Lena Fiebig

Models of epidemics: when contact repetition and clustering should be included.

BackgroundThe spread of infectious disease is determined by biological factors, e.g. the duration of the infectious period, and social factors, e.g. the arrangement of potentially contagious contacts. Repetitiveness and clustering of contacts are known to be relevant factors influencing the transmission of droplet or contact transmitted diseases. However, we do not yet completely know under what conditions repetitiveness and clustering should be included for realistically modelling disease spread.MethodsWe compare two different types of individual-based models: One assumes random mixing without repetition of contacts, whereas the other assumes that the same contacts repeat day-by-day. The latter exists in two variants, with and without clustering. We systematically test and compare how the total size of an outbreak differs between these model types depending on the key parameters transmission probability, number of contacts per day, duration of the infectious period, different levels of clustering and varying proportions of repetitive contacts.ResultsThe simulation runs under different parameter constellations provide the following results: The difference between both model types is highest for low numbers of contacts per day and low transmission probabilities. The number of contacts and the transmission probability have a higher influence on this difference than the duration of the infectious period. Even when only minor parts of the daily contacts are repetitive and clustered can there be relevant differences compared to a purely random mixing model.ConclusionWe show that random mixing models provide acceptable estimates of the total outbreak size if the number of contacts per day is high or if the per-contact transmission probability is high, as seen in typical childhood diseases such as measles. In the case of very short infectious periods, for instance, as in Norovirus, models assuming repeating contacts will also behave similarly as random mixing models. If the number of daily contacts or the transmission probability is low, as assumed for MRSA or Ebola, particular consideration should be given to the actual structure of potentially contagious contacts when designing the model.

Severe Cases of Pandemic (H1N1) 2009 in Children, Germany

In a hospital-based observational study in Germany, we investigated children admitted to pediatric intensive care units and deaths caused by confirmed pandemic (H1N1) 2009 to identify risk factors and outcomes in critically ill children. Ninety-three children were eligible for our study, including 9 with hospital-acquired infections. Seventy-five percent had underlying chronic medical conditions; neurodevelopmental disorders were most prevalent (57%). The proportion of patients having ≥1 risk factor increased with age in years (odds ratio 1.21, p = 0.007). Of 15 deaths, 11 occurred in a pediatric intensive care unit (case-fatality rate 12%, 95% confidence interval 6%-21%). Only 9% of the children had been vaccinated against pandemic (H1N1) 2009; all survived. Our results stress the role of underlying risk factors, especially neurodevelopmental disorders, and the need for improving preventive measures to reduce severe disease and adverse outcomes of pandemic (H1N1) 2009 in children.

Tuberculosis among people living with HIV/AIDS in the German ClinSurv HIV Cohort: long-term incidence and risk factors

BackgroundTuberculosis (TB) still presents a leading cause of morbidity and mortality among people living with HIV/AIDS (PLWHA), including those on antiretroviral therapy. In this study, we aimed to determine the long-term incidence density rate (IDR) of TB and risk factors among PLWHA in relation to combination antiretroviral therapy (cART)-status.MethodsData of PLWHA enrolled from 2001 through 2011 in the German ClinSurv HIV Cohort were investigated using survival analysis and Cox regression.ResultsTB was diagnosed in 233/11,693 PLWHA either at enrollment (N = 62) or during follow-up (N = 171). The TB IDR during follow-up was 0.37 cases per 100 person-years (PY) overall [95% CI, 0.32-0.43], and was higher among patients who never started cART and among patients originating from Sub-Saharan Africa (1.23 and 1.20 per 100PY, respectively). In two multivariable analyses, both patients (I) who never started cART and (II) those on cART shared the same risk factors for TB, namely: originating from Sub-Saharan Africa compared to Germany (I, hazard ratio (HR); [95% CI]) 4.05; [1.87-8.78] and II, HR 5.15 [2.76-9.60], CD4+ cell count <200 cells/μl (I, HR 8.22 [4.36-15.51] and II, HR 1.90 [1.14-3.15]) and viral load >5 log10 copies/ml (I, HR 2.51 [1.33-4.75] and II, HR 1.77 [1.11-2.82]). Gender, age or HIV-transmission risk group were not independently associated with TB.ConclusionIn the German ClinSurv HIV cohort, patients originating from Sub-Saharan Africa, with low CD4+ cell count or high viral load at enrollment were at increased risk of TB even after cART initiation. As patients might be latently infected with Mycobacterium tuberculosis complex, early screening for latent TB infection and implementing isoniazid preventive therapy in line with available recommendations is crucial.

Exposure Patterns Driving Ebola Transmission in West Africa: A Retrospective Observational Study.

Background The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved. Methods and Findings Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola (“cases”) were asked if they had exposure to other potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO’s response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = −0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were better than other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible misclassifications). Conclusions Achieving elimination of Ebola is challenging, partly because of super-spreading. Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. Continued real-time data capture, reporting, and analysis are vital to track transmission patterns, inform resource deployment, and thus hasten and maintain elimination of the virus from the human population.

Higher Rate of Tuberculosis in Second Generation Migrants Compared to Native Residents in a Metropolitan Setting in Western Europe

Background In Western Europe, migrants constitute an important risk group for tuberculosis, but little is known about successive generations of migrants. We aimed to characterize migration among tuberculosis cases in Berlin and to estimate annual rates of tuberculosis in two subsequent migrant generations. We hypothesized that second generation migrants born in Germany are at higher risk of tuberculosis compared to native (non-migrant) residents. Methods A prospective cross-sectional study was conducted. All tuberculosis cases reported to health authorities in Berlin between 11/2010 and 10/2011 were eligible. Interviews were conducted using a structured questionnaire including demographic data, migration history of patients and their parents, and language use. Tuberculosis rates were estimated using 2011 census data. Results Of 314 tuberculosis cases reported, 154 (49.0%) participated. Of these, 81 (52.6%) were first-, 14 (9.1%) were second generation migrants, and 59 (38.3%) were native residents. The tuberculosis rate per 100,000 individuals was 28.3 (95CI: 24.0–32.6) in first-, 10.2 (95%CI: 6.1–16.6) in second generation migrants, and 4.6 (95%CI: 3.7–5.6) in native residents. When combining information from the standard notification variables country of birth and citizenship, the sensitivity to detect second generation migration was 28.6%. Conclusions There is a higher rate of tuberculosis among second generation migrants compared to native residents in Berlin. This may be explained by presumably frequent contact and transmission within migrant populations. Second generation migration is insufficiently captured by the surveillance variables country of birth and citizenship. Surveillance systems in Western Europe should allow for quantifying the tuberculosis burden in this important risk group.

A cluster of multidrug-resistant Mycobacterium tuberculosis among patients arriving in Europe from the Horn of Africa: a molecular epidemiological study

Summary Background The risk of tuberculosis outbreaks among people fleeing hardship for refuge in Europe is heightened. We describe the cross-border European response to an outbreak of multidrug-resistant tuberculosis among patients from the Horn of Africa and Sudan. Methods On April 29 and May 30, 2016, the Swiss and German National Mycobacterial Reference Laboratories independently triggered an outbreak investigation after four patients were diagnosed with multidrug-resistant tuberculosis. In this molecular epidemiological study, we prospectively defined outbreak cases with 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) profiles; phenotypic resistance to isoniazid, rifampicin, ethambutol, pyrazinamide, and capreomycin; and corresponding drug resistance mutations. We whole-genome sequenced all Mycobacterium tuberculosis isolates and clustered them using a threshold of five single nucleotide polymorphisms (SNPs). We collated epidemiological data from host countries from the European Centre for Disease Prevention and Control. Findings Between Feb 12, 2016, and April 19, 2017, 29 patients were diagnosed with multidrug-resistant tuberculosis in seven European countries. All originated from the Horn of Africa or Sudan, with all isolates two SNPs or fewer apart. 22 (76%) patients reported their travel routes, with clear spatiotemporal overlap between routes. We identified a further 29 MIRU-VNTR-linked cases from the Horn of Africa that predated the outbreak, but all were more than five SNPs from the outbreak. However all 58 isolates shared a capreomycin resistance-associated tlyA mutation. Interpretation Our data suggest that source cases are linked to an M tuberculosis clone circulating in northern Somalia or Djibouti and that transmission probably occurred en route before arrival in Europe. We hypothesise that the shared mutation of tlyA is a drug resistance mutation and phylogenetic marker, the first of its kind in M tuberculosis sensu stricto. Funding The Swiss Federal Office of Public Health, the University of Zurich, the Wellcome Trust, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), the Medical Research Council, BELTA-TBnet, the European Union, the German Center for Infection Research, and Leibniz Science Campus Evolutionary Medicine of the Lung (EvoLUNG).

Unchanged Severity of Influenza A(H1N1)pdm09 Infection in Children during First Postpandemic Season

Improvement is needed in preventing severe disease and nosocomial transmission in children beyond pandemic situations.

Multidrug-resistant TB in Eastern region of the EU: is the shorter regimen an exception or a rule?

WHO recently recommended the use of a shorter multidrug-resistant TB (MDR-TB) regimen under programmatic conditions. We assessed eligibility for this regimen in a cohort of 737 adult patients with MDR-TB from Latvia, Lithuania, Estonia and Bucharest city recruited in 2007 and 2009. Only 4.2% of the patients were eligible for this regimen. Ethambutol (64%), pyrazinamide resistance (58%) and previous exposure to second-line TB drugs were major reasons for non-eligibility. High-level resistance to isoniazid is expected due to widespread prevalence of katG mutations. In Eastern Europe, the use of the shorter regimen might be an exception rather than a rule.

HIV-Prevalence in Tuberculosis Patients in Germany, 2002–2009: An Estimation Based on HIV and Tuberculosis Surveillance Data

Tuberculosis (TB) and HIV comorbidity is a major challenge in TB prevention and control but difficult to assess in Germany as in other countries, where data confidentiality precludes notifying the HIV status of TB patients. We aimed to estimate the HIV-prevalence in TB patients in Germany, 2002–2009, and to characterize the HIV/TB patients demographically. Data from the long-term observational open multicentre cohort ClinSurv HIV were used to identify incident TB in HIV-positive individuals. We assessed the cohort’s coverage for the nationwide HIV-positive population by contrasting ClinSurv HIV patients under antiretroviral therapy (ART) with national HIV patient numbers derived from ART prescriptions (data by Insight Health; available for 2006–2009). The HIV-prevalence in TB patients was calculated as the number of HIV/TB cases projected for Germany over all culture-positive TB notifications. From 2002 to 2009, 298 of 15,531 HIV-positive patients enrolled in the ClinSurv HIV cohort were diagnosed with TB. A 21% cohort coverage was determined. The annual estimates of the HIV-prevalence in TB patients were on average 4.5% and ranged from 3.5% (95%CI 2.3–5.1%) in 2007 to 6.6% (95%CI 5.0–8.5%) in 2005. The most recent estimate for 2009 was 4.0% (95%CI 2.6–5.9%). The 298 HIV/TB patients were characterized by a male-to-female ratio of 2.1, by a median age of 38 years at TB diagnosis, and by 59% of the patients having a foreign origin, mainly from Subsahara Africa. We provide, to our knowledge, the first estimate of the HIV-prevalence in TB patients for Germany by joint evaluation of anonymous HIV and TB surveillance data sources. The identified level of HIV in TB patients approximates available surveillance data from neighbouring countries and indicates a non-negligible HIV/TB burden in Germany. Our estimation approach is valuable for epidemiological monitoring of HIV/TB within the current legal frameworks.

Tuberculosis treatment outcome in the European Union and European Economic Area: an analysis of surveillance data from 2002‒2011

Monitoring the treatment outcome (TO) of tuberculosis (TB) is essential to evaluate the effectiveness of the intervention and to identify potential barriers for TB control. The global target is to reach a treatment success rate (TSR) of at least 85%. We aimed to assess the TB TO in the European Union and European Economic Area (EU/EEA) between 2002 and 2011, and to identify factors associated with unsuccessful treatment. Only 18 countries reported information on TO for the whole observation period accounting for 250,854 new culture-confirmed pulmonary TB cases. The 85% target of TSR was not reached in any year between 2002 and 2011 and was on average 78%. The TSR for multidrug-resistant (MDR)-TB cases at 24-month follow-up was 49%. In the multivariable regression model, unsuccessful treatment was significantly associated with increasing age (odds ratio (OR) = 1.02 per a one-year increase, 95% confidence interval (CI): 1.02-1.02), MDR-TB (OR = 8.7, 95% CI: 5.09-14.97), male sex (OR = 1.40, 95% CI: 1.28-1.52), and foreign origin (OR = 1.32, 95% CI: 1.03-1.70). The data highlight that special efforts are required for patients with MDR-TB and the elderly aged ≥65 years, who have particularly low TSR. To allow for valid monitoring at EU level all countries should aim to report TO for all TB cases.