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

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.

Modeling and statistical analysis of the spatio-temporal patterns of seasonal influenza in Israel.

Background: Seasonal influenza outbreaks are a serious burden for public health worldwide and cause morbidity to millions of people each year. In the temperate zone influenza is predominantly seasonal, with epidemics occurring every winter, but the severity of the outbreaks vary substantially between years. In this study we used a highly detailed database, which gave us both temporal and spatial information of influenza dynamics in Israel in the years 1998-2009.

Modelling seasonal influenza in Israel.

Mathematical modeling approaches are used to study the epidemic dynamics of seasonal influenza in Israel. The recent availability of highly resolved ten year timeseries of influenza cases provides an opportunity for modeling and estimating important epidemiological parameters in the Israeli population. A simple but well known SIR discrete-time deterministic model was fitted to consecutive epidemics allowing estimation of the initial number of susceptibles in the population S0, as well as the reproductive number R0 each year.

Onset of a pandemic: characterizing the initial phase of the swine flu (H1N1) epidemic in Israel.

Background: The swine influenza H1N1 first identified in Mexico, spread rapidly across the globe and is considered the fastest moving pandemic in history. The early phase of an outbreak, in which data is relatively scarce, presents scientific challenges on key issues such as: scale, severity and immunity which are fundamental for establishing sound and rapid policy schemes. Our analysis of an Israeli dataset aims at understanding the spatio-temporal dynamics of H1N1 in its initial phase.

[Mathematical models as tools for studying and developing strategies in the case of a pandemic influenza outbreak].

The current spread of swine flu H1N1 raises serious concerns for public health worldwide. Mathematical modelling has proved to be an essential tool for both developing strategies in preparation for an outbreak and for predicting and evaluating the effectiveness of control policies during an outbreak. Given its growing importance, this article outlines some of the fundamental contributions of mathematical modelling in the study of infectious diseases.