Preliminary analysis of the Clificol COVID-19 support project


  • Alexander Tournier Homeopathy Research Institute, London; Institute of Complementary and Integrative Medicine, Faculty of Medicine, University of Bern, Bern, Switzerland
  • Yuen Ying Yvonne Fok Hong Kong Association of Homeopathy



COVID-19, Clificol, Individualization, Cluster analysis, Regression modelling


Background: The Clificol® COVID-19 Support Project is an innovative international project set up during the current crisis to register cases of Covid which received adjunctive homeopathic care. Aims The project aims to describe the demographics, geographic specificities, and time-courses of the cases and shed some light on the notion of Genus Epidemicus in the context of this infection. Beyond this, the project aims to use the data to tackle more fundamental questions in homeopathy, such as the notion of Individualization and the 'Law of Similars’. Methodology: This online multi-national data-collection project receives the support of ECH, ECCH, ICH, HRI, LMHI, and other professional associations; the Governance Committee now consists of 11 representatives, representing 197 associations. The study is designed as an observational study, and standardized consent terms were used to gather anonymized data. The collected data consists of demographic information, severity, conventional diagnosis, treatment, presenting symptoms, and a remedy prescribed at each consultation. The course of the condition is tracked using the ORIDL scale. Besides basic statistics regarding demographics, the notion of Individualisation is investigated by analyzing whether presenting symptoms cluster into tight groups as would be expected by the homeopathic principle of Individualisation (K-Means clustering approach). The connection – Law of Similars – between symptoms and a successful remedy are analyzed using logistic regression modelling (SPSS). Results and discussion: Up-to-date demographic data will be presented at the conference. The preliminary analysis picked up the two most common remedies pictures corresponding to Gelsemium sempervirens (Cluster 1) and Bryonia alba (Cluster 3). Interestingly it found another remedy picture (Cluster 2), which had a much lower success rate (75%) compared to cluster 1 (99%) and 3 (100%). In the preliminary analysis, statistically significant regression models for Gelsemium and Bryonia were built. These show that indeed there is a consistent link – that can be statistically modelled - between sets of symptoms and a successful remedy. With sufficient data, the modelling can be extended to explore the notions of ‘Keynote Symptom’ and ‘Three-Legged Stool’ to see whether such key symptoms or sets of symptoms do indeed come out from the analysis. The approach is limited by the natural inclination of homeopaths to see the symptoms of remedy they think is required in the patient. We hope to be able to use the data to shed some light on this type of bias. Conclusion: The data collected during this pandemic offers a unique opportunity to shed light on some of the core principles of homeopathy. The preliminary analysis is presented to demonstrate the potential of the approach and how powerful it can be provided enough data is gathered. The Clificol COVID-19 data collection project, currently supported by most organizations worldwide, requires more cases to fulfil its ambitious aims.

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