Accepted for/Published in: JMIR Formative Research
Date Submitted: Apr 10, 2022
Open Peer Review Period: Apr 10, 2022 - Jun 5, 2022
Date Accepted: Nov 14, 2022
(closed for review but you can still tweet)
Reaching Populations at Risk for HIV through Targeted Facebook Advertisements: A Cost-Consequence Analysis
ABSTRACT
Background:
Undiagnosed Human Immunodeficiency Virus (HIV) infection continues to be a public health challenge. Our study evaluates the efficacy of different Facebook (FB) advertisements (Ads) approaches targeting HIV testing for at-risk populations.
Objective:
To evaluate and compare the projected cost and efficacy of different simulated FB Ads approaches targeting at-risk populations for HIV based on new HIV diagnoses by age group and geographic region.
Methods:
Using FB platform for video Ad for a ten-day duration targeting HIV at-risk populations (without actually launching Ads), we compared estimated Ads potential reach and cost for age group 13-24 (in which Underdiagnosed HIV is most prevalent), other age groups, United States (US) geographical regions/states, and different campaign budgets. We then estimated Ads cost per new HIV diagnosis based on positivity rates and the average healthcare industry conversion rate.
Results:
On 04/20/2021, the potential reach for targeted Ads to HIV at-risk populations in the US was approximately 16 million for all age groups and 3.3 million for the age group 13-24. When using different FB Ads budgets, the daily reach and the daily clicks per dollar followed a cumulative distribution curve of an exponential function. Using multiple $10 Ads, the Ads cost per every new HIV diagnosis was $13.09-$37.82, with an average cost of $19.45. In contrast, per new HIV diagnosis, a one-time national Ad would cost $72.76 to $452.25, averaged $166.79. The estimated cost per HIV diagnosis averaged $13.96-$55.10 for all age groups, $12.55-$24.67 for all US regions, and was lowest in the South at $12.55.
Conclusions:
Targeted FB Ads are potential means to reach HIV at-risk populations, especially in the South where the disease burden is high and Ad cost per new diagnosis is low. Considering cost-effectiveness, a single higher-cost Ad may have lower cost-effectiveness than same-value multiple lower-cost Ads.
Citation
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Copyright
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