Epidemiology and Social
Spatiotemporal dynamics of the HIV-1 CRF06_cpx epidemic in western Africa
Delatorre, Edson; Bello, Gonzalo
Laboratório de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil.
Correspondence to Gonzalo Bello, Laboratório de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ. Av. Brasil 4365, 21045-900 Rio de Janeiro, RJ, Brazil. Tel: +55 21 3865 8154; fax: +55 21 3865 8173; e-mail: email@example.comfirstname.lastname@example.org
Received 14 November, 2012
Revised 20 December, 2012
Accepted 17 January, 2013
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Objective: To investigate the origin and spatiotemporal dynamics of dissemination of the HIV-1 CRF06_cpx clade in western Africa.
Design: A total of 180 HIV-1 CRF06_cpx-like pol sequences isolated from 12 different countries from west and west-central Africa over a period of 16 years (1995–2010) were analyzed.
Methods: Evolutionary, phylogeographic and demographic parameters were jointly estimated from sequence data using a Bayesian coalescent-based method and combined with molecular epidemiology and spatial accessibility data.
Results: The CRF06_cpx most probably emerged in Burkina Faso in 1979 (1970–1985). From Burkina Faso, the virus was first disseminated to Mali and Nigeria during the 1980s and later to other countries from west and west-central Africa. Demographic reconstruction indicates that the CRF06_cpx epidemic grew exponentially during the 1980s, with a median growth rate of 0.82 year−1 (0.60–1.09 year−1), and after stabilize. We found a negative correlation between CRF06_cpx prevalence and the geographical distance to Burkina Faso's capital. Regional accessibility information agrees with the overall geographical range of the CRF06_cpx, but not fully explains the highly heterogeneous distribution pattern of this CRF at regional level.
Conclusion: The CRF06_cpx epidemic in western Africa probably emerged at the late 1970s and grew during the 1980s at a rate comparable to the HIV-1 epidemics in the United States and Europe. Burkina Faso seems to be the most important epicenter of dissemination of the HIV-1 CRF06_cpx strain at regional level. The explanation for the current geographical distribution of CRF06_cpx is probably multifactorial.
The dispersion of some human immunodeficiency virus type 1 (HIV-1) group M strains out of the epicenter in Central Africa has given rise to a diverse collection of viral lineages with a complex global distribution, that we know today as subtypes and inter-subtype recombinant forms. The HIV-1 circulating recombinant forms (CRFs) and unique recombinants forms have an epidemiologically relevant contribution to the HIV-1 epidemic being responsible for over 20% of all global infections . Importantly, the global proportion of all CRFs combined increased by 4.5% between 2000–2003 and 2004–2007 .
The CRF06_cpx is a complex recombinant that includes genomic segments of subtypes A, G, J, and K . This CRF mainly circulates in western Africa, although its occurrence greatly varies across countries. The CRF06_cpx is the predominant clade in Burkina Faso where it accounts for 40–50% of HIV-1 infections [3–5], whereas its prevalence is reduced to 10–15% in Mali [6,7] and Niger [8,9], 3–8% in Benin , Ghana [11,12], Côte d’Ivoire [13,14], Nigeria , Senegal [16,17], and Togo [18,19], and 1% or less in Guinea Bissau  and Guinea Conakry . This CRF has also been occasionally detected in several west-central African countries including: Cameroon, Central African Republic (CAR), Chad, Equatorial Guinea and Gabon .
Bayesian phylogeographic models has been successfully used to reconstruct the spatial and temporal dispersion pattern of different HIV-1 clades at a regional level in the African continent, including the subtypes A, C and D in East Africa [22,23] and the CRF02_AG in the Congo River basin . Despite extensive data about molecular epidemiology, the spatiotemporal dynamics of dissemination of most prevalent HIV-1 lineages circulating in western Africa remains largely unexplored. Previous studies have reconstructed the migration routes and population dynamics of some HIV-1 clades in west Africa at a country scale, such as the CRF02_AG clade in Guinea Bissau  and the subtype C clade in Senegal ; but none has explored the dissemination dynamics of HIV-1 at a regional level.
In the present study, we used a comprehensive data set of 180 HIV-1 CRF06_cpx-like pol sequences isolated from 12 different countries from west and west-central Africa over a period of 16 years (1995–2010). Spatial and temporal information of sequences was combined with Bayesian analyses to reconstruct simultaneously the onset date, the migration routes and the demographic history of the HIV-1 CRF06_cpx epidemic at a regional scale.
A total of 207 HIV-1 CRF06_cpx pol sequences from different patients of African origin covering the entire protease and partial reverse transcriptase (PR/RT) regions (nt 2253-3272 relative to HXB2 clone) were downloaded from the Los Alamos HIV Sequence Database (www.hiv.lanl.gov) by July 2012. Five sequences with a mosaic profile different to the CRF06_cpx reference sequences and 22 sequences with no information about sampling date were removed. This resulted in a final data set of 180 CRF06_cpx-like pol sequences from west (n = 174) and west-central (n = 6) Africa sampled over a period of 16 years (Table S1, http://links.lww.com/QAD/A311). Sequences were aligned and all sites with major antiretroviral drug resistance mutations in RT (41, 65, 67, 69, 70, 74, 101, 103, 106, 138, 151, 181, 184, 188, 190, 210, 215 and 219) detected in at least two sequences were excluded. Alignment is available from the authors upon request.
The CRF06_cpx-like classification of all pol sequences here included was confirmed by: maximum likelihood phylogenetic analysis, REGA HIV subtyping tool v.2 , and bootscanning analysis using Simplot software v.3.5.1 . The maximum likelihood phylogenetic tree was constructed with the PhyML 3.0 program  using an online web server (http://www.atgc-montpellier.fr/phyml/). The maximum likelihood tree was inferred under the GTR+I+G nucleotide substitution model selected using the jModeltest program , and the heuristic tree search was performed using the SPR branch-swapping algorithm. The approximate likelihood-ratio test based on a Shimodaira-Hasegawa-like procedure was used as a statistical test to calculate branch support. In bootscanning analyses, supporting branching of query sequences with reference sequences from all HIV-1 group M subtypes was determined in Neighbor-Joining trees constructed using the Kimura two-parameter model, within a 250 bp window moving in steps of 10 bases.
Analysis of the spatiotemporal dispersion pattern
The evolutionary rate (μ, nucleotide substitutions per site per year, subst./site per year), the age of the most recent common ancestor (Tmrca, years), the demographic history, and the spatial dynamics of CRF06_cpx circulating in west and west-central Africa were jointly estimated using the Bayesian Markov Chain Monte Carlo (MCMC) approach as implemented in BEAST v1.6.2 . Analyses were performed using the GTR+I+Γ4 nucleotide substitution model and an uncorrelated Lognormal relaxed molecular clock model  under different coalescent models. Migration events throughout the phylogenetic histories and the most relevant migration pathways between locations were identified by applying a standard discrete Bayesian phylogeographic model and the Bayesian stochastic search variable selection (BSSVS) approach , respectively. MCMC chains were run for 5 × 108 generations and adequate chain mixing was checked, after excluding an initial 10%, by calculating the effective sample size using the TRACER v1.4 program (http://beast.bio.ed.ac.uk/Tracer). Maximum clade credibility (MCC) trees were summarized from the posterior distribution of trees with TreeAnnotator and visualized with FigTree v1.3.1 (http://tree.bio.ed.ac.uk/software/figtree). Migratory events and significant nonzero rates obtained by the BSSVS approach were summarized using the cross-platform SPREAD application  and viewed with Google Earth (http://earth.google.com).
The correlation between CRF06_cpx prevalence in each country and the corresponding geographical distance from the country's capital to the Burkina Faso's capital was examined using different regression models. The model with the better fit to the data (higher R2 value) was selected. Statistical calculations were done using the GraphPad Prism version 2.01 program (GraphPad Software, San Diego, California, USA).
Origin of the HIV-1 CRF06_cpx clade
In the present study we used a dataset of 180 CRF06_cpx-like pol sequences isolated from 12 different countries from west and west-Central Africa between 1995 and 2010 (Table S1, http://links.lww.com/QAD/A311). Most (76%) CRF06_cpx-like pol sequences were retrieved from untreated patients (Table S1, http://links.lww.com/QAD/A311). All pol sequences here included branched in a highly supported monophyletic clade and displayed the same G/K mosaic structure that the CRF06_cpx reference sequences (Fig. S1, http://links.lww.com/QAD/A311), thus, confirming their original classification. Importantly, our dataset includes sequences from all African countries with description of CRF06_cpx infections at a prevalence more than 1%, with exception of Niger for which no sequence data for the selected pol gene segment was available in public databases.
The median evolutionary rate of the HIV-1 CRF06_cpx lineage at pol gene directly calculated from the sampling dates of the sequences was estimated at 2.4 × 10−3 (95% HPD: 1.8 × 10−3 – 3.0 × 10−3) subst./site per year, consistent with the order of magnitude of 10−3 expected for HIV-1. The estimated coefficient of rate variation in our dataset was 0.28 (95% HPD: 0.22–0.33). This demonstrates a significant variation of substitution rate among branches and validates the use of a relaxed molecular clock model to reconstruct the time-scale of the CRF06_cpx clade. According to the Bayesian MCMC analysis, the most probable root location of the CRF06_cpx clade was placed in Burkina Faso (posterior state probability, PSP = 0.94), and the onset date of this clade was estimated to be 1979 (95% HPD: 1970–1985) (Fig. 1).
Spatiotemporal dispersal pattern of the HIV-1 CRF06_cpx clade
The spatiotemporal dynamics of CRF06_cpx was reconstructed using a Bayesian phylogeographic diffusion model that takes into account the uncertainty both at the phylogenetic and the viral migration level. The Bayesian MCC tree points to a great level of phylogenetic intermixing of CRF06_cpx sequences from different geographic locations and supports that Burkina Faso, where CRF06_cpx is dominant, has been the epicenter from where this viral strain has spread to neighboring countries (Fig. 1). This analysis identified some highly supported (posterior probability, PP >0.90) country-specific monophyletic clades of small size (n ≤5) in Benin, Chad, Côte d’Ivoire, Mali, Nigeria and Senegal (Fig. 1). A large (n = 9) country-specific monophyletic clade was also detected in Mali, but received low support (PP <0.50).
Reconstruction of viral migrations across time revealed a rapid dissemination of CRF06_cpx across West Africa (Fig. 2). After its emergence in Burkina Faso around the late 1970s, the virus was first disseminated to Mali between 1980 and 1985 and later to Nigeria between 1985 and 1990. During the 1990s the virus migrated from Burkina Faso to southern neighboring countries including Benin, Ghana and Côte d’Ivoire, and also to more distant countries like Chad and Senegal. In more recent times, migrations of the CRF06_cpx clade were detected from Burkina Faso to Togo and west-equatorial African countries (Cameroon, Gabon and Equatorial Guinea). The Bayes factor tests for significant nonzero rates, only supports epidemiological linkage between Burkina Faso and Mali (Bayes factor = 6426), Burkina Faso and Nigeria (Bayes factor = 180), and Burkina Faso and Ghana (Bayes factor = 11) (Fig. 2).
Spatial accessibility and the spread of the HIV-1 CRF06_cpx clade
To better characterize the spatial spread of the HIV-1 CRF06_cpx clade at a regional level, the geographical distribution of CRF06_cpx was superimposed to accessibility data reflecting the travel time to major cities (>50 000 people) (http://bioval.jrc.ec.europa.eu/products/gam/index.htm). Inspection of the African accessibility map revealed that western region is well connected and accessible, and that such a corridor of connectivity also extends to some countries from the central region (Cameroon, CAR, Chad, Equatorial Guinea and Gabon) where the CRF06_cpx has been detected (Fig. S2, http://links.lww.com/QAD/A311). Despite this high interconnectivity of west and west-central African populations, molecular epidemiology data reveals a great variation of the CRF06_cpx prevalence at regional level, ranging from less than 1 to more than 40% (Fig. 3). We found that such prevalence was negatively correlated with the geographical distance to the capital of Burkina Faso (Ouagadougou). As we move away from Ouagadougou the prevalence of CRF06_cpx rapidly decreases following an exponential decay curve (Fig. 3).
Demographic history of the HIV-1 CRF06_cpx clade
To reconstruct the population dynamic pattern of the HIV-1 CRF06_cpx clade, estimate of effective population size (Ne) over time was obtained using a Bayesian skyline plot (BSP) coalescent model. The BSP analysis suggests that the CRF06_cpx clade experienced an initial phase of fast exponential growth during the 1980s, followed by a more recent decline in growth rate since the early 1990s (Fig. 4). This demographic trend was consistent with a model of logistic growth that was then used to estimate the initial growth rate of the CRF06_cpx epidemic. The logistic growth coalescent model indicates that the CRF06_cpx expanded during the 1980s with a median growth rate of 0.82 year−1 (95% HPD: 0.60–1.09 year−1). The demographic pattern of the CRF06_cpx clade was then compared with changes in the estimated number of people living with HIV in those west African countries with a CRF06_cpx prevalence more than 2%. The reconstructed demographic pattern fully agrees with the epidemiological profile of Burkina Faso, where the number of people living with HIV remained relatively stable between 1990 and 2010; but differs from the epidemiological scenario in other west African countries where the HIV epidemic only began to stabilize after the middle 1990s (Fig. 4).
The present study characterized the spatiotemporal dynamics of dispersal of the HIV-1 CRF06_cpx throughout western Africa. The evolutionary and phylogeographic analysis performed here suggests that the CRF06_cpx originated in Burkina Faso in the late 1970s. Burkina Faso, a landlocked country that occupies a central geographical position in western Africa, seems to have been the most important epicenter of the CRF06_cpx dissemination at regional level, continuously exporting the virus to other countries from west and west-Central Africa. Whether the recombination event that originates the CRF06_cpx ancestor took place in Burkina Faso or another African country, however, is not clear. One intriguing point is that the mosaic genome of CRF06_cpx comprises subtypes J and K, two HIV-1 variants detected at low prevalence in central-Africa, but not in Burkina Faso [3–5].
Intense migratory flows were registered from Burkina Faso to neighboring countries during the 1970s and 1980s, particularly to Côte d’Ivoire and Ghana (http://www.oecd.org/migration/38409521.pdf). Our phylogeographic analysis of CRF06_cpx detected significant epidemiological links between Burkina Faso and Mali, Burkina Faso and Nigeria, and Burkina Faso and Ghana; but not between Burkina Faso and Côte d’Ivoire. This may be partially due to sampling bias since the majority (73%) of the CRF06_cpx sequences in our data set was from Burkina Faso, Mali and Nigeria; whereas other countries were represented by a small number of sequences. A more comprehensive sampling of CRF06_cpx viruses may certainly result in the identification of new migration events and epidemiological links not detected in this study. The root position of the CRF06_cpx clade in Burkina Faso may be also sensitive to the sampling bias because most sequences (43%) were from that country. Such root location, however, is fully consistent with epidemiological data that show that prevalence of CRF06_cpx reaches a maximum in Burkina Faso and decreases exponentially as we move away from that country.
Tatem et al. suggest that accessibility between locations have played a major role in the spatial spread of HIV-1 in sub-Saharan Africa. The concentration of most CRF06_cpx infections in western Africa is fully consistent with the strong connectivity of this region and its relative isolation from other African regions, with exception of some west-central African countries where CRF06_cpx has been also detected. Human mobility may have also played an important role in the spatial spread of the CRF06_cpx clade as western Africa appears as an area of intense intermixing of populations at regional level. Quantitative estimates of intra-regional migration indicate that west African countries currently host about 7.5 million migrants from other countries of the region, representing 3% of the regional population, a rate that is above the African average (2%) and that largely exceeds that of the European Union (0.5%) (http://www.oecd.org/migration/38409521.pdf).
Once an HIV variant entered in western Africa, the strong accessibility and the high human mobility between population centers may promote the rapid and homogenous dissemination of the viral strain throughout the region. This may explain the quite homogenous prevalence of the CRF02_AG clade that usually ranges between 40 and 70% across western African countries . The CRF06_cpx prevalence at regional level, however, is much more heterogeneous, ranging from less than 1 to more than 40% [3–20], and seems to be negatively correlated with the geographical distance to Burkina Faso's capital. A small increase in the distance to Ouagadougou is associated with a drastic reduction in the prevalence of CRF06_cpx. This suggests that accessibility and human mobility are not enough to fully explain the complexity of spatial distribution of distinct HIV-1 clades in western Africa, and additional factors may also have influenced such dissemination process.
Our demographic reconstruction suggests that the CRF06_cpx epidemic in western Africa experienced an initial phase of exponential growth during the 1980s followed by a more recent stabilization since the early 1990s. This pattern resemble that previously described for the CRF02_AG epidemic in the same region , with one important difference. The CRF02_AG probably emerged 10 years earlier than the CRF06_cpx and was rapidly disseminated throughout the 1970s and 1980s. At the same time, estimations of UNAIDS indicate that the number of people living with HIV in most western African countries started to stabilize during the 1990s (Fig. 4). We suggest that the later emergence of the CRF06_cpx clade combined with temporal changes in the epidemic growth pattern at regional level during 1990s may have resulted in a less efficient and more heterogeneous dissemination of CRF06_cpx through west-Africa when compared with CRF02_AG.
Coalescent estimations of the HIV-1 epidemic growth rate in southern and eastern African countries (∼0.2–0.4 year−1) [35–37] have been lower than those obtained in countries from western Europe, USA and South America (∼0.5–1.5 year−1) [37–40]. This may reflects the impact of different transmission routes operating at each region. Although HIV transmission in Africa mainly occurred through heterosexual contacts; in Europe and the United States the virus is also transmitted through networks with high rates of partner exchanges like IDU and MSM. The median growth rate here estimated for the CRF06_cpx epidemic in western Africa (0.82 year−1), however, was similar to that projected for HIV-1 epidemics in Europe and the United States. This may suggests that: HIV-1 transmission by heterosexual contacts was more efficient in western Africa than in other African regions; other HIV-1 transmission routes, like the iatrogenic one, also operate in western Africa; or HIV-1 epidemic growth rates in Africa were previously underestimated.
In summary, this study suggests that the CRF06_cpx clade started to circulate in Burkina Faso around the late 1970s and was later spread to other countries from west and west-central African regions. The explanation for the current distribution of CRF06_cpx clade in Africa is probably multifactorial and includes human mobility, accessibility, distance from the epicenter, timing of viral dissemination, and temporal changes in regional epidemic growth pattern among others. Our data also highlight that the initial growth rate of the CRF06_cpx epidemic in western Africa was comparable to that estimated for HIV-1 epidemics in Europe and the United States. These findings offer important insights toward an understanding of the current characteristics and dynamics of the HIV-1 epidemic in western Africa. It will be important to incorporate in future studies new sequences from countries not represented or poorly represented here to test the major conclusions of our model.
We wish to thank Dr Vera Bongertz for critical review of the manuscript.
The study was conceived and designed by G.B. Data acquisition and analysis was performed by E.D. and G.B. G.B. wrote the first draft and E.D. contributed to the final version of the study.
Conflicts of interest
The authors have no conflict of interest.
1. Hemelaar J, Gouws E, Ghys PD, Osmanov S. Global trends in molecular epidemiology of HIV-1 during 2000–2007
2. Montavon C, Toure-Kane C, Nkengasong JN, Vergne L, Hertogs K, Mboup S, et al. CRF06-cpx: a new circulating recombinant form of HIV-1 in West Africa involving subtypes A, G, K, and J
. J Acquir Immune Defic Syndr
3. Ouedraogo-Traore R, Montavon C, Sanou T, Vidal N, Sangare L, Sanou I, et al. CRF06-cpx is the predominant HIV-1 variant in AIDS patients from Ouagadougou, the capital city of Burkina Faso
4. Vergne L, Diagbouga S, Kouanfack C, Aghokeng A, Butel C, Laurent C, et al. HIV-1 drug-resistance mutations among newly diagnosed patients before scaling-up programmes in Burkina Faso and Cameroon
. Antivir Ther
5. Tebit DM, Sangare L, Tiba F, Saydou Y, Makamtse A, Somlare H, et al. Analysis of the diversity of the HIV-1 pol gene and drug resistance associated changes among drug-naive patients in Burkina Faso
. J Med Virol
6. Derache A, Maiga AI, Traore O, Akonde A, Cisse M, Jarrousse B, et al. Evolution of genetic diversity and drug resistance mutations in HIV-1 among untreated patients from Mali between 2005 and 2006
. J Antimicrob Chemother
7. Maiga AI, Fofana DB, Maiga AC, Diallo F, Arkoub ZA, Daou F, et al. Transmitted Antiretroviral Drug Resistance in Newly HIV-Infected and Untreated Patients in Segou and Bamako, Mali
. AIDS Res Hum Retroviruses
8. Mamadou S, Montavon C, Ben A, Djibo A, Rabiou S, Mboup S, et al. Predominance of CRF02-AG and CRF06-cpx in Niger, West Africa
. AIDS Res Hum Retroviruses
9. Charpentier C, Bellecave P, Cisse M, Mamadou S, Diakite M, Peytavin G, et al. High prevalence of antiretroviral drug resistance among HIV-1-untreated patients in Guinea-Conakry and in Niger
. Antivir Ther
10. Chamberland A, Diabate S, Sylla M, Anagounou S, Geraldo N, Zannou DM, et al. Transmission of HIV-1 drug resistance in Benin could jeopardise future treatment options
. Sex Transm Infect
11. Fischetti L, Opare-Sem O, Candotti D, Sarkodie F, Lee H, Allain JP. Molecular epidemiology of HIV in Ghana: dominance of CRF02_AG
. J Med Virol
12. Delgado E, Ampofo WK, Sierra M, Torpey K, Perez-Alvarez L, Bonney EY, et al. High prevalence of unique recombinant forms of HIV-1 in Ghana: molecular epidemiology from an antiretroviral resistance study
. J Acquir Immune Defic Syndr
13. Ayouba A, Lien TT, Nouhin J, Vergne L, Aghokeng AF, Ngo-Giang-Huong N, et al. Low prevalence of HIV type 1 drug resistance mutations in untreated, recently infected patients from Burkina Faso, Cote d’Ivoire, Senegal, Thailand, and Vietnam: the ANRS 12134 study
. AIDS Res Hum Retroviruses
14. Toni T, Masquelier B, Minga A, Anglaret X, Danel C, Coulibaly A, et al. HIV-1 antiretroviral drug resistance in recently infected patients in Abidjan, Cote d’Ivoire: A 4-year survey, 2002–2006
. AIDS Res Hum Retroviruses
15. Chaplin B, Eisen G, Idoko J, Onwujekwe D, Idigbe E, Adewole I, et al. Impact of HIV type 1 subtype on drug resistance mutations in Nigerian patients failing first-line therapy
. AIDS Res Hum Retroviruses
16. Hamel DJ, Sankale JL, Eisen G, Meloni ST, Mullins C, Gueye-Ndiaye A, et al. Twenty years of prospective molecular epidemiology in Senegal: changes in HIV diversity
. AIDS Res Hum Retroviruses
17. Diop-Ndiaye H, Toure-Kane C, Leye N, Ngom-Gueye NF, Montavon C, Peeters M, et al. Antiretroviral drug resistance mutations in antiretroviral-naive patients from Senegal
. AIDS Res Hum Retroviruses
18. Yaotse DA, Nicole V, Roch NF, Mireille PD, Eric D, Martine P. Genetic characterization of HIV-1 strains in Togo reveals a high genetic complexity and genotypic drug-resistance mutations in ARV naive patients
. Infect Genet Evol
19. Dagnra AY, Vidal N, Mensah A, Patassi A, Aho K, Salou M, et al. High prevalence of HIV-1 drug resistance among patients on first-line antiretroviral treatment in Lome, Togo
. J Int AIDS Soc
20. Esbjornsson J, Mild M, Mansson F, Norrgren H, Medstrand P. HIV-1 molecular epidemiology in Guinea-Bissau, West Africa: origin, demography and migrations
. PLoS One
21. Lihana RW, Ssemwanga D, Abimiku A, Ndembi N. Update on HIV-1 diversity in Africa: a decade in review
. AIDS Rev
22. Gray RR, Tatem AJ, Lamers S, Hou W, Laeyendecker O, Serwadda D, et al. Spatial phylodynamics of HIV-1 epidemic emergence in east Africa
23. Delatorre EO, Bello G. Phylodynamics of HIV-1 Subtype C Epidemic in East Africa
. PLoS ONE
24. Faria NR, Suchard MA, Abecasis A, Sousa JD, Ndembi N, Bonfim I, et al. Phylodynamics of the HIV-1 CRF02_AG clade in Cameroon
. Infect Genet Evol
25. Jung M, Leye N, Vidal N, Fargette D, Diop H, Toure Kane C, et al. The origin and evolutionary history of HIV-1 subtype C in Senegal
. PLoS ONE
26. de Oliveira T, Deforche K, Cassol S, Salminen M, Paraskevis D, Seebregts C, et al. An automated genotyping system for analysis of HIV-1 and other microbial sequences
27. Lole KS, Bollinger RC, Paranjape RS, Gadkari D, Kulkarni SS, Novak NG, et al. Full-length human immunodeficiency virus type 1 genomes from subtype C-infected seroconverters in India, with evidence of intersubtype recombination
. J Virol
28. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0
. Syst Biol
29. Posada D. jModelTest: phylogenetic model averaging
. Mol Biol Evol
30. Drummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees
. BMC Evol Biol
31. Drummond AJ, Ho SY, Phillips MJ, Rambaut A. Relaxed phylogenetics and dating with confidence
. PLoS Biol
32. Lemey P, Rambaut A, Drummond AJ, Suchard MA. Bayesian phylogeography finds its roots
. PLoS Comput Biol
33. Bielejec F, Rambaut A, Suchard MA, Lemey P. SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics
34. Tatem AJ, Hemelaar J, Gray RR, Salemi M. Spatial accessibility and the spread of HIV-1 subtypes and recombinants in sub-Saharan Africa
35. Salemi M, de Oliveira T, Soares MA, Pybus O, Dumans AT, Vandamme AM, et al. Different epidemic potentials of the HIV-1B and C subtypes
. J Mol Evol
36. Tully DC, Wood C. Chronology and evolution of the HIV-1 subtype C epidemic in Ethiopia
37. Walker PR, Pybus OG, Rambaut A, Holmes EC. Comparative population dynamics of HIV-1 subtypes B and C: subtype-specific differences in patterns of epidemic growth
. Infect Genet Evol
38. Hue S, Pillay D, Clewley JP, Pybus OG. Genetic analysis reveals the complex structure of HIV-1 transmission within defined risk groups
. Proc Natl Acad Sci U S A
39. Zehender G, Ebranati E, Lai A, Santoro MM, Alteri C, Giuliani M, et al. Population dynamics of HIV-1 subtype B in a cohort of men-having-sex-with-men in Rome, Italy
. J Acquir Immune Defic Syndr
40. Bello G, Soares MA, Schrago CG. The use of bioinformatics for studying HIV evolutionary and epidemiological history in South America
. AIDS Res Treat
CRF06_cpx; HIV-1; phylodynamics; western Africa
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