to the control group. At the same time, we find evidence of significant heterogeneous treatment effects across dwelling categories. For those living in solid houses, bed net use increase by 9-to-11% compared to control, yet we find no significant effect on those living in non-solid dwellings. These effects are amplified in the last 3 months of the campaign, and for individuals with moderate levels of concerns about getting malaria. While incidence of high fever and malaria during the campaign was not affected, the campaign increased the likelihood of solid dwellers seeking medical assistance promptly (within 24 hours) in the event of a fever by 13%.

We use the cross-sectional sample to study impacts 1-to-3 months _after_ the campaign ended. The results indicate that prolonged exposure to the ad campaign, which led to cumulative behavior change, resulted in decreased malaria incidence. Self-reported household-level malaria cases decreased among solid dwellers by 44 % at the extensive margin, and by 53% at the intensive margin, compared to control, but not among those living in non-solid houses. The reduction in malaria incidence is larger among bed net owners and more so among households with at least 1 mosquito net per every 2 members, emphasizing the importance of technology adoption to prevent infection. Our survey-based findings are bolstered by the evidence of baseline balance in demographic and socio-economic characteristics across experimental arms and the consistency of impact estimates across different model specifications and estimators.

We complement this survey evidence with administrative health-facility data on recorded malaria cases from the Indian Health Management Information System (HMIS). Over the 9-month period following the launch of the campaign, monthly malaria incidence in urban areas decreased by 6.2 cases per million people, which is 30% of the overall monthly malaria incidence rate in the pretreatment period. By contrast, and consistent with our survey data, incidence did not significantly change in rural settlements, where non-solid dwellings are substantially more common. Moreover, while the campaign had no impact on the number of tests conducted to diagnose malaria, the urban positivity rates (positive cases/tests) decreased by 2 p.p. and the effect is null in rural areas. These results are robust to different model specifications and estimators.

Overall, our evidence indicates that the MNM campaign benefited households residing in solid dwellings and in urban settlements, but less so those that are particularly susceptible to malaria. The potential cause behind this distinct effect could stem from two factors: (1) content effectiveness (where, upon receiving the ad, it only influenced households residing in solid dwellings) or (2) targeting (the campaign did not sufficiently reached households living in non-solid dwellings). To discern which mechanism might underlie this effect, first we consider ad recall outcomes at the end of the campaign. If the ads reached both solid and non-solid dwellers at similar frequencies, then one would expect both audiences to equally recall them. Yet, we find that ad recall is larger only among treated individuals in solid houses, suggesting that non-solid dwellers were not sufficiently exposed to the ads.

To corroborate this mechanism, we nest an individual-level _feed_ experiment within our crosssectional sample. We use Facebook’s Custom Audience tool to directly retarget ads to a randomly selected half of our survey respondents. Over a 2-week campaign, we reached individuals living 4