Perspectives on model forecasts of the 2014–2015 Ebola epidemic in West Africa: lessons and the way forward

Gerardo Chowell, Cécile Viboud,  Lone Simonsen, Stefano Merler, and Alessandro Vespignani

BMC Medicine

March 1, 2017

ABSTRACT

The unprecedented impact and modeling efforts associated with the 2014–2015 Ebola epidemic in West Africa provides a unique opportunity to document the performances and caveats of forecasting approaches used in near-real time for generating evidence and to guide policy. A number of international academic groups have developed and parameterized mathematical models of disease spread to forecast the trajectory of the outbreak. These modeling efforts often relied on limited epidemiological data to derive key transmission and severity parameters, which are needed to calibrate mechanistic models. Here, we provide a perspective on some of the challenges and lessons drawn from these efforts, focusing on (1) data availability and accuracy of early forecasts; (2) the ability of different models to capture the profile of early growth dynamics in local outbreaks and the importance of reactive behavior changes and case clustering; (3) challenges in forecasting the long-term epidemic impact very early in the outbreak; and (4) ways to move forward. We conclude that rapid availability of aggregated population-level data and detailed information on a subset of transmission chains is crucial to characterize transmission patterns, while ensemble-forecasting approaches could limit the uncertainty of any individual model. We believe that coordinated forecasting efforts, combined with rapid dissemination of disease predictions and underlying epidemiological data in shared online platforms, will be critical in optimizing the response to current and future infectious disease emergencies.

Dynamics affecting the risk of silent circulation when oral polio vaccination is stopped

J.S. Koopman, C.J. Henry, J.H. Park, M.C. Eisenberg, E.L. Ionides, J.N. Eisenberg

Epidemics

March 1, 2017

ABSTRACT

Waning immunity could allow transmission of polioviruses without causing poliomyelitis by promoting silent circulation (SC). Undetected SC when oral polio vaccine (OPV) use is stopped could cause difficult to control epidemics. Little is known about waning. To develop theory about what generates SC, we modeled a range of waning patterns. We varied both OPV and wild polio virus (WPV) transmissibility, the time from beginning vaccination to reaching low polio levels, and the infection to paralysis ratio (IPR). There was longer SC when waning continued over time rather than stopping after a few years, when WPV transmissibility was higher or OPV transmissibility was lower, and when the IPR was higher. These interacted in a way that makes recent emergence of prolonged SC a possibility. As the time to reach low infection levels increased, vaccine rates needed to eliminate polio increased and a threshold was passed where prolonged low-level SC emerged. These phenomena were caused by increased contributions to the force of infection from reinfections. The resulting SC occurs at low levels that would be difficult to detect using environmental surveillance. For all waning patterns, modest levels of vaccination of adults shortened SC. Previous modeling studies may have missed these phenomena because (1) they used models with no or very short duration waning and (2) they fit models to paralytic polio case counts. Our analyses show that polio case counts cannot predict SC because nearly identical polio case count patterns can be generated by a range of waning patterns that generate different patterns of SC. We conclude that the possibility of prolonged SC is real but unquantified, that vaccinating modest fractions of adults could reduce SC risk, and that joint analysis of acute flaccid paralysis and environmental surveillance data can help assess SC risks and ensure low risks before stopping OPV.

Persistent Arthralgia Associated with Chikungunya Virus Outbreak, US Virgin Islands, December 2014–February 2016

Leora R. Feldstein, Ali Rowhani-Rahbar, J. Erin Staples, Marcia R. Weaver, M. Elizabeth Halloran, and Esther M. Ellis

Emerging Infectious Diseases

April, 2017

ABSTRACT

After the 2014–2015 outbreak of chikungunya virus in the US Virgin Islands, we compared the prevalence of persistent arthralgia among case-patients and controls. Prevalence was higher in case-patients than controls 6 and 12 months after disease onset. Continued vaccine research to prevent acute illness and long-term sequelae is essential.

Locally Adaptive Smoothing with Markov Random Fields and Shrinkage Priors

James R. Faulkner and Vladimir N. Minin

Bayesian Analysis

February 24, 2017

ABSTRACT

We present a locally adaptive nonparametric curve fitting method that operates within a fully Bayesian framework. This method uses shrinkage priors to induce sparsity in order-kk differences in the latent trend function, providing a combination of local adaptation and global control. Using a scale mixture of normals representation of shrinkage priors, we make explicit connections between our method and kkth order Gaussian Markov random field smoothing. We call the resulting processes shrinkage prior Markov random fields (SPMRFs). We use Hamiltonian Monte Carlo to approximate the posterior distribution of model parameters because this method provides superior performance in the presence of the high dimensionality and strong parameter correlations exhibited by our models. We compare the performance of three prior formulations using simulated data and find the horseshoe prior provides the best compromise between bias and precision. We apply SPMRF models to two benchmark data examples frequently used to test nonparametric methods. We find that this method is flexible enough to accommodate a variety of data generating models and offers the adaptive properties and computational tractability to make it a useful addition to the Bayesian nonparametric toolbox.

Genome sequencing reveals Zika virus diversity and spread in the Americas

Metsky, H.C. , Matranga, C.B., Wohl, S., Schaffner, S.F., Freije, C.A., Winnicki, S.M., West, K., Qu, J., Baniecki, M.L., Gladden-Young, A., Lin, A.E., Tomkins-Tinch, C.H., Park, D.J., Luo, C.Y., Barnes, K.G., Chak, B., Barbosa-Lima, G., Delatorre, E., Vieira, Y.R., Paul, L.M., Tan, A.L., Porcelli, M.C., Vasquez, C., Cannons, A.C., Cone, M.R., Hogan, K.N., Kopp, E.W. IV, Anzinger, J.J., Garcia, K.F., Parham, L.A., Gélvez Ramírez, R.M., Miranda Montoya, M.C., Rojas, D.P., Brown, C.M., Hennigan, S., Sabina, B., Scotland, S., Gangavarapu, K., Grubaugh, N.D., Oliveira, G., Robles-Sikisaka, R., Rambaut, A., Gehrke, L., Smole, S., Halloran, M.E., Villar Centeno, L.A., Mattar, S., Lorenzana, I., Cerbino-Neto, J., Degrave, W., Bozza, P.T., Gnirke, A., Andersen, K.G., Isern, S., Michael, S., Bozza, F., Souza, T.M.L., Bosch, I., Yozwiak, N.L., MacInnis, B.L., Sabeti, P.C.

bioRxiv

February 18, 2017

Despite great attention given to the recent Zika virus (ZIKV) epidemic in the Americas, much remains unknown about its epidemiology and evolution, in part due to a lack of genomic data. We applied multiple sequencing approaches to generate 100 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analyzed the timing and patterns of introductions into distinct geographic regions, confirming phylogenetic evidence for the origin and rapid expansion of the outbreak in Brazil1 , and for multiple introductions from Brazil into Honduras, Colombia, Puerto Rico, other Caribbean islands, and the continental US. We find that ZIKV circulated undetected in many regions of the Americas for up to a year before the first locally transmitted cases were confirmed, highlighting the challenge of effective surveillance for this virus. We further characterize genetic variation across the outbreak to identify mutations with possible functional implications for ZIKV biology and pathogenesis.

The effective rate of influenza reassortment is limited during human infection

Ashley Sobel Leonard, Micah T. McClain, Gavin J. D. Smith, David E. Wentworth, Rebecca A. Halpin, Xudong Lin, Amy Ransier, Timothy B. Stockwell, Suman R. Das, Anthony S. Gilbert, Rob Lambkin-Williams, Geoffrey S. Ginsburg, Christopher W. Woods, Katia Koelle, Christopher J. R. Illingworth

Plos Pathogens

February 7, 2017

ABSTRACT

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral genome sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited.

Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus

Ashley Sobel Leonard, Daniel Weissman, Benjamin Greenbaum, Elodie Ghedin, Katia Koelle

bioRxiv

January 19, 2017

ABSTRACT

The bottleneck governing infectious disease transmission describes the size of the pathogen population transferred from a donor to a recipient host. Accurate quantification of the bottleneck size is of particular importance for rapidly evolving pathogens such as influenza virus, as narrow bottlenecks would limit the extent of transferred viral genetic diversity and, thus, have the potential to slow the rate of viral adaptation. Previous studies have estimated the transmission bottleneck size governing viral transmission through statistical analyses of variants identified in pathogen sequencing data. The methods used by these studies, however, did not account for variant calling thresholds and stochastic dynamics of the viral population within recipient hosts. Because these factors can skew bottleneck size estimates, we here introduce a new method for inferring transmission bottleneck sizes that explicitly takes these factors into account. We compare our method, based on beta-binomial sampling, with existing methods in the literature for their ability to recover the transmission bottleneck size of a simulated dataset. This comparison demonstrates that the beta-binomial sampling method is best able to accurately infer the simulated bottleneck size. We then apply our method to a recently published dataset of influenza A H1N1p and H3N2 infections, for which viral deep sequencing data from inferred donor-recipient transmission pairs are available. Our results indicate that transmission bottleneck sizes across transmission pairs are variable, yet that there is no significant difference in the overall bottleneck sizes inferred for H1N1p and H3N2. The mean bottleneck size for influenza virus in this study, considering all transmission pairs, was Nb = 196 (95% confidence interval 66-392) virions. While this estimate is consistent with previous bottleneck size estimates for this dataset, it is considerably higher than the bottleneck sizes estimated for influenza from other datasets.

Efficacy and effectiveness of an rVSV-vectored vaccine in preventing Ebola virus disease: final results from the Guinea ring vaccination, open-label, cluster-randomised trial (Ebola Ça Suffit!)

Ana Maria Henao-Restrepo, Anton Camacho, Ira M Longini, Conall H Watson, W John Edmunds, Matthias Egger, Miles W Carroll, Natalie E Dean, Ibrahima Diatta, Moussa Doumbia, Bertrand Draguez, Sophie Duraff our, Godwin Enwere, Rebecca Grais, Stephan Gunther, Pierre-Stéphane Gsell, Stefanie Hossmann, Sara Viksmoen Watle, Mandy Kader Kondé, Sakoba Kéïta, Souleymane Kone, Eewa Kuisma, Myron M Levine, Sema Mandal, Thomas Mauget, Gunnstein Norheim, Ximena Riveros, Aboubacar Soumah, Sven Trelle, Andrea S Vicari, John-Arne Røttingen, Marie-Paule Kieny

Lancet

December 23, 2016

ABSTRACT

Background

rVSV-ZEBOV is a recombinant, replication competent vesicular stomatitis virus-based candidate vaccine expressing a surface glycoprotein of Zaire Ebolavirus. We tested the effect of rVSV-ZEBOV in preventing Ebola virus disease in contacts and contacts of contacts of recently confirmed cases in Guinea, west Africa.

The Long-Term Safety, Public Health Impact, and Cost-Effectiveness of Routine Vaccination with a Recombinant, Live-Attenuated Dengue Vaccine (Dengvaxia): A Model Comparison Study

Stefan Flasche, Mark Jit, Isabel Rodrıguez-Barraquer, Laurent Coudeville, Mario Recker, Katia Koelle, George Milne, Thomas J. Hladish, T. Alex Perkins, Derek A. T. Cummings, Ilaria Dorigatti, Daniel J. Laydon, Guido España, Joel Kelso, Ira Longini, Jose Lourenco, Carl A. B. Pearson, Robert C. Reiner, Luis Mier-y-Teran-Romero, Kirsten Vannice, Neil Ferguson

PLOS Medicine

November 29, 2016

ABSTRACT

Background

Large Phase III trials across Asia and Latin America have recently demonstrated the efficacy of a recombinant, live-attenuated dengue vaccine (Dengvaxia) over the first 25 mo following vaccination. Subsequent data collected in the longer-term follow-up phase, however, have raised concerns about a potential increase in hospitalization risk of subsequent dengue infections, in particular among young, dengue-naïve vaccinees. We here report predictions from eight independent modelling groups on the long-term safety, public health impact, and cost-effectiveness of routine vaccination with Dengvaxia in a range of transmission settings, as characterised by seroprevalence levels among 9-y-olds (SP9). These predictions were conducted for the World Health Organization to inform their recommendations on optimal use of this vaccine.

Methods and Findings

The models adopted, with small variations, a parsimonious vaccine mode of action that was able to reproduce quantitative features of the observed trial data. The adopted mode of action assumed that vaccination, similarly to natural infection, induces transient, heterologous protection and, further, establishes a long-lasting immunogenic memory, which determines disease severity of subsequent infections. The default vaccination policy considered was routine vaccination of 9-y-old children in a three-dose schedule at 80% coverage. The outcomes examined were the impact of vaccination on infections, symptomatic dengue, hospitalised dengue, deaths, and cost-effectiveness over a 30-y postvaccination period. Case definitions were chosen in accordance with the Phase III trials.

All models predicted that in settings with moderate to high dengue endemicity (SP9 ≥ 50%), the default vaccination policy would reduce the burden of dengue disease for the population by 6%–25% (all simulations: –3%–34%) and in high-transmission settings (SP9 ≥ 70%) by 13%–25% (all simulations: 10%– 34%). These endemicity levels are representative of the participating sites in both Phase III trials. In contrast, in settings with low transmission intensity (SP9 ≤ 30%), the models predicted that vaccination could lead to a substantial increase in hospitalisation because of dengue. Modelling reduced vaccine coverage or the addition of catch-up campaigns showed that the impact of vaccination scaled approximately linearly with the number of people vaccinated. In assessing the optimal age of vaccination, we found that targeting older children could increase the net benefit of vaccination in settings with moderate transmission intensity (SP9 = 50%). Overall, vaccination was predicted to be potentially cost-effective in most endemic settings if priced competitively.

The results are based on the assumption that the vaccine acts similarly to natural infection. This assumption is consistent with the available trial results but cannot be directly validated in the absence of additional data. Furthermore, uncertainties remain regarding the level of protection provided against disease versus infection and the rate at which vaccine-induced protection declines.

Conclusions

Dengvaxia has the potential to reduce the burden of dengue disease in areas of moderate to high dengue endemicity. However, the potential risks of vaccination in areas with limited exposure to dengue as well as the local costs and benefits of routine vaccination are important considerations for the inclusion of Dengvaxia into existing immunisation programmes. These results were important inputs into WHO global policy for use of this licensed dengue vaccine.

Climate-driven endemic cholera is modulated by human mobility in a megacity

Javier Perez-Saez, Aaron A. King, Andrea Rinaldoa, Mohammad Yunus, Abu S.G. Faruquec, 
Mercedes Pascual

Advances in Water Resources

November 27, 2016

ABSTRACT

Although a differential sensitivity of cholera dynamics to climate variability has been reported in the spatially heterogeneous megacity of Dhaka, Bangladesh, the specific patterns of spread of the resulting risk within the city remain unclear. We build on an established probabilistic spatial model to investigate the importance and role of human mobility in modulating spatial cholera transmission. Mobility fluxes were inferred using a straightforward and generalizable methodology that relies on mapping population density based on a high resolution urban footprint product, and a parameter-free human mobility model. In accordance with previous findings, we highlight the higher sensitivity to the El Niño Southern Oscillation (ENSO) in the highly populated urban center than in the more rural periphery. More significantly, our results show that cholera risk is largely transmitted from the climate-sensitive core to the periphery of the city, with implications for the planning of control efforts. In addition, including human mobility improves the outbreak prediction performance of the model with an 11 month lead. The interplay between climatic and human mobility factors in cholera transmission is discussed from the perspective of the rapid growth of megacities across the developing world.

phylodyn: an R package for phylodynamic simulation and inference

Michael D. Karcher, Julia A. Palacios, Shiwei Lan, Vladimir N. Minin

Molecular Ecology Resources

November 21, 2016

ABSTRACT

We introduce phylodyn, an r package for phylodynamic analysis based on gene genealogies. The package's main functionality is Bayesian nonparametric estimation of effective population size fluctuations over time. Our implementation includes several Markov chain Monte Carlo-based methods and an integrated nested Laplace approximation-based approach for phylodynamic inference that have been developed in recent years. Genealogical data describe the timed ancestral relationships of individuals sampled from a population of interest. Here, individuals are assumed to be sampled at the same point in time (isochronous sampling) or at different points in time (heterochronous sampling); in addition, sampling events can be modelled with preferential sampling, which means that the intensity of sampling events is allowed to depend on the effective population size trajectory. We assume the coalescent and the sequentially Markov coalescent processes as generative models of genealogies. We include several coalescent simulation functions that are useful for testing our phylodynamics methods via simulation studies. We compare the performance and outputs of various methods implemented in phylodyn and outline their strengths and weaknesses. r package phylodyn is available at https://github.com/mdkarcher/phylodyn.

Drivers of Inter-individual Variation in Dengue Viral Load Dynamics

Rotem Ben-Shachar, Scott Schmidler, Katia Koelle

PLOS Computational Biology

November 17, 2016

ABSTRACT

Dengue is a vector-borne viral disease of humans that endemically circulates in many tropical and subtropical regions worldwide. Infection with dengue can result in a range of disease outcomes. A considerable amount of research has sought to improve our understanding of this variation in disease outcomes and to identify predictors of severe disease. Contributing to this research, patterns of viral load in dengue infected patients have been quantified, with analyses indicating that peak viral load levels, rates of viral load decline, and time to peak viremia are useful predictors of severe disease. Here, we take a complementary approach to understanding patterns of clinical manifestation and inter-individual variation in viral load dynamics. Specifically, we statistically fit mathematical within-host models of dengue to individual-level viral load data to test virological and immunological hypotheses explaining inter-individual variation in dengue viral load. We choose between alternative models using model selection criteria to determine which hypotheses are best supported by the data. We first show that the cellular immune response plays an important role in regulating viral load in secondary dengue infections. We then provide statistical support for the process of antibody-dependent enhancement (but not original antigenic sin) in the development of severe disease in secondary dengue infections. Finally, we show statistical support for serotype-specific differences in viral infectivity rates, with infectivity rates of dengue serotypes 2 and 3 exceeding those of serotype 1. These results contribute to our understanding of dengue viral load patterns and their relationship to the development of severe dengue disease. They further have implications for understanding how dengue transmissibility may depend on the immune status of infected individuals and the identity of the infecting serotype.

Cholera in Cameroon, 2000-2012: Spatial and Temporal Analysis at the Operational (Health District) and Sub Climate Levels

Moise C. Ngwa, Song Liang, Ian T. Kracalik, Lillian Morris, Jason K. Blackburn, Leonard M. Mbam, Simon Franky Baonga Ba Pouth, Andrew Teboh, Yang Yang, Mouhaman Arabi, Jonathan D. Sugimoto, John Glenn Morris, Jr.

PLOS Neglected Tropical Diseases

November 17, 2016

ABSTRACT

Introduction

Recurrent cholera outbreaks have been reported in Cameroon since 1971. However, case fatality ratios remain high, and we do not have an optimal understanding of the epidemiology of the disease, due in part to the diversity of Cameroon’s climate subzones and a lack of comprehensive data at the health district level.

Methods/Findings

A unique health district level dataset of reported cholera case numbers and related deaths from 2000–2012, obtained from the Ministry of Public Health of Cameroon and World Health Organization (WHO) country office, served as the basis for the analysis. During this time period, 43,474 cholera cases were reported: 1748 were fatal (mean annual case fatality ratio of 7.9%), with an attack rate of 17.9 reported cases per 100,000 inhabitants per year. Outbreaks occurred in three waves during the 13-year time period, with the highest case fatality ratios at the beginning of each wave. Seasonal patterns of illness differed strikingly between climate subzones (Sudano-Sahelian, Tropical Humid, Guinea Equatorial, and Equatorial Monsoon). In the northern Sudano-Sahelian subzone, highest number of cases tended to occur during the rainy season (July-September). The southern Equatorial Monsoon subzone reported cases year-round, with the lowest numbers during peak rainfall (July-September). A spatial clustering analysis identified multiple clusters of high incidence health districts during 2010 and 2011, which were the 2 years with the highest annual attack rates. A spatiotemporal autoregressive Poisson regression model fit to the 2010–2011 data identified significant associations between the risk of transmission and several factors, including the presence of major waterbody or highway, as well as the average daily maximum temperature and the precipitation levels over the preceding two weeks. The direction and/or magnitude of these associations differed between climate subzones, which, in turn, differed from national estimates that ignored subzones differences in climate variables.

Conclusions/Significance

The epidemiology of cholera in Cameroon differs substantially between climate subzones. Development of an optimal comprehensive country-wide control strategy for cholera requires an understanding of the impact of the natural and built environment on transmission patterns at the local level, particularly in the setting of ongoing climate change.

Forecasting Epidemiological Consequences of Maternal Immunization

Ana I. Bento and Pejman Rohani

Clinical Infectious Diseases

December 1, 2016

ABSTRACT

Background. The increase in the incidence of whooping cough (pertussis) in many countries with high vaccination coverage is alarming. Maternal pertussis immunization has been proposed as an effective means of protecting newborns during the interval between birth and the first routine dose. However, there are concerns regarding potential interference between maternal antibodies and the immune response elicited by the routine schedule, with possible long-term population-level effects.

Methods. We formulated a transmission model comprising both primary routine and maternal immunization. This model was examined to evaluate the long-term epidemiological effects of routine and maternal immunization, together with consequences of potential immune interference scenarios.

Results. Overall, our model demonstrates that maternal immunization is an effective strategy in reducing the incidence of pertussis in neonates prior to the onset of the primary schedule. However, if maternal antibodies lead to blunting, incidence increases among older age groups. For instance, our model predicts that with 60% routine and maternal immunization coverage and 30% blunting, the incidence among neonates (0–2 months) is reduced by 43%. Under the same scenario, we observe a 20% increase in incidence among children aged 5–10 years. However, the downstream increase in the older age groups occurs with a delay of approximately a decade or more.

Conclusions. Maternal immunization has clear positive effects on infant burden of disease, lowering mean infant incidence. However, if maternally derived antibodies adversely affect the immunogenicity of the routine schedule, we predict eventual population-level repercussions that may lead to an overall increase in incidence in older age groups.

Containing Ebola at the Source with Ring Vaccination

Stefano Merler, Marco Ajelli, Laura Fumanelli, Stefano Parlamento, Ana Pastore y Piontti, Natalie E. Dean, Giovanni Putoto, Dante Carraro, Ira M. Longini Jr.,
M. Elizabeth Halloran, Alessandro Vespignani

PLOS Neglected Tropical Diseases

November 2, 2016

ABSTRACT

Interim results from the Guinea Ebola ring vaccination trial suggest high efficacy of the rVSV-ZEBOV vaccine. These findings open the door to the use of ring vaccination strategies in which the contacts and contacts of contacts of each index case are promptly vaccinated to contain future Ebola virus disease outbreaks. To provide a numerical estimate of the effectiveness of ring vaccination strategies we introduce a spatially explicit agent-based model to simulate Ebola outbreaks in the Pujehun district, Sierra Leone, structurally similar to previous modelling approaches. We find that ring vaccination can successfully contain an outbreak for values of the effective reproduction number up to 1.6. Through an extensive sensitivity analysis of parameters characterising the readiness and capacity of the health care system, we identify interventions that, alongside ring vaccination, could increase the likelihood of containment. In particular, shortening the time from symptoms onset to hospitalisation to 2–3 days on average through improved contact tracing procedures, adding a 2km spatial component to the vaccination ring, and decreasing human mobility by quarantining affected areas might contribute increase our ability to contain outbreaks with effective reproduction number up to 2.6. These results have implications for future control of Ebola and other emerging infectious disease threats.

Eradicating infectious disease using weakly transmissible vaccines

Scott L. Nuismer, Benjamin M. Althouse, Ryan May, James J. Bull, Sean P. Stromberg, Rustom Antia

Royal Society Proceedings B

October 26, 2016

ABSTRACT

Viral vaccines have had remarkable positive impacts on human health as well as the health of domestic animal populations. Despite impressive vaccine successes, however, many infectious diseases cannot yet be efficiently controlled or eradicated through vaccination, often because it is impossible to vaccinate a sufficient proportion of the population. Recent advances in molecular biology suggest that the centuries-old method of individual-based vaccine delivery may be on the cusp of a major revolution. Specifically, genetic engineering brings to life the possibility of a live, transmissible vaccine. Unfortunately, releasing a highly transmissible vaccine poses substantial evolutionary risks, including reversion to high virulence as has been documented for the oral polio vaccine. An alternative, and far safer approach, is to rely on genetically engineered and weakly transmissible vaccines that have reduced scope for evolutionary reversion. Here, we use mathematical models to evaluate the potential efficacy of such weakly transmissible vaccines. Our results demonstrate that vaccines with even a modest ability to transmit can significantly lower the incidence of infectious disease and facilitate eradication efforts. Consequently, weakly transmissible vaccines could provide an important tool for controlling infectious disease in wild and domestic animal populations and for reducing the risks of emerging infectious disease in humans.

Statistical inference in partially observed stochastic compartmental models with application to cell lineage tracking of in vivo hematopoiesis

Jason Xu, Samson Koelle, Peter Guttorp, Chuanfeng Wu, Cynthia E. Dunbar, Janis L. Abkowitz, Vladimir N. Minin

arXiv

October 24, 2016

ABSTRACT

Single-cell lineage tracking strategies enabled by recent experimental technologies have produced significant insights into cell fate decisions, but lack the quantitative framework necessary for rigorous statistical analysis of mechanistic models of cell division and differentiation. In this paper, we develop such a framework with corresponding moment-based parameter estimation techniques for continuous-time stochastic compartmental models that provide a probabilistic description of how cells divide and differentiate. We apply this method to hematopoiesis, the complex mechanism of blood cell production. Viewing compartmental models of cell division and differentiation as multi-type branching processes, we derive closed-form expressions for higher moments in a general class of such models. These analytical results allow us to efficiently estimate parameters of compartmental models of hematopoiesis that are much richer than the models used in previous statistical studies. To our knowledge, the method provides the first rate inference procedure for fitting such models to time series data generated from cellular barcoding experiments. After testing the methodology in simulation studies, we apply our estimator to hematopoietic lineage tracking data from rhesus macaques. Our analysis provides a more complete understanding of cell fate decisions during hematopoiesis in non-human primates, which may be more relevant to human biology and clinical strategies than previous findings in murine studies. The methodology is transferrable to a large class of compartmental models and multi-type branching models, commonly used in studies of cancer progression, epidemiology, and many other fields.

A second-order iterated smoothing algorithm

Dao Nguyen,  Edward L. Ionides

Statistics and Computing

October 15, 2016

ABSTRACT

Simulation-based inference for partially observed stochastic dynamic models is currently receiving much attention due to the fact that direct computation of the likelihood is not possible in many practical situations. Iterated filtering methodologies enable maximization of the likelihood function using simulation-based sequential Monte Carlo filters. Doucet et al. (2013) developed an approximation for the first and second derivatives of the log likelihood via simulation-based sequential Monte Carlo smoothing and proved that the approximation has some attractive theoretical properties. We investigated an iterated smoothing algorithm carrying out likelihood maximization using these derivative approximations. Further, we developed a new iterated smoothing algorithm, using a modification of these derivative estimates, for which we establish both theoretical results and effective practical performance. On benchmark computational challenges, this method beat the first-order iterated filtering algorithm. The method’s performance was comparable to a recently developed iterated filtering algorithm based on an iterated Bayes map. Our iterated smoothing algorithm and its theoretical justification provide new directions for future developments in simulation-based inference for latent variable models such as partially observed Markov process models.

Impact of Age and Sex on CD4+ Cell Count Trajectories following Treatment Initiation: An Analysis of the Tanzanian HIV Treatment Database

Arianna R. Means, Kathryn A. Risher ,Eva L. Ujeneza, Innocent Maposa, Joseph Nondi, Steven E. Bellan 

PLOS One

October 7, 2016

ABSTRACT

New guidelines recommend that all HIV-infected individuals initiate antiretroviral treatment (ART) immediately following diagnosis. This study describes how immune reconstitution varies by gender and age to help identify poorly reconstituting subgroups and inform targeted testing initiatives.

Deep Sequencing of Influenza A Virus from a Human Challenge Study Reveals a Selective Bottleneck and Only Limited Intrahost Genetic Diversification

Ashley Sobel Leonard, Micah T. McClain, Gavin J. D. Smith, David Wentworthd, Rebecca A. Halpin, Xudong Lin, Amy Ransier, Timothy B. Stockwell, Suman Das, Anthony S. Gilbert, Robert Lambkin-Williams, Geoffrey S. Ginsburg, Christopher W. Woods, Katia Koelle

Journal of Virology

October 5, 2016

abstract

Knowledge of influenza evolution at the point of transmission and at the intra-host level remains limited, particularly for human hosts. Here, we analyze a unique viral dataset of next-generation sequencing (NGS) samples generated from a human influenza challenge study wherein 17 healthy subjects were inoculated with egg-passaged virus. Nasal wash samples collected from 7 of these subjects were successfully deep sequenced. From these, we characterized changes in the subjects’ viral populations during infection and identified differences between the virus in these samples and the viral stock used to inoculate the subjects. We first calculated pairwise genetic distances between the subjects’ nasal wash samples, the viral stock, and the A/Wisconsin/67/2005 (H3N2) reference strain used to generate the stock virus. These distances revealed that considerable viral evolution occurred at various points in the human challenge study. Further quantitative analyses indicated that: (1) the viral stock contained genetic variants that originated and likely were selected for during the passaging process; (2) direct intranasal inoculation with the viral stock resulted in a selective bottleneck that reduced nonsynonymous genetic diversity in the viral hemagglutinin and nucleoprotein; and (3) intrahost viral evolution continued over the course of infection. These intrahost evolutionary dynamics were dominated by purifying selection. Our findings indicate that rapid viral evolution can occur during acute influenza infection in otherwise healthy human hosts when the founding population size of the virus is large, as is the case with direct intranasal inoculation.