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Background:  Human parainfluenza viruses (HPIVs) are significant causes of both upper and lower respiratory tract infections with type 3 (HPIV3) causing the most severe disease in the immunocompromised cohorts.  The objective of this study was to analyse the epidemiological nature of a cluster of cases of HPIV3 in a pediatric oncology unit of a major teaching hospital.    Methods:  In order to determine whether the activity observed represented a deviation from the norm, seasonal trends of HPIV3 in the surrounding geographical area as well as on the ward in question were analysed.  The genetic link between cases was established by the phylogenetic analysis of the non-coding hypervariable region between the M (Matrix) and F (fusion) genes of HPIV3. The 15 cases involved and 15 unrelated cases were sequenced.  Transmission routes were subsequently inferred and visualized using Konstanz Information Miner (KNIME) 3.3.2.    Results:  Of the 15 cases identified, 14 were attributed to a point source outbreak. Two out of 14 outbreak cases were found to differ by a single mutation A182C. The outbreak strain was also seen in 1 out of 15 unrelated cases, indicating that it was introduced from the community. Transmission modeling was not able to link all the cases and establish a conclusive chain of transmission. No staff were tested during the outbreak period. No deaths occurred as a result of the outbreak.    Conclusion:  A point source outbreak of HPIV3 was recognized  post factum  on an oncology pediatric unit in a major teaching hospital. This raised concern about the possibility of a future more serious outbreak. Weaknesses in existing systems were identified and a new dedicated respiratory virus monitoring system introduced.  Pediatric oncology units require sophisticated systems for early identification of potentially life-threatening viral outbreaks.

wellcome open research

Unrecognised Outbreak: Human parainfluenza virus infections in a pediatric oncology unit. A new diagnostic PCR and virus monitoring system may allow early detection of future outbreaks