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Systems Modeling Published: March 25, 2024

How Izmir's transit network found its way back after the pandemic

A data-driven analysis of how Izmir's public transport network recovered after COVID-19, and how the rider mix changed along the way.

Municipal ridership records Monthly recovery modeling Linked React chart system Astro reporting flow
How Izmir's transit network found its way back after the pandemic

Story Snapshot

Start with the graphic

A recovery analysis of Izmir's transit system built from four years of open data, showing not only when ridership returned but which fare groups came back first.

19K+ Records analyzed
2021-2024 Time window
2 Linked views

Izmir’s transit recovery was not only about total riders returning. The useful question is which modes and fare groups came back first, and how that changed the shape of the network.

Recovery timeline

How ridership returned, and who returned first

The upper chart compares mode recovery against January 2021. The lower chart shows which fare groups rebuilt the system month by month.

Index mode makes recovery pace visible before raw trip volume takes over.

Use the Index/Trips and Share/Trips toggles, then move through months in either chart.

Mar 202438.7MTram leads the selected month

Selected month summary

Mar 2024: 38.7M total trips.

Tram ranks first, indexed at 296 from January 2021.

Index view · Share mix
0%1807%3614%5476%Jan 2021Jan 2022Jan 2023Jan 2024Mar 2024
Metro
Tram
IZBAN commuter rail
Other
Bus (ESHOT, IZULAS, etc.)
Ferry (IZDENIZ)
0%50%100%Jan 2021Jan 2022Jan 2023Jan 2024Mar 2024
Full fare
Student
Teacher
60+
Free
Other

Selected fare composition

In Mar 2024, the lower view shows whether the rebound was driven more by students, full-fare riders, or the smaller concession groups.

Full fare35.5%
Student37.5%
Teacher0.6%
60+1.8%
Free18.7%
Other5.9%
Selected monthMar 2024
Network total38.7M

Mode ranking

Index mode normalizes each transport mode to its January 2021 starting point. Share mode strips out total volume so the student rebound can be read as a compositional shift rather than just a larger month.
Hover or click any month to lock both views.

What to notice

  • Buses remain the volume backbone, while rail modes show sharper recovery curves when normalized to their 2021 baseline.
  • Student travel becomes easier to read in share mode because the chart stops letting total month size dominate the frame.
  • The recovery is a systems story: mode volume and rider mix change together, not in separate timelines.

Data source: Izmir Metropolitan Municipality Open Data Portal Note: Interactive visualizations are built as native React views so recovery totals and rider mix can be read on the same monthly timeline.

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