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Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis - New York City, May-June 2019.
MMWR Morb Mortal Wkly Rep. 2020 Jul 03; 69(26):815-819.MM

Abstract

In May 2019, the New York City Department of Health and Mental Hygiene (NYCDOHMH) detected an unusual cluster of five salmonellosis patients via automated spatiotemporal analysis of notifiable diseases using free SaTScan software (1). Within 1 day of cluster detection, graduate student interviewers determined that three of the patients had eaten prepared food from the same grocery store (establishment A) located inside the cluster area. NYCDOHMH initiated an investigation to identify additional cases, establish the cause, and provide control recommendations. Overall, 15 New York City (NYC) residents with laboratory-diagnosed salmonellosis who reported eating food from establishment A were identified. The most commonly consumed food item was chicken, reported by 10 patients. All 11 clinical isolates available were serotyped as Salmonella Blockley, sequenced, and analyzed by core genome multilocus sequence typing; isolates had a median difference of zero alleles. Environmental assessments revealed food not held at the proper temperature, food not cooled properly, and potential cross-contamination during chicken preparation. Elevated fecal coliform counts were found in two of four ready-to-eat food samples collected from establishment A, and Bacillus cereus was detected in three. The outbreak strain of Salmonella was isolated from one patient's leftover chicken. Establishing automated spatiotemporal cluster detection analyses for salmonellosis and other reportable diseases could aid in the detection of geographically focused, community-acquired outbreaks even before laboratory subtyping results become available.

Authors

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Pub Type(s)

Journal Article

Language

eng

PubMed ID

32614808

Citation

Latash, Julia, et al. "Salmonellosis Outbreak Detected By Automated Spatiotemporal Analysis - New York City, May-June 2019." MMWR. Morbidity and Mortality Weekly Report, vol. 69, no. 26, 2020, pp. 815-819.
Latash J, Greene SK, Stavinsky F, et al. Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis - New York City, May-June 2019. MMWR Morb Mortal Wkly Rep. 2020;69(26):815-819.
Latash, J., Greene, S. K., Stavinsky, F., Li, S., McConnell, J. A., Novak, J., Rozza, T., Wu, J., Omoregie, E., Li, L., Peterson, E. R., Gutelius, B., & Reddy, V. (2020). Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis - New York City, May-June 2019. MMWR. Morbidity and Mortality Weekly Report, 69(26), 815-819. https://doi.org/10.15585/mmwr.mm6926a2
Latash J, et al. Salmonellosis Outbreak Detected By Automated Spatiotemporal Analysis - New York City, May-June 2019. MMWR Morb Mortal Wkly Rep. 2020 Jul 3;69(26):815-819. PubMed PMID: 32614808.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis - New York City, May-June 2019. AU - Latash,Julia, AU - Greene,Sharon K, AU - Stavinsky,Faina, AU - Li,Sandy, AU - McConnell,Jennifer A, AU - Novak,John, AU - Rozza,Teresa, AU - Wu,Jing, AU - Omoregie,Enoma, AU - Li,Lan, AU - Peterson,Eric R, AU - Gutelius,Bruce, AU - Reddy,Vasudha, Y1 - 2020/07/03/ PY - 2020/7/3/entrez PY - 2020/7/3/pubmed PY - 2020/7/7/medline SP - 815 EP - 819 JF - MMWR. Morbidity and mortality weekly report JO - MMWR Morb. Mortal. Wkly. Rep. VL - 69 IS - 26 N2 - In May 2019, the New York City Department of Health and Mental Hygiene (NYCDOHMH) detected an unusual cluster of five salmonellosis patients via automated spatiotemporal analysis of notifiable diseases using free SaTScan software (1). Within 1 day of cluster detection, graduate student interviewers determined that three of the patients had eaten prepared food from the same grocery store (establishment A) located inside the cluster area. NYCDOHMH initiated an investigation to identify additional cases, establish the cause, and provide control recommendations. Overall, 15 New York City (NYC) residents with laboratory-diagnosed salmonellosis who reported eating food from establishment A were identified. The most commonly consumed food item was chicken, reported by 10 patients. All 11 clinical isolates available were serotyped as Salmonella Blockley, sequenced, and analyzed by core genome multilocus sequence typing; isolates had a median difference of zero alleles. Environmental assessments revealed food not held at the proper temperature, food not cooled properly, and potential cross-contamination during chicken preparation. Elevated fecal coliform counts were found in two of four ready-to-eat food samples collected from establishment A, and Bacillus cereus was detected in three. The outbreak strain of Salmonella was isolated from one patient's leftover chicken. Establishing automated spatiotemporal cluster detection analyses for salmonellosis and other reportable diseases could aid in the detection of geographically focused, community-acquired outbreaks even before laboratory subtyping results become available. SN - 1545-861X UR - https://www.unboundmedicine.com/medline/citation/32614808/Salmonellosis_Outbreak_Detected_by_Automated_Spatiotemporal_Analysis_-_New_York_City,_May-June_2019 L2 - https://doi.org/10.15585/mmwr.mm6926a2 DB - PRIME DP - Unbound Medicine ER -