How Many Foodborne Outbreaks of Salmonella Infection Occurred in France in 1995?

Application of the Capture-Recapture Method to Three Surveillance Systems

Anne Gallay1, Véronique Vaillant1, Philippe Bouvet2, Patrick Grimont2 and Jean-Claude Desenclos1

1 Réseau National de Santé Publique, 14 rue du Val d'Osne, 94410 Saint Maurice, France.
2 Centre National de Référence des Salmonella et des Shigella, Institut Pasteur, 28 Rue du Docteur Roux, 75724 Paris, Cedex 15, France.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Despite control measures, foodborne outbreaks of non-typhi Salmonella infection continue to occur in developed countries. The authors aimed to assess the number of foodborne Salmonella outbreaks that occurred in France in 1995 using a capture-recapture approach. Data from three sources—the National Public Health Network (NPHN), the Ministry of Agriculture (MA), which receives mandatory notification, and the National Salmonella and Shigella Reference Center (NRC)—were collected. Matching algorithms permitted identification of matched outbreaks. The total number of outbreaks was estimated by log-linear modeling taking into account source dependencies and the variable catchability. The final estimate was adjusted for the positive predictive value (66%) of the NRC case definition. The dependence between the NPHN and the MA was also evaluated by means of a qualitative survey. A total of 716 foodborne Salmonella outbreaks were reported to the three sources, and 108 matches were identified. The best-fitting model, taking into account a positive dependence between the NPHN and MA sources, gave an estimate of 757 outbreaks. The sensitivity was 15% for the NPHN, 10% for the MA, and 50% for the NRC. In France, routine mandatory reporting of foodborne Salmonella outbreaks is very incomplete, and it is not representative of the serotype and the type of outbreak.

capture-recapture; disease outbreaks; food poisoning; Salmonella infections

Abbreviations: AIC, Akaike Information Criterion; BIC, Bayesian Information Criterion; CI, confidence interval; DDASS, Direction Départementale des Affaires Sanitaires et Sociales; DSV, Direction des Services Vétérinaires; MA, Ministry of Agriculture; NPHN, National Public Health Network; NRC, National Salmonella and Shigella Reference Center


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Despite prevention and control efforts, Salmonella remains the leading cause of foodborne gastroenteritis outbreaks in developed countries (1GoGo–3Go). Changes in dietary habits, changes in modes of food production and distribution, and increases in the size of more vulnerable populations have been implicated as contributing factors (3GoGoGoGoGoGo–9Go). In humans, Salmonella may cause sporadic disease, family outbreaks, and community outbreaks either limited to a defined population or spread community-wide (10Go). In France, Salmonella is involved in 75.6 percent of reported foodborne outbreaks with an identified causative organism, 70 percent of which occur in a family household (11Go).

Studies performed in Great Britain have shown that the economic impact of foodborne Salmonella outbreaks is far from negligible (12Go, 13Go). Therefore, assessment of the true human and economic burden of Salmonella infection, particularly outbreaks, requires a precise knowledge of its incidence. This is particularly true in France, where data on Salmonella outbreaks are derived from passive mandatory notification of foodborne outbreaks, which is known from anecdotal data to have a very low sensitivity (11Go). In this study, we quantified the level of underascertainment of foodborne Salmonella outbreaks by estimating the true number of outbreaks that occurred in France in 1995, using the capture-recapture method applied to three different sources of information.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Data sources and characteristics
We used data collected by the three French surveillance systems for foodborne outbreaks in 1995: 1) the National Public Health Network (NPHN), to which notification is mandatory through the district public health departments; 2) the Ministry of Agriculture (MA), to which notification is mandatory through the district veterinary departments; and 3) the National Salmonella and Shigella Reference Center (NRC).

Any foodborne outbreak must be reported by the physician, the head of the family, or the chief of the affected community to the district public health department (Direction Départementale des Affaires Sanitaires et Sociales (DDASS)) or the district veterinary service (Direction des Services Vétérinaires (DSV)). After an investigation, the DDASS or the DSV sends a report to the NPHN or the MA, respectively, where it is validated and used for a national annual surveillance summary. Although it is recommended, collaboration between the DDASS and the DSV is not systematic. For both mandatory notification systems, a foodborne outbreak is defined as illness in at least two persons with digestive symptoms that can be attributed to the same food source. For each foodborne outbreak, information is collected on the postal code of occurrence, the date of onset, the date and place of meal consumption, the suspect food items, the organism implicated (and, if it is Salmonella, the serotype), the number of patients affected, and the type of outbreak (family or community).

The NRC receives Salmonella isolates from public and private microbiology laboratories for serotyping (14Go). The sending of isolates to the NRC is voluntary. For each isolate, information is collected on the laboratory postal code, the dates of isolation and of receipt at the NRC, and the serotype. If the isolate is associated with an outbreak, information on the number of patients affected and the type of outbreak (family or community) is also collected. The NRC defines a foodborne Salmonella outbreak as the isolation of Salmonella associated with the occurrence of other cases of gastroenteritis in a defined population or community. A common food origin is not always reported in the NRC data.

Identification of matches
Because foodborne outbreaks are not recorded in each system with a common identifier, we developed matching criteria between the three systems (NPHN, MA, and NRC) according to data common to all systems. A match between the NPHN and the MA had to have the same postal code of occurrence and the same date of onset (1 day). Potential matches were confirmed if the investigation reports sent to the NPHN and the MA had similar characteristics (date, place of occurrence, number of patients, serotype, and implicated food). Date of onset is not recorded at the NRC (dates of isolation and of receipt of the isolate are available); thus, we had to use other criteria to identify matches between the NRC and the other two sources. They were based on the following: the postal code of occurrence; the delay between the date of onset of the outbreak (data from the NPHN and MA) and either the date of isolation of Salmonella recorded by the NRC (delay 1) or the date of receipt of Salmonella at the NRC (delay 2); and, finally, the distribution by quartile of these delays, determined in three previous studies of Salmonella isolates for which the three dates had been collected (15GoGo–17Go) (table 1). Matches between the NPHN and the NRC and between the MA and the NRC had to have 1) the same postal code, 2) a date of onset prior to the date of Salmonella isolation and/or the date of receipt of the isolate at the NRC, 3) delay 1 and/or delay 2 included in one of the quartiles of their estimated distribution, and 4) the same serotype. Although data on the date of isolation or the date of receipt for Salmonella were not all complete, the matches could be identified with either a single delay or both. Since a single notification could match with several others, we considered as a true match the one with the shortest delay 1 and/or delay 2. Matches between the three sources were identified by comparing matches between the NPHN and the MA, the NPHN and the NRC, and the MA and the NRC.


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TABLE 1. Delays (in days) between the dates of onset of foodborne Salmonella outbreaks and the dates of isolation and receipt of Salmonella by the National Salmonella and Shigella Reference Center (NRC), by quartile (Q), France, 1995

 
Capture-recapture estimates
According to the hypothesis of independence between the sources and the equal catchability in each source, estimates of the total number of foodborne Salmonella outbreaks were calculated for each pair of sources using Chapman's (18Go) and Seber's (19Go) unbiased formulae. Two sources are considered independent when the probability of notification of one event in one source is not dependent on its probability of notification in the other source. Equal catchability is fulfilled when the probability of notification of one event is not influenced by its characteristics (i.e., age, gender, severity of symptoms, circumstances of the diagnosis, etc.) in each source. This probability may vary from one source to another or be constant overall. The dependence between two sources was assessed by comparing the estimates obtained for each pair of sources and by calculating the odds ratio (and its 95 percent confidence interval) between the cell counts of the two sources within the third one, as proposed by Wittes and colleagues (20Go, 21Go).

To take into account the dependencies between the sources and potential variable catchability, we estimated the number of outbreaks by log-linear modeling (22Go, 23Go). We used a stepwise procedure with the BMDP 4F program (BMDP Statistical Software, Inc., Los Angeles, California). The choice of the final model was based on the likelihood ratio statistic (G2), the Akaike Information Criterion (AIC), and the Bayesian Information Criterion (BIC), which are functions of the likelihood ratio statistic, with AIC = G2 - 2 df and BIC = G2 - (log N/2{pi}) df, where df is degrees of freedom and N is the number of foodborne outbreaks observed (24Go). The optimal model was the model with the lowest AIC and BIC values. The weighted average of the BIC ("weighted BIC") of all estimates provided by each model was calculated as suggested by Drapper (25Go).

We also stratified the analysis by serotype (S. enteritidis, S. typhimurium, and other serotypes) and type of outbreak (family or community). The total variance was calculated by adding the variance of each stratum. The 95 percent confidence interval was calculated using the method suggested by Hook and Regal (24Go). The sensitivity of each source is the number of foodborne outbreaks reported to the source divided by the total number estimated by the final log-linear model. Sensitivity was also calculated for each stratum of serotype and type of outbreak. The representativeness was assessed by comparing, by stratification variables, the distribution of each source to the distribution estimated by log-linear modeling using the goodness-of-fit {chi}2 test (26Go).

Qualitative assessment of the dependency between the NPHN and the MA
In addition to the log-linear method, we evaluated the dependency between the two mandatory notification systems through a survey of a random sample of 22 districts, for both public health (DDASS) and veterinary (DSV) departments. In each district selected, officers of the DDASS and DSV were interviewed independently by telephone, using a standardized questionnaire, on their handling of foodborne outbreak notifications and their collaboration.

Positive predictive value of the definition used by the NRC
Because notifications to the NPHN and the MA are validated by a systematic procedure, we assumed that their positive predictive value was 100 percent. For the NRC, information about the index meal is not always complete and validated. Therefore, we estimated the positive predictive value of a prospective sample of foodborne Salmonella outbreaks reported to the NRC between February 1 and May 31, 1997. We contacted laboratories of isolation and case physicians by telephone to collect further information on the reported outbreaks. An outbreak was considered truly foodborne if it fulfilled the case definition used for mandatory notification. The positive predictive value obtained was used to correct the estimate of the total number of foodborne Salmonella outbreaks estimated by the capture-recapture analysis, as suggested by LaPorte et al. (27Go).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Among the 780 foodborne Salmonella outbreaks recorded by the three sources in 1995, 64 notifications were excluded from the analysis: 33 were multiple notifications to the same source, 13 had no identification criteria, and 18 did not include information on the serotype or type of outbreak. Of the 716 outbreaks that remained for analysis, 114 had been reported to the NPHN, 73 had been reported to the MA, and 529 had been reported to the NRC; 108 were matches. Of the latter outbreaks, 30 were matches between the NPHN and the MA, 59 were matches between the NPHN and the NRC, 39 were matches between the MA and the NRC, and 20 were matches between all three sources.

The median delay 1 for matched outbreaks was 3.5 days (range, 0–19 days) between the NPHN and the NRC and 3 days (range, 1–18 days) between the MA and the NRC. Delay 2 was similar (10 days) for matches between the NPHN and the NRC (range, 2–37 days) and matches between the MA and the NRC (range, 2–33 days).

In the two-source capture-recapture analysis, the estimate of the total number of foodborne Salmonella outbreaks for the NPHN-MA pair was 3.5 times smaller than the estimates for NPHN-NRC and MA-NRC (table 2). This indicates a strong dependence between the NPHN and the MA, with, among the outbreaks notified to the NRC, an odds ratio between NPHN and MA data of 12.2 (95 percent confidence interval (CI): 5.7, 26.2). The survey of the DDASS and DSV confirmed the strong positive dependency between the two mandatory notification systems: Of the 22 districts surveyed, 10 DDASS and DSV districts indicated that very good collaboration was in place for all types of outbreaks (family or community), 10 had established good collaboration for community outbreaks only, and in two districts the DDASS and the DSV did not collaborate.


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TABLE 2. Two-source capture-recapture estimates of numbers of foodborne Salmonella outbreaks, France, 1995

 
The estimate obtained with the saturated log-linear model was approximately 2–3 times greater than the estimates obtained with the other model, and it had a wide 95 percent confidence interval. The model with an interaction term between the NPHN and the MA had the best adequacy (p = 0.1), the best BIC (-4.7), and an AIC (0.4) superior to the AIC of the saturated model and gave an estimate of 1,065 outbreaks (95 percent CI: 910, 1,220) (table 3). Two interaction terms were further identified, one between the serotype and the NPHN and the other between the type of outbreak and the MA (table 3). With these interaction terms added to the previous model, the BIC and AIC values became -103.2 and -23.2, respectively. The analysis gave the same estimate of number of outbreaks (1,065; 95 percent CI: 913, 1,217), which is also similar to the "weighted BIC" (table 3).


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TABLE 3. Characteristics of log-linear models fitted to three sources of data on foodborne Salmonella outbreaks and their estimates of the total number of outbreaks, France, 1995

 
Forty outbreaks reported to the NRC were included in the study of the positive predictive value of the NRC outbreak case definition. Of the 40 laboratories and physicians contacted, one refused to participate, and no information was available for seven outbreaks. Of the 32 events investigated, 21 were confirmed as foodborne outbreaks, for a positive predictive value of 65.6 percent (95 percent CI: 50, 82). Positive predictive values were similar by serotype. Because the 11 "false positive" outbreaks (sporadic cases associated or not associated with secondary transmission) could not be classified as being of either the family type or the community type, it was not possible to estimate the positive predictive value by type of outbreak and thus to obtain corrected values by type of outbreak.

After correction with the positive predictive value of the NRC, we estimated that 757 (95 percent CI: 651, 863) foodborne Salmonella outbreaks had occurred in France in 1995 (table 4). The sensitivity of the three surveillance systems was estimated at 15 percent for the NPHN, 10 percent for the MA, and 50 percent for the NRC. S. enteritidis outbreaks were reported more often to the NPHN (19 percent) than outbreaks of S. typhimurium (8 percent) and other serotypes (11 percent) (table 4). There were almost three times fewer reports of family outbreaks (5 percent) reported to the MA than community outbreaks (13 percent). Compared with the estimates obtained by the capture-recapture analysis (table 5), there was a statistically significant difference in the serotype distribution for the NPHN (p = 0.001), with an overrepresentation of S. enteritidis (71 percent vs. 54 percent), and in the types of outbreaks for the MA (p = 2 x 10-5), with many fewer family outbreaks reported (52 percent vs. 74 percent).


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TABLE 4. Sensitivity of surveillance systems for foodborne Salmonella outbreaks, by serotype and type of outbreak, France, 1995

 

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TABLE 5. Representativeness of foodborne Salmonella outbreak surveillance systems, by serotype and type of outbreak, France, 1995

 
A total of 753 (95 percent CI: 649, 857) outbreaks were obtained in a two-source analysis after we merged the two dependent sources (NPHN and MA) and adjusted the estimate for the positive predictive value of the NRC. The sensitivity was then 21 percent for the two sources combined and 50 percent for the NRC.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
To the best of our knowledge, this is the first study that used the capture-recapture method to estimate the true number of foodborne Salmonella outbreaks in a given country and year. Despite the lack of a common identifier between the three sources, it was possible to identify matches between the three sources based on the date, place of occurrence, and serotype of each outbreak. In addition, we completed the capture-recapture approach with a qualitative investigation to better understand the mechanisms of dependencies between two of the sources. Furthermore, we estimated the positive predictive value of the case definition of the surveillance system (NRC), which was thought to have a positive predictive value less than 100 percent. After adjusting for the estimated positive predictive value, we concluded that 757 foodborne Salmonella outbreaks occurred in France in 1995, of which only 15 percent (NPHN), 10 percent (MA), and 50 percent (NRC) had been reported to the three surveillance systems, respectively. The sensitivity of 15 percent for the mandatory notification to the NPHN is similar to the one (12.5 percent) found in 1994 during an exhaustive survey of reports of foodborne Salmonella outbreaks in one district of France (28Go). We also showed that notification was not homogeneous in two of the sources: S. enteritidis was better reported to the NPHN than other serotypes, while family outbreaks were far less often reported to the MA than community outbreaks.

To use the capture-recapture method accurately, several conditions must be met (24Go). The definition of the event studied should be the same for each source (29Go, 30Go), a condition that was not met for the NRC. The lower specificity of the definition of the NRC would have induced false positive notifications and therefore an overestimate of outbreaks. This was corrected with the positive predictive value of the case definition of the NRC, as suggested by LaPorte et al. (27Go). Since the notifications to the two mandatory notification sources were routinely validated, we assumed that their positive predictive values were 100 percent.

Since none of the three notification systems shared a unique identifier, we identified matches according to the postal code and date of onset for one pair of sources (NPHN-MA) and according to the postal code and delays between date of onset, date of Salmonella isolation, or receipt by the NRC for the other two pairs of sources (NPHN-NRC and MA-NRC). This matching algorithm, which we did not validate, might have induced either false negative or false positive matches and therefore an under- or overestimated number of outbreaks, particularly for those between the sources NPHN-NRC and MA-NRC. However, it is possible that the opposite effects of false positive matches and false negative matches cancelled each other out (31Go). In addition, the distribution of delay 1 and delay 2 for matched outbreaks between these two pairs of sources was homogeneous (data not shown). Because the NPHN and the MA sources have more common criteria, the specificity and sensitivity of the matching procedure between these two sources was probably less problematic. Furthermore, as Egeland et al. did in another study (32Go), we were able to validate all identified matches by comparing the reports of the two sources. This method allowed us to minimize the number of false positives, but it did not rule the false negatives out.

The qualitative investigation confirmed the positive dependency found statistically between the NPHN and the MA in the capture-recapture analysis. Such studies are recommended for assessment of the dependency between two sources when this dependency cannot be assessed using statistical analysis (33Go). Furthermore, it was useful to understand the mechanisms of the dependency. Since the respective and complementary roles of the NPHN and the MA are both defined by the same regulatory act, we expected to find a strong positive dependency between both sources.

To take into account the dependencies between the three sources and the variable catchability in the different sources, we performed a log-linear analysis. To select the final model, we did not use the "principle of parsimony" (24Go), which would have ignored the interactions between the NPHN and the serotype and between the MA and the type of foodborne outbreak. The model that included these two interaction terms had the best BIC and AIC criteria and gave the same estimate as the one without these two interaction terms. In addition, the "weighted BIC" proposed by Hook and Regal (24Go, 34Go) gave the same estimate. A two-source analysis between the NRC and the NPHN-MA merged together gave an estimate similar to that of the final log-linear model. This simple approach developed by Wittes and colleagues (20Go, 21Go) could be used in future analyses. However, the log-linear model remains relevant for analysis of the dependencies between sources and the interactions with covariables, when at least three sources are considered (24Go).

Serotype and type of outbreak (community and family) introduced variable catchability within the NPHN and MA data, respectively. S. enteritidis was better reported to the NPHN than S. typhimurium or other serotypes, and community outbreaks were more often reported to the MA than family outbreaks. This observation may be explained by more systematic requesting of stool cultures by district health officers when the assumed index meal contains eggs or egg products. In the same way, the DSV probably pays less attention to family outbreaks than to community outbreaks. Analysis of the variable catchability by region would be of interest; however, this was not possible because of the low number of outbreaks in some regions. Moreover, it was not possible to stratify on the size of the outbreaks. Although the data were available in each source, information on this variable was not considered valid, because there were important variations in numbers of patients for the same foodborne outbreak reported to at least two sources (laboratory-confirmed cases versus clinical cases, for example).

Our study estimated the number of outbreaks in which at least one patient had a positive Salmonella stool culture. Therefore, it still underestimated the true number of foodborne Salmonella outbreaks, because it did not take into account outbreaks in which patients did not visit a clinical practitioner or did not have a stool culture, or those for which a common food exposure was not identified (35Go). This estimation does not include the number of sporadic cases. In France, it is estimated that 4–6 percent of patients who consult a general practitioner for acute gastroenteritis have a stool culture, and Salmonella is the most frequently isolated agent (36Go, 37Go). Using the algorithm proposed by Chalker and Blaser (38Go), which adjusts for the problems mentioned above, the true estimate is probably in excess of 2,000 foodborne Salmonella outbreaks yearly.

Assessment of the actual number of foodborne Salmonella outbreaks is a necessary preliminary step for assessing its public health burden. Whatever the design used, studies of the burden of foodborne Salmonella infection, including estimation of the number of sporadic cases and the economic impact, are needed to foster prevention and control efforts in food production, distribution, and consumption (39Go). Analyses conducted according to characteristics such as the type of outbreak are very helpful for adjusting the targeting of prevention and control. Because routine surveillance underestimates the number of family outbreaks more than community outbreaks, less priority is given by public health and food safety authorities for the control of the former. Our quantitative approach, based on routine surveillance data, is a first step in the assessment of the true burden of this unresolved public health problem in France.


    ACKNOWLEDGMENTS
 
This work was supported by a grant from the Fondation pour la Recherche Médicale (Paris, France).

The authors acknowledge Dr. E. Delarocque-Astagneau (National Public Health Network), S. Haeghebaert (National Public Health Network), and F. Lequerrec (Ministry of Agriculture) for validating foodborne outbreaks. The authors also thank the district health and veterinary officers for investigating foodborne outbreaks and forwarding data to the National Public Health Network and the Ministry of Agriculture, respectively.


    NOTES
 
Reprint requests to Dr. Anne Gallay, Institut de Veille Sanitaire, 12 rue du Val d'Osne, 94410 Saint Maurice, France.


    REFERENCES
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 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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Received for publication February 17, 1999. Accepted for publication December 27, 1999.