BMC Infectious Diseases
Volume 19, Issue 1, 2019

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 (Review) (Open Access)

Bozorgmehr K.* , Preussler S. , Wagner U. , Joggerst B. , Szecsenyi J. , Razum O. , Stock C.
  • a Department of General Practice and Health Services Research, University Hospital Heidelberg, INF 130.3, Heidelberg, 69120, Germany, Department of Population Medicine and Health Services Research, School of Public Health, Bielefeld University, Bielefeld, Germany
  • b Institute of Medical Biometry and Informatics (IMBI), University Hospital Heidelberg, Heidelberg, Germany
  • c Public Health Authority, Section for Disease Control, Landkreis Karlsruhe, Karlsruhe, Germany
  • d Public Health Authority, Enzkreis, Pforzheim, Germany
  • e Department of General Practice and Health Services Research, University Hospital Heidelberg, INF 130.3, Heidelberg, 69120, Germany
  • f Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Bielefeld, Germany
  • g Institute of Medical Biometry and Informatics (IMBI), University Hospital Heidelberg, Heidelberg, Germany, Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, DKFZ, Heidelberg, Germany

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. © 2019 The Author(s).

Author Keywords

Global health Screening Migration Asylum seekers tuberculosis Efficiency Modelling Public health Epidemiology Infection control

Index Keywords

Germany refugee Iraqi mass screening human Refugees middle aged statistics and numerical data probability Aged asylum seeker Young Adult health program Humans migrant Adolescent male Emigrants and Immigrants female prediction tuberculosis Bayes theorem communicable disease control measurement accuracy Review medical information prevalence Incidence major clinical study adult world health organization Models, Statistical statistical model disease burden german federal republic public health Child
Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064071012&doi=10.1186%2fs12879-019-3902-x&partnerID=40&md5=a4c283c48e4a7090d127f88242a278f1
DOI: 10.1186/s12879-019-3902-x
ISSN: 14712334
Cited by: 1
Original Language: English