Human gnathostomiasis: A review on the biology of the parasite with special reference on the current therapeutic management

Gnathostoma is a parasitic nematode that can infect a wide range of animal species, but human populations have become accidental hosts because of their habit of eating raw or undercooked meat from a wide variety of intermediate hosts. While gnathostomiasis is considered an endemic disease, cases of human gnathostomiasis have been increasing over time, most notably in nonendemic areas. There are several complexities to this parasitic disease, and this review provides an update on human gnathostomiasis, including the life cycle, diagnosis, treatment, and treatment strategies used to combat drug resistance. Even now, a definitive diagnosis of gnathostomiasis is still challenging because it is difficult to isolate larvae for parasitological confirmation. Another reason is the varying clinical symptoms recorded in reported cases. Clinical cases can be confirmed by immunodiagnosis. For Gnathosotoma spinigerum, the detection of IgG against a specific antigenic band with a molecular weight of 24 kDa from G. spinigerum advanced third-stage larvae (aL3), while for other species of Gnathostoma including G. binucleatum, the 33-kDa antigen protein is being used. This review also discusses cases of recurrence of gnathostomiasis and resistance mechanisms to two effective chemotherapeutics (albendazole and ivermectin) used against gnathostomiasis. This is significant, especially when planning strategies to combat anthelmintic resistance. Lastly, while no new chemotherapeutics against gnathostomiasis have been made available, we describe the management of recurrent gnathostomiasis using albendazole and ivermectin combinations or extensions of drug treatment plans.

A statistical framework for calculating prospective sample sizes and classifying efficacy results for faecal egg count reduction tests in ruminants, horses and swine

The faecal egg count reduction test (FECRT) is the primary diagnostic tool used for detecting anthelmintic resistance at the farm level. It is therefore extremely important that the experimental design of a FECRT and the susceptibility classification of the result use standardised and statistically rigorous methods. Several different approaches for improving the analysis of FECRT data have been proposed, but little work has been published on how to address the issue of prospective sample size calculations. Here, we provide a complete and detailed overview of the quantitative issues relevant to a FECRT starting from basic statistical principles. We then present a new approach for determining sample size requirements for the FECRT that is built on a solid statistical framework, and provide a rigorous anthelminthic drug efficacy classification system for use with FECRT in livestock. Our approach uses two separate statistical tests, a one-sided inferiority test for resistance and a one-sided non-inferiority test for susceptibility, and determines a classification of resistant, susceptible or inconclusive based on the combined result. Since this approach is based on two independent one-sided tests, we recommend that a 90 % CI be used in place of the historically used 95 % CI. This maintains the desired Type I error rate of 5 %, and simultaneously reduces the required sample size. We demonstrate the use of this framework to provide sample size calculations that are rooted in the well-understood concept of statistical power. Tailoring to specific host/parasite systems is possible using typical values for expected pre-treatment and post-treatment variability in egg counts as well as within-animal correlation in egg counts. We provide estimates for these parameters for ruminants, horses and swine based on a re-examination of datasets that were available to us from a combination of published data and other sources. An illustrative example is provided to demonstrate the use of the framework, and parameter estimates are presented to estimate the required sample size for a hypothetical FECRT using ivermectin in cattle. The sample size calculation method and classification framework presented here underpin the sample size recommendations provided in the upcoming FECRT WAAVP guidelines for detection of anthelmintic resistance in ruminants, horses, and swine, and have also been made freely available as open-source software via our website (https://www.fecrt.com).

Genotypic profile of benzimidazole resistance associated with SNP F167Y and F200Y beta-tubulin gene in Brazilian populations of Haemonchus contortus of goats

Benzimidazoles are the most common anthelminthic used for control of gastrointestinal nematodes of goats in the Brazilian semi-arid region. Resistance to these compounds in the nematode Haemonchus contortus has been associated with single nucleotide polymorphisms (SNP) in codons 167 (F167Y) and 200 (F200Y) on the β-tubulin isotype 1 gene. To determine the resistance profile to benzimidazoles of populations of H. contortus of goats of Brazilian semi-arid region, larvae of 29 populations of these nematodes were individually genotyped by real time PCR using a Taqman assay. The percentage of larvae homozygous (RR) for SNP F200Y was relatively low (18.9%), particularly when compared to SNP F167Y (32.7%), indicating that the latter has more relevance in this region. However, the associations between these two SNP demonstrate percentages of resistance ranging from 34.7% to 100% between populations, being the highest percentages for homozygous individuals resistant for the mutation 167 and susceptible to mutation 200 (RR-F167Y/F200Y-SS: 26.7%), followed by combination of heterozygous for both mutations (F167Y-SR/F200Y-SR: 22.8%). These results indicate high levels of resistance in populations of H. contortus of goats in the Brazilian semi-arid region, and thus ineffective antiparasitic control with the use of benzimidazoles in the region.

Mathematical inference on helminth egg counts in stool and its applications in mass drug administration programmes to control soil-transmitted helminthiasis in public health

In the present study, we present a hierarchical model based on faecal egg counts (FECs; expressed in eggs per 1g of stool) in which we first describe the variation in FECs between individuals in a particular population, followed by describing the variance due to counting eggs under a microscope separately for each stool sample. From this general framework, we discuss how to calculate a sample size for assessing a population mean FEC and the impact of an intervention, measured as reduction in FECs, for any scenario of soil-transmitted helminth (STH) epidemiology (the intensity and aggregation of FECs within a population) and diagnostic strategy (amount of stool examined (∼sensitivity of the diagnostic technique) and examination of individual/pooled stool samples) and on how to estimate prevalence of STH in the absence of a gold standard. To give these applications the most wide relevance as possible, we illustrate each of them with hypothetical examples.