Background: Ehrlichia ruminantium is the causal agent of heartwater, a fatal tropical disease affecting ruminants with important economic impacts. This bacterium is transmitted by Amblyomma ticks and is present in sub-Saharan Africa, islands in the Indian Ocean and the Caribbean, where it represents a threat to the American mainland. Methods: An automated DNA extraction method was adapted for Amblyomma ticks and a new qPCR targeting the pCS20 region was developed to improve E. ruminantium screening capacity and diagnosis. The first step in the preparation of tick samples, before extraction, was not automated but was considerably improved by using a Tissue Lyser. The new pCS20 Sol1 qPCR and a previously published pCS20 Cow qPCR were evaluated with the OIE standard pCS20 nested PCR. Results: pCS20 Sol1 qPCR was found to be more specific than the nested PCR, with a 5-fold increase in sensitivity (3 copies/reaction vs 15 copies/reaction), was less prone to contamination and less time-consuming. As pCS20 Sol1 qPCR did not detect Rickettsia, Anasplasma and Babesia species or closely related species such as Panola Mountain Ehrlichia, E. chaffeensis and E. canis, its specificity was also better than Cow qPCR. In parallel, a tick 16S qPCR was developed for the quality control of DNA extraction that confirmed the good reproducibility of the automated extraction. The whole method, including the automated DNA extraction and pCS20 Sol1 qPCR, was shown to be sensitive, specific and highly reproducible with the same limit of detection as the combined manual DNA extraction and nested PCR, i.e. 6 copies/reaction. Finally, 96 samples can be tested in one day compared to the four days required for manual DNA extraction and nested PCR. Conclusions: The adaptation of an automated DNA extraction using a DNA/RNA viral extraction kit for tick samples and the development of a new qPCR increased the accuracy of E. ruminantium epidemiological studies, as well as the diagnostic capabilities and turn-over time for surveillance of heartwater. This new method paves the way for large-scale screening of other bacteria and viruses in ticks as well as genetic characterization of ticks and tick-pathogen coevolution studies. (Résumé d'auteur)