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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. [ABSTRACT FROM AUTHOR]

One of network epidemiology's central assumptions is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We discuss these observations in the context of the temporal and topological structure of the data sets. [ABSTRACT FROM AUTHOR]

The dynamics of infectious diseases that are spread through direct contact have been proven to depend on the strength of community structure or modularity within the underlying network. It has been recently shown that weighted networks with similar modularity values may exhibit different mixing styles regarding the number of connections among communities and their respective weights. However, the effect of mixing style on epidemic behavior was still unclear. In this paper, we simulate the spread of disease within networks with different mixing styles: a dense-weak style (i.e., many edges among the communities with small weights) and a sparse-strong style (i.e., a few edges among the communities with large weights). Simulation results show that, with the same modularity: 1) the mixing style significantly influences the epidemic size, speed, pattern and immunization strategy; 2) the increase of the number of communities amplifies the effect of the mixing style; 3) when the mixing style changes from sparse-strong to dense-weak, there is a ‘saturation point’, after which the epidemic size and pattern become stable. We also provide a mean-field solution of the epidemic threshold and size on weighted community networks with arbitrary external and internal degree distribution. The solution explains the effect of the second moment of the degree distribution, and a symmetric effect of internal and external connections (incl. degree distribution and weight). Our study has both potential significance for designing more accurate metrics for the community structure and exploring diffusion dynamics on metapopulation networks. [ABSTRACT FROM AUTHOR]

Setting: Tuberculosis (TB) is highly prevalent in prisons of the former Soviet Union. Objective: To understand the behavioral, demographic and biological factors placing inmates in Tajikistan at risk for active TB. Design: We administered a behavioral and demographic survey to 1317 inmates in two prison facilities in Sughd province, Tajikistan along with radiographic screening for pulmonary TB. Suspected cases were confirmed bacteriologically. Inmates undergoing TB treatment were also surveyed. In-depth interviews were conducted with former prisoners to elicit relevant social and behavioral characteristics. Results: We identified 59 cases of active pulmonary TB (prevalence 4.5%). Factors independently associated with increased prevalence of active TB were: HIV-infection by self-report (PR 7.88; 95%CI 3.40–18.28), history of previous TB (PR 10.21; 95%CI 6.27–16.63) and infrequent supplemental nutrition beyond scheduled meals (PR 3.00; 95%CI 1.67–5.62). Access to supplemental nutrition was associated with frequency of visits from friends and family and ability to rely on other inmates for help. Conclusion: In prison facilities of Tajikistan, HIV-infection, injection drug use and low access to supplemental nutrition were associated with prevalent cases of active pulmonary TB. Policies that reduce HIV transmission among injection drug users and improve the nutritional status of socially isolated inmates may alleviate the TB burden in Tajikistan’s prisons. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess whether the Government of Kenya's Cash Transfer for Orphans and Vulnerable Children (Kenya CT-OVC) can reduce the risk of HIV among young people by postponing sexual debut. The program provides an unconditional transfer of US$20 per month directly to the main caregiver in the household. An evaluation of the program was implemented in 2007–2009 in seven districts. Fourteen Locations were randomly assigned to receive the program and fourteen were assigned to a control arm. A sample of households was enrolled in the evaluation in 2007. We revisited these households in 2011 and collected information on sexual activity among individuals between 15–25 years of age. We used logistic regression, adjusted for the respondent's age, sex and relationship to caregiver, the age, sex and schooling of the caregiver and whether or not the household lived in Nairobi at baseline, to compare rates of sexual debut among young people living in program households with those living in control households who had not yet entered the program. Our results, adjusted for these covariates, show that the program reduced the odds of sexual debut by 31 percent. There were no statistically significant effects on secondary outcomes of behavioral risk such as condom use, number of partners and transactional sex. Since the CT-OVC provides cash to the caregiver and not to the child, and there are no explicit conditions associated with receipt, these impacts are indirect, and may have been achieved by keeping young people in school. Our results suggest that large-scale national social cash transfer programs with poverty alleviation objectives may have potential positive spillover benefits in terms of reducing HIV risk among young people in Eastern and Southern Africa. [ABSTRACT FROM AUTHOR]

In the Susceptible–Infectious–Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold. [ABSTRACT FROM AUTHOR]

The spread of certain diseases can be promoted, in some cases substantially, by prior infection with another disease. One example is that of HIV, whose immunosuppressant effects significantly increase the chances of infection with other pathogens. Such coinfection processes, when combined with nontrivial structure in the contact networks over which diseases spread, can lead to complex patterns of epidemiological behavior. Here we consider a mathematical model of two diseases spreading through a single population, where infection with one disease is dependent on prior infection with the other. We solve exactly for the sizes of the outbreaks of both diseases in the limit of large population size, along with the complete phase diagram of the system. Among other things, we use our model to demonstrate how diseases can be controlled not only by reducing the rate of their spread, but also by reducing the spread of other infections upon which they depend. [ABSTRACT FROM AUTHOR]

Background: In April 2009, the most recent pandemic of influenza A began. We present the first estimates of pandemic mortality based on the newly-released final data on deaths in 2009 and 2010 in the United States. Methods: We obtained data on influenza and pneumonia deaths from the National Center for Health Statistics (NCHS). Age- and sex-specific death rates, and age-standardized death rates, were calculated. Using negative binomial Serfling-type methods, excess mortality was calculated separately by sex and age groups. Results: In many age groups, observed pneumonia and influenza cause-specific mortality rates in October and November 2009 broke month-specific records since 1959 when the current series of detailed US mortality data began. Compared to the typical pattern of seasonal flu deaths, the 2009 pandemic age-specific mortality, as well as influenza-attributable (excess) mortality, skewed much younger. We estimate 2,634 excess pneumonia and influenza deaths in 2009–10; the excess death rate in 2009 was 0.79 per 100,000. Conclusions: Pandemic influenza mortality skews younger than seasonal influenza. This can be explained by a protective effect due to antigenic cycling. When older cohorts have been previously exposed to a similar antigen, immune memory results in lower death rates at older ages. Age-targeted vaccination of younger people should be considered in future pandemics. [ABSTRACT FROM AUTHOR]

Background: HIV prevalence differs by more than an order of magnitude between South Africa's racial groups. Comparing the sexual behaviors and other risk factors for HIV transmission between the different races may shed light on the determinants of South Africa's generalized HIV epidemic. Methods: Five nationally representative and one city-representative population-based surveys of sexual behavior were used to assess the extent to which various risk factors co-varied with HIV prevalence by race in South Africa. Results: In 2004, the prevalence of HIV was 0.5%, 1%, 3.2% and 19.9% in 15–49 year old whites, Indians, coloureds and blacks respectively. The risk factors which co-varied with HIV prevalence by race in the six surveys were age of sexual debut (in five out of five surveys for men and three out of six surveys for women), age gap (zero surveys in men and three in women), mean number of sex partners in the previous year (five surveys in men and three in women) and concurrent partnerships (five surveys in men and one in women). Condom usage and circumcision were both more prevalent in the high HIV prevalence groups. The reported prevalence of concurrency was 6 to 17 times higher in the black as opposed to the white men in the five surveys. Conclusions: The differences in sexual behavior in general, and the prevalence of concurrency and the number of sexual partners in particular, offer a plausible and parsimonious cause to explain a part of the differing prevalences of HIV between South Africa's racial groups. [ABSTRACT FROM AUTHOR]

Introduction: The objectives of this study are to develop a summary measure of risky sexual practice and examine the factors associated with this among female sex workers (FSWs) in Karnataka, India. Materials and Methods: Data were drawn from special behavioral surveys (SBS) conducted in 2007 among 577 FSWs in two districts of Karnataka, India: Belgaum and Bangalore. FSWs were recruited using the two-stage probability sampling design. FSWs' sexual practice was considered risky if they reported inconsistent condom use with any sexual partner and reported experience of one of the following vulnerabilities to HIV risk: anal sex, alcohol consumption prior to sex and concurrent sexual relationships. Results: About 51% of FSWs had engaged in risky sexual practice. The odds of engaging in risky sex were higher among FSWs who were older (35+ years) than younger (18–25 years) (58% vs. 45%, Adjusted Odds Ratio (AOR): 2.0, 95% confidence interval (CI): 1.2–3.4), who were currently married than never married (61% vs. 51%, AOR: 4.8, 95% CI: 2.5–9.3), who were in sex work for 10+ years than those who were in sex work for less than five years (66% vs. 39%, AOR: 2.6, 95% CI: 1.6–4.2), and who had sex with 3+ clients/day than those who had sex with fewer clients (67% vs. 38%, AOR: 3.7, 95% CI:2.5–5.5). Conclusion: FSWs who are older, currently married, practicing sex work for longer duration and with higher clientele were more likely to engage in risky sexual practices. HIV prevention programs should develop strategies to reach these most-at risk group of FSWs to optimize the effectiveness of such programs. [ABSTRACT FROM AUTHOR]

Sampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample “hidden” populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, especially the community structure, of networks. Our method involves collecting samples of a network by random walks and reconstructing the network by probabilistically coalescing vertices, using vertex attributes to determine the probabilities. Even though our method can only approximately reconstruct a part of the original network, it can recover its community structure relatively well. Moreover, it can find the key vertices which, when immunized, can effectively reduce the spread of an infection through the original network. [ABSTRACT FROM AUTHOR]

Background: Hepatitis C virus (HCV) emerged as sexually transmitted infection among HIV-infected men who have sex with men (MSM). We studied whether HCV circulated in identifiable high-risk MSM subcultures and performed phylogenetic analysis. Methods: HIV-infected MSM were recruited at the sexually transmitted infections (STI) outpatient clinic and a university HIV clinic in Amsterdam, the Netherlands, 2008–2009. Participants completed a detailed questionnaire and were tested for HCV antibodies and RNA, with NS5B regions sequenced for analysis of clusters. Results: Among 786 participants, the median age was 43 (IQR 37–48) years, and 93 (11.8%) were HCV-positive. Seropositivity was associated with belonging to subcultures identified as leather (aOR 2.60; 95% CI 1.56–4.33), rubber/lycra (aOR 2.15; 95% CI 1.10–4.21), or jeans (aOR 2.23; 95% CI 1.41–3.54). The two largest HCV-RNA monophyletic clusters were compared; MSM in cluster I (genotype 1a, n = 13) reported more partners (P = 0.037) than MSM in cluster II (genotype 4d, n = 14), but demographics, subculture characteristics and other risk behaviors did not differ significantly between the two clusters. Discussion: HCV infection is associated with identifiable groups of leather/rubber/lycra/jeans subcultures among HIV-infected MSM. Separate epidemiological HCV transmission networks were not revealed. Active HCV screening and treatment within specific subcultures may reduce HCV spread among all MSM. [ABSTRACT FROM AUTHOR]

Objective: Determine the acceptability and epidemiological impact of increases in HIV testing in gay men in New South Wales (NSW), Australia– particularly pertinent when considering treatment as prevention and the need to reduce undiagnosed infections. Methods: We conducted an online survey and focus groups to assess whether increases in HIV testing would be acceptable to gay men in NSW. In parallel, we assessed the potential impact of increases in testing coverage and/or frequency using an individual-based model of HIV transmission. Results: If sexual practices and the rate of initiating HIV treatment are unchanged then increasing HIV testing reduces infections. Increasing testing frequency has the largest impact, with a 13.8% reduction in HIV infections over 10 years if the ∼55–75% of men who test at least once per year increased their testing frequency to four times per year. If testing levels decrease from current levels then we expect an increase in HIV infections with a sharply rising trend over time. Increasing HIV testing would be acceptable if testing was more convenient. However, only ∼25% of men surveyed were ‘very likely’ to increase their level of HIV testing. Men delayed or avoided testing due to the slowness in obtaining results and if they believed they had not put themselves at risk. Conclusions: An increase in HIV testing alone is unlikely to reduce HIV incidence substantially in NSW gay men– however, the relatively high testing levels need to continue to prevent an increase in HIV infections. In jurisdictions with lower levels of HIV testing, increases in testing coverage and frequency are likely to have a larger impact. Successful treatment as prevention interventions will require increases in testing rates; such increases would be acceptable to gay men in NSW but only if more convenient testing and rapid communication of results were available. [ABSTRACT FROM AUTHOR]