{"doi":"10.1371/journal.pmed.1003042","title":"Mapping and characterising areas with high levels of HIV transmission in sub-Saharan Africa: A geospatial analysis of national survey data","abstract":"BACKGROUND: In the generalised epidemics of sub-Saharan Africa (SSA), human immunodeficiency virus (HIV) prevalence shows patterns of clustered micro-epidemics. We mapped and characterised these high-prevalence areas for young adults (15-29 years of age), as a proxy for areas with high levels of transmission, for 7 countries in Eastern and Southern Africa: Kenya, Malawi, Mozambique, Tanzania, Uganda, Zambia, and Zimbabwe. METHODS AND FINDINGS: We used geolocated survey data from the most recent United States Agency for International Development (USAID) demographic and health surveys (DHSs) and AIDS indicator surveys (AISs) (collected between 2008-2009 and 2015-2016), which included about 113,000 adults-of which there were about 53,000 young adults (27,000 women, 28,000 men)-from over 3,500 sample locations. First, ordinary kriging was applied to predict HIV prevalence at unmeasured locations. Second, we explored to what extent behavioural, socioeconomic, and environmental factors explain HIV prevalence at the individual- and sample-location level, by developing a series of multilevel multivariable logistic regression models and geospatially visualising unexplained model heterogeneity. National-level HIV prevalence for young adults ranged from 2.2% in Tanzania to 7.7% in Mozambique. However, at the subnational level, we found areas with prevalence among young adults as high as 11% or 15% alternating with areas with prevalence between 0% and 2%, suggesting the existence of areas with high levels of transmission Overall, 15.6% of heterogeneity could be explained by an interplay of known behavioural, socioeconomic, and environmental factors. Maps of the interpolated random effect estimates show that environmental variables, representing indicators of economic activity, were most powerful in explaining high-prevalence areas. Main study limitations were the inability to infer causality due to the cross-sectional nature of the surveys and the likely under-sampling of key populations in the surveys. CONCLUSIONS: We found that, among young adults, micro-epidemics of relatively high HIV prevalence alternate with areas of very low prevalence, clearly illustrating the existence of areas with high levels of transmission. These areas are partially characterised by high economic activity, relatively high socioeconomic status, and risky sexual behaviour. Localised HIV prevention interventions specifically tailored to the populations at risk will be essential to curb transmission. More fine-scale geospatial mapping of key populations,-such as sex workers and migrant populations-could help us further understand the drivers of these areas with high levels of transmission and help us determine how they fuel the generalised epidemics in SSA.","journal":"PLoS Medicine","year":2020,"id":65403,"datarank":2.4378949861191392,"base_score":4.07753744390572,"endowment":4.07753744390572,"self_citation_contribution":0.611630616585858,"citation_network_contribution":1.826264369533281,"self_endowment_contribution":0.611630616585858,"citer_contribution":1.826264369533281,"corpus_percentile":91.24313452463835,"corpus_rank":1133,"citation_count":58,"citer_count":45,"citers_with_citation_signal":39,"citers_with_endowment":39,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6933,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":4.1667,"fair_percentile":4.891470498318557,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":345808,"name":"Jan A. C. Hontelez","orcid":"0000-0002-9323-7861","position":1,"is_corresponding":false},{"id":274641,"name":"Federica Giardina","orcid":"0000-0002-3710-0940","position":2,"is_corresponding":false},{"id":345809,"name":"Richard Steen","orcid":"0000-0002-0798-022X","position":3,"is_corresponding":false},{"id":345810,"name":"Nico Nagelkerke","orcid":"0000-0002-5505-7923","position":4,"is_corresponding":false},{"id":22379,"name":"Till Bärnighausen","orcid":"0000-0002-4182-4212","position":5,"is_corresponding":false},{"id":274659,"name":"Sake J. de Vlas","orcid":"0000-0002-1830-5668","position":6,"is_corresponding":false},{"id":345807,"name":"Caroline A. Bulstra","orcid":"0000-0002-3397-2944","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-18T21:13:23.327603Z","pmid":"32142509","pmcid":"PMC7059914","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":0.0,"fair_a":0.0,"fair_i":20.0,"fair_r":25.0,"fair_zscore":-1.1986,"fair_rationale":{"fair_score":4.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":0.0,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not provide any persistent identifier for the dataset it generated; the only identifiers are for the external DHS data sources used in the analysis.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The study's own data are not deposited in a named repository; the paper only states that the utilised data are open-source from external sources.","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"All utilised data are open-source, and the hyperlinks to the different data sources are provided in the Methods section of the manuscript.","grounded":true,"rationale":"The data availability statement refers to the openness of the input data, not to the study's own derived data, and thus does not point to a repository record for the study's dataset. 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[downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":25.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No reuse licence is stated for the study's own data; the CC BY licence applies to the article only. 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A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not provide any persistent identifier for the dataset it generated; the only identifiers are for the external DHS data sources used in the analysis.","gain":16.67,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. 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For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The text does not specify a route to the study's own data with no precondition; the only access is through the open-access article, but this is not stated as a data route. [majority verdict 'no' (4/5 passes agreed)]","gain":16.67,"priority":"essential","scored":true},{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No reuse licence is stated for the study's own data; the CC BY licence applies to the article only. 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In ecology / environmental, describe the data with Darwin Core or Ecological Metadata Language (EML).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Reporting of study design and analysis followed RECORD guidelines ( S1 Checklist ) [ 24 ].","why":"RECORD and STROBE are manuscript reporting guidelines, not data/metadata community standards. [majority verdict 'partial' (4/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No documentation object (README, codebook, data dictionary) is described as accompanying the study's data. [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. 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A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"Data obtained through https://dhsprogram.com/.","why":"The paper provides URLs for the external data sources it depends on, such as the DHS program website. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not state any timeline for availability or persistence of the study's data.","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the ecology / environmental repository accession (e.g. from GBIF, PANGAEA or Dryad) in the reference list."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T11:16:44.340876Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}