|_Table 1:_<br>_Tier_|_WASH Tiers_<br>_Water_|_Sanitation_|_Handwashing_|
|---|---|---|---|
|0|<sup>No supply/ Not</sup><br>functional|<br>No latrine/ Not<br>functional|No facility|
|1|Functional<br>hand‐pump|One functional<br>latrine|Facility with<br>water|
|2|Functional<br>piped water|Two functional<br>latrines|Facility<sup>1</sup>with<br>water and soap|
|3|‐<br>|Three functional<br>latrines|<br>‐|
|4|‐|Four functional<br>latrines|‐|

The poverty figures at the upazila level are derived from the predicted poverty estimates from Steele et al. (2017).<sup>4</sup> It uses overlapping data from i) traditional household surveys (DHS, HIES, 2010 and Census 2011); ii) remote sensing data such as night‐time lights, distance to roads, distance to closest urban settlements, climate variables; and iii) call detail records at varying spatial resolutions to estimate poverty rates using Bayesian geostatistical models (BGMs) (See Annex‐Figure 1 for a upazila level map with poverty estimates). The only other poverty estimate available to us at the time of analysis were the national estimates from Census 2011, which we deemed outdated to use alongside 2017 WASH data.

The upazilas level stunting estimates for children under five were taken from the _Small‐Area Estimation of Child Undernutrition in Bangladesh_ report by Haslett et al. (2014), Bangladesh Bureau of Statistics (BBS) and the World Food Programme (WFP). The estimates combine survey data from the Child and Mother Nutrition Survey of Bangladesh 2012 (CMNS) and the Health and Morbidity Status Survey 2011 (HMSS) which some additional data from the BBS Census 2011.

|_Table 2: HCFs at ea_<br>_Water_|_ch WASH Tie_<br>_Freq._|_r, by category_<br>_%_|
|---|---|---|
|0|7,690|64.67|
|1|3,692|31.05|
|2|509|4.28|
|_Total_|_11,891_|_100_|
|_Sanitation_|Freq.|Percent|
|0|3,539|30.03|
|1|6,402|54.33|
|2|1,586|13.46|
|3|183|1.55|
|4|74|0.63|
|_Total_|_11,891_|_100_|
|_Handwashing_|Freq.|Percent|
|0|1,697|14.27|
|1|4|0.03|
|2|10,190|85.7|
|_Total_|_11,891_|_100_|

# Method

In addition to descriptive statistics, the primary objective of this analysis is to have a upazila level spatial snapshot of the state of WASH in CCs. To this end, we first create tiers for each category of WASH using the available survey data. The questions in the survey are not comprehensive enough to create the complete JMP tiers. However, we follow the JMP guidelines to the extent possible with the available data. Specifically, each of the three category tiers are coded as shown in Table 1.<sup>5</sup> Table 2 shows the number and proportion of CCs that fall under each tier.

Each of the three tiers are then scaled into an index between 0 and 1. The WASH score for each HCF is the aggregate of the three indices combined. And the WASH index is the mean of the HCF WASH scores at the upazila level, scaled between 0 and 1. The upazilas with WASH index below 0.5 are categorized as ranking “low” in WASH, whereas those with a score above 0.5

> 4 Mean probability of households being below $2.50/day using the Progress Out of Poverty Index (PPI) computed using survey data.

> 5 The survey includes whether there was arsenic testing done at the HCF, however, no further information on water treatment or quality was solicited. The survey also includes a question on when the pit latrine was last emptied. However, this information is not complete enough to make a proper assessment of the state of sanitary facilities beyond functionality. Therefore, we leave those out in constructing our index. See Annex‐Table 1 for questionnaire.

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