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TropicalMed
Special Issues
HIV Testing and Antiretroviral Therapy
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HIV Testing and Antiretroviral Therapy

A special issue of Tropical Medicine and Infectious Disease (ISSN 2414-6366).

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1282

Special Issue Editor

Dr. Mohamed Mahdi

E-Mail Website
Guest Editor
1. Laboratory of Retroviral Biochemistry, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
2. Clinical Department of Infectology, University of Debrecen Clinical Centre, 4031 Debrecen, Hungary
Interests: HIV-1; HIV-2; SARS-CoV-2; viral integration; dual infection; antiviral therapy

Special Issue Information

Dear Colleagues,

It has now been over four decades since the discovery of human immunodeficiency virus (HIV). Since then, groundbreaking scientific achievements have allowed the infection to shift from a fatal disease to a more manageable chronic condition, with a significant reduction in morbidity and mortality rates. This has mostly been accomplished through the advancement of antiretroviral therapy (ART). Ongoing research and efforts are focused on optimizing treatment regimens, improving adherence, combating treatment-associated resistance, and exploring long-acting ART formulations in order to enhance quality of life and treatment outcomes. Moreover, early and accurate testing has enabled timely diagnosis and the prevention of further transmission. Innovative community-based approaches and self-testing strategies are being developed to overcome barriers to healthcare access and avoid stigma, as well as limiting the transmission of infection, particularly in disadvantaged populations. Furthermore, integrating testing and ART services into broader healthcare initiatives is critical in addressing inequities and achieving the UNAIDS 95-95-95 targets. This Special Issue will feature extensive reviews, research articles, and commentaries on the topic of ART, new potential inhibitors, and the efficacy of current drugs, especially in the context of resistant mutations and confined HIV groups, as well as HIV-2, novel diagnostic approaches, and epidemiologic studies.

Dr. Mohamed Mahdi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Tropical Medicine and Infectious Disease is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • HIV diagnosis
  • diagnostic innovations in HIV
  • antiretroviral therapy
  • ART drug resistance
  • novel antiretrovirals
  • rapid diagnostic tests
  • HIV/AIDS epidemiology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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32 pages, 4050 KiB  
Article
The Application of Machine Learning Algorithms to Predict HIV Testing Using Evidence from the 2002–2017 South African Adult Population-Based Surveys: An HIV Testing Predictive Model
by Musa Jaiteh, Edith Phalane, Yegnanew A. Shiferaw, Haruna Jallow and Refilwe Nancy Phaswana-Mafuya
Trop. Med. Infect. Dis. 2025, 10(6), 167; https://doi.org/10.3390/tropicalmed10060167 - 14 Jun 2025
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Abstract
There is a significant portion of the South African population with unknown HIV status, which slows down epidemic control despite the progress made in HIV testing. Machine learning (ML) has been effective in identifying individuals at higher risk of HIV infection, for whom [...] Read more.
There is a significant portion of the South African population with unknown HIV status, which slows down epidemic control despite the progress made in HIV testing. Machine learning (ML) has been effective in identifying individuals at higher risk of HIV infection, for whom testing is strongly recommended. However, there are insufficient predictive models to inform targeted HIV testing interventions in South Africa. By harnessing the power of supervised ML (SML) algorithms, this study aimed to identify the most consistent predictors of HIV testing in repeated adult population-based surveys in South Africa. The study employed four SML algorithms, namely, decision trees, random forest, support vector machines (SVM), and logistic regression, across the five cross-sectional cycles of the South African National HIV Prevalence, Incidence, and Behavior and Communication Survey (SABSSM) datasets. The Human Science Research Council (HSRC) conducted the SABSSM surveys and made the datasets available for this study. Each dataset was split into 80% training and 20% testing sets with a 5-fold cross-validation technique. The random forest outperformed the other models across all five datasets with the highest accuracy (80.98%), precision (81.51%), F1-score (80.30%), area under the curve (AUC) (88.31%), and cross-validation average (79.10%) in the 2002 data. Random forest achieved the highest classification performance across all the dates, especially in the 2017 survey. SVM had a high recall (89.12% in 2005, 86.28% in 2008) but lower precision, leading to a suboptimal F1-score in the initial analysis. We applied a soft margin to the SVM to improve its classification robustness and generalization, but the accuracy and precision were still low in most surveys, increasing the chances of misclassifying individuals who tested for HIV. Logistic regression performed well in terms of accuracy = 72.75, precision = 73.64, and AUC = 81.41 in 2002, and the F1-score = 73.83 in 2017, but its performance was somewhat lower than that of the random forest. Decision trees demonstrated moderate accuracy (73.80% in 2002) but were prone to overfitting. The topmost consistent predictors of HIV testing are knowledge of HIV testing sites, being a female, being a younger adult, having high socioeconomic status, and being well-informed about HIV through digital platforms. Random forest’s ability to analyze complex datasets makes it a valuable tool for informing data-driven policy initiatives, such as raising awareness, engaging the media, improving employment outcomes, enhancing accessibility, and targeting high-risk individuals. By addressing the identified gaps in the existing healthcare framework, South Africa can enhance the efficacy of HIV testing and progress towards achieving the UNAIDS 2030 goal of eradicating AIDS. Full article
(This article belongs to the Special Issue HIV Testing and Antiretroviral Therapy)
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7 pages, 1848 KiB  
Case Report
Unmasking Bacillus Calmette–Guérin Immune Reconstitution Inflammatory Syndrome in a Perinatal HIV Transmission—A Case Report
by Daniel Ivanov, Dimitar Strashimirov, Rusina Grozdeva, Evgeni Penchev, Elena Georgieva and Nina Yancheva
Trop. Med. Infect. Dis. 2025, 10(6), 148; https://doi.org/10.3390/tropicalmed10060148 - 23 May 2025
Viewed by 525
Abstract
Bacillus Calmette–Guérin (BCG)-related immune reconstitution inflammatory syndrome (IRIS) is a recognised complication following antiretroviral therapy (ART) initiation in HIV-infected infants. We report the case of a 19-month-old child with undiagnosed perinatally acquired HIV due to maternal nondisclosure. The child developed ipsilateral axillary lymphadenitis [...] Read more.
Bacillus Calmette–Guérin (BCG)-related immune reconstitution inflammatory syndrome (IRIS) is a recognised complication following antiretroviral therapy (ART) initiation in HIV-infected infants. We report the case of a 19-month-old child with undiagnosed perinatally acquired HIV due to maternal nondisclosure. The child developed ipsilateral axillary lymphadenitis at the BCG vaccination site shortly after starting ART. The clinical features and temporal association with ART supported a diagnosis of BCG-IRIS. The child was successfully managed with conservative pharmacological treatment alone—rifampicin, isoniazid, and macrolide therapy—without surgical incision or corticosteroids. Progressive improvement of the lesion was observed, and complete clinical resolution occurred over the following months, alongside immune recovery. This case underscores the importance of recognising BCG-IRIS, even in settings where HIV diagnosis may be delayed, and supports the feasibility of conservative management in paediatric patients, potentially avoiding surgical intervention in settings of localised disease. Full article
(This article belongs to the Special Issue HIV Testing and Antiretroviral Therapy)
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