81 results found
Poletto C, Scarpino SV, Volz EM, 2020, Applications of predictive modelling early in the COVID-19 epidemic., The Lancet Digital Health, Vol: 2, Pages: e498-e499, ISSN: 2589-7500
Ragonnet-Cronin M, Boyd O, Geidelberg L, et al., 2020, COVID-19 epidemic severity is associated with timing of non-pharmaceutical interventions
<jats:p>Background: Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. International comparisons are hampered by highly variable conditions under which epidemics spread and differences in the timing and scale of interventions. Cumulative COVID-19 morbidity and mortality are functions of both the rate of epidemic growth and the duration of uninhibited growth before interventions were implemented. Incomplete and sporadic testing during the early COVID-19 epidemic makes it difficult to identify how long SARS-CoV-2 was circulating in different places. SARS-CoV-2 genetic sequences can be analyzed to provide an estimate of both the time of epidemic origin and the rate of early epidemic growth in different settings. Methods: We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were cross-referenced with dates of the most stringent interventions in each location as well as the number of cumulative COVID-19 deaths following maximum intervention. Phylodynamic methods were used to estimate the rate of early epidemic growth and proxy estimates of epidemic size. Findings: The time elapsed between epidemic origin and maximum intervention is strongly associated with different measures of epidemic severity and explains 46% of variance in numbers infected at time of maximum intervention. The reproduction number is independently associated with epidemic severity. In multivariable regression models, epidemic severity was not associated with census population size. The time elapsed between detection of initial COVID-19 cases to interventions was not associated with epidemic severity, indicating that many locations experienced long periods of cryptic
Volz E, Wiuf C, Grad YH, et al., 2020, Identification of hidden population structure in time-scaled phylogenies, Systematic Biology, Vol: 69, Pages: 884-896, ISSN: 1063-5157
Abstract Population structure influences genealogical patterns, however data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealised genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past, and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with th
Thompson H, Imai N, Dighe A, et al., 2020, SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China, Journal of Travel Medicine, ISSN: 1195-1982
We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%–1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.
Grassly NC, Pons-Salort M, Parker EPK, et al., 2020, Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study, Lancet Infectious Diseases, ISSN: 1473-3099
BACKGROUND: WHO has called for increased testing in response to the COVID-19 pandemic, but countries have taken different approaches and the effectiveness of alternative strategies is unknown. We aimed to investigate the potential impact of different testing and isolation strategies on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We developed a mathematical model of SARS-CoV-2 transmission based on infectiousness and PCR test sensitivity over time since infection. We estimated the reduction in the effective reproduction number (R) achieved by testing and isolating symptomatic individuals, regular screening of high-risk groups irrespective of symptoms, and quarantine of contacts of laboratory-confirmed cases identified through test-and-trace protocols. The expected effectiveness of different testing strategies was defined as the percentage reduction in R. We reviewed data on the performance of antibody tests reported by the Foundation for Innovative New Diagnostics and examined their implications for the use of so-called immunity passports. FINDINGS: If all individuals with symptoms compatible with COVID-19 self-isolated and self-isolation was 100% effective in reducing onwards transmission, self-isolation of symptomatic individuals would result in a reduction in R of 47% (95% uncertainty interval [UI] 32-55). PCR testing to identify SARS-CoV-2 infection soon after symptom onset could reduce the number of individuals needing to self-isolate, but would also reduce the effectiveness of self-isolation (around 10% would be false negatives). Weekly screening of health-care workers and other high-risk groups irrespective of symptoms by use of PCR testing is estimated to reduce their contribution to SARS-CoV-2 transmission by 23% (95% UI 16-40), on top of reductions achieved by self-isolation following symptoms, assuming results are available at 24 h. The effectiveness of test and trace depends strongly on coverage and the timelines
Flaxman S, Mishra S, Gandy A, et al., 2020, Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, Nature, Vol: 584, Pages: 257-261, ISSN: 0028-0836
Following the emergence of a novel coronavirus1 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lockdowns. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates. Our model relies on fixed estimates of some epidemiological parameters such as the infection fatality rate, does not include importation or subnational variation and assumes that changes in the reproduction number are an immediate response to interventions rather than gradual changes in behavior. Amidst the ongoing pandemic, we rely on death data that is incomplete, with systematic biases in reporting, and subject to future consolidation. We estimate that, for all the countries we consider, current interventions have been sufficient to drive the reproduction number Rt below 1 (probability Rt< 1.0 is 99.9%) and achieve epidemic control. We estimate that, across all 11 countries, between 12 and 15 million individuals have been infected with SARS-CoV-2 up to 4th May, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions and lockdown in particular have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.
Volz EM, Hill V, McCrone JT, et al., 2020, Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity
<jats:p>In February 2020 a substitution at the interface between SARS-CoV-2 Spike protein subunits, Spike D614G, was observed in public databases. The Spike 614G variant subsequently increased in frequency in many locations throughout the world. Global patterns of dispersal of Spike 614G are suggestive of a selective advantage of this variant, however the origin of Spike 614G is associated with early colonization events in Europe and subsequent radiations to the rest of the world. Increasing frequency of 614G may therefore be due to a random founder effect. We investigate the hypothesis for positive selection of Spike 614G at the level of an individual country, the United Kingdom, using more than 25,000 whole genome SARS-CoV-2 sequences collected by COVID-19 Genomics UK Consortium. Using phylogenetic analysis, we identify Spike 614G and 614D clades with unique origins in the UK and from these we extrapolate and compare growth rates of co-circulating transmission clusters. We find that Spike 614G clusters are introduced in the UK later on average than 614D clusters and grow to larger size after adjusting for time of introduction. Phylodynamic analysis does not show a significant increase in growth rates for clusters with the 614G variant, but population genetic modelling indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We also investigate the potential influence of Spike 614D versus G on virulence by matching a subset of records to clinical data on patient outcomes. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality, but younger patients have slightly increased odds of 614G carriage. Despite the availability of a very large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of higher transmission rate for 614G, but significant differences in growth, size, and composition of these lineages
Didelot X, Siveroni I, Volz EM, 2020, Additive uncorrelated relaxed clock models for the dating of genomic epidemiology phylogenies, Molecular Biology and Evolution, ISSN: 0737-4038
Phylogenetic dating is one of the most powerful and commonly used methods of drawing epidemiological interpretations from pathogen genomic data. Building such trees requires considering a molecular clock model which represents the rate at which substitutions accumulate on genomes. When the molecular clock rate is constant throughout the tree then the clock is said to be strict, but this is often not an acceptable assumption. Alternatively, relaxed clock models consider variations in the clock rate, often based on a distribution of rates for each branch. However, we show here that the distributions of rates across branches in commonly used relaxed clock models are incompatible with the biological expectation that the sum of the numbers of substitutions on two neighbouring branches should be distributed as the substitution number on a single branch of equivalent length. We call this expectation the additivity property. We further show how assumptions of commonly used relaxed clock models can lead to estimates of evolutionary rates and dates with low precision and biased confidence intervals. We therefore propose a new additive relaxed clock model where the additivity property is satisfied. We illustrate the use of our new additive relaxed clock model on a range of simulated and real datasets, and we show that using this new model leads to more accurate estimates of mean evolutionary rates and ancestral dates.
Fu H, Xi X, Wang H, et al., 2020, Report 30: The COVID-19 epidemic trends and control measures in mainland China
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Estimating the number of undetected COVID-19 cases among travellers from mainland China, Publisher: F1000 Research Ltd
Background: Since the start of the COVID-19 epidemic in late 2019, there have been more than 152 affected regions and countries with over 110,000 confirmed cases outside mainland China.Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries.Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that more than two thirds (70%, 95% CI: 54% - 80%, compared to Singapore; 75%, 95% CI: 66% - 82%, compared to multiple countries) of cases exported from mainland China have remained undetected.Conclusions: These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.
Nouvellet P, Bhatia S, Cori A, et al., 2020, Report 26: Reduction in mobility and COVID-19 transmission
In response to the COVID-19 pandemic, countries have sought to control transmission of SARS-CoV-2by restricting population movement through social distancing interventions, reducing the number ofcontacts.Mobility data represent an important proxy measure of social distancing. Here, we develop aframework to infer the relationship between mobility and the key measure of population-level diseasetransmission, the reproduction number (R). The framework is applied to 53 countries with sustainedSARS-CoV-2 transmission based on two distinct country-specific automated measures of humanmobility, Apple and Google mobility data.For both datasets, the relationship between mobility and transmission was consistent within andacross countries and explained more than 85% of the variance in the observed variation intransmissibility. We quantified country-specific mobility thresholds defined as the reduction inmobility necessary to expect a decline in new infections (R<1).While social contacts were sufficiently reduced in France, Spain and the United Kingdom to controlCOVID-19 as of the 10th of May, we find that enhanced control measures are still warranted for themajority of countries. We found encouraging early evidence of some decoupling of transmission andmobility in 10 countries, a key indicator of successful easing of social-distancing restrictions.Easing social-distancing restrictions should be considered very carefully, as small increases in contactrates are likely to risk resurgence even where COVID-19 is apparently under control. Overall, strongpopulation-wide social-distancing measures are effective to control COVID-19; however gradualeasing of restrictions must be accompanied by alternative interventions, such as efficient contacttracing, to ensure control.
Verity R, Okell LC, Dorigatti I, et al., 2020, Estimates of the severity of coronavirus disease 2019: a model-based analysis., Lancet Infectious Diseases, Vol: 20, Pages: 669-677, ISSN: 1473-3099
BACKGROUND: In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. METHODS: We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. FINDINGS: Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for cen
Grassly N, Pons Salort M, Parker E, et al., 2020, Report 16: Role of testing in COVID-19 control
The World Health Organization has called for increased molecular testing in response to the COVID-19 pandemic, but different countries have taken very different approaches. We used a simple mathematical model to investigate the potential effectiveness of alternative testing strategies for COVID-19 control. Weekly screening of healthcare workers (HCWs) and other at-risk groups using PCR or point-of-care tests for infection irrespective of symptoms is estimated to reduce their contribution to transmission by 25-33%, on top of reductions achieved by self-isolation following symptoms. Widespread PCR testing in the general population is unlikely to limit transmission more than contact-tracing and quarantine based on symptoms alone, but could allow earlier release of contacts from quarantine. Immunity passports based on tests for antibody or infection could support return to work but face significant technical, legal and ethical challenges. Testing is essential for pandemic surveillance but its direct contribution to the prevention of transmission is likely to be limited to patients, HCWs and other high-risk groups.
Flaxman S, Mishra S, Gandy A, et al., 2020, Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries
Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe is now experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. One of the key assumptions of the model is that each intervention has the same effect on the reproduction number across countries and over time. This allows us to leverage a greater amount of data across Europe to estimate these effects. It also means that our results are driven strongly by the data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain. We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact of interventions implemented several weeks earlier. In Italy, we estimate that the effective reproduction number, Rt, dropped to close to 1 around the time of lockdown (11th March), although with a high level of uncertainty. Overall, we estimate that countries have managed to reduce their reproduction number. Our estimates have wide credible intervals and contain 1 for countries that have implemented all interventions considered in our analysis. This means that the reproducti
Ferguson N, Laydon D, Nedjati Gilani G, et al., 2020, Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally requi
Gaythorpe K, Imai N, Cuomo-Dannenburg G, et al., 2020, Report 8: Symptom progression of COVID-19
The COVID-19 epidemic was declared a Public Health Emergency of International Concern (PHEIC) by WHO on 30th January 2020 . As of 8 March 2020, over 107,000 cases had been reported. Here, we use published and preprint studies of clinical characteristics of cases in mainland China as well as case studies of individuals from Hong Kong, Japan, Singapore and South Korea to examine the proportional occurrence of symptoms and the progression of symptoms through time.We find that in mainland China, where specific symptoms or disease presentation are reported, pneumonia is the most frequently mentioned, see figure 1. We found a more varied spectrum of severity in cases outside mainland China. In Hong Kong, Japan, Singapore and South Korea, fever was the most frequently reported symptom. In this latter group, presentation with pneumonia is not reported as frequently although it is more common in individuals over 60 years old. The average time from reported onset of first symptoms to the occurrence of specific symptoms or disease presentation, such as pneumonia or the use of mechanical ventilation, varied substantially. The average time to presentation with pneumonia is 5.88 days, and may be linked to testing at hospitalisation; fever is often reported at onset (where the mean time to develop fever is 0.77 days).
Thompson H, Imai N, Dighe A, et al., 2020, Report 7: Estimating infection prevalence in Wuhan City from repatriation flights
Since the end of January 2020, in response to the growing COVID-19 epidemic, 55 countries have repatriated over 8000 citizens from Wuhan City, China. In addition to quarantine measures for returning citizens, many countries implemented PCR screening to test for infection regardless of symptoms. These flights therefore give estimates of infection prevalence in Wuhan over time. Between 30th January and 1st February (close to the peak of the epidemic in Wuhan), infection prevalence was 0.87% (95% CI: 0.32% - 1.89%). As countries now start to repatriate citizens from Iran and northern Italy, information from repatriated citizens could help inform the level of response necessary to help control the outbreaks unfolding in newly affected areas.
Nascimento FF, Baral S, Geidelberg L, et al., 2020, Phylodynamic analysis of HIV-1 subtypes B, C and CRF 02_AG in Senegal, EPIDEMICS, Vol: 30, ISSN: 1755-4365
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Report 6: Relative sensitivity of international surveillance, Report 6: Relative sensitivity of international surveillance
Since the start of the COVID-19 epidemic in late 2019, there are now 29 affected countries with over 1000 confirmed cases outside of mainland China. In previous reports, we estimated the likely epidemic size in Wuhan City based on air traffic volumes and the number of detected cases internationally. Here we analysed COVID-19 cases exported from mainland China to different regions and countries, comparing the country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different countries. Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that about two thirds of COVID-19 cases exported from mainland China have remained undetected worldwide, potentially resulting in multiple chains of as yet undetected human-to-human transmission outside mainland China.
Volz E, Baguelin M, Bhatia S, et al., 2020, Report 5: Phylogenetic analysis of SARS-CoV-2
Genetic diversity of SARS-CoV-2 (formerly 2019-nCoV), the virus which causes COVID-19, provides information about epidemic origins and the rate of epidemic growth. By analysing 53 SARS-CoV-2 whole genome sequences collected up to February 3, 2020, we find a strong association between the time of sample collection and accumulation of genetic diversity. Bayesian and maximum likelihood phylogenetic methods indicate that the virus was introduced into the human population in early December and has an epidemic doubling time of approximately seven days. Phylodynamic modelling provides an estimate of epidemic size through time. Precise estimates of epidemic size are not possible with current genetic data, but our analyses indicate evidence of substantial heterogeneity in the number of secondary infections caused by each case, as indicated by a high level of over-dispersion in the reproduction number. Larger numbers of more systematically sampled sequences – particularly from across China – will allow phylogenetic estimates of epidemic size and growth rate to be substantially refined.
Dorigatti I, Okell L, Cori A, et al., 2020, Report 4: Severity of 2019-novel coronavirus (nCoV)
We present case fatality ratio (CFR) estimates for three strata of 2019-nCoV infections. For cases detected in Hubei, we estimate the CFR to be 18% (95% credible interval: 11%-81%). For cases detected in travellers outside mainland China, we obtain central estimates of the CFR in the range 1.2-5.6% depending on the statistical methods, with substantial uncertainty around these central values. Using estimates of underlying infection prevalence in Wuhan at the end of January derived from testing of passengers on repatriation flights to Japan and Germany, we adjusted the estimates of CFR from either the early epidemic in Hubei Province, or from cases reported outside mainland China, to obtain estimates of the overall CFR in all infections (asymptomatic or symptomatic) of approximately 1% (95% confidence interval 0.5%-4%). It is important to note that the differences in these estimates does not reflect underlying differences in disease severity between countries. CFRs seen in individual countries will vary depending on the sensitivity of different surveillance systems to detect cases of differing levels of severity and the clinical care offered to severely ill cases. All CFR estimates should be viewed cautiously at the current time as the sensitivity of surveillance of both deaths and cases in mainland China is unclear. Furthermore, all estimates rely on limited data on the typical time intervals from symptom onset to death or recovery which influences the CFR estimates.
Li Y, Liu H, Ramadhani HO, et al., 2020, Genetic clustering analysis for HIV infection among MSM in Nigeriaimplications for intervention, AIDS, Vol: 34, Pages: 227-236, ISSN: 0269-9370
BACKGROUND: The HIV epidemic continues to grow among MSM in countries across sub-Saharan Africa including Nigeria. To inform prevention efforts, we used a phylogenetic cluster method to characterize HIV genetic clusters and factors associated with cluster formation among MSM living with HIV in Nigeria. METHODS: We analyzed HIV-1 pol sequences from 417 MSM living with HIV enrolled in the TRUST/RV368 cohort between 2013 and 2017 in Abuja and Lagos, Nigeria. A genetically linked cluster was defined among participants whose sequences had pairwise genetic distance of 1.5% or less. Binary and multinomial logistic regressions were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with HIV genetic cluster membership and size. RESULTS: Among 417 MSM living with HIV, 153 (36.7%) were genetically linked. Participants with higher viral load (AOR = 1.72 95% CI: 1.04-2.86), no female partners (AOR = 3.66; 95% CI: 1.97-6.08), and self-identified as male sex (compared with self-identified as bigender) (AOR = 3.42; 95% CI: 1.08-10.78) had higher odds of being in a genetic cluster. Compared with unlinked participants, MSM who had high school education (AOR = 23.84; 95% CI: 2.66-213.49), were employed (AOR = 3.41; 95% CI: 1.89-10.70), had bacterial sexually transmitted infections (AOR = 3.98; 95% CI: 0.89-17.22) and were not taking antiretroviral therapy (AOR = 6.61; 95% CI: 2.25-19.37) had higher odds of being in a large cluster (size > 4). CONCLUSION: Comprehensive HIV prevention packages should include behavioral and biological components, including early diagnosis and treatment of both HIV and bacterial sexually transmitted infections to optimally reduce the risk of HIV transmission and acquisition.
Le Vu S, Ratmann O, Delpech V, et al., 2019, HIV-1 transmission patterns in men who have sex with men: insights from genetic source attribution analysis, AIDS Research and Human Retroviruses, Vol: 39, Pages: 805-813, ISSN: 0889-2229
BACKGROUND: Near 60% of new HIV infections in the United Kingdom are estimated to occur in men who have sex with men (MSM). Age-disassortative partnerships in MSM have been suggested to spread the HIV epidemics in many Western developed countries and to contribute to ethnic disparities in infection rates. Understanding these mixing patterns in transmission can help to determine which groups are at a greater risk and guide public health interventions. METHODS: We analyzed combined epidemiologic data and viral sequences from MSM diagnosed with HIV at the national level. We applied a phylodynamic source attribution model to infer patterns of transmission between groups of patients. RESULTS: From pair probabilities of transmission between 14 603 MSM patients, we found that potential transmitters of HIV subtype B were on average 8 months older than recipients. We also found a moderate overall assortativity of transmission by ethnic group and a stronger assortativity by region. CONCLUSIONS: Our findings suggest that there is only a modest net flow of transmissions from older to young MSM in subtype B epidemics and that young MSM, both for Black or White groups, are more likely to be infected by one another than expected in a sexual network with random mixing.
Volz EM, Wiuf C, Grad YH, et al., 2019, Identification of hidden population structure in time-scaled phylogenies, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>Population structure influences genealogical patterns, however data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealised genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial <jats:italic>pol</jats:italic> sequences. This revealed the presence of clades which had grown rapidly in the recent past, and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome <jats:italic>Neisseria go
Volz EM, Siveroni I, 2018, Bayesian phylodynamic inference with complex models, PLoS Computational Biology, Vol: 14, ISSN: 1553-734X
Population genetic modeling can enhance Bayesian phylogenetic inference by providing a realistic prior on the distribution of branch lengths and times of common ancestry. The parameters of a population genetic model may also have intrinsic importance, and simultaneous estimation of a phylogeny and model parameters has enabled phylodynamic inference of population growth rates, reproduction numbers, and effective population size through time. Phylodynamic inference based on pathogen genetic sequence data has emerged as useful supplement to epidemic surveillance, however commonly-used mechanistic models that are typically fitted to non-genetic surveillance data are rarely fitted to pathogen genetic data due to a dearth of software tools, and the theory required to conduct such inference has been developed only recently. We present a framework for coalescent-based phylogenetic and phylodynamic inference which enables highly-flexible modeling of demographic and epidemiological processes. This approach builds upon previous structured coalescent approaches and includes enhancements for computational speed, accuracy, and stability. A flexible markup language is described for translating parametric demographic or epidemiological models into a structured coalescent model enabling simultaneous estimation of demographic or epidemiological parameters and time-scaled phylogenies. We demonstrate the utility of these approaches by fitting compartmental epidemiological models to Ebola virus and Influenza A virus sequence data, demonstrating how important features of these epidemics, such as the reproduction number and epidemic curves, can be gleaned from genetic data. These approaches are provided as an open-source package PhyDyn for the BEAST2 phylogenetics platform.
Dennis AM, Volz E, Frost SDW, et al., 2018, HIV-1 transmission clustering and phylodynamics highlight the important role of young men who have sex with men, AIDS Research and Human Retroviruses, Vol: 34, Pages: 879-888, ISSN: 0889-2229
More persons living with HIV reside in the Southern United States than in any other region, yet little is known about HIV molecular epidemiology in the South. We used cluster and phylodynamic analyses to evaluate HIV transmission patterns in middle Tennessee. We performed cross-sectional analyses of HIV-1 pol sequences and clinical data collected from 2001 to 2015 among persons attending the Vanderbilt Comprehensive Care Clinic. Transmission clusters were identified using maximum likelihood phylogenetics and patristic distance differences. Demographic, risk behavior, and clinical factors were assessed evaluating “active” clusters (clusters including sequences sampled 2011–2015) and associations estimated with logistic regression. Transmission risk ratios for men who have sex with men (MSM) were estimated with phylodynamic models. Among 2915 persons (96% subtype-B sequences), 963 (33%) were members of 292 clusters (distance ≤1.5%, size range 2–39). Most clusters (62%, n = 690 persons) were active, either being newly identified (n = 80) or showing expansion on existing clusters (n = 101). Correlates of active clustering among persons with sequences collected during 2011–2015 included MSM risk and ≤30 years of age. Active clusters were significantly more concentrated in MSM and younger persons than historical clusters. Young MSM (YMSM) (≤26.4 years) had high estimated transmission risk [risk ratio = 4.04 (2.85–5.65) relative to older MSM] and were much more likely to transmit to YMSM. In this Tennessee cohort, transmission clusters over time were more concentrated by MSM and younger age, with high transmission risk among and between YMSM, highlighting the importance of interventions among this group. Detecting active clusters could help direct interventions to disrupt ongoing transmission chains.
Mukandavire C, Walker J, Schwartz S, et al., 2018, Estimating the contribution of key populations towards spread of HIV in Dakar, Senegal, Journal of the International AIDS Society, Vol: 21, ISSN: 1758-2652
IntroductionKey populations including female sex workers (FSW) and men who have sex with men (MSM) bear a disproportionate burden of HIV. However, the role of focusing prevention efforts on these groups for reducing a country’s HIV epidemic is debated. We estimate the extent to which HIV transmission amongst FSW and MSM contributes to overall HIV transmission in Dakar, Senegal, using a dynamic assessment of the population attributable fraction (PAF).MethodsA dynamic transmission model of HIV among FSW, their clients, MSM and the lower-risk adult population was parameterized and calibrated within a Bayesian framework using setting-specific demographic, behavioural, HIV epidemiological, and antiretroviral treatment (ART) coverage data for 1985-2015. We used the model to estimate the 10-year PAF of commercial sex between FSW and their clients, and sex between men, to overall HIV transmission (defined as the percentage of new infections prevented when these modes of transmission are removed). Additionally, we estimated the prevention benefits associated with historical increases in condom use and ART uptake, and impact of further increases in prevention and treatment.ResultsThe model projections suggest that unprotected sex between men contributed to 42% (2.5 to 97.5th percentile range 24-59%) of transmissions between 1995-2005, increasing to 64% (37-79%) from 2015-2025. The 10-year PAF of commercial sex is smaller, diminishing from 21% (7-39%) in 1995 to 14% (5-35%) in 2015. Without ART, 49% (32-71%) more HIV infections would have occurred since 2000, when ART was initiated, whereas without condom use since 1985, 67% (27-179%) more HIV infections would have occurred, and the overall HIV prevalence would have been 60% (29-211%) greater than what it is now. Further large decreases in HIV incidence (68%) can be achieved by scaling up ART in MSM to 74% coverage and reducing their susceptibility to HIV by a two-thirds through any prevention modality.ConclusionsUnprote
Volz E, Didelot X, 2018, Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance, Systematic Biology, Vol: 67, Pages: 719-728, ISSN: 1063-5157
Nonparametric population genetic modeling provides a simple and flexible approach for studying demographic history and epidemic dynamics using pathogen sequence data. Existing Bayesian approaches are premised on stochastic processes with stationary increments which may provide an unrealistic prior for epidemic histories which feature extended period of exponential growth or decline. We show that nonparametric models defined in terms of the growth rate of the effective population size can provide a more realistic prior for epidemic history. We propose a nonparametric autoregressive model on the growth rate as a prior for effective population size, which corresponds to the dynamics expected under many epidemic situations. We demonstrate the use of this model within a Bayesian phylodynamic inference framework. Our method correctly reconstructs trends of epidemic growth and decline from pathogen genealogies even when genealogical data are sparse and conventional skyline estimators erroneously predict stable population size. We also propose a regression approach for relating growth rates of pathogen effective population size and time-varying variables that may impact the replicative fitness of a pathogen. The model is applied to real data from rabies virus and Staphylococcus aureus epidemics. We find a close correspondence between the estimated growth rates of a lineage of methicillin-resistant S. aureus and population-level prescription rates ofβ-lactam antibiotics. The new models are implemented in an open source R package called skygrowth which is available at https://github.com/mrc-ide/skygrowth.
Le Vu S, Ratmann O, Delpech V, et al., 2018, Mixing patterns of HIV transmission among men who have sex with men in the United Kingdom, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Near 60% of new HIV infections in the United Kingdom are estimated to occur in men who have sex with men (MSM). Patterns of mixing between different risk groups of MSM have been suggested to spread the HIV epidemics through age-disassortative partnerships and to contribute to ethnic disparities in infection rates. Understanding these mixing patterns in transmission can help to determine which groups are at a greater risk and guide prevention.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We analyzed combined epidemiologic data and viral sequences from MSM diagnosed with HIV as of mid-2015 at the national level. We applied a phylodynamic source attribution model to infer patterns of transmission between groups of patients by age, ethnicity and region.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>From pair probabilities of transmission between 19 847 MSM patients, we found that potential transmitters of HIV subtype B were on average 5 months older than recipients. We also found a moderate overall assortativity of transmission by ethnic group and a stronger assortativity by region.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our findings suggest that there is only a modest net flow of transmissions from older to young MSM in subtype B epidemics and that young MSM, both for Black or White groups, are more likely to be infected by one another than expected in a sexual network with random mixing.</jats:p></jats:sec>
Le Vu SOK, Ratmann O, Delpech V, et al., 2018, Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases, Epidemics, Vol: 23, Pages: 1-10, ISSN: 1755-4365
Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission.A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors.We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors.
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