One-third of survey respondents in low- and middle-income countries do not use whole genome sequencing, according to one study.

Only 8% reported using WGS routinely and in real time, highlighting minimal adoption of the technology for foodborne disease surveillance outside of the US, Canada and Europe .

The main barriers to implementation were lack of funding, expertise and training gaps, especially for data analysis and interpretation, according to the study published in the journal Pathogens and Foodborne Diseases.

PulseNet International (PNI) carried out the study to identify the challenges countries were facing regarding WGS. The group consists of national, regional and sub-regional laboratories and laboratory networks in 88 countries that track foodborne diseases globally.

Sequencing statistics
Forty-one institutions from 33 of 54 countries in Africa, Asia-Pacific, Latin America, the Caribbean and the Middle East responded to the survey in early 2020. Two-thirds of respondents were national laboratories of reference, including those from national public health, agriculture, and food safety authorities.

One in five use WGS for outbreak investigations after being identified by other means and 28% use it only for research and pilot studies.

Of the labs that have not implemented WGS, 40% outsource sequencing to another institution, but plan to adopt WGS in-house in or after 2022.

Twenty percent of labs do not use WGS for foodborne disease surveillance, although sequencing is done on-site for other purposes. The majority of laboratories that use WGS for post-outbreak investigations or for pilot studies perform the sequencing at their own facility.

In 2019, only 5% of laboratories sequenced more than 1,000 isolates. Although 66% sequenced 0 to 100 isolates that year, the remaining labs sequenced between 100 and 1000 isolates. The majority of tests were performed on foodborne pathogens such as Salmonella, E. coli, Shigella, Vibrio, Campylobacter and Listeria.

Data analysis issues
The capacity for generating sequences is generally greater than that for analyzing or interpreting the data. Computing and bioinformatics capacity was found to be generally weak.

Forty-four percent of respondents said their labs’ ability and expertise to use, develop, optimize, and troubleshoot bioinformatics analysis protocols for WGS data was weak or non-existent.

The majority of laboratories do not have established guidelines for interpreting WGS data such as allele counts or SNP differences for outbreak detection.

End-user knowledge for effective use of WGS data is low. Only a third of laboratories said the level of knowledge and ability to use WGS data for public health decision-making was good or excellent.

Dissemination of WGS results is largely done through traditional methods and data sharing is limited. Traditional methods including Excel spreadsheets, hard copies including fax, and in person or telephone have dominated modern methods such as laboratory information management systems and internal websites.

More than half of the laboratories do not exchange sequencing data with external partners in their country and only half of the respondents sometimes make their sequencing data publicly available.

Half of the labs believe that the PNI should focus on training, especially in the analysis of WGS data, and that access to globally standardized and validated analysis tools and pipelines is essential to progress towards global foodborne disease surveillance using WGS.

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