Assessing the sensitivity and representativeness of the Belgian Sentinel Network of Laboratories using test reimbursement data

Mycoplasma pneumoniae detections before and during the COVID-19 pandemic: results of a global survey, 2017 to 2021

Background

Mycoplasma pneumoniae respiratory infections are transmitted by aerosol and droplets in close contact.

Aim

We investigated global M. pneumoniae incidence after implementation of non-pharmaceutical interventions (NPIs) against COVID-19 in March 2020.

Methods

We surveyed M. pneumoniae detections from laboratories and surveillance systems (national or regional) across the world from 1 April 2020 to 31 March 2021 and compared them with cases from corresponding months between 2017 and 2020. Macrolide-resistant M. pneumoniae (MRMp) data were collected from 1 April 2017 to 31 March 2021.

Results

Thirty-seven sites from 21 countries in Europe, Asia, America and Oceania submitted valid datasets (631,104 tests). Among the 30,617 M. pneumoniae detections, 62.39% were based on direct test methods (predominantly PCR), 34.24% on a combination of PCR and serology (no distinction between methods) and 3.37% on serology alone (only IgM considered). In all countries, M. pneumoniae incidence by direct test methods declined significantly after implementation of NPIs with a mean of 1.69% (SD ± 3.30) compared with 8.61% (SD ± 10.62) in previous years (p < 0.01). Detection rates decreased with direct but not with indirect test methods (serology) (–93.51% vs + 18.08%; p < 0.01). Direct detections remained low worldwide throughout April 2020 to March 2021 despite widely differing lockdown or school closure periods. Seven sites (Europe, Asia and America) reported MRMp detections in one of 22 investigated cases in April 2020 to March 2021 and 176 of 762 (23.10%) in previous years (p = 0.04).

Conclusions

This comprehensive collection of M. pneumoniae detections worldwide shows correlation between COVID-19 NPIs and significantly reduced detection numbers.

One year of laboratory-based COVID-19 surveillance system in Belgium: main indicators and performance of the laboratories (March 2020-21)

BACKGROUND

With the spread of coronavirus disease 2019 (COVID-19), an existing national laboratory-based surveillance system was adapted to daily monitor the epidemiological situation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the Belgium by following the number of confirmed SARS-CoV-2 infections, the number of performed tests and the positivity ratio. We present these main indicators of the surveillance over a one-year period as well as the impact of the performance of the laboratories, regarding speed of processing the samples and reporting results, for surveillance.

METHODS

We describe the evolution of test capacity, testing strategy and the data collection methods during the first year of the epidemic in Belgium.

RESULTS

Between the 1st of March 2020 and the 28th of February 2021, 9,487,470 tests and 773,078 COVID-19 laboratory confirmed cases were reported. Two epidemic waves occurred, with a peak in April and October 2020. The capacity and performance of the laboratories improved continuously during 2020 resulting in a high level performance. Since the end of November 2020 90 to 95% of the test results are reported at the latest the day after sampling was performed.

CONCLUSIONS

Thanks to the effort of all laboratories a performant exhaustive national laboratory-based surveillance system to monitor the epidemiological situation of SARS-CoV-2 was set up in Belgium in 2020. On top of expanding the number of laboratories performing diagnostics and significantly increasing the test capacity in Belgium, turnaround times between sampling and testing as well as reporting were optimized over the first year of this pandemic.

The burden of legionnaires' disease in Belgium, 2013 to 2017

Background

Legionnaires’ disease (LD) is a severe bacterial infection causing pneumonia. Surveillance commonly underestimates the true incidence as not all cases are laboratory confirmed and reported to public health authorities. The aim of this study was to present indicators for the impact of LD in Belgium between 2013 and 2017 and to estimate its true burden in the Belgian population in 2017, the most recent year for which the necessary data were available.

Methods

Belgian hospital discharge data, data from three infectious disease surveillance systems (mandatory notification, sentinel laboratories and the national reference center), information on reimbursed diagnostic tests from the Belgian National Institute for Health and Disability Insurance and mortality data from the Belgian statistical office were used. To arrive at an estimate of the total number of symptomatic cases in Belgium, we defined a surveillance pyramid and estimated a multiplication factor to account for LD cases not captured by surveillance. The multiplication factor was then applied to the pooled number of LD cases reported by the three surveillance systems. This estimate was the basis for our hazard- and incidence-based Disability-Adjusted Life Years (DALYs) calculation. To account for uncertainty in the estimations of the DALYs and the true incidence, we used Monte Carlo simulations with 10,000 iterations.

Results

We found an average of 184 LD cases reported by Belgian hospitals annually (2013–2017), the majority of which were male (72%). The surveillance databases reported 215 LD cases per year on average, 11% of which were fatal within 90 days after diagnosis. The estimation of the true incidence in the community yielded 2674 (95% Uncertainty Interval [UI]: 2425–2965) cases in 2017. LD caused 3.05 DALYs per case (95%UI: 1.67–4.65) and 8147 (95%UI: 4453–12,426) total DALYs in Belgium in 2017, which corresponds to 71.96 (95%UI: 39.33–109.75) DALYs per 100,000 persons.

Conclusions

This analysis revealed a considerable burden of LD in Belgium that is vastly underestimated by surveillance data. Comparison with other European DALY estimates underlines the impact of the used data sources and methodological approaches on burden estimates, illustrating that national burden of disease studies remain essential.

Incidence estimation from sentinel surveillance data; a simulation study and application to data from the Belgian laboratory sentinel surveillance

Background

Inverse probability weighting (IPW) methods can be used to estimate the total number of cases from the sample collected through sentinel surveillance. Central to these methods are the inverse weights which can be derived in several ways and, in this case, represent the probability that laboratory (lab) sentinel surveillance detects a lab-confirmed case.

Methods

We compare different weights in a simulation study. Weights are obtained from the proportion of participating labs over all labs. We adjust these weights for attractiveness and density of labs over population. The market share of sentinel labs, as estimated by the econometric Huff-model, is also considered. Additionally, we investigate the effect of not recognizing sentinel labs as sentinel labs when they report no cases. We estimate the bias associated with the different weights as the difference between the simulated number of cases and the estimate of this total from the sentinel sample.

As motivating data examples, we apply an extended Huff-model to four pathogens under laboratory sentinel surveillance in Belgium between 2010 and 2015 and discuss the model fit. We estimate the total number of lab-confirmed cases associated with Rotavirus, influenza virus, Y. enterocolitica and Campylobacter spp.. The extended Huff-model takes the lab-concept, the number of reimbursements and the number of departments, lab-density, regional borders, distance and competition between labs in account.

Results

Estimates obtained with the Huff-model were most accurate in the more complex simulation scenarios as compared to other weights. In the data examples, several significant coefficients are identified, but the fit of the Huff-model to the Belgian sentinel surveillance data leaves much variability in market shares unexplained.

Conclusion

The Huff-model allows for estimation of the spatial and population coverage of sentinel surveillance and through IPW-methods also for the estimation of the total number of cases. The Huff-model‘s gravity function allows us to differentiate inside an area while estimating from the full dataset. Our data examples show that additional data on the participation to surveillance and practices of labs is necessary for a more accurate estimation.

Bigger and Better? Representativeness of the Influenza A Surveillance Using One Consolidated Clinical Microbiology Laboratory Data Set as Compared to the Belgian Sentinel Network of Laboratories

Infectious diseases remain a serious public health concern globally, while the need for reliable and representative surveillance systems remains as acute as ever. The public health surveillance of infectious diseases uses reported positive results from sentinel clinical laboratories or laboratory networks, to survey the presence of specific microbial agents known to constitute a threat to public health in a given population. This monitoring activity is commonly based on a representative fraction of the microbiology laboratories nationally reporting to a single central reference point. However, in recent years a number of clinical microbiology laboratories (CML) have undergone a process of consolidation involving a shift toward laboratory amalgamation and closer real-time informational linkage. This report aims to investigate whether such merging activities might have a potential impact on infectious diseases surveillance. Influenza data was used from Belgian public health surveillance 2014–2017, to evaluate whether national infection trends could be estimated equally as effectively from only just one centralized CML serving the wider Brussels area (LHUB-ULB). The overall comparison reveals that there is a close correlation and representativeness of the LHUB-ULB data to the national and international data for the same time periods, both on epidemiological and molecular grounds. Notably, the effectiveness of the LHUB-ULB surveillance remains partially subject to local regional variations. A subset of the Influenza samples had their whole genome sequenced so that the observed epidemiological trends could be correlated to molecular observations from the same period, as an added-value proposition. These results illustrate that the real-time integration of high-throughput whole genome sequencing platforms available in consolidated CMLs into the public health surveillance system is not only credible but also advantageous to use for future surveillance and prediction purposes. This can be most effective when implemented for automatic detection systems that might include multiple layers of information and timely implementation of control strategies.

Control of Infectious Diseases in the Era of European Clinical Microbiology Laboratory Consolidation: New Challenges and Opportunities for the Patient and for Public Health Surveillance

Many new innovative diagnostic approaches have been made available during the last 10 years with major impact on patient care and public health surveillance. In parallel, to enhance the cost-effectiveness of the clinical microbiology laboratories (CMLs), European laboratory professionals have streamlined their organization leading to amalgamation of activities and restructuring of their professional relationships with clinicians and public health specialists. Through this consolidation process, an operational model has emerged that combines large centralized clinical laboratories performing most tests on one high-throughput analytical platform connected to several distal laboratories dealing locally with urgent analyses at near point of care. The centralization of diagnostic services over a large geographical region has given rise to the concept of regional-scale "microbiology laboratories network." Although the volume-driven cost savings associated with such laboratory networks seem self-evident, the consequence(s) for the quality of patient care and infectious disease surveillance and control remain less obvious. In this article, we describe the range of opportunities that the changing landscape of CMLs in Europe can contribute toward improving the quality of patient care but also the early detection and enhanced surveillance of public health threats caused by infectious diseases. The success of this transformation of health services is reliant on the appropriate preparation in terms of staff, skills, and processes that would be inclusive of stakeholders. In addition, rigorous metrics are needed to set out more concrete laboratory service performance objectives and assess the expected benefits to society in terms of saving lives and preventing diseases.

Burden of salmonellosis, campylobacteriosis and listeriosis: a time series analysis, Belgium, 2012 to 2020

Salmonellosis, campylobacteriosis and listeriosis are food-borne diseases. We estimated and forecasted the number of cases of these three diseases in Belgium from 2012 to 2020, and calculated the corresponding number of disability-adjusted life years (DALYs). The salmonellosis time series was fitted with a Bai and Perron two-breakpoint model, while a dynamic linear model was used for campylobacteriosis and a Poisson autoregressive model for listeriosis. The average monthly number of cases of salmonellosis was 264 (standard deviation (SD): 86) in 2012 and predicted to be 212 (SD: 87) in 2020; campylobacteriosis case numbers were 633 (SD: 81) and 1,081 (SD: 311); listeriosis case numbers were 5 (SD: 2) in 2012 and 6 (SD: 3) in 2014. After applying correction factors, the estimated DALYs for salmonellosis were 102 (95% uncertainty interval (UI): 8-376) in 2012 and predicted to be 82 (95% UI: 6-310) in 2020; campylobacteriosis DALYs were 1,019 (95% UI: 137-3,181) and 1,736 (95% UI: 178-5,874); listeriosis DALYs were 208 (95% UI: 192-226) in 2012 and 252 (95% UI: 200-307) in 2014. New actions are needed to reduce the risk of food-borne infection with Campylobacter spp. because campylobacteriosis incidence may almost double through 2020.

Surveillance of Infectious Diseases by the Sentinel Laboratory Network in Belgium: 30 Years of Continuous Improvement

In 1983 the sentinel laboratory network was established because of the need to describe the epidemiological evolution of infectious diseases. During the study period of 30 years (1983-2013), microbiology laboratories reported on weekly basis the laboratory diagnosed cases for a selection of infectious diseases. This resulted in a large longitudinal laboratory based database allowing to provide trends over time and distribution by person and place. During this period, adaptations to data collection were made due to changes in diagnostic methods and public health priorities, introduction and application of digital revolution, and multiple reorganizations of the laboratories. Since the surveillance network is dynamic, it necessitates a continuous evaluation to ensure that, over time, it continues to be representative of the general epidemiological trends in the country. Secondly the aim is to examine the robustness and stability of this surveillance system. Here we demonstrated that the flexibility of the data collection methodology by the sentinel laboratory network is unique and that adaptations do not affect the capacity of the system to follow trends. Therefore, the surveillance by this network is representative of the current epidemiological situation in Belgium. To our knowledge, no such surveillance network with such a long-term follow-up and demonstrated stability for multiple infectious diseases in the general population was earlier described. Furthermore, expected trends due to the implementation of vaccination or other events were accurately detected. The collected data obtained from this network allows interesting comparisons with other national and international information sources.