Human Mobility Monitoring using WiFi: Analysis, Modeling, and Applications

Understanding and modeling humans and device mobility has fundamental importance in mobile computing, with implications ranging from network design and location-aware technologies to urban infrastructure planning. Today\u27s users carry a plethora of devices such as smartphones, laptops, tablets, and smartwatches, with each device offering a different set of services resulting in different usage and mobility leading to the research question of understanding and modeling multiple user device trajectories. Additionally, prior research on mobility focuses on outdoor mobility when it is known that users spend 80% of their time indoors resulting in wide gaps in knowledge in the area of indoor mobility of users and devices. Here, I try to fill the gaps in mobility modeling in the areas of understanding and modeling indoor-outdoor human mobility as well as multi-device mobility. In this thesis, I propose the characterization and modeling of human and device mobility. Further, I design and deploy mobility-aware applications for contact tracing of infectious diseases and energy-aware Heating, Ventilation, and Air Conditioning (HVAC) scheduling. I try and answer a sequence of four primary inter-related questions : (1) how is indoor and outdoor user mobility different, (2) are multiple device trajectories belonging to a single user correlated, (3) how to model indoor mobility of users and (4) how to design effective mobility aware applications that are easily deployable and align with long term goals of sustainability as well relay positive societal impact. The insights gained from each question serves as a base to build up on the next question in the series. I present answers to these questions across three main parts of my thesis. The first part comprises of characterization and analysis of human and device mobility. In this part I design and develop tool to extract device trajectories from WiFi system logs syslog and map devices to users. These extracted trajectories and device to user mapping are used to characterize and empirically analyze the mobility of users at varying spatial granularity (indoor, outdoor) and extract device mobility correlations between multiple devices of users and forms the first part of my thesis. In the second part, based on the insights gained from the multi-granular and multi-device mobility characterization stated above, I argue that mobility is inherently hierarchical in nature and propose novel indoor human mobility modeling approach. Third, I leverage the passively observed mobility to design mobility-aware applications that either look back or look ahead in time. WiFiTrace is a look back or backtracking application that is a network-centric contact tracing tool to aid healthcare workers in manual contact tracing of infectious diseases and iSchedule is a look ahead machine learning based mobility-aware energy-saving application that predicts Heating, Ventilation, and Air Conditioning (HVAC) schedule for higher energy savings while increasing user comfort

The impact of limiting long term illness on internal migration in England and Wales: New evidence from census microdata

Previous research has suggested that poor health is associated with reduced migration; this knowledgestems from models based on past censuses, or longitudinal studies which imply that the factors influencing migration are the same between those in good and poor health. This paper addresses these issuesby utilising health-stratified analyses on the 2011 Census Individual Secure Sample for England and Wales.Multilevel models predict the odds of moving for working age adults, controlling for key predictors of migration, estimating the effect of health status on the odds of moving and the destination specific variance in migration. We find that those in poor health are less likely to move, after controlling for individual level characteristics. In contrast with expectations, economic inactivity, marriage and being in African, Caribbean, Black, Other or Mixed ethnic groups were not significant predictors ofmigration among the unhealthy sample, but were for the healthy sample. We conclude that migration is health-selective and propose implications for understanding area level concentrations of poor health in England and Wales

Combining school-catchment area models with geostatistical models for analysing school survey data from low-resource settings: Inferential benefits and limitations

School-based sampling has been used to inform targeted responses for malaria and neglected tropical diseases. Standard geostatistical methods for mapping disease prevalence use the school location to model spatial correlation, which is questionable since exposure to the disease is more likely to occur in the residential location. In this paper, we propose to overcome the limitations of standard geostatistical methods by introducing a modelling framework that accounts for the uncertainty in the location of the residence of the students. By using cost distance and cost allocation models to define spatial accessibility and in absence of any information on the travel mode of students to school, we consider three school catchment area models that assume walking only, walking and bicycling and, walking and motorized transport. We illustrate the use of this approach using two case studies of malaria in Kenya and compare it with the standard approach that uses the school locations to build geostatistical models. We argue that the proposed modelling framework presents several inferential benefits, such as the ability to combine data from multiple surveys some of which may also record the residence location, and to deal with ecological bias when estimating the effects of malaria risk factors. However, our results show that invalid assumptions on the modes of travel to school can worsen the predictive performance of geostatistical models. Future research in this area should focus on collecting information on the modes of transportation to school which can then be used to better parametrize the catchment area models

Scaling up integrated care: can community hospitals be an answer? A multiple-case study from the Emilia-Romagna region in Italy

Integrated care is considered to be essential in improving care for people with chronic conditions who need continuous care. In 2022, the Italian Government asked all regions to build or renovate a massive number of community care facilities, employing European Next Generation funds, to be spent by 2026. Under the theoretical lens of the Structural Contingency Theory, the paper aims at aims at describing the contextual and organizational factors underlying the interconnection between integrated care and community hospitals. The study employs a multiple-case study design, relying both on quantitative and qualitative data, conducted in a 6 months-period. It investigated seven community hospitals belonging to a single Local Health Authority in Emilia-Romagna region in Italy. The choice of the empirical context was driven by Emilia-Romagna's long- and well-established tradition of community-based care. Overall, our analysis shows that community hospitals offers opportunities of integrated care, including better integration between care sectors, between primary care and specialist staff, between healthcare structures and their local community. The study confirms the value of the Structural Contingency Theory and its key message: implementation is not a mechanical step of the policy cycle and requires important adjustments to the planning phase according to environment and organizational factors

Malnutrition assessment methods in adult patients with tuberculosis:A systematic review

OBJECTIVES: Malnutrition is associated with a twofold higher risk of dying in patients with tuberculosis (TB) and considered an important potentially reversible risk factor for failure of TB treatment. The construct of malnutrition has three domains: intake or uptake of nutrition; body composition and physical and cognitive function. The objectives of this systematic review are to identify malnutrition assessment methods, and to quantify how malnutrition assessment methods capture the international consensus definition for malnutrition, in patients with TB. DESIGN: Different assessment methods were identified. We determined the extent of capturing of the three domains of malnutrition, that is, intake or uptake of nutrition, body composition and physical and cognitive function. RESULTS: Seventeen malnutrition assessment methods were identified in 69 included studies. In 53/69 (77%) of studies, body mass index was used as the only malnutrition assessment method. Three out of 69 studies (4%) used a method that captured all three domains of malnutrition. CONCLUSIONS: Our study focused on published articles. Implementation of new criteria takes time, which may take longer than the period covered by this review. Most patients with TB are assessed for only one aspect of the conceptual definition of malnutrition. The use of international consensus criteria is recommended to establish uniform diagnostics and treatment of malnutrition. PROSPERO REGISTRATION NUMBER: CRD42019122832

Employed and unemployed search: The marginal willingness to pay for attributes in Lithuania, the US and the Netherlands

This paper introduces a method for estimating workers' marginal willingness to pay for job attributes employing data on job search activity. Worker's willingness to pay to avoid a temporary contract, which increases the risk of becoming unemployed, is derived for Lithuania. The empirical relevance of this method is further shown re-interpreting studies that examine search behaviour in the U.S. and the Netherlands. We provide estimates of workers' willingness to pay for a wide range of job attributes including the risk of becoming unemployed and promotion prospects. Further, we discuss and apply a method for estimating unemployed individuals' willingness to pay for recall opportunities and the residual entitlement perio

Development Studies Working Paper, no. 64

In recent years the number of people living in informal or 'squatter' settlements in South Africa has mushroomed and virtually every small town or city has one or more squatter settlements associated with it, often next door to the formal residential areas. Using field data collected from 1993 in two informal settlements in the Eastern Cape Province of South Africa this study examines, firstly, the ways in which men and women in these communities organise their lives in their households and in the wider society. Secondly, it assesses the physical environment of informal settlements where there is a lack of service infrastructure, especially water, sewerage facilities, refuse removal and roads. Also, it was assumed that the presence of large numbers of people in an informal settlement has a deleterious effect on natural resources like the soil, wood, vegetation and water and that this may have a significant contribution to environmental pollution and degradation. This aspect was also examined.Digitised by Rhodes University Library on behalf of the Institute of Social and Economic Research (ISER