using the well. However, for them it is not known if the well they were using at baseline was found to have an arsenic level even higher than their own.

# **6 Cost**

This section evaluates the cost-effectiveness of the different sale strategies. Because the RCT did not include an arm with free provision (unlike earlier studies that _only_ included free provision, see for instance Madajewicz et al. 2007 or Bennear et al. 2013), the merit of free provision as compared to our sales strategy is gauged by assuming a range of switching rates consistent with earlier studies.<sup>20</sup> In addition, recall that the change in arsenic contamination for ‘switchers’ cannot be estimated reliably, given that the data only include the arsenic level of the initial source.

Consistent with figures from this study, the calculations assume that tests costs USD0.30 (or BDT24 using an exchange rate of 1USD/80BDT), and that personnel is paid BDT45 per test delivered, with an additional bonus of BDT12 for group sales. An amount of BDT80 per test is added in arm C, to account for the cost of the placards. Consistent with the experimental results, a take up rate of 25% is set in arms A, B and C, while consistent with results from earlier blanket testing a 100% testing rate is used when tests are offered for free. Again using estimates from the RCT, the calculations use a 30% switching rate among users of unsafe wells in arm A, while for arms B and C they use the estimates adjusted for controls and strata fixed effects in column 4 of Table 4. That is, switching rates are assumed to be 0.49 in arm B and 0.70 in arm C. In the case of free provision, switching rates are varied from 0.3 to 0.75, consistent with findings from earlier work that evaluated switching after free provision. In the study area, the fraction of unsafe wells varied in the 16-27% range, while the earlier BAMWSP figures in these same villages varied from 40 to 90%. To cover a wide range of possibilities calculations are shown using a fraction of unsafe wells that is either low (20%), medium (40%) or high (80%). The results are summarized in Table 5, assuming that a policy maker is deciding how best to allocate a total and fixed budget of USD10,000.

While free provision maximizes switching opportunities within a given locality, charging a fee allows for a larger coverage—at the cost of reducing uptake among those with low willingness or ability to pay. Given the fixed budget, the total number of tests ranges from a maximum of 33,333 with individual sales, to a minimum of 7,692 with sales of tests supplied with a metal placard, so that the placards make arm C even more expensive (per test) than free provision without placards. Under the simplifying assumption that the probability of uncovering an unsafe well does not depend on the mode of supply, these figures imply that individual sales (A) would be the strategy that maximizes the number of unsafe wells uncovered, followed by group sales (B) and free provision, while sales with placard (C) would be the worst in this respect. However, the relative performance of the strategies changes once the different switching rates are taken into account. In particular, given the high switching rates observed in B and C, and the relatively low cost of group sales (B), it is group sales that maximize

> 20Jamil et al. (2019), using data from blanket free testing in Araihazar, estimates a total cost of _<_ USD1 per person whose exposure was reduced.

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