Epidemiological bridging by injection drug use drives an early HIV epidemic

Could the 2010 HIV outbreak in Athens, Greece have been prevented? A mathematical modeling study

INTRODUCTION

In 2009 and 2010, Athens, Greece experienced a hepatitis C virus (HCV) and a Human Immunodeficiency Virus (HIV) outbreak among People Who Inject Drugs (PWID), respectively. The HCV outbreak was not detected, while that of HIV was identified in 2011. The integrated HIV-interventions, launched in early 2012, managed to reduce directly the HIV incidence and indirectly the HCV incidence. This study aims to assess what would have been the course of the HIV outbreak and its associated economic consequences if the 2009 HCV outbreak had been detected and integrated interventions had been initiated 1- or 2-years earlier.

METHODS

The model was calibrated to reproduce the observed HIV epidemiological and clinical parameters among PWID of Athens, Greece. We examined the effect of the 1- or 2-years earlier detection scenarios, the 1-year later detection, the non-detection scenario, and compared them to the status quo scenario.

RESULTS

Cumulative HIV cases, under the status-quo scenario during 2009-2019, were 1360 (90% Credible intervals: 290, 2470). If the HCV outbreak had been detected 1- or 2- years earlier, with immediate initiation of integrated interventions, 740 and 1110 HIV cases could be averted by 2019, respectively. Regarding the costs, if there was an efficient notification system to detect the HCV outbreak 1 or 2 years earlier, 35.2-53.2 million euros could be saved compared to the status quo by 2019.

CONCLUSIONS

If the HCV outbreak had been detected and promptly addressed, the HIV outbreak would have been prevented and 35.2-53.2 million euros could have been saved.

Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement

From fake news to innovative technologies, many contagions spread as complex contagions via a process of social reinforcement, where multiple exposures are distinct from prolonged exposure to a single source.1 Contrarily, biological agents such as Ebola or measles are typically thought to spread as simple contagions.2 Here, we demonstrate that these different spreading mechanisms can have indistinguishable population-level dynamics once multiple contagions interact. In the social context, our results highlight the challenge of identifying and quantifying spreading mechanisms, such as social reinforcement,3 in a world where an innumerable amount of ideas, memes and behaviors interact. In the biological context, this parallel allows the use of complex contagions to effectively quantify the non-trivial interactions of infectious diseases.

Identification of major routes of HIV transmission throughout Mesoamerica

BACKGROUND

Migration and travel are major drivers of the spread of infectious diseases. Geographic proximity and a common language facilitate travel and migration in Mesoamerica, which in turn could affect the spread of HIV in the region.

METHODS

6092 HIV-1 subtype B partial pol sequences sampled from unique antiretroviral treatment-naïve individuals from Mexico (40.7%), Guatemala (24.4%), Honduras (19%), Panama (8.2%), Nicaragua (5.5%), Belize (1.4%), and El Salvador (0.7%) between 2011 and 2016 were included. Phylogenetic and genetic network analyses were performed to infer putative relationships between HIV sequences. The demographic and geographic associations with clustering were analyzed and viral migration patterns were inferred using the Slatkin-Maddison approach on 100 iterations of random subsets of equal number of sequences per location.

RESULTS

A total of 1685/6088 (27.7%) of sequences linked with at least one other sequence, forming 603 putative transmission clusters (range: 2-89 individuals). Clustering individuals were significantly more likely to be younger (median age 29 vs 33years, p<0.01) and men-who-have-sex-with-men (40.4% vs 30.3%, p<0.01). Of the 603 clusters, 30 (5%) included sequences from multiple countries with commonly observed linkages between Mexican and Honduran sequences. Eight of the 603 clusters included >10 individuals, including two comprised exclusively of Guatemalans (52 and 89 individuals). Phylogenetic and migration analyses suggested that the Central and Southern regions of Mexico along with Belize were major sources of HIV throughout the region (p<0.01) with genetic flow southward from Mexico to the other nations of Mesoamerica. We also found evidence of significant viral migration within Mexico.

CONCLUSION

International clusters were infrequent, suggesting moderate migration between HIV epidemics of the different Mesoamerican countries. Nevertheless, we observed important sources of transnational HIV spread in the region, including Southern and Central Mexico and Belize.

A syringe-sharing model for the spread of HIV: application to Omsk, Western Siberia

A system of two differential equations is used to model the transmission dynamics of human immunodeficiency virus between 'persons who inject drugs' (PWIDs) and their syringes. Our vector-borne disease model hinges on a metaphorical urn from which PWIDs draw syringes at random which may or may not be infected and may or may not result in one of the two agents becoming infected. The model's parameters are estimated with data mostly from the city of Omsk in Western Siberia. A linear trend in PWID prevalence in Omsk could only be fitted by considering a time-dependent version of the model captured through a secular decrease in the probability that PWIDs decide to share a syringe. A global sensitivity analysis is performed with 14 parameters considered random variables in order to assess their impact on average numbers infected over a 50-year projection. With obvious intervention implications the drug injection rate and the probability of syringe-cleansing are the only parameters whose coefficients of correlations with numbers of infected PWIDs and infected syringes have an absolute value close to or larger than 0.40.

Value of Comprehensive HCV Treatment among Vulnerable, High-Risk Populations

OBJECTIVES

The objective of this study was to explore the trade-offs society and payers make when expanding treatment access to patients with chronic hepatitis C virus (HCV) infection in early stages of disease as well as to vulnerable, high-risk populations, such as people who inject drugs (PWID) and HIV-infected men who have sex with men (MSM-HIV).

METHODS

A discrete time Markov model simulated HCV progression and treatment over 20 years. Population cohorts were defined by behaviors that influence the risk of HCV exposure: PWID, MSM-HIV, an overlap cohort of individuals who are both PWID and MSM-HIV, and all other adults. Six different treatment scenarios were modeled, with varying degrees of access to treatment at different fibrosis stages and to different risk cohorts. Benefits were measured as quality-adjusted life-years and a $150,000/quality-adjusted life-year valuation was used to assess social benefits.

RESULTS

Compared with limiting treatment to METAVIR fibrosis stages F3 or F4 and excluding PWID, expanding treatment to patients in all fibrosis stages and including PWID reduces cumulative new infections by 55% over a 20-year horizon and reduces the prevalence of HCV by 93%. We find that treating all HCV-infected individuals is cost saving and net social benefits are over $500 billion greater compared with limiting treatment. Including PWID in treatment access saves 12,900 to 41,200 lives.

CONCLUSIONS

Increased access to treatment brings substantial value to society and over the long-term reduces costs for payers, as the benefits accrued from long-term reduction in prevalent and incident cases, mortality, and medical costs outweigh the cost of treatment.

Eight challenges for network epidemic models

Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host-pathogen biology (e.g. waning immunity) have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

Dating, marriage, and parenthood for HIV-positive heterosexual Puerto Rican men: normalizing perspectives on everyday life with HIV

HIV-positive men are living long and healthier lives while managing HIV as a chronic illness. Although research has extensively documented the experiences of illness of people living with HIV, dating, marriage, and fatherhood among heterosexual Latino men has not been examined. To address this gap, this study used a qualitative study design to examine patterns and strategies for dating, marriage, and parenthood among 24 HIV-positive heterosexual Puerto Rican men living in Boston. The findings in our study indicate that an HIV diagnosis does not necessarily deter men from having an active sexual life, marrying, or having children. In fact, for some of the men, engaging in these social and life-changing events is part of moving on and normalizing life with HIV; these men planned for, achieved, and interpreted these events in the context of establishing normalcy with HIV. Although the HIV diagnosis discouraged some men from engaging in sexual relations, getting married, or having children, others fulfilled these desires with strategies aimed to reconciling their HIV status in their personal life, including dating or marrying HIV-positive women only. Additional important themes identified in this study include the decision to disclose HIV status to new sexual partners as well as the decision to accept the risk of HIV transmission to a child or partner in order to fulfill desires of fatherhood. Understanding the personal struggles, decision-making patterns, and needs of HIV-positive heterosexual men can aid in designing interventions that support healthy living with HIV.

Do metropolitan HIV epidemic histories and programs for people who inject drugs and men who have sex with men predict AIDS incidence and mortality among heterosexuals?

PURPOSE

We focus on a little-researched issue-how human immunodeficiency virus (HIV) epidemics and programs in key populations in metropolitan areas affect epidemics in other key populations. We consider (1) How are earlier epidemics among people who inject drugs (PWID) and men who have sex with men (MSM) related to later AIDS incidence and mortality among heterosexuals?; (2) Were prevention programs targeting PWID or MSM associated with lower AIDS incidence and mortality among heterosexuals?; and (3) Was the size of the potential bridge population of noninjecting drug users (NIDUs) in a metropolitan area associated with later AIDS incidence and mortality among heterosexuals?

METHODS

Using data for 96 large U.S. metropolitan areas, Poisson regression assessed associations of population prevalences of HIV-infected PWID and MSM (1992); NIDU population prevalence (1992-1994); drug use treatment coverage for PWID (1993); HIV counseling and testing coverage for MSM and for PWID (1992); and syringe exchange presence (2000) with CDC data on AIDS incidence and mortality among heterosexuals in 2006-2008, with appropriate socioeconomic controls.

RESULTS

Population density of HIV+ PWID and of NIDUs were positively related, and prevention programs for PWID negatively related to later AIDS incidence among heterosexuals and later mortality among heterosexuals living with AIDS. HIV+ MSM population density and prevention programs for MSM were not associated with these outcomes.

CONCLUSIONS

Efforts to reduce HIV transmission among PWID and NIDUs may reduce AIDS and AIDS-related mortality among heterosexuals. More research is needed at metropolitan area, network, and individual levels into HIV bridging across key populations and how interventions in one key population affect HIV epidemics in other key populations.

Urbanisation and sexual health: understanding bisexually active men in Hanoi, Vietnam

Background: Men who have sex with men (MSM) in Vietnam are receiving increased attention in recognition of their high-risk behaviours and potential for human immunodeficiency virus (HIV) infection and transmission. Due to societal pressures, many MSM in Vietnam are also bisexually active, which ultimately increases the transmission risks beyond the MSM population. Evidence is emerging that indicates a greater proportion of women in Asia with low-risk sexual activities are contracting HIV from their male partners who have become HIV infected through male-male sex. Methodology: Fourteen focus group discussions exploring sexual and social networks were conducted in Hanoi between July 2010 and September 2010. A total of 96 individuals participated in these sessions. Findings: A risk environment approach was used to analyse the focus group themes of social stigma and marriage, sex with other men in closed settings and transactional sex in Hanoi, an increasingly urbanising and westernising city. Implications: Despite limited evidence globally that bisexual men act as a bridge for sexually transmitted diseases, there is particular concern in Vietnam about this potential risk. HIV rates amongst MSM are rapidly rising and there are reports of women contracting HIV from their male partners who are bisexually active.

Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users

BACKGROUND

HIV transmission risk among non-injection drug users is high due to the co-occurrence of drug use and sexual risk behaviors. The purpose of the current study was to identify patterns of drug use among polysubstance users within a high HIV prevalence population.

METHODS

The study sample included 409 substance users from the Pretoria region of South Africa. Substances used by 20% or more the sample included: cigarettes, alcohol, marijuana and heroin in combination, marijuana and cigarettes in combination, and crack cocaine. Latent class analysis was used to identify patterns of polysubstance use based on types of drugs used. Multivariate logistic regression analyses compared classes on demographics, sexual risk behavior, and disease status.

RESULTS

Four classes of substance use were found: MJ+Cig (40.8%), MJ+Her (30.8%), Crack (24.7%), and Low Use (3.7%). The MJ+Cig class was 6.7 times more likely to use alcohol and 3 times more likely to use drugs before/during sex with steady partners than the Crack class. The MJ+Cig class was 16 times more likely to use alcohol before/during sex with steady partners than the MJ+Her class. The Crack class was 6.1 times more likely to engage in transactional sex and less likely to use drugs before/during steady sex than the MJ+Her class.

CONCLUSIONS

Findings illustrate patterns of drug use among a polysubstance using population that differ in sexual risk behavior. Intervention strategies should address substance use, particularly smoking as a route of administration (ROA), and sexual risk behaviors that best fit this high-risk population.

Incorporating disease and population structure into models of SIR disease in contact networks

We consider the recently introduced edge-based compartmental models (EBCM) for the spread of susceptible-infected-recovered (SIR) diseases in networks. These models differ from standard infectious disease models by focusing on the status of a random partner in the population, rather than a random individual. This change in focus leads to simple analytic models for the spread of SIR diseases in random networks with heterogeneous degree. In this paper we extend this approach to handle deviations of the disease or population from the simplistic assumptions of earlier work. We allow the population to have structure due to effects such as demographic features or multiple types of risk behavior. We allow the disease to have more complicated natural history. Although we introduce these modifications in the static network context, it is straightforward to incorporate them into dynamic network models. We also consider serosorting, which requires using dynamic network models. The basic methods we use to derive these generalizations are widely applicable, and so it is straightforward to introduce many other generalizations not considered here. Our goal is twofold: to provide a number of examples generalizing the EBCM method for various different population or disease structures and to provide insight into how to derive such a model under new sets of assumptions.

Detectable signals of episodic risk effects on acute HIV transmission: strategies for analyzing transmission systems using genetic data

Episodic high-risk sexual behavior is common and can have a profound effect on HIV transmission. In a model of HIV transmission among men who have sex with men (MSM), changing the frequency, duration and contact rates of high-risk episodes can take endemic prevalence from zero to 50% and more than double transmissions during acute HIV infection (AHI). Undirected test and treat could be inefficient in the presence of strong episodic risk effects. Partner services approaches that use a variety of control options will be likely to have better effects under these conditions, but the question remains: What data will reveal if a population is experiencing episodic risk effects? HIV sequence data from Montreal reveals genetic clusters whose size distribution stabilizes over time and reflects the size distribution of acute infection outbreaks (AIOs). Surveillance provides complementary behavioral data. In order to use both types of data efficiently, it is essential to examine aspects of models that affect both the episodic risk effects and the shape of transmission trees. As a demonstration, we use a deterministic compartmental model of episodic risk to explore the determinants of the fraction of transmissions during acute HIV infection (AHI) at the endemic equilibrium. We use a corresponding individual-based model to observe AIO size distributions and patterns of transmission within AIO. Episodic risk parameters determining whether AHI transmission trees had longer chains, more clustered transmissions from single individuals, or different mixes of these were explored. Encouragingly for parameter estimation, AIO size distributions reflected the frequency of transmissions from acute infection across divergent parameter sets. Our results show that episodic risk dynamics influence both the size and duration of acute infection outbreaks, thus providing a possible link between genetic cluster size distributions and episodic risk dynamics.

Model hierarchies in edge-based compartmental modeling for infectious disease spread

We consider the family of edge-based compartmental models for epidemic spread developed in Miller et al. (J R Soc Interface 9(70):890-906, 2012). These models allow for a range of complex behaviors, and in particular allow us to explicitly incorporate duration of a contact into our mathematical models. Our focus here is to identify conditions under which simpler models may be substituted for more detailed models, and in so doing we define a hierarchy of epidemic models. In particular we provide conditions under which it is appropriate to use the standard mass action SIR model, and we show what happens when these conditions fail. Using our hierarchy, we provide a procedure leading to the choice of the appropriate model for a given population. Our result about the convergence of models to the mass action model gives clear, rigorous conditions under which the mass action model is accurate.

EpiFire: An open source C++ library and application for contact network epidemiology

BACKGROUND

Contact network models have become increasingly common in epidemiology, but we lack a flexible programming framework for the generation and analysis of epidemiological contact networks and for the simulation of disease transmission through such networks.

RESULTS

Here we present EpiFire, an applications programming interface and graphical user interface implemented in C++, which includes a fast and efficient library for generating, analyzing and manipulating networks. Network-based percolation and chain-binomial simulations of susceptible-infected-recovered disease transmission, as well as traditional non-network mass-action simulations, can be performed using EpiFire.

CONCLUSIONS

EpiFire provides an open-source programming interface for the rapid development of network models with a focus in contact network epidemiology. EpiFire also provides a point-and-click interface for generating networks, conducting epidemic simulations, and creating figures. This interface is particularly useful as a pedagogical tool.

Agent-based and phylogenetic analyses reveal how HIV-1 moves between risk groups: injecting drug users sustain the heterosexual epidemic in Latvia

Injecting drug users (IDUs) are a driving force for the spread of HIV-1 in Latvia and other Baltic States, accounting for a majority of cases. However, in recent years, heterosexual cases have increased disproportionately. It is unclear how the changes in incidence patterns in Latvia can be explained, and how important IDUs are for the heterosexual sub-epidemic. We introduce a novel epidemic model and use phylogenetic analyses in parallel to examine the spread of HIV-1 in Latvia between 1987 and 2010. Using a hybrid framework with a mean-field description for the susceptible population and an agent-based model for the infecteds, we track infected individuals and follow transmission histories dynamically formed during the simulation. The agent-based simulations and the phylogenetic analysis show that more than half of the heterosexual transmissions in Latvia were caused by IDU, which sustain the heterosexual epidemic. Indeed, we find that heterosexual clusters are characterized by short transmission chains with up to 63% of the chains dying out after the first introduction. In the simulations, the distribution of transmission chain sizes follows a power law distribution, which is confirmed by the phylogenetic data. Our models indicate that frequent introductions reduced the extinction probability of an autonomously spreading heterosexual HIV-1 epidemic, which now has the potential to dominate the spread of the overall epidemic in the future. Furthermore, our model shows that social heterogeneity of the susceptible population can explain the shift in HIV-1 incidence in Latvia over the course of the epidemic. Thus, the decrease in IDU incidence may be due to local heterogeneities in transmission, rather than the implementation of control measures. Increases in susceptibles, through social or geographic movement of IDU, could lead to a boost in HIV-1 infections in this risk group. Targeting individuals that bridge social groups would help prevent further spread of the epidemic.

Modeling the impact of supra-structural network nodes: The case of anonymous syringe sharing and HIV among people who inject drugs

Networks are well understood as crucial to the diffusion of HIV among injection drug users (IDUs), but quasi-anonymous risk nodes - such as shooting galleries - resist measurement and incorporation into empirical analyses of disease diffusion. Drawing on network data from 767 IDUs in Bushwick, Brooklyn, we illustrate the use of calibrated agent-based models (CABMs) to account for network structure, injection practices, and quasi-anonymous transmission in shooting galleries. Results confirm the importance of network structure and actor heterogeneity to the magnitude and speed of HIV transmission. Models further demonstrate that quasi-anonymous injections in shooting galleries increase the speed of HIV diffusion across the whole network and have the greatest impact on HIV seroconversion levels for IDUs at the network periphery. Shooting galleries are shown to be transmission hubs that operate independently of traceable structural ties, linking otherwise unconnected network components. CABMs potentially increase understandings of HIV diffusion dynamics by infusing computer simulations with empirical data.

Endogenous or exogenous spreading of HIV-1 in Nordrhein-Westfalen, Germany, investigated by phylodynamic analysis of the RESINA Study cohort

HIV's genetic instability means that sequence similarity can illuminate the underlying transmission network. Previous application of such methods to samples from the United Kingdom has suggested that as many as 86% of UK infections arose outside of the country, a conclusion contrary to usual patterns of disease spread. We investigated transmission networks in the Resina cohort, a 2,747 member sample from Nordrhein-Westfalen, Germany, sequenced at therapy start. Transmission networks were determined by thresholding the pairwise genetic distance in the pol gene at 96.8% identity. At first blush the results concurred with the UK studies. Closer examination revealed four large and growing transmission networks that encompassed all major transmission groups. One of these formed a supercluster containing 71% of the sex with men (MSM) subjects when the network was thresholded at levels roughly equivalent to those used in the UK studies, though methodological differences suggest that this threshold may be too generous in the current data. Examination of the endo- versus exogenesis hypothesis by testing whether infections that were exogenous to Cologne or to Dusseldorf were endogenous to the greater region supported endogenous spread in MSM subjects and exogenous spread in the endemic transmission group. In intravenous drug using group subjects, it depended on viral strain, with subtype B sequences appearing to have origin exogenous to the Resina data, while non-B sequences (primarily subtype A) were almost completely endogenous to their local community. These results suggest that, at least in Germany, the question of endogenous versus exogenous linkages depends on subject group.

Effects of heterogeneous and clustered contact patterns on infectious disease dynamics

The spread of infectious diseases fundamentally depends on the pattern of contacts between individuals. Although studies of contact networks have shown that heterogeneity in the number of contacts and the duration of contacts can have far-reaching epidemiological consequences, models often assume that contacts are chosen at random and thereby ignore the sociological, temporal and/or spatial clustering of contacts. Here we investigate the simultaneous effects of heterogeneous and clustered contact patterns on epidemic dynamics. To model population structure, we generalize the configuration model which has a tunable degree distribution (number of contacts per node) and level of clustering (number of three cliques). To model epidemic dynamics for this class of random graph, we derive a tractable, low-dimensional system of ordinary differential equations that accounts for the effects of network structure on the course of the epidemic. We find that the interaction between clustering and the degree distribution is complex. Clustering always slows an epidemic, but simultaneously increasing clustering and the variance of the degree distribution can increase final epidemic size. We also show that bond percolation-based approximations can be highly biased if one incorrectly assumes that infectious periods are homogeneous, and the magnitude of this bias increases with the amount of clustering in the network. We apply this approach to model the high clustering of contacts within households, using contact parameters estimated from survey data of social interactions, and we identify conditions under which network models that do not account for household structure will be biased.

The transmission dynamics of infectious diseases are sensitive to the patterns of interactions among susceptible and infectious individuals. Human social contacts are known to be highly heterogeneous (the number of social contacts ranges from few to very many) and to be highly clustered (the social contacts of a single individual tend also to contact each other). To predict the impacts of these patterns on infectious disease transmission, epidemiologists have begun to use random network models, in which nodes represent susceptible, infectious, or recovered individuals and links represent contacts sufficient for disease transmission. This paper introduces a versatile mathematical model that takes both heterogeneous connectivity and clustering into account and uses it to quantify the relative impact of clustered contacts on epidemics and the prediction biases that can arise when clustering and variability in infectious periods are ignored.