National Enteric Surveillance Program (NESP) annual summary 2020

Including serotype tables for 2020, NESP and National Microbiology Laboratory (NML)

Prepared by:
The National Microbiology Laboratory (NML), the Centre for Foodborne, Environmental and Zoonotic Infectious Diseases (CFEZID), Public Health Agency of Canada, and the provincial public health laboratories

Acknowledgements

National Enteric Surveillance Program (NESP) coordination team:

• Celine Nadon, Chief, Surveillance, Outbreak Detection and Response Section, Division of Enteric Diseases, National Microbiology Laboratory (NML)
• Sara Christianson, Chief, Diagnostic and Reference Services Section, Division of Enteric Diseases, NML
• Lori Lozinski, Surveillance Clerk, Division of Enteric Diseases, NML
• Kate Thomas, Manager, Foodborne Disease and AMR Surveillance Division (FDASD), Centre for Foodborne, Environmental and Zoonotic Infectious Diseases (CFEZID)
• Symron Bansal, Epidemiologist, FDASD, CFEZID
• Lauren Sherk, Epidemiologist, FDASD, CFEZID

Provincial laboratory partners:

• BC Centre for Disease Control Public Health Laboratory
• Alberta Precision Laboratories
• Saskatchewan Disease Control Laboratory
• Cadham Provincial Microbiology Laboratory (Manitoba)
• Public Health Ontario
• Laboratoire de santé publique du Québec (LSPQ)
• New Brunswick Public Health Laboratories
• Nova Scotia Public Health Laboratories
• Prince Edward Island Public Health Laboratories
• Newfoundland and Labrador Public Health Laboratory

Provincial/territorial epidemiology partners:

• British Columbia Centre for Disease Control
• Alberta Health
• Saskatchewan Ministry of Health
• Manitoba Health
• Public Health Ontario
• Ministère de la santé et des services sociaux du Québec
• New Brunswick Health
• Nova Scotia Department of Health and Wellness
• Prince Edward Island Department of Health and Wellness
• Newfoundland and Labrador Department of Health and Community Services
• Yukon Health and Social Services
• Northwest Territories Department Health and Social Services
• Nunavut Health and Social Services

Overview

The National Enteric Surveillance Program (NESP) is a collaboration between the Public Health Agency of Canada (PHAC) and the provincial public health laboratories. Through NESP, weekly analysis and reporting is conducted for 14 different organisms causing enteric illness, including 10 of which are nationally notifiable. The data derived from this surveillance system supports detection of multi-provincial clusters and outbreaks, guides public health interventions, and are designed to integrate with national and international efforts to limit the transmission of enteric diseases.

In 2020, a total of 10,000 isolate results were reported; a 35% decrease from the average number of notifications received in the previous five years (15,340). This decrease is likely due, in part, to the impacts of the COVID-19 pandemic. Salmonella spp. continues to be the most common organism identified with 4,919 notifications provided in 2020, representing 49% of all isolates reported. As in previous years, Salmonella Enteritidis (29%) and S. Typhimurium (10%), remain among the top 3 serotypes of all Salmonella reported in 2020. S. Newport (14%) was among the top 3 serotypes in 2020 due to a multi-jurisdictional outbreak in the summer of 2020. Collectively, these three serotypes represent 53% of all Salmonella serotypes identified.

The incidence rate of Shiga toxigenic Escherichia coli (STEC) O157 decreased compared to a relatively stable rate from 2010 to 2019, with 0.62 cases per 100,000 population reported in 2020. A decrease was also observed in the incidence rate of non-O157 STEC isolates in 2020 (0.84 cases per 100,000 population) compared to a high of 1.58 cases per 100,000 population in 2019. This is the fourth consecutive year where more non-O157 STEC isolates were reported than O157 isolates.

The incidence rate of invasive listeriosis in 2020 (0.42 per 100,000 population) is similar to what has been seen in the past 2 years. Over the 8-year period Hepatitis A has been under national surveillance, the highest incidence was reported to the program in 2019 (1.55 cases per 100,000 population) and 2020 saw a rate of 0.67 cases per 100,000 population. In contrast to previous years in which Shigella sonnei constituted the majority of Shigella species reported, in 2020 Shigella flexneri represented 57% of all Shigella reported and the rate of Shigella flexneri (0.59 per 100,000 population) was also higher than the rate of Shigella sonnei (0.40 per 100,000 population). Trends for all other Shigella species were lower in 2020 compared to previous years.

Table of contents

• Acknowledgements
• Overview
• About the National Enteric Surveillance Program (NESP)
• Laboratory-confirmed Isolate Counts & Incidence Rates
• Salmonella
• Escherichia coli
• Listeria monocytogenes
• Shigella
• Hepatitis A

Tables

• Table 1. Multi-jurisdictional Outbreak Investigations in 2020
• Table 2. Number of isolates reported to NESP by major organism group per province or territory, 2020
• Table 3. Annual national totals and rates (per 100,000 population) for enteric pathogens and organism groups reported to NESP, 2015 to 2020
• Table 4. Annual rates (per 100,000 population) of infection per province and territory for select groups of pathogens routinely reported to NESP, 2020
• Table 5. Number of isolates reported to NESP per province and territory for the ten most commonly reported Salmonella serotypes, 2020
• Table 6. National total counts (overall rank) for the ten most commonly reported Salmonella serotypes to NESP, 2015 to 2020

Figures

• Figure 1. Proportion of Salmonella serotypes causing human illness as reported to NESP, 2020 (n= 4,919)
• Figure 2. Annual counts between 2011 to 2020 for the top five non-typhoidal Salmonella serotypes reported to NESP in 2020
• Figure 3. Relative incidence rates (per 100,000 population) of S. Enteritidis, S. Newport, S. Typhimurium, and other Salmonella serotypes reported to NESP by year, 2016 to 2020 compared to the 2011 to 2015 baseline period
• Figure 4. Incidence rates (per 100,000 population) of E. coli O157, non-O157 STEC, and other non-typed E. coli reported to NESP, 1997 to 2020
• Figure 5. Distribution of non-O157 STEC serotypes reported to NESP in 2020 (n=513)
• Figure 6. Incidence rate (per 100,000 population) of the top five serotyped non-O157 STEC serotypes reported to NESP, 2011 to 2020
• Figure 7. Incidence rate (per 100,000 population) of invasive listeriosis reported to NESP by province, 2011 to 2020
• Figure 8. Incidence rate (per 100,000 population) of Shigella species reported to NESP, 1997 to 2020
• Figure 9. National and provincial incidence rate (per 100,000 population) of Hepatitis A reported to NESP, 2013 to 2020

Appendices

• Appendix A. Comparison of national totals, incidence per 100,000 population and proportion captured between the Canadian Notifiable Disease Surveillance System (CNDSS) and the National Enteric Surveillance Program (NESP) for enteric diseases, 2019
• Appendix B. Species and serotype data reported to NESP by province and territory, 2020
  • Table 7. Campylobacter
  • Table 8. E. coli
  • Table 9. Listeria monocytogenes
  • Table 10. Salmonella
  • Table 11. Shigella
  • Table 12. Vibrio
  • Table 13. Yersinia
  • Table 14. Parasites
  • Table 15. Viruses
• Appendix C. Impacts of COVID-19. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019 for select pathogens
  • Figure 10. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, all Salmonella serotypes, overlaid with 2020 Canadian case counts of COVID-19
  • Figure 11. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, all Salmonella serotypes excluding S. Enteritidis, overlaid with 2020 Canadian case counts of COVID-19
  • Figure 12. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, S. Enteritidis, overlaid with 2020 Canadian case counts of COVID-19
  • Figure 13. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, E. coli O157, overlaid with 2020 Canadian case counts of COVID-19
  • Figure 14. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, non-O157 STEC, overlaid with 2020 Canadian case counts of COVID-19
  • Figure 15. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, Listeria monocytogenes, overlaid with 2020 Canadian case counts of COVID-19
  • Figure 16. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019, Shigella, overlaid with 2020 Canadian case counts of COVID-19

About the National Enteric Surveillance Program (NESP)

In Canada, the surveillance of enteric diseases is conducted through NESP and the Canadian Notifiable Diseases Surveillance System (CNDSS)^{Footnote 1}. NESP is jointly administered by PHAC's National Microbiology Laboratory (NML) and the Centre for Foodborne, Environmental and Zoonotic Infectious Diseases (CFEZID). Since 1997, weekly analysis and reporting on laboratory-confirmed cases of enteric illness by the provincial public health laboratories has been conducted through NESP.

NESP provides the first and most timely level of characterization (primarily species and serotype) of data critical to, and integrated with, other surveillance programs. Monitoring aggregated data allows for the rapid evaluation and response to enteric illness outbreaks. In addition, the data allows for the description of trends in pathogen subtypes and in the incidence of nationally notifiable enteric pathogens. CNDSS receives data that are collected by local health units, which is forwarded to provincial/territorial health authorities and collated by PHAC's Centre for Communicable Diseases and Infection Control (CCDIC). These data may be more representative of total numbers of annual illnesses; however, CNDSS is not designed to provide timely information required for cluster or outbreak detection. These two surveillance systems (CNDSS and NESP) are complementary in providing both epidemiological and laboratory results; however, discrepancies between them do exist. Due to the reporting protocols and requirements, CNDSS is a more reliable source of information in terms of total number of illnesses, while NESP data are more current and responsive to trends. A comparison of national case counts and incidence rates for enteric diseases is included (Appendix A).

NESP is also highly complementary to another laboratory-based surveillance system, PulseNet Canada^{Footnote 2}. Also administered by PHAC, PulseNet Canada collects high resolution data in real-time on cases of enteric diseases for the purpose of outbreak detection and response. Due to the additional testing performed (molecular or genomic subtyping), there are differences in turnaround time compared to weekly NESP data. Further, PulseNet Canada surveillance is conducted only for a subset of the organisms that are tracked by NESP.

Data collection

Isolates (or specimens) are submitted to provincial public health laboratories for testing and/or confirmation of the enteric pathogen. On a weekly basis, each provincial public health laboratory summarizes the number of enteric microorganisms isolated from human patients. The information details the genus, species and serotype (where appropriate). The 'report week' for NESP spans the period from Sunday to Saturday and is based on the date the laboratory test was completed, except for in Alberta, where it is based on the date received. Data are submitted to NML either directly (faxing or emailing), or by entering the data via the web-based application (webNESP) hosted on the Canadian Network for Public Health Intelligence (CNPHI). The information is submitted as soon as possible and no later than the second day after a weekend or holiday. An exception to this reporting scheme occurs when the isolate must be sent to another laboratory for completion of the identification. In this case, the isolate is reported at the level of typing or identification attained (e.g. Salmonella sp.) for the week in which it was sent to the reference laboratory. The NESP record is then updated when the final identification is received from the reference laboratory (e.g. report in week 35 that one "Salmonella sp." reported in week 33 has been confirmed as "S. Banana"). This updated information is submitted with the next weekly NESP report form.

All data submitted are aggregated by province and pathogen and do not contain any patient identifiers, locators, or other confidential information. NESP partners endeavor to include only the number of isolates from new cases identified at the laboratory that week, or updates to previously reported numbers. To avoid duplication, the provincial public health laboratories attempt to identify multiple, repeat, or follow-up specimens from the same individual, and consider all identical isolates from the same patient that are collected over a three month period as a single case.

Data collected for surveillance purposes are increasingly being generated using whole genome sequencing (WGS) instead of by classical microbiological methods. Most of the data collected by NESP, however, can be derived from whole genome sequence data in silico (e.g., species identification, serotype), ensuring that the over two decades of data used for NESP analyses will remain compatible with surveillance in the genomics era. Starting in 2018, portions of the data collected and analyzed by NESP will have been generated via WGS.

Data analysis and dissemination

Data analysis is conducted weekly by using an algorithm to determine if the current week case counts are significantly higher than the expected baseline. Statistical significance is based on the cumulative Poisson probability between the reported case count and the retrospective five-year median.

Results from the weekly analysis included in the "NESP Weekly Report" are disseminated to all provincial public health laboratories, at least one epidemiologist or Medical Officer of Health in each province/territory and multiple stakeholders at the federal level. Protocol allows sharing of the reports with other public health professionals who have an operational need to have this information, although, the weekly reports are not intended for public distribution. No response is required by public health professionals to the statistical elevations noted in the reports. The aim is to provide useful and timely information for those responsible for public health action.

In addition to NESP Weekly Reports, partners can perform real-time data analysis, examine trends and display their respective jurisdictions' data within webNESP. PulseNet Canada uses these data in conjunction with laboratory DNA fingerprinting data determined by pulsed-field gel electrophoresis (PFGE) and other molecular/genomic data to detect disease clusters and outbreaks. The resulting data analyses are also shared on CNPHI with provincial public health laboratories, the Canadian Food Inspection Agency (CFIA), Health Canada (HC), PHAC and provincial/territorial epidemiologists. The coordinated assessment of laboratory evidence collected through these complementary laboratory surveillance networks allows for the interpretation of clinical microbiological evidence during multi-jurisdictional epidemiologic investigations, as described in the Food-borne Illness Outbreak Response Protocol (FIORP)^{Footnote 3}.

Limitations

It should be noted that there are some inherent limitations of these data. For some organisms, the number of isolates reported is a subset of laboratory isolations and may not reflect the incidence of disease at the provincial or national level. For example, Campylobacter isolates are not routinely forwarded to provincial public health or central reference laboratories for further testing beyond genus/species characterizations, and are therefore greatly under-represented in NESP. By contrast, Salmonella and E. coli O157 isolates captured by NESP are more representative of the true incidence of disease in Canada, as the number of cases reported to CNDSS and isolates reported to NESP show a high degree of concurrence for both diseases. There may be over-reporting of organisms in NESP due to reporting of multiple specimens from a single patient, but efforts are made to minimize this occurrence. Information regarding extra-intestinal isolation sites and foreign travel are not consistently reported to NESP from all provincial public health laboratories and therefore any interpretation should be considered with caution.

In March of 2020, the COVID-19 pandemic was declared^{Footnote 4} and global public health action was taken to address it. Across Canada and within specific provinces/territories and regions various public health measures were put in place. These public health measures and the adaptations Canadians made to combat COVID-19 not only helped to reduce the transmission of COVID-19 but have also impacted other reported infectious diseases to varying degrees. Interpretation of the 2020 NESP data must be considered in light of these COVID-19 public health measures and adaptations (Appendix C).

Questions and correspondence may be forwarded via email to:

nesp-pnsme@phac-aspc.gc.ca

Laboratory-confirmed isolate counts and incidence rates

In 2020, provincial public health laboratories reported the results of 10,000 isolates of enteric pathogens to NESP, a decrease from the average number of notifications in the previous five years (15,340). The most frequently reported enteric pathogen group was Salmonella, followed by enteric viruses (Norovirus, Hepatitis A, Rotavirus and Adenovirus), and Campylobacter (Table 2). Organism isolate counts reported by province and territory in 2020 can be found in Appendix B.

Annual national incidence rates for the groups of enteric pathogens reported to NESP between 2015 and 2020 are shown in Table 3 and Appendix A. Isolates of E. coli O157 or non-O157 STEC, Listeria monocytogenes, Salmonella and Shigella are routinely forwarded to provincial public health laboratories, while isolates for Campylobacter, Yersinia, enteric parasites (Giardia, Cryptosporidium, Entamoeba histolytica/dispar and Cyclospora) and enteric viruses (Norovirus, Rotavirus and Adenovirus) are not routinely reported to the provincial public health or central reference laboratories. As such, NESP incidence rates are considered to be reflective of the true incidence rate for those routinely reported pathogens enabling the calculation of provincial and territorial incidence rates as shown in Table 4.

Salmonella

A total of 4,919 Salmonella isolates representing 196 serotypes were reported in 2020. Salmonella Enteritidis accounted for 29% of all human salmonellosis, and together with the eight remaining most common serotypes (Figure 1), they constituted 73% of all Salmonella infections reported. National, provincial and territorial case counts for Salmonella reported in 2020 are shown in Table 5 and Appendix B.

Figure 1 - Text description

Salmonella Species	Percentage of total Salmonella
Enteritidis	29%
Newport	14%
Typhimurium	10%
ssp I 4,[5],12:i:-	5%
Heidelberg	4%
Infantis	4%
Thompson	3%
Typhi	2%
Braenderup	2%
Otherfigure 1 note *	28%
Figure 1 Notes Figure 1 Note 1 Other serotypes (1,355 isolates) were divided among 187 serotypes or incomplete antigenic profiles, and 58 isolates were reported as unspecified Salmonella species. Return to figure 1 note * referrer

*Other serotypes (1,355 isolates) were divided among 187 serotypes or incomplete antigenic profiles, and 58 isolates were reported as unspecified Salmonella species.

Compared to the average number of Salmonella notifications received between 2015 and 2019 (7,299 cases), there was a 32.6% decrease observed in 2020 (4,919) likely in part due to the impacts of COVID-19 and the continued impact related to CFIA regulation implemented in April 2019 to address Salmonella in frozen raw breaded chicken products (Figure 2). While S. Enteritidis remained the most common serotype over this time period, changes were observed among the other most commonly reported Salmonella serotypes (Table 6).

Figure 2 - Text description

Salmonella serovar	Year
	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Enteritidis	2763	2117	2019	3337	3209	3433	3278	3083	2254	1422
Newport	195	153	189	224	235	198	143	192	200	693
Typhimurium	661	814	668	671	642	607	602	551	557	468
ssp I 4,[5],12:i	219	281	299	251	280	259	265	263	294	256
Heidelberg	641	1071	733	628	571	580	444	390	267	207
Other serotypes	2325	2544	2362	2739	2780	2739	2581	2821	2778	1873

In May 2017, PulseNet Canada began performing WGS on all Salmonella isolates submitted for routine laboratory-based surveillance, providing high discriminatory genomic subtype data for outbreak detection and response.

Salmonella Enteritidis

In 2020, 1,422 isolates of S. Enteritidis, 28.9% of all Salmonella submissions, were reported to NESP. The incidence rate observed in 2020 was 51.9% lower (3.7 cases per 100,000 population) relative to the 2011 to 2015 baseline period (7.7 cases per 100,000 population). A general decrease in incidence can be seen from 2016 to 2019 as well, suggesting that the rate observed in 2020 is part of an ongoing trend unrelated to the impacts of COVID-19 (Figure 3).

Figure 3 - Text description

Salmonella serovar	Year
	2011-2015	2016	2017	2018	2019	2020
Enteritidis	1	1.24	1.17	1.09	0.78	0.49
Newport	1	0.97	0.69	0.91	0.94	3.21
Typhimurium	1	0.85	0.83	0.75	0.75	0.62
Other	1	0.98	0.89	0.93	0.88	0.61

Salmonella Newport

The incidence rate of S. Newport in 2020 (1.82 per 100,000) was much higher than in 2019 (0.53 per 100,000) and compared to the baseline period (0.57 per 100,000) due to a multi-jurisdictional outbreak of S. Newport consisting of 515 cases with onset dates ranging from June 15 to August 29, 2020 (Table 1).

Salmonella Typhimurium

Compared to the 2011 to 2015 baseline period, a 26% decrease in the incidence of S. Typhimurium cases was noted in 2020 (1.97 versus 1.46 cases per 100,000 population, respectively). From 2015 to 2019, a slight decreasing trend can be seen in the incidence of S. Typhimurium (Figure 3). Although S. Typhimurium continues to rank among the top 3 most common serotypes causing human salmonellosis in Canada, it represents only 10% of all Salmonella isolates reported to NESP in 2020 (Figure 1 and Table 6).

Escherichia coli

Unless otherwise indicated, it is assumed that all the samples reported to NESP from the provinces and territories are Shiga toxigenic Escherichia coli (STEC). The 2020 rate of O157 (0.62 cases per 100,000 population) is lower than the relatively stable rates seen between 2010 to 2019, likely due to the impacts of COVID-19 (Figure 4). In 2020, three provinces reported incidence rates of E. coli O157 higher than the national reported incidence rate: Alberta (1.00 cases per 100,000 population), Manitoba (1.60 cases per 100,000 population), and British Columbia (0.72 cases per 100,000 population) (Table 4). The incidence rate of non-O157 STEC decreased in 2020 (0.84 cases per 100,000 population) from 2019 (1.58 cases per 100,000 population) likely due to the impacts of the pandemic (Figure 4). This is the fourth consecutive year where the proportion of non-O157 STEC isolates reported has exceeded the proportion of O157 isolates. It should be noted that non-O157 STECare reported less consistently than E. coli O157 to NESP and therefore any changes observed over time are a reflection in testing practices by some provincial public health laboratories. Further, 6.6% of isolates were identified using culture-independent diagnostic tests (CIDT), which are PCR-based tests used for the identification of organisms without an isolate cultured. Reflex culture of a CIDT positive sample may obtain an isolate for further sub-typing, which would be updated in NESP.

Among non-O157 STEC isolates that were serotyped, in 2020, 54% of these were represented by five serotypes: E. coli O26, E. coli O111, E. coli O121, E. coli O103, and E. coli O118 (Figure 5). In 2020, 20% of non-O157 STEC did not have additional serotype information. In 2017, a request was submitted by NML to provincial public health laboratories to report the testing method used for the identification of organisms, as the use of CIDTs are becoming more prevalent in Canada.

With the exception of E. coli O121, all of the top 5 serotypes among serotyped E. coli isolates showed a decreased rate per 100,000 population in 2020 compared to 2019, likely due to the impacts of COVID-19 (Figure 6). All E. coli serotypes, including confirmed non-O157 STEC isolates, and any other reported pathotypes are summarized in Appendix B.

Figure 4 - Text description

E. coli group	Year
	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008
E. coli O157	2.79	3.68	3.88	5.60	3.91	3.81	3.01	3.32	2.28	3.00	2.84	1.99
Non-O157 STEC	0.06	0.07	0.04	0.13	0.10	0.23	0.32	0.30	0.14	0.14	0.08	0.04
Non-Typed STEC	0.32	0.27	0.25	0.25	0.28	0.05	0.03	0.03	0.08	0.28	0.18	0.09
E. coli CIDT	0	0	0	0	0	0	0	0	0	0	0	0
Non-STEC	0	0	0	0	0	0	0	0	0	0	0	0

E. coli group	Year
	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
E. coli O157	1.57	1.19	1.40	1.40	1.35	1.29	1.06	1.15	0.95	1.15	1.06	0.62
Non-O157 STEC	0.04	0.02	0.13	0.24	0.37	0.43	0.64	0.57	0.99	1.42	1.58	0.84
Non-Typed STEC	0.21	0.19	0.15	0.18	0.13	0.10	0.05	0.01	0.01	0.04	0.01	0.04
E. coli CIDT	0	0	0	0	0	0	0	0.05	0.14	0.19	0.37	0.14
Non-STEC	0	0	0	0	0	0	0	0	0	0.15	0.87	0.53

Figure 5 - Text description

Non-O157 serotype	Percentage of total non-O157 STEC
O26	19%
O111	13%
O121	10%
O103	10%
O118	3%
Other Non-O157 STECfigure 5 note *	46%
Figure 5 Notes Figure 5 Note 1 Other serotypes (146 isolates) were divided among 36 serotypes and 63 isolates were reported as unspecified non-O157 STEC. Return to figure 5 note * referrer

*Other serotypes (146 isolates) were divided among 36 serotypes and 63 isolates were reported as unspecified non-O157 STEC.

Figure 6 - Text description

Non-O157 STEC serotype	Year
	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
O26	0.01	0.02	0.04	0.08	0.11	0.12	0.15	0.21	0.40	0.16
O111	0.01	0.01	0.02	0.06	0.04	0.02	0.06	0.09	0.25	0.11
O121	0.02	0.03	0.05	0.05	0.07	0.07	0.17	0.11	0.08	0.09
O103	0.01	0.01	0.03	0.02	0.06	0.06	0.07	0.09	0.21	0.08
O118	0	0	0.00	0.01	0.00	0.01	0.02	0.04	0.08	0.02

Listeria monocytogenes

As per the case definition for invasive listeriosis, only isolates obtained from a normally sterile site or placental/fetal tissues should be reported. A decreased number of isolates for invasive listeriosis were reported in 2020 (158) compared to 2019 (174). As there are small numbers of cases of invasive listeriosis within most jurisdictions, the magnitude of the change is greatly affected with a difference of even one case (Figure 7).

Figure 7 - Text description

Province	Year
	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
BC	0.38	0.18	0.24	0.38	0.27	0.41	0.18	0.18	0.29	0.23
AB	0.05	0.13	0.10	0.24	0.12	0.19	0.07	0.37	0.23	0.20
SK	0	0	0	0.18	0.09	0.09	0.43	0.26	0.43	0.51
MB	0.32	0.32	0.16	0.23	0.23	0.15	0	0	0.51	0.51
ON	0.41	0.33	0.31	0.33	0.45	0.68	0.35	0.52	0.52	0.45
QC	0.57	0.66	0.48	0.56	0.34	0.63	0.37	0.48	0.64	0.51
NB	0.40	0.53	1.19	0.40	0.53	0.79	0.52	0.39	0.64	0.77
NS	0.53	0.53	0.85	0.43	0.85	0.42	0.42	0.31	0.21	0.51
PEI	0	0	0.69	0.69	0.69	1.36	1.33	0.65	0	0.63
NL	0	0.19	0.19	0.19	0.19	0.38	0.38	0.19	0.19	0.38

Shigella

There were 393 isolates of Shigella reported in 2020, representing a rate of 1.03 cases per 100,000 population compared to an average of 2.11 cases per 100,000 population reported between 2015 to 2019 (Figure 8). Isolates of Shigella sonnei and Shigella flexneri comprised 38% and 57% of total notifications respectively. Overall trends for Shigella have historically been driven by the incidence of S. sonnei (0.40 cases per 100,000 population). However, the rate of S. flexneri (0.59 cases per 100,000) surpassed that of S. sonnei in 2020 (Figure 8). Among the other Shigella species, incidence trends over time have remained relatively unchanged with an incidence of 0.03 cases per 100,000 population for Shigella boydii and 0.01 cases per 100,000 population for Shigella dysenteriae observed in 2020 (Figure 8). Rates of all species of Shigella noted in Figure 8 were lower in 2020 compared to 2019, likely due to the impacts of COVID-19.

Figure 8 - Text description

Shigella group	Year
	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008
Shigella sp.	0.07	0.08	0.08	0.06	0.08	0.06	0.06	0.02	0.05	0.04	0.03	0.02
Shigella boydii	0.12	0.15	0.16	0.14	0.10	0.12	0.13	0.13	0.09	0.10	0.09	0.10
Shigella dysenteriae	0.06	0.11	0.08	0.08	0.05	0.04	0.10	0.11	0.08	0.07	0.05	0.03
Shigella flexneri	0.59	1.00	0.82	0.68	0.51	0.65	0.64	0.78	0.76	0.60	0.57	0.71
Shigella sonnei	2.41	3.07	1.73	1.83	1.49	2.82	1.66	1.00	1.62	0.81	1.19	1.19

Shigella group	Year
	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Shigella sp.	0.01	0.01	0.00	0.00	0.01	0.00	0.01	0.00	0.00	0.01	0.04	0.01
Shigella boydii	0.11	0.09	0.07	0.13	0.08	0.07	0.04	0.06	0.05	0.07	0.05	0.03
Shigella dysenteriae	0.05	0.05	0.03	0.03	0.03	0.03	0.04	0.04	0.02	0.02	0.03	0.01
Shigella flexneri	0.87	0.92	0.84	0.77	0.68	0.76	0.73	0.72	0.74	0.78	0.88	0.59
Shigella sonnei	0.84	1.11	1.56	1.92	0.97	1.06	1.24	1.42	1.10	1.24	1.20	0.40

Hepatitis A

The national incidence rate for Hepatitis A in 2020 was lower than in 2019 (0.67 cases per 100,000 population in 2020 compared to 1.55 in 2019), likely due to the impacts of COVID-19 (Figure 9). Each provincial and territorial laboratory determines whether to report a case based solely on laboratory testing, without public health follow-up. A positive IgM result could be due to false positive or recent immunization. When local public health follow up occurs it is then determined whether the case meets a confirmed case definition or not. If local public health determines it is not a case (e.g. recent immunization), this information may not always be relayed back to the laboratory, and therefore, our surveillance figures are not corrected. The increases observed in Figure 9 could be a result of change of laboratory detection methods. Conversely, since not all specimens/isolates are referred from the regional and local laboratories to the provincial public health laboratories, viruses, including Hepatitis A,are under-represented in NESP and reported case counts are not representative of the true incidence of the disease in Canada.

Figure 9 - Text description

Province / territory	Year
	2013	2014	2015	2016	2017	2018	2019	2020
National	0.62	0.59	0.51	0.65	0.79	1.08	1.55	0.67
AB	0.65	0.66	0.77	1.33	0.90	1.30	1.19	0.32
BC	0.39	0.45	0.50	0.39	0.45	0.58	0.71	0.39
MB	1.03	0.63	0.39	0.30	1.05	0.52	4.53	1.74
NB	0.53	0	0.13	0	0	0	0.64	1.28
NL	0.19	0.57	0.00	0.76	1.51	5.90	18.34	8.43
NS	0.21	0.43	0.21	1.17	0.63	0.42	2.06	1.02
ON	0.75	0.61	0.50	0.67	0.88	1.38	1.38	0.53
PE	0	0	0	0	0	0	0	1.25
QC	0.42	0.56	0.46	0.49	0.83	0.70	0.69	0.40
SK	1.45	1.53	0.98	0.79	0.78	1.55	4.52	1.70
YK	2.74	0	0	0	0	0	0	0

Appendix A. Comparison of national totals, incidence per 100,000 population and proportion captured between the Canadian Notifiable Disease Surveillance System (CNDSS) and the National Enteric Surveillance Program (NESP) for enteric diseases, 2019^{appendix a table 1 note 1}

Appendix B. Species and serotype data reported to NESP by province and territory, 2020

Cases visiting a different province or territory are captured in the total count for the province or territory where the case was detected.

Appendix C. Impacts of COVID-19. Comparison of NESP weekly isolate counts for 2020 and the average weekly isolate counts for 2015 to 2019 for select pathogens

In March of 2020, the COVID-19 pandemic was declared^{Footnote 4} and global public health action was taken to address it. Across Canada and within specific provinces/territories and regions various public health measures were put in place. These included international^{Footnote 5} and domestic travel restrictions, closing of non-essential businesses and activities (including restaurants, gyms, salons, places of worship, etc.), closing of in-person schools and initiating virtual learning, mandating of face coverings in public and indoor spaces, etc. Additionally, increased public health messaging related to hand washing and cough and sneeze etiquette, reminders about staying home if you were feeling unwell and to get tested for COVID-19 were implemented. These public health measures and the adaptations Canadians made to combat COVID-19 not only helped to reduce the transmission of COVID-19 but have also impacted other reported infectious diseases to varying degrees. Interpretation of the 2020 NESP data must be considered in light of these COVID-19 public health measures and adaptations.

The following figures highlight differences seen in the 2020 NESP data compared with the previous five years (2015 to 2019), for select pathogens. The NESP data are plotted along with the COVID-19 national case numbers as a proxy for the stage of the pandemic and the related public health measures and should not be interpreted as having any direct link between these illnesses.

The impact of the COVID-19 public health measures and adaptations varied across pathogens. For all Salmonella (Figure 10), the steep drop beginning around week 13 is likely associated with the initial implementation of public health measures and the international travel. The spike seen starting in week 28 is related to the S. Newport outbreak. Figures 11 and 12 highlight the differences seen between S. Enteritidis alone and all other Salmonella serotypes excluding S. Enteritidis. The decline seen in the 2020 S. Enteritidis data is sustained throughout the year and this is likely related to both the impacts of COVID-19 public health measures, but also the continued impact related to CFIA regulation implemented in April 2019 to address Salmonella in frozen raw breaded chicken products. In Figures 13 and 14, an initial steep drop around weeks 14 and 15 is seen for E. coli O157 and non-O157 STEC, respectively. For E. coli O157, weeks 24 to 41 appear to have a slight decrease in 2020 compared with the historical average, and then around week 41 until the end of 2020 a larger decrease is apparent. In contrast, non-O157 STECappears to rebound around week 22 and keeps pace with the historical average until week 39 where it then appears to have a slight decrease in 2020 compared with the historical average. This slight difference between E. coli O157 and non-O157 STEC trends may in part be due to the overall general increasing trend of non-O157 STECidentification and reporting that has been seen. Figure 15 shows the 2020 trend for Listeria monocytogenes does not differ greatly from the historical average for 2015 to 2019 and in fact slightly exceeds the historical average. This demonstrates the minimal impact the COVID-19 public health measures had on this organism. Listeria monocytogenes is typically not travel-related and causes severe illness, which may in part explain the consistency with pre-COVID-19 pandemic levels of reported data. For Shigella, similar to what is seen for all Salmonella, in figure 16 the large decrease around week 13 followed by a sustained decrease throughout 2020. Shigella is often travel-related and transmitted through person-to-person contact, which may in part explain the large impact the COVID-19 public health measures would have had on this organism.

In general, larger decreases are seen in pathogens that typically have a larger travel-related proportion, are typically milder or are more frequently related to person-to-person contact. In comparison with Listeria monocytogenes as it is typically severe, is not associated with travel and not acquired through person-to-person contact.

The public health measures that were implemented in response to the COVID-19 pandemic were multifaceted; thus, it is challenging to attribute specific measures to specific enteric disease impacts (perhaps with the exception of the impacts of travel restrictions). That the public health measures also likely caused a major shift in food consumption patterns (i.e., decreasing food purchased and consumed outside the home) further complicates our ability to easily discern these individual impacts. Finally, any changes in medical care-seeking behaviours among Canadians as a result of stay-at-home orders and local healthcare system changes may have also influenced these observations; however, this remains unknown at this time. Additional analysis will be done to further explore the impact of COVID-19 on the occurrence of enteric diseases in Canada as collected and reported by NESP.

Figure 10 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	73	113.2
2	0	90	143.6
3	0	121	132.4
4	0	116	152.4
5	4	103	143
6	3	118	135.2
7	0	100	136.2
8	2	114	132.6
9	6	132	139.4
10	42	135	134.2
11	140	93	148.4
12	1161	128	143.4
13	4054	99	140.4
14	8479	78	164.8
15	9414	74	149.8
16	10035	36	159.2
17	11997	35	165.4
18	11359	34	159.2
19	10988	43	155.8
20	8159	50	151.4
21	7748	51	135.4
22	6564	53	149.6
23	4867	58	154.2
24	3353	60	132.8
25	2609	73	138.2
26	2013	57	129.6
27	2284	85	136.8
28	2030	108	145.8
29	2653	194	158.2
30	3557	216	153.4
31	3043	260	145.6
32	2622	180	144.4
33	2668	147	170.2
34	2740	148	181.2
35	3043	123	177.8
36	3822	140	166
37	4646	86	166.2
38	6633	106	158.6
39	8897	95	144.4
40	12800	103	130.4
41	15708	82	116
42	16142	43	116
43	17638	62	119
44	21485	55	120.2
45	24611	99	113
46	32530	88	117.6
47	33839	73	121
48	39136	58	122.8
49	44007	53	111.6
50	45982	47	134.4
51	46693	42	112.2
52	45124	38	76.6

Figure 11 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	51	66.6
2	0	64	80.4
3	0	88	76.6
4	0	78	85.4
5	4	70	77.6
6	3	78	66.6
7	0	57	71
8	2	78	69.2
9	6	90	72
10	42	97	73.4
11	140	53	72.4
12	1161	91	73.4
13	4054	60	67.6
14	8479	44	76.2
15	9414	50	73.2
16	10035	27	86.6
17	11997	24	92.6
18	11359	18	82.4
19	10988	26	82
20	8159	31	83
21	7748	36	71.8
22	6564	28	84.8
23	4867	35	97
24	3353	37	78
25	2609	48	78.6
26	2013	41	75.8
27	2284	56	83.6
28	2030	93	84.4
29	2653	179	96
30	3557	191	93.4
31	3043	220	88.6
32	2622	145	94.6
33	2668	117	112.4
34	2740	111	113.6
35	3043	100	115
36	3822	112	101
37	4646	72	100.8
38	6633	72	99.6
39	8897	66	92
40	12800	84	81.6
41	15708	64	73.6
42	16142	29	72
43	17638	40	75
44	21485	43	78.6
45	24611	81	76.6
46	32530	67	76
47	33839	54	77.8
48	39136	43	77.8
49	44007	40	75
50	45982	35	81.4
51	46693	28	67.8
52	45124	26	45.4

Figure 12 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	22	46.6
2	0	26	63.2
3	0	33	55.8
4	0	38	67
5	4	33	65.4
6	3	40	68.6
7	0	43	65.2
8	2	36	63.4
9	6	42	67.4
10	42	38	60.8
11	140	40	76
12	1161	37	70
13	4054	39	72.8
14	8479	34	88.6
15	9414	24	76.6
16	10035	9	72.6
17	11997	11	72.8
18	11359	16	76.8
19	10988	17	73.8
20	8159	19	68.4
21	7748	15	63.6
22	6564	25	64.8
23	4867	23	57.2
24	3353	23	54.8
25	2609	25	59.6
26	2013	16	53.8
27	2284	29	53.2
28	2030	15	61.4
29	2653	15	62.2
30	3557	25	60
31	3043	40	57
32	2622	35	49.8
33	2668	30	57.8
34	2740	37	67.6
35	3043	23	62.8
36	3822	28	65
37	4646	14	65.4
38	6633	34	59
39	8897	29	52.4
40	12800	19	48.8
41	15708	18	42.4
42	16142	14	44
43	17638	22	44
44	21485	12	41.6
45	24611	18	36.4
46	32530	21	41.6
47	33839	19	43.2
48	39136	15	45
49	44007	13	36.6
50	45982	12	53
51	46693	14	44.4
52	45124	12	31.2

Figure 13 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	4	4.8
2	0	2	4
3	0	8	3.4
4	0	4	2.4
5	4	1	3.6
6	3	4	3.6
7	0	2	2.6
8	2	4	4
9	6	1	3.4
10	42	4	2.6
11	140	6	3
12	1161	5	4.8
13	4054	5	5
14	8479	1	6.2
15	9414	0	7
16	10035	2	6
17	11997	0	5
18	11359	8	6.4
19	10988	1	4.6
20	8159	2	5
21	7748	2	5.2
22	6564	2	5
23	4867	7	7.4
24	3353	5	5.6
25	2609	4	9.8
26	2013	5	7.4
27	2284	6	8.8
28	2030	10	10.2
29	2653	9	12.6
30	3557	6	11.4
31	3043	6	12.6
32	2622	14	16.4
33	2668	10	18.4
34	2740	13	19
35	3043	10	20
36	3822	4	13.8
37	4646	10	11.6
38	6633	7	11.8
39	8897	6	7.4
40	12800	8	8.2
41	15708	6	6.8
42	16142	2	6.6
43	17638	4	9.6
44	21485	3	7.4
45	24611	2	4.8
46	32530	1	7.4
47	33839	2	9.8
48	39136	3	7.2
49	44007	3	8
50	45982	2	5.6
51	46693	0	6.2
52	45124	0	3.6

Figure 14 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	3	3.8
2	0	3	4.8
3	0	9	5.6
4	0	10	6.2
5	4	7	5.6
6	3	8	5
7	0	10	4.2
8	2	6	7
9	6	7	6.8
10	42	8	3.8
11	140	4	4.4
12	1161	11	5.2
13	4054	3	6
14	8479	11	5.4
15	9414	1	6.4
16	10035	3	6
17	11997	1	8.4
18	11359	4	6.2
19	10988	3	7.6
20	8159	5	10
21	7748	2	4.6
22	6564	8	6.4
23	4867	5	6
24	3353	6	8.4
25	2609	9	7.8
26	2013	5	8.8
27	2284	12	9.4
28	2030	12	7.4
29	2653	9	7.6
30	3557	7	13.2
31	3043	15	8.6
32	2622	5	13.4
33	2668	8	12.2
34	2740	10	8
35	3043	15	10.2
36	3822	11	9.6
37	4646	6	9.2
38	6633	7	9.8
39	8897	8	8
40	12800	7	16.4
41	15708	3	10.6
42	16142	1	8.6
43	17638	3	6.8
44	21485	4	3.8
45	24611	3	5.6
46	32530	2	5.4
47	33839	4	6.8
48	39136	2	6.2
49	44007	6	6.2
50	45982	2	8.8
51	46693	2	4.8
52	45124	1	6

Figure 15 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	1	3
2	0	1	3.6
3	0	1	2.8
4	0	3	1.6
5	4	2	3.6
6	3	2	1.6
7	0	0	2.6
8	2	3	1.8
9	6	2	2.4
10	42	0	1.2
11	140	0	1.2
12	1161	4	1.4
13	4054	2	2
14	8479	2	2.2
15	9414	1	2.2
16	10035	4	2
17	11997	5	2.8
18	11359	3	0.6
19	10988	8	3.2
20	8159	1	2.4
21	7748	0	2.8
22	6564	1	3
23	4867	2	2.2
24	3353	0	2.8
25	2609	1	4
26	2013	0	1.6
27	2284	0	5.8
28	2030	1	5
29	2653	5	2.2
30	3557	6	3.8
31	3043	3	4
32	2622	5	3
33	2668	2	4.6
34	2740	6	3.2
35	3043	8	5.2
36	3822	5	4.4
37	4646	9	4.2
38	6633	5	5.6
39	8897	4	3.6
40	12800	8	3
41	15708	6	3.6
42	16142	4	3.2
43	17638	2	3.6
44	21485	3	2
45	24611	2	2.2
46	32530	3	2.6
47	33839	5	2.6
48	39136	4	2.4
49	44007	4	2
50	45982	1	2.6
51	46693	4	3
52	45124	2	1.8

Figure 16 - Text description

Week Number	COVID-19 Cases 2020	NESP Isolates Total 2020	NESP Isolates Avg 2015-2019
1	0	9	11.8
2	0	8	20.8
3	0	23	14.6
4	0	16	23.2
5	4	22	17.6
6	3	23	14.8
7	0	17	18.6
8	2	16	17.2
9	6	21	16.2
10	42	14	13.2
11	140	22	11.8
12	1161	14	15.2
13	4054	8	15.6
14	8479	10	18
15	9414	5	15.8
16	10035	3	15.8
17	11997	6	13.6
18	11359	3	16.4
19	10988	5	11.4
20	8159	2	13.4
21	7748	3	11.6
22	6564	3	13.8
23	4867	3	11.6
24	3353	3	10
25	2609	3	10.8
26	2013	1	12
27	2284	4	11.8
28	2030	2	11.4
29	2653	7	10
30	3557	6	12.6
31	3043	8	15
32	2622	4	14.4
33	2668	4	14.2
34	2740	8	16.8
35	3043	2	18
36	3822	2	16.2
37	4646	5	14.8
38	6633	9	19.4
39	8897	4	14.8
40	12800	5	16.8
41	15708	7	14
42	16142	1	16.4
43	17638	5	21.6
44	21485	3	13.4
45	24611	1	14.4
46	32530	4	11.6
47	33839	6	17.8
48	39136	10	11
49	44007	4	14
50	45982	1	17
51	46693	4	19.2
52	45124	2	10