Evidence map›Paper›PMID 23056192›Full record

ArticlePloS one2012

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

Amit Huppert, Oren Barnea, Guy Katriel, Rami Yaari, Uri Roll, Lewi Stone

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Amit HuppertThe Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, Israel.
Oren Barnea
Guy Katriel
Rami Yaari
Uri Roll
Lewi Stone

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeasonal 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. We use a discrete-time stochastic epidemic SIR model to find estimates and credible confidence intervals of key epidemiological parameters.

findingsDespite the biological complexity of the disease we found that a simple SIR-type model can be fitted successfully to the seasonal influenza data. This was true at both the national levels and at the scale of single cities.The effective reproductive number R(e) varies between the different years both nationally and among Israeli cities. However, we did not find differences in R(e) between different Israeli cities within a year. R(e) was positively correlated to the strength of the spatial synchronization in Israel. For those years in which the disease was more "infectious", then outbreaks in different cities tended to occur with smaller time lags. Our spatial analysis demonstrates that both the timing and the strength of the outbreak within a year are highly synchronized between the Israeli cities. We extend the spatial analysis to demonstrate the existence of high synchrony between Israeli and French influenza outbreaks.

conclusionsThe data analysis combined with mathematical modeling provided a better understanding of the spatio-temporal and synchronization dynamics of influenza in Israel and between Israel and France. Altogether, we show that despite major differences in demography and weather conditions intra-annual influenza epidemics are tightly synchronized in both their timing and magnitude, while they may vary greatly between years. The predominance of a similar main strain of influenza, combined with population mixing serve to enhance local and global influenza synchronization within an influenza season.

Indexed as

Models, BiologicalSeasonsAlgorithmsAnalysis of VarianceDatabases, FactualDisease OutbreaksFranceHumansIncidenceInfluenza, HumanIsraelSpatial AnalysisTime Factors

Identifiers

PMID23056192
PMCPMC3466289

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.