Charlotte Kjelsø

Participatory Syndromic Surveillance of Influenza in Europe

The growth of digital communication technologies for public health is offering an unconventional means to engage the general public in monitoring community health. Here we present Influenzanet, a participatory system for the syndromic surveillance of influenza-like illness (ILI) in Europe. Through standardized online surveys, the system collects detailed profile information and self-reported symptoms volunteered by participants resident in the Influenzanet countries. Established in 2009, it now includes 10 countries representing more than half of the 28 member states of the European Union population. The experience of 7 influenza seasons illustrates how Influenzanet has become an adjunct to existing ILI surveillance networks, offering coherence across countries, inclusion of nonmedically attended ILI, flexibility in case definition, and facilitating individual-level epidemiological analyses generally not possible in standard systems. Having the sensitivity to timely detect substantial changes in population health, Influenzanet has the potential to become a viable instrument for a wide variety of applications in public health preparedness and control.

Influmeter - an online tool for self-reporting of influenza-like illness in Denmark.

Abstract Background In October 2013, we implemented ‘Influmeter’, a web-based influenza-like illness (ILI) self-reporting system, to monitor ILI in the general population in a timely fashion, to provide data for estimations of the burden of influenza and to gain experience with online surveillance systems, in Denmark. After the season 2013/2014 we evaluated the system to decide on its future use. Methods Influmeter study participants provided personal details upon enrolment and reported symptoms weekly within predefined categories. We compared distribution of Influmeter participants with the Danish population, by sex, age, region, chronic diseases and educational level. We calculated the proportion of participants reporting symptoms of ILI weekly and the proportion of Influmeter ILI cases seeking medical assistance, using the Danish and the EU ILI case definitions. Further, we compared timing of increased ILI rates in Influmeter with existing Danish sentinel ILI surveillance using the Danish case definition. Results Compared with the Danish population, Influmeter had more females (p < 0.001) and persons with a higher education (p < 0.001), while the age group 0–24 was under-represented (p < 0.001). Influmeter ILI activity peaked 1 week before the exceeding of the sentinel epidemic threshold. Depending on ILI case definition 16–22% of ILI cases sought medical assistance. Conclusion Influmeter was useful in the timely monitoring of ILI activity in the population that did not seek medical assistance in relation to ILI. We recommend continuation of the system, targeted enrolment of the young and future analyses adjusted for uneven representation relative to the underlying population.

Salmonella Typhimurium outbreak associated with smoked pork tenderloin in Denmark, January to March 2011

Abstract Background: An outbreak of salmonellosis (Salmonella Typhimurium, phage type DT120) occurred from 26 January to 15 March 2011, in Denmark, with 22 laboratory confirmed cases. Hypothesis-generating patient interviews gave rise to the suspicion that smoked pork tenderloin was the source of infection. The primary objective of this study was to identify the source of the outbreak in order to initiate appropriate control measures. Methods: A matched (1:2) case–control study was conducted. A case was defined as a person residing in Denmark whose stool sample tested positive for S. Typhimurium, with a particular multilocus variable-number tandem repeat profile, from January to March 2011. Controls were matched to cases on age, gender, and municipality of residence. Results: Of 21 interviewed cases, 19 (91%) indicated that they typically ate smoked pork tenderloin more than once a week, compared with 13 (33%) of 39 interviewed controls (matched odds ratio 19.6, 95% confidence interval 2.6–153). Eighteen (86%) cases indicated that they might have consumed smoked pork tenderloin the week before becoming ill, compared with 1 (4%) control who had eaten the product a week before the interview. Two cases provided the brand name of the product and the supermarket where it was purchased. Conclusions: The results show a strong statistically significant association between the consumption of smoked pork tenderloin and S. Typhimurium infection. The European Rapid Alert System for Food and Feed was used to notify these findings to the competent authorities in the country of origin of the product. Subsequently, the smoked pork tenderloin of the brand in question, dating from 1 January to 1 May 2011, was recalled from consumers.

Genomic investigation of a suspected outbreak of Legionella pneumophila ST82 reveals undetected heterogeneity by the present gold-standard methods, Denmark, July to November 2014

Between July and November 2014, 15 community-acquired cases of Legionnaires´ disease (LD), including four with Legionella pneumophila serogroup 1 sequence type (ST) 82, were diagnosed in Northern Zealand, Denmark. An outbreak was suspected. No ST82 isolates were found in environmental samples and no external source was established. Four putative-outbreak ST82 isolates were retrospectively subjected to whole genome sequencing (WGS) followed by phylogenetic analyses with epidemiologically unrelated ST82 sequences. The four putative-outbreak ST82 sequences fell into two clades, the two clades were separated by ca 1,700 single nt polymorphisms (SNP)s when recombination regions were included but only by 12 to 21 SNPs when these were removed. A single putative-outbreak ST82 isolate sequence segregated in the first clade. The other three clustered in the second clade, where all included sequences had < 5 SNP differences between them. Intriguingly, this clade also comprised epidemiologically unrelated isolate sequences from the UK and Denmark dating back as early as 2011. The study confirms that recombination plays a major role in L. pneumophila evolution. On the other hand, strains belonging to the same ST can have only few SNP differences despite being sampled over both large timespans and geographic distances. These are two important factors to consider in outbreak investigations.

Unsupervised Extraction of Epidemic Syndromes from Participatory Influenza Surveillance Self-reported Symptoms

Seasonal influenza surveillance is usually carried out by sentinel general practitioners who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This practice for surveillance is generally affected by two main issues: i) reports are usually released with a lag of about one week or more, ii) the definition of a case of influenza-like illness based on patients symptoms varies from one surveillance system to the other, i.e. from one country to the other. The availability of novel data streams for disease surveillance can alleviate these issues; in this paper, we employed data from Influenzanet, a participatory web-based surveillance project which collects symptoms directly from the general population in real time. We developed an unsupervised probabilistic framework that combines time series analysis of symptoms counts and performs an algorithmic detection of groups of symptoms, hereafter called syndromes. Symptoms counts were collected through the participatory web-based surveillance platforms of a consortium called Influenzanet which is found to correlate with Influenza-like illness incidence as detected by sentinel doctors. Our aim is to suggest how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness’ temporal trends without relying on a specific case definition. We evaluated the performance of our framework by showing that the temporal trends of the detected syndromes closely follow the ILI incidence as reported by the traditional surveillance, and consist of combinations of symptoms that are compatible with the ILI definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition. Author summary This study suggests how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness’ temporal trends without relying on a specific case definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.