Human Immunodeficiency Virus Transmission Dynamics Research Articles

Modelling and analysis of an HIV model with control strategies and cost-effectiveness

The Human Immunodeficiency Virus (HIV) remains a significant public health concern, despite global efforts to reduce new infections and increase access to antiretroviral treatment. While pre-exposure prophylaxis (PrEP) has shown promise in reducing new infections, its overall effectiveness is hindered by challenges in adherence. In this paper, a novel model was proposed. The basic properties of the model were established and the reproduction number for the model without control was computed. We conducted a sensitivity analysis to highlight the need for optimal control analysis and hence proposed an optimal control model that incorporates PrEP, condom use, and antiretroviral treatment to capture the dynamics of HIV transmission. The existence of the optimal control was mathematically proven and Pontryagin’s maximum principle was employed to establish the necessary optimal control conditions. Utilizing demographic and epidemiological parameters specific to South Africa, we conducted numerical simulations. The results demonstrate the community-level benefits of implementing a combination of control measures for HIV reduction. Additionally, a cost-effectiveness analysis was performed to determine the most effective and economically viable control strategies. We anticipate that the findings from this analysis will provide valuable insights for policymakers in designing effective HIV control programmes.

When Bacteria and Viruses Collide: A Tale of Chlamydia trachomatis and Sexually Transmitted Viruses.

The global incidence of sexually transmitted infections (STIs) remains high, with the World Health Organization (WHO) estimating that over 1 million people acquire STIs daily. STIs can lead to infertility, pregnancy complications, and cancers. Co-infections with multiple pathogens are prevalent among individuals with an STI and can lead to heightened infectivity and more severe clinical manifestations. Chlamydia trachomatis (CT) is the most reported bacterial STI worldwide in both men and women, and several studies have demonstrated co-infection of CT with viral and other bacterial STIs. CT is a gram-negative bacterium with a unique biphasic developmental cycle including infectious extracellular elementary bodies (EBs) and metabolically active intracellular reticulate bodies (RBs). The intracellular form of this organism, RBs, has evolved mechanisms to persist for long periods within host epithelial cells in a viable but non-cultivable state. The co-infections of CT with the most frequently reported sexually transmitted viruses: human immunodeficiency virus (HIV), human papillomavirus (HPV), and herpes simplex virus (HSV) have been investigated through in vitro and in vivo studies. These research studies have made significant strides in unraveling the intricate interactions between CT, these viral STIs, and their eukaryotic host. In this review, we present an overview of the epidemiology of these co-infections, while specifically delineating the underlying mechanisms by which CT influences the transmission and infection dynamics of HIV and HSV. Furthermore, we explore the intricate relationship between CT and HPV infection, with a particular emphasis on the heightened risk of cervical cancer. By consolidating the current body of knowledge, we provide valuable insights into the complex dynamics and implications of co-infection involving CT and sexually transmitted viruses.

Dynamical behavior of a stochastic HIV model with logistic growth and Ornstein-Uhlenbeck process

In this paper, we investigate a stochastic human immunodeficiency virus (HIV) model with logistic growth and Ornstein-Uhlenbeck process, which is used to describe the pathogenesis and transmission dynamics of HIV in the population. We first validate that the stochastic system has a unique global solution with any initial value. Then we use a novel Lyapunov function method to establish sufficient conditions for the existence of a stationary distribution of the system, which shows the coexistence of all CD4+ T cells and free viruses. Especially, under some mild conditions which are used to ensure the local asymptotic stability of the quasi-chronic infection equilibrium of the stochastic system, we obtain the specific expression of covariance matrix in the probability density around the quasi-chronic infection equilibrium of the stochastic system. In addition, for completeness, we also obtain sufficient criteria for elimination of all infected CD4+ T cells and free virus particles. Finally, several examples together with comprehensive numerical simulations are conducted to support our analytic results.

Spatial heterogeneity of risk factors associated with HIV prevalence among men who inject drugs in India: An analysis of the data from the integrated bio-behavioral surveillance, India

People who inject drugs (PWID) are India's third-largest vulnerable population to human immunodeficiency virus (HIV) infection. PWID in India are confined to certain geographic locations and exhibit varying injecting and sexual risk behaviors, contributing considerably to increasing HIV trends in specific regions. Spatial heterogeneity in risk factors among vulnerable PWID influences HIV prevalence, transmission dynamics, and disease management. Stratified analysis of HIV prevalence based on risk behaviors and geographic locations of PWID will be instrumental in strategic interventions. To stratify the male PWID based on their risk behaviors in each state and determine the HIV prevalence for each stratum. The behavioral data and HIV prevalence of the national integrated biological and behavioural surveillance (IBBS), a nationwide cross-sectional community-based study conducted in 2014 to 2015, was analyzed. Data from 19,902 men who inject drugs across 53 domains in 29 states of India were included. Women who inject drugs were excluded at the time of IBBS, and hence PWID in this study refers to only men who inject drugs. PWID were categorized based on their risk profile, and the corresponding HIV prevalence for each state was determined. HIV prevalence was the highest (29.6%) in Uttar Pradesh, with a high prevalence of risk behaviors among PWID. High HIV prevalence ranging between 12.1% and 22.4% was observed in a few states in East and North-East India and most states in central and North India. Unsafe injecting and sexual practices were significantly (P < .05) associated with higher HIV prevalence and more significantly in National Capital Territory of Delhi (P < .001). Unsafe injecting practices among PWID were proportionally higher in Western and Central India, whereas unsafe sexual behaviors were widespread among most states. Unsafe sexual practices among male PWID were common. The high prevalence of unsafe injecting had significant HIV infection and transmission risks in Western and Central India. The results emphasize the need for stratified, region-specific interventions and combination approaches for harm reduction among PWID. Strengthening the measures that facilitate the reduction of high-risk behaviors, adoption of safe practices, and utilization of HIV services will positively impact HIV prevention measures among PWID.

Epidemiological Characteristics and Transmissibility of Human Immunodeficiency Virus in Nanning City, China, 2001-2020.

Background: Human immunodeficiency virus (HIV) is a single-stranded RNA virus that can weaken the body's cellular and humoral immunity and is a serious disease without specific drug management and vaccine. This study aimed to evaluate the epidemiologic characteristics and transmissibility of HIV.Methods: Data on HIV follow-up were collected in Nanning City, Guangxi Zhuang Autonomous, China. An HIV transmission dynamics model was built to simulate the transmission of HIV and estimate its transmissibility by comparing the effective reproduction number (Reff) at different stages: the rapid growth period from January 2001 to March 2005, slow growth period from April 2005 to April 2011, and the plateau from May 2011 to December 2019 of HIV in Nanning City.Results: High-risk areas of HIV prevalence in Nanning City were mainly concentrated in suburbs. Furthermore, high-risk groups were those of older age, with lower income, and lower education levels. The Reff in each stage (rapid growth, slow growth, and plateau) were 2.74, 1.62, and 1.15, respectively, which suggests the transmissibility of HIV in Nanning City has declined and prevention and control measures have achieved significant results.Conclusion: Over the past 20 years, the HIV incidence in Nanning has remained at a relatively high level, but its development trend has been curbed. Transmissibility was reduced from 2.74 to 1.15. Therefore, the prevention and treatment measures in Nanning City have achieved significant improvement.

Modelling the geographical spread of HIV among MSM in Guangdong, China: a metapopulation model considering the impact of pre-exposure prophylaxis.

Men who have sex with men (MSM) make up the majority of new human immunodeficiency virus (HIV) diagnoses among young people in China. Understanding HIV transmission dynamics among the MSM population is, therefore, crucial for the control and prevention of HIV infections, especially for some newly reported genotypes of HIV. This study presents a metapopulation model considering the impact of pre-exposure prophylaxis (PrEP) to investigate the geographical spread of a hypothetically new genotype of HIV among MSM in Guangdong, China. We use multiple data sources to construct this model to characterize the behavioural dynamics underlying the spread of HIV within and between 21 prefecture-level cities (i.e. Guangzhou, Shenzhen, Foshan, etc.) in Guangdong province: the online social network via a gay social networking app, the offline human mobility network via the Baidu mobility website, and self-reported sexual behaviours among MSM. Results show that PrEP initiation exponentially delays the occurrence of the virus for the rest of the cities transmitted from the initial outbreak city; hubs on the movement network, such as Guangzhou, Shenzhen, and Foshan are at a higher risk of ‘earliest’ exposure to the new HIV genotype; most cities acquire the virus directly from the initial outbreak city while others acquire the virus from cities that are not initial outbreak locations and have relatively high betweenness centralities, such as Guangzhou, Shenzhen and Shantou. This study provides insights in predicting the geographical spread of a new genotype of HIV among an MSM population from different regions and assessing the importance of prefecture-level cities in the control and prevention of HIV in Guangdong province.This article is part of the theme issue ‘Data science approach to infectious disease surveillance’.

Inferring HIV Transmission Network Determinants Using Agent-Based Models Calibrated to Multi-Data Sources

(1) Background: Calibration of Simpact Cyan can help to improve estimates related to the transmission dynamics of the Human Immunodeficiency Virus (HIV). Age-mixing patterns in sexual partnerships, onward transmissions, and temporal trends of HIV incidence are determinants which can inform the design of efficient prevention, and linkage-to-care programs. Using an agent-based model (ABM) simulation tool, we investigated, through a simulation study, if estimates of these determinants can be obtained with high accuracy by combining summary features from different data sources. (2) Methods: With specific parameters, we generated the benchmark data, and calibrated the default model in three scenarios based on summary features for comparison. For calibration, we used Latin Hypercube Sampling approach to generate parameter values, and Approximation Bayesian Computation to choose the best fitting ones. In all calibration scenarios the mean square root error was used as a measure to depict the estimates accuracy. (3) Results: The accuracy measure showed relatively no difference between the three scenarios. Moreover, we found that in all scenarios, age and gender strata incidence trends were poorly estimated. (4) Conclusions: Using synthetic benchmarks, we showed that it is possible to infer HIV transmission dynamics using an ABM of HIV transmission. Our results suggest that any type of summary feature provides adequate information to estimate HIV transmission network determinants. However, it is advisable to check the level of accuracy of the estimates of interest using benchmark data.

Bayesian multi-response nonlinear mixed-effect model: application of two recent HIV infection biomarkers.

Since the discovery of the human immunodeficiency virus (HIV) 35 years ago, the epidemic is still ongoing in France. To monitor the dynamics of HIV transmission and assess the impact of prevention campaigns, the main indicator is the incidence. One method to estimate the HIV incidence is based on biomarker values at diagnosis and their dynamics over time. Estimating the HIV incidence from biomarkers first requires modeling their dynamics since infection using external longitudinal data. The objective of the work presented here is to estimate the joint dynamics of two biomarkers from the PRIMO cohort. We thus jointly modeled the dynamics of two biomarkers (TM and V3) using a multi-response nonlinear mixed-effect model. The parameters were estimated using Bayesian Hamiltonian Monte Carlo inference. This procedure was first applied to the real data of the PRIMO cohort. In a simulation study, we then evaluated the performance of the Bayesian procedure for estimating the parameters of multi-response nonlinear mixed-effect models.

Human Immunodeficiency Virus (HIV) Drug Resistance, Phylogenetic Analysis, and Superinfection Among Men Who Have Sex with Men and Transgender Women in Sub-Saharan Africa: HIV Prevention Trials Network (HPTN) 075 Study

The HIV Prevention Trials Network (HPTN) 075 study evaluated the feasibility of enrolling and retaining men who have sex with men (MSM) and transgender women (TGW) from Kenya, Malawi, and South Africa. During the study follow-up, 21 participants acquired human immunodeficiency virus (HIV) (seroconverters). We analyzed HIV subtype diversity, drug resistance, transmission dynamics, and HIV superinfection data among MSM and TGW enrolled in HPTN 075. HIV genotyping and drug resistance testing were performed for participants living with HIV who had viral loads >400 copies/mL at screening (prevalent cases, n = 124) and seroconverters (n = 21). HIV pol clusters were identified using Cluster Picker. Superinfection was assessed by a longitudinal analysis of env and pol sequences generated by next-generation sequencing. HIV genotyping was successful for 123/124 prevalent cases and all 21 seroconverters. The major HIV subtypes were A1 (Kenya) and C (Malawi and South Africa). Major drug resistance mutations were detected in samples from 21 (14.6%) of 144 participants; the most frequent mutations were K103N and M184V/I. Phylogenetic analyses identified 11 clusters (2-6 individuals). Clusters included seroconverters only (n = 1), prevalent cases and seroconverters (n = 4), and prevalent cases only (n = 6). Superinfections were identified in 1 prevalent case and 2 seroconverters. The annual incidence of superinfection was higher among seroconverters than among prevalent cases, and was higher than the rate of primary HIV infection in the cohort. This report provides important insights into HIV genetic diversity, drug resistance, and superinfection among MSM and TGW in sub-Saharan Africa. These findings may help to inform future HIV prevention interventions in these high-risk groups.

Impact of Public Safety Policies on Human Immunodeficiency Virus Transmission Dynamics in Tijuana, Mexico.

North Tijuana, Mexico is home to many individuals at high risk for transmitting and acquiring human immunodeficiency virus (HIV). Recently, policy shifts by local government impacted how these individuals were handled by authorities. Here we examined how this affected regional HIV transmission dynamics. HIV pol sequences and associated demographic information were collected from 8 research studies enrolling persons in Tijuana and were used to infer viral transmission patterns. To evaluate the impact of recent policy changes on HIV transmission dynamics, qualitative interviews were performed on a subset of recently infected individuals. Between 2004 and 2016, 288 unique HIV pol sequences were obtained from individuals in Tijuana, including 46.4% from men who have sex with men, 42.1% from individuals reporting transactional sex, and 27.8% from persons who inject drugs (some individuals had >1 risk factor). Forty-two percent of sequences linked to at least 1 other sequence, forming 37 transmission clusters. Thirty-two individuals seroconverted during the observation period, including 8 between April and July 2016. Three of these individuals were putatively linked together. Qualitative interviews suggested changes in policing led individuals to shift locations of residence and injection drug use, leading to increased risk taking (eg, sharing needles). Near real-time molecular epidemiologic analyses identified a cluster of linked transmissions temporally associated with policy shifts. Interviews suggested these shifts may have led to increased risk taking among individuals at high risk for HIV acquisition. With all public policy shifts, downstream impacts need to be carefully considered, as even well-intentioned policies can have major public health consequences.

Incidence of Gonorrhea and Chlamydia Following Human Immunodeficiency Virus Preexposure Prophylaxis Among Men Who Have Sex With Men: A Modeling Study.

Preexposure prophylaxis (PrEP) is highly effective for preventing human immunodeficiency virus (HIV) infection, but risk compensation (RC) in men who have sex with men (MSM) raises concerns about increased sexually transmitted infections (STIs). The Center for Disease Control and Prevention's (CDC's) PrEP guidelines recommend biannual STI screening, which may reduce incidence by treating STIs that would otherwise remain undiagnosed. We investigated these two counteracting phenomena. With a network-based mathematical model of HIV, Neisseria gonorrhoeae (NG), and Chlamydia trachomatis (CT) transmission dynamics among MSM in the United States, we simulated PrEP uptake following the prescription indications and HIV/STI screening recommendations in the CDC guidelines. Scenarios varied PrEP coverage (the proportion of MSM indicated for PrEP who received it), RC (a reduction in the per-act probability of condom use), and the STI screening interval. In our reference scenario (40% coverage, 40% RC), 42% of NG and 40% of CT infections would be averted over the next decade. A doubling of RC would still result in net STI prevention relative to no PrEP. STIs declined because PrEP-related STI screening resulted in a 17% and 16% absolute increase in the treatment of asymptomatic and rectal STIs, respectively. Screening and timely treatment at quarterly vs biannual intervals would reduce STI incidence an additional 50%. Implementation of the CDC PrEP guidelines while scaling up PrEP coverage could result in a significant decline in STI incidence among MSM. Our study highlights the design of PrEP not only as antiretroviral medication but as combination HIV/STI prevention incorporating STI screening.

A Novel Modeling Approach for Estimating Patterns of Migration into and out of San Francisco by HIV Status and Race among Men Who Have Sex with Men.

In the early 1980s, men who have sex with men (MSM) in San Francisco were one of the first populations to be affected by the human immunodeficiency virus (HIV) epidemic, and they continue to bear a heavy HIV burden. Once a rapidly fatal disease, survival with HIV improved drastically following the introduction of combination antiretroviral therapy in 1996. As a result, the ability of HIV-positive persons to move into and out of San Francisco has increased due to lengthened survival. Although there is a high level of migration among the general US population and among HIV-positive persons in San Francisco, in- and out-migration patterns of MSM in San Francisco have, to our knowledge, never been described. Understanding migration patterns by HIV serostatus is crucial in determining how migration could influence both HIV transmission dynamics and estimates of the HIV prevalence and incidence. In this article, we describe methods, results, and implications of a novel approach for indirect estimation of in- and out-migration patterns, and consequently population size, of MSM by HIV serostatus and race in San Francisco. The results suggest that the overall MSM population and all the MSM subpopulations studied decreased in size from 2006 to 2014. Further, there were differences in migration patterns by race and by HIV serostatus. The modeling methods outlined can be applied by others to determine how migration patterns contribute to HIV-positive population size and output from these models can be used in a transmission model to better understand how migration can impact HIV transmission.

Detailed Knowledge About HIV Epidemiology and Transmission Dynamics and Their Associations With Preventive and Risk Behaviors Among Gay, Bisexual, and Other Men Who Have Sex With Men in the United States.

BackgroundGay, bisexual, and other men who have sex with men (GBMSM) in the United States remain disproportionately affected by human immunodeficiency virus (HIV). Yet their testing frequency is suboptimal and condomless anal sex (CAS) is increasing. Behavioral theories posit that information about HIV is a pivotal construct in individual risk reduction. However, measurements of knowledge have traditionally focused on ever hearing about HIV and being aware of the most common routes of spread.ObjectiveUsing a national Web-based sample of sexually active GBMSM, we sought to (1) quantify levels of detailed knowledge about HIV epidemiology and transmission dynamics, (2) describe variations in detailed knowledge levels across demographic strata, and (3) evaluate potential associations of increasing levels of detailed knowledge with HIV testing in the past year and engaging in CAS with a male partner in the past 3 months.MethodsGBMSM were recruited through a social networking website (Facebook) from August to September 2015 and asked 17 knowledge-based questions pertaining to the following 2 domains using a Web-based survey: HIV epidemiology (9 questions including statistics on incidence, prevalence, and distribution) and HIV transmission dynamics (8 questions including modes of spread and per-act transmission probabilities). Ordinal domain-specific indices of detailed knowledge were created for each respondent by summing their number of correct responses. Separate cumulative logit models were used to identify factors independently associated with each index, and multivariable logistic regression models were used to characterize associations with HIV testing history and recently engaging in CAS.ResultsOf the 1064 participants in our study, only half (49.62%, 528/1064) had been tested for HIV in the past year, and almost half (47.84%, 509/1064) had engaged in CAS with a male partner in the past 3 months. Majority scored 3 of 9 epidemiology questions correct (26.88%, 286/1064) and 5 of 8 transmission dynamics questions correct (25.00%, 266/1064). Participants younger than 35 years, of non-Hispanic non-white or Hispanic race and ethnicity, with lower educational levels, and who reported a sexual orientation other than homosexual or gay were significantly less knowledgeable about HIV transmission dynamics. Increasing levels of knowledge about this domain were independently associated with testing in the past year (adjusted odds ratio for each additional correct response: 1.10, 95% CI 1.01-1.20) but not with recent CAS. Increasing knowledge about HIV epidemiology was not associated with either outcome.ConclusionsIncreasing detailed knowledge about HIV epidemiology might not be as important as educating sexually active GBMSM regarding transmission dynamics. Researchers and practitioners designing prevention messages targeting GBMSM should bear in mind that not all knowledge is equal and that some aspects might have a greater positive impact than others. Future research to identify influential content and contemporary modes of delivery is needed.

The population‐level impact of HBV and its vaccination on HIV transmission dynamics

Hepatitis B virus (HBV) and its vaccination strategy may affect human immunodeficiency virus (HIV) transmission dynamics because both viruses have synergistic effects. To quantitatively assess the potential impact of HBV and its vaccination strategy on HIV transmission dynamics at the population level, in this paper, we formulate a deterministic compartmental model that describes the joint dynamics of HBV and HIV. We first derive the explicit expressions for the basic reproduction numbers of HIV and HBV and analyze the dynamics of HIV and HBV subsystems, respectively. Then a systematic qualitative analysis of the full system is also provided, which includes the local and global behavior. By using a set of reasonable parameter values, the full system is numerically investigated to assess the potential impact of HBV and its vaccination strategy on HIV transmission. The direct and indirect population level impact of HBV on HIV is demonstrated by calculating the fraction of HIV infections attributable to HBV and the difference between HIV prevalence in the presence and absence of HBV, respectively. The findings imply that the increase of HBV vaccination rate may unusually accelerate HIV epidemics indirectly, although the direct effect of HBV on HIV transmission decreases as HBV vaccination rate increases. Finally, the potential impact of HIV on HBV transmission dynamics is investigated by way of parenthesis. Copyright © 2016 John Wiley &amp; Sons, Ltd.

A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data.

SummaryEvaluation of large‐scale intervention programmes against human immunodeficiency virus (HIV) is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the frequency of condom use over time, or other self‐reported behaviour changes, for which we generally have limited or potentially biased data. We employ a Bayesian inference methodology that incorporates an HIV transmission dynamics model to estimate condom use time trends from HIV prevalence data. Estimation is implemented via particle Markov chain Monte Carlo methods, applied for the first time in this context. The preliminary choice of the formulation for the time varying parameter reflecting the proportion of condom use is critical in the context studied, because of the very limited amount of condom use and HIV data available. We consider various novel formulations to explore the trajectory of condom use over time, based on diffusion‐driven trajectories and smooth sigmoid curves. Numerical simulations indicate that informative results can be obtained regarding the amplitude of the increase in condom use during an intervention, with good levels of sensitivity and specificity performance in effectively detecting changes. The application of this method to a real life problem demonstrates how it can help in evaluating HIV interventions based on a small number of prevalence estimates, and it opens the way to similar applications in different contexts.

Modeling TB-HIV Syndemic and Treatment

Tuberculosis (TB) and human immunodeficiency virus (HIV) can be considered a deadly human syndemic. In this paper, we formulate a model for TB and HIV transmission dynamics. The model considers both TB and acquired immune deficiency syndrome (AIDS) treatment for individuals with only one of the two infectious diseases or both. The basic reproduction number and equilibrium points are determined and stability is analyzed. Through simulations, we show that TB treatment for individuals with only TB infection reduces the number of individuals that become coinfected with TB and HIV/AIDS and reduces the diseases (TB and AIDS) induced deaths. Analogously, the treatment of individuals with only AIDS also reduces the number of coinfected individuals. Further, TB treatment for coinfected individuals in the active and latent stage of TB disease implies a decrease of the number of individuals that passes from HIV-positive to AIDS.

Coevolution of risk perception, sexual behaviour, and HIV transmission in an agent-based model

Risk perception shapes individual behaviour, and is in turn shaped by the consequences of that behaviour. Here we explore this dynamics in the context of human immunodeficiency virus (HIV) spread. We construct a simplified agent-based model based on a partner selection game, where individuals are paired with others in the population, and through a decision tree, agree on unprotected sex, protected sex, or no sex. An individual's choice is conditioned on their HIV status, their perceived population-level HIV prevalence, and the preferences expressed by the individual with whom they are paired. HIV is transmitted during unprotected sex with a certain probability. As expected, in model simulations, the perceived population-level HIV prevalence climbs along with actual HIV prevalence. During this time, HIV− individuals increasingly switch from unprotected sex to protected sex, HIV+ individuals continue practicing unprotected sex whenever possible, and unprotected sex between HIV+ and HIV− individuals eventually becomes rare. We also find that the perceived population-level HIV prevalence diverges according to HIV status: HIV− individuals develop a higher perceived HIV prevalence than HIV+ individuals, although this result is sensitive to how much information is derived from global versus local sources. This research illustrates a potential mechanism by which distinct groups, as defined by their sexual behaviour, HIV status, and risk perceptions, can emerge through coevolution of HIV transmission and risk perception dynamics.

Six Degrees of Separation: Use of Social Network Analysis to Better Understand Outbreaks of Nosocomial Transmission of Extensively Drug-Resistant Tuberculosis

Six Degrees of Separation: Use of Social Network Analysis to Better Understand Outbreaks of Nosocomial Transmission of Extensively Drug-Resistant Tuberculosis

Editorial Commentary: Network Epidemic Models: Assumptions and Interpretations

Editorial Commentary: Network Epidemic Models: Assumptions and Interpretations

Qualitative assessment of the role of public health education program on HIV transmission dynamics

This paper presents a non-linear deterministic model for assessing the impact of public health education campaign on curtailing the spread of the human immunodeficiency virus (HIV) pandemic in a population. Rigorous qualitative analysis of the model reveals that it exhibits the phenomenon of backward bifurcation (BB), where a stable disease-free equilibrium coexists with a stable endemic equilibrium when a certain threshold quantity, known as the 'effective reproduction number' ('Reff), is less than unity. The epidemiological implication of BB is that a public health education campaign could fail to effectively control HIV even when the classical requirement of having the associated reproduction number less than unity is satisfied. Furthermore, an explicit threshold value is derived above which such an education campaign could lead to detrimental outcome (increase disease burden) and below which it would have positive population-level impact (reduce disease burden in the community). It is shown that the BB phenomenon is caused by imperfect efficacy of the public health education program. The model is used to assess the potential impact of some targeted public health education campaigns using data from numerous countries.