The contact patterns among individuals can significantly affect the progress of an infectious outbreak within a population. Gathering data about these interaction and mixing patterns is essential to assess computational modeling of infectious diseases. Various self-report approaches have been designed in different studies to collect data about contact rates and patterns. Recent advances in sensing technology provide researchers with a bilateral automated data collection devices to facilitate contact gathering overcoming the disadvantages of previous approaches. In this study, a novel unilateral wearable sensing architecture has been proposed that overcome the limitations of the bi-lateral sensing. Our unilateral wearable sensing system gather contact data using hybrid sensor arrays embedded in wearable shirt. A smartphone application has been used to transfer the collected sensors data to the cloud and apply deep learning model to estimate the number of human contacts and the results are stored in the cloud database. The deep learning model has been developed on the hand labelled data over multiple experiments. This model has been tested and evaluated, and these results were reported in the study. Sensitivity analysis has been performed to choose the most suitable image resolution and format for the model to estimate contacts and to analyze the model's consumption of computer resources.

Thesis (PhD)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Water-borne infections have been a menace in many countries around the globe, claiming millions of lives. Cholera in particular has spread to all continents and now on its seventh epidemic. Although control measures have been continually developed through sanitation, vaccination and rehydration, the infection still devastates populations whenever there is an outbreak. In this research work, mathematical models for cholera transmission dynamics with focus on the impact of sanitation and hygiene, metapopulation spread, optimal control and biological control using a bacteriophage specific for pathogenic Vibrio cholerae are constructed and analysed. Vital analyses for the models are precisely given as well as numerical results depicting long term behaviour and the evolution of populations over time. The results of our analysis indicate that; improved sanitation and hand-hygiene are vital in reducing cholera infections; the spread of disease across metapopulations characterised by exchange of individuals and no cross community infection is associated with synchronous fluctuation of populations in both adjacent communities; during control of cholera, the control measures/efforts ought to be optimal especially at the beginning of the epidemic where the outbreak is often explosive in nature; and biological control if well implemented would avert many potential infections by lowering the concentration of pathogenic vibrios in the aquatic environment to values lower than the infectious dose. / AFRIKAANSE OPSOMMING: Water-infeksies is ’n bedreiging in baie lande regoor die wêreld en eis miljoene lewens. Cholera in die besonder, het op sy sewende epidemie na alle kontinente versprei. Hoewel beheermaatreëls voortdurend ontwikkel word deur middel van higiëne, inentings en rehidrasie, vernietig die infeksie steeds bevolkings wanneer daar ’n uitbraak voorkom. In hierdie navorsingswerk, word wiskundige modelle vir cholera-oordrag dinamika met die fokus op die impak van higiëne, metabevolking verspreiding, optimale beheer en biologiese beheer met behulp van ’n bakteriofaag spesifiek vir patogene Vibrio cholerae gebou en ontleed. Noodsaaklike ontledings vir die modelle is gegee sowel as numeriese resultate wat die langtermyn gedrag uitbeeld en die ontwikkeling van die bevolking oor tyd. Die resultate van ons ontleding dui daarop dat; verbeterde higiëne is noodsaaklik in die vermindering van cholera infeksies; die verspreiding van die siekte oor metapopulaties gekenmerk deur die uitruil van individue en geen kruis gemeenskap infeksie wat verband houmet sinchrone skommeling van bevolkings in beide aangrensende gemeenskappe; tydens die beheer van cholera,behoort die beheermaatreëls/pogings optimaal te wees veral aan die begin van die epidemie waar die uitbreking dikwels plofbaar in die natuur is; en biologiese beheer, indien dit goed geïmplementeer word, kan baie potensiële infeksies voorkom deur ’n vermindering in die konsentrasie van patogene vibrio in die water tot waardes laer as die aansteeklike dosis.

Many infectious diseases are spread through interactions between susceptible and infectious individuals. Keeping track of where each exposure to the disease took place, when it took place, and which individuals were involved in the exposure can give public health officials important information that they may use to formulate their interventions. Further, knowing which individuals in the population are at the highest risk of becoming infected with the disease may prove to be a useful tool for public health officials trying to curtail the spread of the disease. Epidemiological models are needed to allow epidemiologists to study the population dynamics of transmission of infectious agents and the potential impact of infectious disease control programs. While many agent-based computational epidemiological models exist in the literature, they focus on the spread of disease rather than exposure risk. These models are designed to simulate very large populations, representing individuals as agents, and using random experiments and probabilities in an attempt to more realistically guide the course of the modeled disease outbreak. The work presented in this thesis focuses on tracking exposure risk to chickenpox in an elementary school setting. This setting is chosen due to the high level of detailed information realistically available to school administrators regarding individuals' schedules and movements. Using an agent-based approach, contacts between individuals are tracked and analyzed with respect to both individuals and locations. The results are then analyzed using a combination of tools from computer science and geographic information science.

Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Clinical results have indicated that abuse of multiple drugs/substances has devastating health and social consequences. The combined abuse of alcohol and the highly addictive methamphetamine has worsened the drug epidemic in South Africa, especially in the Western Cape Province. Using non-linear ordinary differential equations, we formulate a deterministic mathematical model for alcohol-methamphetamine coabuse epidemic. We prove that the growth of the co-abuse epidemic is dependent on the threshold parameters of the individual substances of abuse. The substance with the maximum reproduction number dominates the epidemic. We also prove that the equilibria points of the co-abuse sub-models are locally and globally asymptotically stable when the sub-model threshold parameters are less than unity. Using parameters values derived from the sub-model fittings to data, a population estimate of co-users of alcohol and methamphetamine under treatment is estimated with a prevalence of about 1%. Although the results show of a small proportion of co-users of alcohol and methamphetamine in the province, the prevalence curve is indicative of a persistent problem. Numerical simulation results reveal that co-abuse epidemic would persists when both reproduction numbers are greater than one. Results from sensitivity analysis shows that the individual substance transmission rates between users of methamphetamine and/or alcohol and the general susceptible population are the most vital parameters in the co-abuse epidemic. This suggests the need to emphasise on preventive measures through educational campaigns and social programs that ensure minimal recruitment into alcohol or methamphetamine abuse. Model analysis using the time-dependent controls (policies) emphasizes the need to allocate even more resources on educational campaigns against substance abuse and on effective treatment services that minimizes or eliminates rampant cases of relapse into substance abuse. / AFRIKAANSE OPSOMMING: Kliniese resultate toon dat die misbruik van meer as een dwelmmiddel verwoestende gesondheids-en sosiale gevolge het. Die gekombineerde misbruik van alkohol en die hoogsverslawende methamphetamine het die dwelm-epidemie in Suid-Afrika vererger, veral in die Wes-Kaapse provinsie. Deur van nie-lineere gewone diffensiaalvergelykings gebruik te maak, formuleer ons ’n deterministiese wiskundige model vir epidemie van die gesamentlike misbruik van alkohol en methamphetamine. Ons toon aan dat die groei van die sogenaamde mede-misbruik epidemie afhanklik is van die drumpelparameters van die individuele middels wat misbruik word. Die middels met die grootste voortbringende syfer domineer die epidemie. Ons bewys ook dat die ekwilibriumpunte van die mede-misbruik submodelle plaaslik en globaal asimptoties stabiel is wanneer die sub-model drumpelparameters kleiner as een is. Deur die submodelle op werklike data te pas word waardes vir die drumpelparameters afgelei en word daar beraam dat daar ongeveer 1% van die populasie mede-misbruikers van alkohol en methamphetamine onder behandeling is. Alhoewel die data ’n klein persentasie van mede-misbruikers van alkohol en methamphetamine in die provinsie toon, dui die voorkomskurwe op ’n groeiende endemie en voortdurende probleem. Resultate uit numeriese simulasie toon dat die mede-misbruik epidemie sal voortduur indien beide reproduserende syfers groter as een sal wees. Resultate van sensitiwiteitsanalise toon dat die individuele middeloordragkoerse tussen gebruikers van methamphetamine en/of alkohol en die gewone vatbare populasie die mees noodsaaklike parameters in die mede-misbruik epidemie is. Dit stel voor dat daar meer klem gelê moet word op voorkomingsmaatreëls deur opvoedkundige veldtogte en sosiale programme om te verseker dat minder alkohol en/of methamphetamine misbruik sal word. Model-analise wat gebruik maak van tyd-afhanklike kontroles (beleide) lê verder klem op die feit dat selfs meer hulpbronne aan opvoedkundige veldtogte teen dwelmmisbruik toegewy moet word, asook die effektiewe behandeling wat gevalle van terugval in dwelmmisbruik sal minimeer of elimineer.

Some Epidemic models with fractional derivatives were proved to be well-defined, well-posed and more accurate [34, 51, 116], compared to models with the conventional derivative. An Ebola epidemic model with non-linear transmission is fully analyzed. The model is expressed with the conventional time derivative with a new parameter included, which happens to be fractional (that derivative is called the 􀀀derivative). We proved that the model is well-de ned and well-posed. Moreover, conditions for boundedness and dissipativity of the trajectories are established. Exploiting the generalized Routh-Hurwitz Criteria, existence and stability analysis of equilibrium points for the Ebola model are performed to show that they are strongly dependent on the non-linear transmission. In particular, conditions for existence and stability of a unique endemic equilibrium to the Ebola system are given. Numerical simulations are provided for particular expressions of the non-linear transmission, with model's parameters taking di erent values. The resulting simulations are in concordance with the usual threshold behavior. The results obtained here may be signi cant for the ght and prevention against Ebola haemorrhagic fever that has so far exterminated hundreds of families and is still a ecting many people in West-Africa and other parts of the world. The full comprehension and handling of the phenomenon of shattering, sometime happening during the process of polymer chain degradation [129, 142], remains unsolved when using the traditional evolution equations describing the degradation. This traditional model has been proved to be very hard to handle as it involves evolution of two intertwined quantities. Moreover, the explicit form of its solution is, in general, impossible to obtain. We explore the possibility of generalizing evolution equation modeling the polymer chain degradation and analyze the model with the conventional time derivative with a new parameter. We consider the general case where the breakup rate depends on the size of the chain breaking up. In the process, the alternative version of Sumudu integral transform is used to provide an explicit form of the general solution representing the evolution of polymer sizes distribution. In particular, we show that this evolution exhibits existence of complex periodic properties due to the presence of cosine and sine functions governing the solutions. Numerical simulations are performed for some particular cases and prove that the system describing the polymer chain degradation contains complex and simple harmonic poles whose e ects are given by these functions or a combination of them. This result may be crucial in the ongoing research to better handle and explain the phenomenon of shattering. Lastly, it has become a conjecture that power series like Mittag-Le er functions and their variants naturally govern solutions to most of generalized fractional evolution models such as kinetic, di usion or relaxation equations. The question is to say whether or not this is always true! Whence, three generalized evolution equations with an additional fractional parameter are solved analytically with conventional techniques. These are processes related to stationary state system, relaxation and di usion. In the analysis, we exploit the Sumudu transform to show that investigation on the stationary state system leads to results of invariability. However, unlike other models, the generalized di usion and relaxation models are proven not to be governed by Mittag-Le er functions or any of their variants, but rather by a parameterized exponential function, new in the literature, more accurate and easier to handle. Graphical representations are performed and also show how that parameter, called ; can be used to control the stationarity of such generalized models. / Mathematical Sciences / Ph. D. (Applied Mathematics)

Traditional Public Health decision-support can benefit from the Web and social media revolution. This dissertation presents approaches to mining social media benefiting public health epidemiology. Through discovery and analysis of trends in Influenza related blogs, a correlation to Centers for Disease Control and Prevention (CDC) influenza-like-illness patient reporting at sentinel health-care providers is verified. A second approach considers personal beliefs of vaccination in social media. A vaccine for human papillomavirus (HPV) was approved by the Food and Drug Administration in May 2006. The virus is present in nearly all cervical cancers and implicated in many throat and oral cancers. Results from automatic sentiment classification of HPV vaccination beliefs are presented which will enable more accurate prediction of the vaccine's population-level impact. Two epidemic models are introduced that embody the intimate social networks related to HPV transmission. Ultimately, aggregating these methodologies with epidemic and social network modeling facilitate effective development of strategies for targeted interventions.

Indiana University-Purdue University Indianapolis (IUPUI) / Identifying spatial and temporal patterns of disease occurrence by mapping the residential locations of affected people can provide information that informs response by public health practitioners and improves understanding in epidemiological research. A common method of locating patients at the individual level is geocoding residential addresses stored in electronic medical records (EMRs) using address matching procedures in a geographic information system (GIS). While the process of geocoding is becoming more common in public health studies, few researchers take the time to examine the effects of using different address databases on match rate and positional accuracy of the geocoded results. This research examined and compared accuracy and match rate resulting from four commonly-used geocoding databases applied to sample of 59,341 subjects residing in and around Marion County/ Indianapolis, IN. The results are intended to inform researchers on the benefits and downsides to their selection of a database to geocode patient addresses in EMRs.