Evaluating HIV prevention strategies for populations in key affected groups: the example of Cabo Verde

Agent based modelling of blood borne viruses: a scoping review

BACKGROUND

The models that historically have been used to model infectious disease outbreaks are equation-based and statistical models. However, these models do not capture the impact of individual and social factors that affect the spread of common blood-borne viruses (BBVs) such as human immunodeficiency virus (HIV), hepatitis C virus (HCV), and hepatitis B virus (HBV). Agent-based modelling (ABM) is an alternative modelling approach that is gaining popularity in public health and epidemiology. As the field expands, it is important to understand how ABMs have been applied. In this context, we completed a scoping review of research that has been done on the ABM of BBVs.

METHOD

The inclusion/exclusion criteria were drafted using the idea of Population, Concept, and Context (PCC). The Preferred Reporting Item for Systematic Reviews and Meta-Analysis, an extension to scoping review (PRISMA-ScR), was employed in retrieving ABM literature that studied BBVs. Three databases (Scopus, Pubmed, and Embase) were systematically searched for article retrieval. 200 articles were retrieved from all the databases, with 10 duplicates. After removing the duplicates, 190 papers were screened for inclusion. After analysing the remaining articles, 70 were excluded during the abstract screening phase, and 32 were excluded during the full-text decision. Eighty-eight were retained for the scoping review analysis. To analyse this corpus of 88 papers, we developed a five-level taxonomy that categorised each paper based first on disease type, then transmission mechanism, then modelled population, then geographic location and finally, model outcome.

RESULTS

The result of this analysis show significant gaps in the ABM of BBV literature, particularly in the modeling of social and individual factors influencing BBV transmission.

CONCLUSION

There is a need for more comprehensive models that address various outcomes across different populations, transmission and intervention mechanisms. Although ABMs are a valuable tool for studying BBVs, further research is needed to address existing gaps and improve our understanding of individual and social factors that influence the spread and control of BBVs. This research can inform researchers, modellers, epidemiologists, and public health practitioners of the ABM research areas that need to be explored to reduce the burden of BBVs globally.

Modelling HIV/AIDS epidemiological complexity: A scoping review of Agent-Based Models and their application

OBJECTIVE

To end the AIDS epidemic by 2030, despite the increasing poverty and inequalities, policies should be designed to deal with population heterogeneity and environmental changes. Bottom-up designs, such as the Agent-Based Model (ABM), can model these features, dealing with such complexity. HIV/AIDS has a complex dynamic of structural factors, risk behaviors, biomedical characteristics and interventions. All embedded in unequal, stigmatized and heterogeneous social structure. To understand how ABMs can model this complexity, we performed a scoping review of HIV applications, highlighting their potentialities.

METHODS

We searched on PubMed, Web of Science, and Scopus repositories following the PRISMA extension for scoping reviews. Our inclusion criteria were HIV/AIDS studies with an ABM application. We identified the main articles using a local co-citation analysis and categorized the overall literature aims, (sub)populations, regions, and if the papers declared the use of ODD protocol and limitations.

RESULTS

We found 154 articles. We identified eleven main papers, and discussed them using the overall category results. Most studies model Transmission Dynamics (37/154), about Men who have sex with Men (MSM) (41/154), or individuals living in the US or South Africa (84/154). Recent studies applied ABM to model PrEP interventions (17/154) and Racial Disparities (12/154). Only six papers declared the use of ODD Protocol (6/154), and 34/154 didn't mention the study limitations.

CONCLUSIONS

While ABM is among the most sophisticated techniques available to model HIV/AIDS complexity. Their applications are still restricted to some realities. However, researchers are challenged to think about social structure due model characteristics, the inclusion of these features is still restricted to case-specific. Data and computational power availability can enhance this feature providing insightful results.

Evolving HIV epidemics: the urgent need to refocus on populations with risk

Purpose of review

To explore the comparative importance of HIV infections among key populations and their intimate partners as HIV epidemics evolve, and to review implications for guiding responses.

Recent findings

Even as concentrated epidemics evolve, new infections among current and former key population members and their intimate partners dominate new infections. Prevalent infections in the general population grow primarily because of key population turnover and infections among their intimate partners. In generalized epidemic settings, data and analysis on key populations are often inadequate to assess the impact of key population-focused responses, so they remain limited in coverage and under resourced. Models must incorporate downstream infections in comparing impacts of alternative responses.

Summary

Recognize that every epidemic is unique, moving beyond the overly simplistic concentrated/generalized epidemic paradigm that can misdirect resources. Guide HIV responses by gathering and using locally relevant data, understanding risk heterogeneity, and applying modeling at both national and sub-national levels to optimize resource allocations among different populations for greatest impact. Translate this improved understanding into clear, unequivocal advice for policymakers on where to focus for impact, breaking them free of the generalized/concentrated paradigm limiting their thinking and affecting their decisions.

Potential drivers of HIV acquisition in African-American women related to mass incarceration: an agent-based modelling study

Background

The United States has the highest incarceration rate in the world. Incarceration can increase HIV risk behaviors for individuals involved with the criminal justice system and may be a driver of HIV acquisition within the community.

Methods

We used an agent-based model to simulate HIV transmission in a sexual-contact network representing heterosexual African American men and women in Philadelphia to identify factors influencing the impact of male mass incarceration on HIV acquisition in women. The model was calibrated using surveillance data and assumed incarceration increased the number of sexual contacts and decreased HIV care engagement for men post-release. Incarceration of a partner increased the number of sexual contacts for women. We compared a counterfactual scenario with no incarceration to scenarios varying key parameters to determine what factors drove HIV acquisition in women.

Results

Setting the duration of male high-risk sexual behavior to two years post-release increased the number of HIV transmissions to women by more than 20%. Decreasing post-release HIV care engagement and increasing HIV acquisition risk attributable to sexually transmitted infections (STIs) also increased the number of HIV transmissions to women. Changing the duration of risk behavior for women, the proportion of women engaging in higher risk behavior, and the relative risk of incarceration for HIV-infected men had minimal impact.

Conclusion

The mass incarceration of African American men can increase HIV acquisition in African American women on a population-level through factors including post-release high-risk behaviors, disruption of HIV care engagement among formerly incarcerated men, and increased STI prevalence. These findings suggest that the most influential points of intervention may be programs seeking to reduce male risk behaviors and promote HIV care engagement post-release, as well as STI testing and treatment programs for recently incarcerated men, as well as women with incarcerated partners.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-6304-x) contains supplementary material, which is available to authorized users.

Using medical examiner case narratives to improve opioid overdose surveillance

BACKGROUND

Current opioid overdose mortality surveillance methods do not capture the complexity of the overdose epidemic. Most rely on death certificates, which may underestimate both opioid analgesic and heroin deaths. Categorizing deaths using other characteristics from the death record including route of drug administration may provide useful information to design and evaluate overdose prevention interventions.

METHODS

We reviewed California Electronic Death Reporting System records and San Francisco Office of the Chief Medical Examiner (OCME) toxicology reports and investigative case narratives for all unintentional opioid overdose deaths in San Francisco County from 2006 to 2012. We chose this time period because it encompassed a period of evolution in local opioid use patterns and expansion of overdose prevention efforts. We created a classification system for heroin-related and injection-related opioid overdose deaths and compared demographic, death scene, and toxicology characteristics among these groups.

RESULTS

We identified 816 unintentional opioid overdose deaths. One hundred fifty-two (19%) were standard heroin deaths, as designated by the OCME or by the presence of 6-monoacetylmorphine. An "expanded" classification for heroin deaths incorporating information from toxicology reports and case narratives added 20 additional heroin deaths (13% increase), accounting for 21% of all opioid deaths. Two hundred five deaths (25%) were injection-related, 60% of which were attributed to heroin. A combined classification of expanded heroin and injection-related deaths accounted for 31% of opioid overdose deaths during this period.

CONCLUSIONS

Using additional sources of information to classify opioid overdose cases resulted in a modest increase in the count of heroin overdose deaths but identified a substantial number of non-heroin injection-related opioid analgesic deaths. Including the route of administration in the characterization of opioid overdose deaths can identify meaningful subgroups of opioid users to enhance surveillance efforts and inform targeted public health programming including overdose prevention programs.

The Interaction of Risk Network Structures and Virus Natural History in the Non-spreading of HIV Among People Who Inject Drugs in the Early Stages of the Epidemic

This article explores how social network dynamics may have reduced the spread of HIV-1 infection among people who inject drugs during the early years of the epidemic. Stochastic, discrete event, agent-based simulations are used to test whether a "firewall effect" can arise out of self-organizing processes at the actor level, and whether such an effect can account for stable HIV prevalence rates below population saturation. Repeated simulation experiments show that, in the presence of recurring, acute, and highly infectious outbreaks, micro-network structures combine with the HIV virus's natural history to reduce the spread of the disease. These results indicate that network factors likely played a significant role in the prevention of HIV infection within injection risk networks during periods of peak prevalence. They also suggest that social forces that disturb network connections may diminish the natural firewall effect and result in higher rates of HIV.

Understanding the effects of different HIV transmission models in individual-based microsimulation of HIV epidemic dynamics in people who inject drugs

We investigated how different models of HIV transmission, and assumptions regarding the distribution of unprotected sex and syringe-sharing events ('risk acts'), affect quantitative understanding of HIV transmission process in people who inject drugs (PWID). The individual-based model simulated HIV transmission in a dynamic sexual and injecting network representing New York City. We constructed four HIV transmission models: model 1, constant probabilities; model 2, random number of sexual and parenteral acts; model 3, viral load individual assigned; and model 4, two groups of partnerships (low and high risk). Overall, models with less heterogeneity were more sensitive to changes in numbers risk acts, producing HIV incidence up to four times higher than that empirically observed. Although all models overestimated HIV incidence, micro-simulations with greater heterogeneity in the HIV transmission modelling process produced more robust results and better reproduced empirical epidemic dynamics.