Takeaways from APHA 2019

With nearly 13,000 attendees and 90 concurrent sessions at any given time, the American Public Health Association (APHA) Meeting and Expo is the largest annual gathering of public health professionals. It’s a big event, so it can be overwhelming, but its size provides room for diverse perspectives, multiple emerging issues, and countless innovative solutions to both longstanding and emerging public health challenges.

Though it’s impossible to absorb everything at a conference of this size, I noted two main takeaways during my time at APHA 2019:

  • Social media data is becoming more visible in public health research and can help guide program planning and evaluation
  • There is a continuing push toward linking clinical and community interventions through multisectoral partnerships to address health disparities and social determinants of health

The Use of Social Media to Inform Program Planning and Evaluation

One of the sessions I attended at APHA 2019 highlighted how new data—especially those extracted from social media—have emerged and are being used more frequently in public health research, programming, and evaluation.

Social media provides large publicly available data sets that can provide public health professionals with unique information about a given population. For example, if curated effectively, social media data can inform and guide local, community-based interventions by providing program planners with a better understanding of how the community feels about and responds to topics such as e-cigarettes and immunization.

That said, those data sources are not without their limitations. In addition to inherent biases that often accompany social media-derived data sets, it can also be difficult to detect and remove profiles and posts created by bots. While tools exist to identify bots, their presence continues to impact the credibility and acceptability of social media data.

Though there are challenges to overcome, effective curating of social media posts can provide public health researchers with unique information about a given population and can be useful resources in formative research. Public health practitioners and researchers are still fine-tuning how to maximize the utility of the data. 

RTI has contributed to the emerging science around effective use of social media as a public health data source. For example, we have been developing innovative methods such as: 1) computational algorithms that predict the type and age of individuals who post about e-cigarettes online (Morgan-Lopez et al., 2017; Kim et al., 2017); 2) examining whether youth are being exposed to JUUL e-cigarette marketing on social media (Kim et al., 2019); and 3) in using targeted social media advertisements to recruit survey participants (Guillory et al., 2016; Guillory et al., 208).

Leveraging Multisector Partnerships to Link Clinical and Community Interventions

My second takeaway from APHA 2019 was that there is a continuing focus on leveraging multisector partnerships to link clinical and community interventions to better address social determinants of health. This is a theme that I have found influential in my own work as a chronic disease prevention program evaluator.

I have had the opportunity to interview public health practitioners and clinicians who are working to better understand and help their patients or program participants overcome barriers to accessing preventive health services, managing chronic diseases, and maintaining a healthy lifestyle. We cannot design and evaluate a highly successful program targeting a specific chronic disease, such as diabetes, without also understanding these barriers and other social determinants of health.

The practitioners I’ve spoken with understand that working with underserved populations requires building trust and developing an authentic understanding of the populations’ needs, appropriately tailoring programs and services to meet those needs, building and strengthening relationships with diverse partners, and commitment and flexibility to continuously improve programs and services.   

Due to the growing recognition of the importance of social determinants of health, many funders are requiring programs to build multisectoral partnerships among community based organizations and clinical providers to address health disparities. We have already begun to see more funding opportunities requiring approaches such as these, and expect to see more requests for proposals to evaluate these approaches in the future.

Although these types of programs could address the root causes of many public health issues, it is difficult to define outcomes for these upstream efforts because it can take years for long-term health outcomes such as a decrease in disease prevalence to manifest. Since many public health programs are federally funded and, therefore, pressured to report on concrete outcomes, it could be challenging to secure funding for long-term studies that could evaluate whether and how these approaches yield desirable health outcomes.

In response to that challenge, RTI must determine how to define outcomes for upstream approaches attempting to establish multisectoral partnerships and address health issues more holistically. We need to think more critically and creatively about how we structure the evaluation process, and we have to support the momentum around linking clinical and community interventions to address social determinants of health by disseminating relevant data and program successes.

As a qualitative researcher, I’ve learned that there is no one correct approach, no one-size-fits-all solution to public health challenges, and there is no point at which the tools we use to advance the science of public health will stop evolving. APHA 2019 reminded me that there are still developing opportunities in public health, and I look forward to exploring them further and adding value to the field  with RTI.



Guillory J, Kim A, Murphy J, et al. Comparing twitter and online panels for survey recruitment of e-cigarette users and smokers. J Med Internet Res 2016;18(11):e288. doi:10.2196/jmir.6326.

Guillory, J., Wiant, K. F., Farrelly, M., Fiacco, L., Alam, I., Hoffman, L., ... & Alexander, T. N. (2018). Recruiting Hard-to-Reach Populations for Survey Research: Using Facebook and Instagram Advertisements and In-Person Intercept in LGBT Bars and Nightclubs to Recruit LGBT Young Adults. Journal of medical Internet research, 20(6), e197.

Kim A, Miano T, Chew R, Eggers M, Nonnemaker J (2017). Classification of Twitter Users Who Tweet About E-Cigarettes. JMIR public health and surveillance. 23(3):e63.

Kim AE,  Chew R, Wenger M, et al (2019).  Estimated ages of JUUL Twitter Followers.  JAMA Pediatr. 2019;173(7):690-692. doi:10.1001/jamapediatrics.2019.0922

Morgan-Lopez AA, Kim AE, Chew RF, Ruddle P (2017).Predicting age groups of Twitter users based on language and metadata features. PloS one. 2017; 12(8):e0183537.