Fraction of combinations (two cities and a season) in which incidence curves were found to be significantly different, out of each city's 121 combinations.

<p>Fraction of combinations (two cities and a season) in which incidence curves were found to be significantly different, out of each city's 121 combinations.</p

A map of Israel and the 12 cities analysed in this work.

<p>A map of Israel and the 12 cities analysed in this work.</p

Comparison of Incidence Curves: two examples.

<p><b>Top (A,B):</b> Jerusalem and Holon in the 1999–2000 season. Incidence time series curves (A) are very similar. A period of 120 days containing the largest number of ILI cases (highlighted with a darker band) was used to calculate the likelihood of the observed incidence curves. Histogram of log-likelihoods (B) of 1,000 simulated epidemics (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091909#pone.0091909.e029" target="_blank">equations 20</a>–22) gives a one-sided 95% confidence limit (dashed red line) and the log-likelihood of the real data (solid green line) is very high compared to those of simulated epidemics, indicating that simulated epidemics are less similar than the observed data. <b>Bottom (C,D):</b> Beersheba and Bat Yam in the 2008–2009 season. Dramatic differences in the shape of the incidence curves (C) translate to a very low log-likelihood of the observed epidemic compared to those of simulated ones (D).</p

Estimates for the reporting rate of each city relative to the reporting rate of Tel Aviv (Relative Reporting Rate, RRR) found using the RR/AR model (middle) and the incidence curves comparison method (right).

<p>Estimates for the reporting rate of each city relative to the reporting rate of Tel Aviv (Relative Reporting Rate, RRR) found using the RR/AR model (middle) and the incidence curves comparison method (right).</p

Observed vs. expected attack rates.

<p>Reported attack rates in each city in each season (black) compared to expected results from model fits (red) using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091909#pone.0091909.e007" target="_blank">equations 5</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091909#pone.0091909.e010" target="_blank">6</a>. The expected attack rates in all cities are identical up to a scaling factor of the reporting rate. Note the good fit between the expected and observed attack rates in most cities in most seasons.</p

Correlation matrix of daily incidence rates in all city pairs in 1998–2009.

<p>Correlation matrix of daily incidence rates in all city pairs in 1998–2009.</p

Estimates of the RR/AR model for the attack rate of each season relative to the attack rate of season 1.

<p>Estimates of the RR/AR model for the attack rate of each season relative to the attack rate of season 1.</p

Number of newly-infected corals (NICs).

<p>The red dots represent the number of NICs observed in the field along the studied year. The grey dots represent the median number of NICs as predicted by generating infections according to the SIS epidemic model based on <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004151#pcbi.1004151.e002" target="_blank">Eq 2</a> (see text), and the grey bars represent their 95% confidence interval.</p

Profile likelihood function <i>M</i>(<i>α</i>).

<p>The function is maximized at </p><p></p><p></p><p><mi>α</mi><mo>^</mo></p><p></p><p></p> = 1.9, giving the estimate of parameter <i>α</i>. The insert shows a close up of the 95% CI of <i>α</i> (represented by the red horizontal line).<p></p

Simulated future projections of the local coral community spanning 80 years.

<p>The future projections in panels <b>A</b>, <b>B</b> and <b>C</b> rely on the demographic scenario of constant influx of recruits (64 recruits per year). Panels <b>D</b>, <b>E</b> and <b>F</b> rely on the scenario of free-space regulation of recruitment (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004151#sec016" target="_blank">Material and Methods</a>). Panels <b>A</b> and <b>D</b> are based on the SST time-series measured between June 2006 and May 2007 recurrently from year to year in the corresponding months. Based on this time-series, we generate future projections by adding 0.5°C (panels <b>B</b> and <b>E</b>) and 1°C (panels <b>C</b> and <b>F</b>) to the SST of each month. In these simulations we allow each new recruit to settle randomly anywhere on the 10×10 m plane. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004151#pcbi.1004151.s004" target="_blank">S4 Fig</a> demonstrates robustness of these patterns under mild parameter variations.</p