Multilocus Variable-Number Tandem-Repeat Analysis as an Investigation Tool in Cryptosporidium parvum Outbreaks in Finland and Sweden in 2022

<i>Cryptosporidium</i> is a significant cause of foodborne outbreaks. The 60 kDa glycoprotein gene (<i>gp60</i>) is most often used for subtyping <i>Cryptosporidium</i> species but is not always sufficient for defining clusters and infections sources. The Multilocus Variable-Number Tandem-Repeat Analysis (MLVA) scheme has been developed to better differentiate between subtypes. A cryptosporidiosis outbreak, with 35 cases, was detected in Finland in September 2022. At the same time, in Sweden, three cryptosporidiosis outbreaks, with 107 cases, were detected, leading to international collaboration. In both countries, salad mixes were suspected as being the outbreak source. In the Finnish outbreak, the suspected salad mixes were produced in Sweden. In the Swedish outbreaks, salad mixes from two different producers were suspected. Twenty-nine patient samples which were positive for <i>Cryptosporidium parvum</i> (11 from Finland and 18 from Sweden) were sent for MLVA. The Finnish outbreak samples had different <i>gp60</i> subtypes and MLVA profiles compared to the Swedish samples. In our investigation, MLVA differentiated <i>C. parvum</i> subtypes in more detail than <i>gp60</i> typing. MLVA suggested no connection between the Finnish and Swedish outbreaks. A traceback investigation supported this conclusion. To detect outbreaks and identify infection sources, the timely subtyping of patient samples is crucial and should be implemented in routine surveillance and outbreak investigations.