Publications
307 results found
Cori A, Donnelly CA, dorigatti, et al., 2017, Key data for outbreak evaluation: building on the Ebola experience, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol: 372, ISSN: 1471-2970
Following the detection of an infectious disease outbreak, rapid epidemiological assessmentis critical to guidean effectivepublic health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained inthe West AfricanEbolaepidemic and prior emerging infectious disease outbreaksto set out a checklist of data needed to: 1) quantify severity and transmissibility;2) characterise heterogeneities in transmission and their determinants;and 3) assess the effectiveness of different interventions.We differentiate data needs into individual-leveldata (e.g. a detailed list of reported cases), exposure data(e.g.identifying where / howcases may have been infected) and populationlevel data (e.g.size/demographicsof the population(s)affected andwhen/where interventions were implemented). A remarkable amount of individual-level and exposuredata was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However,gaps in population-level data (particularly around which interventions were applied whenand where)posed challenges to the assessment of (3).Herewehighlight recurrent data issues, give practical suggestions for addressingthese issues and discuss priorities for improvements in data collection in future outbreaks.
Tostevin A, White E, Dunn D, et al., 2017, Recent trends and patterns in HIV-1 transmitted drug resistance in the United Kingdom, HIV Medicine, Vol: 18, Pages: 204-213, ISSN: 1464-2662
ObjectivesTransmission of drug‐resistant HIV‐1 has decreased in the UK since the early 2000s. This analysis reports recent trends and characteristics of transmitted drug resistance (TDR) in the UK from 2010 to 2013.MethodsResistance tests conducted in antiretroviral treatment (ART)‐naïve individuals between 2010 and 2013 were analysed for the presence of transmitted drug resistance mutations (TDRMs), defined as any mutations from a modified 2009 World Health Organization surveillance list, or a modified 2013 International Antiviral Society‐USA list for integrase tests. Logistic regression was used to examine associations between demographics and the prevalence of TDRMs.ResultsTDRMs were observed in 1223 (7.5%) of 16 425 individuals; prevalence declined from 8.1% in 2010 to 6.6% in 2013 (P = 0.02). The prevalence of TDRMs was higher among men who have sex with men (MSM) compared with heterosexual men and women (8.7% versus 6.4%, respectively) with a trend for decreasing TDRMs among MSM (P = 0.008) driven by a reduction in nucleoside reverse transcriptase inhibitor (NRTI)‐related mutations. The most frequently detected TDRMs were K103N (2.2%), T215 revertants (1.6%), M41L (0.9%) and L90M (0.7%). Predicted phenotypic resistance to first‐line ART was highest to the nonnucleoside reverse transcriptase inhibitors (NNRTIs) rilpivirine and efavirenz (6.2% and 3.4%, respectively) but minimal to NRTIs, including tenofovir, and protease inhibitors (PIs). No major integrase TDRMs were detected among 101 individuals tested while ART‐naïve.ConclusionsWe observed a decrease in TDRMs in recent years. However, this was confined to the MSM population and rates remained stable in those with heterosexually acquired HIV infection. Resistance to currently recommended first‐line ART, including integrase inhibitors, remained reassuringly low.
Nouvellet P, Cori A, Garske T, et al., 2017, A simple approach to measure transmissibility and forecast incidence, Epidemics, Vol: 22, Pages: 29-35, ISSN: 1755-4365
Outbreaks of novel pathogens such as SARS, pandemic influenza and Ebola require substantial investments in reactive interventions, with consequent implementation plans sometimes revised on a weekly basis. Therefore, short-term forecasts of incidence are often of high priority. In light of the recent Ebola epidemic in West Africa, a forecasting exercise was convened by a network of infectious disease modellers. The challenge was to forecast unseen “future” simulated data for four different scenarios at five different time points. In a similar method to that used during the recent Ebola epidemic, we estimated current levels of transmissibility, over variable time-windows chosen in an ad hoc way. Current estimated transmissibility was then used to forecast near-future incidence. We performed well within the challenge and often produced accurate forecasts. A retrospective analysis showed that our subjective method for deciding on the window of time with which to estimate transmissibility often resulted in the optimal choice. However, when near-future trends deviated substantially from exponential patterns, the accuracy of our forecasts was reduced. This exercise highlights the urgent need for infectious disease modellers to develop more robust descriptions of processes – other than the widespread depletion of susceptible individuals – that produce non-exponential patterns of incidence.
Doekes HM, Fraser C, Lythgoe KA, 2017, Effect of the latent reservoir on the evolution of HIV at the within- and between-host Levels, PLoS Computational Biology, Vol: 13, Pages: 1-27, ISSN: 1553-734X
The existence of long-lived reservoirs of latently infected CD4+ T cells is the major barrier to curing HIV, and has been extensively studied in this light. However, the effect of these reservoirs on the evolutionary dynamics of the virus has received little attention. Here, we present a within-host quasispecies model that incorporates a long-lived reservoir, which we then nest into an epidemiological model of HIV dynamics. For biologically plausible parameter values, we find that the presence of a latent reservoir can severely delay evolutionary dynamics within a single host, with longer delays associated with larger relative reservoir sizes and/or homeostatic proliferation of cells within the reservoir. These delays can fundamentally change the dynamics of the virus at the epidemiological scale. In particular, the delay in within-host evolutionary dynamics can be sufficient for the virus to evolve intermediate viral loads consistent with maximising transmission, as is observed, and not the very high viral loads that previous models have predicted, an effect that can be further enhanced if viruses similar to those that initiate infection are preferentially transmitted. These results depend strongly on within-host characteristics such as the relative reservoir size, with the evolution of intermediate viral loads observed only when the within-host dynamics are sufficiently delayed. In conclusion, we argue that the latent reservoir has important, and hitherto under-appreciated, roles in both within- and between-host viral evolution.
Didelot X, Fraser C, Gardy J, et al., 2017, Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks, Molecular Biology and Evolution, Vol: 34, Pages: 997-1007, ISSN: 1537-1719
Genomic data is increasingly being used to understand infectious disease epidemiology. Isolates from a given outbreak are sequenced, and the patterns of shared variation are used to infer which isolates within the outbreak are most closely related to each other. Unfortunately, thephylogenetic trees typically used to represent this variation are not directly informative about who infected whom { a phylogenetic tree is not a transmission tree. However, a transmission tree can be inferred from a phylogeny while accounting for within-host genetic diversity by colouring the branches of a phylogeny according to which host those branches were in. Here we extend this approach and show that it can be applied to partially sampled and ongoing outbreaks. This requires computing the correct probability of an observed transmission tree and we herein demonstrate how to do this for a large class of epidemiological models. Wealso demonstrate how the branch colouring approach can incorporate a variable number of unique colours to represent unsampled intermediates in transmission chains. The resulting algorithm is a reversible jump Monte-Carlo Markov Chain, which we apply to both simulated data and real data from an outbreak of tuberculosis. By accounting for unsampled cases and an outbreak which may not have reached its end, our method is uniquely suited to use in a public health environment during real-time outbreak investigations. We implemented this transmission tree inference methodology in an R package called TransPhylo, which is freely available from https://github.com/xavierdidelot/TransPhylo
Lehtinen S, Blanquart F, Croucher NJ, et al., 2017, Evolution of antibiotic resistance is linked to any genetic mechanism affecting bacterial duration of carriage, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 114, Pages: 1075-1080, ISSN: 0027-8424
Mostowy RJ, Croucher NJ, De Maio N, et al., 2017, Frequent recombination of pneumococcal capsule highlights future risks of emergence of novel serotypes
<jats:title>Abstract</jats:title><jats:p>Capsular diversity of<jats:italic>Streptococcus pneumoniae</jats:italic>constitutes a major obstacle in eliminating the pneumococcal disease. Such diversity is genetically encoded by almost 100 variants of the capsule polysaccharide locus (<jats:italic>cps</jats:italic>). However, the evolutionary dynamics of the capsule – the target of the currently used vaccines – remains not fully understood. Here, using genetic data from 4,469 bacterial isolates, we found<jats:italic>cps</jats:italic>to be an evolutionary hotspot with elevated substitution and recombination rates. These rates were a consequence of altered selection at this locus, supporting the hypothesis that the capsule has an increased potential to generate novel diversity compared to the rest of the genome. Analysis of twelve serogroups revealed their complex evolutionary history, which was principally driven by recombination with other serogroups and other streptococci. We observed significant variation in recombination rates between different serogroups. This variation could only be partially explained by the lineage-specific recombination rate, the remaining factors being likely driven by serogroup-specific ecology and epidemiology. Finally, we discovered two previously unobserved mosaic serotypes in the densely sampled collection from Mae La, Thailand, here termed 10X and 21X. Our results thus emphasise the strong adaptive potential of the bacterium by its ability to generate novel serotypes by recombination.</jats:p>
Ratmann O, Hodcroft EB, Pickles M, et al., 2017, Phylogenetic tools for generalized HIV-1 epidemics: findings from the PANGEA-HIV methods comparison, Molecular Biology and Evolution, Vol: 34, Pages: 185-203, ISSN: 1537-1719
Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation > 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods’ development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention.
Yebra G, Hodcroft EB, Ragonnet-Cronin ML, et al., 2016, Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic., Scientific Reports, Vol: 6, ISSN: 2045-2322
HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (gag-pol-env, gag-pol, gag, pol, env and partial pol) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree's using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the gag-pol-env datasets showing the best performance and gag and partial pol sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.
El Bouzidi K, White E, Mbisa JL, et al., 2016, HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK, Journal of Antimicrobial Chemotherapy, Vol: 71, Pages: 3487-3494, ISSN: 0305-7453
BackgroundDarunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings.ObjectivesWe examined darunavir DRMs emerging in clinical practice in the UK.Patients and methodsBaseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PI-naive controls.ResultsOf 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group.ConclusionsOur findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility.
International Ebola Response Team, Agua-Agum J, Ariyarajah A, et al., 2016, Exposure patterns driving Ebola transmissions in West Africa: a retrospective observational study, PLOS Medicine, Vol: 13, ISSN: 1549-1277
BACKGROUND: The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved.METHODS AND FINDINGS: Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola ("cases") were asked if they had exposure to other potential Ebola cases ("potential source contacts") in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO's response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = -0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the
Blanquart F, Grabowski MK, Herbeck J, et al., 2016, A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda, eLife, Vol: 5, ISSN: 2050-084X
Evolutionary theory hypothesizes that intermediate virulence maximizes pathogenfitness as a result of a trade-off between virulence and transmission, but empirical evidenceremains scarce. We bridge this gap using data from a large and long-standing HIV-1 prospectivecohort, in Uganda. We use an epidemiological-evolutionary model parameterised with this data toderive evolutionary predictions based on analysis and detailed individual-based simulations. Werobustly predict stabilising selection towards a low level of virulence, and rapid attenuation of thevirus. Accordingly, set-point viral load, the most common measure of virulence, has declined in thelast 20 years. Our model also predicts that subtype A is slowly outcompeting subtype D, with bothsubtypes becoming less virulent, as observed in the data. Reduction of set-point viral loads shouldhave resulted in a 20% reduction in incidence, and a three years extension of untreatedasymptomatic infection, increasing opportunities for timely treatment of infected individuals.
Lythgoe KA, Blanquart F, Pellis L, et al., 2016, Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics, PLOS Biology, Vol: 14, ISSN: 1545-7885
The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body's viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation.
Agua-Agum J, Allegranzi B, Ariyarajah A, et al., 2016, After Ebola in West Africa - Unpredictable Risks, Preventable Epidemics, New England Journal of Medicine, Vol: 375, Pages: 587-596, ISSN: 1533-4406
Between December 2013 and April 2016, the largest epidemic of Ebola virus disease (EVD) to date generated more than 28,000 cases and more than 11,000 deaths in the large, mobile populations of Guinea, Liberia, and Sierra Leone. Tracking the rapid rise and slower decline of the West African epidemic has reinforced some common understandings about the epidemiology and control of EVD but has also generated new insights. Despite having more information about the geographic distribution of the disease, the risk of human infection from animals and from survivors of EVD remains unpredictable over a wide area of equatorial Africa. Until human exposure to infection can be anticipated or avoided, future outbreaks will have to be managed with the classic approach to EVD control — extensive surveillance, rapid detection and diagnosis, comprehensive tracing of contacts, prompt patient isolation, supportive clinical care, rigorous efforts to prevent and control infection, safe and dignified burial, and engagement of the community. Empirical and modeling studies conducted during the West African epidemic have shown that large epidemics of EVD are preventable — a rapid response can interrupt transmission and restrict the size of outbreaks, even in densely populated cities. The critical question now is how to ensure that populations and their health services are ready for the next outbreak, wherever it may occur. Health security across Africa and beyond depends on committing resources to both strengthen national health systems and sustain investment in the next generation of vaccines, drugs, and diagnostics.
Lamers SL, Barbier A, Ratmann O, et al., 2016, HIV-1 Sequence Data Coverage in Central East Africa from 1959-2013, AIDS Research and Human Retroviruses, ISSN: 0889-2229
Central and Eastern African HIV sequence data has been most critical in understanding the establishment and evolution of the global HIV pandemic. Here we report on the extent of publically available HIV genetic sequence data in the Los Alamos National Laboratory Sequence Database sampled from 1959-2013 from six African countries: Uganda, Kenya, Tanzania, Burundi, the Democratic Republic of Congo, and Rwanda. We have summarized these data, including HIV subtypes, the years sampled, and the genomic regions sequenced. We also provide curated alignments for this important geographic area in five HIV genomic regions with substantial coverage.
Cauchemez S, Nouvellet P, Cori A, et al., 2016, Unraveling the drivers of MERS-CoV transmission., Proceedings of the National Academy of Sciences of the United States of America, Vol: 113, Pages: 9081-9086, ISSN: 1091-6490
With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.
Heffernan A, Barber E, Thomas R, et al., 2016, Impact and Cost-Effectiveness of Point-Of-Care CD4 Testing on the HIV Epidemic in South Africa., PLOS One, Vol: 11, ISSN: 1932-6203
Rapid diagnostic tools have been shown to improve linkage of patients to care. In the context of infectious diseases, assessing the impact and cost-effectiveness of such tools at the population level, accounting for both direct and indirect effects, is key to informing adoption of these tools. Point-of-care (POC) CD4 testing has been shown to be highly effective in increasing the proportion of HIV positive patients who initiate ART. We assess the impact and cost-effectiveness of introducing POC CD4 testing at the population level in South Africa in a range of care contexts, using a dynamic compartmental model of HIV transmission, calibrated to the South African HIV epidemic. We performed a meta-analysis to quantify the differences between POC and laboratory CD4 testing on the proportion linking to care following CD4 testing. Cumulative infections averted and incremental cost-effectiveness ratios (ICERs) were estimated over one and three years. We estimated that POC CD4 testing introduced in the current South African care context can prevent 1.7% (95% CI: 0.4% - 4.3%) of new HIV infections over 1 year. In that context, POC CD4 testing was cost-effective 99.8% of the time after 1 year with a median estimated ICER of US$4,468/DALY averted. In healthcare contexts with expanded HIV testing and improved retention in care, POC CD4 testing only became cost-effective after 3 years. The results were similar when, in addition, ART was offered irrespective of CD4 count, and CD4 testing was used for clinical assessment. Our findings suggest that even if ART is expanded to all HIV positive individuals and HIV testing efforts are increased in the near future, POC CD4 testing is a cost-effective tool, even within a short time horizon. Our study also illustrates the importance of evaluating the potential impact of such diagnostic technologies at the population level, so that indirect benefits and costs can be incorporated into estimations of cost-effectiveness.
Herbeck JT, Mittler JE, Gottlieb GS, et al., 2016, Evolution of HIV virulence in response to widespread scale up of antiretroviral therapy: a modeling study, Virus Evolution, Vol: 2, ISSN: 2057-1577
There are global increases in the use of HIV antiretroviral therapy (ART), guided by clinical benefits of early ART initiation and the efficacy of treatment as prevention of transmission. Separately, it has been shown theoretically and empirically that HIV virulence can evolve over time; observed virulence levels may reflect an adaptive balance between infected lifespan and per-contact transmission rate. However, the potential effects of widespread ART usage on HIV virulence are unknown. To predict these effects, we used an agent-based stochastic model to simulate evolutionary trends in HIV virulence, using set point viral load as a proxy for virulence. We calibrated our model to prevalence and incidence trends of South Africa. We explored two distinct ART scenarios: (1) ART initiation based on HIV-infected individuals reaching a CD4 count threshold; and (2) ART initiation based on individual time elapsed since HIV infection (a scenario that mimics “universal testing and treatment” (UTT) aspirations). In each case, we considered a range in population uptake of ART. We found that HIV virulence is generally unchanged in scenarios of CD4-based initiation. However, with ART initiation based on time since infection, virulence can increase moderately within several years of ART rollout, under high coverage levels and early treatment initiation (albeit within the context of epidemics that are rapidly decreasing in size). Sensitivity analyses suggested the impact of ART on virulence is relatively insensitive to model calibration. Our modeling study suggests that increasing HIV virulence driven by UTT is likely not a major public health concern, but should be monitored in sentinel surveillance, in a manner similar to transmitted resistance to antiretroviral drugs.
Croucher NJ, Mostowy R, Wymant C, et al., 2016, Horizontal DNA transfer mechanisms of bacteria as weapons of intragenomic conflict, PLOS Biology, Vol: 14, ISSN: 1545-7885
Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell-cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing "arms race." Reduced rates of transformation have also been observed in cells infected by MGEs t
Lessler J, Salje H, van Kerkhove M, et al., 2016, Estimating the Severity and Subclinical Burden of Middle East Respiratory Syndrome Coronavirus Infection in the Kingdom of Saudi Arabia, American Journal of Epidemiology, Vol: 183, Pages: 657-663, ISSN: 1476-6256
Not all persons infected with Middle East respiratory syndrome coronavirus (MERS-CoV) develop severe symptoms, which likely leads to an underestimation of the number of people infected and an overestimation of the severity. To estimate the number of MERS-CoV infections that have occurred in the Kingdom of Saudi Arabia, we applied a statistical model to a line list describing 721 MERS-CoV infections detected between June 7, 2012, and July 25, 2014. We estimated that 1,528 (95% confidence interval (CI): 1,327, 1,883) MERS-CoV infections occurred in this interval, which is 2.1 (95% CI: 1.8, 2.6) times the number reported. The probability of developing symptoms ranged from 11% (95% CI: 4, 25) in persons under 10 years of age to 88% (95% CI: 72, 97) in those 70 years of age or older. An estimated 22% (95% CI: 18, 25) of those infected with MERS-CoV died. MERS-CoV is deadly, but this work shows that its clinical severity differs markedly between groups and that many cases likely go undiagnosed.
Agua-Agum J, Ariyarajah A, Blake IM, et al., 2016, Ebola virus disease among male and female persons in West Africa, New England Journal of Medicine, Vol: 374, Pages: 96-98, ISSN: 1533-4406
Ratmann O, van Sighem A, Bezemer D, et al., 2016, Sources of HIV infection among men having sex with men and implications for prevention, Science Translational Medicine, Vol: 8, ISSN: 1946-6242
Pinsent A, Fraser C, Ferguson NM, et al., 2016, A systematic review of reported reassortantviral lineages of influenza A, BMC Infectious Diseases, ISSN: 1471-2334
Nouvellet P, Garske T, Mills HL, et al., 2015, The role of rapid diagnostics in managing Ebola epidemics, Nature, Vol: 528, Pages: S109-S116, ISSN: 0028-0836
Ebola emerged in West Africa around December 2013 and swept through Guinea, Sierra Leone and Liberia, giving rise to 27,748 confirmed, probable and suspected cases reported by 29 July 2015. Case diagnoses during the epidemic have relied on polymerase chain reaction-based tests. Owing to limited laboratory capacity and local transport infrastructure, the delays from sample collection to test results being available have often been 2 days or more. Point-of-care rapid diagnostic tests offer the potential to substantially reduce these delays. We review Ebola rapid diagnostic tests approved by the World Health Organization and those currently in development. Such rapid diagnostic tests could allow early triaging of patients, thereby reducing the potential for nosocomial transmission. In addition, despite the lower test accuracy, rapid diagnostic test-based diagnosis may be beneficial in some contexts because of the reduced time spent by uninfected individuals in health-care settings where they may be at increased risk of infection; this also frees up hospital beds. We use mathematical modelling to explore the potential benefits of diagnostic testing strategies involving rapid diagnostic tests alone and in combination with polymerase chain reaction testing. Our analysis indicates that the use of rapid diagnostic tests with sensitivity and specificity comparable with those currently under development always enhances control, whether evaluated at a health-care-unit or population level. If such tests had been available throughout the recent epidemic, we estimate, for Sierra Leone, that their use in combination with confirmatory polymerase chain-reaction testing might have reduced the scale of the epidemic by over a third.
Cori A, Pickles M, van Sighem A, et al., 2015, CD4+ cell dynamics in untreated HIV-1 infection: overall rates, and effects of age, viral load, sex and calendar time., AIDS, Vol: 29, Pages: 2435-2446, ISSN: 0269-9370
BACKGROUND: CD4 cell count is a key measure of HIV disease progression, and the basis of successive international guidelines for treatment initiation. CD4 cell dynamics are used in mathematical and econometric models for evaluating public health need and interventions. Here, we estimate rates of CD4 decline, stratified by relevant covariates, in a form that is clinically transparent and can be directly used in such models. METHODS: We analyse the AIDS Therapy Evaluation in the Netherlands cohort, including individuals with date of seroconversion estimated to be within 1 year and with intensive clinical follow-up prior to treatment initiation. Owing to the fact that CD4 cell counts are intrinsically noisy, we separate the analysis into long-term trends of smoothed CD4 cell counts and an observation model relating actual CD4 measurements to the underlying smoothed counts. We use a monotonic spline smoothing model to describe the decline of smoothed CD4 cell counts through categories CD4 above 500, 350-500, 200-350 and 200 cells/μl or less. We estimate the proportion of individuals starting in each category after seroconversion and the average time spent in each category. We examine individual-level cofactors which influence these parameters. RESULTS: Among untreated individuals, the time spent in each compartment was 3.32, 2.70, 5.50 and 5.06 years. Only 76% started in the CD4 cell count above 500 cells/μl compartment after seroconversion. Set-point viral load (SPVL) was an important factor: individuals with at least 5 log10 copies/ml took 5.37 years to reach CD4 cell count less than 200 cells/μl compared with 15.76 years for SPVL less than 4 log10 copies/ml. CONCLUSION: Many individuals already have CD4 cell count below 500 cells/μl after seroconversion. SPVL strongly influences the rate of CD4 decline. Treatment guidelines should consider measuring SPVL, whereas mathematical models should incorporate SPVL stratification.
Bezemer D, Cori A, Ratmann O, et al., 2015, Dispersion of the HIV-1 Epidemic in Men Who Have Sex with Men in the Netherlands: A Combined Mathematical Model and Phylogenetic Analysis., PLOS Medicine, Vol: 12, Pages: e1001898-e1001898, ISSN: 1549-1277
BACKGROUND: The HIV-1 subtype B epidemic amongst men who have sex with men (MSM) is resurgent in many countries despite the widespread use of effective combination antiretroviral therapy (cART). In this combined mathematical and phylogenetic study of observational data, we aimed to find out the extent to which the resurgent epidemic is the result of newly introduced strains or of growth of already circulating strains. METHODS AND FINDINGS: As of November 2011, the ATHENA observational HIV cohort of all patients in care in the Netherlands since 1996 included HIV-1 subtype B polymerase sequences from 5,852 patients. Patients who were diagnosed between 1981 and 1995 were included in the cohort if they were still alive in 1996. The ten most similar sequences to each ATHENA sequence were selected from the Los Alamos HIV Sequence Database, and a phylogenetic tree was created of a total of 8,320 sequences. Large transmission clusters that included ≥10 ATHENA sequences were selected, with a local support value ≥ 0.9 and median pairwise patristic distance below the fifth percentile of distances in the whole tree. Time-varying reproduction numbers of the large MSM-majority clusters were estimated through mathematical modeling. We identified 106 large transmission clusters, including 3,061 (52%) ATHENA and 652 Los Alamos sequences. Half of the HIV sequences from MSM registered in the cohort in the Netherlands (2,128 of 4,288) were included in 91 large MSM-majority clusters. Strikingly, at least 54 (59%) of these 91 MSM-majority clusters were already circulating before 1996, when cART was introduced, and have persisted to the present. Overall, 1,226 (35%) of the 3,460 diagnoses among MSM since 1996 were found in these 54 long-standing clusters. The reproduction numbers of all large MSM-majority clusters were around the epidemic threshold value of one over the whole study period. A tendency towards higher numbers was visible in recent years, especially in the more recently
Eaton JW, Bacaer N, Bershteyn A, et al., 2015, Assessment of epidemic projections using recent HIV survey data in South Africa: a validation analysis of ten mathematical models of HIV epidemiology in the antiretroviral therapy era, Lancet Global Health, Vol: 3, Pages: e598-e608, ISSN: 2214-109X
BackgroundMathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012.MethodsWe compared ten model projections of HIV prevalence, HIV incidence, and antiretroviral therapy (ART) coverage for South Africa with estimates from national household survey data from 2012. Model projections for 2012 were made before the publication of the 2012 household survey. We compared adult (age 15–49 years) HIV prevalence in 2012, the change in prevalence between 2008 and 2012, and prevalence, incidence, and ART coverage by sex and by age groups between model projections and the 2012 household survey.FindingsAll models projected lower prevalence estimates for 2012 than the survey estimate (18·8%), with eight models' central projections being below the survey 95% CI (17·5–20·3). Eight models projected that HIV prevalence would remain unchanged (n=5) or decline (n=3) between 2008 and 2012, whereas prevalence estimates from the household surveys increased from 16·9% in 2008 to 18·8% in 2012 (difference 1·9, 95% CI −0·1 to 3·9). Model projections accurately predicted the 1·6 percentage point prevalence decline (95% CI −0·3 to 3·5) in young adults aged 15–24 years, and the 2·2 percentage point (0·5 to 3·9) increase in those aged 50 years and older. Models accurately represented the number of adults on ART in 2012; six of ten models were within the survey 95% CI of 1·54–2·12 million. However, the differential ART coverage between women and men was not fully captured; all model projections of the sex ratio of women to men on ART were lower than the survey estimate of 2·22 (95% CI 1·73–2·71).InterpretationProjec
van Sighem A, Nakagawa F, De Angelis D, et al., 2015, Estimating HIV Incidence, Time to Diagnosis, and the Undiagnosed HIV Epidemic Using Routine Surveillance Data, EPIDEMIOLOGY, Vol: 26, Pages: 653-660, ISSN: 1044-3983
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Jose S, Quinn K, Dunn D, et al., 2015, Virological failure and development of new resistance mutations according to CD4 count at combination antiretroviral therapy initiation, HIV Medicine, Vol: 17, Pages: 368-372, ISSN: 1464-2662
ObjectivesNo randomized controlled trials have yet reported an individual patient benefit of initiating combination antiretroviral therapy (cART) at CD4 counts > 350 cells/μL. It is hypothesized that earlier initiation of cART in asymptomatic and otherwise healthy individuals may lead to poorer adherence and subsequently higher rates of resistance development.MethodsIn a large cohort of HIV-positive individuals, we investigated the emergence of new resistance mutations upon virological treatment failure according to the CD4 count at the initiation of cART.ResultsOf 7918 included individuals, 6514 (82.3%), 996 (12.6%) and 408 (5.2%) started cART with a CD4 count ≤ 350, 351–499 and ≥ 500 cells/μL, respectively. Virological rebound occurred while on cART in 488 (7.5%), 46 (4.6%) and 30 (7.4%) with a baseline CD4 count ≤ 350, 351–499 and ≥ 500 cells/μL, respectively. Only four (13.0%) individuals with a baseline CD4 count > 350 cells/μL in receipt of a resistance test at viral load rebound were found to have developed new resistance mutations. This compared to 107 (41.2%) of those with virological failure who had initiated cART with a CD4 count < 350 cells/μL.ConclusionsWe found no evidence of increased rates of resistance development when cART was initiated at CD4 counts above 350 cells/μL.
Lipsitch M, Donnelly CA, Fraser C, et al., 2015, Potential biases in estimating absolute and relative case-fatality risks during outbreaks, PLOS Neglected Tropical Diseases, Vol: 9, ISSN: 1935-2735
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