Infectious diseases, including influenza, measles, and sexually transmitted diseases, spread from person to person. Different attempts have been made to modify or extend traditional epidemic models to relax homogeneity assumptions, so as to handle more complex and realistic situations. We propose a network-based approach to the modeling and prediction of infectious disease outbreaks. Our focus is on heterogeneous populations where there is variation in individual susceptibility, infectivity, and person-to-person contact patterns. To address the complexity of disease propagation over a contact network, we develop a Bayesian survival model that maps the network onto a latent space and uses latent positions to predict disease transmission. We present an R package (`epinet') implementation of our methods and an application to a high school contact network. The package uses C code to implement an MCMC algorithm to efficiently estimate parameters and predict disease outcomes. Our application involves contact data collected by mobile sensors distributed to individuals, and provides estimates of disease transmission in line with the network structure. In it, we address issues that are of direct interest to public health professionals, such as prediction of future outbreaks of diseases. Questions such as whether quarantine will help mitigate an outbreak can also be explored using our proposed model.

The subject of this thesis is the study of a system of multiple simultaneously spreading diseases, or strains of diseases, in a structured host population. The disease spread is modelled using the well-studied SEIR compartmental model; host population structure is imposed through the use of random graphs, in which each host individual is explicitly connected to a predetermined set of other individuals. Two different graph structures are used: Zipf power-law distributed graphs, in which individuals vary greatly in their number of contacts; and Poisson distributed graphs, in which there is very little variation in the number of contacts. Three separate explorations are undertaken. In the first, the extent to which two SEIR processes will overlap due to chance is examined in the case where they do not affect each other's ability to spread. The overlap is found to increase with increased heterogeneity in the number of contacts, all things equal. Introducing differences in infection probability or a delay between introducing the two strains produces more complex dynamics. I then extend the model to allow strains to modify each other's transmissibility. This is found to lead to modest changes in the size of the outbreak of affected strains, and larger effects on the size of the overlap. The extent of the effect is found to depend strongly on the order in which the strains are introduced to the population. Zipf graphs experience somewhat larger reductions in outbreak size and less reduction of overlap size, but overall the two graphs experience similar effects. This is due to the reduced effect of modification in key high-degree vertices in the Zipf graph being offset by higher local clustering. Finally, I introduce recombination and competition by replacement into the model from the first project. The number of recombinant strains that arise is found to be either very low or very high, with chance governing which occurs. Recombinant strains in Zipf distributed graphs have a significant chance of failing to spread, but not in Poisson distributed graphs. Replacement competition in the presence of a growing number of strains is found to both increase the chance of a strain failing to spread, and to reduce the overall size of outbreaks. This effect is equal in both graph types.

We create a dynamic network model to replicate more closely the population network structures of interest. Network, Norms and HIV/STI Risk Among Youth (NNAHRAY) is a community relationship survey data set, which provides a rare sample of a human risky-behavior contact network. Combining disease compartmental models with our dynamic network model, we simulate the spread of Human Immunodeficiency Virus (HIV) and Herpes Simplex Type 2 Virus (HSV2) with consideration of HSV2's synergistic impact on HIV's transmission. Our model reproduces HIV prevalence, HSV-2 prevalence, and the contact network close to those observed in NNAHRAY, with HIV annual prevalence closer to the estimated values from the literature than those of any disease spread model based on static networks. The success of fitting our model to the target data shows the importance of considering the data sampling process, contact dynamics, and contact network structures. Our model, under certain conditions, has prevalence prediction results that are insensitive to changes in network size. The analysis of various prevention/intervention strategies targeting different risky groups gives important insights into strategy prioritization and illustrates how our model can be used to assist in making public health policy decisions in practice, both for individual diseases and in the more-recent area of study that considers synergy between two diseases.

Epidemiological models traditionally make the assumption that populations are homogeneous. By relaxing that assumption, models often become more complicated, but better representations of the real world. Here we describe new computational tools for studying heterogeneous populations, and we examine consequences of two particular types of heterogeneity: that people are not all equally likely to interact, and that people are not all equally likely to become infected if exposed to a pathogen. Contact network epidemiology provides a robust and flexible paradigm for thinking about heterogeneous populations. Despite extensive mathematical and algorithmic methods, however, we lack a programming framework for working with epidemiological contact networks and for the simulation of disease transmission through such networks. We present EpiFire, a C++ applications programming interface and graphical user interface, which includes a fast and efficient library for generating, analyzing and manipulating networks. EpiFire also provides a variety of traditional and network-based epidemic simulations. Heterogeneous population structure may cause multi-wave epidemics, but urban populations are generally assumed to be too well mixed to have such structure. Multi-wave epidemics are not predicted by simple models, and are particularly problematic for public health officials deploying limited resources. Using a unique empirical interaction network for 103,000 people in Montreal, Canada, we show that large, urban populations may feature sufficient community structure to drive multi-wave dynamics, and that highly connected individuals may play an important role in whether communities are synchronized. Finally, we show that heterogeneous immunity is an important determinant of influenza epidemic size. While many epidemic models assume a homogeneously susceptible population and describe dynamics for one season, the trans-seasonal dynamics of partially immunizing diseases likely play a critical role in determining both future epidemic size and pathogen evolution. We present a multi-season network model of a population exposed to a pathogen conferring partial cross-immunity that decays over time. We fit the model to 25 years of influenza-like illness epidemic data from France using a novel Bayesian technique. Using conservative priors, we estimate important epidemiological quantities that are consistent with empirical studies. / text

El presente proyecto consiste en la creación de un canal de contacto especializado para estudiantes de la comunidad universitaria UPC dentro de la red social Facebook, con la finalidad de que puedan encontrar un espacio online para realizar consultas y/o solicitar servicios sobre asesoramiento y mentoría en cursos de diversas facultades a otros estudiantes o egresados de la universidad, los cuales participarán bajo una modalidad de trabajo freelance. La elección de este mercado objetivo se obtuvo mediante una investigación realizada en un grupo cerrado creado en Facebook destinado para los estudiantes de la UPC, “¿Con qué profesor de la UPC debo matricularme?”. En este portal se detectaron publicaciones de diferentes estudiantes solicitando servicios de asesoría para reforzamiento en diversas materias, como también mentoría para los trabajos parciales y finales. Este grupo de personas comentaron que no es un canal adecuado para realizar dichas solicitudes y cuando han encontrado la “solución” este les llega por correo y en diferentes ocasiones han perdido tiempo, dinero y la calidad del servicio no fue buena. Sin embargo, ese grupo es el nexo que tiene la comunidad de universitarios y es el que más frecuentan. A partir de ello, se encontró la problemática de que los estudiantes de educación superior gastan demasiado tiempo y dinero en la búsqueda de freelancers, arriesgando la calidad de los servicios solicitados. Freelo resulta ser un proyecto viable debido a que los resultados obtenidos en la utilidad neta proyectada para los 3 años son los siguientes: primer año S/. 6,269, segundo año S/.33,400 y tercer año S/. 55,064. / This project consists of the creation of a specialized contact channel for students of the UPC university community within the social network Facebook, so that they can find an online space to make inquiries and / or request advisory and mentoring services in courses from various faculties to other students or graduates of the university, who will participate under a freelance job modality. The choice of this target market was obtained through research carried out in a closed group created on Facebook for UPC students, its name is "Which UPC professor should I enroll with?". In this portal, publications of different students were detected, requesting advisory services for reinforcement in various subjects, as well as mentoring for partial and final works. This group of people also commented that it is not the proper channel to make such requests and when they have found the “solution” it comes in the mail and on different occasions they have lost time, money and quality of service was not good. However, this group is the link that the university community has and is the one that they frequent the most. From this, the problem was found that higher education students spend too much time and money searching for freelancers, risking the quality of the services requested. Freelo turns out to be a viable project because the results obtained in the projected net profit for the 3 years are as follows: first year S /. 6,269, second year S / .33,400 and third year S /. 55,064. / Trabajo de investigación

No description available.

Social contact networks represent proximity relationships between individual agents. Such networks are useful in diverse applications, including epidemiology, wireless networking and urban resilience. The vertices of a social contact network represent individual agents (e.g. people). Time varying edges represent time varying proximity relationship. The networks are relational -- node and edge labels represent important demographic, spatial and temporal attributes. Synthesizing social contact networks that span large urban regions is challenging for several reasons including: spatial, temporal and relational variety of data sources, noisy and incomplete data, and privacy and confidentiality requirements. Moreover, the synthesized networks differ due to the data and methods used to synthesize them. This dissertation undertakes a systematic study of synthesizing urban scale social contact networks within the specific application context of computational epidemiology. It is motivated by three important questions: (i) How does one construct a realistic social contact network that is adaptable to different levels of data availability? (ii) How does one compare different versions of the network for a given region, and what are appropriate metrics when comparing the relational networks? (iii) When does a network have adequate structural details for the specific application we have. We study these questions by synthesizing three social contact networks for Delhi, India. Our case study suggests that we can iteratively improve the quality of a network by adapting to the best data sources available within a framework. The networks differ by the data and the models used. We carry out detailed comparative analyses of the networks. The analysis has three components: (i) structure analysis that compares the structural properties of the networks, (ii) dynamics analysis that compares the epidemic dynamics on these networks and (iii) policy analysis that compares the efficacy of various interventions. We have proposed a framework to systematically analyze how details in networks impact epidemic dynamics over these networks. The results suggest that a combination of multi-level metrics instead of any individual one should be used to compare two networks. We further investigate the sensitivity of these models. The study reveals the details necessary for particular class of control policies. Our methods are entirely general and can be applied to other areas of network science. / Ph. D.

Yes / Mammalian genomes contain several dozens of large (>0.5 Mbp) lineage-specific gene loci harbouring functionally related genes. However, spatial chromatin folding, organization of the enhancer-promoter networks and their relevance to Topologically Associating Domains (TADs) in these loci remain poorly understood. TADs are principle units of the genome folding and represents the DNA regions within which DNA interacts more frequently and less frequently across the TAD boundary. Here, we used Chromatin Conformation Capture Carbon Copy (5C) technology to characterize spatial chromatin interaction network in the 3.1 Mb Epidermal Differentiation Complex (EDC) locus harbouring 61 functionally related genes that show lineage-specific activation during terminal keratinocyte differentiation in the epidermis. 5C data validated by 3D-FISH demonstrate that the EDC locus is organized into several TADs showing distinct lineage-specific chromatin interaction networks based on their transcription activity and the gene-rich or gene-poor status. Correlation of the 5C results with genome-wide studies for enhancer-specific histone modifications (H3K4me1 and H3K27ac) revealed that the majority of spatial chromatin interactions that involves the gene-rich TADs at the EDC locus in keratinocytes include both intra- and inter-TAD interaction networks, connecting gene promoters and enhancers. Compared to thymocytes in which the EDC locus is mostly transcriptionally inactive, these interactions were found to be keratinocyte-specific. In keratinocytes, the promoter-enhancer anchoring regions in the gene-rich transcriptionally active TADs are enriched for the binding of chromatin architectural proteins CTCF, Rad21 and chromatin remodeler Brg1. In contrast to gene-rich TADs, gene-poor TADs show preferential spatial contacts with each other, do not contain active enhancers and show decreased binding of CTCF, Rad21 and Brg1 in keratinocytes. Thus, spatial interactions between gene promoters and enhancers at the multi-TAD EDC locus in skin epithelial cells are cell type-specific and involve extensive contacts within TADs as well as between different gene-rich TADs, forming the framework for lineage-specific transcription. / This study was supported by the grants 5R01AR064580 and 1RO1AR071727 to VAB, TKS and AAS, as well as by the grants from MRC (MR/ M010015/1) and BBSRC (BB/K010050/1) to VAB.

When attempting to mitigate the spread of an epidemic without the use of a vaccine, many measures may be made to dampen the spread of the disease such as physically distancing and wearing masks. The implementation of an effective test and quarantine strategy on a population has the potential to make a large impact on the spread of the disease as well. Testing and quarantining strategies become difficult when a portion of the population are asymptomatic spreaders of the disease. Additionally, a study has shown that randomly testing a portion of a population for asymptomatic individuals makes a small impact on the spread of a disease. This thesis simulates the transmission of the virus that causes COVID-19, SARSCoV- 2, in contact networks gathered from real world interactions in five different environments. In these simulations, several testing and quarantining strategies are implemented with a varying number of tests per day. These strategies include a random testing strategy and several uniform testing strategies, based on knowledge of the underlying network. By modeling the population interactions as a graph, we are able to extract properties of the graph and test based on those metrics, namely the degree of the network. This thesis found many of the strategies had a similar performance to randomly testing the population, save for testing by degree and testing the cliques of the graph, which was found to consistently outperform other strategies, especially on networks that are more dense. Additionally, we found that any testing and quarantining of a population could significantly reduce the peak number of infections in a community.

This thesis focuses on students’ encounters with working life. The thesis aims to contribute to an increased understanding of the potential value of digital job portals in interplay with traditional social networks by capturing students’ perceptions of their paths to working life. A qualitative research method has been applied where respondents from University West have been interviewed both individually and in groups. Both current and previous students were included in the study. Eleven semi-structured individual interviews and two group interviews were conducted and recorded with the support of field notes. Based on this combined approach, which also permitted interaction among the respondents, the study could capture a greater variety of both current and previous students’ experiences. The study contributes with knowledge based on a number of students’ experiences of their encounters with working life, both before and after completing their studies at the university. The results of the study suggest that the interplay between digital job portals and traditional contact networks is of great importance. Digital job portals seem to provide a broad picture of the job opportunities in relation to the education, while the contact networks provide more in-depth understanding as well as relationships that might contribute to actual job offers. Hence, values are created as a result of their interplay. In addition, the study shows that the practice part of the work integrated learning approach at University West is instrumental for students in enriching their contact networks and that this, in turn, often result in their first jobs. On the basis of the results, recommendations are suggested for further studies as well as for actions that might improve the students’ paths to working life.The recommendations concern capturing of previous students’ experiences, analysis of the effects of Work Integrated Learning and in particular different forms of practice, exploringmore aspects of comp / Denna studie handlar om studenters möte med arbetslivet. Syftet har varit att bidra till en ökad förståelse för digitala jobbportalers potentiella värde för studenter i samspel med traditionella kontaktnätverk i studenternas möte med arbetslivet. En kvalitativ forskningsmetod har tillämpats där respondenter i form av alumner och sistaårsstudenter från Högskolan Väst har fått svara på frågor både enskilt och i grupp. Elva semistrukturerade enskilda intervjuer samt två gruppintervjuer har genomförts och spelats inmed stöd av fältanteckningar. Detta för att få en djupare förståelse för respondenternas upplevelser och erfarenheter av vägen till arbetslivet.Studien bidrar med kunskap om ett antal studenters upplevelser och erfarenhet av mötet med arbetslivet, både innan och efter avslutade studier på Högskolan Väst. Studiens resultat tyder på att samspelet mellan digitala jobbportaler och traditionella kontaktnätverk har en stor betydelse. Ett sätt att beskriva samspelet skulle kunna vara att digitala jobbportaler bidrar till en bred bild av arbetsmarknaden kopplat till utbildningen medan kontaktnäten bidrar till djupare förståelse och relationer som kan leda vidare till jobb. Värde skapas i hur dessa kompletterar och samspelar med varandra. I tillägg visar studien på att arbetsintegrerat lärande inte endast är viktigt för att koppla samman teori och praktik utan praktikperioder bidrar även till att berika studenternas kontaktnät, som i sin tur kan skapa förutsättningar för studenterna att få ett första arbete efter studierna. Med utgångspunkt i resultatet utformades rekommendationer för fortsatt arbete. Dessa rör att ta tillvara på tidigare studenters erfarenheter av vägen till arbete, analysera effekterna av AIL och särskilt olika former av praktik, utforska fler aspekter av kompetensförsörjning och -förmedling, samt digitala jobbportalers utformning och funktion.