Identifying asymptomatic spreaders of antimicrobial-resistant pathogens in hospital settings.

Antimicrobial-resistant organisms (AMROs) can colonize people without symptoms for long periods of time, during which these agents can spread unnoticed to other patients in healthcare systems. The accurate identification of asymptomatic spreaders of AMRO in hospital settings is essential for supporting the design of interventions against healthcare-associated infections (HAIs). However, this task remains challenging because of limited observations of colonization and the complicated transmission dynamics occurring within hospitals and the broader community. Here, we study the transmission of methicillin-resistant Staphylococcus aureus (MRSA), a prevalent AMRO, in 66 Swedish hospitals and healthcare facilities with inpatients using a data-driven, agent-based model informed by deidentified real-world hospitalization records. Combining the transmission model, patient-to-patient contact networks, and sparse observations of colonization, we develop and validate an individual-level inference approach that estimates the colonization probability of individual hospitalized patients. For both model-simulated and historical outbreaks, the proposed method supports the more accurate identification of asymptomatic MRSA carriers than other traditional approaches. In addition, in silica control experiments indicate that interventions targeted to inpatients with a high-colonization probability outperform heuristic strategies informed by hospitalization history and contact tracing.

HIV testing and prevention among foreign-born Men Who have Sex with Men: an online survey from Sweden.

BACKGROUND: There is an increasing trend toward international migration worldwide. With it comes a challenge for public health and public funded health care systems to meet the migrating population's health needs. Men who have sex with men are a key population for HIV, contributing an estimated 42% of new HIV cases in Europe in 2013. HIV monitoring data suggest that foreign-born MSM are not only exposed to a high risk of HIV before migration but also while living in Sweden. The aim of this study is to examine HIV testing prevalence and uptake of HIV prevention interventions among foreign-born MSM living in Sweden. METHODS: A web survey available in English and Swedish was conducted from October 1 to October 30, 2013 via a Scandinavian Web community for Lesbian, Gay, Bisexual, Transgender and Intergender people. The web survey included modules on sociodemographics, condom use, sexual risk behaviour and HIV/STI testing experience. 244 eligible MSM participants born abroad and living in Sweden participated in the study. Descriptive and inferential analysis was performed. RESULTS: Half of the foreign-born MSM participants in this study had been tested for HIV during the last 12 months. Participants who had lived in Sweden less than or equal to 5 years were more likely to have been tested for HIV during the last 12 months. Having talked about HIV/STI with a prevention worker during the past year was associated with having been tested for HIV. Requested services among the majority of participants were HIV rapid test, anonymous HIV testing, HIV/STI testing outside of the health care setting and MSM-friendly clinics. CONCLUSION: Efforts are needed to promote HIV testing among foreign-born MSM. Peer outreach, individual and group counselling may be preferred interventions to do so. In addition, it is critically important to increase HIV testing among foreign-born MSM who have lived in Sweden for more than five years. Further research should explore if scale up of implementation of requested services may increase frequency of HIV testing and detection of new cases linked to treatment among foreign-born MSM living in Sweden.

Risk of HIV transmission from patients on antiretroviral therapy: a position statement from the Public Health Agency of Sweden and the Swedish Reference Group for Antiviral Therapy.

The modern medical treatment of HIV with antiretroviral therapy (ART) has drastically reduced the morbidity and mortality in patients infected with this virus. ART has also been shown to reduce the transmission risk from individual patients as well as the spread of the infection at the population level. This position statement from the Public Health Agency of Sweden and the Swedish Reference Group for Antiviral Therapy is based on a workshop organized in the fall of 2012. It summarizes the latest research and knowledge on the risk of HIV transmission from patients on ART, with a focus on the risk of sexual transmission. The risk of transmission via shared injection equipment among intravenous drug users is also examined, as is the risk of mother-to-child transmission. Based on current knowledge, the risk of transmission through vaginal or anal intercourse involving the use of a condom has been judged to be minimal, provided that the person infected with HIV fulfils the criteria for effective ART. This probably also applies to unprotected intercourse, provided that no other sexually transmitted infections are present, although it is not currently possible to fully support this conclusion with direct scientific evidence. ART is judged to markedly reduce the risk of blood-borne transmission between people who share injection equipment. Finally, the risk of transmission from mother to child is very low, provided that ART is started well in advance of delivery.

Information dynamics shape the sexual networks of Internet-mediated prostitution.

Like many other social phenomena, prostitution is increasingly coordinated over the Internet. The online behavior affects the offline activity; the reverse is also true. We investigated the reported sexual contacts between 6,624 anonymous escorts and 10,106 sex buyers extracted from an online community from its beginning and six years on. These sexual encounters were also graded and categorized (in terms of the type of sexual activities performed) by the buyers. From the temporal, bipartite network of posts, we found a full feedback loop in which high grades on previous posts affect the future commercial success of the sex worker, and vice versa. We also found a peculiar growth pattern in which the turnover of community members and sex workers causes a sublinear preferential attachment. There is, moreover, a strong geographic influence on network structure--the network is geographically clustered but still close to connected, the contacts consistent with the inverse-square law observed in trading patterns. We also found that the number of sellers scales sublinearly with city size, so this type of prostitution does not, comparatively speaking, benefit much from an increasing concentration of people.

Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.

Sexual contact patterns, both in their temporal and network structure, can influence the spread of sexually transmitted infections (STI). Most previous literature has focused on effects of network topology; few studies have addressed the role of temporal structure. We simulate disease spread using SI and SIR models on an empirical temporal network of sexual contacts in high-end prostitution. We compare these results with several other approaches, including randomization of the data, classic mean-field approaches, and static network simulations. We observe that epidemic dynamics in this contact structure have well-defined, rather high epidemic thresholds. Temporal effects create a broad distribution of outbreak sizes, even if the per-contact transmission probability is taken to its hypothetical maximum of 100%. In general, we conclude that the temporal correlations of our network accelerate outbreaks, especially in the early phase of the epidemics, while the network topology (apart from the contact-rate distribution) slows them down. We find that the temporal correlations of sexual contacts can significantly change simulated outbreaks in a large empirical sexual network. Thus, temporal structures are needed alongside network topology to fully understand the spread of STIs. On a side note, our simulations further suggest that the specific type of commercial sex we investigate is not a reservoir of major importance for HIV.

The prescription of oral contraceptives and its relation to the incidence of chlamydia and abortion in Sweden 1997-2005.

AIMS: The aim of this study is to examine the association between the prescription of oral contraceptives and the incidence of chlamydia, and between the prescription of oral contraceptives and the number of abortions in a population-based ecological study. METHODS: For this study we used register data from the Swedish Institute for Infectious Disease Control (chlamydia incidence), the Swedish National Board of Health and Welfare (number of abortions), Statistics Sweden (population data), and Apoteket (Swedish pharmacy) (prescriptions for oral contraceptives). We conducted ordinary least squares regression analysis of the association between chlamydia or abortions and the prescription of oral contraceptives. RESULTS: The prescription of oral contraceptives has a positive association on both the incidence of chlamydia and the numbers of abortion. Our best model predicts that prescription of 100 yearly doses of oral contraceptives increase the abortions by 3.3 cases among 16-year-old women and 0.7 cases among 29-year-old women, while cases of chlamydia increase by 6.7 among 16-year-old women and 1.5 among 29-year-old women. CONCLUSIONS: Our findings indicate that the use of oral contraceptives among young people and young adults is positively associated with the chlamydia incidence and the abortion rate in these populations in Sweden.

Scaling laws of human interaction activity.

Even though people in our contemporary technological society are depending on communication, our understanding of the underlying laws of human communicational behavior continues to be poorly understood. Here we investigate the communication patterns in 2 social Internet communities in search of statistical laws in human interaction activity. This research reveals that human communication networks dynamically follow scaling laws that may also explain the observed trends in economic growth. Specifically, we identify a generalized version of Gibrat's law of social activity expressed as a scaling law between the fluctuations in the number of messages sent by members and their level of activity. Gibrat's law has been essential in understanding economic growth patterns, yet without an underlying general principle for its origin. We attribute this scaling law to long-term correlation patterns in human activity, which surprisingly span from days to the entire period of the available data of more than 1 year. Further, we provide a mathematical framework that relates the generalized version of Gibrat's law to the long-term correlated dynamics, which suggests that the same underlying mechanism could be the source of Gibrat's law in economics, ranging from large firms, research and development expenditures, gross domestic product of countries, to city population growth. These findings are also of importance for designing communication networks and for the understanding of the dynamics of social systems in which communication plays a role, such as economic markets and political systems.

Preferential attachment in sexual networks.

Many social networks are characterized by a highly uneven distribution of links. The observed skewed distributions have in several cases been attributed to preferential attachment (PA), a tendency among nodes in a growing network to form new links preferentially to nodes with high numbers of links. We test the PA conjecture in sexual contact networks. A maximum likelihood estimation-based expectation-maximization fitting technique is used to model new partners over a 1-year period based on the number of partners in foregoing periods of 2 years, 4 years, and lifetime. The PA model is modified to account for individual heterogeneity in the inclination to find new partners and fitted to Norwegian survey data on heterosexual men and women. Results show evidence of nonrandom, sublinear PA when comparing the growth in 3- to 5-year periods. The potential implications of these findings are discussed.

Dynamic contact networks of patients and MRSA spread in hospitals.

Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult-to-treat infection. Increasing efforts have been taken to mitigate the epidemics and to avoid potential outbreaks in low endemic settings. Understanding the population dynamics of MRSA is essential to identify the causal mechanisms driving the epidemics and to generalise conclusions to different contexts. Previous studies neglected the temporal structure of contacts between patients and assumed homogeneous behaviour. We developed a high-resolution data-driven contact network model of interactions between 743,182 patients in 485 hospitals during 3,059 days to reproduce the exact contact sequences of the hospital population. Our model captures the exact spatial and temporal human contact behaviour and the dynamics of referrals within and between wards and hospitals at a large scale, revealing highly heterogeneous contact and mobility patterns of individual patients. A simulation exercise of epidemic spread shows that heterogeneous contacts cause the emergence of super-spreader patients, slower than exponential polynomial growth of the prevalence, and fast epidemic spread between wards and hospitals. In our simulated scenarios, screening upon hospital admittance is potentially more effective than reducing infection probability to reduce the final outbreak size. Our findings are useful to understand not only MRSA spread but also other hospital-acquired infections.

Nontrivial resource requirement in the early stage for containment of epidemics.

During epidemic control, containment of the disease is usually achieved through increasing a devoted resource to reduce the infectiousness. However, the impact of this resource expenditure has not been studied quantitatively. For disease spread, the recovery rate can be positively correlated with the average amount of resource devoted to infected individuals. By incorporating this relation we build a novel model and find that insufficient resource leads to an abrupt increase in the infected population size, which is in marked contrast with the continuous phase transitions believed previously. Counterintuitively, this abrupt phase transition is more pronounced in less contagious diseases. Furthermore, we find that even for a single infection source, the public resource needs to be available in a significant amount, which is proportional to the total population size, to ensure epidemic containment. Our findings provide a theoretical foundation for efficient epidemic containment strategies in the early stage.

Inferring individual sexual action dispositions from egocentric network data on dyadic sexual outcomes.

In this paper we present a family of models that allows us to estimate egos' unobserved action dispositions from a joint behavioural outcome of a dyadic social interaction process of both egos' and alters' action dispositions. The method is put to test on a data set containing two different types of dyadic activities of high relevance for the spread of sexually transmitted infections (STI), condom use and anal sex. The data consists of individuals older than 15 years old who visited one of the nine youth clinics in the Vastra Gotaland region of Sweden between February 2010 and March 2011 for STI testing. This is hence a group of special interest for STI interventions. We cannot find any difference in condom disposition between women and men. Condoms are initially used more often in less risky types of relationships, especially if the partner ends up as a main partner. When studying the disposition towards anal sex we do however find a difference between men and women. Women are more against practising anal sex than men while the majority of men are neutral towards anal sex.

Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developing such estimates remains challenging due to limited observation of colonization and complicated transmission dynamics within hospitals and the community. Here, we develop an inference framework that can estimate these key quantities by combining statistical filtering techniques, an agent-based model, and real-world patient-to-patient contact networks, and use this framework to infer nosocomial transmission and infection importation over an outbreak spanning 6 years in 66 Swedish hospitals. In particular, we identify a small number of patients with disproportionately high risk of colonization. In retrospective control experiments, interventions targeted to these individuals yield a substantial improvement over heuristic strategies informed by number of contacts, length of stay and contact tracing.

Improving immunization strategies.

We introduce an immunization method where the percentage of required vaccinations for immunity are close to the optimal value of a targeted immunization scheme of highest degree nodes. Our strategy retains the advantage of being purely local, without the need for knowledge on the global network structure or identification of the highest degree nodes. The method consists of selecting a random node and asking for a neighbor that has more links than himself or more than a given threshold and immunizing him. We compare this method to other efficient strategies on three real social networks and on a scale-free network model and find it to be significantly more effective.

Percolation theory applied to measures of fragmentation in social networks.

We apply percolation theory to a recently proposed measure of fragmentation F for social networks. The measure F is defined as the ratio between the number of pairs of nodes that are not connected in the fragmented network after removing a fraction q of nodes and the total number of pairs in the original fully connected network. We compare F with the traditional measure used in percolation theory, P(infinity), the fraction of nodes in the largest cluster relative to the total number of nodes. Using both analytical and numerical methods from percolation, we study Erdos-Rényi and scale-free networks under various types of node removal strategies. The removal strategies are random removal, high degree removal, and high betweenness centrality removal. We find that for a network obtained after removal (all strategies) of a fraction q of nodes above percolation threshold, P(infinity) approximately (1-F)1/2. For fixed P(infinity) and close to percolation threshold (q=qc), we show that 1-F better reflects the actual fragmentation. Close to qc, for a given P(infinity), 1-F has a broad distribution and it is thus possible to improve the fragmentation of the network. We also study and compare the fragmentation measure F and the percolation measure P(infinity) for a real social network of workplaces linked by the households of the employees and find similar results.

The effect of travel restrictions on the spread of a moderately contagious disease.

BACKGROUND: Much research in epidemiology has been focused on evaluating conventional methods of control strategies in the event of an epidemic or pandemic. Travel restrictions are often suggested as an efficient way to reduce the spread of a contagious disease that threatens public health, but few papers have studied in depth the effects of travel restrictions. In this study, we investigated what effect different levels of travel restrictions might have on the speed and geographical spread of an outbreak of a disease similar to severe acute respiratory syndrome (SARS). METHODS: We used a stochastic simulation model incorporating survey data of travel patterns between municipalities in Sweden collected over 3 years. We tested scenarios of travel restrictions in which travel over distances >50 km and 20 km would be banned, taking into account different levels of compliance. RESULTS: We found that a ban on journeys >50 km would drastically reduce the speed and geographical spread of outbreaks, even when compliance is < 100%. The result was found to be robust for different rates of intermunicipality transmission intensities. CONCLUSION: This study supports travel restrictions as an effective way to mitigate the effect of a future disease outbreak.

Finding Influential Spreaders from Human Activity beyond Network Location.

Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

Implementation of Web-Based Respondent Driven Sampling among Men Who Have Sex with Men in Sweden.

BACKGROUND: Respondent driven sampling (RDS) was designed to study 'hidden' populations, for which there are no available sampling frame. RDS has been shown to recruit far into social networks of the study population and achieve unbiased estimates when certain assumptions are fulfilled. Web-based respondent driven sampling (WebRDS) has been implemented among MSM in Vietnam and produced a sufficient sample of MSM. In order to see if WebRDS could work in a 'hidden' population in a high-income setting, we performed a WebRDS among MSM in Sweden to study a sensitive topic, sexual risk behaviour for HIV/STI and Internet use. METHODS: A cross-sectional survey was implemented between July 11, 2012 and January 21, 2013 by using a WebRDS software. Men, fifteen years old or above, who reported having ever had sex with another man were included. The web-survey explored sociodemographics, sexual risk behaviour for HIV/STI and Internet use. RESULTS: The WebRDS process created a sample of 123 eligible respondents. The mean age among participants was 32 years old. All respondents reported having had unprotected anal intercourse (UAI) with at least one regular and one casual sex partner during the last 12 months. On average participants reported having had UAI with three casual sexual partners and in total having had seven casual sex partners during the last 12 months. CONCLUSION: The WebRDS produced a sample of Internet-using MSM in Sweden who all reported sexual risk behaviour for HIV/STI during the last 12 months. It holds promise for future online studies among MSM and a possibility to reach MSM at risk for HIV/STI with interventions or information. Some challenges were found including short recruitment chains, and further research need to address how to optimize WebRDS online recruitment methods in high income settings.

Sexual networks: implications for the transmission of sexually transmitted infections.

The structures of sexual networks are essential for understanding the dynamics of sexually transmitted infections. Standard epidemiological models largely disregard the complex patterns of intimate contacts. Social network analysis offers important insight into how to conceptualize and model social interaction and has the potential to greatly enhance the understanding of disease epidemics.

Network bipartivity.

Systems with two types of agents with a preference for heterophilous interaction produce networks that are more or less close to bipartite. We propose two measures quantifying the notion of bipartivity. The two measures-one well known and natural, but computationally intractable, and the other computationally less complex, but also less intuitive-are examined on model networks that continuously interpolate between bipartite graphs and graphs with many odd circuits. We find that the bipartivity measures increase as we tune the control parameters of the test networks to intuitively increase the bipartivity, and thus conclude that the measures are quite relevant. We also measure and discuss the values of our bipartivity measures for empirical social networks (constructed from professional collaborations, Internet communities, and field surveys). Here we find, as expected, that networks arising from romantic online interaction have high, and professional collaboration networks have low, bipartivity values. In some other cases, probably due to low average degree of the network, the bipartivity measures cannot distinguish between romantic and friendship oriented interaction.