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. 2021 Jun 14;72(Suppl 3):S188-S194.
doi: 10.1093/cid/ciab195.

Impact of Key Assumptions About the Population Biology of Soil-Transmitted Helminths on the Sustainable Control of Morbidity

Carolin Vegvari  1   2   3 , Federica Giardina  4 , Veronica Malizia  4 , Sake J de Vlas  4 , Luc E Coffeng  4 , Roy M Anderson  1   2   3   5
Affiliations

Impact of Key Assumptions About the Population Biology of Soil-Transmitted Helminths on the Sustainable Control of Morbidity

Carolin Vegvari et al. Clin Infect Dis. .

Abstract

The design and evaluation of control programs for soil-transmitted helminths (STHs) is based on surveillance data recording measurements of egg counts in the stool of infected individuals, which underpin estimates of the prevalence and average intensity of infection. There is considerable uncertainty around these measurements and their interpretation. The uncertainty is composed of several sources of measurement error and the limit of detection of fecal smear tests on the one hand, and key assumptions on STH biology on the other hand, including assumptions on the aggregation of worms within hosts and on the impact of density-dependent influences on worm reproduction. Using 2 independently developed models of STH transmission we show how different aspects of STH biology and human behavior impact on STH surveillance and control programs and how accounting for uncertainty can help to develop optimal and sustainable control strategies to meet the World Health Organization (WHO) morbidity target for STHs.

Keywords: mathematical modeling; morbidity control; programme planning; soil-transmitted helminthes.

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Figures

Figure 1.
Figure 1.
Impact of STH biology on the time course of control programs. Simulated scenarios have been aligned such that 95% of baseline prevalences of any infection of both models fall into the same range (20–50% for Ascaris, a, b; 50–70% for hookworm, c). Differences in the baseline prevalences of moderate-to-high intensity infections are due to different egg production functions used by the 2 models. (a) Example simulations for A. lumbricoides. Impact of aggregation on time to reaching the morbidity target (<2% moderate-to-high intensity infections, dashed line). Aggregation is inversely proportional to the parameter k. (b) Example simulations for hookworm. Impact of the age-prevalence profile on reaching the morbidity target. School-based treatment is less effective where the prevalence is higher in adults. (c) Example simulations for hookworm. Impact of density-dependent saturation of worm reproduction. In high prevalence settings, treatment is less impactful if exponential saturation of egg production is assumed. Abbreviations: EMC, Erasmus MC; ICL, Imperial College London; MHI, moderate and heavy intensity; STH, soil-transmitted helminth.
Figure 2.
Figure 2.
Individual-level egg count over individual-level worm burden data and simulations from EMC and ICL models. From top to bottom: Ascaris, hookworm, Trichuris. From left to right: real-world data (A. lumbricoides from Holland Asaolu 1991 [33], hookworm from Ghadirian 1979 [34], Trichuris from Bundy 1987 [20]), ICL model, EMC model. In column 1 the blue and red lines are the mean of 100 000 samples from the simulated egg production functions of the ICL and EMC models, respectively. Columns 2 and 3 show simulated data of one village of 500 individuals at a high equilibrium prevalence. Abbreviations: EMC, Erasmus MC; ICL, Imperial College London.
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