Digital health is having a profound effect on health systems, changing the balance of power between provider and patient, enabling new models of care, and shifting the focus of health systems toward client-centered health care within low-and middle-income countries. Though many of these changes are just being felt due to resistance by organizations and individuals reluctant to change the status quo, the explosive growth of digital technology globally means that these changes are inevitable. We can expect to see increasing use of telemedicine for remote diagnostics and treatment, protocol-driven health care to improve quality of care, and better access to goods and services through changes in the organization of transportation and delivery services. Data will become central to health systems, whether big data and artificial intelligence tools for surveillance, planning, and management or "personalized data" in the form of universal electronic record systems and customized treatment protocols. As with any disruptive innovation, the growth of digital health will also bring challenges, including who owns, controls, and manages the data being collected and how to maintain privacy and confidentiality in this data-rich world.

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Introduction As oral pre‐exposure prophylaxis (PrEP) services scale up throughout sub‐Saharan Africa (SSA), clients continue to face challenges with sustained PrEP use. PrEP‐related stigma has been shown to influence engagement throughout the HIV PrEP care continuum throughout SSA. Validated quantitative measures of PrEP‐related stigma in SSA are of critical importance to better understand its impacts at each stage of the HIV PrEP care continuum. This study aimed to psychometrically evaluate a PrEP‐related stigma scale for use among key and vulnerable populations in the context of a Kenya national PrEP programme. Methods As part of a larger prospective cohort study nested within Kenya's Jilinde programme, this study used baseline data collected from 1135 participants between September 2018 and April 2020. We used exploratory factor analysis to evaluate the factor structure of a PrEP‐related stigma scale. We also assessed convergent construct validity of the PrEP‐Related Stigma Scale by testing for expected correlations with depression and uptake of HIV services. Finally, we examined the relationship between PrEP‐related stigma and key demographic, psychosocial and behavioural characteristics. Results We identified four dimensions of PrEP‐related stigma: (1) interpersonal stigma, (2) PrEP norms, (3) negative self‐image and (4) disclosure concerns. The scale demonstrated strong internal consistency (α = 0.84), was positively correlated with depressive symptoms and negatively correlated with uptake of HIV services. Multivariable regression analysis demonstrated associations between PrEP‐related stigma and sex worker identity. Conclusions The adapted and validated PrEP‐Related Stigma Scale can enable programmes to quantify how PrEP‐related stigma and its dimensions may differentially impact outcomes on the HIV PrEP care continuum, evaluate stigma interventions and tailor programmes accordingly. Opportunities exist to validate the scale in other populations and explore further dimensions of PrEP‐related stigma.

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BACKGROUND Highly effective COVID-19 vaccines are available and free of charge in the United States. With adequate coverage, their use may help return life back to normal and reduce COVID-19–related hospitalization and death. Many barriers to widespread inoculation have prevented herd immunity, including vaccine hesitancy, lack of vaccine knowledge, and misinformation. The Ad Council and COVID Collaborative have been conducting one of the largest nationwide targeted campaigns (“It’s Up to You”) to communicate vaccine information and encourage timely vaccination across the United States. More than 300 major brands, digital and print media companies, and community-based organizations support the campaigns to reach distinct audiences. OBJECTIVE The goal of this study was to use aggregated mobility data to assess the effectiveness of the campaign on COVID-19 vaccine uptake. METHODS Campaign exposure data were collected from the Cuebiq advertising impact measurement platform consisting of about 17 million opted-in and deidentified mobile devices across the country. A Bayesian spatiotemporal hierarchical model was developed to assess campaign effectiveness through estimating the association between county-level campaign exposure and vaccination rates reported by the Centers for Disease Control and Prevention. To minimize potential bias in exposure to the campaign, the model included several control variables (eg, age, race or ethnicity, income, and political affiliation). We also incorporated conditional autoregressive residual models to account for apparent spatiotemporal autocorrelation. RESULTS The data set covers a panel of 3104 counties from 48 states and the District of Columbia during a period of 22 weeks (March 29 to August 29, 2021). Officially launched in February 2021, the campaign reached about 3% of the anonymous devices on the Cuebiq platform by the end of March, which was the start of the study period. That exposure rate gradually declined to slightly above 1% in August 2021, effectively ending the study period. Results from the Bayesian hierarchical model indicate a statistically significant positive association between campaign exposure and vaccine uptake at the county level. A campaign that reaches everyone would boost the vaccination rate by 2.2% (95% uncertainty interval: 2.0%-2.4%) on a weekly basis, compared to the baseline case of no campaign. CONCLUSIONS The “It’s Up to You” campaign is effective in promoting COVID-19 vaccine uptake, suggesting that a nationwide targeted mass media campaign with multisectoral collaborations could be an impactful health communication strategy to improve progress against this and future pandemics. Methodologically, the results also show that location intelligence and mobile phone–based monitoring platforms can be effective in measuring impact of large-scale digital campaigns in near real time.