2023
DOI: 10.1098/rspb.2022.2204
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Diagnosis of helminths depends on worm fecundity and the distribution of parasites within hosts

Abstract: Helminth transmission and morbidity are dependent on the number of mature parasites within a host; however, observing adult worms is impossible for many natural infections. An outstanding challenge is therefore relating routine diagnostics, such as faecal egg counts, to the underlying worm burden. This relationship is complicated by density-dependent fecundity (egg output per worm reduces due to crowding at high burdens) and the skewed distribution of parasites (majority of helminths aggregated in a small frac… Show more

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Cited by 12 publications
(11 citation statements)
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“…The pre-treatment egg counts (EPG) showed a strong linear relationship with the number of worms recovered after the treatment. It was also of note that the fecundity of O. viverrini appeared to be related to the degree of parasite aggregation within the host body and negatively associated with the total worm burden in each host individual 35 , 36 . In the present study, the number of cases in whom worm recovery was performed was small (only 10), and the density-dependent reduction in worm fecundity was difficult to analyze.…”
Section: Discussionmentioning
confidence: 97%
“…The pre-treatment egg counts (EPG) showed a strong linear relationship with the number of worms recovered after the treatment. It was also of note that the fecundity of O. viverrini appeared to be related to the degree of parasite aggregation within the host body and negatively associated with the total worm burden in each host individual 35 , 36 . In the present study, the number of cases in whom worm recovery was performed was small (only 10), and the density-dependent reduction in worm fecundity was difficult to analyze.…”
Section: Discussionmentioning
confidence: 97%
“…The number of samples of each kind are listed in Table 1 and the distribution of EPG among humans is shown in Fig 1 . We transform EPG to worm counts and vice versa in individuals and animals with a density-dependent transformation function where the EPG output per worm decreases with an increasing number of worms in an individual [ 41 ]. We assume that a single parasite within a host is capable of producing eggs through self-fertilization [ 42 ].…”
Section: Methodsmentioning
confidence: 99%
“…The complex life cycle of many indirectly transmitted macroparasites makes elucidation of adult worm burden, the evaluation of control and drug trial success, and establishment of baselines of infection levels in pre-clinical trials difficult, as adult worms of many species (e.g. Schistosoma mansoni (2), Wuchereria bancrofti (3), Onchocerca volvulus (4), Opisthorchis viverrini (5) or Trichuris trichiura (6)) are either very difficult or impossible to retrieve from a patient. As such, inferring whether a trial macrofilaricide has successfully killed all adult worms, with any subsequent infection being due to reinfection, or whether treatment failure has been followed by repopulation of microfilariae (mf), or renewed reproduction and excretion of larvae from surviving adults, is impossible using current diagnostics.…”
Section: Introductionmentioning
confidence: 99%
“…As such, inferring whether a trial macrofilaricide has successfully killed all adult worms, with any subsequent infection being due to reinfection, or whether treatment failure has been followed by repopulation of microfilariae (mf), or renewed reproduction and excretion of larvae from surviving adults, is impossible using current diagnostics. Moreover, estimating adult worm burden, a key parameter for assessing infection severity and individual contribution to community transmission, based on sampled offspring is problematic, as helminth larval abundance does not necessarily linearly predict adult worm burden, and instead often follows a density-dependent pattern (5,7,8), with adults only sporadically contributing to the larval pool at any given time (9). This gap introduces a considerable level of uncertainty for mathematical models – key tools for informing policy and control success.…”
Section: Introductionmentioning
confidence: 99%
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