FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Pathogens / Relationship Between Mean Faecal Gastrointestinal Nematode E...
Pathogens (Basel, Switzerland)2026; 15(2); 156; doi: 10.3390/pathogens15020156

Relationship Between Mean Faecal Gastrointestinal Nematode Egg Excretion in Horses and Its Variability: Implications for Control.

Abstract: Faecal egg counts (FECs) are used to assess the intensity of gastrointestinal nematode (GIN) infections in herbivores. FEC distribution is aggregated, meaning that approximately 20% of animals harbour 80% of infections. In times of escalating anthelmintic resistance, it may be necessary to restrict treatment to the animals with the heaviest infections. This strategy is called targeted selective treatment (TST) and is relevant to GIN, for example. The difficulty lies in identifying which animals to treat. One solution is to select potentially at-risk animals based on age (for example, treating the young) or to perform individual faecal egg counts (though this is costly). We propose a solution for determining the suitability of selective treatment based on the level of FEC (200 or 500 eggs per gram of faeces). First, we demonstrated that the mean FEC in a group is strictly related to its variance (Taylor's power law) using published data and our own unpublished data on horses from France, Poland, and Mexico. The study focused on small and large strongyles in horses. Taylor's power law states that sample variance (Var) and the population mean are related by a simple equation: Var = a Mean^b or log(Var) = log(a) + b log(Mean). The influence of factors such as age, status (mare, stallion, yearling, etc.), day-to-day variability, and previous anthelmintic treatments did not alter this relationship. To reduce the number of FECs, we estimated the mean FEC on a composite faecal sample. We then calculated the variability and therefore the number of horses with an FEC above the chosen acceptable level. When the mean is high, the number of horses to be treated is also high and TST is not beneficial. When the FEC is average, TST may be worthwhile, either based on the FEC of individual horses or on the horse class at risk. Based on the percentage of horses with an FEC above the acceptable level, farmers can decide whether to treat all animals or establish a TST protocol. Caution should be exercised when using TST in the presence of large strongyles.
Get Full Text
Publication Date: 2026-02-02 PubMed ID: 41754409PubMed Central: PMC12942807DOI: 10.3390/pathogens15020156Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Overview

  • This study investigates the relationship between the average faecal egg count (FEC) of gastrointestinal nematodes in horses and the variability of these counts, aiming to inform targeted treatment strategies to control parasite infections.
  • By understanding this relationship, the research provides guidance on when selective treatment of only high-infection horses is effective versus when treating all animals might be necessary.

Background

  • Gastrointestinal nematode (GIN) infections in herbivores, including horses, are commonly assessed via faecal egg counts (FECs), which measure the number of nematode eggs per gram of faeces.
  • FEC data tend to be aggregated, meaning a small proportion of animals typically carry the majority of the parasite burden (approximately 20% of horses carry 80% of infections).
  • Anthelmintic resistance (resistance to deworming drugs) is increasing, making it important to reduce unnecessary treatments and strategically target only the animals with heavy infections.
  • Targeted selective treatment (TST) is a strategy that treats only the horses with the highest FECs, potentially limiting drug use and slowing resistance development.

The Challenge

  • The primary difficulty in applying TST is identifying which horses need treatment without testing every individual—testing all horses is costly and labor-intensive.
  • Approaches like treating based on age or other risk factors are commonly used, but may not always perfectly identify the heaviest infections.
  • This research seeks a method to evaluate when selective treatment is suitable based on the mean FEC and its variability within a group.

Key Methods and Findings

  • Data were collected from both published sources and new, unpublished datasets involving horses from France, Poland, and Mexico, focusing on infections with small and large strongyles—common nematodes in horses.
  • The study examined the relationship between the mean FEC and the variance in FEC within groups of horses, using Taylor’s power law, which states the variance in counts relates to the mean by a power function: Var = a Mean^b.
  • In logarithmic terms: log(Var) = log(a) + b log(Mean), verifying this relationship supports predictability of variance based on mean values.
  • This relationship held true regardless of variables including age, sex, daily fluctuations in egg excretion, and prior anthelmintic treatments.
  • To reduce testing effort, the researchers estimated the mean FEC from composite faecal samples created by pooling individual samples, which still allowed them to estimate the variability and identify how many horses might exceed a particular FEC threshold.

Implications for Treatment Strategies

  • When the average FEC in a group is high, many horses have counts above the threshold, meaning that most animals would need treatment—making TST less beneficial compared to treating all horses.
  • When the average FEC is moderate or low, TST becomes more valuable, because it is possible to accurately identify and treat only the small subset of heavily infected horses.
  • Farmers can use the estimated percentage of horses exceeding the chosen FEC threshold (e.g., 200 or 500 eggs per gram) to decide whether it is cost-effective and epidemiologically sound to apply TST or to treat the entire group.
  • Particular caution is advised when large strongyles are present, as the risk profile and control strategies may differ, implying TST might not be appropriate.

Conclusions

  • The study provides a valuable practical tool by linking mean FEC levels to infection spread within groups, enabling better-informed decisions on parasite control strategies.
  • It highlights the potential to reduce unnecessary anthelmintic use by selectively treating animals in groups with moderate infection levels, thereby mitigating resistance risk and treatment costs.
  • The approach using composite samples for mean FEC estimation could lower diagnostic costs while still providing actionable data on population-level parasite burdens.
  • Overall, this research supports more sustainable parasite management practices in equine populations through informed application of targeted selective treatment based on scientifically grounded variability analysis.

Cite This Article

APA
Cabaret J, Guerrero Molina C, Martínez-Ortiz-de Montellano C, Alcala Canto Y. (2026). Relationship Between Mean Faecal Gastrointestinal Nematode Egg Excretion in Horses and Its Variability: Implications for Control. Pathogens, 15(2), 156. https://doi.org/10.3390/pathogens15020156

Publication

Pathogens (Basel, Switzerland)
ISSN: 2076-0817
NlmUniqueID: 101596317
Country: Switzerland
Language: English
Volume: 15
Issue: 2
PII: 156

Researcher Affiliations

Cabaret, Jacques
  • SantéSocioVéto, 8 Pl. Carré de Busserolle, 37100 Tours, France.
Guerrero Molina, Cristina
  • Departamento de Parasitologia, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autonoma de Mexico (UNAM), Ciudad de Mexico 04510, Mexico.
Martínez-Ortiz-de Montellano, Cintli
  • Departamento de Parasitologia, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autonoma de Mexico (UNAM), Ciudad de Mexico 04510, Mexico.
Alcala Canto, Yazmin
  • Departamento de Parasitologia, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autonoma de Mexico (UNAM), Ciudad de Mexico 04510, Mexico.

MeSH Terms

  • Animals
  • Horses
  • Feces / parasitology
  • Parasite Egg Count
  • Nematode Infections / veterinary
  • Nematode Infections / parasitology
  • Nematode Infections / drug therapy
  • Horse Diseases / parasitology
  • Horse Diseases / drug therapy
  • Nematoda / isolation & purification
  • Anthelmintics / therapeutic use

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 49 references
  1. Poulin R. Are there general laws in parasite ecology?. Parasitology 2007;134:763–776.
    doi: 10.1017/S0031182006002150pubmed: 17234043google scholar: lookup
  2. Gaba S, Ginot V, Cabaret J. Modelling macroparasite aggregation using a nematode-sheep system: The Weibull distribution as an alternative to the negative binomial distribution?. Parasitology 2005;131:393–401.
    doi: 10.1017/S003118200500764Xpubmed: 16178361google scholar: lookup
  3. Relf VE, Morgan ER, Hodgkinson JE, Matthews JB. Helminth egg excretion with regard to age, gender and management practices on UK Thoroughbred studs. Parasitology 2013;140:641–652.
    doi: 10.1017/S0031182012001941pubmed: 23351718google scholar: lookup
  4. Kaplan RM, Nielsen MK. An evidence-based approach to equine parasite control: It ain’t the 60s anymore. Equine Vet. Educ. 2010;22:306–316.
    doi: 10.1111/j.2042-3292.2010.00084.xgoogle scholar: lookup
  5. Morrill A, Poulin R, Forbes MR. Interrelationships a, d properties of parasite aggregation measures: A user’s guide. Int. J. Parasitol. 2023;53:763–776.
    doi: 10.1016/j.ijpara.2023.06.004pubmed: 37467873google scholar: lookup
  6. Barger IA. The statistical distribution of trichostrongylid nematodes in grazing lambs. Int. J. Parasitol. 1985;15:645–649.
    doi: 10.1016/0020-7519(85)90010-4pubmed: 4093237google scholar: lookup
  7. Boag B, Hackett CA, Topham PB. The use of Taylor’s Power Law to describe the aggregated distribution of gastro-intestinal nematodes of sheep. Int. J. Parasitol. 1992;22:267–270.
    doi: 10.1016/S0020-7519(05)80003-7pubmed: 1639561google scholar: lookup
  8. Taylor LR. Aggregation, variance, and the mean. Nature 1961;189:732–735.
    doi: 10.1038/189732a0google scholar: lookup
  9. Smith HF. An empirical law describing heterogeneity in the yields of agricultural crops. J. Agric. Sci. 1938;28:1–23.
    doi: 10.1017/S0021859600050516google scholar: lookup
  10. Taylor RA. Taylor’s Power Law: Order and Pattern in Nature. Academic Press; London, UK: 2019. 640p.
  11. Morgan ER, Segonds-Pichon A, Ferté H, Duncan P, Cabaret J. Anthelmintic Treatment and the Stability of Parasite Distribution in Ruminants. Animals 2023;13:1882.
    doi: 10.3390/ani13111882pmc: PMC10251989pubmed: 37889834google scholar: lookup
  12. Murphy D, Love S. The pathogenic effects of experimental cyathostome infections in ponies. Vet. Parasitol. 1997;70:99–110.
    doi: 10.1016/S0304-4017(96)01153-3pubmed: 9195714google scholar: lookup
  13. Kilani M, Chermette R, Guillot J, Polack B, Duncan JL, Cabaret J. Infectious and Parasitic Diseases of Livestock. 2. Bacterial Diseases, Fungal Diseases, Parasitic Diseases. Tec & Toc Lavoisier; Paris, France: 2010. Gastrointestinal nematodes; pp. 1481–16003.
  14. Kaplan RM. Anthelmintic resistance in nematodes of horses. Vet. Res. 2002;33:491–507.
    doi: 10.1051/vetres:2002035pubmed: 12387486google scholar: lookup
  15. Silva PA, Cernea M, Madeira de Carvalho L. Anthelmintic Resistance in Equine Nematodes-A Review on the Current Situation, with Emphasis in Europe. Bull. Univ. Agric. Sci. Vet. 2019;76.
    doi: 10.15835/buasvmcn-vm:2019.0028pmc: PMC7160458pubmed: 32313376google scholar: lookup
  16. Uriarte J, Cabaret J, Tanco JA. The distribution and abundance of parasitic infections in sheep grazing on irrigated or on non-irrigated pastures in North-Eastern Spain. Ann. De Rech. Vétérinaires 1985;16:321–325.
    pubmed: 4091485
  17. Duncan JL, Love S. Preliminary observations on an alternative strategy for the control of horse strongyles. Equine Vet. J. 1991;23:226–228.
    doi: 10.1111/j.2042-3306.1991.tb02762.xpubmed: 1909236google scholar: lookup
  18. Gomez HH, Georgi JR. Equine helminth infections: Control by selective chemotherapy. Equine Vet. J. 1991;23:198–200.
    doi: 10.1111/j.2042-3306.1991.tb02754.xpubmed: 1884701google scholar: lookup
  19. Nielsen MK. Sustainable equine parasite control: Perspectives and research needs. Vet. Parasitol. 2012;185:32–44.
    doi: 10.1016/j.vetpar.2011.10.012pubmed: 22055611google scholar: lookup
  20. Pfister K, van Doorn D. New perspectives in equine intestinal parasitic disease: Insights in monitoring helminth infections. Vet. Clin. North America. Equine Pract. 2018;34:141–153.
    doi: 10.1016/j.cveq.2017.11.009pubmed: 29426708google scholar: lookup
  21. Matthee S, McGeoch MA. Helminths in horses: Use of selective treatment for the control of strongyles. J. S. Afr. Vet. Assoc. 2004;75:129–136.
    doi: 10.4102/jsava.v75i3.468pubmed: 15628805google scholar: lookup
  22. Becher AM, Mahling M, Nielsen MK, Pfister K. Selective anthelmintic therapy of horses in the Federal states of Bavaria (Germany) and Salzburg (Austria): An investigation into strongyle egg shedding consistency. Vet. Parasitol. 2010;171:116–122.
    doi: 10.1016/j.vetpar.2010.03.001pubmed: 20356680google scholar: lookup
  23. Lüthin S, Zollinger A, Basso W, Bisig M, Caspari N, Eng V, Frey CF, Grimm F, Igel P, Lüthi S. Strongyle faecal egg counts in Swiss horses: A retrospective analysis after the introduction of a selective treatment strategy. Vet. Parasitol. 2023;323:110027.
    doi: 10.1016/j.vetpar.2023.110027pubmed: 37837729google scholar: lookup
  24. Jürgenschellert L, Krücken J, Bousquet E, Bartz J, Heyer N, Nielsen MK, von Samson-Himmelstjerna G. Occurrence of strongylid nematode parasites on horse farms in Berlin and Brandenburg, Germany, with high seroprevalence of Strongylus vulgaris infection. Front. Vet. Sci. 2022;9:892920.
    doi: 10.3389/fvets.2022.892920pmc: PMC9226773pubmed: 35754549google scholar: lookup
  25. Sallé G, Cortet J, Koch C, Reigner F, Cabaret J. Economic assessment of FEC-based targeted selective drenching in horses. Vet. Parasitol. 2015;214:159–166.
    doi: 10.1016/j.vetpar.2015.09.006pubmed: 26414907google scholar: lookup
  26. Vineer HR, Vande Velde F, Bull K, Claerebout E, Morgan ER. Attitudes towards worm egg counts and targeted selective treatment against equine cyathostomins. Prev. Vet. Med. 2017;144:66–74.
    doi: 10.1016/j.prevetmed.2017.05.002pubmed: 28716205google scholar: lookup
  27. Kornaś S, Cabaret J, Skalska M, Nowosad B. Horse infection with intestinal helminths in relation to age, sex, access to grass and farm system. Vet. Parasitol. 2010;174:285–291.
    doi: 10.1016/j.vetpar.2010.09.007pubmed: 20933334google scholar: lookup
  28. Pagnon R. Résistance aux Anthelminthiques des Strongles Chez les Equidés: Enquête Dans un Centre Equestre du Sud de la France. Ph.D. Thesis. Université de Toulouse; Toulouse, France: 2005. 121p.
  29. Kaplan RK, Denwood MJ, Nielsen MK, Thamsborg SM, Torgerson PR, Gilleard JS, Dobson RJ, Vercruysse J, Levecke B. World Association for the Advancement of Veterinary Parasitology (W.A.A.V.P.) guideline for diagnosing anthelmintic resistance using the faecal egg count. reduction test in ruminants, horses and swine. Vet. Parasitol. 2023;318:109936.
    doi: 10.1016/j.vetpar.2023.109936pubmed: 37121092google scholar: lookup
  30. Henriksen SA, Korsholm H. A method for culture and recovery of gastrointestinal strongyle larvae. Nordisk Vet. Med. 1983;35:429–430.
    pubmed: 6672763
  31. Amer M.M., Desouky A.Y., Helmy N.M., Abdou A.M., Sorour S.S.. Identifying 3rd larval stages of common strongylid and non-strongylid nematodes (class: Nematoda) infecting Egyptian equines based on morphometric analysis.. BMC Vet. Res. 2022;18:432.
    doi: 10.1186/s12917-022-03526-8pmc: PMC9743504pubmed: 36503529google scholar: lookup
  32. Eisler Z., Bartos I., Kertész J.. Fluctuation scaling in complex systems: Taylor’s law and beyond.. Adv. Phys. 2008;57:89–142.
    doi: 10.1080/00018730801893043google scholar: lookup
  33. Johnson P.T.J., Wilber M.Q.. Biological and statistical processes jointly drive population aggregation: Using host–parasite interactions to understand Taylor’s power law.. Proc. R. Soc. B. 2017;284:20171388.
    doi: 10.1098/rspb.2017.1388pmc: PMC5627205pubmed: 28931738google scholar: lookup
  34. McVinish R., Lester R.J.G.. Measuring aggregation in parasite populations.. J. R. Soc. Interface. 2020;17:20190886.
    doi: 10.1098/rsif.2019.0886pmc: PMC7211486pubmed: 32289241google scholar: lookup
  35. Tinsley R.C., Vineer H.R., Grainger-Wood R., Morgan E.R.. Heterogeneity in helminth infections: Factors influencing aggregation in a simple host–parasite system.. Parasitology. 2020;147:65–77.
    doi: 10.1017/S003118201900129Xpmc: PMC10317700pubmed: 31488226google scholar: lookup
  36. Galvani A.P.. Immunity, antigenic heterogeneity, and aggregation of helminth parasites.. J. Parasitol. 2003;89:232–241.
    doi: 10.1645/0022-3395(2003)089[0232:IAHAAO]2.0.CO;2pubmed: 12760634google scholar: lookup
  37. Boag B., Lello J., Fenton A., Tompkins D.M., Hudson P.J.. Patterns of parasite aggregation in the wild European rabbit (Oryctolagus cuniculus). Int. J. Parasitol. 2001;31:1421–1428.
    doi: 10.1016/S0020-7519(01)00270-3pubmed: 11595228google scholar: lookup
  38. Morgan E.R., Cavill L., Curry G.E., Wood R.M., Mitchell E.S.E.. Effects of aggregation and sample size on composite faecal egg counts in sheep.. Vet. Parasitol. 2005;131:79–87.
    doi: 10.1016/j.vetpar.2005.04.021pubmed: 15921855google scholar: lookup
  39. Eysker M., Bakker J., Van Den Berg M., Van Doorn D.C.K., Ploeger H.W.. The use of age-clustered pooled faecal samples for monitoring worm control in horses.. Vet. Parasitol. 2008;151:249–255.
    doi: 10.1016/j.vetpar.2007.10.008pubmed: 18037244google scholar: lookup
  40. Nielsen M.K., Baptiste K.E., Tolliver S.C., Collins S.S., Lyons E.T.. Analysis of multiyear studies in horses in Kentucky to ascertain whether counts of eggs and larvae per gram of feces are reliable indicators of numbers of strongyles and ascarids present.. Vet. Parasitol. 2010;174:77–84.
    doi: 10.1016/j.vetpar.2010.08.007pubmed: 20850927google scholar: lookup
  41. Martínez-Ortiz de Montellano C., González-Reyes L., Toledo-Alvarado H.O.. Epidemiological patterns of cyathostominae burden in Warmblood horses in Mexico.. WAAVP 2025; Proceedings of the 30th Conference of the World Association for the Advancements of Veterinary Parasitology Curitiba, Brazil. 17–21 August 2025; pp. 61–62.
  42. Matthews J.B.. Anthelmintic resistance in equine nematodes.. Int. J. Parasitol. Drugs Drug Resist. 2014;4:310–315.
    doi: 10.1016/j.ijpddr.2014.10.003pmc: PMC4266799pubmed: 25516842google scholar: lookup
  43. Nielsen M.K., Mittel L., Grice A., Erskine M., Graves E., Vaala W., Tully R.C., French D.D.. AAEP Parasite Control Guidelines.. 2013.
  44. Rendle D., Austin C., Bowen M., Cameron I., Furtado T., Hodgkinson J., McGorum B., Matthews J.. Equine de-worming: A consensus on current best practice.. UK-Vet Equine 2019;3:1–14.
    doi: 10.12968/ukve.2019.3.S.3google scholar: lookup
  45. Wilkes E.J.A., Woodgate R.G., Raidal S.L., Hughes K.J.. The application of faecal egg count results and statistical inference for clinical decision making in foals.. Vet. Parasitol. 2019;270:7–12.
    doi: 10.1016/j.vetpar.2019.04.010pubmed: 31213242google scholar: lookup
  46. Denwood M.J., Love S., Innocent G.T., Matthews L., McKendrick I.J., Hillary N., Reid S.W.J.. Quantifying the sources of variability in equine faecal egg counts: Implications for improving the utility of the method.. Vet. Parasitol. 2012;188:120–126.
    doi: 10.1016/j.vetpar.2012.03.005pubmed: 22469484google scholar: lookup
  47. Lester H.E., Morgan E.R., Hodgkinson J.E., Matthews J.B.. Analysis of strongyle egg shedding consistency in horses and factors that affect it.. J. Equine Vet. Sci. 2018;60:113–119.
    doi: 10.1016/j.jevs.2017.04.006google scholar: lookup
  48. Kuzmina T.A., Lyons E.T., Tolliver S.C., Dzeverin I.I., Kharchenko V.A.. Fecundity of various species of strongylids (Nematoda: Strongylidae)—Parasites of domestic horses.. Parasitol. Res. 2012;111:2265–2271.
    doi: 10.1007/s00436-012-3077-5pubmed: 22903448google scholar: lookup
  49. Fleurance G., Martin-Rosset W., Dumont B., Duncan P., Farrugia A., Lecomte T.. Environmental impact of horses.. In: Martin-Rosset W., editor. Equine nutrition. Wageningen Academic Publishers; Wageningen, The Netherlands: 2013. pp. 481–504.

Citations

This article has been cited 0 times.
Subscribe to our newsletter
Join 99,000 horse owners like you who receive our email updates on horse health and nutrition.