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. 2019 Apr 3;19(1):304.
doi: 10.1186/s12879-019-3902-x.

Using country of origin to inform targeted tuberculosis screening in asylum seekers: a modelling study of screening data in a German federal state, 2002-2015

Kayvan Bozorgmehr  1   2 , Stella Preussler  3 , Ulrich Wagner  4 , Brigitte Joggerst  5 , Joachim Szecsenyi  6 , Oliver Razum  7 , Christian Stock  3   8
Affiliations

Using country of origin to inform targeted tuberculosis screening in asylum seekers: a modelling study of screening data in a German federal state, 2002-2015

Kayvan Bozorgmehr et al. BMC Infect Dis. .

Abstract

Background: Screening programmes for tuberculosis (TB) among immigrants rarely consider the heterogeneity of risk related to migrants' country of origin. We assess the performance of a large screening programme in asylum seekers by analysing (i) the difference in yield and numbers needed to screen (NNS) by country and WHO-reported TB burden, (ii) the possible impact of screening thresholds on sensitivity, and (iii) the value of WHO-estimated TB burden to improve the prediction accuracy of screening yield.

Methods: We combined individual data of 119,037 asylum seekers screened for TB in Germany (2002-2015) with TB estimates of the World Health Organization (WHO) (1990-2014) for their 81 countries of origin. Adjusted rate ratios (aRR) and 95% credible intervals (CrI) of the observed yield of screening were calculated in Bayesian Poisson regression models by categories of WHO-estimated TB incidence. We assessed changes in sensitivity depending on screening thresholds, used WHO TB estimates as prior information to predict TB in asylum seekers, and modelled country-specific probabilities of numbers needed to screen (NNS) conditional on different screening thresholds.

Results: The overall yield was 82 per 100,000 and the annual yield ranged from 44.1 to 279.7 per 100,000. Country-specific yields ranged from 10 (95%- CrI: 1-47) to 683 (95%-CrI: 306-1336) per 100,000 in Iraqi and Somali asylum seekers, respectively. The observed yield was higher in asylum seekers from countries with a WHO-estimated TB incidence > 50 relative to those from countries ≤50 per 100,000 (aRR: 4.17, 95%-CrI: 2.86-6.59). Introducing a threshold in the range of a WHO-estimated TB incidence of 50 and 100 per 100,000 resulted in the lowest "loss" in sensitivity. WHO's TB prevalence estimates improved prediction accuracy for eight of the 11 countries, and allowed modelling country-specific probabilities of NNS.

Conclusions: WHO's TB data can inform the estimation of screening yield and thus be used to improve screening efficiency in asylum seekers. This may help to develop more targeted screening strategies by reducing uncertainty in estimates of expected country-specific yield, and identify thresholds with lowest loss in sensitivity. Further modelling studies are needed which combine clinical, diagnostic and country-specific parameters.

Keywords: Asylum seekers; Efficiency; Epidemiology; Global health; Infection control; Migration; Modelling; Public health; Screening; Tuberculosis.

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Conflict of interest statement

Ethics approval and consent to participate

The study findings are based on anonymous administrative data. This study is therefore exempt from ethical clearance according to the regulations of the Medical Ethics Committee of the Medical Faculty of Heidelberg University. Individual consent was not required due to the retrospective and anonymous nature of the study.

Consent for publication

The study findings are based on anonymous administrative data. Consent for publication is not required.

Competing interests

The material submitted in this manuscript is original and has not been submitted elsewhere. BJ was public health officer in the public health authority Karlsruhe until 2015. UW is public health officer in the public health authority Karlsruhe, Section for Disease Control, mandating the TB screening in the state reception centre Karlsruhe. CS is full time employee of Boehringer Ingelheim Pharma GmbH & Co. KG since October 2018. The company had no role in the design, analysis or interpretation of this study. Views expressed in this article are those of the authors and do not necessarily reflect those of Boehringer Ingelheim Pharma GmbH & Co. KG. The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Yield and number needed to screen with credible intervals by age, sex, period, country of origin and WHO category of estimated incidence TB, N = 119,037 asylum seekers, 2002–2015, Germany. Legend: a Yield; b Number needed to screen, NNS. Y-Axis: log-scale. Plot size shows numbers of individuals screened
Fig. 2
Fig. 2
Absolute number of TB cases, yield of screening, and proportion of asylum seekers from low- and intermediate-incidence TB countries, N = 119,037 asylum seekers, 2002–2015, Germany. Legend: a Absolute number of TB cases and yield of screening by year; b proportion of asylum seekers from low- and intermediate-incidence TB countries by year
Fig. 3
Fig. 3
Percentage change relative to index year 2002 in number of TB cases, yield of screening, proportion of asylum seekers from low- and intermediate-incidence TB countries, and number of asylum seekers screened, N = 119,037 asylum seekers, 2002–2015, Germany
Fig. 4
Fig. 4
Difference in yield of screening in asylum seekers from countries depending on the WHO-estimated incidence of TB in their country of origin, adjusted for age, sex, and period-effects, 2002–2015, Germany, N = 116,813. Legend: Cut-off: Derived from WHO-estimated incidence of TB per 100,000. RR: Relative rate. CrI: Credible interval. Estimates derived from five distinct multiple Bayesian Poisson regression models. The reference group for each cut-off (e.g. ≥ 150) is the group of asylum seekers from countries with values of WHO-estimated TB incidence lower than the respective cut-off (e.g. < 150)
Fig. 5
Fig. 5
Scatter plot of observed yield of screening (per 100,000) and number of individuals screened by country of origin and WHO category of TB incidence, N = 116,995 asylum seekers, 2002–2015, Germany. Legend: X-axis: logarithmic scale. TB incidence in country of origin for Kosovo is taken from the review of Kurhasani et al. [40] due to missing data in WHO Global TB database
Fig. 6
Fig. 6
Impact of screening thresholds on sensitivity of screening, N = 116,995 asylum seekers, 2002–2015, Germany. Legend: a) Undetected cases of TB, b) Individuals not screened, c) Undetected TB cases among individuals not screened (per 1000), X-axis: Cut-off based on WHO-reported TB incidence per 100,000. Dotted lines: Cut-off calculated based on lower and upper bound of 95% confidence intervals reported by WHO. Difference to N=119,037 due to missing information on country of origin among =2042 asylum seekers
Fig. 7
Fig. 7
Densities of the prior distribution on the basis of the WHO data, the binomial distribution on the basis of the German screening data and the density of the posterior beta distribution of the prevalence for each country
Fig. 8
Fig. 8
Plot of the probability that the posterior distribution of expected TB prevalence in asylum seekers from a given country of origin lies above a given NNS value
See this image and copyright information in PMC

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