High fidelity wastewater surveillance as an early warning tool for diphtheria in the German Ruhr metropolitan area

Diphtheria is re-emerging as a public health concern in Europe, with recent fatalities underlining the need for strengthened surveillance. In highly vaccinated populations, limited clinical suspicion and reduced routine testing can obscure low-level circulation of toxigenic strains, increasing the risk of silent spread. In addition to classical Corynebacterium diphtheriae infections, the potential mobilization of the diphtheria toxin (tox) gene within and possibly beyond different Corynebacterium species represents a growing threat.

We developed a high-fidelity wastewater-based surveillance approach capable of detecting tox genes as an early warning system to complement clinical and laboratory-based monitoring.

During routine metagenomic surveillance, including weekly monitoring of the local wastewater treatment plant, screening with a tox-specific Hidden Markov Model (HMM) detected tox signals in 18 of 160 environmental samples. Technical and sample-availability constraints allowed PCR confirmation of 15 HMM-positive samples, and 14 of these PCR products were confirmed by amplicon sequencing. One detection coincided spatially and temporally with a tox-positive Corynebacterium clinical case: wastewater from the hospital ward and downstream treatment plant was positive that week and negative the following week. No corresponding clinical isolates were identified for the other wastewater signals. Although not conclusive, this concordance supports alerting clinicians and public-health authorities when tox is detected in wastewater.