ArticleBMC infectious diseases2017
Synchronicity of influenza activity within Phoenix, AZ during the 2015-2016 seasonal epidemic.
Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVariability in the timing of influenza epidemics has been observed across global and regional scales, but this variability has not been studied extensively at finer spatial scales. As such, the aim of this study was to test whether influenza cases were synchronized across sites and/or age-groups within a major city.
methodsWe used influenza cases identified by rapid influenza tests from a network of clinics across Phoenix, AZ during the 2015-2016 influenza A season. We used a combination of KS tests and a bootstrapping approach to evaluate whether the temporal distribution of cases varied by site and/or age group.
resultsOur analysis indicates that the timing of influenza cases during the 2015-2016 seasonal influenza epidemic were generally synchronized across sites and age groups. That said, we did observe some statistically significant differences in the timing of cases across some sites, and by site and age group. We found no evidence that influenza activity consistently begins or peaks earlier in children than in adults.
conclusionsTo our knowledge, this is the first study to investigate differences in the intra-urban timing of influenza using influenza-specific case data. We were able to show evidence that influenza cases are not entirely synchronized across an urban area, but the differences we observed were relatively minor. It is important to understand the geographic scale at which influenza is synchronized in order to gain a better understanding of local transmission dynamics, and to determine the appropriate geographic scale that influenza surveillance data should be aggregated for prediction and warning systems.
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