Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information

Abstract

BackgroundEstimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH) control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalence following treatment in Viet Nam. The model is stationary and to date, the prediction has been obtained by calculating the transition probabilities between the different classes of intensity following the first year of drug distribution and assuming that these remain constant in subsequent years. However, to run this model longitudinal parasitological data (including intensity of infection) are required for two consecutive years from at least 200 individuals. Since this amount of data is not often available from STH control programmes, the possible application of the model in control programme is limited. The present study aimed to address this issue by adapting the existing Markov model to allow its application when a more limited amount of data is available and to test the predictive capacities of these simplified models.MethodWe analysed data from field studies conducted with different combination of three parameters: (i) the frequency of drug administration; (ii) the drug distributed; and (iii) the target treatment population (entire population or school-aged children only). This analysis allowed us to define 10 sets of standard transition probabilities to be used to predict prevalence changes when only baseline data are available (simplified model 1). We also formulated three equations (one for each STH parasite) to calculate the predicted prevalence of the different classes of intensity from the total prevalence. These equations allowed us to design a simplified model (SM2) to obtain predictions when the classes of intensity at baseline were not known. To evaluate the performance of the simplified models, we collected data from the scientific literature on changes in STH prevalence during the implementation of 26 control programmes in 16 countries. Using the baseline data observed, we applied the simplified models and predicted the onward prevalence of STH infection at each time-point for which programme data were available. We then compared the output from the model with the observed data from the programme.ResultsThe comparison between the model-predicted prevalence and the observed values demonstrated a good accuracy of the predictions. In 77% of cases the original model predicted a prevalence within five absolute percentage points from the observed figure, for the simplified model one in 69% of cases and for the simplified model two in 60% of cases. We consider that the STH Markov model described here could be an important tool for programme managers to monitor the progress of their control programmes and to select the appropriate intervention. We also developed, and made freely available online, a software tool to enable the use of the STH Markov model by personnel with limited knowledge of mathematical models.

Development and evaluation of a Markov model to predict changes in schistosomiasis prevalence in response to praziquantel treatment: a case study of Schistosoma mansoni in Uganda and Mali

“…A Markov statistical model was developed to capture soil-transmitted helminth (STH) infection dynamics through rounds of MDA (with benzimidazoles), by Montresor and colleagues in 2013 [ 16 , 17 ]. The authors demonstrated that their model successfully predicted changes in the prevalence of Ascaris lumbricoides , Trichuris trichiura and hookworm (consisting of the two species that infect humans: Ancylostoma duodenale and Necator americanus ) through five rounds of MDA using data collected at baseline and after one round of treatment in Vietnam to parameterize the Markov Transition Probability (MTP) matrix; the essential ingredient of such Markov models.…”

“…The authors demonstrated that their model successfully predicted changes in the prevalence of Ascaris lumbricoides , Trichuris trichiura and hookworm (consisting of the two species that infect humans: Ancylostoma duodenale and Necator americanus ) through five rounds of MDA using data collected at baseline and after one round of treatment in Vietnam to parameterize the Markov Transition Probability (MTP) matrix; the essential ingredient of such Markov models. The predictive capability of the model was also successfully validated against STH data from 26 control programmes in 16 countries [ 17 ].…”

The public health benefit and burden of mass drug administration programs in Vietnamese schoolchildren: Impact of mebendazole

“…The difference in public health morbidity associated with STH is quantified before and after the introduction of mebendazole MDA for eight million Vietnamese children aged 5–14 years for five years, reaching 80% coverage [ 20 ]. To do this we adopted a Markov model published by Montresor et al [ 9 , 19 ]. The model predicts the prevalence of hookworm, A .…”

“…A published Markov model developed to monitor MDA programs for school-aged children was adopted to simulate the estimated reduction in STH prevalence due to mebendazole MDA [ 9 , 19 ]. The model we adopted was Transition Probability Matrix Set (TPMS) 4 from the Supplementary Material of Montresor et al (2016), representing the treatment of 1324 school-aged children with mebendazole every 12 months (Table A in S1 Text ).…”

“…A DALY is equivalent to one healthy life year lost. This study focuses on Vietnam, building on a previously published model of STH prevalence progression after treatment with anthelmintic drugs, which are supplied to Vietnam through the MDA program [ 9 , 19 ]. While multiple anthelmintic drugs are donated for the treatment of STH, data from the pharmaceutical supply chain was only collected for mebendazole.…”