Rate and predictors of loss to follow-up in HIV care in a low-resource setting: analyzing critical risk periods

By identifying when HIV-positive individuals are most at risk of dropping out, healthcare providers can create better strategies to keep more people engaged in their treatment—and ultimately, help reduce the spread of HIV.

Published in Biomedical Research

Rate and predictors of loss to follow-up in HIV care in a low-resource setting: analyzing critical risk periods
Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Explore the Research

BioMed Central
BioMed Central BioMed Central

Rate and predictors of loss to follow-up in HIV care in a low-resource setting: analyzing critical risk periods - BMC Infectious Diseases

Background Patient loss-to-follow-up (LTFU) in HIV care is a major challenge, especially in low-resource settings. Although the literature has focused on the total rate at which patients disengage from care, it has not sufficiently examined the specific risk periods during which patients are most likely to disengage from care. By addressing this gap, researchers and healthcare providers can develop more targeted interventions to improve patient engagement in HIV care. Methods We conducted a retrospective cohort study on newly enrolled adult HIV patients at seven randomly selected high-volume health facilities in Ethiopia from May 2022 to April 2024. Data analysis was performed using SPSS version 26, with a focus on the incidence rate of LTFU during the critical risk periods. Cumulative hazard analysis was used to compare event distributions, whereas a Poisson regression model was used to identify factors predicting LTFU, with statistical significance set at p < 0.05. Results The analysis included 737 individuals newly enrolled in HIV care; 165 participants (22.4%, 95% CI: 19.5–25.2) were LTFU by the end of two years, of which 50.1% occurred within the first 6 months, 29.7% within 7–12 months, and 19.4% from 13 to 24 months on ART. The overall incidence rate of LTFU was 18.3 per 1,000 PMO (95% CI: 15.9–20.6), with rates of 167.7 in the first 6 months, 55.4 in 7–12 months, and 18.1 in 13–24 months. Incomplete addresses lacking a phone number or location information (IRR: 1.61; 95% CI: 1.14, 2.27) and poor adherence (IRR: 1.78; 95% CI: 1.28, 2.48) were factors predicting the incidence rate of LTFU. Conclusion LTFU peaked in the first 6 months, accounting for approximately half of total losses, remained elevated from months 7–12, and stabilized after the first year of HIV care and treatment. Address information and adherence were predictors of LTFU. To effectively minimize LTFU, efforts should focus on intensive support during the first six months of care, followed by sustained efforts and monitoring in the next six months. Our findings highlight a critical period for targeted interventions to reduce LTFU in HIV care.

Why Do Some People Stop HIV Treatment? Understanding the Key Moments

In the global fight against HIV, keeping people engaged in their treatment is crucial. Even though many countries aim to meet ambitious HIV care goals by 2030, a significant challenge remains: helping those who start HIV treatment continue their care and keep their virus under control. A big part of this challenge is what’s known as "loss to follow-up" (LTFU).

What is Loss to Follow-Up (LTFU)?

LTFU happens when someone on HIV treatment misses their medical appointments or stops taking their medication for over 28 days. This is a serious issue, as it can lead to poorer health, increased risk of death, and a higher chance of spreading HIV to others because the virus isn’t being suppressed.

When Do People Stop Treatment?

This study looked at 737 adults who were new to HIV care and identified the times when they were most likely to stop their treatment:

  • The First 6 Months Are Critical: About 50% of the people who dropped out of care did so within the first six months. This early period is a high-risk time, with an LTFU rate nine times higher than later periods (13-24 months). People might face challenges like dealing with side effects, struggling to adjust to a new routine, or not yet seeing the benefits of the medication.
  • 7-12 Months: A Continued Risk: Even though the risk of dropping out decreases after the first six months, many people still struggle to stick with their treatment during months 7-12. About 30% of those who stopped care did so during this time. Factors like financial difficulties, stigma, or transportation issues can continue to affect them.
  • After 12 Months: A More Stable Phase: After a year on treatment, the dropout rate drops significantly. By this time, many patients have adjusted to their routine, seen improvements in their health, and are more committed to their treatment.

What Can We Do About It?

The findings suggest that the first six months of HIV treatment are a make-or-break time. Health programs should focus on providing extra support during this period, such as helping patients manage side effects and offering counseling. Continued support is also important in the following months to help people overcome challenges that might come up later.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Follow the Topic

HIV infections
Life Sciences > Health Sciences > Biomedical Research > Pathogenesis > Infection > Infectious Diseases > HIV infections

Related Collections

With Collections, you can get published faster and increase your visibility.

The rise of invasive fungal infections: diagnostics, antifungal stewardship, prophylaxis, and genetics

BMC Infectious Diseases is calling for submissions to our Collection on The rise of invasive fungal infections: diagnostics, antifungal stewardship, prophylaxis, and genetics.

In recent years, the incidence of invasive fungal infections (IFI) has shown a concerning upward trend, presenting a formidable challenge in clinical settings worldwide. This Collection aims to explore multidimensional aspects crucial for understanding and combating these infections. We invite submissions that explore a wide array of topics within the scope of IFI, including but not limited to:

- Diagnostics: advances in fungal diagnostics, including novel biomarkers, imaging modalities, and molecular techniques, are pivotal for timely and accurate identification of fungal pathogens

- Antifungal stewardship: the prudent use of antifungal agents to mitigate resistance and optimize patient outcomes, and strategies for stewardship (including surveillance, guidelines, and therapeutic drug monitoring)

- Antifungal prophylaxis: effective prophylactic measures in high-risk patient populations (examining prophylactic regimens, their efficacy, and impact on patient outcomes)

- Host and pathogen genetics: understanding the genetic factors influencing both host susceptibility and fungal virulence, and research on genetic markers, host-pathogen interactions, and implications for personalized treatment approaches

- Fungal genetics: insights into fungal genome characteristics, evolution, and mechanisms of resistance, and research exploring fungal genetic diversity, adaptation, and transmission dynamics

- Imaging: imaging technologies that contribute significantly to the diagnosis and management of invasive fungal infections, their clinical utility, and integration with diagnostic algorithms

This Collection aims to foster a dialogue among researchers, clinicians, and healthcare providers on the complexities surrounding IFI. This Collection supports and amplifies research related to SDG 3: Good Health & Well-being.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.

Publishing Model: Open Access

Deadline: Feb 28, 2026

Cutting-edge diagnostics for infectious diseases: emerging technologies and approaches

BMC Infectious Diseases invites submissions for a Collection on Cutting-edge diagnostics for infectious diseases.

The field of diagnostics for infectious diseases is rapidly evolving, driven by the need for timely and accurate detection methods. Traditional diagnostic techniques often fall short in terms of speed and sensitivity, highlighting a pressing need for innovative solutions. Recent advances in technologies such as molecular diagnostics, biosensors, and next-generation sequencing are paving the way for more efficient and reliable testing methodologies. These emerging approaches have the potential to revolutionize the identification of pathogens, enabling faster clinical decision-making and improving patient outcomes.

Addressing the challenges posed by infectious diseases is critical, particularly in an era marked by global health crises and the rise of antimicrobial resistance. The development and implementation of rapid diagnostic tools can facilitate timely interventions, ultimately reducing morbidity and mortality rates. As researchers and healthcare professionals work collaboratively, significant strides have been made in understanding the complexities of infectious diseases. This includes the adaptation of point-of-care testing technologies that bring laboratory capabilities closer to patients, thus enhancing the capacity for early diagnosis and treatment.

If current research trends continue, we may see transformative advancements that integrate artificial intelligence and machine learning into diagnostic processes. Such innovations could lead to the creation of smart diagnostics that not only detect infections with high accuracy but also provide real-time surveillance data. Future technologies may enable rapid identification of emerging pathogens, thus enhancing public health response strategies and mitigating outbreaks before they escalate.

- Advances in molecular diagnostics for infectious diseases

- Innovations in rapid diagnostic testing

- Applications of next-generation sequencing in pathogen detection

- Biosensors for real-time infectious disease monitoring

- Point-of-care testing technologies and their impact

This Collection supports and amplifies research related to SDG 3: Good Health and Well-being.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.

Publishing Model: Open Access

Deadline: Jan 31, 2026