The Role of Viral Introductions in Sustaining Community-Based HIV Epidemics in Rural Uganda: Evidence from Spatial Clustering, Phylogenetics, and Egocentric Transmission Models
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{"title"=>"The Role of Viral Introductions in Sustaining Community-Based HIV Epidemics in Rural Uganda: Evidence from Spatial Clustering, Phylogenetics, and Egocentric Transmission Models", "type"=>"journal", "authors"=>[{"first_name"=>"Mary K.", "last_name"=>"Grabowski", "scopus_author_id"=>"26767777800"}, {"first_name"=>"Justin", "last_name"=>"Lessler", "scopus_author_id"=>"22951309100"}, {"first_name"=>"Andrew D.", "last_name"=>"Redd", "scopus_author_id"=>"25648218300"}, {"first_name"=>"Joseph", "last_name"=>"Kagaayi", "scopus_author_id"=>"8606720300"}, {"first_name"=>"Oliver", "last_name"=>"Laeyendecker", "scopus_author_id"=>"6508223313"}, {"first_name"=>"Anthony", "last_name"=>"Ndyanabo", "scopus_author_id"=>"23009363300"}, {"first_name"=>"Martha I.", "last_name"=>"Nelson", "scopus_author_id"=>"15758216500"}, {"first_name"=>"Derek A.T.", "last_name"=>"Cummings", "scopus_author_id"=>"9842706300"}, {"first_name"=>"John Baptiste", "last_name"=>"Bwanika", "scopus_author_id"=>"56122973200"}, {"first_name"=>"Amy C.", "last_name"=>"Mueller", "scopus_author_id"=>"55321442300"}, {"first_name"=>"Steven J.", "last_name"=>"Reynolds", "scopus_author_id"=>"35248919000"}, {"first_name"=>"Supriya", "last_name"=>"Munshaw", "scopus_author_id"=>"55979056700"}, {"first_name"=>"Stuart C.", "last_name"=>"Ray", "scopus_author_id"=>"7402324121"}, {"first_name"=>"Tom", "last_name"=>"Lutalo", "scopus_author_id"=>"56734294200"}, {"first_name"=>"Jordyn", "last_name"=>"Manucci", "scopus_author_id"=>"42061874700"}, {"first_name"=>"Aaron A.R.", "last_name"=>"Tobian", "scopus_author_id"=>"6507043607"}, {"first_name"=>"Larry W.", "last_name"=>"Chang", "scopus_author_id"=>"23975476800"}, {"first_name"=>"Chris", "last_name"=>"Beyrer", "scopus_author_id"=>"7006179947"}, {"first_name"=>"Jacky M.", "last_name"=>"Jennings", "scopus_author_id"=>"7201785482"}, {"first_name"=>"Fred", "last_name"=>"Nalugoda", "scopus_author_id"=>"6602860635"}, {"first_name"=>"David", "last_name"=>"Serwadda", "scopus_author_id"=>"7003660739"}, {"first_name"=>"Maria J.", "last_name"=>"Wawer", "scopus_author_id"=>"7005336689"}, {"first_name"=>"Thomas C.", "last_name"=>"Quinn", "scopus_author_id"=>"7402748962"}, {"first_name"=>"Ronald H.", "last_name"=>"Gray", "scopus_author_id"=>"7403689672"}], "year"=>2014, "source"=>"PLoS Medicine", "identifiers"=>{"pmid"=>"24595023", "doi"=>"10.1371/journal.pmed.1001610", "sgr"=>"84899033140", "isbn"=>"1549-1277", "scopus"=>"2-s2.0-84899033140", "issn"=>"15491676", "pui"=>"372909846"}, "id"=>"a70071d7-eaf9-3899-ae33-0c6efb1c5007", "abstract"=>"BACKGROUND: It is often assumed that local sexual networks play a dominant role in HIV spread in sub-Saharan Africa. The aim of this study was to determine the extent to which continued HIV transmission in rural communities--home to two-thirds of the African population--is driven by intra-community sexual networks versus viral introductions from outside of communities.\\n\\nMETHODS AND FINDINGS: We analyzed the spatial dynamics of HIV transmission in rural Rakai District, Uganda, using data from a cohort of 14,594 individuals within 46 communities. We applied spatial clustering statistics, viral phylogenetics, and probabilistic transmission models to quantify the relative contribution of viral introductions into communities versus community- and household-based transmission to HIV incidence. Individuals living in households with HIV-incident (n = 189) or HIV-prevalent (n = 1,597) persons were 3.2 (95% CI: 2.7-3.7) times more likely to be HIV infected themselves compared to the population in general, but spatial clustering outside of households was relatively weak and was confined to distances <500 m. Phylogenetic analyses of gag and env genes suggest that chains of transmission frequently cross community boundaries. A total of 95 phylogenetic clusters were identified, of which 44% (42/95) were two individuals sharing a household. Among the remaining clusters, 72% (38/53) crossed community boundaries. Using the locations of self-reported sexual partners, we estimate that 39% (95% CI: 34%-42%) of new viral transmissions occur within stable household partnerships, and that among those infected by extra-household sexual partners, 62% (95% CI: 55%-70%) are infected by sexual partners from outside their community. These results rely on the representativeness of the sample and the quality of self-reported partnership data and may not reflect HIV transmission patterns outside of Rakai.\\n\\nCONCLUSIONS: Our findings suggest that HIV introductions into communities are common and account for a significant proportion of new HIV infections acquired outside of households in rural Uganda, though the extent to which this is true elsewhere in Africa remains unknown. Our results also suggest that HIV prevention efforts should be implemented at spatial scales broader than the community and should target key populations likely responsible for introductions into communities.", "link"=>"http://www.mendeley.com/research/role-viral-introductions-sustaining-communitybased-hiv-epidemics-rural-uganda-evidence-spatial-clust", "reader_count"=>67, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>2, "Researcher"=>16, "Student > Doctoral Student"=>9, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>1, "Student > Master"=>8, "Other"=>3, "Student > Bachelor"=>6, "Lecturer"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>2, "Researcher"=>16, "Student > Doctoral Student"=>9, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>1, "Student > Master"=>8, "Other"=>3, "Student > Bachelor"=>6, "Lecturer"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>11, "Agricultural and Biological Sciences"=>7, "Arts and Humanities"=>1, "Business, Management and Accounting"=>1, "Computer Science"=>3, "Earth and Planetary Sciences"=>1, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>2, "Nursing and Health Professions"=>2, "Mathematics"=>3, "Medicine and Dentistry"=>24, "Psychology"=>2, "Social Sciences"=>7}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>24}, "Social Sciences"=>{"Social Sciences"=>7}, "Psychology"=>{"Psychology"=>2}, "Mathematics"=>{"Mathematics"=>3}, "Unspecified"=>{"Unspecified"=>11}, "Environmental Science"=>{"Environmental Science"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>7}, "Computer Science"=>{"Computer Science"=>3}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}}, "reader_count_by_country"=>{"United States"=>3, "Spain"=>1}, "group_count"=>9}

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  • {"files"=>["https://ndownloader.figshare.com/files/1406462"], "description"=>"a<p>99% of partnerships were intra-household.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "18-mo"], "article_id"=>951073, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.t005", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_HIV_infection_by_partner_type_over_18_mo_study_interval_/951073", "title"=>"Probability of HIV infection by partner type over 18-mo study interval.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406463"], "description"=>"a<p>Estimate includes infections attributable to ART-naïve HIV-prevalent and -incident cases and household partners with missing HIV status.</p>b<p>Estimate includes extra-household, intra-community, and extra-community partners.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "transmissions", "geographic", "infected", "egocentric"], "article_id"=>951074, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.t004", "stats"=>{"downloads"=>7, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Attributable_HIV_transmissions_by_geographic_location_of_sexual_partner_and_gender_of_newly_infected_participant_estimated_from_egocentric_transmission_model_/951074", "title"=>"Attributable HIV transmissions by geographic location of sexual partner and gender of newly infected participant (estimated from egocentric transmission model).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406480", "https://ndownloader.figshare.com/files/1406481", "https://ndownloader.figshare.com/files/1406482", "https://ndownloader.figshare.com/files/1406483", "https://ndownloader.figshare.com/files/1406484", "https://ndownloader.figshare.com/files/1406485", "https://ndownloader.figshare.com/files/1406486", "https://ndownloader.figshare.com/files/1406487", "https://ndownloader.figshare.com/files/1406488", "https://ndownloader.figshare.com/files/1406489", "https://ndownloader.figshare.com/files/1406490", "https://ndownloader.figshare.com/files/1406491", "https://ndownloader.figshare.com/files/1406492", "https://ndownloader.figshare.com/files/1406493", "https://ndownloader.figshare.com/files/1406494", "https://ndownloader.figshare.com/files/1406495", "https://ndownloader.figshare.com/files/1406496", "https://ndownloader.figshare.com/files/1406497", "https://ndownloader.figshare.com/files/1406498", "https://ndownloader.figshare.com/files/1406499", "https://ndownloader.figshare.com/files/1406500", "https://ndownloader.figshare.com/files/1406501"], "description"=>"<div><p>Background</p><p>It is often assumed that local sexual networks play a dominant role in HIV spread in sub-Saharan Africa. The aim of this study was to determine the extent to which continued HIV transmission in rural communities—home to two-thirds of the African population—is driven by intra-community sexual networks versus viral introductions from outside of communities.</p><p>Methods and Findings</p><p>We analyzed the spatial dynamics of HIV transmission in rural Rakai District, Uganda, using data from a cohort of 14,594 individuals within 46 communities. We applied spatial clustering statistics, viral phylogenetics, and probabilistic transmission models to quantify the relative contribution of viral introductions into communities versus community- and household-based transmission to HIV incidence. Individuals living in households with HIV-incident (<i>n</i> = 189) or HIV-prevalent (<i>n</i> = 1,597) persons were 3.2 (95% CI: 2.7–3.7) times more likely to be HIV infected themselves compared to the population in general, but spatial clustering outside of households was relatively weak and was confined to distances <500 m. Phylogenetic analyses of <i>gag</i> and <i>env</i> genes suggest that chains of transmission frequently cross community boundaries. A total of 95 phylogenetic clusters were identified, of which 44% (42/95) were two individuals sharing a household. Among the remaining clusters, 72% (38/53) crossed community boundaries. Using the locations of self-reported sexual partners, we estimate that 39% (95% CI: 34%–42%) of new viral transmissions occur within stable household partnerships, and that among those infected by extra-household sexual partners, 62% (95% CI: 55%–70%) are infected by sexual partners from outside their community. These results rely on the representativeness of the sample and the quality of self-reported partnership data and may not reflect HIV transmission patterns outside of Rakai.</p><p>Conclusions</p><p>Our findings suggest that HIV introductions into communities are common and account for a significant proportion of new HIV infections acquired outside of households in rural Uganda, though the extent to which this is true elsewhere in Africa remains unknown. Our results also suggest that HIV prevention efforts should be implemented at spatial scales broader than the community and should target key populations likely responsible for introductions into communities.</p><p><i>Please see later in the article for the Editors' Summary</i></p></div>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "viral", "introductions", "sustaining", "community-based", "epidemics", "spatial", "egocentric"], "article_id"=>951090, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001610.s001", "https://dx.doi.org/10.1371/journal.pmed.1001610.s002", "https://dx.doi.org/10.1371/journal.pmed.1001610.s003", "https://dx.doi.org/10.1371/journal.pmed.1001610.s004", "https://dx.doi.org/10.1371/journal.pmed.1001610.s005", "https://dx.doi.org/10.1371/journal.pmed.1001610.s006", "https://dx.doi.org/10.1371/journal.pmed.1001610.s007", "https://dx.doi.org/10.1371/journal.pmed.1001610.s008", "https://dx.doi.org/10.1371/journal.pmed.1001610.s009", "https://dx.doi.org/10.1371/journal.pmed.1001610.s010", "https://dx.doi.org/10.1371/journal.pmed.1001610.s011", "https://dx.doi.org/10.1371/journal.pmed.1001610.s012", "https://dx.doi.org/10.1371/journal.pmed.1001610.s013", "https://dx.doi.org/10.1371/journal.pmed.1001610.s014", "https://dx.doi.org/10.1371/journal.pmed.1001610.s015", "https://dx.doi.org/10.1371/journal.pmed.1001610.s016", "https://dx.doi.org/10.1371/journal.pmed.1001610.s017", "https://dx.doi.org/10.1371/journal.pmed.1001610.s018", "https://dx.doi.org/10.1371/journal.pmed.1001610.s019", "https://dx.doi.org/10.1371/journal.pmed.1001610.s020", "https://dx.doi.org/10.1371/journal.pmed.1001610.s021", "https://dx.doi.org/10.1371/journal.pmed.1001610.s022"], "stats"=>{"downloads"=>41, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Role_of_Viral_Introductions_in_Sustaining_Community_Based_HIV_Epidemics_in_Rural_Uganda_Evidence_from_Spatial_Clustering_Phylogenetics_and_Egocentric_Transmission_Models_/951090", "title"=>"The Role of Viral Introductions in Sustaining Community-Based HIV Epidemics in Rural Uganda: Evidence from Spatial Clustering, Phylogenetics, and Egocentric Transmission Models", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406447"], "description"=>"<p>(A) Rakai (∼2,200 km<sup>2</sup>), a rural district in southwest Uganda, with population ∼450,000 (∼700 communities). RCCS R13 study participants (<i>n</i> = 1,085) reported 1,169 sexual partners with primary residence outside the Rakai District, but within Uganda (where disclosed, residential locations of sexual partners are indicated with red dots on the map). Only three sexual partners were reported to be living outside Uganda (two in Tanzania and one in the United Kingdom, not shown). (B) The Rakai district at a higher resolution, with the 11 geographic regions surveyed in RCCS R13 indicated in color. There are two primary highways (Masaka Road to Tanzania and the Trans-African National Highway to Rwanda and the Democratic Republic of the Congo [DR of Congo]) and numerous secondary roads that extend throughout the district.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health"], "article_id"=>951059, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.g001", "stats"=>{"downloads"=>3, "page_views"=>27, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rakai_District_Uganda_/951059", "title"=>"Rakai District, Uganda.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406449"], "description"=>"<p>Spatial clustering analyses show whether HIV prevalence or incidence is elevated within certain distances of other HIV-seropositive persons. We define the spatial clustering of HIV-seropositive individuals as τ(<i>d</i><sub>1</sub>,<i>d</i><sub>2</sub>), the relative probability that an HIV-seropositive person resides within a distance window, <i>d</i><sub>1</sub> to <i>d</i><sub>2</sub>, from another HIV-seropositive person compared to the probability that any individual is HIV seropositive in the entire study population. Where spatial clustering exists, values of τ(<i>d</i><sub>1</sub>,<i>d</i><sub>2</sub>) exceed one. Shaded areas show the 95% bootstrapped confidence intervals for spatial clustering estimates. (A) The spatial clustering between HIV-seropositive persons (prevalent or incident cases with other prevalent or incident cases; red). (B) The spatial clustering of HIV-seroincident cases with ART-naïve HIV-seroprevalent persons (yellow). (C) The spatial clustering of HIV-seroincident cases with other HIV-seroincident cases (blue). (D) A blowup of the area where significant extra-household spatial clustering (<500 m) was identified among all HIV-seropositive persons (marked with black box in [A–C]). Data are shown only up to 10 km (no significant spatial clustering was observed beyond this distance).</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "clustering", "hiv-seropositive", "persons", "households", "geographic", "windows", "250", "10", "km", "centered", "50", "125"], "article_id"=>951061, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.g002", "stats"=>{"downloads"=>2, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spatial_clustering_of_HIV_seropositive_persons_within_households_0_km_and_in_geographic_windows_of_250_m_up_to_10_km_the_first_window_is_10_8211_250_m_and_windows_are_centered_every_50_m_starting_at_125_m_/951061", "title"=>"Spatial clustering of HIV-seropositive persons within households (0 km) and in geographic windows of 250 m up to 10 km (the first window is 10–250 m, and windows are centered every 50 m starting at 125 m).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406452"], "description"=>"<p>(A) Boxplots of the intra-subtype <i>gag</i> genetic pairwise distances for epidemiologically linked (Epi linked) incident couples (i.e., at least one member of the couple was an incident case) and for all epidemiologically unlinked incident pairs of individuals in RCCS R13. (B) Boxplots of intra-subtype <i>gag</i> genetic pairwise distances by the geographic distance between the incident pair. (C) A ML phylogenetic tree (radial) of HIV-1 subtype A <i>gag</i> sequences from HIV-seroprevalent (<i>n</i> = 245) and HIV-incident (<i>n</i> = 55) cases, where taxa are colored by the geographic region from which they were isolated. Reference strains (<i>n</i> = 87) are in black. Grey circles indicate nodes with bootstrap support of ≥70%; black circles indicate intra-household clusters; † indicates an intra-household virus also sharing a cluster with at least one other household. Additional radial and rectangular phylogenetic trees for HIV-1 subtypes A, D, and C for <i>gag</i> and <i>env</i> genes are included in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s005\" target=\"_blank\">Figures S5</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s006\" target=\"_blank\">S6</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s007\" target=\"_blank\">S7</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s008\" target=\"_blank\">S8</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s009\" target=\"_blank\">S9</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s010\" target=\"_blank\">S10</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s011\" target=\"_blank\">S11</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s012\" target=\"_blank\">S12</a>, <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001610#pmed.1001610.s013\" target=\"_blank\">S13</a>.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "phylogenetic", "hiv-1"], "article_id"=>951064, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.g003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maximum_likelihood_phylogenetic_analyses_of_the_HIV_1_gag_gene_/951064", "title"=>"Maximum likelihood phylogenetic analyses of the HIV-1 <i>gag</i> gene.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406454"], "description"=>"<p>The dotted blue line represents the border of a hypothetical community.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "inferential", "methods"], "article_id"=>951066, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.g004", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_inferential_methods_and_study_results_and_conclusions_/951066", "title"=>"Summary of inferential methods and study results and conclusions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406456"], "description"=>"a<p>“Married, polygamous” for women refers to a woman in a marital relationship with a man who has multiple wives.</p>b<p>Self-reported sexual partners from the egocentric partnership block of the RCCS study questionnaire (records up to four partners in the last 12 mo).</p>c<p>Categories not mutually exclusive (i.e., participants may report multiple partners with different HIV serostatus).</p>d<p>Partners were considered to be on ART if they were using ART for 50% or more of the corresponding index participant's time at risk.</p>e<p>Partner on ART for 58% of the newly infected index participant's time at risk (previous to current survey interval).</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "hiv-seronegative", "-incident", "egocentric"], "article_id"=>951068, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.t003", "stats"=>{"downloads"=>1, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Descriptive_characteristics_of_HIV_seronegative_and_incident_participants_in_egocentric_partner_analysis_n_9_520_/951068", "title"=>"Descriptive characteristics of HIV-seronegative and -incident participants in egocentric partner analysis (<i>n</i> = 9,520).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406458"], "description"=>"a<p>Categories not mutually exclusive.</p>b<p>Refers to clusters of two individuals who shared the same household.</p>c<p>Refers to clusters of two or more individuals who spanned households but shared the same community.</p>d<p>Refers to clusters of two or more individuals who spanned households and communities.</p>e<p>Refers to clusters of two or more individuals who spanned households, communities, and geographic regions.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "95", "phylogenetic", "clusters", "915", "sequences", "hiv-infected", "rccs"], "article_id"=>951070, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.t002", "stats"=>{"downloads"=>3, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_95_phylogenetic_clusters_identified_in_maximum_likelihood_phylogenetic_analyses_HKY_85_of_915_gag_sequences_and_1_026_env_sequences_obtained_from_1_099_HIV_infected_participants_in_RCCS_R13_/951070", "title"=>"Characteristics of 95 phylogenetic clusters identified in maximum likelihood phylogenetic analyses (HKY-85) of 915 <i>gag</i> sequences and 1,026 <i>env</i> sequences obtained from 1,099 HIV-infected participants in RCCS R13.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-04 02:45:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1406459"], "description"=>"a<p>Married refers to currently married individuals and includes married monogamous and married polygamous individuals.</p>b<p>Calculated using Poisson regression and assuming that HIV seroconversion occurred at the midpoint of the follow-up interval.</p>", "links"=>[], "tags"=>["Computational biology", "population genetics", "Sequence analysis", "epidemiology", "Epidemiological methods", "Infectious disease epidemiology", "Molecular epidemiology", "Spatial epidemiology", "Global health", "Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV epidemiology", "HIV prevention", "Infectious disease control", "Infectious disease modeling", "Public health", "46", "rakai", "communities", "11", "geographic", "surveyed", "rccs"], "article_id"=>951071, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Mary K. Grabowski", "Justin Lessler", "Andrew D. Redd", "Joseph Kagaayi", "Oliver Laeyendecker", "Anthony Ndyanabo", "Martha I. Nelson", "Derek A. T. Cummings", "John Baptiste Bwanika", "Amy C. Mueller", "Steven J. Reynolds", "Supriya Munshaw", "Stuart C. Ray", "Tom Lutalo", "Jordyn Manucci", "Aaron A. R. Tobian", "Larry W. Chang", "Chris Beyrer", "Jacky M. Jennings", "Fred Nalugoda", "David Serwadda", "Maria J. Wawer", "Thomas C. Quinn", "Ronald H. Gray"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001610.t001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_statistics_for_the_46_Rakai_communities_within_11_geographic_regions_surveyed_in_RCCS_R13_/951071", "title"=>"Summary statistics for the 46 Rakai communities (within 11 geographic regions) surveyed in RCCS R13.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-04 02:45:10"}

PMC Usage Stats | Further Information

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