{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T22:28:04Z","timestamp":1787092084116,"version":"build-2736575974"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T00:00:00Z","timestamp":1781136000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":69,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Innovative Pharmaceutical Association South Africa","award":["Innovative Pharmaceutical Association South Africa"],"award-info":[{"award-number":["Innovative Pharmaceutical Association South Africa"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Orphanet J Rare Dis"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Rare diseases (RDs) collectively affect a significant proportion of the population, yet their burden in South Africa (SA) remains poorly defined due to limited diagnostic capacity and infrastructure, inadequate epidemiological data and poor surveillance systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To estimate the point prevalence of RDs in SA by integrating Orphanet-derived point prevalence data with national population statistics, identify disease characteristics and affected sub-groups, and assess the proportion of patients requiring high-cost treatments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A cross-sectional epidemiologic study was conducted using Orphanet\u2019s validated methodology and four curated datasets (epidemiology, natural history, functional consequences, and medical domains). Inclusion criteria excluded cancers, infections, poisonings, and conditions without point prevalence data. RDs were classified by direct (population-based) or indirect (case\/family report) point prevalence rates integrated with 2024 South African population estimates (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200963015904). Additional analyses were performed for age of onset, inheritance patterns, medical domains, associated disability, and access to high-cost treatment access in SA.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 3728 RD were included in the study, relating to 58% of unique Orphanet disorder entities. The estimated mean point prevalence of these RDs in SA was 4.8% (range: 3.7%\u20135.9%), corresponding to 3030204 (range: 2321906\u20133738503) affected individuals. Only 11% of RDs accounted for 98% of this patient burden. Most conditions had childhood onset (77%) and were inherited in an autosomal recessive (42%) or autosomal dominant (27%) pattern. Approximately 1.33\u00a0million (44%) patients in SA are estimated to experience moderate to severe functional disabilities related to the 3728 RD in the study. High-cost treatment was applicable to &lt;\u20095% of patients for included RD, yet only 25 of 59 globally approved orphan drugs are currently available in SA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study provides the first national-level, evidence-based estimate of RD prevalence in SA using global Orphanet data. The findings confirm a substantial, mostly paediatric burden, with significant disability and limited treatment access. Results support investment in newborn screening, integrated community genetic services, early diagnosis, and equitable care models. These estimates offer a critical foundation for evidence-based national RD policy development and service planning, and a replicable approach for other low- and middle-income countries.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13023-026-04444-w","type":"journal-article","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T10:26:08Z","timestamp":1781173568000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The estimated burden of rare diseases in South Africa using Orphanet: an epidemiological analysis"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9566-6248","authenticated-orcid":false,"given":"Helen Louise","family":"Malherbe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sujani","family":"Odendaal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1859-3989","authenticated-orcid":false,"given":"Ana","family":"Kukava","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3646-7469","authenticated-orcid":false,"given":"Caterina","family":"Lucano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,11]]},"reference":[{"key":"4444_CR1","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1038\/s41431-019-0508-0","volume":"28","author":"SN Wakap","year":"2020","unstructured":"Wakap SN, Lambert DM, Olry A, Rodwell C, Gueydan C, Lanneau V, Murphy D, Le Cam Y, Rath A. 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