A satellite-derived dataset on vegetation phenology across Central Asia from 2001 to 2023.

Satellite-observed land surface phenology (LSP) data have helped us better understand terrestrial ecosystem dynamics at large scales. However, uncertainties remain in comprehending LSP variations in Central Asian drylands. In this article, an LSP dataset covering Central Asia (45-100°E, 33-57°N) is introduced. This LSP dataset was produced based on Moderate Resolution Imaging Spectroradiometer (MODIS) 0.05-degree daily reflectance and land cover data. The phenological dynamics of drylands were tracked using the seasonal profiles of near-infrared reflectance of vegetation (NIRv). NIRv time series processing involved the following steps: identifying low-quality observations, smoothing the NIRv time series, and retrieving LSP metrics. In the smoothing step, a median filter was first applied to reduce spikes, after which the stationary wavelet transform (SWT) was used to smooth the NIRv time series. The SWT was performed using the Biorthogonal 1.1 wavelet at a decomposition level of 5. Seven LSP metrics were provided in this dataset, and they were categorized into the following three groups: (1) timing of key phenological events, (2) NIRv values essential for the detection of the phenological events throughout the growing season, and (3) NIRv value linked to vegetation growth state during the growing season. This LSP dataset is useful for investigating dryland ecosystem dynamics in response to climate variations and human activities across Central Asia.

Motor improvement of remote programming in patients with Parkinson's disease after deep brain stimulation: a 1-year follow-up.

Background: Remote programming (RP) is an emerging technology that enables the adjustment of implantable pulse generators (IPGs) via the Internet for people with Parkinson's disease (PwPD) who have undergone deep brain stimulation (DBS). Previous studies have not comprehensively explored the effectiveness of RP in managing motor symptoms, often omitting assessments such as the rigidity and retropulsion tests during the follow-up. This study evaluates the comprehensive improvements in motor performance and the potential cost benefits of RP for PwPD with DBS. Methods: A retrospective analysis was conducted on two groups of patients-those who received RP and those who received standard programming (SP). Clinical outcomes including motor improvement, quality of life, and daily levodopa dosage were compared between the groups during a 12 (± 3)-month in-clinic follow-up. Results: A total of 44 patients were included in the study, with 18 in the RP group and 26 in the SP group. No significant differences were observed in the frequency of programming sessions or clinical outcomes between the groups (p > 0.05). However, the RP group experienced significantly lower costs per programming session than the SP group (p < 0.05), despite patients in the former group living further from our center (p < 0.05). Conclusions: Our findings suggest that RP could significantly reduce the costs of programming for PwPD with DBS, especially without compromising the effectiveness of treatment across all motor symptoms in the short term.

Virtual Objective Structured Clinical Examination (OSCE) Training in the Pandemic Era: Feasibility, Satisfaction, and the Road Ahead.

INTRODUCTION: Objective Structured Clinical Examinations (OSCEs) are essential assessments for evaluating the clinical competencies of medical students. The COVID-19 pandemic caused a significant disruption in medical education, prompting institutions to adopt virtual formats for academic activities. This study analyzes the feasibility, satisfaction, and experiences of pediatric board candidates and faculty during virtual or electronic OSCE (e-OSCE) training sessions using Zoom video communication (Zoom Video Communications, Inc., San Jose, USA). METHODS: This is a post-event survey assessing the perceptions of faculty and candidates and the perceived advantages and obstacles of e-OSCE. RESULTS: A total of 142 participants were invited to complete a post-event survey, and 105 (73.9%) completed the survey. There was equal gender representation. More than half of the participants were examiners. The overall satisfaction with the virtual e-OSCE was high, with a mean score of 4.7±0.67 out of 5. Most participants were likely to recommend e-OSCE to a friend or colleague (mean score 8.84±1.51/10). More faculty (66.1%) than candidates (40.8%) preferred e-OSCE (P=0.006). CONCLUSION: Transitioning to virtual OSCE training during the pandemic proved feasible, with high satisfaction rates. Further research on virtual training for OSCE in medical education is recommended to optimize its implementation and outcomes.

Temperature and ST-segment morphology remote monitoring: new perspectives for implantable cardiac monitors in Brugada syndrome.

INTRODUCTION: Patients with Brugada syndrome (BrS) face an increased risk of ventricular arrhythmias and sudden cardiac death. Implantable cardiac monitors (ICMs) have emerged as effective tools for detecting arrhythmias in BrS. Technological advancements, including temperature sensors and improved subcutaneous electrocardiogram (subECG) signal quality, hold promise for further enhancing their utility in this population. METHODS AND RESULTS: We present a case of a 40-year-old man exhibiting a BrS type 2 pattern on 12-lead ECG, who underwent ICM insertion (BIOMONITOR IIIm, BIOTRONIK) due to drug-induced BrS type 1 pattern and a history of syncope, with a negative response to programmed ventricular stimulation. The device contains an integrated temperature sensor and can transmit daily vital data, such as mean heart rate and physical activity. Several months later, remote alerts indicated a temperature increase, along with transmitted subECGs suggesting a fever-induced BrS type 1 pattern. The patient was promptly advised to commence antipyretic therapy. Over the following days, remotely monitored parameters showed decreases in mean temperature, physical activity, and mean heart rate, without further recurrence of abnormal subECGs. CONCLUSION: ICMs offer valuable insights beyond arrhythmia detection in BrS. Early detection of fever using embedded temperature sensors may improve patient management, while continuous subECG morphological analysis has the potential to enhance risk stratification in BrS patients.

Telemedicine and Remote Management of Patients with Heart Failure: From Theory to Daily Practice.

Background: Heart failure (HF) is responsible for a high number of hospitalizations, caused by a progressive worsening quality of life. Telemedicine allows for better management of patients' complex conditions, improving the care released. However, the risk of remaining at a testing stage often limits the integration of remote care in daily pathways for HF patients. The aim of this study is to outline the steps needed to integrate telemedicine activities into ordinary HF clinic practices. This methodology is applied to observe activities and trend improvements over a 12-month routine phase. Method: Three steps have been defined for an efficient introduction of remote care services in ordinary activities, integrating them with traditional in-person care: (i) introduction of temporary telemedicine projects, (ii) systematization of telemedicine pathways, and (iii) evaluation of monitoring phase. Observational data have been collected from structured interviews to show the rate of telemedicine activities achieved in clinical practice over the last year. Results: The methodology has been proposed in the HF clinic of the Italian hospital ASST Bergamo Est. After an initial testing phase, in which usability and user experience have been tested, four different remote activities were added: (i) telemonitoring for patients with an implantable device, (ii) follow-up televisits, (iii) nursing telephone support, and (iv) high-intensity telesurveillance pathways for patients after an HF acute event. During the last year, 218 telemonitoring pathways, 75 televisits, 500 telephone calls, and nine telesurveillance pathways have been performed. Success rates were high, and patients gave positive feedback. Conclusion: By integrating multiple telemedicine activities, it has been possible to better manage complex patients, keep track of disease progression, and improve their participation in care.

Impact of Remote Patient Monitoring Systems on Nursing Time, Healthcare Providers, and Patient Satisfaction in General Wards.

INTRODUCTION: Remote patient monitoring systems (RPMS) are increasingly integrated into hospital wards to improve patient safety and reduce the workload on healthcare professionals (HCPs). This study evaluates the efficacy of RPMS in general wards, focusing on their impact on nursing efficiency, patient care, HCPs, and patient satisfaction. METHODS: A comprehensive time-motion study was conducted along with surveys targeting HCPs and patients in M.S. Ramaiah Memorial Hospital, Bangalore, India, which has implemented RPMS in general wards. The study involved observing and comparing nursing activities in RPMS-equipped wards versus control wards without RPMS across various shifts. In addition, feedback on the system's impact on patient safety, overall care quality, and usability was gathered through a survey form. RESULTS: RPMS decreases the amount of time nurses spend on routine monitoring, communication, and coordination, enabling a 43.11% increase in time available for patient care. More than 89% of HCPs noted improvements in the level of care and overall patient safety. More than 80% of the HCPs also noted improvement in the patient's experience. More than 50% of HCPs find RPMS easy to use and user-friendly. More than 60% of the patients noted an overall improvement in care quality. CONCLUSION: RPMS has proven to be a valuable asset in hospital wards, enhancing patient monitoring and safety while reducing the workload on staff. In addition, significant time savings on routine tasks and high satisfaction levels from both staff and patients underscore the system's benefits.

Research progress on the mechanism of action and clinical application of remote ischemic post-conditioning for acute ischemic stroke.

Remote ischemic post-conditioning (RIPostC) can reduce cerebral ischemia reperfusion injury (IRI) by inducing endogenous protective effects, the distal limb ischemia post-treatment and in situ ischemia post-treatment were classified according to the site of intervention. And in the process of clinical application distal limb ischemia post-treatment is more widely used and more conducive to clinical translation. Therefore, in this paper, we review the mechanism of action and clinical application of RIPostC in cerebral ischemia, hoping to provide reference help for future experimental directions and clinical translation.

Multidisciplinary approach to diagnostic radiology education: a novel educational intervention for Turkish medical students.

Teleconferencing can facilitate a multidisciplinary approach to teaching radiology to medical students. This study aimed to determine whether an online learning approach enables students to appreciate the interrelated roles of radiology and other specialties during the management of different medical cases. Turkish medical students attended five 60-90-minute online lectures delivered by radiologists and other specialists from the United States and Canada through Zoom meetings between November 2020 and January 2021. Student ambassadors from their respective Turkish medical schools recruited their classmates with guidance from the course director. Students took a pretest and posttest to assess the knowledge imparted from each session and a final course survey to assess their confidence in radiology and the value of the course. A paired t-test was used to assess pretest and posttest score differences. A 4-point Likert-type scale was used to assess confidence rating differences before and after attending the course sessions. A total of 1,458 Turkish medical students registered for the course. An average of 437 completed both pre- and posttests when accounting for all five sessions. Posttest scores were significantly higher than pretest scores for each session (P < 0.001). A total of 546 medical students completed the final course survey evaluation. Students' rating of their confidence in their radiology knowledge increased after taking the course (P < 0.001). Students who took our course gained an appreciation for the interrelated roles of different specialties in approaching medical diagnoses and interpreting radiological findings. These students also reported an increased confidence in radiology topics and rated the course highly relevant and insightful. Overall, our findings indicated that multidisciplinary online education can be feasibly implemented for medical students by video teleconferencing.

Socio-economic differences in remote schoolwork during the COVID-19 pandemic: a trend analysis of the 2020 and 2021 school-closure periods using the UK Understanding Society data.

In the United Kingdom, the COVID-19 pandemic in 2020 and 2021 led to two extended periods of school closures. Research on inequality of learning opportunity as a result of these closures used a single indicator of socio-economic status, neglecting important determinants of remote learning. Using data from the Understanding Society (USoc) COVID-19 surveys we analysed the levels and differentials in the uptake of remote schoolwork using parental social class, information technology (IT) availability in the home and parental working patterns to capture the distinct resources that families needed to complete remote schoolwork. This is also the first study to assess the extent to which the differentials between socio-economic groups changed between the first and second school-closure periods caused by the pandemic. We found that each of the three factors showed an independent association with the volume of remote schoolwork and that their effect was magnified by their combination. Children in families where the main parent was in an upper-class occupation, where both parents worked from home and where the children had their own IT spent more time doing remote schoolwork than other groups, particularly compared to children of single parents who work from home, children in families where the main parent was in a working-class occupation, where the child had to share IT, and where the parents did not work regularly from home. The differentials between socio-economic groups in the uptake of schoolwork were found to be stable between the two school-closure periods.

Spectral enhancement of PlanetScope using Sentinal-2 images to estimate soybean yield and seed composition.

Soybean is an essential crop to fight global food insecurity and is of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during crop growth and development influences nutrient accumulation in soybean seeds, remote sensing offers a unique opportunity to estimate seed traits from the standing crops. Capturing phenological developments that influence seed composition requires frequent satellite observations at higher spatial and spectral resolutions. This study introduces a novel spectral fusion technique called multiheaded kernel-based spectral fusion (MKSF) that combines the higher spatial resolution of PlanetScope (PS) and spectral bands from Sentinel 2 (S2) satellites. The study also focuses on using the additional spectral bands and different statistical machine learning models to estimate seed traits, e.g., protein, oil, sucrose, starch, ash, fiber, and yield. The MKSF was trained using PS and S2 image pairs from different growth stages and predicted the potential VNIR1 (705 nm), VNIR2 (740 nm), VNIR3 (783 nm), SWIR1 (1610 nm), and SWIR2 (2190 nm) bands from the PS images. Our results indicate that VNIR3 prediction performance was the highest followed by VNIR2, VNIR1, SWIR1, and SWIR2. Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images.

Prediction of heart failure events based on physiologic sensor data in HINODE defibrillator patients.

AIMS: Hospitalizations are common in patients with heart failure and are associated with high mortality, readmission and economic burden. Detecting early signs of worsening heart failure may enable earlier intervention and reduce hospitalizations. The HeartLogic algorithm is designed to predict worsening heart failure using diagnostic data from multiple device sensors. The main objective of this analysis was to evaluate the sensitivity of the HeartLogic alert calculation in predicting worsening heart failure events (HFEs). We also evaluated the false positive alert rate (FPR) and compared the incidence of HFEs occurring in a HeartLogic alert state to those occurring out of an alert state. METHODS: The HINODE study enrolled 144 patients (81 ICD and 63 CRT-D) with device sensor data transmitted via a remote monitoring system. HeartLogic alerts were then retrospectively simulated using relevant sensor data. Clinicians and patients were blinded to calculated alerts. Reported adverse events with HF symptoms were adjudicated and classified by an independent HFE committee. Sensitivity was defined as the ratio of the number of detected usable HFEs (true positives) to the total number of usable HFEs. A false positive alert was defined as an alert with no usable HFE between the alert onset date and the alert recovery date plus 30 days. The patient follow-up period was categorized as in alert state or out of alert state. The event rate ratio was the HFE rate calculated in alert to out of alert. RESULTS: The patient cohort was 79% male and had an average age of 68 ± 12 years. This analysis yielded 244 years of follow-up data with 73 HFEs from 37 patients. A total of 311 HeartLogic alerts at the nominal threshold (16) occurred across 106 patients providing an alert rate of 1.27 alerts per patient-year. The HFE rate was 8.4 times greater while in alert compared with out of alert (1.09 vs. 0.13 events per patient-year; P < 0.001). At the nominal alert threshold, 80.8% of HFEs were detected by a HeartLogic alert [95% confidence interval (CI): 69.9%-89.1%]. The median time from first true positive alert to an adjudicated clinical HFE was 53 days. The FPR was 1.16 (95% CI: 0.98-1.38) alerts per patient-year. CONCLUSIONS: Results suggest that signs of worsening HF can be detected successfully with remote patient follow-up. The use of HeartLogic may predict periods of increased risk for HF or clinically significant events, allowing for early intervention and reduction of hospitalization in a vulnerable patient population.

Inhibition of proline-rich tyrosine kinase 2 restores cardioprotection by remote ischaemic preconditioning in type 2 diabetes.

BACKGROUND AND PURPOSE: Remote ischaemic preconditioning (rIPC) for cardioprotection is severely impaired in diabetes, and therapeutic options to restore it are lacking. The vascular endothelium plays a key role in rIPC. Given that the activity of endothelial nitric oxide synthase (eNOS) is inhibited by proline-rich tyrosine kinase 2 (Pyk2), we hypothesized that pharmacological Pyk2 inhibition could restore eNOS activity and thus restore remote cardioprotection in diabetes. EXPERIMENTAL APPROACH: New Zealand obese (NZO) mice that demonstrated key features of diabetes were studied. The consequence of Pyk2 inhibition on endothelial function, rIPC and infarct size after myocardial infarction were evaluated. The impact of plasma from mice and humans with or without diabetes was assessed in isolated buffer perfused murine hearts and aortic rings. KEY RESULTS: Plasma from nondiabetic mice and humans, both subjected to rIPC, caused remote tissue protection. Similar to diabetic humans, NZO mice demonstrated endothelial dysfunction. NZO mice had reduced circulating nitrite levels, elevated arterial blood pressure and a larger infarct size after ischaemia and reperfusion than BL6 mice. Pyk2 increased the phosphorylation of eNOS at its inhibitory site (Tyr656), limiting its activity in diabetes. The cardioprotective effects of rIPC were abolished in diabetic NZO mice. Pharmacological Pyk2 inhibition restored endothelial function and rescued cardioprotective effects of rIPC. CONCLUSION AND IMPLICATIONS: Endothelial function and remote tissue protection are impaired in diabetes. Pyk2 is a novel target for treating endothelial dysfunction and restoring cardioprotection through rIPC in diabetes.

Environmental and geographical factors influencing the spread of SARS-CoV-2 over 2 years: a fine-scale spatiotemporal analysis.

Introduction: Since its emergence in late 2019, the SARS-CoV-2 virus has led to a global health crisis, affecting millions and reshaping societies and economies worldwide. Investigating the determinants of SARS-CoV-2 diffusion and their spatiotemporal dynamics at high spatial resolution is critical for public health and policymaking. Methods: This study analyses 194,682 georeferenced SARS-CoV-2 RT-PCR tests from March 2020 and April 2022 in the canton of Vaud, Switzerland. We characterized five distinct pandemic periods using metrics of spatial and temporal clustering like inverse Shannon entropy, the Hoover index, Lloyd's index of mean crowding, and the modified space-time DBSCAN algorithm. We assessed the demographic, socioeconomic, and environmental factors contributing to cluster persistence during each period using eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), to consider non-linear and spatial effects. Results: Our findings reveal important variations in the spatial and temporal clustering of cases. Notably, areas with flatter epidemics had higher total attack rate. Air pollution emerged as a factor showing a consistent positive association with higher cluster persistence, substantiated by both immission models and, to a lesser extent, tropospheric NO2 estimations. Factors including population density, testing rates, and geographical coordinates, also showed important positive associations with higher cluster persistence. The socioeconomic index showed no significant contribution to cluster persistence, suggesting its limited role in the observed dynamics, which warrants further research. Discussion: Overall, the determinants of cluster persistence remained across the study periods. These findings highlight the need for effective air quality management strategies to mitigate air pollution's adverse impacts on public health, particularly in the context of respiratory viral diseases like COVID-19.

Too much ado about data: Continuous remote monitoring of water temperatures, circulation and throughput can assist in the reduction of hospital-associated waterborne infections.

BACKGROUND: National and international guidance provides advice on maintenance and management of water systems in healthcare buildings, however, healthcare-associated waterborne infections (HAWI) are increasing. This narrative review identifies parameters critical to water quality in healthcare buildings and assesses if remote sensor monitoring can deliver safe water systems thus reducing HAWI. METHOD: A narrative review was performed using the following search terms 1) consistent water temperature AND waterborne pathogen control OR nosocomial infection 2) water throughput AND waterborne pathogen control OR nosocomial infection 3) remote monitoring of in-premise water systems AND continuous surveillance for temperature OR throughput OR flow OR use. Databases employed were PubMed, CDSR (Clinical Study Data Request) and DARE (Database of Abstracts of Reviews of Effects) from Jan 2013 - Mar 2024. FINDINGS: Single ensuite-patient rooms, expansion of wash-hand basins, widespread glove use, alcohol gel and wipes have increased water system stagnancy resulting in amplification of waterborne pathogens and transmission risk of Legionella, Pseudomonas and Non-Tuberculous Mycobacteria. Manual monitoring does not represent temperatures across large complex water systems. This review deems that multiple point continuous remote sensor monitoring is effective at identifying redundant and low use outlets, hydraulic imbalance and inconsistent temperature delivery across in-premise water systems. CONCLUSION: As remote monitoring becomes more common there will be greater recognition of failures in temperature control, hydraulics and balancing in water systems and there remains much to learn as we adopt this developing technology within our hospitals.

Applications of teleneuropsychology to the screening and monitoring of epilepsy.

Epilepsy is an inherently dynamic disease and neuropsychology plays a key role in the formulation, monitoring and management of the condition. Teleneuropsychology provides an opportunity for neuropsychology to increase its accessibility, reach and efficiency, using focussed assessments to target epilepsy relevant domains at critical timepoints in the disease trajectory. Neuropsychologists working with epilepsy have, however, been comparatively slow to adopt telehealth methods. Here we review recent developments in teleneuropsychology, with particular reference to applications and considerations in Late Onset Epilepsy. Three different approaches to remote assessment of cognition are discussed: unsupervised, computer-administered assessments; telephone-based assessments; and videoconference-based assessments. Uptake of unsupervised, computer-administered (browser or app-based) assessments has been strongest in aging research, where there is now evidence of feasibility, reliability, and validity, especially for measures of speed and working memory. Telephone-based assessments are well established in older aged cohorts and have recently been applied in epilepsy. Such assessments are widely accessible from a technology perspective, though reliance on a purely oral medium limits cognitive domain coverage. Videoconference based assessments have partially addressed this limitation, though continue to rely largely upon finding ways to administer legacy materials via the medium rather than intrinsically exploiting the technology. We argue that the future of neuropsychology requires development of integrated videoconference-based, computer-assisted cognitive testing, combining the benefits of computerised assessments with the advantages of human led assessments. Such an approach will be applicable across neuropsychological conditions, from childhood through to older adults.

Silk fibroin wetting stability film induced by polyamide-amine-epichlorohydrin (PAE) for intelligent sensing system.

Protein materials gain new functions and applicability through redesigns in protein structure and engineering confer. However, the application and development of proteins for use in flexible devices that fit in flexible devices that fit the surface of human skin is hindered by their poor wet stability. Here, we described the design of wet-stable materials based on the reconstruction of silk fibroin (SF). The combination of polyamide-amine-epichlorohydrin (PAE) was used as a traction rope to bring SF molecular chains closer to each other, to facilitate the self-assembly of SF through branching and lengthening of molecular chains, and change its crystalline structure. SF/PAE composite films that exhibited huge improvement in ductility and wet stability were combined with flexible SF substrates via patterning and ion sputtering to prepare flexible sensors. In addition, the SF/PAE sensing system equipped with a microprocessor and Bluetooth module enabled the real-time remote acquisition of human health signals such as vocal cords, joints, pulse and meridians. This reconfiguration of the SF structure will advance the systematic exploration of protein structures and the development of protein materials for intelligent device applications.

Intra-annual vegetation changes and spatial variation in China over the past two decades based on remote sensing and time-series clustering.

Vegetation is an important link between land, atmosphere, and water, making its changes of great significance. However, existing research has predominantly focused on long-term vegetation changes, neglecting the intra-annual variations of vegetation. Hence, this study is based on the Enhanced Vegetation Index (EVI) data from 2000 to 2022, with a time step of 16 days, to analyze the intra-annual patterns of vegetation changes in China. The average intra-annual EVI values for each municipal-level administrative region were calculated, and the time-series k-means clustering algorithm was employed to divide these regions, exploring the spatial variations in China's intra-annual vegetation changes. Finally, the ridge regression and random forest methods were utilized to assess the drivers of intra-annual vegetation changes. The results showed that: (1) China's vegetation status exhibits a notable intra-annual variation pattern of "high in summer and low in winter," and the changes are more pronounced in the northern regions than in the southern regions; (2) the intra-annual vegetation changes exhibit remarkable regional disparities, and China can be optimally clustered into four distinct clusters, which align well with China's temperature and precipitation zones; and (3) the intra-annual vegetation changes demonstrate significant correlations with meteorological factors such as dew point temperature, precipitation, maximum temperature, and sea-level pressure. In conclusion, our study reveals the characteristics, spatial patterns and driving forces of intra-annual vegetation changes in China, which contribute to explaining ecosystem response mechanisms, providing valuable insights for ecological research and the formulation of ecological conservation and management strategies.

Exploring fine-scale urban landscapes using satellite data to predict the distribution of Aedes mosquito breeding sites.

BACKGROUND: The spread of mosquito-transmitted diseases such as dengue is a major public health issue worldwide. The Aedes aegypti mosquito, a primary vector for dengue, thrives in urban environments and breeds mainly in artificial or natural water containers. While the relationship between urban landscapes and potential breeding sites remains poorly understood, such a knowledge could help mitigate the risks associated with these diseases. This study aimed to analyze the relationships between urban landscape characteristics and potential breeding site abundance and type in cities of French Guiana (South America), and to evaluate the potential of such variables to be used in predictive models. METHODS: We use Multifactorial Analysis to explore the relationship between urban landscape characteristics derived from very high resolution satellite imagery, and potential breeding sites recorded from in-situ surveys. We then applied Random Forest models with different sets of urban variables to predict the number of potential breeding sites where entomological data are not available. RESULTS: Landscape analyses applied to satellite images showed that urban types can be clearly identified using texture indices. The Multiple Factor Analysis helped identify variables related to the distribution of potential breeding sites, such as buildings class area, landscape shape index, building number, and the first component of texture indices. Models predicting the number of potential breeding sites using the entire dataset provided an R² of 0.90, possibly influenced by overfitting, but allowing the prediction over all the study sites. Predictions of potential breeding sites varied highly depending on their type, with better results on breeding sites types commonly found in urban landscapes, such as containers of less than 200 L, large volumes and barrels. The study also outlined the limitation offered by the entomological data, whose sampling was not specifically designed for this study. Model outputs could be used as input to a mosquito dynamics model when no accurate field data are available. CONCLUSION: This study offers a first use of routinely collected data on potential breeding sites in a research study. It highlights the potential benefits of including satellite-based characterizations of the urban environment to improve vector control strategies.

Evaluation of a Remote Patient Monitoring Program During the COVID-19 Pandemic: Retrospective Case Study With a Mixed Methods Explanatory Sequential Design.

BACKGROUND: Community health center (CHC) patients experience a disproportionately high prevalence of chronic conditions and barriers to accessing technologies that might support the management of these conditions. One such technology includes tools used for remote patient monitoring (RPM), the use of which surged during the COVID-19 pandemic. OBJECTIVE: The aim of this study was to assess how a CHC implemented an RPM program during the COVID-19 pandemic. METHODS: This retrospective case study used a mixed methods explanatory sequential design to evaluate a CHC's implementation of a suite of RPM tools during the COVID-19 pandemic. Analyses used electronic health record-extracted health outcomes data and semistructured interviews with the CHC's staff and patients participating in the RPM program. RESULTS: The CHC enrolled 147 patients in a hypertension RPM program. After 6 months of RPM use, mean systolic blood pressure (BP) was 13.4 mm Hg lower and mean diastolic BP 6.4 mm Hg lower, corresponding with an increase in hypertension control (BP<140/90 mm Hg) from 33.3% of patients to 81.5%. Considerable effort was dedicated to standing up the program, reinforced by organizational prioritization of chronic disease management, and by a clinician who championed program implementation. Noted barriers to implementation of the RPM program were limited initial training, lack of sustained support, and complexities related to the RPM device technology. CONCLUSIONS: While RPM technology holds promise for addressing chronic disease management, successful RPM program requires substantial investment in implementation support and technical assistance.