Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends

Karanth, Shraddha; Patel, Jitendra; Shirmohammadi, Adel; Pradhan, Abani K.

doi:10.1016/j.crfs.2023.100525

Current Research in Food Science

2023

DOI: 10.1016/j.crfs.2023.100525

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Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends

Shraddha Karanth

Jitendra Patel

Adel Shirmohammadi

et al.

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Cited by 2 publications

References 48 publications

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Harnessing artificial intelligence in microbial food safety: global progress and implications in the ASEAN region

Panaligan,

Sy,

Sarza

2024

Int J of Food Sci Tech

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SummaryFood safety remains one of the major concerns in ASEAN, with many of the recent developmental plans and published policies in the region being focused on the topic. Most recent WHO data indicate that over 90% of the food safety burden in ASEAN is due to microbial foodborne diseases. However, conventional systems for controlling FBDs are resource‐intensive and require significant infrastructure which may not yet be present in ASEAN. Prior work on the use of Artificial intelligence (AI) in food safety application has shown its potential to reduce costs and increase efficiency. However, there remains a paucity in such research specific for the ASEAN region. In this review, the state of microbial food safety and the unique challenges in the ASEAN region are presented. The global state‐of‐the‐art of microbial food safety applications of AI are presented and possible steps for its adaptation to the ASEAN context are then discussed.

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Harnessing artificial intelligence in microbial food safety: global progress and implications in the ASEAN region

Panaligan,

Sy,

Sarza

2024

Int J of Food Sci Tech

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Salmonella and Salmonellosis: An Update on Public Health Implications and Control Strategies

Galán-Relaño,

Valero Díaz,

Huerta Lorenzo

et al. 2023

Animals

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Salmonellosis is globally recognized as one of the leading causes of acute human bacterial gastroenteritis resulting from the consumption of animal-derived products, particularly those derived from the poultry and pig industry. Salmonella spp. is generally associated with self-limiting gastrointestinal symptoms, lasting between 2 and 7 days, which can vary from mild to severe. The bacteria can also spread in the bloodstream, causing sepsis and requiring effective antimicrobial therapy; however, sepsis rarely occurs. Salmonellosis control strategies are based on two fundamental aspects: (a) the reduction of prevalence levels in animals by means of health, biosecurity, or food strategies and (b) protection against infection in humans. At the food chain level, the prevention of salmonellosis requires a comprehensive approach at farm, manufacturing, distribution, and consumer levels. Proper handling of food, avoiding cross-contamination, and thorough cooking can reduce the risk and ensure the safety of food. Efforts to reduce transmission of Salmonella by food and other routes must be implemented using a One Health approach. Therefore, in this review we provide an update on Salmonella, one of the main zoonotic pathogens, emphasizing its relationship with animal and public health. We carry out a review on different topics about Salmonella and salmonellosis, with a special emphasis on epidemiology and public health, microbial behavior along the food chain, predictive microbiology principles, antimicrobial resistance, and control strategies.

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Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends

Cited by 2 publications

References 48 publications

Harnessing artificial intelligence in microbial food safety: global progress and implications in the ASEAN region

Harnessing artificial intelligence in microbial food safety: global progress and implications in the ASEAN region

Salmonella and Salmonellosis: An Update on Public Health Implications and Control Strategies

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