D'après le rapport de l'OMS en 2015, près de la moitié de la population mondiale est exposée au risque du paludisme et le plus grand nombre des cas recensés se trouve en Afrique subsaharienne. Madagascar fait partie des pays où le paludisme est encore endémique. La géographie et le climat de l'île se traduisent par une répartition assez particulière du paludisme. Les plus fortes incidences sont observées sur les littoraux alors que les plus faibles le sont sur les Hautes Terres Centrales. Cinq zones épidémiologiques et opérationnelles ont été définies par les services de lutte contre le paludisme : Est, Ouest, Sud, Hautes Terres et les Marges. Cette étude vise à apporter une meilleure compréhension de l'épidémiologie du paludisme et de mesurer l'impact des mobilités humaines sur la transmission des zones à forte transmission vers les zones à faible transmission afin de contribuer à mieux cibler les actions de contrôle par les acteurs de la santé publique. Elle offre une nouvelle approche permettant d'évaluer la dynamique spatio-temporelle du paludisme, de quantifier la circulation de l'infection palustre en tenant compte de la mobilité de la population par l’utilisation des données de téléphonie mobile et d'identifier les principales zones exportatrices et importatrices de la maladie. En premier lieu, à travers une analyse rétrospective des données d'incidence, ce travail a montré une hétérogénéité évidente dans chaque stratification épidémiologique et la recrudescence de la maladie sur les Hautes Terres et les Marges. En second lieu, indépendamment de la densité de la population, nous avons montré que les Hautes Terres et surtout la capitale Antananarivo sont une zone à fort risque d'importation de paludisme et que les zones exportatrices sont surtout situées à l'Est et à l'Ouest. Enfin, notre enquête de terrain a souligné l'importance d'une mobilité inter district faible et d'une mobilité intra district voire intra communale importante qui mériterait d'être prise en compte dans la mesure de la circulation de l'infection palustre. Cette étude a permis de mettre en lumière que le paludisme est très dynamique à Madagascar avec un degré d'intensité différent même si les zones appartiennent à la même stratification. Ce constat devrait se traduire par une adaptation des stratégies de lutte. Enfin, la mobilité humaine joue un rôle important dans la transmission. A l'heure où la téléphonie mobile s'est largement diffusée à Madagascar, son utilisation pour estimer le déplacement des populations devient un outil pertinent pour contribuer à orienter le contrôle des maladies. / According to the 2015 WHO report, almost half of the world population is exposed to malaria, with the largest number of reported cases in sub-Saharan Africa. Madagascar is one of the countries where malaria is still endemic because of its geographical location. As a matter of fact, the geography and climate of the island gives a specific epidemiological stratification of malaria. There are five malaria epidemiological zones: East, West, South, Highlands and Fringe. The highest incidence is observed on coastal areas, while the lowest incidence is observed on the Central Highlands. This study aims to provide a better understanding of the epidemiology of malaria and to measure the impact of human mobility on transmission from high transmission areas to low transmission areas in order to help better target control actions by public health actors. This study proposes an alternative approach to assess the spatiotemporal dynamics of malaria, quantify the circulation of malaria infection and take into account the mobility of the population to identify the main source and sink areas of malaria. Firstly, through a retrospective analysis of incidence data, this work showed a clear heterogeneity in each stratum, and an increase the Highlands and the Fringe areas. Secondly, regardless of the population density, we have shown that the Highlands and especially the capital of Madagascar, Antananarivo, was a zone at high risk of the importation of malaria. The source areas were mainly in the eastern and the western part of the country. Finally, our field survey highlighted the importance of low inter-district mobility and high intra-district or even intra-communal mobility which should be taken into consideration when assessing the spreading of malaria infection. This study revealed that malaria is very dynamic in Madagascar with a different degree of intensity even if such areas belong to the same stratum. This observation should translate into an adaptation of control strategies. Finally, human mobility plays a leading part in the transmission. At a time when mobile telephony has spread widely in Madagascar, its use to estimate the mobility of populations is becoming a relevant tool to help guide disease control.

Leadership has been claimed to be a critical determinant of success and failure in international negotiations. This thesis brings together the study of leadership in multilateral negotiations with the emerging discipline of climate change-induced human mobility. This is done by investigating the prevalence of leadership in the climate change and human mobility nexus, looking at three different actors: the Alliance of Small Island States, Bangladesh and Norway. These actors were analyzed in two different ways: first, by describing how each actor exercise leadership using an analytical framework informed by leadership theories. Second, by investigating whether these actors seem to be recognized as leaders by others, conducting and analyzing a survey from the United Nations Climate Change Conference 2018, COP24. The results indicate that all three actors can be said to exercise leadership in the area of climate change-induced migration, although they exercise leadership in slightly different ways. Out of the three actors that were analyzed, AOSIS was the only actor that seemed to be recognized by others as a leader in the effort to address climate change-induced human mobility.

The gradually communitisation of migration policies in the European Union (EU) coincides with the increase of human flows in the Schengen area, driven largely by the characteristics and economic demands of the global network society. In this process, the tension is deposited between the need for Community harmonization in the embryonic foundations of a principle of solidarity aimed at protecting humanana mobility ("Europe without borders") and the effective adoption of legal acts sustained by the security perception of migration ("Fortress Europe"). Under such assumptions, the research analyzes the communitarisation process of selective migration policies (refoulement of irregular immigrants and attracting highly skilled workers) and the emergence of immigration restriction techniques (technological surveillance of external borders and landless of migration control), with special Featured establishing a European Border Surveillance System (EUROSUR). We opted for the dialectical-inductive approach to the topic in order to suit the analysis of the intertwining of migration policies, normative acts and judicial decisions and their itineraries and contextual contradictions. As for the procedure, especially the monographic methods were used, historical, comparative and case study. It investigates how human mobility in Europe fall within the overall context of migration, through the analysis of normative sources devoted to ticket management and national residence of third countries in the EU, with the purpose of gauging how is the division of powers on migration. We analyze also the human rights guaranteed to migrants through the jurisprudence of the European Court of Human Rights (ECHR) and the Agency's reports of the European Union Fundamental Rights (EU). Community Directives were analyzed related to the co-optation of qualified immigrants and immigrant repulsion undocumented, featured reflections of the security obsession that marks the European migration strategies. Finally, it approaches the implementation of EUROSUR, relating to the consolidation of surveillance as an emerging paradigm in the global legal scenario. Finally, it is concluded that the regional management of migration under the logic of selectivity by giving a Community surveillance, accelerates economic crises in countries of origin, increasing the volume of mobility towards the destination countries. / A progressiva comunitarização das políticas migratórias no âmbito da União Europeia (UE) coincide com o aumento dos fluxos humanos no espaço Schengen, motivado, em larga medida, pelas características e demandas econômicas da sociedade global em rede. Nesse processo, sedimenta-se a tensão entre a necessidade de harmonização comunitária sobre os fundamentos embrionários de um princípio de solidariedade voltado à proteção da mobilidade humana ( Europa sem fronteiras ) e a efetiva adoção de atos jurídicos sustentados por uma percepção securitária das migrações ( fortaleza Europa ). Sob tais premissas, a pesquisa analisa o processo de comunitarização de políticas migratórias seletivas (repulsão de imigrantes irregulares e atração de trabalhadores altamente qualificados) e a emergência de técnicas de restrição migratória (vigilância tecnológica das fronteiras externas e desterritorialização do controle migratório), com especial destaque à criação do Sistema Europeu de Vigilância de Fronteiras (EUROSUR). Optou-se pela abordagem dialético-indutiva do tema, a fim de adequar a análise ao entrelaçamento entre políticas migratórias, atos normativos, decisões judiciais e seus respectivos itinerários e contradições contextuais. Já quanto ao procedimento, foram utilizados sobretudo os métodos monográfico, histórico, comparativo e estudos de caso. Investiga-se de que modo a mobilidade humana na Europa se insere no contexto global das migrações, através da análise das fontes normativas consagradas à gestão do ingresso e permanência de nacionais de países terceiros no território da UE, com o fim de aferir como se dá a repartição de competências em matéria migratória. Analisa-se, também, os direitos humanos garantidos aos migrantes através da jurisprudência da Corte Europeia de Direitos Humanos e dos relatórios da Agência dos Direitos Fundamentais da União Europeia. Foram analisadas Diretivas comunitárias relacionadas à cooptação de imigrantes qualificados e repulsão de imigrantes em situação irregular, reflexos destacados da obssessão securitária que marca as estratégias migratórias europeias. Por fim, aborda-se a implementação do EUROSUR, relacionando-a à consolidação da vigilância como paradigma emergente no cenário jurídico global. Ao final, conclui-se que a gestão regional da migração sob a lógica da seletividade, através da comunitarização da vigilância, além de incompatível com as diretrizes do cosmopolitismo migratório, também acelera as crises econômicas nos países de origem, intensificando o volume da mobilidade rumo aos países de destino.

Mobile devices such as smartphones and smart watches are ubiquitous companions of humans’ daily life. Since 2014, there are more mobile devices on Earth than humans. Mobile applications utilize sensors and actuators of these devices to support individuals in their daily life. In particular, 24% of the Android applications leverage users’ mobility data. For instance, this data allows applications to understand which places an individual typically visits. This allows providing her with transportation information, location-based advertisements, or to enable smart home heating systems. These and similar scenarios require the possibility to access the Internet from everywhere and at any time. To realize these scenarios 83% of the applications available in the Android Play Store require the Internet to operate properly and therefore access it from everywhere and at any time. Mobile applications such as Google Now or Apple Siri utilize human mobility data to anticipate where a user will go next or which information she is likely to access en route to her destination. However, predicting human mobility is a challenging task. Existing mobility prediction solutions are typically optimized a priori for a particular application scenario and mobility prediction task. There is no approach that allows for automatically composing a mobility prediction solution depending on the underlying prediction task and other parameters. This approach is required to allow mobile devices to support a plethora of mobile applications running on them, while each of the applications support its users by leveraging mobility predictions in a distinct application scenario. Mobile applications rely strongly on the availability of the Internet to work properly. However, mobile cellular network providers are struggling to provide necessary cellular resources. Mobile applications generate a monthly average mobile traffic volume that ranged between 1 GB in Asia and 3.7 GB in North America in 2015. The Ericsson Mobility Report Q1 2016 predicts that by the end of 2021 this mobile traffic volume will experience a 12-fold increase. The consequences are higher costs for both providers and consumers and a reduced quality of service due to congested mobile cellular networks. Several countermeasures can be applied to cope with these problems. For instance, mobile applications apply caching strategies to prefetch application content by predicting which applications will be used next. However, existing solutions suffer from two major shortcomings. They either (1) do not incorporate traffic volume information into their prefetching decisions and thus generate a substantial amount of cellular traffic or (2) require a modification of mobile application code. In this thesis, we present novel human mobility and application usage prediction algorithms for mobile devices. These two major contributions address the aforementioned problems of (1) selecting a human mobility prediction model and (2) prefetching of mobile application content to reduce cellular traffic. First, we address the selection of human mobility prediction models. We report on an extensive analysis of the influence of temporal, spatial, and phone context data on the performance of mobility prediction algorithms. Building upon our analysis results, we present (1) SELECTOR – a novel algorithm for selecting individual human mobility prediction models and (2) MAJOR – an ensemble learning approach for human mobility prediction. Furthermore, we introduce population mobility models and demonstrate their practical applicability. In particular, we analyze techniques that focus on detection of wrong human mobility predictions. Among these techniques, an ensemble learning algorithm, called LOTUS, is designed and evaluated. Second, we present EBC – a novel algorithm for prefetching mobile application content. EBC’s goal is to reduce cellular traffic consumption to improve application content freshness. With respect to existing solutions, EBC presents novel techniques (1) to incorporate different strategies for prefetching mobile applications depending on the available network type and (2) to incorporate application traffic volume predictions into the prefetching decisions. EBC also achieves a reduction in application launch time to the cost of a negligible increase in energy consumption. Developing human mobility and application usage prediction algorithms requires access to human mobility and application usage data. To this end, we leverage in this thesis three publicly available data set. Furthermore, we address the shortcomings of these data sets, namely, (1) the lack of ground-truth mobility data and (2) the lack of human mobility data at short-term events like conferences. We contribute with JK2013 and UbiComp Data Collection Campaign (UbiDCC) two human mobility data sets that address these shortcomings. We also develop and make publicly available a mobile application called LOCATOR, which was used to collect our data sets. In summary, the contributions of this thesis provide a step further towards supporting mobile applications and their users. With SELECTOR, we contribute an algorithm that allows optimizing the quality of human mobility predictions by appropriately selecting parameters. To reduce the cellular traffic footprint of mobile applications, we contribute with EBC a novel approach for prefetching of mobile application content by leveraging application usage predictions. Furthermore, we provide insights about how and to what extent wrong and uncertain human mobility predictions can be detected. Lastly, with our mobile application LOCATOR and two human mobility data sets, we contribute practical tools for researchers in the human mobility prediction domain.

Mobile devices such as smartphones and smart watches are ubiquitous companions of humans’ daily life. Since 2014, there are more mobile devices on Earth than humans. Mobile applications utilize sensors and actuators of these devices to support individuals in their daily life. In particular, 24% of the Android applications leverage users’ mobility data. For instance, this data allows applications to understand which places an individual typically visits. This allows providing her with transportation information, location-based advertisements, or to enable smart home heating systems. These and similar scenarios require the possibility to access the Internet from everywhere and at any time. To realize these scenarios 83% of the applications available in the Android Play Store require the Internet to operate properly and therefore access it from everywhere and at any time. Mobile applications such as Google Now or Apple Siri utilize human mobility data to anticipate where a user will go next or which information she is likely to access en route to her destination. However, predicting human mobility is a challenging task. Existing mobility prediction solutions are typically optimized a priori for a particular application scenario and mobility prediction task. There is no approach that allows for automatically composing a mobility prediction solution depending on the underlying prediction task and other parameters. This approach is required to allow mobile devices to support a plethora of mobile applications running on them, while each of the applications support its users by leveraging mobility predictions in a distinct application scenario. Mobile applications rely strongly on the availability of the Internet to work properly. However, mobile cellular network providers are struggling to provide necessary cellular resources. Mobile applications generate a monthly average mobile traffic volume that ranged between 1 GB in Asia and 3.7 GB in North America in 2015. The Ericsson Mobility Report Q1 2016 predicts that by the end of 2021 this mobile traffic volume will experience a 12-fold increase. The consequences are higher costs for both providers and consumers and a reduced quality of service due to congested mobile cellular networks. Several countermeasures can be applied to cope with these problems. For instance, mobile applications apply caching strategies to prefetch application content by predicting which applications will be used next. However, existing solutions suffer from two major shortcomings. They either (1) do not incorporate traffic volume information into their prefetching decisions and thus generate a substantial amount of cellular traffic or (2) require a modification of mobile application code. In this thesis, we present novel human mobility and application usage prediction algorithms for mobile devices. These two major contributions address the aforementioned problems of (1) selecting a human mobility prediction model and (2) prefetching of mobile application content to reduce cellular traffic. First, we address the selection of human mobility prediction models. We report on an extensive analysis of the influence of temporal, spatial, and phone context data on the performance of mobility prediction algorithms. Building upon our analysis results, we present (1) SELECTOR – a novel algorithm for selecting individual human mobility prediction models and (2) MAJOR – an ensemble learning approach for human mobility prediction. Furthermore, we introduce population mobility models and demonstrate their practical applicability. In particular, we analyze techniques that focus on detection of wrong human mobility predictions. Among these techniques, an ensemble learning algorithm, called LOTUS, is designed and evaluated. Second, we present EBC – a novel algorithm for prefetching mobile application content. EBC’s goal is to reduce cellular traffic consumption to improve application content freshness. With respect to existing solutions, EBC presents novel techniques (1) to incorporate different strategies for prefetching mobile applications depending on the available network type and (2) to incorporate application traffic volume predictions into the prefetching decisions. EBC also achieves a reduction in application launch time to the cost of a negligible increase in energy consumption. Developing human mobility and application usage prediction algorithms requires access to human mobility and application usage data. To this end, we leverage in this thesis three publicly available data set. Furthermore, we address the shortcomings of these data sets, namely, (1) the lack of ground-truth mobility data and (2) the lack of human mobility data at short-term events like conferences. We contribute with JK2013 and UbiComp Data Collection Campaign (UbiDCC) two human mobility data sets that address these shortcomings. We also develop and make publicly available a mobile application called LOCATOR, which was used to collect our data sets. In summary, the contributions of this thesis provide a step further towards supporting mobile applications and their users. With SELECTOR, we contribute an algorithm that allows optimizing the quality of human mobility predictions by appropriately selecting parameters. To reduce the cellular traffic footprint of mobile applications, we contribute with EBC a novel approach for prefetching of mobile application content by leveraging application usage predictions. Furthermore, we provide insights about how and to what extent wrong and uncertain human mobility predictions can be detected. Lastly, with our mobile application LOCATOR and two human mobility data sets, we contribute practical tools for researchers in the human mobility prediction domain.

Dans différents domaines de recherche, la modélisation est devenue un outil efficace pour étudier et prédire l’évolution possible d’un système, en particulier en épidémiologie. En raison de la mondialisation et de la mutation génétique de certaines maladies ou vecteurs de transmission, plusieurs épidémies sont apparues dans des régions non encore concernées ces dernières années. Dans cette thèse, un modèle décrivant la transmission de l’épidémie de chikungunya à la population humaine est étudié. Ce modèle prend en compte la mobilité spatiale des humains, ce qui est nouveau. En effet, c’est un facteur intéressant qui a influencé la réapparition de plusieurs maladies épidémiques. Le déplacement des moustiques est omis puisqu’il est limité à quelques mètres. Le modèle complet (modèle EDOs-EDPs) est alors composé d’un système à réaction-diffusion (prenant la forme d’équations différentielles partielles (EDPs) paraboliques semi-linéaires) couplé à des équations différentielles ordinaires (EDOs). Nous démontrons pour ce modèle, d’abord l’existence et l’unicité de la solution globale, sa positivité et sa bornitude, puis nous donnons quelques simulations numériques. Dans ce modèle, certains paramètres ne sont pas directement accessibles à partir des expériences et doivent être estimés numériquement. Cependant, avant de rechercher leurs valeurs, il est essentiel de vérifier l’identifiabilité des paramètres pour déterminer si l’ensemble des paramètres inconnus peut être déterminé de manière unique à partir des données. Cette étude permettra de s’assurer que les procédures numériques peuvent être couronnées de succès. Si l’identifiabilité n’est pas assurée, certaines données supplémentaires doivent être ajoutées. En fait, une première étude d’identifiabilité a été effectuée pour le modèle EDOs en considérant que le nombre d’œufs peut être facilement compté. Toutefois, après avoir discuté avec les chercheurs épidémiologistes, il apparaît que c’est le nombre de larves qui peut être estimé semaines par semaines. Ainsi, nous ferons une étude d’identifiabilité pour le nouveau modèle EDOs-EDPs avec cette hypothèse. Grâce à l’intégration de l’une des équations du modèle, on obtient des équations plus faciles reliant les entrées, les sorties et les paramètres, ce qui simplifie vraiment l’étude d’identifiabilité. A partir de l’étude d’identifiabilité, une méthode et une procédure numérique sont proposés pour estimer les paramètres sans en avoir connaissance. / In different fields of research, modeling has become an effective tool for studying and predicting the possible evolution of a system, particularly in epidemiology. Due to the globalization and the genetic mutation of certain diseases or transmission vectors, several epidemics have appeared in regions not yet concerned in the last years. In this thesis, a model describing the transmission of the chikungunya epidemic to the human population is studied. As a novelty, this model incorporates the spatial mobility of humans. Indeed, it is an interesting factor that has influenced the re-emergence of several epidemic diseases. The displacement of mosquitoes is omitted since it is limited to a few meters. The complete model (ODEs-PDEs model) is then composed of a reaction-diffusion system (taken the form of semi-linear parabolic partial differential equations (PDEs)) coupled with ordinary differential equations (ODEs). We prove the existence, uniqueness, positivity and boundedness of a global solution of this model at first and then give some numerical simulations. In such a model, some parameters are not directly accessible from experiments and have to be estimated numerically. However, before searching for their values, it is essential to verify the identifiability of parameters in order to assess whether the set of unknown parameters can be uniquely determined from the data. This study will insure that numerical procedures can be successful. If the identifiability is not ensured, some supplementary data have to be added. In fact, a first identifiability study had been done for the ODEs model by considering that the number of eggs can be easily counted. However, after discussing with epidemiologist searchers, it appears that it is the number of larvae which can be estimated weeks by weeks. Thus, we will do an identifiability study for the novel ODEs-PDEs model with this assumption. Thanks to an integration of one of the model equations, some easier equations linking the inputs, outputs and parameters are obtained which really simplify the study of identifiability. From the identifiability study, a method and numerical procedure are proposed for estimating the parameters without any knowledge of them.

This thesis is a descriptive study of problem representations of climate-induced human mobility in policy. Two cases which are severely impacted by climate change have been selected for the analysis: Kiribati and Andaman and Nicobar Islands. Policies of these cases are analysed through a qualitative text analysis following the methodological approach “What’s the Problem Represented to Be?”. A particular focus is given to the issue of “planned relocations” as this is a form of human movement that is, per definition, driven by policy. The analysis found negative representations of human mobility to be present in both cases, but also positive representations in the case of Kiribati. Planned relocations were represented as something necessary and difficult by both the cases, but a substantial difference concerned the intended length of such movements. Lastly, this study highlights the need for further research on policy engagement in climate-induced human mobility.

The migration of the lesbian, gay, bisexual, trans- and queer (LGBTQ) people from Central America to or through Mexico has increased in recent years. People are leaving spaces of violence and exclusion related to their sexual and/or gender identity and search conditions for a livable life. Yet, the migration implies an exposure to different sorts of violence, wherefore this thesis explores how the vulnerability of Central American queer people is (re)produced in a situation of human mobility in Mexico. Further, the thesis examines how protection is made (im)possible for the LGBTQ community in religious shelters. The research is based on qualitative research and thirteen semi-structured interviews, carried out in Mexico in 2020, with representatives from shelters, universities and civil society organizations working with migrants and LGBTQ people.   Queer people are disproportionally exposed to vulnerability in Mexico and migrating does not necessary imply that life becomes livable. Since their lives are likely to be understood as ungrievable lives by the heteronormative society, the violence and the exposure to vulnerability of this populations becomes largely invisible. Thus, religious shelters both include and exclude LGBTQ people, depending on how they imagine boundaries.

The present paper examines possible changes in temporal urban diversity caused by the COVID-19 pandemic in Stockholm and Uppsala metropolitan areas. In addition to general changes in diversity, potential differences of diversity levels at locations with varying socioeconomic characteristics are examined. The diversity levels are calculated based on mobile phone data and defined by the inflow and distribution of individuals to locations. The time frame involves eight study dates and extends from January to April 2020. The paper reaches the following conclusions. (1) Diversity levels display a general decline during the pandemic, with one exception - Easter Holidays. (2) Individuals residing in areas with high proportions of highly educated individuals or visible minorities experience a decrease in diversity whereas the opposite is true for areas with high proportions of low-income earners or senior citizens (3) The increase in diversity in the two last mentioned areas, which are located in remote parts of the metropolitan area, coincide with decreasing levels of diversity in the central parts of the metropolitan area. It is possible that changes in diversity levels in these areas can be explained by changes in general behavioural trends, e.g. incentives to avoid crowded city center areas.

Thesis (M. A. (Social Work)) -- University of Limpopo, 2021 / Southern Africa encounters an exceptional international human mobility. Several studies view South Africa as a host country for a large number of immigrants, particularly migrant youth who come from other African countries. Upon their arrival in South Africa, studies show that migrant youth encounter a vast number of challenges such as being excluded from welfare services of South Africa. It is from this background that this study sought to explore survival strategies that migrant youth in Musina Town employ for their sustainability. This study presents qualitative findings on the survival strategies employed by migrant youth in Musina Town, Limpopo Province of South Africa. Ten migrant youth in Musina Town who are accommodated in shelters managed by churches were used as a case study and were purposively and conveniently selected to participate in the study. Data was collected through face to face semi-structured interviews and analysed thematically through the assistance of the Nvivo software. The resilience, neoclassical and network theories were used to guide the study. However, the resilience theory served as the over-arching theory of the study as it is more relevant and appropriate in explaining how migrant youth bounced back to normality after the hardships they experienced in South Africa. Findings reveal that bad economic conditions from countries of origin pushed young people to South Africa for better livelihoods. However, due to lack of funds, some crossed borders fraudulently for their survival. Upon their arrival in South Africa, findings further revealed that some migrant youth engage in criminal acts to make a living. It was also found that some migrant youth are involved in sex work to make a living. Social networking with their counterparts, street vending, cheap and exploitative labour were also found to be strategies employed by migrant youth for their sustainable livelihoods. It is thus concluded that migrant youth in South Africa are exposed to bad conditions upon their arrival in the country for their sustainable livelihoods. Findings also reveal various coping strategies that migrant youth employ to mitigate their exclusion from South African welfare services. Recommendations which include integrated intervention and future research are provided in this study