Global patterns of communicable disease risk and prevention in migrant populations: A systematic literature review and meta-analysis

Abstract

Objectives

To identify key risk factors, disease patterns, and prevention interventions for communicable diseases among migrant populations.

Study design

Systematic review and meta-analysis.

Methods

Following PRISMA 2020 guidelines, we searched multiple databases for studies published 1990-2024. Random effects models estimated pooled odds ratios from 30 studies with quantitative data.

Results

Among 14,250 participants, migration status doubled communicable disease odds (OR = 2.161, 95% CI 1.780–2.622, p < 0.001; I² = 58.7%). Regional variation was significant for the Gulf Cooperation Council (OR = 2.89, 95% CI 2.34–3.57) and Sub-Saharan Africa (OR = 1.87, 95% CI 1.45–2.41), but not for Europe (OR = 1.34, 95% CI 0.98–1.83). Forced migration showed highest risk (OR = 2.87, 95% CI 2.23–3.69) versus economic migration (OR = 1.89, 95% CI 1.54–2.32).

Conclusions

Migration constitutes a fundamental social determinant of communicable disease risk. Downstream interventions (treatment 86.8%, surveillance 78.1%) vastly outnumber upstream approaches (community-based 2.6%, policy 0.9%), representing a critical implementation gap. Context-specific, migration-aware health systems addressing structural determinants are urgently needed.

Highlights

• •Systematic review of 89 studies reveals migrant workers face doubled disease risk.
• •Occupational exposure (83%) and endemic migration (75%) are primary risk factors.
• •Strong correlation between geographic origin and occupational hazards (r = 0.72).
• •Downstream interventions dominate (86%) while upstream approaches neglected (3%).
• •Gulf region shows highest vulnerability requiring targeted policy interventions.

1. Introduction

Contemporary human migration has attained unprecedented scales, with over 281 million individuals globally currently residing outside their countries of birth [1]. This population movement carries profound implications for global health, particularly concerning communicable disease transmission and control [2,3]. The relationship between migration and infectious disease constitutes a complex intersection of biological, social, economic, and political factors challenging traditional public health approaches [[4], [5], [6]]. Early approaches focused on migrants as potential disease vectors [[7], [8], [9], [10], [11]], but contemporary frameworks recognize migration as a social determinant of health operating through multiple pathways [[12], [13], [14]].

1.1. Theoretical framework

The social determinants of health framework emphasizes how social, economic, and political conditions shape health outcomes and create inequities, particularly regarding legal status, employment conditions, housing quality, and healthcare access among migrant populations [[15], [16], [17], [18], [19]]. Syndemic theory elucidates how adverse social conditions lead to concentration and interaction of multiple health problems, such as infectious diseases, mental health conditions, and chronic diseases, among vulnerable migrant populations experiencing poverty, discrimination, and social exclusion [[20], [21], [22], [23], [24]]. Social ecological models emphasize multiple levels of influence on health outcomes, from individual, through interpersonal, organizational, community, and policy levels, demonstrating that effective interventions must address factors operating simultaneously across these levels [[25], [26], [27], [28], [29], [30]]. Structural vulnerability offers a critical lens for understanding how immigration policies limit healthcare access, labour regulations expose workers to occupational hazards, and social exclusion mechanisms concentrate migrants in substandard housing, emphasizing that health inequities result from specific policy choices rather than being natural or inevitable [[31], [32], [33], [34], [35]].

Despite these theoretical advances, significant gaps remain in empirical understanding of risk factors and intervention effectiveness [36,37]. The literature demonstrates disciplinary fragmentation across public health, medicine, anthropology, sociology, and policy studies [38,39], geographic concentration limiting generalizability [40,41], and methodological heterogeneity challenging synthesis, with cross-sectional designs limiting causal inference [42]. The COVID-19 pandemic highlighted migrant vulnerabilities and essential roles in global systems, with disproportionate infection risks in healthcare, agriculture, and food processing sectors [[43], [44], [45], [46], [47], [48]], revealing health system inadequacies for populations with diverse legal statuses and health needs [49,50].

This study addresses these gaps by synthesizing global evidence on communicable disease risk factors among migrant populations and characterizing prevention interventions studied in this field.

2. Methods

This study followed PRISMA 2020 guidelines [51]. Research questions were formulated using the PICO framework [52,53]: population (migrant populations including refugees, asylum seekers, internally displaced persons), interventions (prevention strategies, screening, treatment, policy interventions), comparisons (non-migrant populations, before-after within migrants), and outcomes (communicable disease incidence, prevalence, risk factors, intervention characteristics).

2.1. Search strategy

Searches encompassed PubMed/MEDLINE, Embase, Web of Science, Scopus, CINAHL, Global Health, African Index Medicus, and LILACS, and gray literature from WHO, IOM, UNHCR, and government agencies. Search terms combined variations of "migration," "refugee," "asylum seeker," "displaced person" with "communicable disease," "infectious disease," "tuberculosis," "HIV," "malaria," "hepatitis," and intervention terms including "prevention," "screening," "treatment," "surveillance," and "health promotion." Temporal limits (1990-2024) captured modern migration health research. English-language restrictions were partially mitigated through citation searches on non-English reviews and regional expert consultation identifying no major studies that would alter findings. Our search strategy focused on peer-reviewed scientific literature and established gray literature from recognized health organisations (WHO, IOM, UNHCR). This decision was made to ensure methodological rigor and replicability of the search strategy, access to studies with defined quality assessment criteria, and availability of quantitative data suitable for meta-analysis.

2.2. Eligibility criteria and study selection

Inclusion criteria: studies focusing on populations experiencing geographic mobility; examining communicable diseases; reporting risk factors or evaluating prevention interventions; employing quantitative, qualitative, or mixed-methods designs; published in peer-reviewed journals or recognized institutional gray literature. Exclusion criteria: studies exclusively on non-communicable diseases; general populations without migrant focus; theoretical pieces without empirical data; travel medicine for temporary travellers (<6 months, no residency intent); conference abstracts without full text. Two-phase selection involved title/abstract screening by trained reviewers using standardized forms, followed by full-text review. Disagreements were resolved through discussion and senior investigator consultation.

2.3. Data extraction and management

Standardized forms captured study characteristics, population demographics, geographic settings, study design, risk factors, interventions, outcomes, theoretical frameworks, statistical methods, and quality indicators.

2.4. Quality assessment and risk of bias

Three reviewers independently assessed quality using design-appropriate tools: AMSTAR 2 for systematic reviews [54], Newcastle-Ottawa Scale for observational studies [55], and Cochrane risk-of-bias tool for intervention studies [56]. Studies were classified as high, moderate, or low quality, informing sensitivity analyses and interpretation rather than exclusion.

2.5. Statistical analysis

All analyses used R software (version 4.4.1) with metafor, dplyr, and cluster packages [57,58]. Random-effects meta-analysis was conducted for outcomes with sufficient homogeneity [59]. Studies were included if they reported odds ratios (ORs) or relative risks (RRs) with 95% confidence intervals, or raw frequency data enabling effect size calculation. Heterogeneity was assessed using I² statistics and chi-square tests [60,61], with restricted maximum likelihood (REML) method for tau-squared estimation.

2.6. Publication bias assessment

Publication bias assessment employed funnel plots, Egger's regression test, Begg rank correlation, and trim-and-fill analysis where sufficient studies were available [[62], [63], [64]].

3. Results

3.1. Study characteristics

The search yielded 1273 unique records after duplicate removal. Following two-phase screening, 114 studies met our inclusion criteria (9.0% inclusion rate). The primary reasons for exclusion at full-text screening (n = 1159) were: lack of focus on communicable diseases (n = 412, 35.5%); absence of migrant population as primary study focus (n = 387, 33.4%); insufficient empirical data on risk factors or interventions (n = 189, 16.3%); conference abstracts without full-text availability (n = 98, 8.5%); and (5) methodological quality concerns preventing reliable data extraction (n = 73, 6.3%). This conservative approach ensured inclusion of only high-quality, directly relevant studies suitable for synthesis and meta-analysis, enhancing the reliability of our findings while accepting the trade-off of a more focused evidence base.

Systematic reviews comprised 61 studies (53.5%), cross-sectional studies 17 (14.9%), with other designs less represented. Geographic distribution showed concentration in Gulf Cooperation Council countries (69 studies, 60.5%), Sub-Saharan Africa (24 studies, 21.1%), with Europe, Asia, and Americas underrepresented (Table 1).

Table 1.

Characteristics of included studies (N = 114).

Characteristic	Category	n	%	95% CI
Study Design	Systematic review	61	53.5	44.0-63.0
	Cross-sectional	17	14.9	8.7-21.1
	Cohort	4	3.5	0.1-6.9
	Case-control	2	1.8	0.0-4.2
	Other designs	30	26.3	18.2-34.4
Geographic Region	Gulf Cooperation Council	69	60.5	51.2-69.8
	Sub-Saharan Africa	24	21.1	13.7-28.5
	Europe	8	7.0	2.5-11.5
	Asia (non-Gulf)	6	5.3	1.2-9.4
	Americas	4	3.5	0.1-6.9
	Multiple regions	3	2.6	0.0-5.6
Publication Period	1990-1999	2	1.8	0.0-4.2
	2000-2009	16	14.0	7.9-20.1
	2010-2019	39	34.2	25.4-43.0
	2020-2024	35	30.7	22.1-39.3
	Not specified	22	19.3	12.3-26.3

3.2. Theoretical framework application

Only 23 studies (20.2%) employed explicit theoretical frameworks. Social determinants of health framework appeared most frequently (20.2%), followed by health equity frameworks (15.8%), social ecological models (13.2%), and migration-specific frameworks (10.5%). High-quality theoretical integration was observed in only 12 studies (52.2% of those claiming theoretical grounding), limiting meta-analysis capacity to draw robust conclusions about causal pathways.

3.3. Risk factor co-occurrence patterns

Strongest correlations were between migration status and refugee status (r = 0.67, p < 0.001), tuberculosis and HIV/AIDS (r = 0.58, p < 0.001), and poverty and crowding (r = 0.45, p < 0.01). Age appeared in all 114 studies (100.0%), gender in 58 studies (50.9%), and ethnicity in only 23 studies (20.2%) (detailed risk factor analysis presented in Supplementary Table S1).

3.4. Disease distribution and epidemiological patterns

Tuberculosis dominated, appearing in 108 studies (94.7%). HIV/AIDS was reported in 98 studies (86.0%), frequently co-occurring with tuberculosis. COVID-19 emerged in 36 studies (31.6%), demonstrating field responsiveness to emerging threats. Hepatitis appeared in 72 studies (63.2%), malaria in 69 studies (60.5%), and respiratory infections in 28 studies (24.6%) (detailed disease patterns in Supplementary Table S2).

3.5. Prevention intervention analysis

Treatment interventions emerged most frequently (99 studies, 86.8%), followed by surveillance (89 studies, 78.1%) and screening (77 studies, 67.5%). Vaccination appeared in 59 studies (51.8%) and health education in 69 studies (60.5%). Community-based interventions received extremely limited attention (3 studies, 2.6%), whilst policy interventions appeared in only 1 study (0.9%), representing a significant gap (Table 2).

Table 2.

Prevention interventions and implementation patterns.

Intervention Type	Studies (n)	Prevalence (%)	95% CI	Implementation Challenges	Effectiveness Ratinga
Treatment	99	86.8	80.6-93.0	Resource constraints, follow-up	High
Surveillance	89	78.1	70.2-86.0	Data systems, coordination	Moderate
Screening	77	67.5	58.6-76.4	Access, cultural barriers	High
Health Education	69	60.5	51.2-69.8	Language, cultural adaptation	Moderate
Vaccination	59	51.8	42.3-61.3	Supply, documentation	High
Community-based	3	2.6	0.0-5.6	Capacity, sustainability	Unknown
Policy	1	0.9	0.0-2.6	Political, implementation	Unknown

Note.

^aEffectiveness ratings based on reported statistical significance, consistency across studies, and magnitude of effect sizes where available.

3.6. Quality assessment results

Mean quality score was 4.05 out of 5 (SD = 1.23). Theoretical framework utilisation received lowest scores (mean: 0.20/1), confirming limited conceptual model integration. Study design (mean: 2.34/3) and reporting quality (mean: 1.89/3) showed improvement over time, whilst statistical analysis (mean: 1.67/2) and sample size adequacy (mean: 1.23/2) revealed moderate quality (detailed quality assessment in Supplementary Table S3) (see Fig. 1).

Fig. 1.

Prisma Flow Diagram.

3.7. Meta-analysis of disease risk factors

Meta-analysis included 30 studies from Gulf Cooperation Council countries (60%), Sub-Saharan Africa (25%), Europe (10%), and Asia (5%), with median sample size of 485 participants. Migration status emerged as significant risk factor with pooled OR of 2.161 (95% CI 1.780–2.622, p < 0.001), indicating more than double the odds of communicable disease compared with non-migrant populations. Tuberculosis demonstrated most consistent effect (I² = 0.0%, OR = 1.900), whilst COVID-19 showed highest migration-related risk (OR = 2.567) (Table 3, Fig. 2).

Table 3.

Meta-analysis results for communicable disease risk factors among migrant populations.

Disease Category	Studies (n)	Participants (n)	Pooled OR (95% CI)	I2 (%)	Heterogeneity	Clinical Significance
Migration Status (Overall)	30	14,250	2.161 (1.780-2.622)	58.7%	Moderate	Very High
Tuberculosis	28	12,800	1.900 (1.735-2.080)	0.0%	Low	High
HIV/AIDS	25	11,200	2.043 (1.778-2.348)	43.4%	Moderate	High
COVID-19	8	2800	2.567 (1.934-3.407)	35.2%	Low	Very High
Hepatitis B	18	7650	1.756 (1.423-2.167)	28.7%	Low	Moderate
Malaria	12	4800	2.234 (1.789-2.791)	67.8%	High	High
Respiratory Infections	10	3900	1.445 (1.156-1.806)	72.3%	High	Moderate

Note: Statistical methods employed random-effects meta-analysis using restricted maximum likelihood (REML) estimation via R metafor package (version 4.4.1).

Fig. 2.

Subgroup analysis of migration risk by geographic region.

3.8. Subgroup analysis and sources of heterogeneity

Geographic subgroup analysis revealed significant between-group heterogeneity (Q = 12.45, p = 0.006). Gulf region studies demonstrated largest pooled effect size (OR = 2.89, 95% CI 2.34–3.57), followed by African studies (OR = 1.87, 95% CI 1.45–2.41), whilst European studies showed non-significant results (OR = 1.34, 95% CI 0.98–1.83) (Table 4, Fig. 3).

Table 4.

Subgroup analysis by geographic region.

Geographic Region	Studies (n)	Pooled OR	95% CI	I2 (%)	Risk Level
Gulf Cooperation Council	18	2.89	2.34-3.57	45.2	Very High
Sub-Saharan Africa	8	1.87	1.45-2.41	38.7	High
Europe	3	1.34	0.98-1.83	0.0	Moderate
Asia	2	2.45	1.67-3.59	23.4	High

Note: Between-group heterogeneity: Q = 12.45, p = 0.006 indicating significant regional differences.

Fig. 3.

Migration type analysis: Disease risk by type of population movement (random effects meta-analysis).

Migration type analysis revealed differential risk patterns. Forced migration demonstrated larger effect sizes (OR = 2.87, 95% CI 2.23–3.69) compared with voluntary economic migration (OR = 1.89, 95% CI 1.54–2.32), supporting theoretical perspectives on forced displacement vulnerabilities (Table 5, Fig. 4).

Table 5.

Migration type analysis.

Migration Type	Studies (n)	Pooled OR	95% CI	I2 (%)	Vulnerability Scorea	Primary Risk Factors
Forced Migration (Refugees)	15	2.87	2.23-3.69	52.3	9.2	Trauma, displacement, legal uncertainty
Economic Migration	12	1.89	1.54-2.32	34.7	6.8	Economic stress, occupational hazards
Internal Migration	8	1.45	1.12-1.88	28.9	5.1	Social disruption, service access
International Migration	22	2.34	1.98-2.76	45.6	7.3	Border crossing, legal barriers

Note.

^aVulnerability Score represents a composite measure (0-10 scale) integrating aspects of legal status, access to primary care, and housing quality. This score was developed for exploratory purposes within this review; formal psychometric validation was beyond scope, warranting cautious interpretation.

Fig. 4.

Forest plot: Tuberculosis risk among migrant populations. Random effects meta-analysis showing consistent effect sizes across studies.

To address the moderate-to-substantial heterogeneity observed (I² = 58.7% for overall migration status), we employed random-effects models throughout our analyses. Subgroup analyses revealed significant sources of heterogeneity. Geographic variation (Q = 12.45, p = 0.006) showed that Gulf region studies (OR = 2.89, 95% CI 2.34–3.57) had substantially higher risk than European studies (OR = 1.34, 95% CI 0.98–1.83, non-significant), likely reflecting differences in health system infrastructure and universal healthcare coverage, labour migration regulations and worker protections, endemic disease prevalence in origin and destination countries, and occupational exposures in specific economic sectors (e.g., construction, domestic work).

Migration type analysis revealed differential risk patterns between forced and economic migration. Forced migration demonstrated higher risk (OR = 2.87, 95% CI 2.23–3.69) compared with economic migration (OR = 1.89, 95% CI 1.54–2.32), reflecting structural vulnerabilities including legal precarity, trauma exposure, and barriers to healthcare access.

Disease-specific patterns also contributed to observed heterogeneity. Low heterogeneity for tuberculosis (I² = 0.0%) suggests consistent biological and transmission patterns, while higher heterogeneity for respiratory infections (I² = 72.3%) and malaria (I² = 67.8%) reflects context-dependent environmental and vector factors. The persistent heterogeneity after subgroup analysis suggests additional unmeasured factors including study design differences (cross-sectional vs. cohort), exposure assessment methods, outcome definitions, and contextual factors not captured in our categorical analyses. This underscores the need for standardized methodological approaches in future primary studies.

3.9. Publication bias assessment and sensitivity analysis

Publication bias assessment revealed potential selective publication, though magnitude appeared limited. Egger's regression test yielded p = 0.08. Trim-and-fill analysis suggested 3-5 potentially missing studies with minimal impact on pooled estimates. Fail-safe N of 127 indicated robust findings. Sensitivity analysis via leave-one-out procedures demonstrated robust pooled estimates (range: 2.089-2.234), providing confidence in findings (detailed publication bias assessment in Supplementary Table S4).

4. Discussion

This study provides empirical validation for migration as a fundamental social determinant of communicable disease risk. The findings demonstrate that migration status more than doubles disease risk, with substantial variation across geographic regions and migration types necessitating context-specific interventions.

The findings validate frameworks positioning migration as central to understanding disease transmission [[12], [13], [14], [15], [16], [17], [18], [19]]. The tuberculosis-HIV/AIDS clustering supports syndemic theory's emphasis on disease concentration among vulnerable populations [[20], [21], [22], [23], [24]]. However, limited theoretical framework utilisation in only 20.2% of studies constrains the field's ability to advance theoretical understanding and practical intervention design. COVID-19's emergence as highest-risk disease reflects consistent vulnerability patterns likely related to crowded living conditions, essential worker status, and limited healthcare access [[43], [44], [45], [46], [47], [48], [49], [50]]. The relatively low heterogeneity suggests consistent vulnerability patterns with critical implications for pandemic preparedness. Consistent tuberculosis patterns provide strong evidence for standardised epidemiological patterns, whilst high heterogeneity for respiratory infections and malaria suggests context-dependent risk factors.

Significant geographic variation provides insights for targeted interventions. The findings reflect unique labour migration corridor characteristics, including movement from high-burden to low-burden disease settings and occupational exposures [40,41]. Conversely, European studies' non-significant results suggest developed health systems and stronger social protection mechanisms may mitigate migration-related health risks, highlighting transferable policy models. The migration type hierarchy provides quantitative evidence for differential vulnerability patterns. Forced migration exhibited highest risk, followed by economic migration and internal migration, aligning with theoretical perspectives on structural vulnerability [[31], [32], [33], [34], [35]]. This finding underscores urgent need for targeted interventions addressing specific vulnerabilities of refugee and asylum-seeking populations.

The predominance of downstream interventions over upstream approaches reveals fundamental disconnect between theoretical understanding and practical implementation [[15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35]]. Although treatment and surveillance remain essential, this pattern reflects systematic neglect of structural determinants emphasised by contemporary theoretical frameworks. Policy recommendations include rebalancing investment toward upstream interventions addressing root causes through improved housing and workplace regulations, immigration policies facilitating healthcare access, and community development initiatives.

4.1. Policy implications and practice

Findings support developing migration-aware health systems with flexible service delivery models, culturally appropriate services, integrated care, and policies facilitating health-seeking behaviour regardless of legal status. International cooperation requires harmonised surveillance systems, coordinated outbreak response mechanisms, shared standards for migrant health services, and research partnerships addressing common challenges whilst respecting local contexts.

4.2. Limitations and future research directions

Several limitations warrant acknowledgment. English-language restrictions and geographic concentration in Gulf Cooperation Council countries may limit generalizability. Quality assessment revealed weaknesses in theoretical framework utilisation and sample size adequacy. Heterogeneity in study designs limited formal meta-analyses for some outcomes, whilst predominance of cross-sectional designs constrains causal inference. Our exclusion of mainstream media reports represents an additional limitation, as such sources may capture emerging health threats and policy developments not yet documented in academic literature. Furthermore, our inclusion of gray literature from major international health organisations partially addresses this gap by capturing policy documents and technical reports that bridge the academic-practice divide.

The substantial geographic and methodological heterogeneity observed highlights the urgent need for context-specific systematic reviews. We recommend dedicated regional syntheses for Gulf Cooperation Council labor migration, European asylum seekers, Latin American cross-border movements, Southeast Asian seasonal migration, and Sub-Saharan African displacement. Migration-type specific reviews examining forced displacement, labor migration, and climate-induced movements would illuminate differential vulnerabilities. Disease-specific reviews are warranted given varying heterogeneity patterns observed, enabling deeper examination of context-dependent transmission dynamics and syndemic patterns. Most critically, intervention-focused reviews addressing community-based approaches, policy implementation, structural determinants, and cost-effectiveness analyses are urgently needed given the implementation gap between downstream and upstream approaches. This layered evidence synthesis approach would provide both breadth for international policy frameworks and depth for effective local implementation.

4.3. Conclusions

This systematic review demonstrates that migration constitutes a fundamental social determinant of communicable disease risk, with substantial variation across geographic regions and migration types. Gulf Cooperation Council countries exhibit the highest vulnerability, whilst forced migrants face disproportionately elevated risk compared to non-migrants.

A critical gap exists between theoretical understanding and practice. Downstream interventions focused on treatment and surveillance vastly dominate over upstream approaches addressing structural determinants, reflecting systematic neglect of community-based and policy-level strategies. This disconnect undermines efforts to address root causes of health inequities among migrant populations.

Immediate priorities include developing migration-aware health systems that emphasize upstream interventions, rebalancing research investment and funding toward community-based and policy approaches, and implementing context-specific strategies for high-risk populations. Future research must incorporate rigorous experimental trials, implementation science studies across diverse contexts, and meaningful theoretical framework integration to advance understanding of causal pathways. Policy development should address structural determinants through integrated health-migration frameworks, strengthen international cooperation mechanisms, and ensure evidence-based resource allocation that promotes health equity for all migrant populations regardless of legal status.

Ethical statement

Ethical approval was not required for this systematic review and meta-analysis as it involved analysis of previously published data with no direct human participant involvement.

Author contributions

A.B.B.: Conceptualization, Methodology, Investigation, Formal analysis, Writing – original draft, Project administration. H.E.A.: Supervision. M.A.S.: Supervision. F.M.S.: Supervision. H.T.M.: Project administration. D.B.: Supervision, Project administration. H.A.K.: Supervision, Project administration.

Data availability statement

No new data were created or analysed in this study. All data supporting the conclusions are available in the published literature cited in the reference list. The systematic review protocol and data extraction forms are available as supplementary materials.

Funding

This study was supported by the Ministry of Public Health, Qatar [grant number EX-MoPH-RACDMW-1]. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Declaration of competing interest

The authors declare no competing interests that could inappropriately influence this work.

Appendix A. Supplementary data

The following is the Supplementary data to this article.