Number of outbreaks by healthcare setting and reporting healthcare facility, Germany, 1 November 2011 to 31 October 2012.

<p>Note: Percentages may not add up to 100% due to rounding. Multidrug resistant organisms (MDROs).</p

Pathogens identified in reported HAI-outbreaks (n = 578), Germany, 1 November 2011 to 31 October 2012.

<p>Median and range as min. and max. within outbreaks. Note: Numbers of colonised, symptomatic infected and fatalities may not add up to number of all cases (see discussion). Percentages may not add up to total 100% due to rounding.</p

Number of outbreaks by reporting hospital ward, Germany; 1 November 2011 to 31 October 2012.

<p>Note: Percentages may not add up to 100% due to rounding. Multidrug resistant organisms (MDROs).</p

Number of received notifications and their relation to outbreaks matching the case definition – Mandatory outbreak reporting in Germany, 1 November 2011 to 31 October 2012.

<p>Number of received notifications and their relation to outbreaks matching the case definition – Mandatory outbreak reporting in Germany, 1 November 2011 to 31 October 2012.</p

Monthly outbreaks – Mandatory outbreak reporting in Germany, 1 November 2011 to 31 October 2012.

<p>Monthly outbreaks – Mandatory outbreak reporting in Germany, 1 November 2011 to 31 October 2012.</p

Monthly distribution of laboratory positive dengue cases during epidemic and non epidemic years.

<p>A strong seasonality in the dengue cases distribution was observed during epidemic years with outbreaks occurring usually between January and July. By contrast, dengue cases occurred almost every month without a clear seasonal pattern during non epidemic years.</p

Epidemiology of dengue fever and evolution of annual mean temperature in Noumea-New Caledonia (1971–2010).

<p>The predominant circulating serotype (DENV-1, DENV-2, DENV-3 or DENV-4) is indicated in black characters. When other serotypes were detected, they are indicated in little grey characters. Annual dengue incidence rates observed in Noumea over the 1995–2010 period are highly correlated with dengue incidence rates observed in New Caledonia (Spearman coefficient <i>rho</i> = 0.99, <i>p</i>-value = 1*10⁻¹⁴). Annual dengue incidence rates in Noumea (1971–1994) were estimated (green dotted line with circles) on the basis of the relationship between incidence rates observed in New Caledonia (grey line) and those observed in Noumea (blue dotted line with crosses) using a linear model. During the 1971–2010 period, dengue incidence rates and annual mean temperatures (from January to December) were significantly correlated in Noumea (Spearman's coefficient <i>rho</i> = 0.426, <i>p</i>-value = 0.007). An increasing trend of dengue outbreaks amplitude and annual mean temperatures were observed during this 40-year study period.</p

Relationship between maximal temperatures and dengue outbreaks in Noumea.

<p>Averages and 95% confidence intervals (IC95%) of max Temp (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001470#pntd-0001470-g004" target="_blank">Figure 4a</a>) and NOD_max Temp_32 (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001470#pntd-0001470-g004" target="_blank">Figure 4b</a>) calculated monthly during epidemic and non epidemic years were compared from August (year <i>y</i>-1) to July (year <i>y</i>). The peak of max Temp preceded the epidemic peak of dengue with a lag of 1–2 months. The number of days with max Temp exceeding 32°C during the first quarter of the year was significantly higher during epidemic years than during non epidemic years, especially in February (NOD_max Temp_32_February = 7.25 versus 2 days, respectively).</p

SVM explicative model of dengue outbreaks in Noumea (leave-one-out cross validation).

<p>The model estimates the probability of dengue outbreak occurrence (red bars) each year according to the number of days with maximal temperature exceeding 32°C during the first quarter of the year (NOD_max Temp_32_JFM), and the number of days with maximal relative humidity exceeding 95% during January (NOD_max RH_95_January). Results obtained in leave-one-out cross validation are presented in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001470#pntd-0001470-g005" target="_blank">Figure 5a</a>. The black line indicates the annual dengue incidence rate, and black diamonds indicate epidemic years according to the median method. The ROC curve (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001470#pntd-0001470-g005" target="_blank">Figure 5b</a>) indicates the rates of true and false positives for different detection thresholds. For example, for a probability of dengue outbreak above 65% (0.65), 15 of 20 epidemic years are predicted correctly (true positive rate = 75%) with only one false alarm (false positive rate = 5%). The sensitivity of the model for this threshold is 75% (15 epidemic years predicted correctly/20 epidemic years), the specificity 95% (19 non epidemic years predicted correctly/20 non epidemic years), the positive predictive value 94% (15 epidemic years predicted correctly/16 epidemic years predicted by the model), and the negative predictive value 79% (19 non epidemic years predicted correctly/24 non epidemic years predicted by the model).</p

SVM predictive model of dengue outbreaks in Noumea (leave-one-out cross validation).

<p>The model estimates the probability of dengue outbreak occurrence (red bars) each year <i>y</i> according to the quarterly mean of maximal relative humidity during October–November–December (max RH_OND), and the monthly mean of maximal temperature in December (max Temp_December) year <i>y</i>-1. Results obtained in leave-one-out cross validation are presented in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001470#pntd-0001470-g007" target="_blank">Figure 7a</a>. The black line indicates the annual dengue incidence rate, and black diamonds indicate epidemic years according to the median method. The ROC curve (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001470#pntd-0001470-g007" target="_blank">Figure 7b</a>) indicates the rates of true and false positives for different detection thresholds. For example, for a probability of dengue outbreak above 65% (0.65), 11 of 20 epidemic years were predicted correctly (true positive rate = 55%) with three false alarms (false positive rate = 15%). The sensitivity of this model for this threshold is 55% (11 epidemic years predicted correctly/10 epidemic years), the specificity 85% (17 non epidemic years predicted correctly/20 non epidemic years), the positive predictive value 79% (11 epidemic years predicted correctly/14 epidemic years predicted by the model), and the negative predictive value 65% (17 non epidemic years predicted correctly/26 non epidemic years predicted by the model).</p