Commentary: Exploiting randomized exposure to early childhood deworming programmes to study long run effects: A research programme in progress.
A recent article by Jullien et al. offers a critical appraisal of three studies which address the long run impact of deworming, including my 2014 working paper, 'The Long Run Effects of Early Childhood Deworming on Literacy and Numeracy: Evidence from Uganda' This working paper is part of an ongoing research project which continues to incorporate new data from the study setting as it is publicly released. First I offer responses to the authors' critique of the 2014 working paper, and then provide information about the ongoing research project. My 2014 working paper examined the long run impact of deworming, delivered through an earlier cluster randomized deworming trial by Alderman et al. on numeracy and literacy outcomes. In the original trial, all children (treatment and control) received a set of basic health services such as Vitamin A supplementation and vaccination, and those in the treatment group were given these interventions plus deworming treatment. Interventions were delivered every 6 months over a period of 3 years. Examination of the long run impact of these interventions required a measurement of educational outcomes, for which I used a large scale survey known as Uwezo, which since 2010 has measured basic numeracy and literacy annually in Uganda, Kenya and Tanzania. The geographical comprehensiveness of the Uwezo survey meant that literacy and numeracy data from the 2010 and 2011 survey rounds were available for a random sample of 710 children from the programme's target age group during the programme period (from 2000 to 2003) in 22 out of the original 50 trial communities. The authors' primary critique is that my study uses this subset of the clusters from the original deworming trial; the authors state that, as a result, 'the analysis is at high risk of attrition bias, due to loss of clusters' I disagree that there is a priori reason to expect bias in the estimated treatment effect. The communities for the original trial were partitioned into treatment and control randomly (via coin toss) and Uwezo documents state that their survey's selection of communities was also random within every district of Uganda, and that the selection of households was by systematic random sampling within villages. Thus the clusters sampled by Uwezo should be, by design, a random subset of the full set of trial communities. A subsample of the original trial clusters that is randomly generated in this way should not be a biased sample. Selective or biased sampling should also manifest as imbalance between treatment and control. Although imbalance is possible given the relatively modest number of clusters, in my paper I found no significant differences between treatment and control communities across a range of demographic and socioeconomic variables. While the authors state in Table 3 that 'some confounders [access to water and private education] appear unbalanced' both the balance table provided in the original working paper and an augmented version, which I shared with the authors upon their request, show no significant differences between treatment and control communities on these variables. The access to water variable, which the authors highlight, is not significantly different between treatment and control despite relatively large differences because of a very high intra cluster correlation for this variable (0.72) within communities. This point relates closely to another criticism, which is that the analysis does not address migration. Since the survey captures a random selection of treatment and control communities, there is no a priori reason to expect that selection into treatment 10 11 years earlier would affect migration patterns in late childhood or early adolescence. Nonetheless, migration could be an issue in two ways, both of which work against the possibility of detecting a significant effect. First, it adds measurement error to the definition of treatment, attenuating estimated treatment effects. Second, whereas preschool and primary school age children are unlikely to migrate for school or work, International Journal of Epidemiology, 2016, Vol. 45, No. 6 2159
International journal of epidemiology