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


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


October 24, 2016


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


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 


October 7, 2016


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


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. 

The First Reported Outbreak of Chikungunya in the U.S. Virgin Islands, 2014–2015

Leora R. Feldstein, Esther M. Ellis, Ali Rowhani-Rahbar, M. Elizabeth Halloran, Brett R. Ellis

American Journal of Tropical Medicine and Hygiene

July 11, 2016


The chikungunya virus (CHIKV) epidemic in the Americas is of significant public health importance due to the lack of effective control and prevention strategies, severe disease morbidity among susceptible populations, and potential for persistent arthralgia and long-term impaired physical functionality. Using surveillance data of suspected CHIKV cases, we describe the first reported outbreak in the U.S. Virgin Islands. CHIKV incidence was highest among individuals aged 55–64 years (13.1 cases per 1,000 population) and lowest among individuals aged 0–14 years (1.8 cases per 1,000 population). Incidence was higher among women compared to men (6.6 and 5.0 cases per 1,000 population, respectively). More than half of reported laboratory-positive cases experienced fever lasting 2–7 days, chills/rigor, myalgia, anorexia, and headache. No clinical symptoms apart from the suspected case definition of fever ≥ 38°C and arthralgia were significantly associated with being a reported laboratory-positive case. These results contribute to our knowledge of demographic risk factors and clinical manifestations of CHIKV disease and may aid in mitigating future CHIKV outbreaks in the Caribbean.

Spatiotemporal dynamics of the Ebola epidemic in Guinea and implications for vaccination and disease elimination: a computational modeling analysis

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

BioMed Central

September 7, 2016


Background: Among the three countries most affected by the Ebola virus disease outbreak in 2014–2015, Guinea presents an unusual spatiotemporal epidemic pattern, with several waves and a long tail in the decay of the epidemic incidence. 
Methods: Here, we develop a stochastic agent-based model at the level of a single household that integrates detailed data on Guinean demography, hospitals, Ebola treatment units, contact tracing, and safe burial interventions. The microsimulation-based model is used to assess the effect of each control strategy and the probability of elimination of the epidemic according to different intervention scenarios, including ring vaccination with the recombinant vesicular stomatitis virus-vectored vaccine. 
Results: The numerical results indicate that the dynamics of the Ebola epidemic in Guinea can be quantitatively explained by the timeline of the implemented interventions. In particular, the early availability of Ebola treatment units and the associated isolation of cases and safe burials helped to limit the number of Ebola cases experienced by Guinea. We provide quantitative evidence of a strong negative correlation between the time series of cases and the number of traced contacts. This result is confirmed by the computational model that suggests that contact tracing effort is a key determinant in the control and elimination of the disease. In data-driven microsimulations, we find that tracing at least 5–10 contacts per case is crucial in preventing epidemic resurgence during the epidemic elimination phase. The computational model is used to provide an analysis of the ring vaccination trial highlighting its potential effect on disease elimination. 
Conclusions: We identify contact tracing as one of the key determinants of the epidemic’s behavior in Guinea, and we show that the early availability of Ebola treatment unit beds helped to limit the number of Ebola cases in Guinea.

Spatial spread of the West Africa Ebola epidemic

Andrew M. Kramer, J. Tomlin Pulliam, Laura W. Alexander, Andrew W. Park, Pejman Rohani, John M. Drake

Royal Society
Open Science

August 3, 2016


Controlling Ebola outbreaks and planning an effective response to future emerging diseases are enhanced by understanding the role of geography in transmission. Here we show how epidemic expansion may be predicted by evaluating the relative probability of alternative epidemic paths.We compared multiple candidate models to characterize the spatial network over which the 2013–2015 West Africa epidemic of Ebola virus spread and estimate the effects of geographical covariates on transmission during peak spread. The best model was a generalized gravity model where the probability of transmission between locations depended on distance, population density and international border closures between Guinea, Liberia and Sierra Leone and neighbouring countries. This model out-performed alternative models based on diffusive spread, the force of infection, mobility estimated from cell phone records and other hypothesized patterns of spread. These findings highlight the importance of integrated geography to epidemic expansion and may contribute to identifying both the most vulnerable unaffected areas and locations of maximum intervention value.

Projected spread of Zika virus in the Americas

Qian Zhang, Kaiyuan Sun, Matteo Chinazzi, Ana Pastore-Piontti, Natalie E. Dean, Diana Patricia Rojas, Stefano Merler, Dina Mistry, Piero Poletti, Luca Rossi, Margaret Bray, M. Elizabeth Halloran, Ira M. Longini Jr., Alessandro Vespignani


July 28, 2016


We use a data-driven global stochastic epidemic model to project past and future spread of the Zika virus (ZIKV) in the Americas. The model has high spatial and temporal resolution, and integrates real-world demographic, human mobility, socioeconomic, temperature, and vector density data. We estimate that the first introduction of ZIKV to Brazil likely occurred between August 2013 and April 2014. We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through December 2016. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of cases of microcephaly assuming three levels of risk associated with ZIKV infection during the first trimester of pregnancy. Our approach represents an early modeling effort aimed at projecting the potential magnitude and timing of the ZIKV epidemic that might be refined as new and more accurate data from the region will be available.

Predictive modeling of cholera outbreaks in Bangladesh

Amanda A. Koepke, Ira M. Longini, Jr., M. Elizabeth Halloran, Jon Wakefield, and Vladimir N. Minin

Annals of Applied Statistics

July 22, 2016


Despite seasonal cholera outbreaks in Bangladesh, little is known about the relationship between environmental conditions and cholera cases. We seek to develop a predictive model for cholera outbreaks in Bangladesh based on environmental predictors. To do this, we estimate the contribution of environmental variables, such as water depth and water temperature, to cholera outbreaks in the context of a disease transmission model. We implement a method which simultaneously accounts for disease dynamics and environmental variables in a Susceptible-Infected-Recovered-Susceptible (SIRS) model. The entire system is treated as a continuous-time hidden Markov model, where the hidden Markov states are the numbers of people who are susceptible, infected or recovered at each time point, and the observed states are the numbers of cholera cases reported. We use a Bayesian framework to fit this hidden SIRS model, implementing particle Markov chain Monte Carlo methods to sample from the posterior distribution of the environmental and transmission parameters given the observed data. We test this method using both simulation and data from Mathbaria, Bangladesh. Parameter estimates are used to make short-term predictions that capture the formation and decline of epidemic peaks. We demonstrate that our model can successfully predict an increase in the number of infected individuals in the population weeks before the observed number of cholera cases increases, which could allow for early notification of an epidemic and timely allocation of resources.

Extrapolating theoretical efficacy of inactivated influenza A/H5N1 virus vaccine from human immunogenicity studies

Leora R. Feldstein, Laura Matrajt, M. Elizabeth Halloran, Wendy A. Keitel, Ira M. Longini Jr., H5N1 Vaccine Working Group


July 19, 2016


Influenza A virus subtype H5N1 has been a public health concern for almost 20 years due to its potential ability to become transmissible among humans. Phase I and II clinical trials have assessed safety, reactogenicity and immunogenicity of inactivated influenza A/H5N1 virus vaccines. A shortage of vaccine is likely to occur during the first months of a pandemic. Hence, determining whether to give one dose to more people or two doses to fewer people to best protect the population is essential. We use hemagglutination–inhibition antibody titers as an immune correlate for avian influenza vaccines. Using an established relationship to obtain a theoretical vaccine efficacy from immunogenicity data from thirteen arms of six phase I and phase II clinical trials of inactivated influenza A/H5N1 virus vaccines, we assessed: (1) the proportion of theoretical vaccine efficacy achieved after a single dose (defined as primary response level), and (2) whether theoretical efficacy increases after a second dose, with and without adjuvant. Participants receiving vaccine with AS03 adjuvant had higher primary response levels (range: 0.48–0.57) compared to participants receiving vaccine with MF59 adjuvant (range: 0.32–0.47), with no observed trends in primary response levels by antigen dosage. After the first and second doses, vaccine with AS03 at dosage levels 3.75, 7.5 and 15 mcg had the highest estimated theoretical vaccine efficacy: Dose (1) 45% (95% CI: 36–57%), 53% (95% CI: 42–63%) and 55% (95% CI: 44–64%), respectively and Dose (2) 93% (95% CI: 89–96%), 97% (95% CI: 95–98%) and 97% (95% CI: 96–100%), respectively. On average, the estimated theoretical vaccine efficacy of lower dose adjuvanted vaccines (AS03 and MF59) was 17% higher than that of higher dose unadjuvanted vaccines, suggesting that including an adjuvant is dose-sparing. These data indicate adjuvanted inactivated influenza A/H5N1 virus vaccine produces high theoretical efficacy after two doses to protect individuals against a potential avian influenza pandemic.

The epidemiology and transmissibility of Zika virus in Girardot and San Andres island, Colombia, September 2015 to January 2016

DP Rojas, NE Dean, Y Yang, E Kenah, J Quintero, S Tomasi, EL Ramirez, Y Kelly, C Castro, G Carrasquilla, ME Halloran, IM Longini


July 14, 2016


Transmission of Zika virus (ZIKV) was first detected in Colombia in September 2015. As of April 2016, Colombia had reported over 65,000 cases of Zika virus disease (ZVD). We analysed daily surveillance data of ZVD cases reported to the health authorities of San Andres and Girardot, Colombia, between September 2015 and January 2016. ZVD was laboratory-confirmed by reverse transcription-polymerase chain reaction (RT-PCR) in the serum of acute cases within five days of symptom onset. We use daily incidence data to estimate the basic reproductive number (R0) in each population. We identified 928 and 1,936 reported ZVD cases from San Andres and Girardot, respectively. The overall attack rate for reported ZVD was 12.13 cases per 1,000 residents of San Andres and 18.43 cases per 1,000 residents of Girardot. Attack rates were significantly higher in females in both municipalities (p < 0.001). Cases occurred in all age groups with highest rates in 20 to 49 year-olds. The estimated R0 for the Zika outbreak was 1.41 (95% confidence interval (CI): 1.15–1.74) in San Andres and 4.61 (95% CI: 4.11–5.16) in Girardot. Transmission of ZIKV is ongoing in the Americas. The estimated R0 from Colombia supports the observed rapid spread.

Multi-epitope Models Explain How Preexisting Antibodies Affect the Generation of Broadly Protective Responses to Influenza

Veronika I. Zarnitsyna, Jennie Lavine, Ali Ellebedy, Rafi Ahmed, Rustom Antia

Plos Pathogens

June 23, 2016


The development of next-generation influenza vaccines that elicit strain-transcendent immunity against both seasonal and pandemic viruses is a key public health goal. Targeting the evolutionarily conserved epitopes on the stem of influenza’s major surface molecule, hemagglutinin, is an appealing prospect, and novel vaccine formulations show promising results in animal model systems. However, studies in humans indicate that natural infection and vaccination result in limited boosting of antibodies to the stem of HA, and the level of stem-specific antibody elicited is insufficient to provide broad strain-transcendent immunity. Here, we use mathematical models of the humoral immune response to explore how pre-existing immunity affects the ability of vaccines to boost antibodies to the head and stem of HA in humans, and, in particular, how it leads to the apparent lack of boosting of broadly cross-reactive antibodies to the stem epitopes. We consider hypotheses where binding of antibody to an epitope: (i) results in more rapid clearance of the antigen; (ii) leads to the formation of antigen-antibody complexes which inhibit B cell activation through Fcγ receptor-mediated mechanism; and (iii) masks the epitope and prevents the stimulation and proliferation of specific B cells. We find that only epitope masking but not the former two mechanisms to be key in recapitulating patterns in data. We discuss the ramifications of our findings for the development of vaccines against both seasonal and pandemic influenza.

Accurate Measurement of the Effects of All Amino-Acid Mutations on Influenza Hemagglutinin

Michael B. Doud, Jesse D. Bloom


June 3, 2016


Influenza genes evolve mostly via point mutations, and so knowing the effect of every amino-acid mutation provides information about evolutionary paths available to the virus. We and others have combined high-throughput mutagenesis with deep sequencing to estimate the effects of large numbers of mutations to influenza genes. However, these measurements have suffered from substantial experimental noise due to a variety of technical problems, the most prominent of which is bottlenecking during the generation of mutant viruses from plasmids. Here we describe advances that ameliorate these problems, enabling us to measure with greatly improved accuracy and reproducibility the effects of all amino-acid mutations to an H1 influenza hemagglutinin on viral replication in cell culture. The largest improvements come from using a helper virus to reduce bottlenecks when generating viruses from plasmids. Our measurements confirm at much higher resolution the results of previous studies suggesting that antigenic sites on the globular head of hemagglutinin are highly tolerant of mutations. We also show that other regions of hemagglutinin—including the stalk epitopes targeted by broadly neutralizing antibodies—have a much lower inherent capacity to tolerate point mutations. The ability to accurately measure the effects of all influenza mutations should enhance efforts to understand and predict viral evolution.

Clinical, epidemiological and virological characteristics of the first detected human case of avian influenza A(H5N6) virus

Rusheng Zhang, Tianmu Chen, Xinhua Ou, Ruchun Liu, Yang Yang , Wen Ye, Jingfang Chen, Dong Yao, Biancheng Sun, Xixing Zhang, Jianxiang Zhou, Yan Sun, Faming Chen, Shi-Ping Wang

Infection, Genetics and Evolution

June 1, 2016


A human infection with novel avian influenza A H5N6 virus emerged in Changsha city, China in February, 2014. This is the first detected human case among all human cases identified from 2014 to early 2016. We obtained and summarized clinical, epidemiological, and virological data from this patient. Complete genome of the virus was determined and compared to other avian influenza viruses via the construction of phylogenetic trees using the neighbor-joining approach. A girl aged five and half years developed fever and mild respiratory symptoms on Feb. 16, 2014 and visited hospital on Feb. 17. Throat swab specimens were obtained from the patient and a novel reassortant avian influenza A H5N6 virus was detected. All eight viral gene segments were of avian origin. The hemagglutinin (HA) and neuraminidase (NA) gene segments were closely related to A/duck/Sichuan/NCXN11/2014(H5N1) and A/chicken/Jiangxi/12782/2014(H10N6) viruses, respectively. The six internal genes were homologous to avian influenza A (H5N2) viruses isolated in duck from Jiangxi in China. This H5N6 virus has not gained genetic mutations necessary for human infection and was suggested to be sensitive to neuraminidase inhibitors, but resistant to adamantanes. Epidemiological investigation of the exposure history of the patient found that a live poultry market could be the source place of infection and the incubation period was 2–5 days. This novel reassortant Avian influenza A(H5N6) virus could be low pathogenic in humans. The prevalence and genetic evolution of this virus should be closely monitored.

Projected Impact of Dengue Vaccination in Yucatán, Mexico.

Thomas J. Hladish, Carl A. B. Pearson, Dennis L. Chao, Diana Patricia Rojas, Gabriel L. Recchia,  Héctor Gómez-Dantés, M. Elizabeth Halloran, Juliet R. C. Pulliam, Ira M. Longini

PLOS Neglected Tropical Diseases

May 26, 2016


Dengue vaccines will soon provide a new tool for reducing dengue disease, but the effectiveness of widespread vaccination campaigns has not yet been determined. We developed an agent-based dengue model representing movement of and transmission dynamics among people and mosquitoes in Yucatán, Mexico, and simulated various vaccine scenarios to evaluate effectiveness under those conditions. This model includes detailed spatial representation of the Yucatán population, including the location and movement of 1.8 million people between 375,000 households and 100,000 workplaces and schools. Where possible, we designed the model to use data sources with international coverage, to simplify re-parameterization for other regions. The simulation and analysis integrate 35 years of mild and severe case data (including dengue serotype when available), results of a seroprevalence survey, satellite imagery, and climatological, census, and economic data. To fit model parameters that are not directly informed by available data, such as disease reporting rates and dengue transmission parameters, we developed a parameter estimation toolkit called AbcSmc, which we have made publicly available. After fitting the simulation model to dengue case data, we forecasted transmission and assessed the relative effectiveness of several vaccination strategies over a 20 year period. Vaccine efficacy is based on phase III trial results for the Sanofi-Pasteur vaccine, Dengvaxia. We consider routine vaccination of 2, 9, or 16 year-olds, with and without a one-time catch-up campaign to age 30. Because the durability of Dengvaxia is not yet established, we consider hypothetical vaccines that confer either durable or waning immunity, and we evaluate the use of booster doses to counter waning. We find that plausible vaccination scenarios with a durable vaccine reduce annual dengue incidence by as much as 80% within five years. However, if vaccine efficacy wanes after administration, we find that there can be years with larger epidemics than would occur without any vaccination, and that vaccine booster doses are necessary to prevent this outcome.

Mathematical Model Reveals the Role of Memory CD8 T Cell Populations in Recall Responses to Influenza

Veronika I. Zarnitsyna, Andreas Handel, Sean R. McMaster, Sarah L. Hayward, Jacob E. Kohlmeier, Rustom Antia

Frontiers in Immunology

May 9, 2016


The current influenza vaccine provides narrow protection against the strains included in the vaccine, and needs to be reformulated every few years in response to the constantly evolving new strains. Novel approaches are directed toward developing vaccines that provide broader protection by targeting B and T cell epitopes that are conserved between different strains of the virus. In this paper, we focus on developing mathematical models to explore the CD8 T cell responses to influenza, how they can be boosted, and the conditions under which they contribute to protection. Our models suggest that the interplay between spatial heterogeneity (with the virus infecting the respiratory tract and the immune response being generated in the secondary lymphoid organs) and T cell differentiation (with proliferation occurring in the lymphoid organs giving rise to a subpopulation of resident T cells in the respiratory tract) is the key to understand the dynamics of protection afforded by the CD8 T cell response to influenza. Our results suggest that the time lag for the generation of resident T cells in the respiratory tract and their rate of decay following infection are the key factors that limit the efficacy of CD8 T cell responses. The models predict that an increase in the level of central memory T cells leads to a gradual decrease in the viral load, and, in contrast, there is a sharper protection threshold for the relationship between the size of the population of resident T cells and protection. The models also suggest that repeated natural influenza infections cause the number of central memory CD8 T cells and the peak number of resident memory CD8 T cells to reach their plateaus, and while the former is maintained, the latter decays with time since the most recent infection.

Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees

Eben Kenah, Tom Britton, M. Elizabeth Halloran, Ira M. Longini Jr

PLoS Computational Biology

April 12, 2016


Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology.

Identification of Low- and High-Impact Hemagglutinin Amino Acid Substitutions That Drive Antigenic Drift of Influenza A(H1N1) Viruses

William T. Harvey, Donald J. Benton, Victoria Gregory, James P. J. Hall, Rodney S. Daniels, Trevor Bedford, Daniel T. Haydon, Alan J. Hay, John W. McCauley, Richard Reeve 

PLoS Pathogens

April 8, 2016


Determining phenotype from genetic data is a fundamental challenge. Identification of emerging antigenic variants among circulating influenza viruses is critical to the vaccine virus selection process, with vaccine effectiveness maximized when constituents are antigenically similar to circulating viruses. Hemagglutination inhibition (HI) assay data are commonly used to assess influenza antigenicity. Here, sequence and 3-D structural information of hemagglutinin (HA) glycoproteins were analyzed together with corresponding HI assay data for former seasonal influenza A(H1N1) virus isolates (1997–2009) and reference viruses. The models developed identify and quantify the impact of eighteen amino acid substitutions on the antigenicity of HA, two of which were responsible for major transitions in antigenic phenotype. We used reverse genetics to demonstrate the causal effect on antigenicity for a subset of these substitutions. Information on the impact of substitutions allowed us to predict antigenic phenotypes of emerging viruses directly from HA gene sequence data and accuracy was doubled by including all substitutions causing antigenic changes over a model incorporating only the substitutions with the largest impact. The ability to quantify the phenotypic impact of specific amino acid substitutions should help refine emerging techniques that predict the evolution of virus populations from one year to the next, leading to stronger theoretical foundations for selection of candidate vaccine viruses. These techniques have great potential to be extended to other antigenically variable pathogens.

Differential and enhanced response to climate forcing in diarrheal disease due to rotavirus across a megacity of the developing world

Pamela P. Martinez, Aaron A. King, Mohammad Yunus, 
A. S. G. Faruque, Mercedes Pascual

Proceedings of the National Academy of Sciences

March 28, 2016


The role of climate forcing in the population dynamics of infectious diseases has typically been revealed via retrospective analyses of incidence records aggregated across space and, in particular, over whole cities. Here, we focus on the transmission dynamics of rotavirus, the main diarrheal disease in infants and young children, within the megacity of Dhaka, Bangladesh. We identify two zones, the densely urbanized core and the more rural periphery, that respond differentially to flooding. Moreover, disease seasonality differs substantially between these regions, spanning variation comparable to the variation from tropical to temperate regions. By combining process-based models with an extensive disease surveillance record, we show that the response to climate forcing is mainly seasonal in the core, where a more endemic transmission resulting from an asymptomatic reservoir facilitates the response to the monsoons. The force of infection in this monsoon peak can be an order of magnitude larger than the force of infection in the more epidemic periphery, which exhibits little or no postmonsoon outbreak in a pattern typical of nearby rural areas. A typically smaller peak during the monsoon season nevertheless shows sensitivity to interannual variability in flooding. High human density in the core is one explanation for enhanced transmission during troughs and an associated seasonal monsoon response in this diarrheal disease, which unlike cholera, has not been widely viewed as climate-sensitive. Spatial demographic, socioeconomic, and environmental heterogeneity can create reservoirs of infection and enhance the sensitivity of disease systems to climate forcing, especially in the populated cities of the developing world.