Dataset Information

Evaluating syndromic surveillance systems at institutions of higher education (IHEs): a retrospective analysis of the 2009 H1N1 influenza pandemic at two universities.

ABSTRACT:

Background

Syndromic surveillance has been widely adopted as a real-time monitoring tool for timely response to disease outbreaks. During the second wave of the pH1N1 pandemic in Fall 2009, two major universities in Washington, DC collected data that were potentially indicative of influenza-like illness (ILI) cases in students and staff. In this study, our objectives were three-fold. The primary goal of this study was to characterize the impact of pH1N1 on the campuses as clearly as possible given the data available and their likely biases. In addition, we sought to evaluate the strengths and weaknesses of the data series themselves, in order to inform these two universities and other institutions of higher education (IHEs) about real-time surveillance systems that are likely to provide the most utility in future outbreaks (at least to the extent that it is possible to generalize from this analysis).

Methods

We collected a wide variety of data that covered both student ILI cases reported to medical and non-medical staff, employee absenteeism, and hygiene supply distribution records (from University A only). Communication data were retrieved from university broadcasts, university preparedness websites, and H1N1-related on campus media reports. Regional data based on the Centers for Disease Control and Prevention Outpatient Influenza-like Illness Surveillance Network (CDC ILINet) surveillance network, American College Health Association (ACHA) pandemic influenza surveillance data, and local Google Flu Trends were used as external data sets. We employed a "triangulation" approach for data analysis in which multiple contemporary data sources are compared to identify time patterns that are likely to reflect biases as well as those that are more likely to be indicative of actual infection rates.

Results

Medical personnel observed an early peak at both universities immediately after school began in early September and a second peak in early November; only the second peak corresponded to patterns in the community at large. Self-reported illness to university deans' offices was also relatively increased during mid-term exam weeks. The overall volume of pH1N1-related communication messages similarly peaked twice, corresponding to the two peaks of student ILI cases.

Conclusions

During the 2009 H1N1 pandemic, both University A and B experienced a peak number of ILI cases at the beginning of the Fall term. This pattern, seen in surveillance systems at these universities and to a lesser extent in data from other IHEs, most likely resulted from students bringing the virus back to campus from their home states coupled with a sudden increase in population density in dormitories and lecture halls. Through comparison of data from different syndromic surveillance data streams, paying attention to the likely biases in each over time, we have determined, at least in the case of the pH1N1 pandemic, that student health center data more accurately depicted disease transmission on campus at both universities during the Fall 2009 pandemic than other available data sources.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC3151236 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Publications

Evaluating syndromic surveillance systems at institutions of higher education (IHEs): a retrospective analysis of the 2009 H1N1 influenza pandemic at two universities.

Zhang Ying Y May Larissa L Stoto Michael A MA

BMC public health 20110726

<h4>Background</h4>Syndromic surveillance has been widely adopted as a real-time monitoring tool for timely response to disease outbreaks. During the second wave of the pH1N1 pandemic in Fall 2009, two major universities in Washington, DC collected data that were potentially indicative of influenza-like illness (ILI) cases in students and staff. In this study, our objectives were three-fold. The primary goal of this study was to characterize the impact of pH1N1 on the campuses as clearly as poss ...[more]

PMID: 21791092

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Project description:BackgroundSyndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally.MethodsWe systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify "emergency department" and "syndromic surveillance" were applied to NICE healthcare, Global Health and Scopus databases.ResultsIn total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan).ConclusionsEDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to 'real-time', with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future.Prospero numberCRD42017069150 .

Project description:BackgroundIn April 2009, a novel triple-reassortant swine influenza A H1N1 virus ("A/H1N1pdm"; also known as SOIV) was detected and spread globally as the first influenza pandemic of the 21(st) century. Sequencing has since been conducted at an unprecedented rate globally in order to monitor the diversification of this emergent virus and to track mutations that may affect virus behavior.Methodology/principal findingsBy Sanger sequencing, we determined consensus whole-genome sequences for A/H1N1pdm viruses sampled nationwide in Canada over 33 weeks during the 2009 first and second pandemic waves. A total of 235 virus genomes sampled from unique subjects were analyzed, providing insight into the temporal and spatial trajectory of A/H1N1pdm lineages within Canada. Three clades (2, 3, and 7) were identifiable within the first two weeks of A/H1N1pdm appearance, with clades 5 and 6 appearing thereafter; further diversification was not apparent. Only two viral sites displayed evidence of adaptive evolution, located in hemagglutinin (HA) corresponding to D222 in the HA receptor-binding site, and to E374 at HA2-subunit position 47. Among the Canadian sampled viruses, we observed notable genetic diversity (1.47 x 10?³ amino acid substitutions per site) in the gene encoding PB1, particularly within the viral genomic RNA (vRNA)-binding domain (residues 493-757). This genome data set supports the conclusion that A/H1N1pdm is evolving but not excessively relative to other H1N1 influenza A viruses. Entropy analysis was used to investigate whether any mutated A/H1N1pdm protein residues were associated with infection severity; however no virus genotypes were observed to trend with infection severity. One virus that harboured heterozygote coding mutations, including PB2 D567D/G, was attributed to a severe and potentially mixed infection; yet the functional significance of this PB2 mutation remains unknown.Conclusions/significanceThese findings contribute to enhanced understanding of Influenza A/H1N1pdm viral dynamics.

Dataset Information

Evaluating syndromic surveillance systems at institutions of higher education (IHEs): a retrospective analysis of the 2009 H1N1 influenza pandemic at two universities.

Background

Methods

Results

Conclusions

Publications

Evaluating syndromic surveillance systems at institutions of higher education (IHEs): a retrospective analysis of the 2009 H1N1 influenza pandemic at two universities.

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