Evidence for supercoughers in an analysis of six tuberculosis cohorts from China, Peru, The Gambia and Uganda

BACKGROUND: It is very difficult to observe tuberculosis (TB) transmission chains and thus, identify superspreaders. We investigate cough duration as a proxy measure of transmission to assess the presence of potential TB superspreaders.DESIGN: We analyzed six studies from China, Peru, The Gambia and Uganda, and determined the distribution of cough duration and compared it with several theoretical distributions. To determine factors associated with cough duration, we used linear regression and boosted regression trees to examine the predictive power of patient, clinical and environmental characteristics.RESULTS: We found within-study heterogeneity in cough duration and strong similarities across studies. Approximately 20% of patients contributed 50% of total cough days, and around 50% of patients contributed 80% of total cough days. The cough duration distribution suggested an initially increasing, and subsequently, decreasing hazard of diagnosis. While some of the exposure variables showed statistically significant associations with cough duration, none of them had a strong effect. Multivariate analyses of different model types did not produce a model that had good predictive power.CONCLUSION: We found consistent evidence for the presence of supercoughers, but no characteristics predictive of such individuals.

An online decision tree for vaccine efficacy trial design during infectious disease epidemics: The InterVax-Tool

•

Phase 3 vaccine efficacy trial design during outbreaks and emergencies is challenging.

•

InterVax-Tool (vaxeval.com) is a structured decision-support tool for trial design.

•

Optimal design must include epidemiological, statistical, ethical, and logistical difficulties.

•

Navigating these issues in real-time requires tools to assist in decision-making.

•

Dynamic guidance, note taking, and tailored choices are key to good user engagement.

Background

Licensed vaccines are urgently needed for emerging infectious diseases, but the nature of these epidemics causes challenges for the design of phase III trials to evaluate vaccine efficacy. Designing and executing rigorous, fast, and ethical, vaccine efficacy trials is difficult, and the decisions and limitations in the design of these trials encompass epidemiological, logistical, regulatory, statistical, and ethical dimensions.

Results

Trial design decisions are complex and interrelated, but current guidance documents do not lend themselves to efficient decision-making. We created InterVax-Tool (http://vaxeval.com), an online, interactive decision-support tool, to help diverse stakeholders navigate the decisions in the design of phase III vaccine trials.

InterVax-Tool offers high-level visual and interactive assistance through a set of four decision trees, guiding users through selection of the: (1) Primary Endpoint, (2) Target Population, (3) Randomization Scheme, and, (4) Comparator. We provide guidance on how key considerations – grouped as Epidemiological, Vaccine-related, Infrastructural, or Sociocultural – inform each decision in the trial design process.

Conclusions

InterVax-Tool facilitates structured, transparent, and collaborative discussion of trial design, while recording the decision-making process. Users can save and share their decisions, which is useful both for comparing proposed trial designs, and for justifying particular design choices.

Here, we describe the goals and features of InterVax-Tool as well as its application to the design of a Zika vaccine efficacy trial.

Downgrading disease transmission risk estimates using terminal importations

As emerging and re-emerging infectious arboviruses like dengue, chikungunya, and Zika threaten new populations worldwide, officials scramble to assess local severity and transmissibility, with little to no epidemiological history to draw upon. Indirect estimates of risk from vector habitat suitability maps are prone to great uncertainty, while direct estimates from epidemiological data are only possible after cases accumulate and, given environmental constraints on arbovirus transmission, cannot be widely generalized beyond the focal region. Combining these complementary methods, we use disease importation and transmission data to improve the accuracy and precision of a priori ecological risk estimates. We demonstrate this approach by estimating the spatiotemporal risks of Zika virus transmission throughout Texas, a high-risk region in the southern United States. Our estimates are, on average, 80% lower than published ecological estimates-with only six of 254 Texas counties deemed capable of sustaining a Zika epidemic-and they are consistent with the number of autochthonous cases detected in 2017. Importantly our method provides a framework for model comparison, as our mechanistic understanding of arbovirus transmission continues to improve. Real-time updating of prior risk estimates as importations and outbreaks arise can thereby provide critical, early insight into local transmission risks as emerging arboviruses expand their global reach.

Evaluation of alternative endpoints for ZIKV vaccine efficacy trials

Zika virus (ZIKV) infection during pregnancy is associated with microcephaly and other birth defects, collectively termed Congenital Zika Syndrome (CZS). During the epidemic in 2015-16, ZIKV spread through the Americas and quickly joined the list of other known teratogenic pathogens, TORCH. Multiple ZIKV vaccines have been developed for protection of pregnant women and women of childbearing age. However, ZIKV infection incidence has since waned substantially, and adverse birth outcomes are rare outcomes of infection. Studying a vaccine's protective efficacy against CZS in a large phase III clinical trial may be infeasible in such times of low incidence. Should trials be initiated, researchers may resort to alternative clinical endpoints. In this study, we simulate a variety of vaccine clinical trial scenarios to evaluate the feasibility of the CZS endpoint in vaccine studies and compare CZS to other potential outcomes: ZIKV infection detected through weekly, biweekly, or monthly testing and laboratory-confirmed, symptomatic Zika Virus Disease. We compare the sample size required for 80% statistical power to detect vaccine efficacy and trial duration for each scenario. Our results show the feasibility of CZS clinical endpoints depends on the timing of simulated clinical trials in the course of a seasonal epidemic, due to CZS risk varying with trimester of infection. This result highlights additional considerations needed when designing vaccine efficacy trials of protection against teratogenic pathogens.

Analyzing Vaccine Trials in Epidemics With Mild and Asymptomatic Infection

Vaccine efficacy against susceptibility to infection (VE_S), regardless of symptoms, is an important endpoint of vaccine trials for pathogens with a high proportion of asymptomatic infection, because such infections may contribute to onward transmission and long-term sequelae, such as congenital Zika syndrome. However, estimating VE_S is resource-intensive. We aimed to identify approaches for accurately estimating VE_S when limited information is available and resources are constrained. We modeled an individually randomized vaccine trial by generating a network of individuals and simulating an epidemic. The disease natural history followed a “susceptible-exposed-infectious/symptomatic (or infectious/asymptomatic)-recovered” model. We then used 7 approaches to estimate VE_S, and we also estimated vaccine efficacy against progression to symptoms (VE_P). A corrected relative risk and an interval-censored Cox model accurately estimate VE_S and only require serological testing of participants once, while a Cox model using only symptomatic infections returns biased estimates. Only acquiring serological endpoints in a 10% sample and imputing the remaining infection statuses yields unbiased VE_S estimates across values of the basic reproduction number (R₀) and accurate estimates of VE_P for higher R₀ values. Identifying resource-preserving methods for accurately estimating VE_S and VE_P is important in designing trials for diseases with a high proportion of asymptomatic infection.

Competing Effects of Indirect Protection and Clustering on the Power of Cluster-Randomized Controlled Vaccine Trials

Power considerations for trials evaluating vaccines against infectious diseases are complicated by indirect protective effects of vaccination. While cluster-randomized controlled trials (cRCTs) are less statistically efficient than individually randomized controlled trials (iRCTs), a cRCT's ability to measure direct and indirect vaccine effects may mitigate the loss of efficiency due to clustering. Within cRCTs, the number and size of clusters affects 3 determinants of power: the effect size being measured, disease incidence, and intracluster correlation. We simulated trials conducted in a collection of small communities to assess how indirect protection and clustering affected the power of cRCTs and iRCTs during an emerging epidemic. Across diverse parameters, we found that within the same trial population, cRCTs were never more powerful than iRCTs, although the difference can be small. We also identified 2 effects that attenuated the loss of cRCT power traditionally associated with increased cluster size. First, if enrollment of fewer, larger clusters was performed to achieve higher vaccine coverage within vaccinated communities, this increased the effect to be measured and, consequently, power. Second, the greater rate of imported transmission in larger communities may increase the attack rate and similarly mitigate loss of power relative to a trial in many, smaller communities.

Couple serostatus patterns in sub-Saharan Africa illuminate the relative roles of transmission rates and sexual network characteristics in HIV epidemiology

HIV prevalence has surpassed 30% in some African countries while peaking at less than 1% in others. The extent to which this variation is driven by biological factors influencing the HIV transmission rate or by variation in sexual network characteristics remains widely debated. Here, we leverage couple serostatus patterns to address this question. HIV prevalence is strongly correlated with couple serostatus patterns across the continent; in particular, high prevalence countries tend to have a lower ratio of serodiscordancy to concordant positivity. To investigate the drivers of this continental pattern, we fit an HIV transmission model to Demographic and Health Survey data from 45,041 cohabiting couples in 25 countries. In doing so, we estimated country-specific HIV transmission rates and sexual network characteristics reflective of pre-couple and extra-couple sexual contact patterns. We found that variation in the transmission rate could parsimoniously explain between-country variation in both couple serostatus patterns and prevalence. In contrast, between-country variation in pre-couple or extra-couple sexual contact rates could not explain the observed patterns. Sensitivity analyses suggest that future work should examine the robustness of this result to between-country variation in how heterogeneous infection risk is within a country, or to assortativity, i.e. the extent to which individuals at higher risk are likely to partner with each other.

The cost-effectiveness of oral HIV pre-exposure prophylaxis and early antiretroviral therapy in the presence of drug resistance among men who have sex with men in San Francisco

BACKGROUND

Poor adherence to either antiretroviral treatment (ART) or pre-exposure prophylaxis (PrEP) can promote drug resistance, though this risk is thought to be considerably higher for ART. In the population of men who have sex with men (MSM) in San Francisco, PrEP coverage reached 9.6% in 2014 and has continued to rise. Given the risk of drug resistance and high cost of second-line drugs, the costs and benefits of initiating ART earlier while expanding PrEP coverage remain unclear.

METHODS

We develop an infection-age-structured mathematical model and fit this model to the annual incidence of AIDS cases and deaths directly, and to resistance and demographic data indirectly. We investigate the impact of six various intervention scenarios (low, medium, or high PrEP coverage, with or without earlier ART) over the next 20 years.

RESULTS

Low (medium, high) PrEP coverage with earlier ART could prevent 22% (42%, 57%) of a projected 44,508 total new infections and 8% (26%, 41%) of a projected 18,426 new drug-resistant infections, and result in a gain of 43,649 (74,048, 103,270) QALYs over 20 years compared to the status quo, at a cost of $4745 ($78,811, $115,320) per QALY gained, respectively.

CONCLUSIONS

High PrEP coverage with earlier ART is expected to provide the greatest benefit but also entail the highest costs among the strategies considered. This strategy is cost-effective for the San Francisco MSM population, even considering the acquisition and transmission of ART-mediated drug resistance. However, without a substantial increase to San Francisco's annual HIV budget, the most advisable strategy may be initiating ART earlier, while maintaining current strategies of PrEP enrollment.

Simulations for designing and interpreting intervention trials in infectious diseases

BACKGROUND

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods.

DISCUSSION

Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects.

CONCLUSION

Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.

Early antiretroviral therapy and potent second-line drugs could decrease HIV incidence of drug resistance

Early initiation of antiretroviral therapy (ART) reduces the risk of drug-sensitive HIV transmission but may increase the transmission of drug-resistant HIV. We used a mathematical model to estimate the long-term population-level benefits of ART and determine the scenarios under which earlier ART (treatment at 1 year post-infection, on average) could decrease simultaneously both total and drug-resistant HIV incidence (new infections). We constructed an infection-age-structured mathematical model that tracked the transmission rates over the course of infection and modelled the patients' life expectancy as a function of ART initiation timing. We fitted this model to the annual AIDS incidence and death data directly, and to resistance data and demographic data indirectly among men who have sex with men (MSM) in San Francisco. Using counterfactual scenarios, we assessed the impact on total and drug-resistant HIV incidence of ART initiation timing, frequency of acquired drug resistance, and second-line drug effectiveness (defined as the combination of resistance monitoring, biomedical drug efficacy and adherence). Earlier ART initiation could decrease the number of both total and drug-resistant HIV incidence when second-line drug effectiveness is sufficiently high (greater than 80%), but increase the proportion of new infections that are drug resistant. Thus, resistance may paradoxically appear to be increasing while actually decreasing.

Assessing real-time Zika risk in the United States

Background

Confirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV’s low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic.

Methods

We present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics.

Results

We assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk.

Conclusions

This framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2394-9) contains supplementary material, which is available to authorized users.

Reevaluating Cumulative HIV-1 Viral Load as a Prognostic Predictor: Predicting Opportunistic Infection Incidence and Mortality in a Ugandan Cohort

Recent studies have evaluated cumulative human immunodeficiency virus type 1 (HIV-1) viral load (cVL) for predicting disease outcomes, with discrepant results. We reviewed the disparate methodological approaches taken and evaluated the prognostic utility of cVL in a resource-limited setting. Using data on the Infectious Diseases Institute (Makerere University, Kampala, Uganda) cohort, who initiated antiretroviral therapy in 2004-2005 and were followed up for 9 years, we calculated patients' time-updated cVL by summing the area under their viral load curves on either a linear scale (cVL1) or a logarithmic scale (cVL2). Using Cox proportional hazards models, we evaluated both metrics as predictors of incident opportunistic infections and mortality. Among 489 patients analyzed, neither cVL measure was a statistically significant predictor of opportunistic infection risk. In contrast, cVL2 (but not cVL1) was a statistically significant predictor of mortality, with each log10 increase corresponding to a 1.63-fold (95% confidence interval: 1.02, 2.60) elevation in mortality risk when cVL2 was accumulated from baseline. However, whether cVL is predictive or not hinges on difficult choices surrounding the cVL metric and statistical model employed. Previous studies may have suffered from confounding bias due to their focus on cVL1, which strongly correlates with other variables. Further methodological development is needed to illuminate whether the inconsistent predictive utility of cVL arises from causal relationships or from statistical artifacts.

Statistical power and validity of Ebola vaccine trials in Sierra Leone: a simulation study of trial design and analysis

BACKGROUND

Safe and effective vaccines could help to end the ongoing Ebola virus disease epidemic in parts of west Africa, and mitigate future outbreaks of the virus. We assess the statistical validity and power of randomised controlled trial (RCT) and stepped-wedge cluster trial (SWCT) designs in Sierra Leone, where the incidence of Ebola virus disease is spatiotemporally heterogeneous, and is decreasing rapidly.

METHODS

We projected district-level Ebola virus disease incidence for the next 6 months, using a stochastic model fitted to data from Sierra Leone. We then simulated RCT and SWCT designs in trial populations comprising geographically distinct clusters at high risk, taking into account realistic logistical constraints, and both individual-level and cluster-level variations in risk. We assessed false-positive rates and power for parametric and non-parametric analyses of simulated trial data, across a range of vaccine efficacies and trial start dates.

FINDINGS

For an SWCT, regional variation in Ebola virus disease incidence trends produced increased false-positive rates (up to 0·15 at α=0·05) under standard statistical models, but not when analysed by a permutation test, whereas analyses of RCTs remained statistically valid under all models. With the assumption of a 6-month trial starting on Feb 18, 2015, we estimate the power to detect a 90% effective vaccine to be between 49% and 89% for an RCT, and between 6% and 26% for an SWCT, depending on the Ebola virus disease incidence within the trial population. We estimate that a 1-month delay in trial initiation will reduce the power of the RCT by 20% and that of the SWCT by 49%.

INTERPRETATION

Spatiotemporal variation in infection risk undermines the statistical power of the SWCT. This variation also undercuts the SWCT's expected ethical advantages over the RCT, because an RCT, but not an SWCT, can prioritise vaccination of high-risk clusters.

FUNDING

US National Institutes of Health, US National Science Foundation, and Canadian Institutes of Health Research.

Frequent and seasonally variable sublethal anthrax infections are accompanied by short-lived immunity in an endemic system

Few studies have examined host-pathogen interactions in wildlife from an immunological perspective, particularly in the context of seasonal and longitudinal dynamics. In addition, though most ecological immunology studies employ serological antibody assays, endpoint titre determination is usually based on subjective criteria and needs to be made more objective. Despite the fact that anthrax is an ancient and emerging zoonotic infectious disease found world-wide, its natural ecology is not well understood. In particular, little is known about the adaptive immune responses of wild herbivore hosts against Bacillus anthracis. Working in the natural anthrax system of Etosha National Park, Namibia, we collected 154 serum samples from plains zebra (Equus quagga), 21 from springbok (Antidorcas marsupialis) and 45 from African elephants (Loxodonta africana) over 2-3 years, resampling individuals when possible for seasonal and longitudinal comparisons. We used enzyme-linked immunosorbent assays to measure anti-anthrax antibody titres and developed three increasingly conservative models to determine endpoint titres with more rigourous, objective mensuration. Between 52 and 87% of zebra, 0-15% of springbok and 3-52% of elephants had measurable anti-anthrax antibody titres, depending on the model used. While the ability of elephants and springbok to mount anti-anthrax adaptive immune responses is still equivocal, our results indicate that zebra in ENP often survive sublethal anthrax infections, encounter most B. anthracis in the wet season and can partially booster their immunity to B. anthracis. Thus, rather than being solely a lethal disease, anthrax often occurs as a sublethal infection in some susceptible hosts. Though we found that adaptive immunity to anthrax wanes rapidly, subsequent and frequent sublethal B. anthracis infections cause maturation of anti-anthrax immunity. By triggering host immune responses, these common sublethal infections may act as immunomodulators and affect population dynamics through indirect immunological and co-infection effects. In addition, with our three endpoint titre models, we introduce more mensuration rigour into serological antibody assays, even under the often-restrictive conditions that come with adapting laboratory immunology methods to wild systems. With these methods, we identified significantly more zebras responding immunologically to anthrax than have previous studies using less comprehensive titre analyses.