Person:

Murray, Megan

Rationale: Understanding the genetic variations among Mycobacterium tuberculosis (MTB) strains with differential ability to transmit would be a major step forward in preventing transmission. Objectives: To describe a method to extend conventional proxy measures of transmissibility by adjusting for patient-related factors, thus strengthening the causal association found with bacterial factors. Methods: Clinical, demographic and molecular fingerprinting data were obtained during routine surveillance of verified MTB cases reported in the Netherlands between 1993 and 2011, and the phylogenetic lineages of the isolates were inferred. Odds ratios for host risk factors for clustering were used to obtain a measure of each patient's and cluster's propensity to propagate (CPP). Mean and median cluster sizes across different categories of CPP were compared amongst four different phylogenetic lineages. Results: Both mean and median cluster size grew with increasing CPP category. On average, CPP values from Euro-American lineage strains were higher than Beijing and EAI strains. There were no significant differences between the mean and median cluster sizes among the four phylogenetic lineages within each CPP category. Conclusions: Our finding that the distribution of CPP scores was unequal across four different phylogenetic lineages supports the notion that host-related factors should be controlled for to attain comparability in measuring the different phylogenetic lineages' ability to propagate. Although Euro-American strains were more likely to be in clusters in an unadjusted analysis, no significant differences among the four lineages persisted after we controlled for host factors.

Understanding why some human populations remain persistently poor remains a significant challenge for both the social and natural sciences. The extremely poor are generally reliant on their immediate natural resource base for subsistence and suffer high rates of mortality due to parasitic and infectious diseases. Economists have developed a range of models to explain persistent poverty, often characterized as poverty traps, but these rarely account for complex biophysical processes. In this Essay, we argue that by coupling insights from ecology and economics, we can begin to model and understand the complex dynamics that underlie the generation and maintenance of poverty traps, which can then be used to inform analyses and possible intervention policies. To illustrate the utility of this approach, we present a simple coupled model of infectious diseases and economic growth, where poverty traps emerge from nonlinear relationships determined by the number of pathogens in the system. These nonlinearities are comparable to those often incorporated into poverty trap models in the economics literature, but, importantly, here the mechanism is anchored in core ecological principles. Coupled models of this sort could be usefully developed in many economically important biophysical systems—such as agriculture, fisheries, nutrition, and land use change—to serve as foundations for deeper explorations of how fundamental ecological processes influence structural poverty and economic development.

Background: Throughout the Ebola virus disease (EVD) epidemic in West Africa, field laboratory testing for EVD has relied on complex, multi-step real-time reverse transcription PCR (RT-PCR) assays; an accurate sample-to-answer RT-PCR test would reduce time to results and potentially increase access to testing. We evaluated the performance of the Cepheid GeneXpert Ebola assay on clinical venipuncture whole blood (WB) and buccal swab (BS) specimens submitted to a field biocontainment laboratory in Sierra Leone for routine EVD testing by RT-PCR (“Trombley assay”). Methods and Findings: This study was conducted in the Public Health England EVD diagnostic laboratory in Port Loko, Sierra Leone, using residual diagnostic specimens remaining after clinical testing. EDTA-WB specimens (n = 218) were collected from suspected or confirmed EVD patients between April 1 and July 20, 2015. BS specimens (n = 71) were collected as part of a national postmortem screening program between March 7 and July 20, 2015. EDTA-WB and BS specimens were tested with Xpert (targets: glycoprotein [GP] and nucleoprotein [NP] genes) and Trombley (target: NP gene) assays in parallel. All WB specimens were fresh; 84/218 were tested in duplicate on Xpert to compare WB sampling methods (pipette versus swab); 43/71 BS specimens had been previously frozen. In all, 7/218 (3.2%) WB and 7/71 (9.9%) BS samples had Xpert results that were reported as “invalid” or “error” and were excluded, leaving 211 WB and 64 BS samples with valid Trombley and Xpert results. For WB, 22/22 Trombley-positive samples were Xpert-positive (sensitivity 100%, 95% CI 84.6%–100%), and 181/189 Trombley-negative samples were Xpert-negative (specificity 95.8%, 95% confidence interval (CI) 91.8%–98.2%). Seven of the eight Trombley-negative, Xpert-positive (Xpert cycle threshold [Ct] range 37.7–43.4) WB samples were confirmed to be follow-up submissions from previously Trombley-positive EVD patients, suggesting a revised Xpert specificity of 99.5% (95% CI 97.0%–100%). For Xpert-positive WB samples (n = 22), Xpert NP Ct values were consistently lower than GP Ct values (mean difference −4.06, 95% limits of agreement −6.09, −2.03); Trombley (NP) Ct values closely matched Xpert NP Ct values (mean difference −0.04, 95% limits of agreement −2.93, 2.84). Xpert results (positive/negative) for WB sampled by pipette versus swab were concordant for 78/79 (98.7%) WB samples, with comparable Ct values for positive results. For BS specimens, 20/20 Trombley-positive samples were Xpert-positive (sensitivity 100%, 95% CI 83.2%–100%), and 44/44 Trombley-negative samples were Xpert-negative (specificity 100%, 95% CI 92.0%–100%). This study was limited to testing residual diagnostic samples, some of which had been frozen before use; it was not possible to test the performance of the Xpert Ebola assay at point of care. Conclusions: The Xpert Ebola assay had excellent performance compared to an established RT-PCR benchmark on WB and BS samples in a field laboratory setting. Future studies should evaluate feasibility and performance outside of a biocontainment laboratory setting to facilitate expanded access to testing.

Background: During the 2014 Ebola virus disease (EVD) outbreak, policy-makers were confronted with difficult decisions on how best to test the efficacy of EVD vaccines. On one hand, many were reluctant to withhold a vaccine that might prevent a fatal disease from study participants randomized to a control arm. On the other, regulatory bodies called for rigorous placebo-controlled trials to permit direct measurement of vaccine efficacy prior to approval of the products. A stepped-wedge cluster study (SWCT) was proposed as an alternative to a more traditional randomized controlled vaccine trial to address these concerns. Here, we propose novel “ordered stepped-wedge cluster trial” (OSWCT) designs to further mitigate tradeoffs between ethical concerns, logistics, and statistical rigor. Methodology/Principal Findings We constructed a spatially structured mathematical model of the EVD outbreak in Sierra Leone. We used the output of this model to simulate and compare a series of stepped-wedge cluster vaccine studies. Our model reproduced the observed order of first case occurrence within districts of Sierra Leone. Depending on the infection risk within the trial population and the trial start dates, the statistical power to detect a vaccine efficacy of 90% varied from 14% to 32% for standard SWCT, and from 67% to 91% for OSWCTs for an alpha error of 5%. The model’s projection of first case occurrence was robust to changes in disease natural history parameters. Conclusions/Significance: Ordering clusters in a step-wedge trial based on the cluster’s underlying risk of infection as predicted by a spatial model can increase the statistical power of a SWCT. In the event of another hemorrhagic fever outbreak, implementation of our proposed OSWCT designs could improve statistical power when a step-wedge study is desirable based on either ethical concerns or logistical constraints.

Introduction: Evidence for minimally symptomatic Ebola virus (EBOV) infection is limited. During the 2013–16 outbreak in West Africa, it was not considered epidemiologically relevant to published models or projections of intervention effects. In order to improve our understanding of the transmission dynamics of EBOV in humans, we investigated the occurrence of minimally symptomatic EBOV infection in quarantined contacts of reported Ebola virus disease cases in a recognized ‘hotspot.’ Methodology/Principal Findings We conducted a cross-sectional serosurvey in Sukudu, Kono District, Sierra Leone, from October 2015 to January 2016. A blood sample was collected from 187 study participants, 132 negative controls (individuals with a low likelihood of previous exposure to Ebola virus), and 30 positive controls (Ebola virus disease survivors). IgG responses to Ebola glycoprotein and nucleoprotein were measured using Alpha Diagnostic International ELISA kits with plasma diluted at 1:200. Optical density was read at 450 nm (subtracting OD at 630nm to normalize well background) on a ChroMate 4300 microplate reader. A cutoff of 4.7 U/mL for the anti-GP ELISA yielded 96.7% sensitivity and 97.7% specificity in distinguishing positive and negative controls. We identified 14 seropositive individuals not known to have had Ebola virus disease. Two of the 14 seropositive individuals reported only fever during quarantine while the remaining 12 denied any signs or symptoms during quarantine. Conclusions/Significance: By using ELISA to measure Zaire Ebola virus antibody concentrations, we identified a significant number of individuals with previously undetected EBOV infection in a ‘hotspot’ village in Sierra Leone, approximately one year after the village outbreak. The findings provide further evidence that Ebola, like many other viral infections, presents with a spectrum of clinical manifestations, including minimally symptomatic infection. These data also suggest that a significant portion of Ebola transmission events may have gone undetected during the outbreak. Further studies are needed to understand the potential risk of transmission and clinical sequelae in individuals with previously undetected EBOV infection.

Background: Studies show obesity decreases risk of tuberculosis (TB) disease. There is limited evidence on whether high body mass index also protects against TB infection; how very high body mass indices influence TB risk; or whether nutritional status predicts this risk in children. We assessed the impact of body mass index on incident TB infection and disease among adults and children. Methods and Findings: We conducted a prospective cohort study among household contacts of pulmonary TB cases in Lima, Peru. We determined body mass index at baseline and followed participants for one year for TB infection and disease. We used Cox proportional regression analyses to estimate hazard ratios for incident TB infection and disease. We enrolled 14,044 household contacts, and among 6853 negative for TB infection and disease at baseline, 1787 (26.1%) became infected. A total of 406 contacts developed secondary TB disease during follow-up. Body mass index did not predict risk of TB infection but overweight household contacts had significantly decreased risk of TB disease (HR 0.48; 95% CI 0.37–0.64; p <0.001) compared to those with normal weight. Among adults, body mass index ≥ 35 kg/m2 continued to predict a lower risk of TB disease (HR 0.30; 95% CI 0.12–0.74; p 0.009). We found no association between high body mass index and TB infection or disease among children under 12 years of age. Conclusions: High body mass index protects adults against TB disease even at levels ≥ 35 kg/m2. This protective effect does not extend to TB infection and is not seen in children.