Infectious Diseases Among Migrant Populations
Bibliographic record
Abstract
Abstract Increasing human mobility, of which migration is a component, is a key driver of microorganism circulation. Migration is a minor component of all human mobility, with most movement due to international tourism, travel for work, business, or study, and military operations abroad. Migration flows from southern low-income countries to the industrialized north have steadily increased as a consequences of a complex array of distal and proximal factors such as economic inequality, climate change, political turbulence, war and persecution, and family reunification. This has raised concerns about the potential transmission and reintroduction of microorganisms and infectious diseases into high-income host countries from migrants with asymptomatic infections such as tuberculosis, HIV, viral hepatitis, malaria, Chagas disease, and arboviral infections. These factors contribute to the mounting hostile attitude sometimes observed in receiving countries and deserve careful scientific assessment to inform policies and interventions. The available evidence does not support the hypothesis that migrants constitute a relevant infectious public health risk for the local population, although careful epidemiological surveillance is mandatory, especially where competent vectors for specific infection are present in the destination area, where certain diseases may potentially be introduced or reintroduced. The greatest risk of infectious diseases is to the migrants themselves due to increased risk of exposure within their own communities and from the burden of undetected and untreated infections caused by marginalization and poor living conditions. The health conditions vary at the different stages of settlement and interventions need to be tailored accordingly. In the early arrival phase the main health concerns are psychological, traumatic, and chronic conditions. Crowded unhygienic living conditions often experienced by migrants in reception camps coupled with low vaccination rate may facilitate the transmission of respiratory or gastrointestinal infections or vaccine-preventable diseases. After resettlement, undetected infections and the lack of access to health care due to social marginalization may lead to the reactivation or progression of infections such as tuberculosis, viral hepatitis, HIV, and chronic helminthiasis. These outcomes could be prevented through screening and treatment and would benefit both migrants and the host populations. Pretravel interventions that increase the awareness of the possible infectious risks in their countries of origin are critical to decrease travel-related infection among visiting friends and relatives, especially those traveling with children. Migrant-friendly health systems that ensure prompt access to diagnosis and treatment, regardless of legal status, are the best interventions to limit the burden and transmission of infections in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".