sentinel survey sample to women of the same age group.<sup>15</sup> The application of the methodology is based on the assumption that the age/gender distribution for women in the DHS closely reflects that observed in the sentinel data.<sup>16</sup> However, this is not likely to be the case since the sentinel survey refers to pregnant women who attended sentinel sites, while DHS covers all women age 15 to 49. Two important issues that need to be investigated in this context, before we can confidently move ahead, are thus whether: 1) any sub-group of women in the DHS sample matches sentinel survey women in terms of age/education distribution, so that we could restrict our predictions to that specific subgroup; and 2) to what extent the population of women residing in districts with sentinel sites is representative of women nationwide?

The first issue is important because if the total DHS sample is far from being close to the sentinel data by age/education distribution, we have to focus on the sub-group of DHS women closest to sentinel survey women (such as pregnant women or antenatal clinic attendees) and/or we must reweigh the sentinel survey data so that it becomes representative by age/education of a particular sub-group or all women in the DHS.

The second issue is important because a crucial assumption we make in estimating the model based on sentinel survey data is that no strong selectivity exists in terms of sentinel sites’ placement across the districts (i.e., the population of women from districts with sentinel sites is fairly representative of the total population of women).<sup>17</sup> The first issue is investigated by looking at the age/education distributions for various sub-groups of women in the DHS 2000 (all women, ANC attendees who gave birth last year, ANC attendees that agreed to having a blood sample drawn and who gave a birth last year, currently pregnant women) and comparing them to the distributions for

> 15 This means that we have to drop only 15 out of 7300 observations  for which age is observed (the total sample size of 2001 sentinel survey is 7372).

> 16 The key issue in extrapolating from antenatal clinic data to a population of all women (age 15 to 49) is that in the ANC data there is literally no information on women who have not recently been pregnant. Hence, similar to other matching techniques, such as the Propensity Score Matching, the proposed method assumes that these women do not differ significantly on individual _unobserved_ variables from those who do get captured.  This assumption may be reasonable given that the average fertility rate in Malawi is 5.7 children born/woman. To check for the robustness of the results, predictions are made not only for all women (age 15-49) in the DHS, but also for the sub-samples of the currently pregnant women and ANC attendees in the DHS. Those results are reported and discussed further in the paper. One should also keep in mind that the assumptions made when extrapolating the prevalence directly from the ANC data to the total population (as it is done conventionally in many countries) are more involved and less plausible compared to those that are involved in the SAE methodology.

> 17 Note that only 18 out of 26 districts have sentinel sites.

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