50 µl. The mice (n = 12) were observed for 21 days p.i. and their symptoms, mortality and weight loss were recorded. On day 3, 5 and 7 p.i., three mice per group were euthanized, and the lungs, brains, spleens and kidneys were taken out and homogenized with a total of 2 ml of PBS containing 0.1% BSA.Specific-pathogen-free female BALB/c mice, aged 6 to 8 weeks old, were purchased from the Center for Disease Control and Prevention in Hubei Province, China. Mice were bred in the Animal Resource Center at the Wuhan Institute of Virology, Chinese Academy of Sciences. All mice were maintained in specific-pathogen-free conditions. The BALB/c mice were divided into three groups, including two experimental groups and one control group, twenty-one each group. For the experimental groups, each mouse was anaesthetized with pentobarbital sodium and infected intranasally with 10For histopathological analysis, lungs of SPF chicken were removed immediately following euthanasia, and fixed with 10% formalin at 4°C. Subsequently, lungs were stained with Hematoxylin and Eosin (H&E), and examined for pathological changes corresponding to infection. Images were obtained on an Nikon80i light microscope at 400-fold original magnification.Sera were harvested from the four groups of inoculated chickens on day 21 p.i. for confirmation of seroconversion and antigenic analysis by HI assays with 1.0% chicken erythrocytes according to relevant recommendation of OIE.The nucleotide sequences obtained in this study are available from GenBank under accession numbers JX437684 to JX437691, KF714772- KF714787.The results of the test groups were evaluated by Student's t-test; if p-value is less than 0.05, the difference was considered significant. The survival rates of the mice in the test and control groups were compared by using Fisher's exact test.From October 2010 to October 2012, three H9N2 subtype AIVs were isolated from Dongting Lake wetland. One virus was isolated from fresh egret fececs collected in Dongting Lake Egret Nature Reserve and named A/Egret/Hunan/1/2012 (H9N2). The other two viruses were isolated from cloacal swabs collected in poultry markets and named A/Chicken/Hunan/12/2011(H9N2) and A/Chicken/Hunan/1/2012 (H9N2), respectively.The whole genomes of the three viruses isolated in this study were sequenced and then nucleic acid and protein sequence homology were compared . Genes oThe HA and NA genes of the A/Egret/Hunan/1/2012 virus had about 83% homology with those of A/Chicken/Hunan/12/2011 and A/Chicken/Hunan/1/2012 viruses and homology of the NS gene was even lower (70%). The genes of two poultry-derived viruses shared high homology except the PB1 gene. Nucleotide homology of the PB1 gene between the two poultry viruses was only 90.6%, lower than the PB1 gene homology between A/Chicken/Hunan/1/2012 and A/Egret/Hunan/1/2012 (96.8%). Some genes of the two poultry viruses also had high homology with those of the H7N9 virus isolated from pigeons in Shanghai in 2013  .Phylogenetic analysis indicated that the HA and NA genes of the two poultry-derived viruses belonged to the CK/Bei/94-like lineage, which had two subgroups represented by A/Duck/HongKong/Y280/97 and A/Chicken/Shanghai/F/98, respectively. The HA genes of the two poultry-derived viruses belonged to the subgroup represented by A/Duck/HongKong/Y280/97 . Except Amino acid sequence analysis revealed the connecting peptide of HA was ASDR/G in A/Egret/Hunan/1/2012 virus and RSSR/G in the two chicken isolates . The RSSFor the polymerase complex, no amino acid substitution was found in sites related to host specificity and viral replication , indicating that these three isolates were low pathogenic to mammal and avian hosts p<0.05)  or intranasal (i.n) injection. The chickens infected with A/Chicken/Hunan/12/2011 virus via either route presented similar clinical symptoms. They started showing hoarse voices and listlessness from day 3 p.i.; one chicken in the intranasal group died on day 5 p.i., then they started to recover on day 9 p.i.. Virus shedding was observed for most infected chickens, and virus could be detected in both pharynges and cloaca. Viral load in pharynges and cloaca peaked on day 3 p.i. in both route groups. On day 7 p.i., virus test was negative in the cloaca for all the chickens, but pharyngeal samples from most chickens were still positive. Chickens inoculated with A/Egret/Hunan/1/2012 virus via either route did not present significant clinical symptoms and no chicken died. Virus was detected only in one chicken of the intranasal group in both pharyngeal and cloacal samples on day 1 p.i., all the other chickens were tested negative for virus at all the time points post-infection. The chicken number of virus shedding in A/Chicken/Hunan/12/2011 virus-infected was far more than that of A/Egret/Hunan/1/2012 virus- infected (p<0.05) .Chicken lung tissue pathology revealed obvious pulmonary inflammatory responses on day 3 and 7 p.i. in chickens infected with the poultry-derived H9N2 virus. Partial necrosis appeared in lung tissues on day 3 and 7 p.i., more severe on day 3. The results indicated that poultry-derived H9N2 virus could not only replicate effectively in chickens, but also cause cellular inflammatory response and lung tissue injury. In contrast, the egret-derived H9N2 virus was less pathogenic to chickens than chicken-derived virus . The hisIn addition, A/Egret/Hunan/1/2012 virus was 8 passaged continuously in the lungs of SPF white Leghorn chickens. No chicken showed overt clinical symptoms (such as hoarse voice and listlessness) and they kept normal food and water intake. The P0 to P8 chicken lung homogenate were inoculated into SPF eggs and cultured for 48–72 hours in a 37°C incubator and the allantoic fluid of chicken embryos were performed hemagglutination test. The virus was detected only in the P0 sample, no virus were detected in lungs of egret-derived H9N2 virus-infected at 3d p.i. and no antibody was detected at 21d p.i. for the rest 8 passages.All chickens infected with A/Chicken/Hunan/12/2011 virus had seroconversion on day 21 p.i with very high HI titer. In contrast, none of the chickens inoculated with A/Egret/Hunan/1/2012 virus, either via i.v or i.n, showed seroconversion (positive if HI>16).A/Egret/Hunan/1/2012 and A/Chicken/Hunan/12/2011 viruses were also used for mice infection experiments. None of the mice showed overt symptoms and all mice survived. The egret-derived isolate group showed slight weight loss, whereas the poultry-derived isolate group showed symptoms such as slight piloerection and trembling and more weight loss as compared to the egret-derived isolate group. Their weight started to rebound from day 7 p.i. .Virus detection was performed on lung, brain, spleen and kidney tissues taken on day 3, 5 and 7 p.i.. The results indicated only the poultry-derived virus could replicate in the lungs of mice, but the viral load was low and the result was positive only on day 3 and 5 p.i.. No virus was detected in the other organs. The egret-derived virus did not replicate in the lungs of mice and virus detection was negative for the other organs .Antisera were collected on day 21 post-infection. The cross-reactivity of the three viruses was investigated by HI assay. The antisera to A/Chicken/Hunan/12/2011 virus could cross-react well with A/Chicken/Hunan/1/2012 and A/Chicken/Hunan/12/2011 viruses . The HI Last several years, human infections of H9N2 subtype avian influenza viruses have occurred, which have increasingly gained more attention In recent years, CK/BJ/94-like AIVs have been prevalent in poultry in central and southern China Reports on H9N2 AIV isolated from wild birds have been rare recently. In the present study, one H9N2 virus was obtained from egrets in Dongting Lake, which, although clearly differed from the two poultry-derived H9N2 viruses, but shared 96.8% homology in PB1 nucleotide sequence with A/Chicken/Hunan/1/2012 virus, suggesting it exchanged gene segments with poultry-derived viruses.Virus challenge experiments indicated that virus shedding occurred in most chickens infected with the poultry-derived viruses whereas the egret-derived virus could not replicate effectively in chickens. These findings indicated that the poultry-derived H9N2 viruses could not only adapt well in chickens, but also could shed virus into the environment, which increased the possibility of AIV transmission and reassortment among susceptible animals. In contrast, the egret-derived H9N2 virus was not yet capable of infecting chicken. The M gene plays a decisive role in cross-species transmission and pathogenicity of AIV. The M gene in the two poultry-derived H9N2 viruses belonged to the G1-like lineage, the same lineage as the M gene isolated from the Hongkong human H9N2 infection cases. Studies have shown that M gene is related to host range of influenza viruses and their adaptability to new hosts. Whether the M gene of the H9N2 poultry isolates in this study is directly related to cross-species transmission needs to be confirmed by further studies All chickens infected with the chicken-derived isolates showed seroconversion and HI test results showed little antigenic variation between the two H9N2 viruses. No chickens infected with the egret-derived isolate showed seroconversion. Cross-reactivity was observed between antisera to the chicken-derived isolate and the egret-derived virus, although the titers were low, indicating the HA of A/Chicken/Hunan/12/2011 and A/Egret/Hunan/1/2012 viruses shared antigenic sites. Results of HI test and the HA gene phylogenetic analysis were consistent in that the two viral genomes had big differences.Results from lung passage of the egret H9N2 virus in SPF chicken indicated that this virus could not cross-species transmit effectively. Chickens could clear the virus by their own immune system. The chicken-derived H9N2 viruses could replicate in the lungs of mice without adaptation (though the titers were low) whereas the egret-derived virus could not replicate in the lungs of mice. This finding indicated that it would take an ongoing adaptation process for un-adapted poultry H9N2 viruses to replicate stably and become pathogenic to mammalian hosts, and it would take even longer evolution for a wild bird derived H9N2 virus to adapt to mammals.This study performed preliminary analysis of the biological characteristics of the H9N2 viruses isolated from different sources and found big differences between them, and it seemed that some more mutations and further evolution would be required for the wild-bird derived virus to adapt to poultry. These findings laid a foundation for further studies on virulence enhancement and molecular mechanism of pathogenesis of influenza viruses. The ongoing molecular epidemiology surveillance for H9 viruses in poultry-markets, lakes and wetlands is necessary for understanding their roles in the evolution of highly pathogenic influenza viruses and to prevent their potential pandemic in poultry and humans.Figure S1Histopathological changes of lungs are shown by Hematoxylin and Eosin (H&E) staining after virus infection. A, infected by E1 virus 3d p.i., there was pulmonary congestion, proliferation of bronchial epithelial cells in tertiary bronchus, cellular inflammatory infiltration in the lamina propria, and thickening of pulmonary capillary with red blood cell. B, infected by E1 virus 7d p.i., there was pulmonary congestion, thickening of small blood vessels and pulmonary capillary filled with red blood cell. C, infected by C12 virus 3d p.i., there was lung interlobular necrosis and inflammatory cells aggregation. D, infected by C12 virus 7d p.i., there was pulmonary slight gore, a small amount of pulmonary capillary serous fluid exudation.(TIF)Click here for additional data file.


Genetic analyses of highly pathogenic avian influenza A(H5N8) virus from the Netherlands, and comparison with strains from Europe, South Korea, and Japan, showed a close relation. Data suggest the strains were probably carried to the Netherlands by migratory wild birds from Asia, possibly through overlapping flyways and common breeding sites in Siberia. Highly pathogenic avian influenza (HPAI) A(H5N8) virus probably originated in China, where it was isolated in 2009–2010  were found near the affected farms, leading to the hypothesis that infection was carried by the wild ducks. Genetic analysis of the virus indicated that isolates from infected domesticated ducks and dead Baikal teals in the surrounding area in South Korea strongly resembled earlier isolates from China (A. platyrhynchos) and Baikal teals that HPAI (H5N1) and (H5N8) virus isolates did not cause serious illness or death in these species. Recent phylogenetic studies of HPAI (H5H8) viruses isolated from infected poultry and wild birds in 2014 in South Korea indicate that migrating birds played a key role in the introduction and spread of the virus in the initial phase of the 2014 outbreak (Cygnus columbianus bewickii) tested positive for the HPAI (H5N8) virus. We conducted full-length sequencing to elucidate the origin of the HPAI (H5N8) virus detected in the Netherlands.Beginning in January 2014, H5N8 virus spread rapidly in South Korea, initially mainly among farmed ducks. During the first outbreaks among farmed ducks, numerous dead Baikal teals  on November 14. RNA was extracted from cloacal and oropharyngeal samples from clinically affected hens with positive results from the screening influenza real-time reverse transcription PCR  in Sakha, northeastern Russia, is a precursor phylogenetically located at the node of European and Chiba viruses  and viruses from poultry and wild birds from Europe and 2 strains from Japan (A/duck/Chiba/26-372-48/2014 and A/duck/Chiba/26-372-61/2014) detected thereafter are closely related. Analysis also showed that the viruses are descendants of 3 strains isolated in early 2014: A/broiler duck/Buan2/2014 and A/Baikal teal/Korea/Donglim3/2014 from South Korea and A/chicken/Kumamoto/1-7/2014 from Japan. HPAI (H5N8) virus isolated from a wigeon  and EpiFlu (http://www.gisaid.org) databases, the H5N8 virus from the Netherlands shares the highest similarity with strain A/Baikal teal/Korea/Donglim3/2014 from South Korea.We determined the number of per site base substitutions between the sequences by using the maximum composite likelihood in MEGA6  virus from the Netherlands indicates that the virus probably was spread by migratory wild birds from Asia, possibly through overlapping flyways and common breeding sites in Siberia. In addition to the outbreak in the Netherlands, several other outbreaks of HPAI (H5N8) virus infections were reported in Europe at the end of 2014 after exponentially increasing deaths occurred in chicken and turkey flocks. Genetic sequences submitted to the EpiFlu database indicated that the viruses from Europe showed a strong similarity to viruses isolated earlier in 2014 in South Korea, China, and Japan. An H5N8 virus isolated from a wigeon in Russia in September 2014 is located in the phylogenetic tree near the node of all sequences for H5N8 viruses from Europe. In regard to time, this location fits the hypothesized route of H5N8 virus introduction into Europe. Furthermore, for several reasons, it is highly likely that the introduction of HPAI (H5N8) virus into the indoor-layer farm in the Netherlands occurred via indirect contact. First, despite intensive monitoring, H5N8 viruses have never been detected in commercial poultry or wild birds in the Netherlands. Second, when the virus was detected, the Netherlands had no direct trade contact with other European countries or Asia that might explain a route of introduction. Third, because of the severity of disease in galliforms, outbreaks of H5N8 in the Netherlands before November 2014 would have been noticed.Sequences of the H5N8 virus isolates from the Netherlands were compared with sequences obtained from the Global Initiative on Sharing Avian Influenza Data’s EpiFlu Database.


To the Editor: The earliest clinical cases of Zika virus infection were reported from continental South America in 2015  tests specific for dengue . Of these 50 patients, 30 (60%) were female. Most of these patients reported illness onset during December 9–27, 2015  were female. A total of 22 (8%) samples were positive for dengue; 2 were positive for chikungunya. Of the remaining 252 patients, 50 (20%) had 27, 2015  Figure 1The most commonly reported signs and symptoms were fever (86%), exanthema (72%), and headache (62%). The clinical characteristics of these infections showed no statistically significant difference with those associated with dengue and chikungunya virus infections and with cases found to be negative for all 3 viruses, suggesting that the negative cases could represent Zika virus infections  Table. OBy using Vero E6 cells (American Type Culture Collection), we isolated Zika virus from 9 samples . Phylogenetic analysis of 5 Zika virus sequences  placed these isolated (GenBank accession nos. KU724096–100) within the Asian lineage, the lineage involved in the spread of Zika virus in the Americas  Figure 2By using molecular methods, we confirmed diagnoses in 27% of patients during this outbreak. The distribution of positive results suggests that Zika virus was the predominant etiologic virus in this cohort, but we cannot firmly conclude this because most specimens tested negative for Zika, dengue, and chikungunya viruses.Although results from patient sampling and laboratory testing are not comparable, an assessment in Puerto Rico was able to detect Zika virus RNA by rRT-PCR or IgM by ELISA in 19% of 155 patients with suspected Zika virus infection (Several reasons might exist for the high proportion of specimens testing negative for Zika virus. Viremia is often low and short-lived in persons infected with Zika virus (The Panama Ministry of Health is following up with known pregnant women of the Guna Yala region who report Zika virus infection symptoms and is testing urine samples by using Zika virus–specific rRT-PCR within 14 days of symptom onset. Pregnant women confirmed to have Zika virus infection will receive ultrasound monitoring; however, the test has relatively low positive predictive value for detecting microcephaly (Distribution of symptoms by patients with Zika, dengue, and chikungunya virus infections in the Guna Yala region of Panama, November 27, 2015–January 22, 2016; epidemiologic curve for the outbreak of Zika virus infection in this region; and maximum-likelihood tree of the Zika virus isolated during the outbreak.


While experts have suspected a causal link between outbreaks of Zika virus and microcephaly, it was not demonstrated. The currently available data are here organized into the Austin Bradford Hill's aspects of evidence for the consideration of causality. WHO declared a Public Health Emergency of International Concern in January 2016 (http://www.who.int/mediacentre/news/statements/2016/1st-emergency-committee-zika/en/). Based on the spatial and temporal correlation of these clusters with outbreaks of Zika virus infections a few months before, a causal link is suspected. Whether the observed link between infection and microcephaly is indeed causal needs careful assessment—not the least because we might fall into the trap of ecological fallacy, inferring a causal association on the individual level from an association on the aggregate or population level.After the emergence of unusual clusters of microcephaly among babies born in the fall of 2015 in Brazil—and, retrospectively, in French Polynesia—Here, we organize the currently available data into Austin Bradford Hill's aspects of evidence for the consideration of causality Hill, . AlthougStudies to characterize the strength of this association in terms of odds ratios from case–control studies or (preferable) relative risks from cohort studies are already underway. These should be able to answer how much more likely a mother infected with Zika virus any time during pregnancy, or in a specific time window, will be giving birth to a child with microcephaly compared to mothers who were not infected. On the ecological level, a strong increase in microcephaly cases is not by itself evidence for a strong causal association because there might be confounding or biases. Nevertheless, if there were a strong causal association, we would expect to see a large increase in cases of microcephaly in a population with many Zika virus infections during pregnancy.et al, If the association is causal, maternal Zika virus infection would consistently predict a risk of microcephaly in the fetus or newborn. But such data are not available yet. Isolated cases of congenital microcephaly and Zika virus infection outside the outbreak areas, such as the travel‐associated cases on Hawaii and in Slovenia, provide some limited evidence toward a consistent association regardless of area of permanent residence factors specific to being pregnant in Brazil and other affected areas.et al, There is some evidence that a number of other flaviviruses can cause congenital brain malformations in humans and animals. Among the animal pathogenic flaviviruses, Wesselsbron or Japanese encephalitis viruses are known to cause teratogenic effects  in the unborn child. Among the manifestations of CRS is microcephaly with cerebral calcifications (Katz et al, et al, Causal links specific to microcephaly are established for viruses from other families, such as Although the initial suspicion of a causal relationship was based on observed clusters of microcephaly trailing Zika virus outbreaks on the population level, we can already see other evidence supporting a causal relationship in regard to some of Austin Bradford Hill's aspects. This is particularly true for temporality, biological plausibility, and analogy. But clearly many gaps remain to be filled until we can decide “that the most likely explanation is causation” Hill, . Especiaet al, This Opinion only addresses the putative link between Zika virus infection during pregnancy and congenital microcephaly. In addition, there are hints of associated ocular problems in newborns (Ventura Because we cannot yet characterize the association between Zika virus and microcephaly as causal, that in itself is no reason to shift the investigative focus to other hypotheses. Any other putative factors put forward as demonstrating similarly lagged correlations with recognized clusters of microcephaly, such as exposures to certain insecticides or medications, must be put through the same rigorous process of judging the evidence. They can be considered in case–control and cohort studies as additional exposures, to either confirm or refute any role in the causation of microcephaly in the groups of women who are studied.We hope that applying the Bradford Hill aspects of evidence for epidemiological causation provides a useful checklist for current and future evidence for or against a causal association between Zika virus infection in pregnancy and congenital microcephaly. Giving the ongoing epidemiological and molecular research, especially in the Americas, some of the questions that we raised in this Opinion may already be answered by the time this article is published.


Zika virus is an emerging human pathogen of great concern due to putative links to microcephaly and Guillain-Barre syndrome. Here, we report the complete genomes, including the 5′ and 3′ untranslated regions, of five Zika virus isolates, one from the Asian lineage and four from the African lineage. Zika virus (ZIKV) is an emerging human pathogen of great concern due to putative links to severe birth defects  and a rAedes. ZIKV belongs to the Spondweni serocomplex within the genus Flavivirus and the family Flaviviridae. Viruses in the genus Flavivirus have single-stranded positive-sense RNA genomes of ~11 kb in size  and belong to the African lineage . One virde novo contigs and publically available ZIKV genomes) using Bowtie2 (http://broadinstitute.github.io/picard), and a new consensus was generated using a combination of SAMtools version 0.1.18 , converted to cDNA using SuperScript III (Invitrogen) and amplified using sequence-independent single-primer amplification  combined Bowtie2 , duplican 0.1.18  and custFlavivirus genus .Genome accession numbers to public databases are listed in


Productivity costs can strongly impact cost-effectiveness outcomes. This study investigated the impact in the context of expensive hospital drugs. This study aimed to: (1) investigate the effect of productivity costs on cost-effectiveness outcomes, (2) determine whether economic evaluations of expensive drugs commonly include productivity costs related to paid and unpaid work, and (3) explore potential reasons for excluding productivity costs from the economic evaluation. We conducted a systematic literature review to identify economic evaluations of 33 expensive drugs. We analysed whether evaluations included productivity costs and whether inclusion or exclusion was related to the study population’s age, health and national health economic guidelines. The impact on cost-effectiveness outcomes was assessed in studies that included productivity costs. Of 249 identified economic evaluations of expensive drugs, 22 (9 %) included productivity costs related to paid work. One study included unpaid productivity. Mostly, productivity cost exclusion could not be explained by the study population’s age and health status, but national guidelines appeared influential. Productivity costs proved often highly influential. This study indicates that productivity costs in economic evaluations of expensive hospital drugs are commonly and inconsistently ignored in economic evaluations. This warrants caution in interpreting and comparing the results of these evaluations.The online version of this article (doi:10.1007/s10198-015-0685-x) contains supplementary material, which is available to authorized users. The development of new and expensive health care technologies has increased the pressure on national health care budgets. Hence, there is a growing focus on whether new interventions offer value for money in terms of cost-effectiveness. This may especially be the case for very expensive interventions with an expected high budget impact, such as newly developed drugs administered in a hospital setting (e.g. new chemotherapies for cancer patients).and societal perspective. However, most countries prescribing a health care perspective allow presenting additional cost-effectiveness scenarios that include broader societal costs, such as productivity costs. England and Wales, where the National Institute for Health and Care Excellence (NICE) operates [In order to determine the relative cost-effectiveness of new expensive interventions, many countries prescribe conducting a health economic evaluation. In an economic evaluation the health effects of two or more treatments are compared to their respective costs. Most countries that prescribe economic evaluations have formulated national health economic guidelines stipulating how these evaluations should be conducted. National guidelines are likely (and intended) to influence how economic evaluations are conducted in practice. One important aspect in such guidelines is the perspective the evaluation should take. Economic evaluations adopting a health care perspective include costs falling on the health care budget only, whereas economic evaluations adopting a societal perspective aim to include all relevant effects and costs, regardless of who bears the costs and who receives the benefits. Approximately half of the national guidelines on the ISPOR ‘pharmacoeconomic guidelines around the world’ website  prescriboperates  and New In the health economic literature, adopting a societal perspective is often advocated –7. HowevAn important question is how such a difference in perspective could potentially affect decision-making. This obviously depends on the additional cost categories included in the analysis when performed from a societal perspective and their relative magnitude. The most influential cost category in that context may be productivity costs. Productivity costs can be defined as “costs associated with production loss and replacement costs due to illness, disability and death of productive persons, both paid and unpaid” . ProductEven though half of the national health economic guidelines prescribe a societal perspective and productivity costs and savings can be substantial, previous studies suggest that, depending on the types of interventions and economic evaluations studied, not more than 8–31 % of economic evaluations actually include productivity costs related to paid work –13. The Therefore, this study sought to answer the question whether inclusion of these costs in expensive drugs studies is influential, in other words, whether they have a substantial impact on cost-effectiveness outcomes. Moreover, it aimed to determine whether cost-effectiveness studies of expensive drugs administered in a hospital setting normally include productivity costs related to paid and unpaid work. In addition, we aimed to explore how productivity costs were calculated in economic evaluations, i.e. which methodology was used to estimate productivity costs. Finally, we explored potential reasons for excluding productivity costs from the economic evaluation, such as countries’ health economic reimbursement submission guidelines as well as age and health status of the studies’ patient populations.To meet the study objectives, we conducted an extensive systematic review of economic evaluations of 33 distinct expensive drugs administered in a hospital setting.Before describing and discussing the methods and results of our systematic review, in the Background Section we first discuss productivity costs and the potential explanations for the poor inclusion of productivity costs in economic evaluations of health care interventions.Commonly, four categories of costs are distinguished in health economic evaluations: direct costs within health care, direct costs outside health care, indirect costs within health care and indirect costs outside health care , 7. ThisFollowing ‘the rule of reason’, which states that if costs “…are trivially small or do not differ across regimens, their inclusion will have little effect on the final results of an analysis, and they may therefore be omitted at the analyst’s discretion” , productFirst, if productivity is not affected by some treatment, including productivity related costs would be superfluous, such as with some treatments aimed at very mild conditions or treatments aimed at very severe conditions in which patients are fully impaired without expectation of returning to paid or unpaid work . In most cases, however, whether health interventions will affect patients’ productivity is difficult to predict.Second, following to the rule of reason, productivity cost inclusion would be irrelevant if productivity is unchanged relative to the comparator (i.e. if productivity changes are similar in both the intervention and comparator groups), since productivity costs will then not change incremental cost-effectiveness ratios. For most interventions, determining up front whether productivity costs in both study arms will be equal is difficult, and excluding productivity costs on this ground is thus debatable.Third, and also related to the rule of reason, productivity costs related to paid work may also be seen as less relevant for economic evaluations of interventions targeted at people not of working age. For instance, if most of the patients receiving an intervention are above retirement age, productivity losses related to paid work may be negligible. Note, however, that this is not the case for losses related to unpaid work. Treatments targeted at very young patients could affect future productivity, rendering productivity costs an important factor. Whether such effects are considered important to economic evaluations also depends on the valuation method chosen: related costs or savings should be included if using the human capital approach  but not A final rationale for ignoring productivity costs in line with the rule of reason might be the expectation that these costs are not very influential if direct costs are relatively high. This might be the case in economic evaluations of (very) expensive drugs, especially when these drugs are administered in a (costly) inpatient setting. When, as a rule, productivity costs have little effect on cost-effectiveness outcomes in economic evaluations of expensive hospital drugs, they might be excluded a priori, limiting the burden to patients, and saving time and other resources. If the costs are influential Next to questions on the relevance of productivity costs in some situations, the inclusion of productivity costs may lead to equity concerns, because their inclusion may favour reimbursement of health interventions targeted at the working population , 27. If A number of reasons highlighted above may affect the inclusion of productivity costs in economic evaluations of expensive hospital drugs. We therefore set out to review the literature in order to investigate this further, as highlighted next.We performed an extensive systematic review of all 33 drugs on the Dutch ‘expensive drug list’ in June 2009 to identify any economic evaluation. Table We used the Cochrane Library and PubMed databases with a publication date limit of January 1998 to June 2009.Queries used for the database search were the drugs’ names and “cost” or “costs”. Inclusion criteria were (1) unique scientific articles in peer-reviewed journals in English, and (2) titles with terms or phrases such as cost(s), budget, economic, financial, price, money, dollar, economy, expenditure, pay, expense, fund, resource, reimbursement, consumption, or expensive. After excluding any reviews, we read abstracts of the remaining articles to determine if they were indeed economic evaluations. Finally, the full texts of the remaining articles were examined (with the exception of those unavailable in the Netherlands or British Library). Title and abstract searches were independently undertaken by two researchers. Full text examinations were carried out by two people in close collaboration.After identifying economic evaluations of expensive drugs, we investigated whether they included productivity costs related to paid or unpaid work and, if they did, how productivity losses were measured and valued. In order to do so we read the method sections of the papers and we examined the tables presenting the costs included in the individual studies.Next, we explored whether the choice of including or excluding productivity costs is related to 1) age—working age of the patient population, (2) the patient population’s ability to work based on disease severity and (3) national health economic guidelines. Where possible we extracted the reported average or median age and the illness of the patients in the study populations. If the age of the patients was not reported in the paper, such as in several health economic modelling papers, we examined the paper reporting on the original clinical trial on which the modelling study was based. To explore whether age may explain the inclusion of productivity costs related to paid work, we assumed that at least a considerable part of a study population would be of working age if the average age of the study population was between 18 and 70. Subsequently, it was investigated whether inclusion or exclusion of productivity costs was related to the (estimated) health related ability to work, or the likelihood that at least a part of the patient population in individual studies would lose or regain the ability to work (in comparison to the control group). These estimations were based on a medical doctor’s expert opinion regarding the severity of disease of the patient populations as extracted from the papers  patients would not be able to perform paid work regardless of treatment). We also examined whether studies aligned with their national health economic guidelines regarding productivity costs. National and regional health economic guidelines were retrieved through the ISPOR ‘pharmacoeconomic guidelines around the world’ website [ age—workFor the studies that included productivity costs, the percentage of total cost accounted for by productivity costs was calculated and reported. We then excluded productivity costs from the study’s incremental cost-effectiveness ratio(s) to analyse the impact of productivity costs on cost-effectiveness outcomes. We described whether inclusion of productivity costs led to change in incremental cost-effectiveness and the magnitude of the change. For cost-minimization studies  we examined only changes in incremental costs. All prices were adjusted to 2009 euros using the European Union Harmonized Indices of Consumer Prices published by Eurostat .The database search resulted in 2,157 articles in Pubmed and 422 in the Cochrane Library, 834 of which were doubles  of productivity costs of all 249 economic evaluations was compared with the study-populations’ median or average age, the estimated work ability and the health economic guidelines of the respective countries. As can be seen in Table Based on national health economic guidelines, for 56 of the 249 economic evaluations, productivity cost inclusion was not allowed  but four of the 56 included productivity costs anyway , 37–39. Three , 46, 47 Regarding the measurement of productivity costs, only seven studies , 48–51 dWith regard to the valuation of lost work, ten of the 22 studies , 45, 49 We could not determine the proportion of total costs accounted for by productivity costs for 11 of the 22 articles due to a limited level of detail in the presented cost items. Four of these 11 , 42, 47 The remaining 11 articles provided information on the absolute amount of productivity costs. In these 11 studies, 37 estimates were available of productivity costs related to an intervention or comparator. Twenty-four of these estimates valued productivity costs according to the human capital approach , 50, 54;To study the impact of productivity costs on cost-effectiveness outcomes, the ICERs, including productivity cost, were recalculated after excluding these costs in the analyses. Since CMAs obviously do not present ICERs, given the assumption of equal effectiveness between comparators, we recalculated the cost differences after excluding productivity costs. Because only one study considered unpaid labour, we limited our calculations to paid labour only. Recalculation of cost-effectiveness outcomes was only possible for the 15 CUAs and three CMAs  specifying the amount of productivity costs, or the effect of productivity costs on the ICER. The change in incremental cost-effectiveness after excluding productivity costs is shown in Fig. We drew two fictive ICER thresholds in the figure for illustrative purposes: one at approximately €40,000 per incremental QALY in the region of the upper limit of the UK costs per QALY threshold  and one A comparison of ICERs with the inclusion and exclusion of productivity costs shows that ICERs increase due to inclusion of productivity costs in six out of 36 cases , 54. In Taking into account the fictive threshold of €40,000 per QALY, eight ICERs exceed the threshold when excluding productivity costs, while not exceeding the threshold when including productivity costs , 51, 52.This study investigated productivity cost inclusion and its impact on cost-effectiveness outcomes in economic evaluations of very expensive drugs. Moreover, the applied methodology regarding productivity cost measurement and valuation was assessed and possible explanatory factors for exclusion of these costs were explored. The results showed that productivity costs were excluded in over 90 % of the investigated economic evaluations. If productivity costs were included, the applied methods were mostly poorly reported.Regarding the main objective of this study, determining whether productivity costs have a substantial impact on cost-effectiveness outcomes, when productivity costs were actually included this was clearly the case. Despite the high direct costs related to expensive drug treatment, productivity costs reflect a relatively high proportion of total costs and can strongly affect incremental cost-effectiveness ratios. With a fixed €40,000 threshold (somewhere in the region of the upper limit of the UK threshold ), decisiGiven the potential strong effects of productivity costs on final outcomes, productivity costs cannot be simply excluded in economic evaluations of expensive hospital drugs based on ‘the rule of reason’ introduced by Gold et al. . Neverthwhen to include productivity costs and how to do so. Several studies did not seem to adhere to their national corresponding guidelines. Partly, this may be explained by some studies not being conducted for reimbursement submission purposes; however, such information was not presented in the papers. It is unclear what the consequences are of not adhering to national guidelines. Likely this differs between countries. Notably, in most of the studies we examined, clear information on how productivity costs were derived was lacking. It has been suggested that the decision to include productivity costs may be driven by strategic considerations regarding the expected influence on final outcomes, resulting in a selection-perspective bias [A secondary objective of our study was to determine the extent to which productivity costs inclusion or exclusion is related to patients’ ages, severity of illness and countries’ health economic reimbursement submission guidelines. Assuming that an average study-population age below 70 implies that a considerable number of the patients are still of working age, age does not seem to explain the exclusion of productivity costs in economic evaluations of expensive hospital drugs. Health status may be of influence, however. In approximately one-third of the studies, the severity of illness of the patients could have been a reason for excluding productivity costs (related to paid work) up front. Moreover, our results indicate that health economic guidelines influence productivity cost inclusion or exclusion, but most guidelines leave room for judging ive bias . AlthougA limitation of our review is that by necessity we assessed the impact of productivity costs on cost-effectiveness outcomes based on the studies that actually included them. The amount of productivity costs in these studies may poorly reflect productivity costs in studies excluding these costs, especially if based on strategic considerations. Moreover, we were unable to determine how inclusion or exclusion of productivity costs related to unpaid work affects cost-effectiveness outcomes, since only one economic evaluation in our review considered unpaid work. Finally, we did not study or discuss the impact of the lack of scientific consensus regarding appropriate methods of measuring and valuing productivity costs on the exclusion of these costs. Numerous instruments, for example, can measure productivity costs (mainly related to paid work) but which instrument provides the most valid estimate is currently unknown. Estimates that vary substantially , 59 by uNext to measurement difficulties, the valuation of productivity costs (related to paid work) has been fiercely debated , 60–64. Productivity costs lead to noticeable differences in cost-effectiveness outcomes of economic evaluations of treatments with expensive hospital drugs. Despite the high direct costs related to the drugs, productivity costs reflect a non-negligible part of total costs when included and, therefore, a priori exclusion of productivity costs is not easy to defend when adopting a societal perspective. Ignoring productivity costs in economic evaluations of expensive hospital drugs without clear motive could imply ignoring important societal costs. That notwithstanding, productivity costs related to paid work are omitted in the majority of cases and productivity costs related to unpaid work are seldom included. The neglect of productivity costs is to some extent explained by the relevant national health economic guidelines prescribing a health care perspective, but the rationale for the majority of studies is unclear. We would argue that if productivity costs are ignored, motivation should be clear. Moreover, excluding productivity costs simply to comply with national guidelines does not render them less relevant to society or welfare improvement. Therefore, in countries prescribing a health care perspective a two-perspective approach, in which ICERs are presented from both a societal and health care perspective (as was done by some studies in this review), may be advisable .Supplementary material 1 (DOC 164 kb)Below is the link to the electronic supplementary material.


To determine risk for Middle East respiratory syndrome coronavirus transmission from camels to humans, we tested serum from 191 persons with various levels of exposure to an infected dromedary herd. We found no serologic evidence of human infection, suggesting that zoonotic transmission of this virus from dromedaries is rare. Cases of Middle East respiratory syndrome (MERS) in humans continue to be reported from the Arabian Peninsula and the Middle East. The largest number of cases has been reported by Saudia Arabia: 818 cases leading to 351 deaths as of December 5, 2014 . They frequently consumed fresh unboiled milk from the camels, of which at least 1 dam and 7 calves were retrospectively confirmed to have been MERS-CoV infected  direct contact with the infected herd  and included veterinary staff and attendants. Because this herd was also used for veterinary teaching and research, animals were frequently handled for clinical examination and specimen collection. With the exception of disposable gloves, which were worn by the veterinarians during examinations, personal protective equipment  was not used. Group 3 comprised 30 veterinary surgeons and clinical support staff working at the Clinical Research Center at the Faculty of Veterinary Medicine and Animal Resources, King Faisal University, Saudi Arabia, who were not exposed to the infected herd. This largest clinical veterinary center in southeastern Saudi Arabia also serves the adjacent countries of the United Arab Emirates, Qatar, Bahrain, Kuwait, and Oman. Camels from across Saudi Arabia and the Gulf states are brought to this research center. Although we did not conduct MERS-CoV testing on camels brought for routine clinical care, some animals may have been shedding MERS-CoV. Staff members came into daily contact with domestic livestock of all species, including dromedaries, of which at least 20 arrived daily for treatment. Disposable gloves were used for examinations, but no respiratory or eye protection was used.Group 4 comprised 3 workers in a camel abattoir in Al Hasa, where 25–35 camels were slaughtered daily. These workers did not wear personal protective equipment. Group 5 comprised 146 persons in the same (Al Hasa) region who were not exposed to camels in their professional work. This group served as negative controls. >50% reduction of signal was also sought as a more sensitive signal of neutralization, which would have been further confirmed in virus plaque neutralization assays.Serum from these 191 persons was tested for MERS-CoV antibodies by using a pseudoparticle neutralization assay that has been previously described, validated, and demonstrated to be at least as sensitive as microneutralization assays . The virus infecting the herd was genetically similar to viruses that had previously infected humans, including in the amino acid sequence of the virus spike protein  from persons exposed to the infected herd was optimal in terms of detecting a serologic response. However, data on antibody titers after asymptomatic or mild MERS-CoV infections are limited, and our conclusion about lack of human infection must be subject to that caveat. Our findings do not imply that dromedaries are not a source of infection for humans. Spillover infection of humans may be more common in other settings in which humans are exposed over sustained periods to animals among which virus prevalence is higher. For example, animals from diverse origins with varying immune status that are housed together in abattoirs before slaughter may provide opportunity for virus amplification and persistence, analogous to that seen with avian influenza virus in live poultry markets  virus, in which the virus can be ubiquitous in live poultry markets in some settings but human infection and disease remain stochastic and rare  (