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An Ebola outbreak of unprecedented scope emerged in West Africa in December 2013 and presently continues unabated in the countries of Guinea, Sierra Leone, and Liberia. Ebola is not new to Africa, and outbreaks have been confirmed as far back as 1976. The current West African Ebola outbreak is the largest ever recorded and differs dramatically from prior outbreaks in its duration, number of people affected, and geographic extent. The emergence of this deadly disease in West Africa invites many questions, foremost among these: why now, and why in West Africa? Here, we review the sociological, ecological, and environmental drivers that might have influenced the emergence of Ebola in this region of Africa and its spread throughout the region. Containment of the West African Ebola outbreak is the most pressing, immediate need. A comprehensive assessment of the drivers of Ebola emergence and sustained human-to-human transmission is also needed in order to prepare other countries for importation or emergence of this disease. Such assessment includes identification of country-level protocols and interagency policies for outbreak detection and rapid response, increased understanding of cultural and traditional risk factors within and between nations, delivery of culturally embedded public health education, and regional coordination and collaboration, particularly with governments and health ministries throughout Africa. Public health education is also urgently needed in countries outside of Africa in order to ensure that risk is properly understood and public concerns do not escalate unnecessarily. To prevent future outbreaks, coordinated, multiscale, early warning systems should be developed that make full use of these integrated assessments, partner with local communities in high-risk areas, and provide clearly defined response recommendations specific to the needs of each community.

Environmentally mediated infectious disease transmission models provide a mechanistic approach to examining environmental interventions for outbreaks, such as water treatment or surface decontamination. The shift from the classical SIR framework to one incorporating the environment requires codifying the relationship between exposure to environmental pathogens and infection, i.e. the dose-response relationship. Much of the work characterizing the functional forms of dose-response relationships has used statistical fit to experimental data. However, there has been little research examining the consequences of the choice of functional form in the context of transmission dynamics. To this end, we identify four properties of dose-response functions that should be considered when selecting a functional form: low-dose linearity, scalability, concavity, and whether it is a single-hit model. We find that i) middle- and high-dose data do not constrain the low-dose response, and different dose-response forms that are equally plausible given the data can lead to significant differences in simulated outbreak dynamics; ii) the choice of how to aggregate continuous exposure into discrete doses can impact the modeled force of infection; iii) low-dose linear, concave functions allow the basic reproduction number to control global dynamics; and iv) identifiability analysis offers a way to manage multiple sources of uncertainty and leverage environmental monitoring to make inference about infectivity. By applying an environmentally mediated infectious disease model to the 1993 Milwaukee Cryptosporidium outbreak, we demonstrate that environmental monitoring allows for inference regarding the infectivity of the pathogen and thus improves our ability to identify outbreak characteristics such as pathogen strain.

Background Fomite mediated transmission can be an important pathway causing significant disease transmission in number of settings such as schools, daycare centers, and long-term care facilities. The importance of these pathways relative to other transmission pathways such as direct person-person or airborne will depend on the characteristics of the particular pathogen and the venue in which transmission occurs. Here we analyze fomite mediated transmission through a comparative analysis across multiple pathogens and venues. Methods We developed and analyzed a compartmental model that explicitly accounts for fomite transmission by including pathogen transfer between hands and surfaces. We consider two sub-types of fomite-mediated transmission: direct fomite (e.g., shedding onto fomites) and hand-fomite (e.g., shedding onto hands and then contacting fomites). We use this model to examine three pathogens with distinct environmental characteristics (influenza, rhinovirus, and norovirus) in four venue types. To parameterize the model for each pathogen we conducted a thorough literature search. Results Based on parameter estimates from the literature the reproductive number ( R 0 ) for the fomite route for rhinovirus and norovirus is greater than 1 in nearly all venues considered, suggesting that this route can sustain transmission. For influenza, on the other hand, R 0 for the fomite route is smaller suggesting many conditions in which the pathway may not sustain transmission. Additionally, the direct fomite route is more relevant than the hand-fomite route for influenza and rhinovirus, compared to norovirus. The relative importance of the hand-fomite vs. direct fomite route for norovirus is strongly dependent on the fraction of pathogens initially shed to hands. Sensitivity analysis stresses the need for accurate measurements of environmental inactivation rates, transfer efficiencies, and pathogen shedding. Conclusions Fomite-mediated transmission is an important pathway for the three pathogens examined. The effectiveness of environmental interventions differs significantly both by pathogen and venue. While fomite-based interventions may be able to lower R 0 for fomites below 1 and interrupt transmission, rhinovirus and norovirus are so infectious ( R 0 > > 1 ) that single environmental interventions are unlikely to interrupt fomite transmission for these pathogens.

Background The human papillomavirus (HPV) is the most common sexually transmitted infection and is linked to several types of cancer. HPV vaccination uptake in the U.S. is relatively low, despite the vaccine’s high efficacy. Some parents of adolescents have concerns that vaccination will encourage sexual behavior and therefore choose not to vaccinate. Previous studies investigating vaccination and sexual behavior have included only young women and girls. Methods The objective of this study is to assess associations between HPV-vaccination and sexual behavior in a college-age cohort of both men and women. We analyzed questionnaire data collected from the Michigan HPV and Oropharyngeal Cancer Study, a cohort study designed to investigate HPV infection and its association with sexual behavior (data collected 2015–17, Ann Arbor, MI). Here, we consider vaccination status, sexual behavior, and substance use among 241 college-aged men and women. Logistic, Poisson, and Cox regression were used to determine the relationship between probability of sexual debut, number of sexual partners, and HPV vaccination status at baseline as well as between age at sexual debut and vaccination status at debut. Results HPV vaccination status was not significantly associated with an increased likelihood of sexual debut (odds ratio: 0.80 (95% CI: 0.41–1.58), decreased age of sexual debut (hazard ratio: 0.81 (95% CI: 0.65–1.00), nor an increased number of sexual partners (per year sexually active; incidence rate ratio: 1.27 (95% CI: 0.86–1.87)) in this cohort, after controlling for age, race, sex, and substance use. Instead, race or alcohol use were independent predictors of sexual behavior. Conclusions Concerns about the influence of the HPV vaccine on sexual behavior are likely unfounded for both men and women. These results can aid in increasing vaccine acceptability, inform and strengthen physician recommendations, and ultimately reduce the burden of HPV and HPV-related cancers in the U.S.

Randomized controlled trials (RCTs) evaluate hypotheses in specific contexts and are often considered the gold standard of evidence for infectious disease interventions, but their results cannot immediately generalize to other contexts (e.g., different populations, interventions, or disease burdens). Mechanistic models are one approach to generalizing findings between contexts, but infectious disease transmission models (IDTMs) are not immediately suited for analyzing RCTs, since they often rely on time-series surveillance data. We developed an IDTM framework to explain relative risk outcomes of an infectious disease RCT and applied it to a water, sanitation, and hygiene (WASH) RCT. This model can generalize the RCT results to other contexts and conditions. We developed this compartmental IDTM framework to account for key WASH RCT factors: i) transmission across multiple environmental pathways, ii) multiple interventions applied individually and in combination, iii) adherence to interventions or preexisting conditions, and iv) the impact of individuals not enrolled in the study. We employed a hybrid sampling and estimation framework to obtain posterior estimates of mechanistic parameter sets consistent with empirical outcomes. We illustrated our model using WASH Benefits Bangladesh RCT data (n = 17,187). Our model reproduced reported diarrheal prevalence in this RCT. The baseline estimate of the basic reproduction number R 0 for the control arm (1.10, 95% CrI: 1.07, 1.16) corresponded to an endemic prevalence of 9.5% (95% CrI: 7.4, 13.7%) in the absence of interventions or preexisting WASH conditions. No single pathway was likely able to sustain transmission: pathway-specific R 0 s for water, fomites, and all other pathways were 0.42 (95% CrI: 0.03, 0.97), 0.20 (95% CrI: 0.02, 0.59), and 0.48 (95% CrI: 0.02, 0.94), respectively. An IDTM approach to evaluating RCTs can complement RCT analysis by providing a rigorous framework for generating data-driven hypotheses that explain trial findings, particularly unexpected null results, opening up existing data to deeper epidemiological understanding.

Many cancers are understood to be the product of multiple somatic mutations or other rate-limiting events. Multistage clonal expansion (MSCE) models are a class of continuous-time Markov chain models that capture the multi-hit initiation-promotion-malignant-conversion hypothesis of carcinogenesis. These models have been used broadly to investigate the epidemiology of many cancers, assess the impact of carcinogen exposures on cancer risk, and evaluate the potential impact of cancer prevention and control strategies on cancer rates. Structural identifiability (the analysis of the maximum parametric information available for a model given perfectly measured data) of certain MSCE models has been previously investigated. However, structural identifiability is a theoretical property and does not address the limitations of real data. In this study, we use pancreatic cancer as a case study to examine the practical identifiability of the two-, three-, and four-stage clonal expansion models given age-specific cancer incidence data using a numerical profile-likelihood approach. We demonstrate that, in the case of the three- and four-stage models, several parameters that are theoretically structurally identifiable, are, in practice, unidentifiable. This result means that key parameters such as the intermediate cell mutation rates are not individually identifiable from the data and that estimation of those parameters, even if structurally identifiable, will not be stable. We also show that products of these practically unidentifiable parameters are practically identifiable, and, based on this, we propose new reparameterizations of the model hazards that resolve the parameter estimation problems. Our results highlight the importance of identifiability to the interpretation of model parameter estimates.

Differences in prognosis in HPV-positive and HPV-negative oral (oropharyngeal and oral cavity) squamous cell carcinomas (OSCCs) and increasing incidence of HPV-related cancers have spurred interest in demographic and temporal trends in OSCC incidence. We leverage multistage clonal expansion (MSCE) models coupled with age-period-cohort (APC) epidemiological models to analyze OSCC data in the SEER cancer registry (1973-2012). MSCE models are based on the initiation-promotion-malignant conversion paradigm in carcinogenesis and allow for interpretation of trends in terms of biological mechanisms. APC models seek to differentiate between the temporal effects of age, period, and birth cohort on cancer risk. Previous studies have looked at the effect of period and cohort on tumor initiation, and we extend this to compare model fits of period and cohort effects on each of tumor initiation, promotion, and malignant conversion rates. HPV-related, HPV-unrelated except oral tongue, and HPV-unrelated oral tongue sites are best described by placing period and cohort effects on the initiation rate. HPV-related and non-oral-tongue HPV-unrelated cancers have similar promotion rates, suggesting similar tumorigenesis dynamics once initiated. Estimates of promotion rates at oral tongue sites are lower, corresponding to a longer sojourn time; this finding is consistent with the hypothesis of an etiology distinct from HPV or alcohol and tobacco use. Finally, for the three subsite groups, men have higher initiation rates than women of the same race, and black people have higher promotion than white people of the same sex. These differences explain part of the racial and sex differences in OSCC incidence.

The role of viral interaction—where one virus enhances or inhibits infection with another virus—in respiratory virus transmission is not well characterized. This study used data from 4029 total participants from 957 households who participated in a prospective household cohort study in Southeast Michigan, U.S.A to examine how viral coinfection and cocirculation may impact transmission of symptomatic influenza and respiratory syncytial virus infections. We utilized multivariable mixed effects regression to estimate transmission risk when index cases were coinfected with multiple viruses and when viruses cocirculated within households. This analysis included 201 coinfections involving influenza A virus, 67 involving influenza B virus, and 181 involving respiratory syncytial virus. We show that exposure to symptomatic coinfected index cases was associated with reduced risk of influenza A virus and respiratory syncytial virus transmission compared to exposure to singly infected cases, while infection with another virus was associated with increased risk of acquisition of these viruses. Exposure to coinfected cases among contacts infected with other viruses was associated with increased risk of influenza B virus acquisition. These results suggest that viral interaction may impact symptomatic transmission of these viruses. Interactions between respiratory viruses in co-infections may impact their transmission dynamics but impacts at the individual-level are not well understood. Here, the authors use data from a prospective household-based cohort study to investigate the impact of co-infection on transmission and acquisition of influenza and RSV.

Background Varicella zoster virus (VZV) is one of the eight known human herpesviruses. Initial VZV infection results in chickenpox, while viral reactivation following a period of latency manifests as shingles. Separate vaccines exist to protect against both initial infection and subsequent reactivation. Controversy regarding chickenpox vaccination is contentious with most countries not including the vaccine in their childhood immunization schedule due to the hypothesized negative impact on immune-boosting, where VZV reactivation is suppressed through exogenous boosting of VZV antibodies from exposure to natural chickenpox infections. Methods Population-level chickenpox and shingles notifications from Thailand, a country that does not vaccinate against either disease, were previously fitted with mathematical models to estimate rates of VZV transmission and reactivation. Here, multiple chickenpox and shingles vaccination scenarios were simulated and compared to a model lacking any vaccination to analyze the long-term impacts of VZV vaccination. Results As expected, simulations suggested that an introduction of the chickenpox vaccine, at any coverage level, would reduce chickenpox incidence. However, chickenpox vaccine coverage levels above 35% would increase shingles incidence under realistic estimates of shingles coverage with the current length of protective immunity from the vaccine. A trade-off between chickenpox and shingles vaccination coverage was discovered, where mid-level chickenpox coverage levels were identified as the optimal target to minimize total zoster burden. Only in scenarios where shingles vaccine provided lifelong immunity or coverage exceeded current levels could large reductions in both chickenpox and shingles be achieved. Conclusions The complicated nature of VZV makes it impossible to select a single vaccination scenario as universal policy. Strategies focused on reducing both chickenpox and shingles incidence, but prioritizing the latter should maximize efforts towards shingles vaccination, while slowly incorporating chickenpox vaccination. Alternatively, countries may wish to minimize VZV complications of both chickenpox and shingles, which would lead to maximizing vaccine coverage levels across both diseases. Balancing the consequences of vaccination to overall health impacts, including understanding the impact of an altered mean age of infection for both chickenpox and shingles, would need to be considered prior to any vaccine introduction.