This evidence portal is a repository of research publications and high-yield evidence briefs on COVID-19 and its intersection with migration health.
The scientific literature and knowledge base on the epidemic rapidly expand daily. Tremendous efforts are being made by the global community of clinicians, researchers and journal editors to advance scientific evidence to guide policy and decision making at the field level. However, there is a need to build evidence platforms to share and distill key findings emergent from this growing body of scientific literature that is relevant to migration, health, and human mobility to ultimately assist evidence-informed decision making from a migration lens.
The portal contains:
- An interactive, open-source, searchable (and downloadable) repository of research publications on COVID-19 in relation to migrants, migration, and human mobilitybased on the quantitative analysis of the thematic trends and impact of relevant publications.
- The full paper of the quantitative analysis of publications on COVID-19 and migration health (i.e., bibliometric analysis).
- High-yield evidence briefs that align with the COVID-19 Global Preparedness and Response Plan and with IOM’s Global Strategic Preparedness and Response Plan (SRP).
- Profiling migration health and COVID-19 related analysis, research, and commentaries in partnership with the Migration Health and Development Research Initiative (MHADRI), a global network of migration health research experts/scholars.
Research Publications on COVID-19 and Migration Health
This section reflects the output of the publication mapping exercise involving the quantitative assessment of a set of published scientific articles (i.e., bibliometric analysis) on COVID-19 with reference to migrants, migration, and human mobility. Bibliometric analysis provides an important snapshot of a specific field of interest/domain. The baseline information from bibliometric analysis helps identify research gaps that future studies can investigate. The bibliometric analysis conducted by IOM and MHADRI on international migration and health is one example.
- As of 30 March 2020, the publications related to COVID-19 totaled 21,779 (no restriction set in terms of language and subject area). From this, a total of 43 publications were relevant to migration health and human mobility.
- Most of the studies investigated the cases and disease transmission dynamics of COVID-19 in the context of national and international population movement, with most studies undertaken in China. The distribution of research to date indicates the role of travel and migration in the importation of the virus.
- Research on the epidemiology of the disease among migrant groups such as migrant workers, internally displaced persons (IDPs), refugees and asylum seekers is lacking. Evidence with attribution to migrant groups within clinical datasets are seldom reported.
- Despite multiple studies from high-income countries (HICs) using mathematical modelling to predict spread, and model social distancing, border closures and impacts on health care system capacities, there were only a few studies that model outbreak in low-to-middle-income countries (LMICs) contexts. None hitherto have focused on camps and camp-like situations.
- There is a real need to strengthen the current knowledge base on the epidemiology and social determinants of COVID-19 and examine health-related outcomes in specific migrant groups, especially migrant workers.
- Investigations on COVID-19 and migration health should not be limited to the role of movement/mobility in the dynamic importation of cases in a pandemic; a more inclusive research strategy that integrates the relevant interests of migrant populations should be considered.
- Advocating for the right to health of migrants and migrant inclusion within the global, regional, national and sub-national pandemic preparedness and response plans is of critical importance.
- The most productive authors and institutions come from Hong Kong, whose geographical proximity to and socio-economic ties with China were likely contributing factors in their early contributions to the field.
Network map of common keywords
The network map below shows an overview of the common keywords that appear in the title, abstract, and keywords of the relevant publications retrieved on the topic of COVID-19 and migration health. Network maps of keywords reveal key topics in a research area or domain as well as the relationship (co-occurrence) between common keywords. It is a relative indicator of important research areas that are drawing attention in the field.
- The large circles in the figure represent the most frequently occurring author keywords in the research publications (N=43) such as ‘pneumonia’ (n=26), ‘epidemic’ (n=22), ‘travel’ (n=19), ‘quarantine’ (n=18), ‘outbreak’ (n=15), and ‘disease transmission’ (n=14).
- The lines connecting the circles represent the co-occurring keywords. The distance between two keywords approximates how strongly the words are related based on the number of their co-occurrences (i.e., the more publications in which two keywords co-occur, the stronger the relation between them). Thus, the strongly related words appear closer together on the map.
- Each distinct color represents a cluster of keywords that are strongly related to each other. In the figure, ‘pneumonia’, ‘travel’, and ‘disease transmission’ are strongly related to ‘virology’, ‘animals’, ‘nonhuman’, ‘zoonosis’, ‘fever’, ‘genetics’, and ‘pandemic’ (red cluster). The keyword ‘epidemic’ is strongly related to ‘outbreak’, ‘quarantine’, ‘mass screening’, ‘air travel’, ‘travel medicine’, ‘global health’, ‘infection control’, and ‘risk assessment’ – these keywords are shown to be closer together forming the green cluster.
- These topics on COVID-19 and migration health can be classified into the following thematic areas: disease epidemiology (i.e., travel, disease transmission, virology, animals, nonhuman, zoonosis, genetics, pandemic); clinical management (i.e., pneumonia and fever); and public health intervention (i.e., quarantine, control, etc.).
Note: See the full paper for the Methodology and Limitations of this analysis.