What question did this study set out to answer?

The aim was to determine if using finetype data could enhance the detection of clusters of invasive meningococcal disease serogroup B.

April 8, 2026Epidemiology and Infection0 citationsOpen Access

Invasive meningococcal B disease: spatiotemporal cluster identification using finetype data, The Netherlands, 2005-2023

MBMarta BertranNational Institute for Public Health and the Environment JKJan van de KassteeleNational Institute for Public Health and the Environment LVLinda J. VisserNational Institute for Public Health and the Environment

Key Points

The aim was to determine if using finetype data could enhance the detection of clusters of invasive meningococcal disease serogroup B.
Analyzed national surveillance data of IMD-B cases from 2005 to 2023
Calculated expected baselines for finetypes using a generalized linear model
Applied Poisson scan-statistics via SaTScan TM to identify clusters
Compared results with epidemiological and cgMLST data
Identified 42 spatiotemporal clusters across 37 finetypes, comprising 132 cases (8%)
Most clusters were small, with a median size of 2 cases
High sensitivity was shown, as all 14 epidemiologically linked cases were captured in detected clusters
Strain diversity was high, and 68% of finetypes were unique.

Abstract

This study assessed whether systematically using finetype data in national surveillance of invasive meningococcal disease serogroup B (IMD-B) in the Netherlands could improve cluster detection in order to prevent further cases through public health actions.We analyzed 2005-2023 data, including 1642 IMD-B cases (95%; N=1729) with complete finetype and municipality information.Using a generalized linear model, we calculated expected baselines for each finetype including temporal trends.Using SaTScan TM , we applied Poisson scan-statistics with a 365-day window to identify spatiotemporal clusters, comparing results to epidemiological and core-genome multi locus sequence typing (cgMLST) data.Of 453 finetypes, 308 (68%) occurred once; diversity was high (Gini-Simpson index 0.96).We identified 42 spatiotemporal clusters across 37 finetypes, comprising 132 cases (8%), with a median cluster size of two (range 2-21) and duration of 45 days (range 6-356).Between zero and five clusters were detected yearly.Among 18 cases with known epidemiological links, 14 (78%) were within detected spatiotemporal clusters.CgMLST data from eight clusters supported some clusters but rejected others.Systematic cluster detection using finetype could reveal missed epidemiological links, potentially enabling public health action.However, its impact in preventing additional IMD-B cases is likely limited due to small cluster sizes, though, meaningful given the severity of IMD-B.Simple finetype mapping may provide a resource-efficient alternative to SaTScan TM .Key results: Outline your key results and their importance in 3-5 short bullet points Of 1642 IMD-B cases with complete finetype, there were 453 distinct finetypes, with 68% occurring only once. Strain diversity was high, with a 4% (annual range 3-9%) probability that two random cases shared the same finetype. Using SaTScan TM , we detected 42 spatiotemporal clusters across 37 finetypes, accounting for 8% of cases, but most clusters were small (median size 2). Among 14 case-pairs present in the IMD-B data with confirmed epidemiological links, all 14 were captured within clusters detected by SaTScan TM , indicating high sensitivity. Systematic cluster detection using finetype data is unlikely to prevent many additional cases due to small cluster sizes, but may help prioritize clusters for further epidemiological and/or genomic investigation, with simple finetype mapping offering a practical alternative to SaTScan TM .

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