Cross-border Population Movements Research Articles

A new methodology for probabilistic flood displacement risk assessment: the case of Fiji and Vanuatu

This paper presents an enhanced probabilistic flood displacement risk assessment methodology. Several techniques have been proposed to estimate the number of people at risk of being displaced triggered due to climatic extremes. Among these methods, the probabilistic approach is promising for its quantitative nature and versatility at different scales. However, it has so far been limited to assessing loss of housing as the sole cause of displacement. The proposed methodology addresses this limitation by considering two additional elements beyond the traditional evaluation of housing loss: the likelihood of losing means of livelihood, directly included in the computation, and the likelihood of losing access to essential services, such as schools and health centers, provided as a factor to increase the propensity to displace. This new methodology is applied to assess flood disaster displacement risk in Fiji and Vanuatu, where climate change, coupled with the vulnerability of exposed assets, poses an existential threat to these Pacific islands, potentially leading to internal and cross-border population movements. Different climate scenarios were considered: current climate conditions (1979–2016 period), medium-term projected climate conditions (2016–2060), and long-term projected climate conditions (2061–2100). The average annual displacement increases in Fiji and Vanuatu by a factor of 3 and 4, respectively, in the projected long-term pessimistic climate scenario compared to current conditions. Depending on the country and climate change scenario, 20 to 40% of these displacements stem from loss of livelihoods as a dominant factor, highlighting the importance of considering this aspect in the vulnerability approach. The outcomes of these scenarios serve as the foundation for implementing displacement risk adaptation and management measures. This novel quantitative methodology holds significant potential for applications in larger domains and even globally.

Securitization of Cross-border Population Movements

This paper examines three examples of the securitization of cross-border population movements within a few selected countries of South and South East Asia. These cases include: a) the forced movement of the Rohingya population form Myanmar to Bangladesh; b) the movement of the Bengali population from Bangladesh and West Bengal to the Assam State of India; and c) the labour migration between India and Bangladesh. It employs Barry Buzan’s ‘Non- Traditional Security’ and ‘Securitisation’ framework. It first identifies why these destination countries have securitized migration, then locates the process through which states, as well as political parties, student groups, and several other sections of the civil society of the destination countries, have securitized migration through different types of ‘speech acts.’ The paper demonstrates that securitization failed to resolve the challenges thrown up by the forced and voluntary population movements between these countries. Rather, it severely compromised the human security of those men, women and children who were forced to move or voluntarily engage in labour migration.

Spatial patterns and climate drivers of malaria in three border areas of Brazil, Venezuela and Guyana, 2016–2018

In 2020, 77% of malaria cases in the Americas were concentrated in Venezuela, Brazil, and Colombia. These countries are characterized by a heterogeneous malaria landscape and malaria hotspots. Furthermore, the political unrest in Venezuela has led to significant cross-border population movement. Hence, the aim of this study was to describe spatial patterns and identify significant climatic drivers of malaria transmission along the Venezuela-Brazil-Guyana border, focusing on Bolivar state, Venezuela and Roraima state, Brazil. Malaria case data, stratified by species from 2016 to 2018, were obtained from the Brazilian Malaria Epidemiology Surveillance Information System, the Guyana Vector Borne Diseases Program, the Venezuelan Ministry of Health, and civil society organizations. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. A Poisson regression model was developed with a conditional autoregressive prior structure and posterior parameters were estimated using the Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. There were 685,498 malaria cases during the study period. Plasmodium vivax was the predominant species (71.7%, 490,861). Malaria hotspots were located in eight municipalities along the Venezuela and Guyana international borders with Brazil. Plasmodium falciparum increased by 2.6% (95% credible interval [CrI] 2.1%, 2.8%) for one meter increase in altitude, decreased by 1.6% (95% CrI 1.5%, 2.3%) and 0.9% (95% CrI 0.7%, 2.4%) per 1 cm increase in 6-month lagged precipitation and each 1 °C increase of minimum temperature without lag. Each 1 °C increase of 1-month lagged maximum temperature increased P. falciparum by 0.6% (95% CrI 0.4%, 1.9%). P. vivax cases increased by 1.5% (95% CrI 1.3%, 1.6%) for one meter increase in altitude and decreased by 1.1% (95% CrI 1.0%, 1.2%) and 7.3% (95% CrI 6.7%, 9.7%) for each 1 cm increase of precipitation lagged at 6-months and 1 °C increase in minimum temperature lagged at 6-months. Each 1°C increase of two-month lagged maximum temperature increased P. vivax by 1.5% (95% CrI 0.6%, 7.1%). There was no significant residual spatial clustering after accounting for climatic covariates. Malaria hotspots were located along the Venezuela and Guyana international border with Roraima state, Brazil. In addition to population movement, climatic variables were important drivers of malaria transmission in these areas.

Migration and Hybrid Political Regimes: Navigating the Legal Landscape in Russia

In recent years, migration, foreign, and domestic policies to regulate movement and international relations have become embedded fields of study. Myron Weiner examined state-to-state relations depending on actions or inactions vis-a-vis international migration and concluded that the internationalization of migration highlighted “new and conflicting interests into considerations of policies affecting migration in both sending and receiving countries.” Stephen Castles, Mark J. Miller, and Ammendola Giuseppe wrote about “globalization of migration,” which is “the tendency” of getting the countries’ foreign and national politics “crucially affected by migratory movements.” Some scholars tried to theorize the relationship between migration, foreign, and domestic policies. Kelly Greenhill investigated widely deployed but largely unrecognized instruments of state influence on “cross-border population movements that are deliberately created or manipulated in order to induce political, military and/or economic concessions from a target state or states.” Andrew Geddes determined that migration is shaped not only by states’ foreign policy interests but also by changes in states’ domestic politics.

Why Physical Barriers Backfire: How Immigration Enforcement Deters Return and Increases Asylum Applications

What, if any, effect do physical barriers have on cross-border population movements? The foundational claim that barriers reduce migration flows remains unsupported. We conceptualize barriers as a tool of immigration enforcement, which we contend is one form of state repression. State repression could reduce mobilization (reduce immigration), have no effect on mobilization (barriers as symbolic political tools), or increase mobilization (backfire). We evaluate the relationship between barriers and cross-border population movements using a global directed dyad-year dataset for the 1990–2016 time period of all contiguous dyads and nearby non-contiguous dyads. Using instrumental variables, we find that physical barriers actually increase refugee flows, consistent with the “backfire effect” identified in research on United States immigration enforcement policies on its Mexican border. Furthermore, we find that state repression (immigration enforcement) creates this “backfire effect” via a “sunk costs” problem that reduces movements of people and increases movement of status from migrant to refugee.

Population Movement Patterns Among the Democratic Republic of the Congo, Rwanda, and Uganda During an Outbreak of Ebola Virus Disease: Results from Community Engagement in Two Districts - Uganda, March 2019.

Tailoring communicable disease preparedness and response strategies to unique population movement patterns between an outbreak area and neighboring countries can help limit the international spread of disease. Global recognition of the value of addressing community connectivity in preparedness and response, through field work and visualizing the identified movement patterns, is reflected in the World Health Organization's declaration on July 17, 2019, that the 10th Ebola virus disease (Ebola) outbreak in the Democratic Republic of the Congo (DRC) was a Public Health Emergency of International Concern (1). In March 2019, the Infectious Diseases Institute (IDI), Uganda, in collaboration with the Ministry of Health (MOH) Uganda and CDC, had previously identified areas at increased risk for Ebola importation by facilitating community engagement with participatory mapping to characterize cross-border population connectivity patterns. Multisectoral participants identified 31 locations and associated movement pathways with high levels of connectivity to the Ebola outbreak areas. They described a major shift in the movement pattern between Goma (DRC) and Kisoro (Uganda), mainly through Rwanda, when Rwanda closed the Cyanika ground crossing with Uganda. This closure led some travelers to use a potentially less secure route within DRC. District and national leadership used these results to bolster preparedness at identified points of entry and health care facilities and prioritized locations at high risk further into Uganda, especially markets and transportation hubs, for enhanced preparedness. Strategies to forecast, identify, and rapidly respond to the international spread of disease require adapting to complex, dynamic, multisectoral cross-border population movement, which can be influenced by border control and public health measures of neighboring countries.

Case Definitions Used During the First 6 Months of the 10th Ebola Virus Disease Outbreak in the Democratic Republic of the Congo - Four Neighboring Countries, August 2018-February 2019.

On August 1, 2018, the Democratic Republic of the Congo (DRC) declared its 10th Ebola virus disease (Ebola) outbreak in an area with a high volume of cross-border population movement to and from neighboring countries. The World Health Organization (WHO) designated Rwanda, South Sudan, and Uganda as the highest priority countries for Ebola preparedness because of the high risk for cross-border spread from DRC (1). Countries might base their disease case definitions on global standards; however, historical context and perceived risk often affect why countries modify and adapt definitions over time, moving toward or away from regional harmonization. Discordance in case definitions among countries might reduce the effectiveness of cross-border initiatives during outbreaks with high risk for regional spread. CDC worked with the ministries of health (MOHs) in DRC, Rwanda, South Sudan, and Uganda to collect MOH-approved Ebola case definitions used during the first 6 months of the outbreak to assess concordance (i.e., commonality in category case definitions) among countries. Changes in MOH-approved Ebola case definitions were analyzed, referencing the WHO standard case definition, and concordance among the four countries for Ebola case categories (i.e., community alert, suspected, probable, confirmed, and case contact) was assessed at three dates (2). The number of country-level revisions ranged from two to four, with all countries revising Ebola definitions by February 2019 after a December 2018 peak in incidence in DRC. Case definition complexity increased over time; all countries included more criteria per category than the WHO standard definition did, except for the "case contact" and "confirmed" categories. Low case definition concordance and lack of awareness of regional differences by national-level health officials could reduce effectiveness of cross-border communication and collaboration. Working toward regional harmonization or considering systematic approaches to addressing country-level differences might increase efficiency in cross-border information sharing.

Türkiye Cumhuriyeti’ne Yönelen Kitlesel Göç Hareketleri ve Kabul Mekanizmasındaki Yaklaşımlara İlişkin Bir İnceleme: 1989 Bulgaristan, 1991 Irak ve 2011 Suriye Göçleri

<p class="ql-align-justify">The Republic of Turkey has faced intense migration movements in accordance with the historical continuity of the Anatolian geography since its foundation process. Some of the mentioned migration movements took place within the framework of the mass movements following&nbsp;political developments in neighboring countries. The mass cross-border population movements have been of particular importance in the three recent migrations, with their intensities and the way they are met. The 1989 Bulgarian migration, the 1991 Iraqi migration and the Syrian migration after 2011 have been comparable, having similarities&nbsp;and differences in this context. The study focused on the development processes of related migration movements and the similarities and differences in the accepted policies of the Turkish public against these migration movements, theoretical approaches and the historical depth of the Turkish migration law.&nbsp;

Risk assessment of malaria transmission at the border area of China and Myanmar

BackgroundIn order to achieve the goal of malaria elimination, the Chinese government launched the National Malaria Elimination Programme in 2010. However, as a result of increasing cross-border population movements, the risk of imported malaria cases still exists at the border areas of China, resulting in a potential threat of local transmission. The focus of this paper is to assess the Plasmodium vivax incidences in Tengchong, Yunnan Province, at the border areas of China and Myanmar.MethodsTime series of P. vivax incidences in Tengchong from 2006 to 2010 are collected from the web-based China Information System for Disease Control and Prevention, which are further separated into time series of imported and local cases. First, the seasonal and trend decomposition are performed on time series of imported cases using Loess method. Then, the impact of climatic factors on the local transmission of P. vivax is assessed using both linear regression models (LRM) and generalized additive models (GAM). Specifically, the notion of vectorial capacity (VCAP) is used to estimate the transmission potential of P. vivax at different locations, which is calculated based on temperature and rainfall collected from China Meteorological Administration.ResultsComparing with Ruili County, the seasonal pattern of imported cases in Tengchong is different: Tengchong has only one peak, while Ruili has two peaks during each year. This may be due to the different cross-border behaviors of peoples in two locations. The vectorial capacity together with the imported cases and the average humidity, can well explain the local incidences of P. vivax through both LRM and GAM methods. Moreover, the maximum daily temperature is verified to be more suitable to calculate VCAP than the minimal and average temperature in Tengchong County.ConclusionTo achieve malaria elimination in China, the assessment results in this paper will provide further guidance in active surveillance and control of malaria at the border areas of China and Myanmar.

Risk assessment of malaria in land border regions of China in the context of malaria elimination.

BackgroundCross-border malaria transmission poses a challenge for countries to achieve and maintain malaria elimination. Because of a dramatic increase of cross-border population movement between China and 14 neighbouring countries, the malaria epidemic risk in China’s land border regions needs to be understood.MethodsIn this study, individual case-based epidemiological data on malaria in the 136 counties of China with international land borders, from 2011 to 2014, were extracted from the National Infectious Disease Information System. The Plasmodium species, seasonality, spatiotemporal distribution and changing features of imported and indigenous cases were analysed using descriptive spatial and temporal methods.ResultsA total of 1948 malaria cases were reported, with 1406 (72.2%) imported cases and 542 (27.8%) indigenous cases. Plasmodium vivax is the predominant species, with 1536 malaria cases occurrence (78.9%), following by Plasmodium falciparum (361 cases, 18.5%), and the others (51 cases, 2.6%). The magnitude and geographic distribution of malaria in land border counties shrunk sharply during the elimination period. Imported malaria cases were with a peak of 546 cases in 2011, decreasing yearly in the following years. The number of counties with imported cases decreased from 28 counties in 2011 to 26 counties in 2014. Indigenous malaria cases presented a markedly decreasing trend, with 319 indigenous cases in 2011 reducing to only 33 indigenous cases in 2014. The number of counties with indigenous cases reduced from 26 counties in 2011 to 10 counties in 2014. However, several bordering counties of Yunnan province adjacent to Myanmar reported indigenous malaria cases in the four consecutive years from 2011 to 2014.ConclusionsThe scale and extent of malaria occurrence in the international land border counties of China decreased dramatically during the elimination period. However, several high-risk counties, especially along the China–Myanmar border, still face a persistent risk of malaria introduction and transmission. The study emphasizes the importance and urgency of cross-border cooperation between neighbouring countries to jointly face malaria threats to elimination goals.

Accuracy and completeness of patient pathways--the benefits of national data linkage in Australia.

BackgroundThe technical challenges associated with national data linkage, and the extent of cross-border population movements, are explored as part of a pioneering research project. The project involved linking state-based hospital admission records and death registrations across Australia for a national study of hospital related deaths.MethodsThe project linked over 44 million morbidity and mortality records from four Australian states between 1st July 1999 and 31st December 2009 using probabilistic methods. The accuracy of the linkage was measured through a comparison with jurisdictional keys sourced from individual states. The extent of cross-border population movement between these states was also assessed.ResultsData matching identified almost twelve million individuals across the four Australian states. The percentage of individuals from one state with records found in another ranged from 3-5 %. Using jurisdictional keys to measure linkage quality, results indicate a high matching efficiency (F measure 97 to 99 %), with linkage processing taking only a matter of days.ConclusionsThe results demonstrate the feasibility and accuracy of undertaking cross jurisdictional linkage for national research. The benefits are substantial, particularly in relation to capturing the full complement of records in patient pathways as a result of cross-border population movements.The project identified a sizeable ‘mobile’ population with hospital records in more than one state. Research studies that focus on a single jurisdiction will under-enumerate the extent of hospital usage by individuals in the population. It is important that researchers understand and are aware of the impact of this missing hospital activity on their studies.The project highlights the need for an efficient and accurate data linkage system to support national research across Australia.

Healthy migration: A public health and development imperative for south(ern) Africa

South Africa (SA), like the rest of the Southern African Development Community, has a high prevalence of communicable diseases, an increasing non-communicable disease burden, and diverse internal and cross-border population movements. Healthy migration is good for development, but current prevention, testing and treatment responses within public health systems - particularly for chronic conditions - fail to engage with migration. Understanding of migration is poor within sectors responsible for developing appropriate responses; negative, unsupported assumptions relating to the prevalence of cross-border migration, the spread of disease, and the burden on receiving health systems prevail. In SA, public health responses fail to address internal and cross-border mobilities, and non-nationals face challenges in accessing healthcare. Of particular concern is the lack of nationally and regionally co-ordinated strategies to ensure treatment continuity for chronic conditions. Co-ordinated, evidence-informed responses to migration, mobility and health are urgently needed. These will have developmental and public health benefits for all.

The Dynamics of European Integration

Part 1 Economic and technical dynamics: regional integration in a networked world economy, Albert Bressand and Kalypso Nicolaidis technology and the dynamics of integration, Margaret Sharp changing patterns of monetary interdependence, Elke Thiel. Part 2 Centre and periphery: patterns of production and trade, Per Magnus Wijkman the European community and its sub-systems, Philippe de Schoutheete Nordic cooperation, Carl-Einar Stalvant the central European dimension, Richard Davy the Mediterranean dimension, Roberto Aliboni. Part 3 Social dynamics: cross-border population movements, Federico Romero cultural linkages, Bruno de Witte. Part 4 Legal and institutional patterns: making multilateral negotiations work, Helen Wallace administrative interaction, Wolfgang Wessels the legal dimension, Renaud Dehousse and Joseph H.H.Weiler the changing security framework, Reinhardt Rummel and Peter Schmidt conclusions - community politics and institutional change, Robert O.Keohane and Stanley Hoffmann.