Spatio-temporal synchrony of influenza in cities across Israel: the "Israel is one city" hypothesis.

PLoS One

Biomathematics Unit, Department of Zoology, Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv, Israel; School of Mathematics and Geospatial Sciences, RMIT University, Melbourne, Victoria, Australia.

Published: May 2015

We analysed an 11-year dataset (1998-2009) of Influenza-Like Illness (ILI) that was based on surveillance of ∽23% of Israel's population. We examined whether the level of synchrony of ILI epidemics in Israel's 12 largest cities is high enough to view Israel as a single epidemiological unit. Two methods were developed to assess the synchrony: (1) City-specific attack rates were fitted to a simple model in order to estimate the temporal differences in attack rates and spatial differences in reporting rates of ILI. The model showed good fit to the data (R2  =  0.76) and revealed considerable differences in reporting rates of ILI in different cities (up to a factor of 2.2). (2) A statistical test was developed to examine the null hypothesis (H0) that ILI incidence curves in two cities are essentially identical, and was tested using ILI data. Upon examining all possible pairs of incidence curves, 77.4% of pairs were found not to be different (H0 was not rejected). It was concluded that all cities generally have the same attack rate and follow the same epidemic curve each season, although the attack rate changes from season to season, providing strong support for the "Israel is one city" hypothesis. The cities which were the most out of synchronization were Bnei Brak, Beersheba and Haifa, the latter two being geographically remote from all other cities in the dataset and the former geographically very close to several other cities but socially separate due to being populated almost exclusively by ultra-orthodox Jews. Further evidence of assortative mixing of the ultra-orthodox population can be found in the 2001-2002 season, when ultra-orthodox cities and neighborhoods showed distinctly different incidence curves compared to the general population.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951499PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0091909PLOS

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