{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T03:32:07Z","timestamp":1772163127704,"version":"3.50.1"},"reference-count":52,"publisher":"American Society for Microbiology","issue":"2","license":[{"start":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T00:00:00Z","timestamp":1707177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T00:00:00Z","timestamp":1707177600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"funder":[{"name":"MEC | Instituto de Salud Carlos III","award":["PI20\/01397"],"award-info":[{"award-number":["PI20\/01397"]}]},{"DOI":"10.13039\/501100007245","name":"Fundaci\u00f3n para el Conocimiento Madri+d","doi-asserted-by":"crossref","award":["AVATAR-EPAMEC"],"award-info":[{"award-number":["AVATAR-EPAMEC"]}],"id":[{"id":"10.13039\/501100007245","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["Microbiol Spectr"],"published-print":{"date-parts":[[2024,2,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    The epidemiology of sexually transmitted infections (STIs) is complex due to the coexistence of various pathogens, the variety of transmission modes derived from sexual orientations and behaviors at different ages and genders, and sexual contact hotspots resulting in network transmission. There is also a growing proportion of recreational drug users engaged in high-risk sexual activities, as well as pharmacological self-protection routines fostering non-condom practices. The frequency of asymptomatic patients makes it difficult to develop a comprehensive approach to STI epidemiology. Modeling approaches are required to deal with such complexity. Membrane computing is a natural computing methodology for the virtual reproduction of epidemics under the influence of deterministic and stochastic events with an unprecedented level of granularity. The application of the LOIMOS program to STI epidemiology illustrates the possibility of using it to shape appropriate interventions. Under the conditions of our basic landscape, including sexual hotspots of individuals with various risk behaviors, an increase in condom use reduces STIs in a larger proportion of heterosexuals than in same-gender sexual contacts and is much more efficient for reducing\n                    <jats:italic>Neisseria gonorrhoeae<\/jats:italic>\n                    than\n                    <jats:italic>Chlamydia<\/jats:italic>\n                    and lymphogranuloma venereum infections. Amelioration from diagnostic STI screening could be instrumental in reducing\n                    <jats:italic>N. gonorrhoeae<\/jats:italic>\n                    infections, particularly in men having sex with men (MSM), and\n                    <jats:italic>Chlamydia trachomatis<\/jats:italic>\n                    infections in the heterosexual population; however, screening was less effective in decreasing lymphogranuloma venereum infections in MSM. The influence of STI epidemiology of sexual contacts between different age groups (&lt;35 and \u226535 years) and in bisexual populations was also submitted for simulation.\n                  <\/jats:p>\n                  <jats:sec>\n                    <jats:title>IMPORTANCE<\/jats:title>\n                    <jats:p>The epidemiology of sexually transmitted infections (STIs) is complex and significantly influences sexual and reproductive health worldwide. Gender, age, sexual orientation, sexual behavior (including recreational drug use and physical and pharmacological protection practices), the structure of sexual contact networks, and the limited application or efficiency of diagnostic screening procedures create variable landscapes in different countries. Modeling techniques are required to deal with such complexity. We propose the use of a simulation technology based on membrane computing, mimicking in silico STI epidemics under various local conditions with an unprecedented level of detail. This approach allows us to evaluate the relative weight of the various epidemic drivers in various populations at risk and the possible outcomes of interventions in particular epidemiological landscapes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1128\/spectrum.02728-23","type":"journal-article","created":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T09:01:06Z","timestamp":1704877266000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":3,"title":["Membrane computing simulation of sexually transmitted bacterial infections in hotspots of individuals with various risk behaviors"],"prefix":"10.1128","volume":"12","author":[{"given":"Marcelino","family":"Campos","sequence":"first","affiliation":[{"name":"Department of Microbiology, Ram\u00f3n y Cajal University Hospital, IRYCIS, Madrid, Spain"},{"name":"Valencian Research Institute for Artificial Intelligence (VRAIN), Polytechnic University of Valencia, Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8447-0960","authenticated-orcid":false,"given":"Juan Carlos","family":"Gal\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Ram\u00f3n y Cajal University Hospital, IRYCIS, Madrid, Spain"},{"name":"Center for Biomedical Research in Epidemiology and Public Health Network (CIBERESP) Madrid, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mario","family":"Rodr\u00edguez-Dom\u00ednguez","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Ram\u00f3n y Cajal University Hospital, IRYCIS, Madrid, Spain"},{"name":"Center for Biomedical Research in Epidemiology and Public Health Network (CIBERESP) Madrid, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 M.","family":"Sempere","sequence":"additional","affiliation":[{"name":"Valencian Research Institute for Artificial Intelligence (VRAIN), Polytechnic University of Valencia, Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos","family":"Llorens","sequence":"additional","affiliation":[{"name":"Biotechvana, Valencia, Scientific Park University of Valencia, Paterna, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7930-3033","authenticated-orcid":true,"given":"Fernando","family":"Baquero","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Ram\u00f3n y Cajal University Hospital, IRYCIS, Madrid, Spain"},{"name":"Center for Biomedical Research in Epidemiology and Public Health Network (CIBERESP) Madrid, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"235","reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41564-022-01177-x"},{"key":"e_1_3_3_3_2","volume-title":"Global health sector strategies on, respectively, HIV, viral hepatitis and sexually transmitted infections for the period 2022-2030","author":"World Health Organization","year":"2022","unstructured":"World Health Organization. 2022. 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