The rising cost of Long COVID and ME/CFS in Germany (2020 - 2024)

This repository complements our report:

Daniell J, Brand J, Paessler D, Heydecke J, Schoening S, McLennan AK. 2025. The rising cost of Long COVID and ME/CFS in Germany. Hamburg and Karlsruhe: ME/CFS Research Foundation and Risklayer.

Link to report 📄

The report introduces a reproducible framework for modelling the progression of SARS-CoV-2 infections to Long COVID and/or ME/CFS as well as calculating associated costs in Germany. The model simulates the progression of these conditions over time by integrating COVID-19 case data with vaccination rates, reinfection probabilities, and age group distributions. It estimates the resulting health outcomes and uses established risk modelling approaches to quantify associated societal, employer, and personal costs. The scripts provided here implement the simulation and economic estimation methods described in the report, enabling users to replicate key findings, test assumptions, or adapt the model to different contexts.

Repository Structure

• code/ – Contains Python scripts for data processing, simulating the progression of Long COVID and ME/CFS, and cost estimation.
• input/ – Includes input datasets such as adjusted COVID-19 case numbers and vaccination rates for the Python scripts.
• output/ – Stores the results generated by the model (four different pemutations), including simulated case numbers and economic cost estimates.

Case Tracking & Cost Estimation Scripts

The repository contains two primary Python scripts in its code/ directory, each serving a distinct purpose in modelling the progression and economic impact of Long COVID and ME/CFS in Germany.

1. LongCOVID_MECFS_v2025-Part1_CaseTracker.py

Purpose: This script models the progression from acute COVID-19 to Long COVID and ME/CFS cases in Germany over time.

Key Functions:

• Data input: Loads COVID-19 case data and vaccination rates from the input/ directory.
• Case progression modelling: Applies transition probabilities to estimate the number of individuals developing Long COVID and subsequently ME/CFS, considering factors such as age groups, vaccination status, and reinfection rates.
• Temporal analysis: Tracks the evolution of cases from 2020 to 2024, providing insights into trends and patterns over time.
• Output generation: Saves the modelled Long COVID and ME/CFS cases in so-called case trackers (.csv files).

2. LongCOVID_MECFS_v2025-Part2_TotalCostEstimate.py

Purpose: This script calculates the economic impact associated with the projected Long COVID and ME/CFS cases generated by the first script.

Key Functions:

• Data integration: Imports the case trackers which were created in the first script and intergrates daily economic costs which were claculated as part of this study.
• Cost modelling: Applies cost estzimates per case to calculate total economic burden, considering personal, employer, society and medical losses resulting from reduced valueadd and increased expenditure.
• Model permutations: Iterates through different parameter combinations, simulating cases across varying assumptions (age group probabilities and disability ratings).
• Output generation: Exports daily cost breakdowns and related statistics per permutation (.csv files) for reporting and visualisation.

License

The code in this repository is licensed under the MIT License. The data are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

✍️ Attribution

If you use or adapt this work, please cite the original authors and link back to this repository.