New approaches to measuring anthelminthic drug efficacy: parasitological responses of childhood schistosome infections to treatment with praziquantel. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Walker, Martin; Mabud, Tarub; Olliaro, Piero; Coulibaly, Jean; King, Charles; Raso, Giovanna; Scherrer, Alexandra; Stothard, J.; Sousa-Figueiredo, José; Stete, Katarina; Utzinger, Jürg; Basáñez, Maria-Gloria
• Is Part Of: Parasites & vectors. Volume 9:Issue 1(2016)
• Page Start: 1
• Page End: 15
• Publication Date: 2016-12
• Subjects: Schistosomiasis -- Praziquantel -- Anthelminthic drug efficacy -- Egg reduction rate -- Conditional models -- Marginal models -- Bayesian methods; Parasitism -- Periodicals; Parasites -- Periodicals; Vector-pathogen relationships -- Periodicals; Animals as carriers of disease -- Periodicals; Insects as carriers of disease -- Periodicals; 616.96
• DOI: 10.1186/s13071-016-1312-0
• Languages: English
• ISSNs: 1756-3305

Abstract

Abstract Background By 2020, the global health community aims to control and eliminate human helminthiases, including schistosomiasis in selected African countries, principally by preventive chemotherapy (PCT) through mass drug administration (MDA) of anthelminthics. Quantitative monitoring of anthelminthic responses is crucial for promptly detecting changes in efficacy, potentially indicative of emerging drug resistance. Statistical models offer a powerful means to delineate and compare efficacy among individuals, among groups of individuals and among populations. Methods We illustrate a variety of statistical frameworks that offer different levels of inference by analysing data from nine previous studies on egg counts collected from African children before and after administration of praziquantel. Results We quantify responses to praziquantel as egg reduction rates (ERRs), using different frameworks to estimate ERRs among population strata, asaverage responses, and within strata, asindividual responses. We compare our model-based average ERRs to corresponding model-free estimates, using as reference the World Health Organization (WHO) 90 % threshold of optimal efficacy. We estimate distributions of individual responses and summarize the variation among these responses as the fraction of ERRs falling below the WHO threshold. Conclusions Generic models for evaluating responses to anthelminthics deepen our understanding of variation among populations, sub-populations and individuals. We discuss the future application of statistical modelling approaches for monitoring and evaluation of PCT programmes targeting human helminthiases in the context of the WHO 2020 control and elimination goals.