Epidemiological burden of sexually transmitted infections and dermatovenereological diseases: Challenges in epidemiological data collection and the role of digital technologies (A narrative review)
DOI:
https://doi.org/10.37800/RM.2.2026.733Keywords:
sexually transmitted infections , dermatovenereological diseases, epidemiology, prevalence, surveillance systems, digital health, artificial intelligenceAbstract
Introduction: Sexually transmitted infections (STIs) continue to pose a major global public health challenge and are closely associated with reproductive health outcomes and dermatological morbidity. Despite relatively low mortality, their epidemiological burden is substantial and often underestimated, as surveillance systems primarily rely on registered cases, while a considerable proportion of infections remains undiagnosed or unreported.
The study aimed to analyze the epidemiological burden of sexually transmitted infections and dermatovenereological diseases and to evaluate modern approaches to data collection and digital epidemiological surveillance.
Materials and Methods: A narrative literature review was conducted using publications indexed in PubMed (MEDLINE), the Cochrane Library, and Google Scholar. Studies published between 2014 and 2024 were prioritized. Articles presenting epidemiological data on STIs and dermatovenereological diseases, as well as those addressing digital health technologies, were included. Following a stepwise screening process, 50 publications were selected for qualitative synthesis.
Results: Considerable variability in prevalence estimates was identified across different data sources and study designs. Population-based studies generally demonstrate a higher disease burden than clinical datasets, indicating a significant hidden burden due to underdiagnosis and underreporting. In many settings, reliance on officially registered cases fails to reflect the true prevalence because of asymptomatic infections, self-treatment, and the use of private healthcare services. Digital health technologies, including teledermatology, electronic health records, and artificial intelligence-based tools, have the potential to improve disease detection, surveillance, and data integration.
Conclusion: The epidemiological burden of STIs and dermatovenereological diseases is likely underestimated due to limitations of current surveillance systems. Integration of multiple data sources and digital health technologies may enhance epidemiological monitoring and support more effective healthcare planning.
References
1. Richard MA, Paul C, Nijsten T, Gisondi P, Salavastru C, Taieb C, Trakatelli M, Puig L, Stratigos A. EADV burden of skin diseases project team. Prevalence of most common skin diseases in Europe: a population-based study. J Eur Acad Dermatol Venereol. 2022;36(7):1088-1096. https://doi.org/10.1111/jdv.18050
2. Alam MN, Husain MA, Siddiqua A, Mohammad Babar ZU, Hasan MR. The prevalence of skin and venereal diseases among geriatric patients attending a tertiary care hospital in Dhaka, Bangladesh. Bangladesh J Med Sci. 2019;18(1):130-135.
https://doi.org/10.3329/bjms.v18i1.39563
3. Report on global sexually transmitted infection surveillance, 2018. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO. ISBN 978-92-4-156569-1.
https://iris.who.int/server/api/core/bitstreams/34f651af-6318-4b7d-9bcb-97ac7423b9b7/content
4. Kubrak A, Zimny-Zając A, Makuch S, Pawelec Ł, Jankowska-Polańska B, Tański W, Szepietowski JC, Agrawal S. Epidemiology of skin diseases in Poland: analysis of prevalence and risk factors: a cross-sectional study. Dermatol Ther (Heidelb). 2025;15(8):2179-2199.
https://doi.org/10.1007/s13555-025-01464-5
5. Ahmed R, Mondal KA. Pattern of skin and venereal diseases among patients attending OPD of dermatology and venereology at Rangpur Medical College Hospital, Bangladesh. Saudi J Med Pharm Sci. 2020;6(9):610-615.
https://doi.org/10.36348/sjmps.2020.v06i09.004
6. Hossain SMI, Rahman MM, Alam MS. The prevalence of skin and venereal diseases among patients in a Bangladesh tertiary care hospital. Planet (Barisal) [Internet]. 2021;5(1):57-61. Available from:
https://bdjournals.org/index.php/planet/article/view/11
7. Richard MA, Paul C, Nijsten T, Gisondi P, Salavastru C, Taieb C, Trakatelli M, Puig L, Stratigos A. EADV burden of skin diseases project team. Prevalence of most common skin diseases in Europe: a population-based study. J Eur Acad Dermatol Venereol. 2022;36(7):1088-1096.
https://doi.org/10.1111/jdv.18050
8. Svensson A, Ofenloch RF, Bruze M, Naldi L, Cazzaniga S, Elsner P, Goncalo M, Schuttelaar MLA, Diepgen TL. Prevalence of skin disease in a population-based sample of adults from five European countries. Br J Dermatol. 2018;178(5):1111-1118.
https://doi.org/10.1111/bjd.16248
9. Tizek L, Schielein MC, Seifert F, Biedermann T, Böhner A, Zink A. Skin diseases are more common than expected: screening results of an unreferred population at the Munich Oktoberfest. J Eur Acad Dermatol Venereol. 2019;33(7):1421-1428.
https://doi.org/10.1111/jdv.15494
10. Richard MA, Corgibet F, Beylot-Barry M, Barbaud A, Bodemer C, Chaussade V, D’Incan M, Joly P, Leccia MT, Meurant JM, Petit A, Geffroy BR, Sei JF, Taieb C, Misery L, Ezzedine K. Sex- and age-adjusted prevalence estimates of five chronic inflammatory skin diseases in France: results of the “OBJECTIFS PEAU” study. J Eur Acad Dermatol Venereol. 2018;32(11):1967-1971.
https://doi.org/10.1111/jdv.14959
11. Misery L, Jourdan E, Huet F, Brenaut E, Cadars B, Virassamynaïk S, Sayag M, Taieb C. Sensitive skin in France: prevalence, relationship with age and skin type, and impact on quality of life. J Eur Acad Dermatol Venereol. 2018;32(5):791-795.
https://doi.org/10.1111/jdv.14837
12. Misery L, Loser K, Ständer S. Sensitive skin. J Eur Acad Dermatol Venereol. 2016;30(Suppl 1):2-8.
https://doi.org/10.1111/jdv.13532
13. Chen W, Dai R, Li L. Prevalence of self-declared sensitive skin: a systematic review and meta-analysis. J Eur Acad Dermatol Venereol. 2020;34(8):1779-1788.
https://doi.org/10.1111/jdv.16166
14. Amgarth-Duff I, Thomas H, Ricciardo BM, Anderson L, Stephens M, Currie BJ, Steer AC, Tong SYC, Crooks K, Hempenstall A, Tatian A, Foster R, Kavalam G, Pallegedara T, Walls K, Bowen A. Systematic review of evidence for treatment and management of common skin conditions in resource-limited settings: an update. Trop Med Int Health. 2024;29(11):923-950.
https://doi.org/10.1111/tmi.14047
15. Augustin M, Kirsten N, Körber A, Wilsmann-Theis D, Itschert G, Staubach-Renz P, Maul JT, Zander N. Prevalence, predictors and comorbidity of dry skin in the general population. J Eur Acad Dermatol Venereol. 2019;33(1):147-150.
https://doi.org/10.1111/jdv.15157
16. Mekić S, Jacobs LC, Gunn DA, Mayes AE, Ikram MA, Pardo LM, Nijsten T. Prevalence and determinants of xerosis cutis in middle-aged and elderly populations: a cross-sectional study. J Am Acad Dermatol. 2019;81(4):963-969.e2.
https://doi.org/10.1016/j.jaad.2018.12.038
17. Jiang Q, Wang Y, Liu Y, Zhu D, Xie Y, Zhao J, Weng Y, Tang Y, Feng H, Li Y, Wang J, Cai Y, Kang Z, Ou Y, Chen D. Prevalence and associated factors of dry skin among older inpatients: a multicenter cross-sectional study. Int J Nurs Stud. 2022;135:104358.
https://doi.org/10.1016/j.ijnurstu.2022.104358
18. Strange TA, Clark HL, Dixon LJ. Potentially traumatic events, posttraumatic stress symptoms, and skin-related quality of life among adults with self-reported skin disease symptoms. Arch Dermatol Res. 2024;317(1):19.
https://doi.org/10.1007/s00403-024-03451-w
19. Bagri M, Nijhawan M, Nijhawan S, Bishnoi S, Agarwal S. Pattern of common skin diseases among school-going children in a semi-urban area of Jaipur: a cross-sectional study. Indian J Paediatr Dermatol. 2020;21(4):275-278.
https://doi.org/10.4103/ijpd.IJPD_90_19
20. Murzina E, Bardova K, Patselia M, Barinova M, Yurchyk Y. Dermatoses of chronic nature: new developments in diagnosis and treatment. Health Leadership and Quality of Life. 2025; 4:695. https://doi.org/10.56294/hl2025695
21. Igissinov N, Kulmirzayeva D, Bilyalova Z, Akpolatova G, Mamyrbayeva M, Zhumagaliyeva G. Age and spatial peculiarities of non-neoplastic diseases of the skin and subcutaneous tissue in Kazakhstan, 2003-2015. Iran J Public Health. 2017;46(11):1572-1578.
https://ijph.tums.ac.ir/index.php/ijph/article/view/11224
22. Kemaykin VM, Tabinbaev NB, Khudaibergenova MS, Olifirovich AA, Abdrakhmanova LM, Denning DW, Klimko N. An estimate of severe and chronic fungal diseases in the Republic of Kazakhstan. J Fungi (Basel). 2018;4(1):34.
https://doi.org/10.3390/jof4010034
23. Bissenbay A, Zhigailov A, Maltseva E, Egemberdieva R, Skiba Y, Mamadaliyev S. Borreliosis: a hidden threat for Kazakhstan. Eurasian J Appl Biotechnol. 2019;(2):15-27.
https://doi.org/10.11134/btp.2.2019.2
24. Prilepskaya VN, Gomberg M, Kothari S, Yee K, Kulkarni A, Garland SM, Giuliano AR. Estimating the burden of illness related to genital warts in Russia: a cross-sectional study. J Health Econ Outcomes Res. 2020;7(2):182-188.
https://doi.org/10.36469/jheor.2020.182-188
25. Kubanov AA, Bogdanova EV. Dermatovenereology in the Russian Federation: results of 2023. Vestn Dermatol Venerol. 2024;100(4):9-24.
https://doi.org/10.25208/vdv16795
26. Zilberberg NV, Polyakova NV, Syrneva TA, Levchik NK, Iglikov VA. Socio-demographic and clinical-epidemiological aspects of syphilis at the present stage. Dermatovenerol Cosmetol. 2023;9:374-379.
https://doi.org/10.34883/PI.2023.9.4.020
27. Osmonaliev MK, Koibagarova AA, Yusupova DM, Shakirova AT, Khalikova AU. To the 100th anniversary of the dermatovenerological service of Kyrgyzstan – the history of development. Health Care Kyrgyzstan. 2022;(4):212-215.
https://elibrary.ru/item.asp?id=49500000
28. Karabaev BB, Beisheeva NJ, Satybaldieva AB, Ismailova AD, Pessler F, Akmatov MK. Seroprevalence of hepatitis B, hepatitis C, HIV, Treponema pallidum, and co-infections among blood donors in Kyrgyzstan: a retrospective analysis (2013-2015). Infect Dis Poverty. 2017;6(1):2-9. https://doi.org/10.1186/s40249-016-0221-0
29. Rakhmatulina MR, Porsokhonova D.F., Novoselova E.Y., Inoyatov A.S. Epidemiological and clinical aspects of syphilis incidence in the Russian Federation and the Republic of Uzbekistan: comparative analysis. Vestn Dermatol Venerol. 2025;101(2):23-38.
https://doi.org/10.25208/vdvXXXXX
30. McRae C, Zhang TD, Seeley LD, Anderson M, Turner L, Graham LV. Patient perceptions of artificial intelligence and telemedicine in dermatology: a narrative review. JMIR Dermatol. 2025;8(1):e75454.
31. López-Pardo Rico M, Ginarte Val M, Sánchez-Aguilar Rojas MD, Martínez Leboráns L, Rodríguez Otero C, Flórez Á. Teledermatology vs face-to-face dermatology for melanoma diagnosis: a systematic review. Cancers (Basel). 2025;17(17):2836.
https://doi.org/10.3390/cancers17172836
32. Zama D, Borghesi A, Ranieri A, Manieri E, Pierantoni L, Andreozzi L, Dondi A, Neri I, Lanari M, Calegari R. Perspectives and challenges of telemedicine and artificial intelligence in pediatric dermatology. Children (Basel). 2024;11(11):1401.
https://doi.org/10.3390/children11111401
33. Ijaz M. Effectiveness of telemedicine in dermatology services: a systematic review. Br J Dermatol. 2025;193(Suppl 1):ljaf085.526.
https://doi.org/10.1093/bjd/ljaf085.526
34. Zou Q, Luo Y, Hao D, Li M, Jihui C. Validation and application of DLQI score in psoriasis patients. J Health Popul Nutr. 2024;43(1):92.
https://doi.org/10.1186/s41043-024-00587-3
35. Johns JR, Vyas J, Ali FM, Ingram JR, Salek S, Finlay AY. DLQI as a benchmark in validation of quality-of-life instruments: a systematic review. J Eur Acad Dermatol Venereol. 2024. https://doi.org/10.1111/jdv.20321
36. Vyas J, Johns JR, Ali FM, Ingram JR, Salek S, Finlay AY. Validation aspects of DLQI: a systematic review. Acta Derm Venereol. 2024;104:adv41120.
https://doi.org/10.2340/actadv.v104.41120
37. Elder A, Ring C, Heitmiller K, Gabriel Z, Saedi N. The role of artificial intelligence in cosmetic dermatology-Current, upcoming, and future trends. J Cosmet Dermatol. 2021;20(1):48-52.
https://doi.org/10.1111/jocd.13797
38. Jain AWay D, Gupta V, Gao Y, de Oliveira Marinho G, Hartford J, Sayres R, Kanada K, Eng C, Nagpal K, DeSalvo KB, Corrado GS, Peng L, Webster DR, Dunn RC, Coz D, Huang SJ, Liu Y, Bui P, Liu Y. Development and assessment of an AI-based tool for skin condition diagnosis. JAMA Netw Open. 2021;4(4):e217249.
https://doi.org/10.1001/jamanetworkopen.2021.7249
39. Gniadecki R. A decade of progress and innovation in dermatology. Front Med (Lausanne). 2025;11:1546471.
https://doi.org/10.3389/fmed.2025.1546471
40. Patel S, Wang JV, Motaparthi K, Lee JB. Artificial intelligence in dermatology for the clinician. Clin Dermatol. 2021;39(4):667-672.
https://doi.org/10.1016/j.clindermatol.2021.03.012
41. Li CX, Shen CB, Xue K, Shen X, Jing Y, Wang ZY, Xu F, Meng RS, Yu JB, Cui Y. Artificial intelligence in dermatology: past, present, and future. Chin Med J (Engl). 2019;132(17):2017-2020.
https://doi.org/10.1097/CM9.0000000000000372
42. Khafizova AA, Khafizova, AA, Galimov, A., Kharisova, SR, Grebenshchikova, LY, Yagudina, RI, Smirnova, LM. Impact of healthcare digitalization on medical education. Contemp Educ Technol. 2023;15(4):ep479.
https://doi.org/10.30935/cedtech/13768
43. Soe NN, Kusanandar II, Latt PM, Ong J. Clinical Applications of AI in Sexually Transmitted Infection and Anogenital Dermatoses in Sexual Health: A Systematic Review and Meta-Analysis. 2025;3:1-25.
https://doi.org/ 10.21203/rs.3.rs-6002285/v1
44. Muhaba KA, Dese K, Aga TM, Zewdu FT, Simegn GL. Automatic skin disease diagnosis using deep learning from clinical image and patient information. Skin Health Dis. 2021;2(1):e81. https://doi.org/10.1002/ski2.81
45. Busard CI, Cohen AD, Wolf P, Gkalpakiotis S, Cazzaniga S, Stern RS, Hutten BA, Feldhamer I, Quehenberger F, Lichem R, Kojanova M, Adenubiova E, Addis A, Naldi L, Spuls PI. Biologics combined with systemic agents in psoriasis: real-life data. J Eur Acad Dermatol Venereol. 2018;32(2):245-253.
https://doi.org/ 10.1111/jdv.14583
46. Yin H, Chen H, Zhang W, Zhang J, Cui T, Li Y, Yu N, Yu Y, Long H, Xiao R, Su Y, Li Y, Zhang G, Tan Y, Wu H, Lu Q. Image-based remote evaluation of PASI scores using YOLO-v4. Exp Dermatol. 2024;33(4):e15082.
https://doi.org/10.1111/exd.15082
47. Singh A, Sinha DK, Dhanda N. Impact of image classification in dermatology. In: Emerging Technologies for Computing, Communication and Smart Cities. Singapore: Springer; 2022. p. 671-681.
https://doi.org/10.1007/978-981-16-6202-6_53
48. Verschoore M, Dlova N. Advances in dermatology in sub-Saharan Africa. 2022;61(7):841-847.
https://doi.org/10.1111/ijd.16073
49. Dvornikov AS, Minkina OV, Grebenshchikova E, Vvedenskaya ER, Mylnikova I. Dermatology and telemedicine: goals, advantages and disadvantages. Bull RSMU. 2021;(4):5-9.
50. Rutter KJ, Ashraf I, Cordingley L, Rhodes LE. Quality of life in photodermatoses: a systematic review. Br J Dermatol. 2020;182(5):1092-1102.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Б.У. Кенжебаева, М.А. Баймуратова , С.Б. Калмаханов , Д.Б. Абдукаликова , Б.И. Имашева
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The articles published in this Journal are licensed under the CC BY-NC-ND 4.0 (Creative Commons Attribution – Non-Commercial – No Derivatives 4.0 International) license, which provides for their non-commercial use only. Under this license, users have the right to copy and distribute the material in copyright but are not permitted to modify or use it for commercial purposes. Full details on the licensing are available at https://creativecommons.org/licenses/by-nc-nd/4.0/.
