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Sentiment Analysis of Twitter Posts Related to a COVID-19 Test & Trace Program in NYC

Tsai, Krystle A; Chau, Michelle M; Wang, Juncheng; Thorpe, Lorna E; Massar, Rachel E; Conderino, Sarah; Berry, Carolyn A; Islam, Nadia S; Bershteyn, Anna; Bragg, Marie A
As part of a program evaluation of the New York City Test & Trace program (T2)-one of the largest such programs in the USA-we conducted a study to assess how implementing organizations (NYC Health + Hospitals, government agencies, CBOs) communicated information about the T2 program on Twitter. Study aims were as follows: (1) quantify user engagement of posts ("tweets") about T2 by NYC organizations on Twitter and (2) examine the emotional tone of social media users' T2-related tweets in our sample of 1987 T2-related tweets. Celebrities and CBOs generated more user engagement (0.26% and 0.07%, respectively) compared to government agencies (e.g., Mayor's Office, 0.0019%), reinforcing the value of collaborating with celebrities and CBOs in social media public health campaigns. Sentiment analysis revealed that positive tweets (46.5%) had higher user engagement than negative tweets (number of likes: R2 = .095, p < .01), underscoring the importance of positively framing messages for effective public health campaigns.
PMCID:11461426
PMID: 39325247
ISSN: 1468-2869
CID: 5705772

Scale-Up of COVID-19 Testing Services in NYC, 2020-2021: Lessons Learned to Maximize Reach, Equity and Timeliness

Thorpe, Lorna E; Conderino, Sarah; Bendik, Stefanie; Berry, Carolyn; Islam, Nadia; Massar, Rachel; Chau, Michelle; Larson, Rita; Paul, Margaret M; Hong, Chuan; Fair, Andrew; Titus, Andrea R; Bershteyn, Anna; Wallach, Andrew
During infectious disease epidemics, accurate diagnostic testing is key to rapidly identify and treat cases, and mitigate transmission. When a novel pathogen is involved, building testing capacity and scaling testing services at the local level can present major challenges to healthcare systems, public health agencies, and laboratories. This mixed methods study examined lessons learned from the scale-up of SARS-CoV-2 testing services in New York City (NYC), as a core part of NYC's Test & Trace program. Using quantitative and geospatial analyses, the authors assessed program success at maximizing reach, equity, and timeliness of SARS-CoV-2 diagnostic testing services across NYC neighborhoods. Qualitative analysis of key informant interviews elucidated key decisions, facilitators, and barriers involved in the scale-up of SARS-CoV-2 testing services. A major early facilitator was the ability to establish working relationships with private sector vendors and contractors to rapidly procure and manufacture necessary supplies locally. NYC residents were, on average, less than 25 min away from free SARS-CoV-2 diagnostic testing services by public transport, and services were successfully directed to most neighborhoods with the highest transmission rates, with only one notable exception. A key feature was to direct mobile testing vans and rapid antigen testing services to areas based on real-time neighborhood transmission data. Municipal leaders should prioritize fortifying supply chains, establish cross-sectoral partnerships to support and extend testing services, plan for continuous testing and validation of assays, ensure open communication feedback loops with CBO partners, and maintain infrastructure to support mobile services during infectious disease emergencies.
PMCID:11461424
PMID: 39316309
ISSN: 1468-2869
CID: 5705752

Evaluation of the New York City COVID-19 case investigation and contact tracing program: a cascade of care analysis

Conderino, Sarah; E Thorpe, Lorna; Shilpi Islam, Nadia; A Berry, Carolyn; Bendik, Stefanie; Massar, Rachel; Hong, Chuan; Fair, Andrew; Bershteyn, Anna
BACKGROUND:New York City (NYC) was the first COVID-19 epicenter in the United States and home to one of the country's largest contact tracing programs, NYC Test & Trace (T2). Understanding points of attrition along the stages of program implementation and follow-up can inform contact tracing efforts for future epidemics or pandemics. The objective of this study was to evaluate the completeness and timeliness of T2 case and contact notification and monitoring using a "cascade of care" approach. METHODS:This cross-sectional study included all SARS-CoV-2 cases and contacts reported to T2 from May 31, 2020 to January 1, 2022. Attrition along the "cascade of care" was defined as: (1) attempted, (2) reached, (3) completed intake (main outcome), (4) eligible for monitoring, and (5) successfully monitored. Timeliness was assessed: (1) by median days from a case's date of testing until their positive result was reported to T2, (2) from result until the case was notified by T2, and (3) from a case report of a contact until notification of the contact. RESULTS:A total of 1.45 million cases and 1.38 million contacts were reported to T2 during this period. For cases, attrition occurred evenly across the first three cascade steps (~-12%) and did not change substantially until the Omicron wave in December 2021. During the Omicron wave, the proportion of cases attempted dropped precipitously. For contacts, the largest attrition occurred between attempting and reaching (-27%), and attrition rose with each COVID-19 wave as contact volumes increased. Attempts to reach contacts discontinued entirely during the Omicron wave. Overall, 67% of cases and 49% of contacts completed intake interviews (79% and 57% prior to Omicron). T2 was timely, with a median of 1 day to receive lab results, 2 days to notify cases, and < 1 day to notify contacts. CONCLUSIONS:T2 provided a large volume of NYC residents with timely notification and monitoring. Engagement in the program was lower for contacts than cases, with the largest gap coming from inability to reach individuals during call attempts. To strengthen future test-and-trace efforts, strategies are needed to encourage acceptance of local contact tracer outreach attempts.
PMCID:11363647
PMID: 39210385
ISSN: 1471-2458
CID: 5702042

Descriptive Epidemiology of New York City Older Adult Patients With Multiple Chronic Conditions

Conderino, Sarah; Dodson, John; Meng, Yuchen; Weiner, Mark G; Rabin, Catherine; Jacobs, Wilson; Bakshi, Parampreet; Lee, Melissa; Uguru, Jenny; Thorpe, Lorna E
We characterized comorbidity profiles and cardiometabolic risk factors among older adults with multiple chronic conditions (MCCs) in New York City using an intersectionality approach. Electronic health record data were obtained from the INSIGHT Clinical Research Network on 367,901 New York City residents aged 50 years or older with MCCs. Comorbidity profiles were heterogeneous. The most common profile across sex and racial and ethnic groups was co-occurring hypertension and hyperlipidemia; prevalence of these 2 conditions differed across groups (4.7%-7.3% co-occurrence alone, 65.1%-88.0% with other conditions). Significant sex and racial and ethnic differences were observed, which may reflect accumulated disparities in risk factors and health care access across the life course.
PMCID:11318948
PMID: 39089737
ISSN: 1545-1151
CID: 5696582

Decline in use of high-risk agents for tight glucose control among older adults with diabetes in New York City: 2017-2022

Zhang, Jeff; Kanchi, Rania; Conderino, Sarah; Levy, Natalie K; Adhikari, Samrachana; Blecker, Saul; Davis, Nichola; Divers, Jasmin; Rabin, Catherine; Weiner, Mark; Thorpe, Lorna; Dodson, John A
BACKGROUND:This study aimed to examine the prevalence of inappropriate tight glycemic control in older adults with type 2 diabetes and other chronic conditions in New York City, and to identify factors associated with this practice. METHODS:We conducted a retrospective cohort study using the INSIGHT Clinical Research Network. The study population included 11,728 and 15,196 older adults in New York City (age ≥ 75 years) with a diagnosis of type 2 diabetes, and at least one other chronic medical condition, in 2017 and 2022, respectively. The main outcome of interest was inappropriate tight glycemic control, defined as HbA1c <7.0% (<53 mmol/mol) with prescription of at least one high-risk agent (insulin or insulin secretagogue). RESULTS:The proportion of older adults with inappropriate tight glycemic control decreased by nearly 19% over a five-year period (19.4% in 2017 to 15.8% in 2022). There was a significant decrease in insulin (27.8% in 2017; 24.3% in 2022) and sulfonylurea (29.4% in 2017; 21.7% in 2022) medication prescription, and increase in use of GLP-1 agonists (1.8% in 2017; 11.4% in 2022) and SGLT-2 inhibitors (5.8% in 2017; 25.1% in 2022), among the total population. Factors associated with inappropriate tight glycemic control in 2022 included history of heart failure (adjusted odds ratio [aOR] 1.38), chronic kidney disease ([aOR] 1.93), colorectal cancer ([aOR] 1.38), acute myocardial infarction ([aOR] 1.28), "other" ([aOR] 0.72) or "unknown" ([aOR] 0.72) race, and a point increase in BMI ([aOR] 0.98). CONCLUSIONS:We found an encouraging trend toward less use of high-risk medication strategies for older adults with type 2 diabetes and multiple chronic conditions. However, one in six patients in 2022 still had inappropriate tight glycemic control, indicating a need for continued efforts to optimize diabetes management in this population.
PMCID:11368607
PMID: 38980267
ISSN: 1532-5415
CID: 5687172

Patterns and drivers of disparities in pediatric asthma outcomes among medicaid-enrolled children living in subsidized housing in NYC

Titus, Andrea R; Terlizzi, Kelly; Conderino, Sarah; Ðoàn, Lan N; Kim, Byoungjun; Thorpe, Lorna E
OBJECTIVE:There are persistent disparities in pediatric asthma morbidity in the U.S. We linked claims data with information on neighborhood-level risk factors to explore drivers of asthma disparities among Medicaid-enrolled children in New York City subsidized housing. METHODS:We constructed a cohort of Medicaid-enrolled children living in public or other subsidized housing, based on residential address, in NYC between 2016 and 2019 (n = 108,969). We examined claims-derived asthma prevalence across age and racial and ethnic groups, integrating census tract-level information and using the Bayesian Improved Surname Geocoding (BISG) algorithm to address high rates of missing data in self-reported race and ethnicity. We used inverse probability weighting (IPW) to explore the extent to which disparities persisted when exposure to asthma risk factors - related to the built environment, neighborhood poverty, and air quality - were balanced across groups. This analysis was conducted in 2022-2023. RESULTS:Claims-derived asthma prevalence was highest among children <7 years at baseline and among non-Hispanic Black and Hispanic children. For example, among children aged 3-6 years at baseline, claims-derived prevalence was 17.3% and 18.1% among non-Hispanic Black and Hispanic children, respectively, compared to 9.3% and 9.0% among non-Hispanic White and non-Hispanic Asian American/Pacific Islander children. Using IPW to balance exposure to asthma risk factors across racial and ethnic groups attenuated, but did not eliminate, disparities in asthma prevalence. CONCLUSIONS:We found high asthma burden among children living in subsidized housing. Modifiable place-based characteristics may be important contributors to pediatric asthma disparities.
PMID: 38908569
ISSN: 1096-0260
CID: 5672562

Antipsychotic drugs in first-episode psychosis: A target trial emulation in the FEP-CAUSAL Collaboration

Szmulewicz, Alejandro G; Martínez-Alés, Gonzalo; Logan, Roger; Ferrara, Maria; Kelly, Christian; Fredrikson, Diane; Gago, Juan; Conderino, Sarah; Díaz-Caneja, Covadonga M; Galvañ, Joaquín; Thorpe, Lorna; Srihari, Vinod; Yatham, Lakshmi; Sarpal, Deepak K; Shinn, Ann K; Arango, Celso; Öngür, Dost; Hernán, Miguel A; Fep-Causal Collaboration, On Behalf Of The
Good adherence to antipsychotic therapy helps prevent relapses in First Episode Psychosis (FEP). We used data from the FEP-CAUSAL Collaboration, an international consortium of observational cohorts to emulate a target trial comparing antipsychotics with treatment discontinuation as the primary outcome. Other outcomes included all-cause hospitalization. We benchmarked our results to estimates from EUFEST, a randomized trial conducted in the 2000s. We included 1097 patients with a psychotic disorder and less than 2 years since psychosis onset. Inverse probability weighting was used to control for confounding. The estimated 12-month risks of discontinuation for aripiprazole, first-generation agents, olanzapine, paliperidone, quetiapine, and risperidone (95% CI) were: 61.5% (52.5-70.6), 73.5% (60.5-84.9), 76.8% (67.2-85.3), 58.4% (40.4-77.4), 76.5% (62.1-88.5), and 74.4% (67.0-81.2) respectively. Compared with aripiprazole, the 12-month risk differences (95% CI) were -15.3% (-30.0, 0.0) for olanzapine, -12.8% (-25.7, -1.0) for risperidone, and 3.0% (-21.5, 30.8) for paliperidone. The 12-month risks of hospitalization were similar between agents. Our estimates support use of aripiprazole and paliperidone as first-line therapies for FEP. Benchmarking yielded similar results for discontinuation and absolute risks of hospitalization as in the original trial, suggesting that data from the FEP-CAUSAL Collaboration data sufficed to approximately remove confounding for these clinical questions.
PMID: 38576166
ISSN: 1476-6256
CID: 5653302

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network

Hirsch, Annemarie G; Conderino, Sarah; Crume, Tessa L; Liese, Angela D; Bellatorre, Anna; Bendik, Stefanie; Divers, Jasmin; Anthopolos, Rebecca; Dixon, Brian E; Guo, Yi; Imperatore, Giuseppina; Lee, David C; Reynolds, Kristi; Rosenman, Marc; Shao, Hui; Utidjian, Levon; Thorpe, Lorna E; ,
INTRODUCTION:Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS:The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION:The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.
PMCID:10806714
PMID: 38233060
ISSN: 2044-6055
CID: 5626662

Beyond traffic jam alleviation: evaluating the health and health equity impacts of New York City's congestion pricing plan

Ghassabian, Akhgar; Titus, Andrea R; Conderino, Sarah; Azan, Alexander; Weinberger, Rachel; Thorpe, Lorna E
New York City (NYC) is slated to be the first jurisdiction in the USA to implement a cordon-based congestion tax, which will be levied on vehicles entering its Central Business District. Several cities around the world, for example, London and Stockholm, have had similar cordon-based pricing programmes, defined as road pricing that charges drivers a fee for entering a specified area (typically a congested urban centre). In addition to reducing congestion and creating revenue, projections suggest the NYC congestion pricing plan may yield meaningful traffic-related air quality improvements that could result in health benefits. NYC is a large city with high air pollution and substantial racial/ethnic and socioeconomic health inequities. The distinct geography and meteorological conditions of the city also suggest that the policy's impact on air quality may extend beyond the NYC metropolitan area. As such, the potential breadth, directionality and magnitude of health impacts on communities who might be heavily affected by the nation's first congestion pricing plan should be empirically investigated. We briefly review evaluation studies of other cordon-based congestion pricing policies and argue that implementation of this policy provides an excellent opportunity to employ a quasi-experimental study design to evaluate the policy's impacts on air quality and health outcomes across population subgroups using a health equity lens. We discuss why real-time evaluations of the NYC congestion pricing plan can potentially help optimise benefits for communities historically negatively affected by traffic-related air pollution. Assessing intended and unintended impacts on health equity is key to achieving these goals.
PMID: 38195634
ISSN: 1470-2738
CID: 5624072

Association between racial residential segregation and walkability in 745 U.S. cities

Spoer, Ben R; Conderino, Sarah E; Lampe, Taylor M; Ofrane, Rebecca H; De Leon, Elaine; Thorpe, Lorna E; Chang, Virginia W; Elbel, Brian
Despite higher chronic disease prevalence, minoritized populations live in highly walkable neighborhoods in US cities more frequently than non-minoritized populations. We investigated whether city-level racial residential segregation (RRS) was associated with city-level walkability, stratified by population density, possibly explaining this counterintuitive association. RRS for Black-White and Latino-White segregation in large US cities was calculated using the Index of Dissimilarity (ID), and walkability was measured using WalkScore. Median walkability increased across increasing quartiles of population density, as expected. Higher ID was associated with higher walkability; associations varied in strength across strata of population density. RRS undergirds the observed association between walkability and minoritized populations, especially in higher population density cities.
PMID: 37774640
ISSN: 1873-2054
CID: 5602802