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An undiagnosed HIV infection remains a public health challenge. In the digital era, social media and digital health communication have been widely used to accelerate research, improve consumer health, and facilitate public health interventions including HIV prevention.
We aimed to evaluate and compare the projected cost and efficacy of different simulated Facebook (FB) advertisement (ad) approaches targeting at-risk populations for HIV based on new HIV diagnosis rates by age group and geographic region in the United States.
We used the FB ad platform to simulate (without actually launching) an automatically placed video ad for a 10-day duration targeting at-risk populations for HIV. We compared the estimated total ad audience, daily reach, daily clicks, and cost. We tested ads for the age group of 13 to 24 years (in which undiagnosed HIV is most prevalent), other age groups, US geographic regions and states, and different campaign budgets. We then estimated the ad cost per new HIV diagnosis based on HIV positivity rates and the average health care industry conversion rate.
On April 20, 2021, the potential reach of targeted ads to at-risk populations for HIV in the United States was approximately 16 million for all age groups and 3.3 million for age group 13 to 24 years, with the highest potential reach in California, Texas, Florida, and New York. When using different FB ad budgets, the daily reach and daily clicks per US dollar followed a cumulative distribution curve of an exponential function. Using multiple US $10 ten-day ads, the cost per every new HIV diagnosis ranged from US $13.09 to US $37.82, with an average cost of US $19.45. In contrast, a 1-time national ad had a cost of US $72.76 to US $452.25 per new HIV diagnosis (mean US $166.79). The estimated cost per new HIV diagnosis ranged from US $13.96 to US $55.10 for all age groups (highest potential reach and lowest cost in the age groups 20-29 and 30-39 years) and from US $12.55 to US $24.67 for all US regions (with the highest potential reach of 6.2 million and the lowest cost per new HIV diagnosis at US $12.55 in the US South).
Targeted personalized FB ads are a potential means to encourage at-risk populations for HIV to be tested, especially those aged 20 to 39 years in the US South, where the disease burden and potential reach on FB are high and the ad cost per new HIV diagnosis is low. Considering the cost efficiency of ads, the combined cost of multiple low-cost ads may be more economical than a single high-cost ad, suggesting that local FB ads could be more cost-effective than a single large-budget national FB ad.
Complications and risks from undiagnosed HIV infections continue to be a public health challenge [
In the last decade, social media has provided health communication solutions for multiple health challenges, including patient outreach and education. Despite concerns about privacy and data use [
Meta Inc (Menlo Park) continues to lead the social media market with 2.91 billion active users monthly as of the fourth quarter of 2021 [
The Chicago pre-exposure prophylaxis (PrEP) campaign (PrEP4L) was launched in 2016 and used the FB ad platform to disseminate nonstigmatizing health education to high-risk populations. PrEP4L garnered 6,970,127 views on FB and 1,719,446 views on Instagram. The average number of visitors to the PrEP4L website from this campaign was 182 per day, with a click through rate (CTR) of 0.06%, which is below the industry standard of 0.5% to 0.9% for social campaigns [
Researchers used FB-provided estimates during ad creation to demonstrate that FB ad audience estimates can be used to model regional variations in the prevalence of health conditions such as obesity [
In this US-centric study, we evaluated and compared the projected cost and efficacy of different FB ad approaches, simulating a 10-day video ad campaign that targets at-risk populations for HIV to estimate the costs for every resulting new HIV diagnosis using the health care industry conversion rate [
In this study, we refer to FB ad metrics as defined by FB [
Study definitions.
Term | Definition |
Detailed targeting | An option available during FBa adb creation that allows promoters to define the group of people that will see an ad on FB. It may include other pages or ads users click on and activities they engage with on FB. Additional selection criteria include demographics such as age, gender, location, and network connection speed. |
Ad goal | A choice that promoters make when creating an ad to share with FB to influence the result they receive from the promotion. Promoters can also select an “automatic” goal by allowing FB to set the most relevant goal based on other ad settings. |
Estimated potential reach | The estimated maximum audience size that could see an ad based on the selected target criteria, ad placements, and how many people were shown ads on FB apps and services in the past 30 d. Potential reach is not an estimate of how many people will actually see the ad and may change with time. Estimates are not designed to match census population. |
Estimated daily reach | The estimated number of people an FB ad will reach in a certain audience each day based on budget and ad bid. Ad bid is how much an advertiser is willing to pay for a specific action. |
Estimated daily link clicks | The estimated number of link clicks that an FB ad will receive each day based on a campaign performance and estimated daily reach. |
Cost per 1000 people reached | The average cost to reach 1000 people with an FB ad; reach can be a more insightful metric than impressions, because it measures how many people were exposed to an ad and how efficiently an ad reached them. |
Conversion rate | The percentage of users who perform a desired action after clicking on an ad. |
aFB: Facebook.
bad: advertisement.
We created an FB video ad for a 10-day period without launching it. First, we selected the FB ad goal (
FB ads allow promoters to choose a budget, and based on the budget, FB provides an estimated daily reach and estimated daily number of link clicks. For each state, we adjusted the budget to reach the total estimated target population in 10 days, which meant that we targeted an estimated 10% of the total potential reach per day. We adjusted our budget to the nearest US $10 to achieve this goal. We documented the budget, estimated daily reach, and estimated daily clicks for 2 manually adjusted budgets for each ad campaign. The first budget was adjusted to target the highest estimated reach over 10 days, and the second budget was adjusted to target the lowest estimated reach over 10 days (
“Facebook Ads platform screenshot”—an example of post boosting with automatic goal that lets Facebook target the most relevant advertiser goal and the button label selection “learn more”.
“Facebook Ads platform screenshot”—The Facebook Ads platform allows users to select gender, age, location, and other detailed target criteria based on demographics, interests, behaviors, and more. It also provides potential reach of the defined target audience.
“Facebook Ads platform screenshot”—an example of adjusting the Facebook Ads campaign settings to 10 days using US $10 total budget. Facebook provides estimated people reached per day and estimated daily link clicks.
We collected the estimated daily reach and daily clicks for a single ad with the same criteria targeting the entire United States at multiple budget set points ranging from US $10 to US $1,000,000 to explore the differences in reach and link clicks at different budget levels.
Finally, for every state, we estimated the cost of ads for every new HIV diagnosis secondary to the campaign based on estimated daily clicks (provided by FB), the health care industry conversion rate [
Proposed framework to evaluate cost and efficacy of Facebook (FB) advertisements (ads) to reach population at risk for diseases with health promotion ads for disease screening.
As all the data used in our study were publicly available, no institutional review board approval was required. All FB ad estimates used for modeling the cost per new HIV diagnosis were collected from the provided anonymous estimates on the FB ad platform without launching any ads. Hence, as no simulated study ads reached consumers, informed consent was not required. FB was not a collaborator in this study.
On April 20, 2021, the potential reach for our criteria (men with 1 or more of the following interests as defined by FB: “homosexuality, same-sex marriage, same-sex relationship, transgenderism, or LGBT community”) in the United States was approximately 16 million for all age groups and approximately 3.3 million for the age group 13 to 24 years.
California had the highest potential reach at 430,000, followed by Texas (360,000), Florida (210,000), and New York (200,000;
On the basis of the average estimated budget to reach the maximum audience for each state in the age group 13 to 24 years, the estimated average cost per 1000 individuals reached was the lowest in Alaska, Maine, and West Virginia (US $12-US $12.99), followed by Arkansas and Mississippi (US $13-US $13.99) and Alabama, Hawaii, Louisiana, New Hampshire, Ohio, South Dakota, and Vermont (US $14-US $14.99). The estimated average cost per 1000 individuals reached was the highest in Rhode Island and Wyoming at US $20, followed by Florida, New York, and Utah (US $19-US $19.99) and California, Georgia, Iowa, Massachusetts, New Jersey, Oregon, Pennsylvania, Virginia, and Washington (US $18-US $18.99;
The average FB ad cost for every new HIV diagnosis was the lowest in Alabama, Kentucky, Mississippi, Oklahoma, and West Virginia (US $136.97-US $199.99), followed by Arkansas, Delaware, Louisiana, North Carolina, South Carolina, Tennessee, Texas, and Virginia (US $200-US $249.99) and Florida, Georgia, Indiana, Iowa, Kansas, Maine, Maryland, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin (US $250-US $299.99). The highest estimated average ad’s cost for every new HIV diagnosis was found in California at US $610.60, followed by Washington (US $547.99), Utah (US $515.02), and New Jersey (US $508.03;
Using a single ad with the same target criteria for the entire United States demonstrated an estimated average cost per 1000 of US $18.50 and an estimated average cost per new HIV diagnosis of US $257.51.
Estimated total reach, daily reach, and daily link clicks on the Facebook Ads platform based on the selected target criteria for age group 13 to 24 years and the manually adjusted budget to include the total reach on both extreme ends of the provided estimated range of reach.
State | Total estimated reach | Lowest adjusted budget (US $) | Highest adjusted budget (US $) | Estimated lowest daily reach at the lowest budget | Estimated highest daily reach at the lowest budget | Estimated lowest daily reach at the highest budget | Estimated highest daily reach at the highest budget | Estimated lowest daily link clicks at the lowest budget | Estimated highest daily link clicks at the lowest budget | Estimated lowest daily link clicks at the highest budget | Estimated highest daily link clicks at the highest budget |
Alabama | 46,000 | 200 | 1150 | 1600 | 4700 | 4600 | 13,200 | 50 | 146 | 114 | 330 |
Alaska | 8300 | 30 | 170 | 287 | 830 | 831 | 2400 | 5 | 19 | 16 | 46 |
Arizona | 78,000 | 450 | 2180 | 2700 | 7800 | 7800 | 22,500 | 67 | 194 | 158 | 456 |
Arkansas | 29,000 | 120 | 660 | 998 | 2900 | 2900 | 8300 | 21 | 61 | 52 | 152 |
California | 430,000 | 3440 | 12,430 | 14,900 | 43,000 | 43,000 | 124,200 | 288 | 832 | 718 | 2100 |
Colorado | 59,000 | 290 | 1790 | 2000 | 5900 | 5900 | 16,900 | 56 | 162 | 140 | 405 |
Connecticut | 35,000 | 170 | 910 | 1200 | 3500 | 3500 | 10,000 | 26 | 77 | 65 | 188 |
Delaware | 9400 | 60 | 240 | 345 | 997 | 940 | 2700 | 8 | 22 | 17 | 48 |
Florida | 210,000 | 1520 | 6460 | 7300 | 21,000 | 21,000 | 60,600 | 187 | 539 | 435 | 1300 |
Georgia | 120,000 | 810 | 3730 | 4100 | 12,000 | 12,000 | 34,600 | 98 | 284 | 244 | 704 |
Hawaii | 14,000 | 60 | 350 | 476 | 1400 | 1400 | 3900 | 9 | 25 | 25 | 71 |
Idaho | 19,000 | 100 | 570 | 688 | 2000 | 1900 | 5400 | 20 | 59 | 44 | 127 |
Illinois | 120,000 | 560 | 3390 | 4100 | 12,000 | 1200 | 34,500 | 120 | 347 | 285 | 823 |
Indiana | 64,000 | 320 | 1900 | 2200 | 6500 | 6400 | 18,400 | 64 | 185 | 149 | 431 |
Iowa | 26,000 | 140 | 800 | 914 | 2600 | 2600 | 7400 | 30 | 88 | 66 | 190 |
Kansas | 26,000 | 120 | 670 | 926 | 2700 | 2600 | 7400 | 25 | 72 | 57 | 165 |
Kentucky | 41,000 | 190 | 1100 | 1400 | 4100 | 4100 | 11,800 | 50 | 145 | 115 | 331 |
Louisiana | 45,000 | 200 | 1110 | 1600 | 4500 | 4500 | 12,900 | 38 | 110 | 86 | 249 |
Maine | 12,000 | 40 | 260 | 452 | 1300 | 1200 | 3400 | 12 | 35 | 27 | 78 |
Maryland | 61,000 | 340 | 1760 | 2100 | 6100 | 6100 | 17,600 | 47 | 136 | 120 | 347 |
Massachusetts | 64,000 | 360 | 1990 | 2200 | 6400 | 6400 | 18,400 | 57 | 165 | 141 | 406 |
Michigan | 86,000 | 420 | 2640 | 3000 | 8600 | 8600 | 24,700 | 86 | 250 | 207 | 599 |
Minnesota | 44,000 | 190 | 1330 | 1600 | 4500 | 4400 | 12,600 | 36 | 104 | 97 | 280 |
Mississippi | 31,000 | 130 | 730 | 1100 | 3100 | 3100 | 8800 | 30 | 88 | 71 | 205 |
Missouri | 54,000 | 240 | 1520 | 1900 | 5400 | 5400 | 1550 | 49 | 142 | 124 | 357 |
Montana | 9900 | 50 | 300 | 349 | 1000 | 1000 | 2900 | 10 | 28 | 22 | 64 |
Nebraska | 18,000 | 80 | 500 | 616 | 1800 | 1800 | 5100 | 19 | 54 | 44 | 127 |
Nevada | 37,000 | 200 | 1080 | 1300 | 3700 | 3700 | 10,600 | 32 | 92 | 77 | 222 |
New Hampshire | 11,000 | 60 | 260 | 409 | 1200 | 1100 | 3000 | 12 | 37 | 25 | 73 |
New Jersey | 88,000 | 670 | 2650 | 3000 | 8800 | 8800 | 25,300 | 69 | 198 | 166 | 481 |
New Mexico | 26,000 | 120 | 670 | 884 | 2600 | 2600 | 7400 | 25 | 73 | 58 | 167 |
New York | 200,000 | 1370 | 6300 | 6900 | 20,000 | 20,000 | 57,700 | 188 | 545 | 435 | 1300 |
North Carolina | 110,000 | 600 | 3050 | 3800 | 11,000 | 11,000 | 31,700 | 98 | 283 | 224 | 648 |
North Dakota | 6400 | 30 | 150 | 256 | 740 | 661 | 1900 | 6 | 19 | 13 | 38 |
Ohio | 110,000 | 520 | 3310 | 3800 | 11,000 | 11,000 | 31,700 | 113 | 327 | 266 | 770 |
Oklahoma | 40,000 | 190 | 1060 | 1400 | 4000 | 4000 | 11,400 | 41 | 117 | 95 | 274 |
Oregon | 37,000 | 230 | 1160 | 1300 | 3700 | 3700 | 10,600 | 35 | 101 | 85 | 246 |
Pennsylvania | 110,000 | 650 | 3330 | 3800 | 11,000 | 11,000 | 31,700 | 93 | 268 | 232 | 670 |
Rhode Island | 11,000 | 60 | 380 | 375 | 1100 | 1100 | 3100 | 11 | 31 | 28 | 82 |
South Carolina | 49,000 | 250 | 1450 | 1700 | 4900 | 4900 | 14,100 | 43 | 124 | 108 | 311 |
South Dakota | 6700 | 30 | 170 | 318 | 918 | 684 | 2000 | 7 | 22 | 15 | 44 |
Tennessee | 67,000 | 310 | 1790 | 2300 | 6800 | 6700 | 19,200 | 61 | 176 | 148 | 428 |
Texas | 360,000 | 2240 | 10,610 | 12,400 | 36,000 | 36,000 | 104,000 | 316 | 913 | 751 | 2200 |
Utah | 40,000 | 260 | 1290 | 1400 | 4000 | 4000 | 11,500 | 33 | 97 | 84 | 242 |
Vermont | 5700 | 30 | 140 | 251 | 726 | 591 | 1700 | 6 | 20 | 13 | 38 |
Virginia | 85,000 | 530 | 2570 | 2900 | 8500 | 8500 | 24,400 | 76 | 221 | 179 | 518 |
Washington | 68,000 | 470 | 2040 | 2400 | 6800 | 6800 | 19,600 | 51 | 146 | 128 | 369 |
West Virginia | 14,000 | 50 | 300 | 495 | 1400 | 1400 | 3900 | 15 | 44 | 37 | 106 |
Wisconsin | 48,000 | 220 | 1370 | 1700 | 4800 | 4800 | 13,700 | 51 | 147 | 120 | 346 |
Wyoming | 5500 | 30 | 190 | 195 | 564 | 567 | 1600 | 6 | 18 | 15 | 44 |
Sum all states | 3,294,900 | 19,750 | 95,960 | 114,334 | 330,875 | 318,774 | 933,950 | 2896 | 8388 | 6941 | 20,196 |
All United Statesa | 3,300,000 | 17,480 | 104,590 | 114,200 | 330,000 | 330,000 | 953,600 | 3700 | 10,700 | 9300 | 27,000 |
Estimated potential reach on Facebook per state on April 20, 2021, based on the target audience.
Average estimated Facebook Ads budget per state, manually adjusted to reach the potential reach based on target audience in each state on April 20, 2021.
Average cost per 1000 reach on the Facebook Ads platform per state on April 20, 2021, based on target audience.
Average Facebook Ads cost per new HIV diagnosis per state as simulated on April 20, 2021, based on Facebook potential reach, Facebook estimated link clicks, average health care industry conversion rate, and the Centers for Disease Control and Prevention-reported average positivity rate per US regions.
When we created a single ad using the criteria for the entire United States at different budgets ranging from US $10 to US $1,000,000, the daily reach per dollar and daily clicks per dollar followed the cumulative distribution curve of an exponential function (
Using an estimated reach of 16 million active US FB users on April 20, 2021, the ad cost per new HIV diagnosis for a 1-time national ad ranged from US $72.76 to US $452.25, with an average cost of US $166.79. In contrast, the cost range for every new HIV diagnosis with a campaign using multiple daily US $10 ads over 10 days was lower at US $13.09 to US $37.82 with an average cost of US $19.45. The estimated daily clicks per US $10 were also higher when using multiple daily US $10 ads and averaged 28 clicks per day compared with 3 daily clicks per US $10 when using a single US ad.
Cumulative distribution function curve of exponential distribution that “reach per budget” on the Facebook (FB) advertisement (ad) platform follows based on simulated different budgets for same target audience with same ad settings.
Cumulative distribution function curve of exponential distribution that “clicks per budget” on Facebook (FB) advertisement (ad) platform follows based on simulated different budgets for same target audience with same ad settings.
Using multiple US $10 ads for our target audience in the United States across multiple age groups, the lowest average estimated cost per new HIV diagnosis was in the age groups 20 to 29 and 30 to 39 years (US $13.96 and US $14.72, respectively). Potential reach was the highest in the age group 20 to 29 years at 5.4 million, followed by the age group 30 to 39 years at 3.8 million and 3.2 million for the age group greater than 50 years. Potential reach was the lowest for the age group 13 to 19 years at 890,000. Estimated daily clicks using US $10 ten-day campaign ads were similar for all age groups (31-33), except for the age group 13 to 19 years where the estimated daily clicks were lower at 11. The estimated ad’s cost per HIV test averaged US $0.28 to US $0.29 for all age groups, except the age group 13 to 19 years, for which the estimated ad’s cost per HIV test averaged US $0.83. The estimated ad’s cost per HIV diagnosis averaged US $13.96 to US $34.97 for all age groups, except the age group 13 to 19 years that averaged US $55.10 (
Estimated advertisements (ads) cost per new HIV diagnosis for different age groups and geographic locations based on previously reported HIV positivity rates and estimated total reach on Facebook for the target audience of each age group and geographic location.
Targeting characteristics | New HIV positivity test percentagea | Potential reach on Facebook | Estimated positive tests | Estimated ads cost per new HIV diagnosis (US $) | |
|
|||||
|
13-19 | 1.50 | 890,000 | 58 | 55.10 |
|
20-29 | 2.10 | 5,400,000 | 1298 | 13.96 |
|
30-39 | 1.90 | 3,800,000 | 712 | 14.72 |
|
40-49 | 1.30 | 2,200,000 | 261 | 22.20 |
|
50+ | 0.80 | 3,200,000 | 166 | 34.97 |
|
|||||
|
Northeast | 1.30 | 2,700,000 | 337 | 24.11 |
|
Midwest | 1.60 | 2,900,000 | 390 | 19.26 |
|
South | 2.30 | 6,200,000 | 1339 | 12.55 |
|
West | 1.20 | 3,800,000 | 508 | 25.25 |
|
US dependent areas | 1.10 | 150,000 | 7 | 24.67 |
|
Total | 1.70 | 16,000,000 | 2115 | 19.45 |
aCenters for Disease Control and Prevention funded HIV testing: United States, Puerto Rico, and the United States Virgin Islands, 2017 [
Using multiple US $10 ads for the target audience in different US regions, the lowest average estimated cost per new HIV diagnosis was in the South (US $12.55), followed by the Midwest (US $19.26). Potential reach was highest in the South at 6.2 million, followed by the West at 3.8 million, 2.9 million in the Midwest, 2.7 million in the Mideast, and 150,000 in the US dependent territories. The estimated daily clicks using US $10 ten-day campaign ads were similar for all regions at 29-34. The estimated ad cost per HIV test averaged US $0.27 to US $0.31 for all US regions and was the lowest in the US dependent territories at US $0.27. The estimated ads cost per HIV diagnosis averaged US $12.55 to US $24.67 for all US regions and was the lowest in the South at US $12.55 (
Creating FB ads that target at-risk populations for HIV infection in US states, regions, and age groups while comparing different ad budgets revealed interesting and useful findings, including potential low ad cost per new HIV diagnosis and higher cost efficiency for low-budget ads. On April 20, 2021, the potential reach for our target criteria in the United States was approximately 16 million for all age groups and 3.3 million for the age group 13 to 24 years—the group that had the highest rate of undiagnosed HIV infection. The estimated ad cost per new HIV diagnosis averaged US $13.96 to US $55.10 for all age groups and was the highest in the age group 13 to 19 years at US $55.10. The estimated ad cost per new HIV diagnosis averaged US $12.55 to US $24.67 for all US regions and was the lowest in the South at US $12.55. Comparing different ad budgets, low-budget ads were more cost-effective than high-budget ads, as the daily reach per US dollar and the daily clicks per US dollar followed the cumulative distribution curve of an exponential function on the FB ad platform. We concluded that multiple small campaigns would generate similar results to larger campaigns at a lower cost.
Understanding the variables contributing to the cost and efficacy of social media ads for health promotion is important in the digital era [
Although our framework focuses on FB ads, evaluating the platform’s potential as a health communication solution should be the first step when considering social media for health promotion. Selecting the best social media platform for health promotion campaigns can be accomplished by understanding the available criteria for targeting, comparing reach estimates of the target audience on the social media platform to real-world estimates of the population at risk, and examining the penetration rates of different social media platforms among the population of interest. For example, in our study, among all age groups, we found the highest FB ad cost per new HIV diagnosis in the age group 13 to 19 years. This may be explained by the lower penetration of FB among this age group than other platforms such as TikTok and Snapchat. In addition, these estimates are subject to user interaction with the ad’s design and content, which is beyond the scope of this study.
Since the emergence of the HIV epidemic, US health departments, community organizations, and health care providers have helped people with HIV become aware of their diagnosis and live longer. Timely, active, and complete surveillance is the mainstay of effective public health action, as undiagnosed, acute HIV infection carries an increased risk of complications and spread. As social media can help identify and stop microepidemics, the Joint United Nations Programme on HIV or AIDS highlighted the use of social media to facilitate community engagement as a critical component in HIV control efforts [
Owing to the global economic crisis in 2008, a major reduction in HIV prevention resources occurred at the state, local, and federal levels. To counteract the effect of decreased funding, the CDC published a guide on high-impact prevention to maximize the effect of limited resources [
Despite the decrease in the annual number and rate of HIV diagnoses in the United States from 2015 to 2019 [
As public health efforts to reach HIV-positive individuals are hampered by financial constraints, an understanding of cost becomes crucial to investing in appropriate resources. In 2013, the CDC designed the “Start Talking. Stop HIV.” page on FB (as part of a larger “ACT against AIDS” campaign) to reach and influence gay and bisexual men to spark conversations about HIV prevention and sexual health [
For future implementation of our simulated models, ethical considerations targeting at-risk populations for HIV who are frequently marginalized and disadvantaged should include community advisory groups empowered by representatives of the proposed recipients of the ads. This will promote engagement in the development of the study design and ad’s content to accomplish inclusion of the targeted participants for intervention while balancing the concern of representation that may have a further stigmatizing effect. In addition, future implementation designs should ensure the protection of participants’ privacy while targeting vulnerable populations, which may generate an identifiable digital trail.
Since our study was conducted, multiple social media platforms have changed their policies to prevent targeting users younger than 18 years with disinformation. In addition, FB no longer allows targeting sexual orientation interests, which may hinder public health outreach efforts on the platform for sexual health education. Considering the challenge of misinformation spreading via social media platforms and the resulting societal harm [
Our study has several limitations that must be discussed. First, during the ad creation process for each state, the manually adjusted budget was rounded up to the closest US $10, which may falsely increase the estimated cost per click, cost per 1000 reach, and cost per new HIV diagnosis, especially in the states with the lowest potential reach. Second, we did not use the average health care industry CTR in our estimations, given that CTR is usually based on impressions, and the platform only provides estimated reach and estimated clicks during the process of ad creation. If estimated impressions were available during the creation of ads, we would have used the industry CTR to calculate estimated clicks from impressions and performed subsequent simulations. Third, potential reach, estimated daily reach, and estimated daily clicks were collected on the same day to avoid fluctuations that occurred based on different ads bidding and active FB users in the prior 30 days to data collection. All these estimates may change substantially when using a different time range given the fluctuations associated with the ad platform seasonality. Fourth, in our simulations, we used the positivity rates published in the CDC-funded HIV testing report from 2017, which has the most recently reported US data for test positivity rates for different age groups and US regions, and it may be different from the 2021 estimates. Fifth, we used the health care industry average conversion rate on FB as reported by WordStream based on a sample of 256 US clients in all industries between November 2016 and January 2017, which may also differ from the 2021 average health care conversion rate. Finally, our proposed feasibility model is subject to the limitations and algorithms of the social media platform because it is heavily based on estimates provided by the FB ad platform during the process of ad creation. FB ad estimates are based on multiple factors, including ad bids and active FB and Instagram users, may be intentionally misleading, and are not designed to match the census population.
Targeted FB ads have the potential to reach populations at risk for HIV and to facilitate education on exposure risks, HIV testing, and PrEP. This is especially critical in the Southern United States given the increased rates of new HIV diagnoses, high potential reach of FB, and low cost per new HIV diagnosis. Although FB allows targeted and granular location-based and interest-based ads at varying budgets (critical for public health interventions), our study found that multiple small-budget ads were more cost-efficient than 1 large-budget ad campaign. From a public health perspective, this translates into local FB ads being more economical than a single large-budget national FB ad. Therefore, our future efforts will leverage these findings by focusing on populations at risk for HIV in the Dallas-Fort Worth metroplex through different FB ads targeting strategies to delineate the best combination of interest- and location-based targeting criteria to improve HIV care.
Data published and supplementary data available [
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Centers for Disease Control and Prevention
click through rate
lesbian, gay, bisexual, and transgender
pre-exposure prophylaxis
RJM has received research grants from the Centers for Disease Control and Prevention and research funding from the Sergey Brin Family Foundation, the Verily Life Sciences, and the Texas Health Resources Clinical Scholars Program. None of the remaining authors have declared any conflict of interest. AEN receives research funds from Gilead Sciences. CUL is a shareholder of Celanese and Markel and received an honorarium from Springer.