Partnership dynamics in mathematical models and implications for representation of sexually transmitted infections: a review

A Review of Network Models for HIV Spread

BACKGROUND

HIV/AIDS has been a global health crisis for over 4 decades. Network models, which simulate human behavior and intervention impacts, have become an essential tool in guiding HIV prevention strategies and policies. However, no comprehensive survey of network models in HIV research has been conducted. This article fills that gap, offering a summary of past work and future directions to engage more researchers and inform policy related to eliminating HIV.

SETTING

Network models explicitly represent interactions between individuals, making them well-suited to study HIV transmission dynamics. Two primary modeling paradigms exist: a mechanistic approach from applied mathematics and a statistical approach from the social sciences. Each has distinct strengths and weaknesses, which should be understood for effective application to HIV research.

METHODS

We conducted a systematic review of network models used in HIV research, detailing the model types, populations, interventions, behaviors, datasets, and software used, while identifying potential future research directions.

RESULTS

Network models are particularly valuable for studying behaviors central to HIV transmission, such as partner selection and treatment adherence. Unlike traditional models, they focus on individual behaviors, aligning them with clinical practice. However, more accurate network data are needed for better model calibration and actionable insights.

CONCLUSIONS

This article serves as a point of reference for HIV researchers interested in applying network models and understanding their limitations. To our knowledge, this is the most comprehensive review of HIV network models to date.

Modelling the role of tourism in the spread of HIV: A case study from Malaysia

This study aimed to assess the role of tourism in the spread of human immunodeficiency virus (HIV) using Malaysian epidemiological data on HIV and acquired immunodeficiency syndrome (AIDS) incidence from 1986 to 2004. A population-level mathematical model was developed with the following compartments: the population susceptible to HIV infection, the clinically confirmed HIV-positive population, the population diagnosed with AIDS, and the tourist population. Additionally, newborns infected with HIV were considered. Sensitivity analyses and variations in fixed parameter values were used to explore the effect of changes to various parameter values on HIV incidence in the model. It was determined that variations in the rate of HIV-positive inbound tourist entries and the rate of foreign tourist exits (i.e., the duration of time tourists spent in Malaysia) significantly impacted the predicted incidence of HIV and AIDS in Malaysia. The model's fit to observed HIV and AIDS incidence was evaluated, resulting in adjusted R2 values of 53.3% and 53.2% for HIV and AIDS, respectively. Furthermore, the reproduction number (R0) was also calculated to quantify the stability of the HIV endemicity in Malaysia. The findings suggest that a steady-state level of HIV in Malaysia is achievable based on the low value ofR 0  = 0.0136, and the disease-free equilibrium was stable from the negative eigenvalues obtained, which is encouraging from a public health perspective. The Partial Rank Correlation Coefficient (PRCC) values between the proportion of newborns born HIV-positive, the rate of Malaysian tourist entries returning home after contracting HIV, and the rate of foreign tourist exits have a significant impact on theR 0 . The methods provide a framework for epidemiological modelling of HIV spread through transient population groups. The model results suggest that the role of tourism should not be overlooked within the set of available measures to mitigate the spread of HIV.

Development of a predictive machine learning model for pathogen profiles in patients with secondary immunodeficiency

BACKGROUND

Secondary immunodeficiency can arise from various clinical conditions that include HIV infection, chronic diseases, malignancy and long-term use of immunosuppressives, which makes the suffering patients susceptible to all types of pathogenic infections. Other than HIV infection, the possible pathogen profiles in other aetiology-induced secondary immunodeficiency are largely unknown.

METHODS

Medical records of the patients with secondary immunodeficiency caused by various aetiologies were collected from the First Affiliated Hospital of Nanchang University, China. Based on these records, models were developed with the machine learning method to predict the potential infectious pathogens that may inflict the patients with secondary immunodeficiency caused by various disease conditions other than HIV infection.

RESULTS

Several metrics were used to evaluate the models' performance. A consistent conclusion can be drawn from all the metrics that Gradient Boosting Machine had the best performance with the highest accuracy at 91.01%, exceeding other models by 13.48, 7.14, and 4.49% respectively.

CONCLUSIONS

The models developed in our study enable the prediction of potential infectious pathogens that may affect the patients with secondary immunodeficiency caused by various aetiologies except for HIV infection, which will help clinicians make a timely decision on antibiotic use before microorganism culture results return.

Rates of sexual partner acquisition from nationally representative surveys: variation between countries and by age, sex, wealth, partner and HIV status

BACKGROUND

Knowing levels and determinants of partnership acquisition will help inform interventions that try to reduce transmission of sexually transmitted infections (STIs) including HIV.

METHODS

We used population-based, cross-sectional data from 47 Demographic and Health Surveys to calculate rates of partner acquisition among men and women (15-49years), and identified socio-demographic correlates for partner acquisition. Partner acquisition rates were estimated as the total number of acquisitions divided by the person-time in the period covered by the survey. For each survey and by sex, we estimated age-specific partner acquisition rates and used age-adjusted piecewise exponential survival models to explore whether there was any association between wealth, HIV status and partner status with partner acquisition rates.

RESULTS

Across countries, the median partner acquisition rates were 30/100 person-years for men (interquartile range 21-45) and 13/100 person-years for women (interquartile range 6-18). There were substantial variations in partner acquisition rates by age. Associations between wealth and partner acquisition rates varied across countries. People with a cohabiting partner were less likely to acquire a new one, and this effect was stronger for women than men and varied substantially between countries. Women living with HIV had higher partner acquisition rates than HIV-negative women but this association was less apparent for men. At a population level, partner acquisition rates were correlated with HIV incidence.

CONCLUSIONS

Partner acquisition rates are variable and are associated with important correlates of STIs and thus could be used to identify groups at high risk of STIs.

Changes in Sexual Behaviors with Opposite-Sex Partners and Sexually Transmitted Infection Outcomes Among Females and Males Ages 15-44 Years in the USA: National Survey of Family Growth, 2008-2019

Rates of reported gonorrhea and chlamydial infections have increased substantially over the past decade in the USA and disparities persist across age and race/ethnicity. We aimed to understand potential changes in sexual behaviors, sexual network attributes, and sexually transmitted infection (STI) screening that may be contributing to these trends. We analyzed data from 29,423 female and 24,605 male respondents ages 15-44 years from the National Survey of Family Growth, 2008-2019. We used survey-weighted linear or logistic regression to evaluate linear temporal trends in sexual behaviors with opposite-sex partners, network attributes, and STI testing, treatment, and diagnosis. Significant declines were observed in condom use at last vaginal sex, mean number of vaginal sex acts, proportion of condom-protected sex acts in the past 4 weeks, and racial/ethnic homophily with current partners among males and females from 2008-2010 through 2017-2019. Among males, mean number of female partners in the past 12 months and concurrency also declined, while the percent reporting ever having sex with another male increased. Past-year testing for chlamydia and any STI increased among females. Research is needed to understand how these changes interact and potentially contribute to increasing reported gonorrhea and chlamydia diagnoses and identify avenues for future intervention.