Differences found in patient profiles and incidence trends between migrants and native-born Tuberculosis patients in Ireland; 2011-2021

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While Ireland is a low TB incidence country, with crude incidence rates (CIRs) in the Irish-born below 6 per 100,000 population since 2011, CIRs in the foreign-born population are up to 13 times higher. This study aims to inform TB prevention and care by analysing the differences in the epidemiology of TB in native-born and foreign-born populations in Ireland. Methods: A cross-sectional analysis of all TB notifications reported to the Irish TB Surveillance System from 2011–2021 was performed. Temporal trends in CIRs were analysed using Negative-binomial regression. Independent variables selected with a p value of < 0.25 in univariable analysis were investigated in a multivariable logistic regression model comparing TB patient characteristics between migrants and Irish-born. Results: Of the 3,364 TB patients, 48% were among migrants. Compared to Irish-born, migrants with TB were younger, had higher odds of living with HIV, extra-pulmonary disease, infection with drug-resistant strains and residence in congregate residential settings with lower odds linkage to outbreaks. Recently arrived migrants with TB had higher proportions of international protection applicants and refugees, pulmonary disease and people living with HIV. Between 2011–2021, a significantly declining temporal trend was present for migrants, Irish-born and total TB patients. Between 2017 and 2021, a significantly declining temporal trend was still present in Irish-born and total patients, but the trend was no longer significant among migrants with TB. Discussion/Conclusion: A heightened awareness of extrapulmonary TB within health systems is needed given the high levels observed among migrants with TB. The pace of TB decline among migrants is slower than among Irish-born and has plateaued in the final years of this study period, making TB elimination targets more difficult to achieve. Differences in the epidemiology of TB reported by this study can be used to inform and enhance future TB service provision and promote migrant health. tuberculosis epidemiology incidence public health emigration and immigration Figures Figure 1 Figure 2 Introduction Tuberculosis (TB) remains a global public health threat that was responsible for 1.3 million deaths in 2022 alone, with 7,000 of those considered excess deaths due to health service disruption association with the Covid-10 emergency response [ 1 ]. Ireland has experienced a steady decline in TB since the 1950s when crude incidence rates (CIRs) were over 220 per 100,000 population, to a CIR of < 5 per 100,000 during 2023, becoming a low TB incidence country in 2010 [ 2 ]. While CIRs in the Irish-born remain below six per 100,000 population since 2011, CIRs in the foreign-born population have been up to 13 times higher [ 2 ]. Migrants are a very diverse population group and consequently their TB risk is influenced by many factors. Background risk of infection in the country of origin is a key component, however the process of migration itself can alter the risk of acquiring new infection or developing TB disease. While migrant populations often comprise individuals who are young, financially stable and healthy enough to travel, sub-populations who are forced to travel via hazardous land and sea migration routes are at increased risk, due to the overcrowding, food insecurity and stressful conditions that can occur [ 3 – 5 ]. After arrival in the destination country the risk of TB may be further influenced by migrant demography and health status, along with structural and social determinants such as presence of screening programmes, health system accessibility and socioeconomic profile [ 6 – 8 ]. International migration is increasing globally with the European region experiencing some of the steepest increases in recent years, from 50 million in 1990 to 87 million in 2020 [ 9 ]. Similarly, Ireland has also experienced a steady increase in the proportion of the population that was born abroad, from 10% in 2002 to 20% in 2022[ 10 , 11 ]. Given these increasing global migration trends, stimulated by rising environmental and political instability, migrants remain a key population for TB prevention and care activities. For this reason, an enhanced understanding of the epidemiologic patterns among native-born and foreign-born TB patients is required. This study aims to inform future TB prevention and care activities by analysing the differences in the epidemiology of TB in native-born and foreign-born populations within the Irish context, and by providing an in-depth analysis of patient profiles of migrants with TB. Methods 1.1. Study population We utilised a retrospective cohort study design to perform a cross-sectional secondary data analysis of all active TB notifications reported to the Irish National TB Surveillance System and notified to the Computerised Infectious Disease Reporting (CIDR) system between 2011 and 2021.[ 8 ] 1.2. Definitions The European Union Commission TB surveillance case definition for active TB was used [ 12 ]. Migrants with TB were defined as patients who were born outside Ireland but notified with TB in Ireland. Resistance to aTB drugs was defined as resistance to one or more of the following drugs: isoniazid, rifampicin, ethambutol, pyrazinamide, streptomycin, any second-line injectable (e.g amikacin, kanamycin) or any fluoroquinolone (e.g levofloxacin, moxifloxacin). Multi-drug resistance (MDR) was defined as resistance to both isoniazid and rifampicin and extremely drug-resistant (XDR) TB was defined using the pre-2021 World Health Organization (WHO) definition of resistance to rifampicin and any fluoroquinolone and a second line injectable. 1.3. Data analysis Chi squared test for trend in proportions, Kruskal Wallis or Wilcoxon Rank Sum Tests were used to test associations between independent variables and categorical outcomes. Crude incidence rates (CIRs) and age specific incidence rates (ASIRs) per 100,000 population were calculated using 2016 census population denominators stratified by country of birth and age. Temporal trends in CIRs were analysed using Negative-binomial regression and incidence rate ratios (IRRs). Temporal trends were assessed for total patients, migrant patients and Irish-born patients for both the full study period (2011–2021) and the latter half (2017–2021). Independent variables selected based on clinical relevance and literature review with a p value of ≤ 0.25 in univariable analysis were investigated in a multivariable logistic regression model comparing patient characteristics of migrants with TB compared to Irish-born with TB. We assessed the potential effect of excluding patients with missing data from the model by comparing the distribution of each of the 11 selected independent variables by the dependent variable within the complete cases sample, and within the total sample. The distributions were broadly similar between the two samples. Independent variables were assessed for co-linearity using Variable Inflation Factor (VIF) analysis and removed if the VIF was > 9.0. Variables with the highest Wald p-value and lowest Likelihood Ratio (LR) test statistic were removed one at a time through backwards stepwise elimination until all variables had a Wald p-value of < 0.05. Model fit was assessed using Hosmer and Lemeshow’s test and models were compared using the Akiki Information Criterion Weights (AICw). The mean TB incidence estimate per 100,000 population for each migrant birth country for the study period was calculated using the annual incidence estimates published by the WHO [ 13 ]. Birth countries were then classified as one of the following incidence categories: low = 0.0-9.9, medium = 10.0-39.9, high = 40.0-99.9 and very high ≥ 100. Time between arrival in Ireland and notification as a TB patient was estimated by subtracting arrival year from notification year, and categorised as follows: <2 years, 2–4 years, 5–9 years and ≥ 10 years. Data were analysed using MS Excel, Stata 14 and R software [ 14 , 15 ]. 1.4. Protection of human subjects: Ethical approval was received from the research ethics committee in the School of Nursing and Midwifery, Trinity College Dublin. Informed consent was not sought from the patients in this study as the legal basis for processing surveillance data in Ireland is not consent but based on GDPR Articles 6(1)(c) and 6(1)(e); Articles 9(2)(i) and 9(2)(j) and the Infectious Disease Regulations [ 16 , 17 ]. Furthermore, as this was a secondary data analysis of anonymized data there was no requirement for informed consent under the Health Research Regulations Act 2018 [ 18 ]. All data processing was compliant with the General Data Protection Regulations. Results Epidemiology of TB among migrant patients compared to Irish-born: Of the 3,364 TB patients notified between 2011 and 2021, 48% (n = 1,605) were among migrants, 47% (n = 1,593) were among Irish-born and 5% (n = 166) did not have country of birth reported. Overall, 5% (n = 153) of total patients were reported as being an International Protection Applicant or Refugee (IPARs). Table 1 summarises the overall distribution of patient characteristics alongside results of univariable and multivariable logistic regression analysis results for predictors of TB among migrants compared to TB among Irish-born. Age and sex Median ages were significantly younger among migrant with TB compared to Irish-born, and among IPARs compared to non-IPAR migrants (31 versus 34 years respectively). Cumulative age specific incidence rates were higher among migrants with TB in all age groups (Figure S1 ). Male to female ratio was 1.3 among migrants with TB and 1.7 among Irish-born. Clinical features : Lower proportions of pulmonary TB (PTB) were observed among migrants with TB (57.9%) compared to Irish-born (77.6%). Compared to Irish-born, migrants with TB also had higher odds of having normal chest X-ray (CXR) result (OR: 3.13, CI: 2.45–4.02) and computerised tomography (CT) thorax scan results (OR: 3.62, CI: 1.92–7.26). A significantly shorter median interval between onset and diagnosis was observed among migrants with TB (63 days, range: 0–3,294) compared to Irish-born (75 days, range: 0–2,111) (p = 0.001) (Figure S2). Drug resistance Drug susceptibility testing (DST) data was available for 73.8% (n = 2,360) of total patients. Infection with a drug-resistant strain was reported in in 17.3% of migrants with TB and 7.3% of Irish-born. Forty patients with MDR-TB were migrants (90.9%) and all three patients with XDR-TB were migrants. Of the 47 patients with M/XDR-TB, 79.5% (n = 35) had PTB. Infection with non-MDR poly resistant strains was reported in 40 patients (0.2%) from 17 countries of origin, seven (17.5%) of these were among Irish-born. Multivariable logistic regression analysis results : After backwards stepwise elimination, seven independent variables remained as significant predictors of TB among migrants in the final model (Table 1 ). Compared to Irish-born, migrants with TB were younger with a higher adjusted odds of living with HIV (OR: 3.8, CI: 1.99 to 7.73), extrapulmonary disease (OR: 3.14, CI: 2.09 to 4.79), infection with drug-resistant strains (OR: 2.30, CI: 1.37 to 4.01), residence in the Midlands area of Ireland (OR: 3.26, CI: 1.24 to 9.69). Migrants with TB had a lower odds of being associated with an outbreak (OR: 0.16, CI:0.09 to 0.28). All metrics of the model assumptions were acceptable with 83% of binned residuals within error bounds. Variable Inflation Factor (VIF) analysis indicated that levels of co-linearity were low. Hosmer Lemeshow’s test found no evidence of poor model fit (statistic: 9.5, p = 0.304). Temporal trends : Between 2011 and 2021, a significantly declining temporal trend was present in the annual crude incidence rates (CIRs) per 100,000 population for all three patient cohorts analysed; migrants with TB, Irish-born TB and total TB patients. Between 2011–2021, annual CIRs declined from 9.0 to 4.4 for total patients (IRR: 0.95; CI: 0.94–0.96), from 25.2 to 15.2 among migrants with TB (IRR: 0.96; CI: 0.95–0.98) and from 5.6 to 1.2 among Irish-born (IRR: 0.89; CI: 0.86–0.92). Between 2017 and 2021, a significantly declining temporal trend was still present in Irish-born (IRR: 0.76; CI: 0.69–0.83) and total patients (IRR: 0.91; CI: 0.88–0.95), but the trend was no longer significant among migrants with TB (IRR: 0.96; CI: 0.91–1.01) (Fig. 1 ). Epidemiology of migrants with TB: Migrants with TB originated from 98 countries. The majority of migrants with TB (68.5%) originated from countries classified as very high TB incidence (CIR ≥ 100 / 100,000 population) according to the mean WHO incidence estimate for the study period. Annual CIRs by TB incidence category are illustrated in Figure S3. Patient characteristics of migrants with TB differed according to the incidence level in the origin-country (Table S1 ). Migrants with TB originating from very high incidence countries had the highest proportions of people living with HIV (PLWH) and with previous TB screening in Ireland, and the lowest proportions with PTB and being linked to an outbreak. A significant trend in the proportion of international protection applicants and refugees (IPARs) was observed in relation to the increasing incidence category. The top ten birth-countries of migrants with TB differed when ranked by patient numbers versus by the mean annual CIR in Ireland, with the exception of India, Pakistan and Somalia which were ranked by both metrics. Birth-countries with the highest number of migrants with TB comprised six very high TB incidence countries, two high incidence and two medium incidence countries. Birth-countries with the highest TB CIRs in this study were all classified as very high TB incidence countries according to the mean WHO CIR estimates. Table 2 displays the mean CIR and the percentage of migrants with TB originating from each of the birth-countries for the study period in either top ten category. CIRs for migrants with TB from Eritrea, Botswana, Malawi and Somalia were higher in Ireland than the mean CIR estimates reported by WHO in these countries (Fig. 2 ). The proportion of IPARs was higher among patients from birth-countries with the highest CIRs (9.8%) compared to the remaining countries (5.1%), with highest proportions of IPARs found in migrants from Eritrea (75.0%), Somalia (27.7%), Uganda (12.5%) and Malawi (12.0%). Interval between arrival and notification Year of arrival in Ireland was reported for 66.7% of migrants with TB. The median interval between arrival in Ireland and notification with TB was 5 years (mean = 7 years) and ranged from 0–59 years with years of arrival spanning from 1954 to 2021. The median interval was shorter between 2019–2021 (3 years). Migrants with TB who were diagnosed < 2 years after arrival were significantly younger and had higher proportions of IPARs, PLWH and PTB. The proportions of migrants with TB from very high incidence countries decreased in line with length of stay in Ireland (72–65%). Table 3 summarises the patient characteristics of migrants with TB according to the interval between their arrival in Ireland and notification with TB. Discussion This study reveals key clinical and epidemiological differences in the patient profile of migrants with TB compared to Irish-born, and within the migrant subgroups studied. Compared to Irish-born, migrants with TB were younger, with higher odds of living with HIV, extra-pulmonary disease (EPTB), infection with a drug-resistant strain and residence in a congregate setting; with lower odds of being linked to an outbreak. While a highly diverse range of origin-countries was observed in this study, the majority of migrants with TB (69%) originated from very high TB incidence countries. This contrasts with the Irish population denominator where 14% of migrants originated from high TB incidence countries [ 19 ]. Similar to studies in Europe and the United States [ 20 – 22 ], EPTB was more common among migrants with three times higher adjusted odds of EPTB compared to Irish-born. Accordingly, migrants with TB were almost twice as likely to have a normal CT thorax scan result and a normal chest X-ray result. Currently there is no systematic TB screening programme in Ireland, but thoracic TB symptom screening is offered mainly to international protection applicants (IPAs) and new entrant health-care professionals from high TB incidence countries [ 23 ]. Results from this study suggest that such screening could miss up to 40% of migrants with TB and may need to be supplemented by targeting high-risk migrant groups for TB infection screening to support TB elimination in Ireland [ 24 ]. This finding supports the development of a new-entrant immigrant TBI management programme as one of the key actions in Ireland’s Tuberculosis Strategy [ 25 ]. Proportions of EPTB increased in tandem with incidence in the origin-country and similar to European studies, were highest among patients originating from South-Asia [ 20 , 26 ]. In keeping with the lower levels of PTB, migrants with TB had lower odds of being associated with an outbreak, which is supported by findings in the literature that migrants with TB tend to contribute less to transmission [ 27 – 29 ]. This study found migrants with TB had almost four times higher adjusted odds of living with HIV than Irish-born, higher than reported by a large-scale European study which found the proportions of PLWH among migrants with TB were twice as high compared to native-born TB [ 22 ]. Birth-countries with the highest proportions of PLWH in this study were mainly from Sub-Saharan Africa reflecting the co-epidemic of TB-HIV in this region [ 30 ]. Despite a strong recommendation to offer HIV testing to all TB patients [ 31 ], only 42% had their HIV status reported. Levels of completeness were further reduced for birth-countries with lower HIV prevalence, possibly reflecting lower likelihoods of clinicians offering testing to those populations. Addressing HIV-associated TB through integrated prevention and care remains a key commitment of the WHO End TB strategy [ 32 ]. Higher levels of drug-resistance were found among migrants with TB compared to Irish-born, with the level of MDR broadly similar to that previously reported among migrants with TB in Europe [ 22 ]. Most patients infected with MDR-TB strains in this study originated in Eastern Europe reflecting background levels reported in surveillance data for these origin-countries [ 33 ]. Although advances in MDR-TB treatment have been made, it remains a significant obstacle to TB elimination, particularly as 80% of patients with MDR-TB in this study had a pulmonary component, which was comparable with findings from other international studies [ 34 ]. Two key social determinants, housing type and employment status, were significant at univariable level. Migrants with TB had an increased odds of living in congregate residential settings compared to Irish-born patients, which is a key risk factor for transmission [ 7 , 35 ] Migrants with TB also had higher adjusted odds of being in paid employment compared to Irish-born patients, indicating a potential benefit from directly observed treatment (DOT) via video rather than in-person DOT to facilitate continued attendance in work-place and support treatment success [ 36 ]. As previously observed by other European studies of migrants with TB, differences were observed in the top birth-countries when analysed by CIRs rather than patient numbers, with the exception of India, Pakistan and Somalia which were ranked by both metrics [ 37 , 38 ]. Our study aligned with four of the eight most common origin-countries reported by Vasiliu et al among migrant TB patients (India, Pakistan, Romania and Somalia) and four of the top five countries reported by Domaszewska et al. Both these studies also reported CIRs that diverged from the published WHO estimates, and similar to this study, migrants from Eritrea and Somalia had higher CIRs compared to the WHO estimate while migrants from Mongolia, Nepal and Pakistan migrants had lower CIRs. In contrast to these studies, we observed CIRs that were higher than WHO estimates among migrants from Malawi and Botswana. The divergence in CIRs within birth-countries in Ireland, are likely to be influenced by many factors including type of migrant (economic versus IPARs), mode of migration (transit through hostile conditions such as migrant camps) and conditions upon entry to destination country (accessibility of health systems, screening, housing quality). Higher CIRs among Eritreans in Ireland could be influenced by the majority also being IPARs (75%) and possibly experiencing both adverse conditions and increased exposures during hazardous migration pathways, combined with an increased case-detection rate due to being offered TB screening during voluntary initial health assessments at International Protection Applicant accommodation centres [ 39 ]. Conversely, lower rates observed among migrants from India and Mongolia are likely influenced by the fact that migrants from these countries are not routinely offered screening so may have a lower case-detection rate, as well as more often being economic migrants who travel under better conditions. In keeping with this, these countries had the lowest proportion of IPARs among the birth-countries with 10 highest CIRs and employment rates of > 64% according to Census data [ 40 ]. A lower prevalence was estimated for visa applicants from India, Pakistan and Nepal in Australia and was thought to be a reflection of the type of migrant applying for residence [ 41 ]. The findings that recently arrived migrants with TB had higher proportions of IPARs, PTB and PLWH are likely influenced by the practice of offering initial health assessments, that include pulmonary TB symptom screening and HIV testing, to International Protection Applicants (IPAs) upon arrival in Ireland [ 39 ]. However, IPARs remain a small proportion of migrants in this study overall (12% of migrants with TB) and include refugees as well as IPAs. A study of migrant TB in low TB incidence European destination countries between 2014–2020 also found higher proportions of PTB among recently arrived migrants which was similarly thought to be linked to the use of chest X-ray based screening for IPARs [ 42 ]. While it is commonly accepted that the highest risk of TB among migrants occurs in the first few years after arrival in the destination country due to reactivation of remotely acquired infection in the origin-country or via new infection acquired during hazardous conditions along the migration pathway [ 3 , 6 , 43 ], other studies have found that the increased risk persists for several years after arrival and can be influenced by recurring travel to the origin-country [ 44 – 46 ]. This study found that over half of migrants with TB presented more than five years after arrival in Ireland, indicating a need to ensure continued access to TB diagnosis and care for this population. Strengths : This study utilised a programmatic data source of all patients with active TB notified in Ireland, helping to reduce selection bias in the sample. Patients were reported according to a standardised European Union (EU) case definition aiding the generalisability of results to other jurisdictions. We analysed the data for all countries of birth, rather than pre-selected based on highest numbers to provide an alternate view of TB risk among migrants via CIRs. This study is the first to characterise recent migrants with TB in Ireland and includes several key time periods; before and after the global migration peak in 2015/2016 and the early Covid-19 pandemic period, but prior to recent wars in Ukraine and Palestine which are currently influencing the epidemiology of TB through increased asylum seeking. Limitations : This study was mostly limited by issues relating to availability of denominator data and poor completeness of the numerator data. Census data may underestimate the true number of migrants resident in Ireland, particularly among undocumented migrants, causing some rates to overestimated. Conversely, undocumented migrants may be under diagnosed, possibly due to fears of accessing health services, leading to underestimation of rates presented. The 2016 Census of population was used throughout as the 2022 Census was not available for all countries of birth reported among TB patients. It is possible that population changes during the intervening period have reduced the accuracy of CIRs calculated in this study. Irish population data on recently arrived migrants are not available by country of birth so it was not possible to calculate birth-country specific CIRs for this key population. Key variables such as HIV status and social risk factors had low levels of completeness which may have introduced bias within the results. Conclusions & recommendations While screening for PTB remains a key tool in reducing the infectious reservoir, a heightened awareness of EPTB within health systems is needed. Future TBI screening programmes will also need to rule out EPTB prior to offering TBI treatment. The pace of TB decline among migrants is slower than among Irish-born and has plateaued in the final years of this study period, making TB elimination targets more difficult to achieve. Elevated CIRs observed among migrant subpopulations indicate that factors in addition to incidence in the birth-country need to be considered when evaluating the risk of TB in migrants. Denominator data by country of birth for recently arrived migrants is needed to understand the dynamics of migration in Ireland and how it may be linked to the evolving epidemiology of infectious diseases such as TB. More complete data are needed for key indicators such as HIV status and year of arrival in the country. Differences in the epidemiology of TB reported by this study can be used to inform and enhance future TB service provision and promote migrant health. Declarations Ethics approval and consent to participate Ethical approval was received from the research ethics committee in the School of Nursing and Midwifery, Trinity College Dublin. Informed consent was not sought from the patients in this study as the legal basis for processing surveillance data in Ireland is not consent but based on GDPR Articles 6(1)(c) and 6(1)(e); Articles 9(2)(i) and 9(2)(j) and the Infectious Disease Regulations [16,17]. Furthermore, as this was a secondary data analysis of anonymized data there was no requirement for informed consent under the Health Research Regulations Act 2018 [18]. All data processing was compliant with the General Data Protection Regulations . Consent for publication Not applicable. Availability of data and materials The authors do not have authorisation to share the data used in this study based on the conditions of data access. The raw data used in this study are available upon reasonable request to the Health Protection Surveillance Centre, Health Service Executive. Competing interests Not applicable. Funding This study was undertaken as part of Ms Sarah Jackson’s doctoral project in Trinity College Dublin and is funded by the Health Service Executive, Ireland. The funders did not have a role in this study. Authors' contributions SJ acquired the data, conducted the analysis and wrote the original draft. All authors contributed to the conceptualisation, interpretation of results, critical review and editing of the manuscript. All authors approved the final manuscript. Acknowledgements: The authors would like to thank all the patients whose data were used in this research and the health care professionals who collected the data. 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Mangan JM, Woodruff RS, Winston CA, Nabity SA, Haddad MB, Dixon MG, et al. Recommendations for Use of Video Directly Observed Therapy During Tuberculosis Treatment — United States, 2023. MMWR Morb Mortal Wkly Rep 2023;72:313–6. https://doi.org/10.15585/mmwr.mm7212a4. Vasiliu A, Köhler N, Altpeter E, Ægisdóttir TR, Amerali M, de Oñate WA, et al. Tuberculosis incidence in foreign-born people residing in European countries in 2020. Eurosurveillance 2023;28:2300051. https://doi.org/10.2807/1560-7917.ES.2023.28.42.2300051. Domaszewska T, Koch A, Jackson S, Arrazola de Oñate W, Guthmann JP, Hauer B, et al. Tuberculosis rates in immigrants to low-incidence European countries: epidemiological differences and similarities. Eurosurveillance 2025;30. https://doi.org/10.2807/1560-7917.ES.2025.30.11.2400489. HSE Social Inclusion. Report of the Refugee and Applicants Seeking Protection Blood Borne Virus and Tuberculosis Screening Implementation Advisory Group. 2023. Central Statistics Office. Population Aged 15 Years and Over 2016 by Principal Economic Status and Birthplace 2016. Trauer JM, Williams B, Laemmle-Ruff I, Horyniak D, Caplice LVS, McBryde ES, et al. Tuberculosis in migrants to Australia: Outcomes of a national screening program. Lancet Reg Health West Pac 2021;10. https://doi.org/10.1016/j.lanwpc.2021.100135. Jackson S, Hauer B, Guthmann J-P, O´Meara M, Sizaire V, Nordstrand K, et al. Differences found in patient characteristics of migrant tuberculosis sub-populations within low TB incidence European countries, 2014-2020. Pre-Print Available at: Https://WwwResearchsquareCom/Article/Rs-6214584/V1 2025. Lonnroth K, Mor Z, Erkens C, Bruchfeld J, Nathavitharana RR, Van Der Werf MJ, et al. Tuberculosis in migrants in low-incidence countries: Epidemiology and intervention entry points. International Journal of Tuberculosis and Lung Disease 2017;21:624–36. https://doi.org/10.5588/ijtld.16.0845. Dale KD, Trauer JM, Dodd PJ, Houben RMGJ, Denholm JT. 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Tables Table 1 TB patient characteristics by migrant status and logistic regression analysis results; Ireland 2011–2021 Characteristic Missing Overall N = 3,198 Non-migrant N = 1,593 Migrant N = 1,605 Univariable Multivariable (N = 825) cOR (95% CI) p-value aOR (95% CI) p-value Median age (IQR) 4 (0.1%) 40.0 (28.0) 53.0 (33.0) 34.0 (16.0) 0.95 (0.95 to 0.96) < 0.001 0.97 (0.95 to 0.98) < 0.001 Sex 4 (0.1%) < 0.001 Female 1,276 (40%) 588 (37%) 688 (43%) — Male 1,918 (60%) 1,005 (63%) 913 (57%) 0.78 (0.67 to 0.89) Geographical area 0 (0%) < 0.001 0.037 East 1,387 (43%) 563 (35%) 824 (51%) — — Midlands 155 (4.8%) 69 (4.3%) 86 (5.4%) 0.85 (0.61 to 1.19) 3.26 (1.24 to 9.69) Midwest 196 (6.1%) 104 (6.5%) 92 (5.7%) 0.60 (0.45 to 0.82) 1.10 (0.63 to 1.92) North East 228 (7.1%) 115 (7.2%) 113 (7.0%) 0.67 (0.51 to 0.89) 1.45 (0.57 to 4.05) North West 115 (3.6%) 77 (4.8%) 38 (2.4%) 0.34 (0.22 to 0.50) 0.62 (0.27 to 1.47) South 610 (19%) 396 (25%) 214 (13%) 0.37 (0.30 to 0.45) 0.65 (0.41 to 1.03) South East 262 (8.2%) 146 (9.2%) 116 (7.2%) 0.54 (0.42 to 0.71) 0.76 (0.46 to 1.28) West 245 (7.7%) 123 (7.7%) 122 (7.6%) 0.68 (0.52 to 0.89) 1.16 (0.58 to 2.37) Employment status 371 (12%) < 0.001 0.024 Paid employment 1,041 (37%) 399 (28%) 642 (45%) — — Unemployed 929 (33%) 428 (30%) 501 (35%) 0.73 (0.61 to 0.87) 0.82 (0.56 to 1.19) Retired 443 (16%) 403 (29%) 40 (2.8%) 0.06 (0.04 to 0.09) 0.27 (0.12 to 0.60) Student/Child 329 (12%) 135 (9.6%) 194 (14%) 0.89 (0.69 to 1.15) 0.86 (0.45 to 1.70) Other 85 (3.0%) 46 (3.3%) 39 (2.8%) 0.53 (0.34 to 0.82) 0.81 (0.35 to 1.90) Current housing type 343 (11%) < 0.001 Private house 2,646 (93%) 1,352 (94%) 1,294 (92%) — Congregate residential setting 105 (3.7%) 36 (2.5%) 69 (4.9%) 2.00 (1.34 to 3.05) Homeless 27 (0.9%) 16 (1.1%) 11 (0.8%) 0.72 (0.32 to 1.54) Prison 22 (0.8%) 9 (0.6%) 13 (0.9%) 1.51 (0.65 to 3.67) Residential care facility 20 (0.7%) 18 (1.2%) 2 (0.1%) 0.12 (0.02 to 0.40) Other housing 35 (1.2%) 14 (1.0%) 21 (1.5%) 1.57 (0.80 to 3.16) Disease site 36 (1.1%) < 0.001 < 0.001 Pulmonary 2,140 (68%) 1,223 (78%) 917 (58%) — — Extrapulmonary 1,022 (32%) 353 (22%) 669 (42%) 2.53 (2.17 to 2.95) 3.14 (2.09 to 4.79) Outbreak associated 0 (0%) < 0.001 < 0.001 Not linked to outbreak 2,875 (90%) 1,345 (84%) 1,530 (95%) — — Outbreak associated 323 (10%) 248 (16%) 75 (4.7%) 0.27 (0.20 to 0.35) 0.16 (0.09 to 0.28) People living with HIV 1,804 (56%) < 0.001 < 0.001 Negative 1,266 (91%) 554 (96%) 712 (87%) — — Positive 128 (9.2%) 22 (3.8%) 106 (13%) 3.75 (2.38 to 6.16) 3.80 (1.99 to 7.73) First line drug resistance 838 (26%) < 0.001 0.001 Sensitive 2,065 (88%) 1,046 (93%) 1,019 (83%) — — Resistant 295 (13%) 82 (7.3%) 213 (17%) 2.67 (2.05 to 3.51) 2.30 (1.37 to 4.01) M/XDR-TB 838 (26%) < 0.001 No 2,315 (98%) 1,126 (100%) 1,189 (97%) — Yes 45 (1.9%) 2 (0.2%) 43 (3.5%) 20.4 (6.26 to 125) Previous TB screening in Ireland 887 (28%) < 0.001 No 1,953 (85%) 908 (80%) 1,045 (89%) — Yes 358 (15%) 224 (20%) 134 (11%) 0.52 (0.41 to 0.65) Previous TB diagnosis 801 (25%) 0.086 No 2,188 (91%) 1,089 (90%) 1,099 (92%) — Yes 209 (8.7%) 117 (9.7%) 92 (7.7%) 0.78 (0.58 to 1.04) Patient type 362 (11%) 0.004 Hospital inpatient 1,658 (58%) 876 (61%) 782 (56%) — Hospital outpatient 914 (32%) 425 (29%) 489 (35%) 1.29 (1.10 to 1.52) Other 264 (9.3%) 145 (10%) 119 (8.6%) 0.92 (0.71 to 1.19) Diabetes 1,862 (58%) > 0.99 No 1,204 (90%) 648 (90%) 556 (90%) — Yes 132 (9.9%) 71 (9.9%) 61 (9.9%) 1.00 (0.70 to 1.43) Immunosuppression 1,841 (58%) 0.033 No 1,067 (79%) 569 (76%) 498 (81%) — Yes 290 (21%) 175 (24%) 115 (19%) 0.75 (0.58 to 0.98) Substance use 1,881 (59%) < 0.001 No 945 (72%) 475 (62%) 470 (86%) — Yes 372 (28%) 297 (38%) 75 (14%) 0.26 (0.19 to 0.34) Table 2 Migrant source countries with top 10 highest percentage of patients or CIR between 2011–2021, Ireland Country of birth Mean CIR Median CIR Mean WHO estimate Ranking in Ireland WHO Mean CIR category Years with patients Total patients % of migrant with TB Eritrea 443.5 609.8 110.7 Top 10 CIR Very high 7 8 0.5 Botswana 359.7 359.7 336.3 Top 10 CIR Very high 6 11 0.7 Somalia 284.8 333.3 269.5 Top 10 CIR & number Very high 10 47 2.9 Malawi 269.6 237.2 200.0 Top 10 CIR Very high 8 25 1.6 Mongolia 166.2 261.1 428.0 Top 10 CIR Very high 6 7 0.4 Indonesia 161.4 0.0 325.7 Top 10 CIR Very high 5 6 0.4 Uganda 150.9 207.5 201.7 Top 10 CIR Very high 6 8 0.5 Nepal 147.2 124.5 261.6 Top 10 CIR Very high 8 13 0.8 India 137.4 133.5 244.1 Top 10 CIR & number Very high 11 317 19.8 Pakistan 126.9 100.8 268.1 Top 10 CIR & number Very high 11 180 11.2 Philippines 83.3 81.5 555.6 Top 10 number Very high 11 135 8.4 South Africa 73.1 61.8 858.0 Top 10 number Very high 11 65 4.0 Nigeria 36.8 30.2 219.0 Top 10 number Very high 11 67 4.2 Romania 35.2 41.8 73.8 Top 10 number High 11 111 6.9 Lithuania 12.3 12.0 48.9 Top 10 number High 11 45 2.8 Poland 4.7 4.3 17.2 Top 10 number Medium 11 59 3.7 United Kingdom 1.5 1.1 10.3 Top 10 number Medium 11 47 2.9 Table 3 Migrant TB patient characteristics by interval between arrival and notification; Ireland Characteristic N (%) Overall N = 1,071 Interval between arrival in Ireland and TB diagnosis 0–1 N = 239 2–4 N = 295 5–9 N = 239 10+ N = 298 p-value a Median age (IQR) 34.0 (15.0) 31.0 (12.0) 30.0 (11.0) 34.0 (12.0) 42.0 (16.0) < 0.001 (% missing) 0.2 0 0 0.4 0.3 Sex 0.33 Female 473 (44%) 104 (44%) 120 (41%) 116 (49%) 133 (45%) Male 596 (56%) 135 (56%) 175 (59%) 123 (51%) 163 (55%) (% missing) 0.2 0 0 0 0.7 International Protection Applicant < 0.001 No 799 (86%) 164 (77%) 223 (85%) 174 (89%) 238 (93%) Yes 127 (14%) 49 (23%) 38 (15%) 22 (11%) 18 (7.0%) (% missing) 14 11 12 18 14 WHO TB incidence category 0.016 Low 20 (1.9%) 3 (1.3%) 1 (0.3%) 6 (2.5%) 10 (3.4%) Medium 110 (10%) 15 (6.3%) 23 (7.9%) 30 (13%) 42 (14%) High 184 (17%) 49 (21%) 50 (17%) 34 (14%) 51 (17%) Very high 749 (70%) 172 (72%) 217 (75%) 169 (71%) 191 (65%) (% missing) 0.7 0 1.4 0 1.3 Previous TB screening in Ireland 0.006 No 814 (88%) 202 (94%) 226 (89%) 172 (84%) 214 (85%) Yes 113 (12%) 13 (6.0%) 29 (11%) 32 (16%) 39 (15%) (% missing) 13 10 14 15 15 Previous TB diagnosis 0.67 No 839 (93%) 192 (92%) 225 (93%) 192 (95%) 230 (92%) Yes 65 (7.2%) 16 (7.7%) 17 (7.0%) 11 (5.4%) 21 (8.4%) (% missing) 16 13 18 15 16 Disease site 0.007 Pulmonary 626 (59%) 163 (68%) 167 (57%) 129 (54%) 167 (56%) Extrapulmonary 443 (41%) 76 (32%) 127 (43%) 110 (46%) 130 (44%) (% missing) 0.2 0 0.3 0 0.3 Months between onset and diagnosis, Median (IQR) 2.0 (3.2) 1.7 (2.2) 2.1 (3.0) 2.0 (3.7) 2.6 (3.7) 0.014 (% missing) 32 33 30 33 31 Outbreak associated 0.034 Not linked to outbreak 1,026 (96%) 232 (97%) 274 (93%) 232 (97%) 288 (97%) Outbreak associated 45 (4.2%) 7 (2.9%) 21 (7.1%) 7 (2.9%) 10 (3.4%) (% missing) 0 0 0 0 0 People living with HIV 0.004 Negative 542 (89%) 103 (80%) 154 (91%) 120 (92%) 165 (90%) Positive 69 (11%) 26 (20%) 15 (8.9%) 10 (7.7%) 18 (9.8%) (% missing) 43 46 43 46 39 First line drug resistance 0.59 Sensitive 697 (81%) 158 (81%) 196 (79%) 165 (84%) 178 (81%) Resistant 160 (19%) 36 (19%) 52 (21%) 31 (16%) 41 (19%) (% missing) 20 19 16 18 27 M/XDR-TB 0.39 No 826 (96%) 187 (96%) 235 (95%) 191 (97%) 213 (97%) Yes 31 (3.6%) 7 (3.6%) 13 (5.2%) 5 (2.6%) 6 (2.7%) (% missing) 20 19 16 18 27 Employment status < 0.001 Paid employment 479 (46%) 76 (33%) 136 (47%) 115 (49%) 152 (52%) Unemployed 365 (35%) 92 (40%) 89 (31%) 81 (35%) 103 (35%) Retired 26 (2.5%) 9 (3.9%) 4 (1.4%) 2 (0.9%) 11 (3.8%) Student/Child 147 (14%) 44 (19%) 50 (17%) 32 (14%) 21 (7.2%) Other 29 (2.8%) 10 (4.3%) 10 (3.5%) 4 (1.7%) 5 (1.7%) (% missing) 2.3 3.3 2.0 2.1 2.0 Current housing type < 0.001 Private house 952 (92%) 183 (79%) 271 (93%) 218 (94%) 280 (98%) Congregate residential / care setting 60 (5.8%) 35 (15%) 15 (5.2%) 8 (3.4%) 2 (0.7%) Prison / Homeless 10 (1.0%) 2 (0.9%) 2 (0.7%) 4 (1.7%) 2 (0.7%) Other housing 16 (1.5%) 11 (4.8%) 2 (0.7%) 2 (0.9%) 1 (0.4%) (% missing) 3.1 3.3 1.7 2.9 4.4 [a] Kruskal-Wallis rank sum test; Pearson's Chi-squared test.. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6469195","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452713011,"identity":"c608f1d7-00a4-4802-ab4b-ec19a9d0fc86","order_by":0,"name":"Sarah Jackson","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACxgYGZhAtxw8kJBgMSNBiLNlGrBYgAGtJ3HAMpIUo9e2HHxv+qKhj3Hy/+eENhgIbIhzWk2aczHPmMLPZMTZjCwaDNCK0NOQwH2ZsO8BmdoyHDeiXw0Ro6X/DfPBnWx2PcRtYy38itMzIYU7gbWOWMGADazlAjJZnxsZAvxhIHEsztkgwSCasxbA/+bEkMMTq+5sPP7zx4Y8dEVoakHkJhDUwMMgTo2gUjIJRMApGOAAAKf0zHjk2+KkAAAAASUVORK5CYII=","orcid":"","institution":"The University of Dublin","correspondingAuthor":true,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Jackson","suffix":""},{"id":452713012,"identity":"05a76df7-960c-4656-95c7-bc5b880ba9d0","order_by":1,"name":"Zubair Kabir","email":"","orcid":"","institution":"University College Cork","correspondingAuthor":false,"prefix":"","firstName":"Zubair","middleName":"","lastName":"Kabir","suffix":""},{"id":452713013,"identity":"8af4fd75-6e32-4e58-a6b8-4ac9fd0911b2","order_by":2,"name":"Catherine Comiskey","email":"","orcid":"","institution":"The University of Dublin","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"","lastName":"Comiskey","suffix":""}],"badges":[],"createdAt":"2025-04-17 07:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6469195/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6469195/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82357270,"identity":"cea1523b-e6a0-45de-9939-5588c79ce724","added_by":"auto","created_at":"2025-05-09 11:21:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76575,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual number of TB patients and crude incidence rate per 100, 000 population by migrant status\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6469195/v1/ecb564500b505bc9a0640024.png"},{"id":82360132,"identity":"7295e88d-9c92-42e4-8ecd-9e895a3a9cc0","added_by":"auto","created_at":"2025-05-09 11:37:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60331,"visible":true,"origin":"","legend":"\u003cp\u003eOrigin-countries with 10 highest mean crude incidence rates compared to WHO incidence estimates, Ireland 2011-2021\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6469195/v1/f61277bdb4b2fa2beb43a0d6.png"},{"id":85801330,"identity":"86074a80-88f4-4aeb-b5e9-99821990854d","added_by":"auto","created_at":"2025-07-01 23:31:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2225177,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6469195/v1/952d77e4-ff90-4fb7-8e17-492d9fb60ab8.pdf"},{"id":82357277,"identity":"fd8456ff-d68f-4bd9-a814-e60c1ed01351","added_by":"auto","created_at":"2025-05-09 11:21:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":309588,"visible":true,"origin":"","legend":"","description":"","filename":"SupMatDifferencesmigrantsnativebornTBIreland201121.docx","url":"https://assets-eu.researchsquare.com/files/rs-6469195/v1/db84cd7f229ac6c42f57e1a8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Differences found in patient profiles and incidence trends between migrants and native-born Tuberculosis patients in Ireland; 2011-2021","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTuberculosis (TB) remains a global public health threat that was responsible for 1.3\u0026nbsp;million deaths in 2022 alone, with 7,000 of those considered excess deaths due to health service disruption association with the Covid-10 emergency response [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Ireland has experienced a steady decline in TB since the 1950s when crude incidence rates (CIRs) were over 220 per 100,000 population, to a CIR of \u0026lt; 5 per 100,000 during 2023, becoming a low TB incidence country in 2010 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While CIRs in the Irish-born remain below six per 100,000 population since 2011, CIRs in the foreign-born population have been up to 13 times higher [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMigrants are a very diverse population group and consequently their TB risk is influenced by many factors. Background risk of infection in the country of origin is a key component, however the process of migration itself can alter the risk of acquiring new infection or developing TB disease. While migrant populations often comprise individuals who are young, financially stable and healthy enough to travel, sub-populations who are forced to travel via hazardous land and sea migration routes are at increased risk, due to the overcrowding, food insecurity and stressful conditions that can occur [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. After arrival in the destination country the risk of TB may be further influenced by migrant demography and health status, along with structural and social determinants such as presence of screening programmes, health system accessibility and socioeconomic profile [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e–\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInternational migration is increasing globally with the European region experiencing some of the steepest increases in recent years, from 50\u0026nbsp;million in 1990 to 87\u0026nbsp;million in 2020 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Similarly, Ireland has also experienced a steady increase in the proportion of the population that was born abroad, from 10% in 2002 to 20% in 2022[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Given these increasing global migration trends, stimulated by rising environmental and political instability, migrants remain a key population for TB prevention and care activities. For this reason, an enhanced understanding of the epidemiologic patterns among native-born and foreign-born TB patients is required.\u003c/p\u003e \u003cp\u003eThis study aims to inform future TB prevention and care activities by analysing the differences in the epidemiology of TB in native-born and foreign-born populations within the Irish context, and by providing an in-depth analysis of patient profiles of migrants with TB.\u003c/p\u003e "},{"header":"Methods","content":"\u003ch2\u003e1.1. Study population\u003c/h2\u003e\u003cp\u003eWe utilised a retrospective cohort study design to perform a cross-sectional secondary data analysis of all active TB notifications reported to the Irish National TB Surveillance System and notified to the Computerised Infectious Disease Reporting (CIDR) system between 2011 and 2021.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e\u003ch2\u003e1.2. Definitions\u003c/h2\u003e\u003cp\u003eThe European Union Commission TB surveillance case definition for active TB was used [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Migrants with TB were defined as patients who were born outside Ireland but notified with TB in Ireland. Resistance to aTB drugs was defined as resistance to one or more of the following drugs: isoniazid, rifampicin, ethambutol, pyrazinamide, streptomycin, any second-line injectable (e.g amikacin, kanamycin) or any fluoroquinolone (e.g levofloxacin, moxifloxacin). Multi-drug resistance (MDR) was defined as resistance to both isoniazid and rifampicin and extremely drug-resistant (XDR) TB was defined using the pre-2021 World Health Organization (WHO) definition of resistance to rifampicin and any fluoroquinolone and a second line injectable.\u003c/p\u003e\u003ch2\u003e1.3. Data analysis\u003c/h2\u003e\u003cp\u003eChi squared test for trend in proportions, Kruskal Wallis or Wilcoxon Rank Sum Tests were used to test associations between independent variables and categorical outcomes. Crude incidence rates (CIRs) and age specific incidence rates (ASIRs) per 100,000 population were calculated using 2016 census population denominators stratified by country of birth and age. Temporal trends in CIRs were analysed using Negative-binomial regression and incidence rate ratios (IRRs). Temporal trends were assessed for total patients, migrant patients and Irish-born patients for both the full study period (2011–2021) and the latter half (2017–2021).\u003c/p\u003e\u003cp\u003eIndependent variables selected based on clinical relevance and literature review with a p value of ≤ 0.25 in univariable analysis were investigated in a multivariable logistic regression model comparing patient characteristics of migrants with TB compared to Irish-born with TB. We assessed the potential effect of excluding patients with missing data from the model by comparing the distribution of each of the 11 selected independent variables by the dependent variable within the complete cases sample, and within the total sample. The distributions were broadly similar between the two samples. Independent variables were assessed for co-linearity using Variable Inflation Factor (VIF) analysis and removed if the VIF was \u0026gt; 9.0. Variables with the highest Wald p-value and lowest Likelihood Ratio (LR) test statistic were removed one at a time through backwards stepwise elimination until all variables had a Wald p-value of \u0026lt; 0.05. Model fit was assessed using Hosmer and Lemeshow’s test and models were compared using the Akiki Information Criterion Weights (AICw).\u003c/p\u003e\u003cp\u003eThe mean TB incidence estimate per 100,000 population for each migrant birth country for the study period was calculated using the annual incidence estimates published by the WHO [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Birth countries were then classified as one of the following incidence categories: low = 0.0-9.9, medium = 10.0-39.9, high = 40.0-99.9 and very high ≥ 100.\u003c/p\u003e\u003cp\u003eTime between arrival in Ireland and notification as a TB patient was estimated by subtracting arrival year from notification year, and categorised as follows: \u0026lt;2 years, 2–4 years, 5–9 years and ≥ 10 years.\u003c/p\u003e\u003cp\u003eData were analysed using MS Excel, Stata 14 and R software [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003e1.4. Protection of human subjects:\u003c/h2\u003e\u003cp\u003e Ethical approval was received from the research ethics committee in the School of Nursing and Midwifery, Trinity College Dublin. Informed consent was not sought from the patients in this study as the legal basis for processing surveillance data in Ireland is not consent but based on GDPR Articles 6(1)(c) and 6(1)(e); Articles 9(2)(i) and 9(2)(j) and the Infectious Disease Regulations [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, as this was a secondary data analysis of anonymized data there was no requirement for informed consent under the Health Research Regulations Act 2018 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. All data processing was compliant with the General Data Protection Regulations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eEpidemiology of TB among migrant patients compared to Irish-born:\u003c/p\u003e\n\u003cp\u003eOf the 3,364 TB patients notified between 2011 and 2021, 48% (n\u0026thinsp;=\u0026thinsp;1,605) were among migrants, 47% (n\u0026thinsp;=\u0026thinsp;1,593) were among Irish-born and 5% (n\u0026thinsp;=\u0026thinsp;166) did not have country of birth reported. Overall, 5% (n\u0026thinsp;=\u0026thinsp;153) of total patients were reported as being an International Protection Applicant or Refugee (IPARs). Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the overall distribution of patient characteristics alongside results of univariable and multivariable logistic regression analysis results for predictors of TB among migrants compared to TB among Irish-born.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAge and sex\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMedian ages were significantly younger among migrant with TB compared to Irish-born, and among IPARs compared to non-IPAR migrants (31 versus 34 years respectively). Cumulative age specific incidence rates were higher among migrants with TB in all age groups (Figure \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). Male to female ratio was 1.3 among migrants with TB and 1.7 among Irish-born.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical features\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eLower proportions of pulmonary TB (PTB) were observed among migrants with TB (57.9%) compared to Irish-born (77.6%). Compared to Irish-born, migrants with TB also had higher odds of having normal chest X-ray (CXR) result (OR: 3.13, CI: 2.45\u0026ndash;4.02) and computerised tomography (CT) thorax scan results (OR: 3.62, CI: 1.92\u0026ndash;7.26). A significantly shorter median interval between onset and diagnosis was observed among migrants with TB (63 days, range: 0\u0026ndash;3,294) compared to Irish-born (75 days, range: 0\u0026ndash;2,111) (p\u0026thinsp;=\u0026thinsp;0.001) (Figure S2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDrug resistance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDrug susceptibility testing (DST) data was available for 73.8% (n\u0026thinsp;=\u0026thinsp;2,360) of total patients. Infection with a drug-resistant strain was reported in in 17.3% of migrants with TB and 7.3% of Irish-born. Forty patients with MDR-TB were migrants (90.9%) and all three patients with XDR-TB were migrants. Of the 47 patients with M/XDR-TB, 79.5% (n\u0026thinsp;=\u0026thinsp;35) had PTB. Infection with non-MDR poly resistant strains was reported in 40 patients (0.2%) from 17 countries of origin, seven (17.5%) of these were among Irish-born.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMultivariable logistic regression analysis results\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eAfter backwards stepwise elimination, seven independent variables remained as significant predictors of TB among migrants in the final model (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared to Irish-born, migrants with TB were younger with a higher adjusted odds of living with HIV (OR: 3.8, CI: 1.99 to 7.73), extrapulmonary disease (OR: 3.14, CI: 2.09 to 4.79), infection with drug-resistant strains (OR: 2.30, CI: 1.37 to 4.01), residence in the Midlands area of Ireland (OR: 3.26, CI: 1.24 to 9.69). Migrants with TB had a lower odds of being associated with an outbreak (OR: 0.16, CI:0.09 to 0.28).\u003c/p\u003e\n\u003cp\u003eAll metrics of the model assumptions were acceptable with 83% of binned residuals within error bounds. Variable Inflation Factor (VIF) analysis indicated that levels of co-linearity were low. Hosmer Lemeshow\u0026rsquo;s test found no evidence of poor model fit (statistic: 9.5, p\u0026thinsp;=\u0026thinsp;0.304).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTemporal trends\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eBetween 2011 and 2021, a significantly declining temporal trend was present in the annual crude incidence rates (CIRs) per 100,000 population for all three patient cohorts analysed; migrants with TB, Irish-born TB and total TB patients. Between 2011\u0026ndash;2021, annual CIRs declined from 9.0 to 4.4 for total patients (IRR: 0.95; CI: 0.94\u0026ndash;0.96), from 25.2 to 15.2 among migrants with TB (IRR: 0.96; CI: 0.95\u0026ndash;0.98) and from 5.6 to 1.2 among Irish-born (IRR: 0.89; CI: 0.86\u0026ndash;0.92). Between 2017 and 2021, a significantly declining temporal trend was still present in Irish-born (IRR: 0.76; CI: 0.69\u0026ndash;0.83) and total patients (IRR: 0.91; CI: 0.88\u0026ndash;0.95), but the trend was no longer significant among migrants with TB (IRR: 0.96; CI: 0.91\u0026ndash;1.01) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eEpidemiology of migrants with TB:\u003c/p\u003e\n\u003cp\u003eMigrants with TB originated from 98 countries. The majority of migrants with TB (68.5%) originated from countries classified as very high TB incidence (CIR\u0026thinsp;\u0026ge;\u0026thinsp;100 / 100,000 population) according to the mean WHO incidence estimate for the study period. Annual CIRs by TB incidence category are illustrated in Figure S3.\u003c/p\u003e\n\u003cp\u003ePatient characteristics of migrants with TB differed according to the incidence level in the origin-country (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). Migrants with TB originating from very high incidence countries had the highest proportions of people living with HIV (PLWH) and with previous TB screening in Ireland, and the lowest proportions with PTB and being linked to an outbreak. A significant trend in the proportion of international protection applicants and refugees (IPARs) was observed in relation to the increasing incidence category.\u003c/p\u003e\n\u003cp\u003eThe top ten birth-countries of migrants with TB differed when ranked by patient numbers versus by the mean annual CIR in Ireland, with the exception of India, Pakistan and Somalia which were ranked by both metrics. Birth-countries with the highest number of migrants with TB comprised six very high TB incidence countries, two high incidence and two medium incidence countries. Birth-countries with the highest TB CIRs in this study were all classified as very high TB incidence countries according to the mean WHO CIR estimates. Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e displays the mean CIR and the percentage of migrants with TB originating from each of the birth-countries for the study period in either top ten category. CIRs for migrants with TB from Eritrea, Botswana, Malawi and Somalia were higher in Ireland than the mean CIR estimates reported by WHO in these countries (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The proportion of IPARs was higher among patients from birth-countries with the highest CIRs (9.8%) compared to the remaining countries (5.1%), with highest proportions of IPARs found in migrants from Eritrea (75.0%), Somalia (27.7%), Uganda (12.5%) and Malawi (12.0%).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInterval between arrival and notification\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eYear of arrival in Ireland was reported for 66.7% of migrants with TB. The median interval between arrival in Ireland and notification with TB was 5 years (mean\u0026thinsp;=\u0026thinsp;7 years) and ranged from 0\u0026ndash;59 years with years of arrival spanning from 1954 to 2021. The median interval was shorter between 2019\u0026ndash;2021 (3 years). Migrants with TB who were diagnosed\u0026thinsp;\u0026lt;\u0026thinsp;2 years after arrival were significantly younger and had higher proportions of IPARs, PLWH and PTB. The proportions of migrants with TB from very high incidence countries decreased in line with length of stay in Ireland (72\u0026ndash;65%). Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e summarises the patient characteristics of migrants with TB according to the interval between their arrival in Ireland and notification with TB.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study reveals key clinical and epidemiological differences in the patient profile of migrants with TB compared to Irish-born, and within the migrant subgroups studied. Compared to Irish-born, migrants with TB were younger, with higher odds of living with HIV, extra-pulmonary disease (EPTB), infection with a drug-resistant strain and residence in a congregate setting; with lower odds of being linked to an outbreak. While a highly diverse range of origin-countries was observed in this study, the majority of migrants with TB (69%) originated from very high TB incidence countries. This contrasts with the Irish population denominator where 14% of migrants originated from high TB incidence countries [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSimilar to studies in Europe and the United States [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e–\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], EPTB was more common among migrants with three times higher adjusted odds of EPTB compared to Irish-born. Accordingly, migrants with TB were almost twice as likely to have a normal CT thorax scan result and a normal chest X-ray result. Currently there is no systematic TB screening programme in Ireland, but thoracic TB symptom screening is offered mainly to international protection applicants (IPAs) and new entrant health-care professionals from high TB incidence countries [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Results from this study suggest that such screening could miss up to 40% of migrants with TB and may need to be supplemented by targeting high-risk migrant groups for TB infection screening to support TB elimination in Ireland [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This finding supports the development of a new-entrant immigrant TBI management programme as one of the key actions in Ireland’s Tuberculosis Strategy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Proportions of EPTB increased in tandem with incidence in the origin-country and similar to European studies, were highest among patients originating from South-Asia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In keeping with the lower levels of PTB, migrants with TB had lower odds of being associated with an outbreak, which is supported by findings in the literature that migrants with TB tend to contribute less to transmission [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e–\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study found migrants with TB had almost four times higher adjusted odds of living with HIV than Irish-born, higher than reported by a large-scale European study which found the proportions of PLWH among migrants with TB were twice as high compared to native-born TB [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Birth-countries with the highest proportions of PLWH in this study were mainly from Sub-Saharan Africa reflecting the co-epidemic of TB-HIV in this region [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Despite a strong recommendation to offer HIV testing to all TB patients [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], only 42% had their HIV status reported. Levels of completeness were further reduced for birth-countries with lower HIV prevalence, possibly reflecting lower likelihoods of clinicians offering testing to those populations. Addressing HIV-associated TB through integrated prevention and care remains a key commitment of the WHO End TB strategy [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHigher levels of drug-resistance were found among migrants with TB compared to Irish-born, with the level of MDR broadly similar to that previously reported among migrants with TB in Europe [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Most patients infected with MDR-TB strains in this study originated in Eastern Europe reflecting background levels reported in surveillance data for these origin-countries [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Although advances in MDR-TB treatment have been made, it remains a significant obstacle to TB elimination, particularly as 80% of patients with MDR-TB in this study had a pulmonary component, which was comparable with findings from other international studies [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTwo key social determinants, housing type and employment status, were significant at univariable level. Migrants with TB had an increased odds of living in congregate residential settings compared to Irish-born patients, which is a key risk factor for transmission [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] Migrants with TB also had higher adjusted odds of being in paid employment compared to Irish-born patients, indicating a potential benefit from directly observed treatment (DOT) via video rather than in-person DOT to facilitate continued attendance in work-place and support treatment success [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs previously observed by other European studies of migrants with TB, differences were observed in the top birth-countries when analysed by CIRs rather than patient numbers, with the exception of India, Pakistan and Somalia which were ranked by both metrics [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our study aligned with four of the eight most common origin-countries reported by Vasiliu et al among migrant TB patients (India, Pakistan, Romania and Somalia) and four of the top five countries reported by Domaszewska et al. Both these studies also reported CIRs that diverged from the published WHO estimates, and similar to this study, migrants from Eritrea and Somalia had higher CIRs compared to the WHO estimate while migrants from Mongolia, Nepal and Pakistan migrants had lower CIRs. In contrast to these studies, we observed CIRs that were higher than WHO estimates among migrants from Malawi and Botswana. The divergence in CIRs within birth-countries in Ireland, are likely to be influenced by many factors including type of migrant (economic versus IPARs), mode of migration (transit through hostile conditions such as migrant camps) and conditions upon entry to destination country (accessibility of health systems, screening, housing quality). Higher CIRs among Eritreans in Ireland could be influenced by the majority also being IPARs (75%) and possibly experiencing both adverse conditions and increased exposures during hazardous migration pathways, combined with an increased case-detection rate due to being offered TB screening during voluntary initial health assessments at International Protection Applicant accommodation centres [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Conversely, lower rates observed among migrants from India and Mongolia are likely influenced by the fact that migrants from these countries are not routinely offered screening so may have a lower case-detection rate, as well as more often being economic migrants who travel under better conditions. In keeping with this, these countries had the lowest proportion of IPARs among the birth-countries with 10 highest CIRs and employment rates of \u0026gt; 64% according to Census data [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. A lower prevalence was estimated for visa applicants from India, Pakistan and Nepal in Australia and was thought to be a reflection of the type of migrant applying for residence [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe findings that recently arrived migrants with TB had higher proportions of IPARs, PTB and PLWH are likely influenced by the practice of offering initial health assessments, that include pulmonary TB symptom screening and HIV testing, to International Protection Applicants (IPAs) upon arrival in Ireland [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. However, IPARs remain a small proportion of migrants in this study overall (12% of migrants with TB) and include refugees as well as IPAs. A study of migrant TB in low TB incidence European destination countries between 2014–2020 also found higher proportions of PTB among recently arrived migrants which was similarly thought to be linked to the use of chest X-ray based screening for IPARs [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile it is commonly accepted that the highest risk of TB among migrants occurs in the first few years after arrival in the destination country due to reactivation of remotely acquired infection in the origin-country or via new infection acquired during hazardous conditions along the migration pathway [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], other studies have found that the increased risk persists for several years after arrival and can be influenced by recurring travel to the origin-country [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e–\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This study found that over half of migrants with TB presented more than five years after arrival in Ireland, indicating a need to ensure continued access to TB diagnosis and care for this population.\u003c/p\u003e\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStrengths\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eThis study utilised a programmatic data source of all patients with active TB notified in Ireland, helping to reduce selection bias in the sample. Patients were reported according to a standardised European Union (EU) case definition aiding the generalisability of results to other jurisdictions. We analysed the data for all countries of birth, rather than pre-selected based on highest numbers to provide an alternate view of TB risk among migrants via CIRs. This study is the first to characterise recent migrants with TB in Ireland and includes several key time periods; before and after the global migration peak in 2015/2016 and the early Covid-19 pandemic period, but prior to recent wars in Ukraine and Palestine which are currently influencing the epidemiology of TB through increased asylum seeking.\u003c/p\u003e\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLimitations\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eThis study was mostly limited by issues relating to availability of denominator data and poor completeness of the numerator data. Census data may underestimate the true number of migrants resident in Ireland, particularly among undocumented migrants, causing some rates to overestimated. Conversely, undocumented migrants may be under diagnosed, possibly due to fears of accessing health services, leading to underestimation of rates presented. The 2016 Census of population was used throughout as the 2022 Census was not available for all countries of birth reported among TB patients. It is possible that population changes during the intervening period have reduced the accuracy of CIRs calculated in this study. Irish population data on recently arrived migrants are not available by country of birth so it was not possible to calculate birth-country specific CIRs for this key population. Key variables such as HIV status and social risk factors had low levels of completeness which may have introduced bias within the results.\u003c/p\u003e"},{"header":"Conclusions \u0026 recommendations","content":"\u003cp\u003eWhile screening for PTB remains a key tool in reducing the infectious reservoir, a heightened awareness of EPTB within health systems is needed. Future TBI screening programmes will also need to rule out EPTB prior to offering TBI treatment. The pace of TB decline among migrants is slower than among Irish-born and has plateaued in the final years of this study period, making TB elimination targets more difficult to achieve. Elevated CIRs observed among migrant subpopulations indicate that factors in addition to incidence in the birth-country need to be considered when evaluating the risk of TB in migrants. Denominator data by country of birth for recently arrived migrants is needed to understand the dynamics of migration in Ireland and how it may be linked to the evolving epidemiology of infectious diseases such as TB. More complete data are needed for key indicators such as HIV status and year of arrival in the country. Differences in the epidemiology of TB reported by this study can be used to inform and enhance future TB service provision and promote migrant health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was received from the research ethics committee in the School of Nursing and Midwifery, Trinity College Dublin. Informed consent was not sought from the patients in this study as the legal basis for processing surveillance data in Ireland is not consent but based on GDPR Articles 6(1)(c) and 6(1)(e); Articles 9(2)(i) and 9(2)(j) and the Infectious Disease Regulations [16,17].\u0026nbsp;Furthermore, as this was a secondary data analysis of anonymized data there was no requirement for informed consent under the Health Research Regulations Act 2018 [18]. All data processing was compliant with the General Data Protection Regulations\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors do not have authorisation to share the data used in this study based on the conditions of data access. The raw data used in this study are available upon reasonable request to the Health Protection Surveillance Centre, Health Service Executive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was undertaken as part of Ms Sarah Jackson\u0026rsquo;s doctoral project in Trinity College Dublin and is funded by the Health Service Executive, Ireland. The funders did not have a role in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSJ acquired the data, conducted the analysis and wrote the original draft. All authors contributed to the conceptualisation, interpretation of results, critical review and editing of the manuscript. All authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all the patients whose data were used in this research and the health care professionals who collected the data. The authors would also like to acknowledge Julie Arnott, University College Cork, for peer review of the Stata code used to clean the surveillance dataset and the Central Statistics Office for providing bespoke denominator data tabulations. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Global Tuberculosis Report, 2023; TB burden estimates 2011-2021 2024.\u003c/li\u003e\n\u003cli\u003eHSE Health Protection Surveillance Centre. Tuberculosis in Ireland: provisional trends in surveillance data. 2025. https://www.hpsc.ie/a-z/vaccinepreventable/tuberculosistb/tbdataandreports/TB%20Trends%20in%20Ireland%202018-2022.pdf (accessed March 21, 2025).\u003c/li\u003e\n\u003cli\u003eWalker TM, Merker M, Knoblauch AM, Helbling P, Schoch OD, van der Werf MJ, et al. A cluster of multidrug-resistant Mycobacterium tuberculosis among patients arriving in Europe from the Horn of Africa: a molecular epidemiological study. Lancet Infect Dis 2018;18:431\u0026ndash;40. https://doi.org/10.1016/S1473-3099(18)30004-5.\u003c/li\u003e\n\u003cli\u003eSarivalasis A, Zellweger J-P, Faouzi M, Daher O, Deslarzes C, Bodenmann P. Factors associated with latent tuberculosis among asylum seekers in Switzerland: a cross-sectional study in Vaud County. BMC Infect Dis 2012;12:285. https://doi.org/10.1186/1471-2334-12-285.\u003c/li\u003e\n\u003cli\u003eRendon A, Centis R, Zellweger J-P, Solovic I, Torres-Duque CA, Robalo Cordeiro C, et al. Migration, TB control and elimination: Whom to screen and treat. Pulmonology 2018;24:99\u0026ndash;105. https://doi.org/10.1016/j.rppnen.2017.11.007.\u003c/li\u003e\n\u003cli\u003ePareek M, Greenaway C, Noori T, Munoz J, Zenner D. The impact of migration on tuberculosis epidemiology and control in high-income countries: a review. BMC Med 2016;14:48. https://doi.org/10.1186/S12916-016-0595-5.\u003c/li\u003e\n\u003cli\u003eHayward S, Harding RM, McShane H, Tanner R. Factors influencing the higher incidence of tuberculosis among migrants and ethnic minorities in the UK. F1000Res 2018;7. https://doi.org/10.12688/F1000RESEARCH.14476.2/DOI.\u003c/li\u003e\n\u003cli\u003eHargreaves JR, Boccia D, Evans CA, Adato M, Petticrew M, Porter JDH. The social determinants of tuberculosis: from evidence to action. Am J Public Health 2011;101:654\u0026ndash;62. https://doi.org/10.2105/ajph.2010.199505.\u003c/li\u003e\n\u003cli\u003eInternational Organization for Migration. 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College Station, TX: StataCorp LLC 2015.\u003c/li\u003e\n\u003cli\u003eEuropean Parliament and Council. General Data Protection Regulation. 2016.\u003c/li\u003e\n\u003cli\u003eInfectious Diseases Regulations. Ireland: 1981.\u003c/li\u003e\n\u003cli\u003eData Protection Act (Section 36(2)) (Health Research) Regulations. 2018.\u003c/li\u003e\n\u003cli\u003eCentral Statistics Office. Population usually resident and present in the State 2011 to 2016; by birthplace and single year of age 2016. https://data.cso.ie/ (accessed January 15, 2024).\u003c/li\u003e\n\u003cli\u003eHayward SE, Rustage K, Nellums LB, van der Werf MJ, Noori T, Boccia D, et al. Extrapulmonary tuberculosis among migrants in Europe, 1995 to 2017. Clin Microbiol Infect 2021;27:1347.e1-1347.e7. https://doi.org/10.1016/J.CMI.2020.12.006.\u003c/li\u003e\n\u003cli\u003ePeto HM, Pratt RH, Harrington TA, LoBue PA, Armstrong LR. Epidemiology of Extrapulmonary Tuberculosis in the United States, 1993\u0026ndash;2006. Clinical Infectious Diseases 2009;49:1350\u0026ndash;7. https://doi.org/10.1086/605559.\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;dm\u0026ouml;n C, Zucs P, van der Werf MJ. Migration-related tuberculosis: epidemiology and characteristics of tuberculosis cases originating outside the European Union and European Economic Area, 2007 to 2013. Euro Surveill 2016;21. https://doi.org/10.2807/1560-7917.ES.2016.21.12.30164.\u003c/li\u003e\n\u003cli\u003eHSE Health Protection Surveillance Centre. Guidelines on the Prevention and Control of Tuberculosis in Ireland 2010.\u003c/li\u003e\n\u003cli\u003eAl Abri S, Kasaeva T, Migliori GB, Goletti D, Zenner D, Denholm J, et al. Tools to implement the World Health Organization End TB Strategy: Addressing common challenges in high and low endemic countries. International Journal of Infectious Diseases 2020;92:S60\u0026ndash;8. https://doi.org/10.1016/j.ijid.2020.02.042.\u003c/li\u003e\n\u003cli\u003eHSE National Health Protection Office. A Collaborative Tuberculosis Strategy for Ireland: 2024-2030 2024.\u003c/li\u003e\n\u003cli\u003eLuque L, Rodrigo T, Garc\u0026iacute;a-Garc\u0026iacute;a JM, Casals M, Millet JP, Cayl\u0026agrave; J, et al. Factors Associated With Extrapulmonary Tuberculosis in Spain and Its Distribution in Immigrant Population. Open Respiratory Archives 2020;2:119\u0026ndash;26. https://doi.org/10.1016/j.opresp.2020.04.004.\u003c/li\u003e\n\u003cli\u003eStucki D, Ballif M, Egger M, Furrer H, Altpeter E, Battegay M, et al. Standard genotyping overestimates transmission of mycobacterium tuberculosis among immigrants in a low-incidence country. J Clin Microbiol 2016;54:1862\u0026ndash;70. https://doi.org/10.1128/JCM.00126-16.\u003c/li\u003e\n\u003cli\u003eWalker TM, Lalor MK, Broda A, Ortega LS, Morgan M, Parker L, et al. Assessment of Mycobacterium tuberculosis transmission in Oxfordshire, UK, 2007-12, with whole pathogen genome sequences: An observational study. Lancet Respir Med 2014;2:285\u0026ndash;92. https://doi.org/10.1016/S2213-2600(14)70027-X.\u003c/li\u003e\n\u003cli\u003eSandgren A, Sane Schepisi M, Sotgiu G, Huitric E, Migliori GB, Manissero D, et al. Tuberculosis transmission between foreign- and native-born populations in the EU/EEA: a systematic review. European Respiratory Journal 2014;43:1159\u0026ndash;71. https://doi.org/10.1183/09031936.00117213.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO global lists of high burden countries for tuberculosis, TB/HIV and multidrug / rifampicin-resistant TB (MDR / RR-TB), 2021\u0026ndash;2025 2021.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO consolidated guidelines on tuberculosis. Module 6: tuberculosis and comorbidities. 2024.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Implementing the End TB Strategy: The essentials 2022 update 2022.\u003c/li\u003e\n\u003cli\u003eEuropean Centre for Disease Prevention and Control / World Health Organization. Tuberculosis surveillance and monitoring in Europe 2025 - 2023 data 2025.\u003c/li\u003e\n\u003cli\u003eEimer J, Patimeteeporn C, Jensenius M, Gkrania-Klotsas E, Duvignaud A, Barnett ED, et al. Multidrug-resistant tuberculosis imported into low-incidence countries-a GeoSentinel analysis, 2008-2020. J Travel Med 2021;28. https://doi.org/10.1093/jtm/taab069.\u003c/li\u003e\n\u003cli\u003eBaker M, Das D, Venugopal K, Howden-Chapman P. Tuberculosis associated with household crowding in a developed country. J Epidemiol Community Health (1978) 2008;62:715\u0026ndash;21. https://doi.org/10.1136/JECH.2007.063610.\u003c/li\u003e\n\u003cli\u003eMangan JM, Woodruff RS, Winston CA, Nabity SA, Haddad MB, Dixon MG, et al. Recommendations for Use of Video Directly Observed Therapy During Tuberculosis Treatment \u0026mdash; United States, 2023. MMWR Morb Mortal Wkly Rep 2023;72:313\u0026ndash;6. https://doi.org/10.15585/mmwr.mm7212a4.\u003c/li\u003e\n\u003cli\u003eVasiliu A, K\u0026ouml;hler N, Altpeter E, \u0026AElig;gisd\u0026oacute;ttir TR, Amerali M, de O\u0026ntilde;ate WA, et al. Tuberculosis incidence in foreign-born people residing in European countries in 2020. Eurosurveillance 2023;28:2300051. https://doi.org/10.2807/1560-7917.ES.2023.28.42.2300051.\u003c/li\u003e\n\u003cli\u003eDomaszewska T, Koch A, Jackson S, Arrazola de O\u0026ntilde;ate W, Guthmann JP, Hauer B, et al. Tuberculosis rates in immigrants to low-incidence European countries: epidemiological differences and similarities. Eurosurveillance 2025;30. https://doi.org/10.2807/1560-7917.ES.2025.30.11.2400489.\u003c/li\u003e\n\u003cli\u003eHSE Social Inclusion. Report of the Refugee and Applicants Seeking Protection Blood Borne Virus and Tuberculosis Screening Implementation Advisory Group. 2023.\u003c/li\u003e\n\u003cli\u003eCentral Statistics Office. Population Aged 15 Years and Over 2016 by Principal Economic Status and Birthplace 2016.\u003c/li\u003e\n\u003cli\u003eTrauer JM, Williams B, Laemmle-Ruff I, Horyniak D, Caplice LVS, McBryde ES, et al. Tuberculosis in migrants to Australia: Outcomes of a national screening program. Lancet Reg Health West Pac 2021;10. https://doi.org/10.1016/j.lanwpc.2021.100135.\u003c/li\u003e\n\u003cli\u003eJackson S, Hauer B, Guthmann J-P, O\u0026acute;Meara M, Sizaire V, Nordstrand K, et al. Differences found in patient characteristics of migrant tuberculosis sub-populations within low TB incidence European countries, 2014-2020. Pre-Print Available at: Https://WwwResearchsquareCom/Article/Rs-6214584/V1 2025.\u003c/li\u003e\n\u003cli\u003eLonnroth K, Mor Z, Erkens C, Bruchfeld J, Nathavitharana RR, Van Der Werf MJ, et al. Tuberculosis in migrants in low-incidence countries: Epidemiology and intervention entry points. International Journal of Tuberculosis and Lung Disease 2017;21:624\u0026ndash;36. https://doi.org/10.5588/ijtld.16.0845.\u003c/li\u003e\n\u003cli\u003eDale KD, Trauer JM, Dodd PJ, Houben RMGJ, Denholm JT. Estimating long-term tuberculosis reactivation rates in australian migrants. Clinical Infectious Diseases 2020;70:2111\u0026ndash;8. https://doi.org/10.1093/cid/ciz569.\u003c/li\u003e\n\u003cli\u003eLangholz Kristensen K, Ravn P, Petersen JH, Hargreaves S, Nellums LB, Friedland JS, et al. Long-term risk of tuberculosis among migrants according to migrant status: A cohort study. Int J Epidemiol 2020;49:776\u0026ndash;85. https://doi.org/10.1093/IJE/DYAA063.\u003c/li\u003e\n\u003cli\u003eRonald L, Campbell J, Balshaw R, Roth D, Romanowski K, Marra F, et al. Predicting tuberculosis risk in the foreign-born population of British Columbia, Canada: Retrospective population-based cohort study. Am J Respir Crit Care Med 2017;195. https://doi.org/10.1164/ajrccm-conference.2017.B63.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTB patient characteristics by migrant status and logistic regression analysis results; Ireland 2011\u0026ndash;2021\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;3,198\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNon-migrant\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,593\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMigrant\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,605\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUnivariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMultivariable (N\u0026thinsp;=\u0026thinsp;825)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ecOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian age (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.0 (28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.0 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.0 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 (0.95 to 0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97 (0.95 to 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,276 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e588 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e688 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,918 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,005 (63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e913 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78 (0.67 to 0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographical area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEast\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,387 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e563 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e824 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMidlands\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85 (0.61 to 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.26 (1.24 to 9.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMidwest\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60 (0.45 to 0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10 (0.63 to 1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNorth East\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e228 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e113 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67 (0.51 to 0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.45 (0.57 to 4.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNorth West\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.34 (0.22 to 0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62 (0.27 to 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSouth\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e610 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e396 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.37 (0.30 to 0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65 (0.41 to 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSouth East\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e262 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.54 (0.42 to 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76 (0.46 to 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWest\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e245 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.68 (0.52 to 0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.16 (0.58 to 2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e371 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePaid employment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,041 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e399 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e642 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eUnemployed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e929 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e428 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e501 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73 (0.61 to 0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82 (0.56 to 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRetired\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e443 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e403 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06 (0.04 to 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27 (0.12 to 0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStudent/Child\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e329 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e194 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89 (0.69 to 1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86 (0.45 to 1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53 (0.34 to 0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81 (0.35 to 1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent housing type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e343 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePrivate house\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,646 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,352 (94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,294 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eCongregate residential setting\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.00 (1.34 to 3.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHomeless\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72 (0.32 to 1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePrison\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.51 (0.65 to 3.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eResidential care facility\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12 (0.02 to 0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOther housing\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.57 (0.80 to 3.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePulmonary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,140 (68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,223 (78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e917 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExtrapulmonary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,022 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e353 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e669 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.53 (2.17 to 2.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.14 (2.09 to 4.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutbreak associated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNot linked to outbreak\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,875 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,345 (84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,530 (95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOutbreak associated\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e323 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e248 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27 (0.20 to 0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16 (0.09 to 0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeople living with HIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,804 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNegative\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,266 (91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e554 (96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e712 (87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePositive\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.75 (2.38 to 6.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.80 (1.99 to 7.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst line drug resistance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e838 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSensitive\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,065 (88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,046 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,019 (83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eResistant\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e295 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e213 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.67 (2.05 to 3.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.30 (1.37 to 4.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eM/XDR-TB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e838 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,315 (98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,126 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,189 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.4 (6.26 to 125)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious TB screening in Ireland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e887 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,953 (85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e908 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,045 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e358 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e224 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52 (0.41 to 0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious TB diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e801 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.086\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,188 (91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,089 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,099 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e209 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78 (0.58 to 1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e362 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHospital inpatient\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,658 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e876 (61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e782 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHospital outpatient\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e914 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e425 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e489 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29 (1.10 to 1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e264 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (0.71 to 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,862 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,204 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e648 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e556 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132 (9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (0.70 to 1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmunosuppression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,841 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.033\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,067 (79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e569 (76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e498 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e290 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e175 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75 (0.58 to 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstance use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,881 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e945 (72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e475 (62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e470 (86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e372 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e297 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26 (0.19 to 0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMigrant source countries with top 10 highest percentage of patients or CIR between 2011\u0026ndash;2021, Ireland\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCountry of birth\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean CIR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedian CIR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean WHO estimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRanking in Ireland\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWHO Mean CIR category\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYears with patients\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal patients\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e% of migrant with TB\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEritrea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e443.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e609.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBotswana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e359.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e359.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e336.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSomalia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e284.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e333.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e269.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR \u0026amp; number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalawi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e269.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e237.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMongolia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e166.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e261.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e428.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndonesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e161.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e325.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUganda\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e150.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e207.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e201.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNepal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e147.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e124.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e261.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e137.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e133.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e244.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR \u0026amp; number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePakistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e268.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 CIR \u0026amp; number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhilippines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e555.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e858.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e219.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRomania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLithuania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePoland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnited Kingdom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTop 10 number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMigrant TB patient characteristics by interval between arrival and notification; Ireland\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,071\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eInterval between arrival in Ireland and TB diagnosis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u0026ndash;1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;239\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u0026ndash;4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;295\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u0026ndash;9\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;239\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e10+\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;298\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian age (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.0 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.0 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.0 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.0 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.0 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e133 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e596 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e175 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e163 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternational Protection Applicant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e799 (86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e164 (77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e223 (85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e238 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e127 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWHO TB incidence category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLow\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMedium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHigh\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e184 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eVery high\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e749 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172 (72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e217 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169 (71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191 (65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious TB screening in Ireland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e814 (88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e202 (94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e226 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172 (84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214 (85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e113 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious TB diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e839 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e192 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e225 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e192 (95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e230 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePulmonary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e626 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e163 (68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eExtrapulmonary\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e443 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e127 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonths between onset and diagnosis, Median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutbreak associated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNot linked to outbreak\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,026 (96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e232 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e274 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e232 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e288 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOutbreak associated\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeople living with HIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNegative\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e542 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154 (91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePositive\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst line drug resistance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSensitive\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e697 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196 (79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165 (84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e178 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eResistant\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eM/XDR-TB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e826 (96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e187 (96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e235 (95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e213 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePaid employment\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e479 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eUnemployed\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e365 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRetired\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStudent/Child\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e147 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent housing type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePrivate house\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e952 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e183 (79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e271 (93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e218 (94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e280 (98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCongregate residential / care setting\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePrison / Homeless\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOther housing\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e(% missing)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e[a] Kruskal-Wallis rank sum test; Pearson\u0026apos;s Chi-squared test..\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"tuberculosis, epidemiology, incidence, public health, emigration and immigration","lastPublishedDoi":"10.21203/rs.3.rs-6469195/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6469195/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eIntroduction:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTuberculosis (TB) remains a global public health threat that was responsible for 1.3\u0026nbsp;million deaths in 2022 alone. While Ireland is a low TB incidence country, with crude incidence rates (CIRs) in the Irish-born below 6 per 100,000 population since 2011, CIRs in the foreign-born population are up to 13 times higher. This study aims to inform TB prevention and care by analysing the differences in the epidemiology of TB in native-born and foreign-born populations in Ireland.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA cross-sectional analysis of all TB notifications reported to the Irish TB Surveillance System from 2011\u0026ndash;2021 was performed. Temporal trends in CIRs were analysed using Negative-binomial regression. Independent variables selected with a p value of \u0026lt;\u0026thinsp;0.25 in univariable analysis were investigated in a multivariable logistic regression model comparing TB patient characteristics between migrants and Irish-born.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOf the 3,364 TB patients, 48% were among migrants. Compared to Irish-born, migrants with TB were younger, had higher odds of living with HIV, extra-pulmonary disease, infection with drug-resistant strains and residence in congregate residential settings with lower odds linkage to outbreaks. Recently arrived migrants with TB had higher proportions of international protection applicants and refugees, pulmonary disease and people living with HIV. Between 2011\u0026ndash;2021, a significantly declining temporal trend was present for migrants, Irish-born and total TB patients. Between 2017 and 2021, a significantly declining temporal trend was still present in Irish-born and total patients, but the trend was no longer significant among migrants with TB.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDiscussion/Conclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA heightened awareness of extrapulmonary TB within health systems is needed given the high levels observed among migrants with TB. The pace of TB decline among migrants is slower than among Irish-born and has plateaued in the final years of this study period, making TB elimination targets more difficult to achieve. Differences in the epidemiology of TB reported by this study can be used to inform and enhance future TB service provision and promote migrant health.\u003c/p\u003e","manuscriptTitle":"Differences found in patient profiles and incidence trends between migrants and native-born Tuberculosis patients in Ireland; 2011-2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 11:21:43","doi":"10.21203/rs.3.rs-6469195/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9db98a86-2d55-4526-9c7b-3bf3683312f9","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-01T23:23:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 11:21:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6469195","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6469195","identity":"rs-6469195","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}