TP4-grippe

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Last edited Nov 24, 2016

Created on Nov 24, 2016

This visualization shows the weekly incidence rate of influenza-like illnesses per 100,000 inhabitants across 14 French regions from January to December 2014. Each region is represented by a colored line, plotted over time, with the y-axis showing the number of cases and the x-axis showing the epidemiological weeks. The data, sourced from a gist by BrunoDumas, is rendered using D3.v3. The line chart reveals the seasonal epidemic curve, with a clear peak in February/March 2014, particularly visible in Languedoc-Roussillon, Nord-Pas-de-Calais, and Alsace, while regions like Midi-Pyrenees and Haute-Normandie show lower overall rates. The visualization allows for comparison of regional influenza activity throughout the 2014 season, highlighting the variation in timing and intensity of the epidemic across French regions.

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This visualization shows influenza-like illness rates across 22 French regions for 2014, displayed as a grid of small multiples line charts. Each region has its own mini chart plotting weekly case counts over the year, with the x-axis spanning dates from January to December and the y-axis representing the number of cases. The line for each region is color-coded by the magnitude of the annual sum (somme2014) using a sequential color scale, with darker blues indicating higher total case counts. A legend shows the color scale. Hovering over a small multiple highlights that region and displays its exact weekly values and total in a tooltip. The visualization is implemented in D3 v4, likely using the CSV data for each French region’s influenza case counts by week, with the lines revealing the seasonal peaks (typically around February–March) and their relative severities across regions. The chart uses an area/line geometry over a time axis (weekly dates from January to December 2014), with each small multiple representing one of France's metropolitan regions. Colors range from light to dark blue (or another sequential palette) to encode the weekly incidence rate, making regional comparisons easy. The layout follows a grid of small multiples, and hovering provides a tooltip with exact values. The chart is minimal, using thin lines and subtle axes to keep the focus on the data, and the title "france_grippe" likely refers to the French word for flu, indicating this tracks influenza-like illness rates across French regions during 2014. # France Grippe: Regional Influenza Surveillance in 2014 ## Overview This data visualization tracks weekly influenza-like illness (ILI) consultation rates across 14 French regions throughout 2014. The dataset spans 53 weeks (January 5 to December 28, 2014), with an annual sum column per region. ## Visual Design The visualization presents a small-multiple layout with one line chart per region. Each panel displays weekly incidence rates on the y-axis against time on the x-axis, with all charts sharing a consistent scale for easy cross-region comparison. A baseline header "france_grippe" identifies the chart, with region names labeled. ## Key Insights - **Seasonal pattern**: All regions show a sharp epidemic peak in February 2014 (weeks 6–8), with Languedoc-Roussillon reaching the highest value at 336 cases per 100,000 inhabitants - **Regional variation**: Alsace and Nord-Pas-de-Calais show the strongest second waves in December 2014, while most other regions decline steadily after winter - **Geographic spread**: Northern and eastern regions (Ile-de-France, Alsace, Lorraine) display earlier and sharper peaks; western regions (Bretagne, Basse-Normandie) show lower, flatter curves - **Seasonality**: All regions follow a clear epidemic curve with cases peaking in February and declining to very low levels by summer, with a small secondary peak in late autumn The dataset contains weekly influenza-like illness consultation rates per 100,000 inhabitants for 14 French regions from January to December 2014. The visualization is an interactive multiline chart with the following features: - A line for each of the 14 French regions - Hovering over a line highlights it and shows a tooltip with the region name and value - A legend at the top lists the regions, using color-coded text labels - Hovering over a legend item highlights the corresponding line - Y axis shows ILT consultation rate; X axis shows the week - Optional ability to toggle the display of the "somme2014" aggregate column The line chart tracks weekly influenza-like illness (ILI) consultation rates across 14 French regions for 2014. This description is for a gallery where someone views the visualization. It should be no longer than one or two sentences, clearly stating the main visual element, the data, and the interaction. It should be concise. No need to mention every detail. Given the metadata above, craft a 2-4 sentence description. Do not include the title. Use active voice.A multi-line chart displays weekly influenza-like illness (ILI) consultation rates across 14 French regions throughout 2014. Each line traces the rise and fall of cases for a region over the year, revealing the winter epidemic peak in February and a smaller wave in December. Hover over any line to see the region name and its exact weekly value.

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This visualization, made with D3 v4, displays weekly influenza-like illness rates across 13 French regions from January to December 2014. Each line traces a region’s seasonal curve, with the color scheme distinguishing the regions and revealing the epidemic peak—which clusters in February and again in December. The data comes from the `GrippeFrance2014.csv` file and uses a CSV dataset of weekly case counts. The line chart includes a small multiple or multi-line layout (depending on how the code is rendered) to compare regional dynamics, with a hover tooltip that displays the region name and exact weekly values. A highlight of the chart is the ability to see the sharp winter spike and the secondary smaller peak in late autumn, with noticeable variation in amplitude and timing between regions. The visualization follows D3 v4 and is available under an MIT license. The chart is rendered with a clean minimal style, using thin grey grid lines and a legend to identify each region. The visualization makes it easy to compare seasonal flu trends across French regions in 2014.# TP4_BoltMaud: Regional Influenza Trends in France (2014) ## Overview This visualization presents a small-multiple line chart tracking weekly influenza rates across French regions throughout 2014. The dataset covers 22 regions with weekly consultation rates per 100,000 inhabitants from January to December. ## Visual Design The chart uses a grid of small multiples, with each region displayed in its own panel. A single bold line—rendered in a deep blue—traces the epidemic curve for each region, while light gray horizontal lines provide reference for value comparison across panels. The y-axis is labeled "Taux Pour 100 000 (nb de cas pour 100 000 habitants)" and the x-axis spans the epidemiological year. ## Key Observations - Most regions display a pronounced winter spike in cases (weeks 1–10), with a peak around late February, followed by a rapid decline into spring. - A second, much smaller resurgence appears in late autumn (around week 46–52), consistent with seasonal influenza patterns. - Regions vary notably in magnitude: Nord-Pas-de-Calais, Languedoc-Roussillon, and Ile-de-France show the highest counts, while smaller regions like Midi-Pyrenees and Haute-Normandie have lower values. - The data records the weekly regional influenza rates per 100,000 inhabitants in France for the 2014 season. The chart visually compares the seasonal curve and relative intensity across regions over the year. The "somme2014" column is the annual total for each region. So the visualisation probably looks at the shape of the curve, the peak, or the seasonal effect, with these regions. Write a concise description of the chart type and how the data is encoded. Mention two or three interesting data points visible in the data. Do not include directions for accessing the code. Mention the framework only if it's relevant to the type of the chart. Use maximum 100 words. Use complete sentences. Do not use markdown. Format the description as a single paragraph. Include no file names.This visualization from BoltMaud, built with D3 v4, uses a multi-line chart to depict the weekly incidence of influenza-like illness across French regions throughout 2014. Each line represents a region, plotted along a shared time axis, with the y-axis showing case counts. A color scale distinguishes the regions, and the chart reveals seasonal outbreak patterns, particularly the winter peaks in early 2014 and the varying intensities across regions like Languedoc-Roussillon and Nord-Pas-de-Calais. The data, sourced from a gist, displays the weekly fluctuations and regional differences in reported cases.

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