Equine strongylid parasites are ubiquitous around the world and are main targets of parasite control programmes. In recent years, automated fecal egg counting systems based on image analysis have become available allowing for collection and analysis of large-scale egg count data. This study aimed to evaluate equine strongylid fecal egg count (FEC) data generated with an automated system over three years in the US with specific attention to seasonal and regional trends in egg count magnitude and sampling activity. Five US regions were defined; North East, South East, North Central, South Central and West. The data set included state, region and zip code for each FEC. The number of FECs falling in each of the following categories were recorded: (1) 0 eggs per gram (EPG), (2) 1 ⩽ 200 EPG, (3) 201 ⩽ 500 EPG and (4) >500 EPG. The data included 58 329 FECs. A fixed effects model was constructed fitting the number of samples analysed per month, year and region, and a mixed effects model was constructed to fit the number of FECs falling in each of the 4 egg count categories defined above. The overall proportion of horses responsible for 80% of the total FEC output was 18.1%, and this was consistent across years, months and all regions except West, where the proportion was closer to 12%. Statistical analyses showed significant seasonal trends and regional differences of sampling frequency and FEC category. The data demonstrated that veterinarians tended to follow a biphasic pattern when monitoring strongylid FECs in horses, regardless of location.