BackgroundSocial media have been increasingly adopted by health agencies to disseminate information, interact with the public, and understand public opinion. Among them, the Centers for Disease Control and Prevention (CDC) is one of the first US government health agencies to adopt social media during health emergencies and crisis. It had been active on Twitter during the 2016 Zika epidemic that caused 5168 domestic noncongenital cases in the United States.ObjectiveThe aim of this study was to quantify the temporal variabilities in CDC’s tweeting activities throughout the Zika epidemic, public engagement defined as retweeting and replying, and Zika case counts. It then compares the patterns of these 3 datasets to identify possible discrepancy among domestic Zika case counts, CDC’s response on Twitter, and public engagement in this topic.MethodsAll of the CDC-initiated tweets published in 2016 with corresponding retweets and replies were collected from 67 CDC–associated Twitter accounts. Both univariate and multivariate time series analyses were performed in each quarter of 2016 for domestic Zika case counts, CDC tweeting activities, and public engagement in the CDC-initiated tweets.ResultsCDC sent out >84.0% (5130/6104) of its Zika tweets in the first quarter of 2016 when Zika case counts were low in the 50 US states and territories (only 560/5168, 10.8% cases and 662/38,885, 1.70% cases, respectively). While Zika case counts increased dramatically in the second and third quarters, CDC efforts on Twitter substantially decreased. The time series of public engagement in the CDC-initiated tweets generally differed among quarters and from that of original CDC tweets based on autoregressive integrated moving average model results. Both original CDC tweets and public engagement had the highest mutual information with Zika case counts in the second quarter. Furthermore, public engagement in the original CDC tweets was substantially correlated with and preceded actual Zika case counts.ConclusionsConsiderable discrepancies existed among CDC’s original tweets regarding Zika, public engagement in these tweets, and actual Zika epidemic. The patterns of these discrepancies also varied between different quarters in 2016. CDC was much more active in the early warning of Zika, especially in the first quarter of 2016. Public engagement in CDC’s original tweets served as a more prominent predictor of actual Zika epidemic than the number of CDC’s original tweets later in the year.

Background This study aimed to examine the early experience of nusinersen for spinal muscular atrophy (SMA) from the patient and caregiver perspective. Methods A 54‐item online survey was administered to adult patients and caregivers of pediatric patients diagnosed with SMA. Results Overall, respondents (56 patients and 45 caregivers) were satisfied with nusinersen. Satisfaction was highest on changes in energy, stamina, and motor function and lowest on treatment administration and overall time commitment. Differences were noted for treatment effect sustained over time as reported by adult patients vs caregivers reporting on behalf of pediatric patients. Respondents reported insurance approval as a key barrier to access, particularly among adult patients. Conclusions Despite therapeutic advances, there remain significant unmet needs for SMA. Challenges with administration and barriers to access potentially limit the number of patients treated or delay treatment. Continued efforts are needed to develop more treatment options and to improve access to treatments.

Background Hypoglycemia prognostic models contingent on prospective, self-reported survey data offer a powerful avenue for determining real-world event susceptibility and interventional targets. Objective This protocol describes the design and implementation of the 1-year iNPHORM (Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-world Models) study, which aims to measure real-world self-reported severe and nonsevere hypoglycemia incidence (daytime and nocturnal) in American adults with type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues, and develop and internally validate prognostic models for severe, nonsevere daytime, and nonsevere nocturnal hypoglycemia. As a secondary objective, iNPHORM aims to quantify the effects of different antihyperglycemics on hypoglycemia rates. Methods iNPHORM is a prospective, 12-wave internet-based panel survey that was conducted across the United States. Americans (aged 18-90 years) with self-reported type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues were conveniently sampled via the web from a pre-existing, closed, probability-based internet panel (sample frame). A sample size of 521 baseline responders was calculated for this study. Prospective data on hypoglycemia and potential prognostic factors were self-assessed across 14 closed, fully automated questionnaires (screening, baseline, and 12 monthly follow-ups) that were piloted using semistructured interviews (n=3) before fielding; no face-to-face contact was required as part of the data collection. Participant responses will be analyzed using multivariable count regression and machine learning techniques to develop and internally validate prognostic models for 1-year severe and 30-day nonsevere daytime and nocturnal hypoglycemia. The causal effects of different antihyperglycemics on hypoglycemia rates will also be investigated. Results Recruitment and data collection occurred between February 2020 and March 2021 (ethics approval was obtained on December 17, 2019). A total of 1694 participants completed the baseline questionnaire, of whom 1206 (71.19%) were followed up for 12 months. Most follow-up waves (10,470/14,472, 72.35%) were completed, translating to a participation rate of 179% relative to our target sample size. Over 70.98% (856/1206) completed wave 12. Analyses of sample characteristics, quality metrics, and hypoglycemia incidence and prognostication are currently underway with published results anticipated by fall 2022. Conclusions iNPHORM is the first hypoglycemia prognostic study in the United States to leverage prospective, longitudinal self-reports. The results will contribute to improved real-world hypoglycemia risk estimation and potentially safer, more effective clinical diabetes management. Trial Registration ClinicalTrials.gov NCT04219514; https://clinicaltrials.gov/ct2/show/NCT04219514 International Registered Report Identifier (IRRID) DERR1-10.2196/33726

Main objectiveTo determine how and to what extent COVID-19 has affected real-world, self-reported glycaemic management in Americans with type 1 or type 2 diabetes taking insulin and/or secretagogues, with or without infection.DesignA cross-sectional substudy using data from the Investigating Novel Predictions of Hypoglycemia Occurrence using Real-world Models panel survey.SettingUSA.ParticipantsAmericans 18–90 years old with type 1 or 2 diabetes taking insulin and/or secretagogues were conveniently sampled from a probability-based internet panel.Primary outcome measureA structured, COVID-19-specific questionnaire was administered to assess the impact of the pandemic (irrespective of infection) on socioeconomic, behavioural/clinical and psychosocial aspects of glycaemic management.ResultsData from 667 respondents (type 1 diabetes: 18%; type 2 diabetes: 82%) were analysed. Almost 25% reported A1c values ≥8.1%. Rates of severe and non-severe hypoglycaemia were 0.68 (95% CI 0.5 to 0.96) and 2.75 (95% CI 2.4 to 3.1) events per person-month, respectively. Ten respondents reported a confirmed or probable COVID-19 diagnosis. Because of the pandemic, 24% of respondents experienced difficulties affording housing; 28% struggled to maintain sufficient food to avoid hypoglycaemia; and 19% and 17% reported challenges accessing diabetes therapies and testing strips, respectively. Over one-quarter reported issues retrieving antihyperglycaemics from the pharmacy and over one-third reported challenges consulting with diabetes providers. The pandemic contributed to therapeutic non-adherence (14%), drug rationing (17%) and reduced monitoring (16%). Many struggled to keep track, and in control, of hypoglycaemia (12%–15%) and lacked social support to help manage their risk (19%). Nearly half reported decreased physical activity. Few statistically significant differences were observed by diabetes type.ConclusionsCOVID-19 was found to cause substantial self-reported deficiencies in glycaemic management. Study results signal the need for decisive action to restabilise routine diabetes care in the USA.Trial registration numberNCT04219514.

All MAAs offered a simple discount patient access scheme and/or a reduced drug cost commercial access agreement. CONCLUSIONS: New NICE approved MAAs increased each year since 2015, were characterised by a standard format structured around the data required to answer key uncertainties and always included financial agreements to minimise NHS treatment costs during the MAA period.