Phylodynamic analysis to inform prevention efforts in mixed HIV epidemics

Volz, Erik; Ndembi, Nicaise; Nowak, Rebecca G.; Kijak, Gustavo H.; Idoko, John; Dakum, Patrick; Royal, Walter; Baral, Stefan; Dybul, Mark; Blattner, William A.; Charurat, Man

doi:10.1093/ve/vex014

Cited by 24 publications

(26 citation statements)

References 33 publications

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“…Previous analyses have shown a large role for commercial sex in some sub‐Saharan HIV epidemics , but this is the first to suggest that MSM, including individuals who identify as cis‐male and TGW, could also be having an important role in some lower‐ and middle‐income country settings, where other analyses have suggested a small role . This is likely due to the different behavioural and epidemiological situation among MSM in Dakar compared to these other settings.…”

Section: Discussionmentioning

confidence: 99%

“…These analyses challenge the conventional wisdom and existing epidemiological tools such as the MOT model. In contrast, two recent studies for Nigeria and Cote d'Ivoire suggest MSM contribute little (<10%) to these HIV epidemics [14,15]. This is despite MSM experiencing a high HIV burden [4,16,17] and engaging in sexual partnerships with women, so contributing bridging infections to the wider population [18].…”

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confidence: 97%

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Estimating the contribution of key populations towards the spread ofHIVin Dakar, Senegal

et al. 2018

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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 among 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 to 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). In addition, 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 to 59%) of transmissions between 1995 and 2005, increasing to 64% (37 to 79%) from 2015 to 2025. The 10‐year PAF of commercial sex is smaller, diminishing from 21% (7 to 39%) in 1995 to 14% (5 to 35%) in 2015. Without ART, 49% (32 to 71%) more HIV infections would have occurred since 2000, when ART was initiated, whereas without condom use since 1985, 67% (27 to 179%) more HIV infections would have occurred, and the overall HIV prevalence would have been 60% (29 to 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 two‐thirds through any prevention modality.ConclusionsUnprotected sex between men may be an important contributor to HIV transmission in Dakar, due to suboptimal coverage of evidence‐informed interventions. Although existing interventions have effectively reduced HIV transmission among adults, it is crucial that further strategies address the unmet need among MSM.

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Estimating the contribution of key populations towards the spread ofHIVin Dakar, Senegal

et al. 2018

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“…This figure increased to 5.8% by 2001 (2.6 million), before declining to 2.8% in 2017 (3.1 million) 2,16 . Previous reports have identified subtype G and the CRF02_AG as the most common HIV-1 variants in Nigeria [17][18][19][20] . In addition, the CRF43_02G was recently shown to be highly prevalent in the capital Abuja 21 .…”

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confidence: 96%

“…In addition, the CRF43_02G was recently shown to be highly prevalent in the capital Abuja 21 . However, the estimates of each strain's contribution to the Nigerian HIV-1 epidemic have varied considerably, with frequency estimates ranging from 22-50% for subtype G, and 19-60% for the CRF02_AG [18][19][20][21][22][23][24][25] . These variations could have several reasons, Recombination analysis.…”

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Characterisation of HIV-1 Molecular Epidemiology in Nigeria: Origin, Diversity, Demography and Geographic Spread

Nazziwa

Faria

Chaplin

et al. 2020

Sci Rep

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Nigeria has the highest number of AIDS-related deaths in the world. In this study, we characterised the HIV-1 molecular epidemiology by analysing 1442 HIV-1 pol sequences collected 1999-2014 from four geopolitical zones in Nigeria using state-of-the-art maximum-likelihood and Bayesian phylogenetic analyses. The main circulating forms were the circulating recombinant form (CRF) 02_AG (44% of the analysed sequences), CRF43_02G (16%), and subtype G (8%). Twenty-three percent of the sequences represented unique recombinant forms (URFs), whereof 37 (11%) could be grouped into seven potentially novel CRFs. Bayesian phylodynamic analysis suggested that five major Nigerian HIV-1 subepidemics were introduced in the 1960s and 1970s, close to the Nigerian Civil War. The analysis also indicated that the number of effective infections decreased in Nigeria after the introduction of free antiretroviral treatment in 2006. Finally, Bayesian phylogeographic analysis suggested gravity-like dynamics in which virus lineages first emerge and expand within large urban centers such as Abuja and Lagos, before migrating towards smaller rural areas. This study provides novel insight into the Nigerian HIV-1 epidemic and may have implications for future HIV-1 prevention strategies in Nigeria and other severely affected countries.

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“…The PhyDyn package model markup language requires specifying the non-zero 80 elements of F (t), G(t) and µ(t). There are multiple published examples of simple 81 compartmental models developed in this framework [18][19][20][21][22][23]. In the following sections, 82 we give examples of simple compartmental models related to infectious diease dynamics 83 and show how these models can be defined within this framework.…”

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Bayesian phylodynamic inference with complex models

Volz

Siveroni

2018

Preprint

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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 BEAST phylogenetics platform. Introduction 1 Mechanistic models guided by expert knowledge can form an efficient prior on epidemic 2 history when conducting phylodynamic inference with genetic data [1]. Parameters 3 estimated by fitting mechanistic models, such as the reproduction number R 0 , are 4 important for epidemic surveillance and forecasting. Compartmental models defined in 5 terms of ordinary or stochastic differential equations are the most common type of 6 mathematical infectious disease model, but in the area of phylodynamic inference, 7 non-parametric approaches based on skyline coalescent models [2] or 8 sampling-birth-death models [3] are more commonly used. Methods to translate 9compartmental infectious disease models into a population genetic framework have been 10 developed only recently [4][5][6][7][8]. We address the gap in software tools for epidemic 11 modeling and phylogenetic inference by developing a BEAST package, PhyDyn, which 12 includes a highly-flexible mark-up language for defining compartmental infectious 13 1/17 disease models in terms of ordinary differential equations. This flexible framework 14 enables phylodynamic inference with the majority of published compartmental models, 15 such as the common susceptible-infected-removed (SIR) model [9] and its variants, ...

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Phylodynamic analysis to inform prevention efforts in mixed HIV epidemics

Cited by 24 publications

References 33 publications

Estimating the contribution of key populations towards the spread ofHIVin Dakar, Senegal

Estimating the contribution of key populations towards the spread ofHIVin Dakar, Senegal

Characterisation of HIV-1 Molecular Epidemiology in Nigeria: Origin, Diversity, Demography and Geographic Spread

Bayesian phylodynamic inference with complex models

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