Salmonella Statistics from CDC

This information is sourced from the CDC that lists every identified and named Salmonella Serotype (culture confirmed and partially serotyped) between 2006-2016. While there are over 2,500 serovars, CDC only identified names for 1,020 of them. Below is a summary that reflects the number of illnesses associated with each in this timeframe. To find the CDC document online the title is “National Enteric Disease Surveillance: Salmonella Annual Report, 2016”.

Number of serotypes with 1 case listed – 302
Number of serotypes with 2 cases listed – 108
Number of serotypes with 3 cases listed – 78
Number of serotypes with 4 cases listed – 65
Number of serotypes with 5 cases listed – 42
Number of serotypes with 6-10 cases listed – 101 – This is still an average of only .6-1 case per year
Total – 696

Consideration: With only 1-10 cases listed over a 10 year span one can argue that these seroytypes can’t be, beyond a reasonable doubt, confirmed as the sole cause of illness. Most likely the carriers were otherwise ill and, in searching to identify another disease process these serovars of salmonella were found but were likely not causing illness.

Number of serotypes with 11-20 cases listed – 76 – This is an average of 1.1-2 cases per year
Number of serotypes with 21-100 cases listed – 123 – This is an average of 2-10 cases per year
Number of serotypes with 101-500 cases listed – 62 – This is an average of 10.1-50 cases per year
SUMMARY –
Number of serotypes with less than 1,000 infections in 10 years is 957 out of 1,020.

Number of serotypes with 500-10,000 cases listed – 56 – This is an average of 50.1-1,000 cases per year
CDC considers these of minor concern as they, like the rest listed previously, are not monitored.

Number of serotypes in excess of 10,000 cases listed -8 – This is an average of 1,007-8,330 cases per year
These 8 serotypes are monitored by the CDC.

Interestingly, Salmonella outbreaks are consistently seasonal, being the least likely to cause infection in February, most likely in August. https://www.cdc.gov/nationalsurveillance/data/salm2016/Figure4.xlsx

This list summarizes the top 47 most infectious strains in order of most virulent to least:

1) Enteritidis – 83,303 cases

2) Typhimurium – 63,773 cases

3) Newport – 47,481 cases

4) Javiana – 25,955 cases

5) 4,[5],12:i:- – 18,189 cases

6) Heidelberg – 13,627 cases

7) Montevideo – 11,495 cases

8) Muenchen – 10,379 cases

9) Infantis – 10,077 cases (2012 = 1,106, Diamond Pet Food Recall was 49 of those – Therefore DRY pet food contributed to 0.0048% of cases)

10) Saintpaul – 9,799 cases

11) Oranienburg – 8,012 cases

12) Braenderup – 7,878 cases

13) Thompson – 6,332 cases

14) Mississippi – 5,711 cases

15) Typhi – 4,788 cases

16) Agona – 4,685 cases

17) Paratyphi B var. L(+) tartrate + – 4,486 cases

18) Bareilly – 4,210 cases

19) Poona – 3,844 cases

20) O:4 – 3,547 cases

21) Berta – 3,038 cases

22) Schwarzengrund – 2,934 cases (2007 = 300 infection, Diamond Pet Food Recall was 62 of those) (Mars Pet Care caused CDC regulated outbreak in humans between 2006-2008 of 79. Therefore DRY pet food contributed to 0.048% of cases)

23) Anatum – 2,872 cases

24) Hadar – 2,601 cases

25) Litchfield – 2,499 cases

26) Stanley – 2,370 cases

27) Hartford – 2,293 cases

28) Mbandaka – 2,284 cases

29) 4, [5], 12:b:- – 2,275 cases

30) Unspecified – 2,210 cases

31) Sandiego – 1,982 cases

32) Panama – 1,980 cases

33) Norwich – 1,935 cases

34) 13,23:b:- 1,921 cases

35) O:7 – 1,203 cases

36) Rubislaw – 1,757 cases

38) Paratyphi A – 1,716 cases

39) Senftenberg – 1,678 cases

40) Dublin – 1,388 cases

41) Tennessee – 1,326 cases

42) Give – 1,309 cases

43) Derby – 1,249 cases

44) O:9 – 1,229 cases

45) Miami – 1,203 cases

46) Kentucky – 1,026 cases

47) Adelaide – 1,001 cases

Salmonella Reading was blamed for a raw pet food related illness in humans. However, no legal action was ever taken in this instance, implying that this link could never be definitively made. In total, Salmonella Reading has been associated with 858 illnesses in the 10 year span, making it an uncommon perpetrator in the world of Salmonella and the primary listed source of Salmonella Reading is pre-cut melons, not meat.
Incidence are as follows:
2006 – 50 cases
2007 – 57 cases
2008 – 46 cases
2009 – 53 cases
2010 – 33 cases
2011 – 42 cases
2012 – 58 cases
2013 – 55 cases
2014 – 104 cases
2015 – 139 cases
2016 – 221 cases

Surveillance for Foodborne Disease Outbreaks United States Annual Reports are available to show CDC indicated sources of pathogenic infections in humans each year. 2014 (which is the most current summarized document as of 12-2018) states the following:

1) From over 13,000 cases and 864 CDC regulated outbreaks only 21 recalls were implemented.

2) Sources of outbreaks:

1) Restaurants – 65% of outbreaks and 44% of illnesses

2) Catering and Banquet – 12% of outbreaks and 29% of illnesses

3) Private Home – 12% of outbreaks and 7% of illnesses

4) Institutional Location – 4% of outbreaks and 13% of illnesses

5) Other locations (Grocery, Farm/Dairy, Fair/Festival) – 4% of outbreaks, 4% of illnesses

6) Hospital/Nursing Homes – 1% of outbreaks, 1% of illnesses

7) Private location (place of worship) – 2% of outbreaks, 3% of illnesses

Pet Food is not listed

Most common food causes:

1) Seeded vegetables – 16%

2) Fish – 21%

3) Chicken ~ 12%

4) Diary – 10%

5) Beef (comprising 20% of recalls (not outbreaks) and only 20% of those were from Salmonella)

3) Salmonella accounts for 30% of all pathogen infections in the United States

Click to access foodborne-outbreaks-annual-report-2014-508.pdf

These are the states with the highest incidence of Salmonella: https://www.statista.com/statistics/379025/us-salmonella-rate-by-state/

One thought on “Salmonella Statistics from CDC

  1. Not sure how you juggle all those numbers without your brain exploding My only gift is noticing that at the end of the article, “dairy” is spelled as “diary.” Pretty sure you meant dairy? Lol

    Sent from my iPhone

    >

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s