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1.
Arch Argent Pediatr ; 119(2): 76-82, 2021 04.
Article in English, Spanish | MEDLINE | ID: covidwho-1183983

ABSTRACT

INTRODUCTION: The objective of this study was to analyze available resources, guidelines in use, and preparedness to care for newborn infants at maternity centers in Argentina during the COVID-19 pandemic. METHOD: Cross-sectional study based on a survey administered to medical and nursing staff. In May 2020, Argentine facilities with more than 500 annual births were contacted; 58 % of these were from the public sector. RESULTS: In total, 104/147 facilities answered (71 %). All had guidelines for care during the pandemic, and 93 % indicated they had been trained on how to use them. A companion was not allowed during childbirth in 26 % of private facilities and in 60 % of public ones (p < 0.01). Deferred cord clamping was recommended in 87 %; rooming-in with asymptomatic newborns was promoted in 62 %; breastfeeding using protective measures was recommended in 70 %; and breast milk using a bottle, in 23 %. In 94 %, family visiting in the Neonatology Unit was restricted. Difficulties included the unavailability of individual rooms for symptomatic newborn infants and a potential shortage of health care staff and personal protective equipment. CONCLUSIONS: All facilities are aware of the national guidelines to fight the pandemic. Most have the resources to comply with the recommended protective measures. There is uncertainty as to whether personal protective equipment, staff, and physical space available at the different facilities would be enough if cases increased significantly.


Subject(s)
/prevention & control , Health Resources/supply & distribution , Infant Care/organization & administration , Infection Control/organization & administration , Maternal Health Services/organization & administration , Argentina/epidemiology , Cross-Sectional Studies , Female , Health Care Surveys , Health Policy , Humans , Infant Care/statistics & numerical data , Infant, Newborn , Infection Control/instrumentation , Infection Control/methods , Infection Control/statistics & numerical data , Male , Maternal Health Services/statistics & numerical data , Pandemics , Personal Protective Equipment/supply & distribution , Practice Guidelines as Topic , Pregnancy
2.
JMIR Mhealth Uhealth ; 9(3): e27232, 2021 03 26.
Article in English | MEDLINE | ID: covidwho-1183778

ABSTRACT

BACKGROUND: Contact tracing apps are potentially useful tools for supporting national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide. OBJECTIVE: Our goal was to develop and propose an item set that was suitable for describing and monitoring nationally issued COVID-19 contact tracing apps. This item set could provide a framework for describing the key technical features of such apps and monitoring their use based on widely available information. METHODS: We used an open-source intelligence approach (OSINT) to access a multitude of publicly available sources and collect data and information regarding the development and use of contact tracing apps in different countries over several months (from June 2020 to January 2021). The collected documents were then iteratively analyzed via content analysis methods. During this process, an initial set of subject areas were refined into categories for evaluation (ie, coherent topics), which were then examined for individual features. These features were paraphrased as items in the form of questions and applied to information materials from a sample of countries (ie, Brazil, China, Finland, France, Germany, Italy, Singapore, South Korea, Spain, and the United Kingdom [England and Wales]). This sample was purposefully selected; our intention was to include the apps of different countries from around the world and to propose a valid item set that can be relatively easily applied by using an OSINT approach. RESULTS: Our OSINT approach and subsequent analysis of the collected documents resulted in the definition of the following five main categories and associated subcategories: (1) background information (open-source code, public information, and collaborators); (2) purpose and workflow (secondary data use and warning process design); (3) technical information (protocol, tracing technology, exposure notification system, and interoperability); (4) privacy protection (the entity of trust and anonymity); and (5) availability and use (release date and the number of downloads). Based on this structure, a set of items that constituted the evaluation framework were specified. The application of these items to the 10 selected countries revealed differences, especially with regard to the centralization of the entity of trust and the overall transparency of the apps' technical makeup. CONCLUSIONS: We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can be easily applied to publicly issued information. The application of these criteria might help governments to identify design features that promote the successful, widespread adoption of COVID-19 tracing apps among target populations and across national boundaries.


Subject(s)
Contact Tracing , Mobile Applications , /epidemiology , Contact Tracing/methods , Global Health , Humans , Intelligence
3.
J Glaucoma ; 30(3): e50-e53, 2021 03 01.
Article in English | MEDLINE | ID: covidwho-1183056

ABSTRACT

PURPOSE: To report a case of bilateral acute angle-closure glaucoma associated with hyponatremia in the setting of chlorthalidone use and SARS-CoV-2 infection, and to demonstrate the challenges of managing this patient given her infectious status. METHODS: This was a case report. CASE: A 65-year-old woman taking chlorthalidone for hypertension presented to the emergency room with headache, pain, and blurry vision in both eyes and was found to be in bilateral acute angle closure. On laboratory investigation, she was severely hyponatremic and also tested positive for SARS-CoV-2. B-scan ultrasound demonstrated an apparent supraciliary effusion in the right eye. Following stabilization of her intraocular pressures with medical management, she ultimately underwent cataract extraction with iridectomies and goniosynechiolysis in both eyes. CONCLUSIONS: We report a rare case of bilateral acute angle-closure glaucoma associated with hyponatremia. Chlorthalidone use and perhaps SARS-CoV-2 infection may have contributed to this electrolyte abnormality and unique clinical presentation. In addition, we discuss the challenges of managing this complex patient with active SARS-CoV-2 infection during the pandemic.


Subject(s)
/epidemiology , Glaucoma, Angle-Closure/surgery , Intraocular Pressure/physiology , Iridectomy/methods , Acute Disease , Aged , Comorbidity , Female , Glaucoma, Angle-Closure/epidemiology , Glaucoma, Angle-Closure/physiopathology , Humans , Pandemics
4.
Circulation ; 143(13): 1274-1286, 2021 03 30.
Article in English | MEDLINE | ID: covidwho-1180993

ABSTRACT

BACKGROUND: Heart rate-corrected QT interval (QTc) prolongation, whether secondary to drugs, genetics including congenital long QT syndrome, and/or systemic diseases including SARS-CoV-2-mediated coronavirus disease 2019 (COVID-19), can predispose to ventricular arrhythmias and sudden cardiac death. Currently, QTc assessment and monitoring relies largely on 12-lead electrocardiography. As such, we sought to train and validate an artificial intelligence (AI)-enabled 12-lead ECG algorithm to determine the QTc, and then prospectively test this algorithm on tracings acquired from a mobile ECG (mECG) device in a population enriched for repolarization abnormalities. METHODS: Using >1.6 million 12-lead ECGs from 538 200 patients, a deep neural network (DNN) was derived (patients for training, n = 250 767; patients for testing, n = 107 920) and validated (n = 179 513 patients) to predict the QTc using cardiologist-overread QTc values as the "gold standard". The ability of this DNN to detect clinically-relevant QTc prolongation (eg, QTc ≥500 ms) was then tested prospectively on 686 patients with genetic heart disease (50% with long QT syndrome) with QTc values obtained from both a 12-lead ECG and a prototype mECG device equivalent to the commercially-available AliveCor KardiaMobile 6L. RESULTS: In the validation sample, strong agreement was observed between human over-read and DNN-predicted QTc values (-1.76±23.14 ms). Similarly, within the prospective, genetic heart disease-enriched dataset, the difference between DNN-predicted QTc values derived from mECG tracings and those annotated from 12-lead ECGs by a QT expert (-0.45±24.73 ms) and a commercial core ECG laboratory [10.52±25.64 ms] was nominal. When applied to mECG tracings, the DNN's ability to detect a QTc value ≥500 ms yielded an area under the curve, sensitivity, and specificity of 0.97, 80.0%, and 94.4%, respectively. CONCLUSIONS: Using smartphone-enabled electrodes, an AI DNN can predict accurately the QTc of a standard 12-lead ECG. QTc estimation from an AI-enabled mECG device may provide a cost-effective means of screening for both acquired and congenital long QT syndrome in a variety of clinical settings where standard 12-lead electrocardiography is not accessible or cost-effective.


Subject(s)
Artificial Intelligence , Electrocardiography/methods , Heart Diseases/diagnosis , Heart Rate/physiology , Adult , Aged , Area Under Curve , /virology , Electrocardiography/instrumentation , Female , Heart Diseases/physiopathology , Humans , Long QT Syndrome/diagnosis , Long QT Syndrome/physiopathology , Male , Middle Aged , Prospective Studies , ROC Curve , Sensitivity and Specificity , Smartphone
5.
Pediatr Emerg Care ; 37(4): 232-236, 2021 Apr 01.
Article in English | MEDLINE | ID: covidwho-1180679

ABSTRACT

OBJECTIVES: The purposes of this study were to describe the clinical characteristics of febrile infants younger than 90 days with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, to investigate the prevalence of serious bacterial infections (SBIs) in these infants, and to compare the risk of SBI in SARS-CoV-2-positive febrile infants with sex- and age-matched SARS-CoV- 2-negative febrile infants. METHODS: This was a retrospective cohort study conducted from March to November 2020 in a tertiary children's hospital. Patients were identified by International Classification of Diseases, 10th Revision codes and included if age was younger than 90 days, a SARS-CoV-2 test was performed, and at least 1 bacterial culture was collected. Positive cases of SARS-CoV-2 were age- and sex-matched to negative controls for analysis. Serious bacterial infection was defined as a urinary tract infection, bacterial enteritis, bacteremia, and/or bacterial meningitis. RESULTS: Fifty-three SARS-CoV-2-positive infants were identified with a higher rate of respiratory symptoms and lower white blood cell and C-reactive protein values than their SARS-CoV-2 matched controls. The rate of SBI in the SARS-CoV-2-positive infants was 8% compared with 34% in the controls; the most common infections were urinary tract infections (6% vs 23%). There were no cases of bacteremia or bacterial meningitis in the COVID-19 (coronavirus disease 2019) infants and 2 (4%) cases of bacteremia in the controls. The relative risk of any SBI between the 2 groups was 0.22 (95% confidence interval, 0.1-0.6; P ≤ 0.001). CONCLUSIONS: These results suggest that febrile infants younger than 90 days with COVID-19 have lower rates of SBI than their matched SARS-CoV-2-negative controls. These data are consistent with previous studies describing lower risks of SBI in febrile infants with concomitant viral respiratory tract infections.


Subject(s)
Bacterial Infections/etiology , Emergency Service, Hospital/statistics & numerical data , Risk Assessment/methods , Bacterial Infections/epidemiology , Female , Follow-Up Studies , Humans , Infant , Infant, Newborn , Male , Prevalence , Retrospective Studies , United States
6.
Biosci Rep ; 41(3)2021 03 26.
Article in English | MEDLINE | ID: covidwho-1180288

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has induced an ongoing global health crisis. Here we utilized a combination of targeted amino acids (AAs) and clinical biochemical profiling to analyze the plasma of coronavirus disease 2019 (COVID-19) subjects at the hospitalization stage and 1-month post-infection convalescent stage, respectively, to investigate the systematic injury during COVID-19 disease progress. We found the virus-induced inflammatory status and reduced liver synthesis capacity in hospitalized patients, which manifested with increased branched-chain AAs (BCAAs), aromatic AAs (AAAs), one-carbon related metabolites, and decreased methionine. Most of these disturbances during infection recover except for the increased levels of medium-chain acylcarnitines (ACs) in the convalescent subjects, implying the existence of incomplete fatty acids oxidation during recovery periods. Our results suggested that the imbalance of the AA profiling in COVID-19 patients. The majority of disturbed AAs recovered in 1 month. The incomplete fatty acid oxidation products suggested it might take longer time for convalescent patients to get complete recovery.


Subject(s)
Amino Acids/metabolism , /virology , /physiology , Adult , Aged , Aged, 80 and over , Amino Acids/blood , Biomarkers , /epidemiology , Comorbidity , Female , Hospitalization , Host-Pathogen Interactions , Humans , Male , Metabolomics/methods , Middle Aged , Severity of Illness Index
7.
Epidemiol Infect ; 149: e78, 2021 03 16.
Article in English | MEDLINE | ID: covidwho-1180197

ABSTRACT

The molecular epidemiology of the virus and mapping helps understand the epidemics' evolution and apply quick control measures. This study provides genomic evidence of multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) introductions into Sri Lanka and virus evolution during circulation. Whole-genome sequences of four SARS-CoV-2 strains obtained from coronavirus disease 2019 (COVID-19) positive patients reported in Sri Lanka during March 2020 were compared with sequences from Europe, Asia, Africa, Australia and North America. The phylogenetic analysis revealed that the sequence of the sample of the first local patient collected on 10 March, who contacted tourists from Italy, was clustered with SARS-CoV-2 strains collected from Italy, Germany, France and Mexico. Subsequently, the sequence of the isolate obtained on 19 March also clustered in the same group with the samples collected in March and April from Belgium, France, India and South Africa. The other two strains of SARS-CoV-2 were segregated from the main cluster, and the sample collected from 16 March clustered with England and the sample collected on 30 March showed the highest genetic divergence to the isolate of Wuhan, China. Here we report the first molecular epidemiological study conducted on circulating SARS-CoV-2 in Sri Lanka. The finding provides the robustness of molecular epidemiological tools and their application in tracing possible exposure in disease transmission during the pandemic.


Subject(s)
/genetics , /isolation & purification , Amino Acids/analysis , Disease Outbreaks/prevention & control , Genomics/methods , Humans , Sri Lanka
8.
Lancet Respir Med ; 9(4): 349-359, 2021 04.
Article in English | MEDLINE | ID: covidwho-1180127

ABSTRACT

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London.


Subject(s)
/diagnosis , Clinical Decision Rules , Clinical Decision-Making/methods , Clinical Deterioration , Aged , Aged, 80 and over , /therapy , Critical Care/statistics & numerical data , Female , Hospital Mortality , Humans , Intensive Care Units/statistics & numerical data , Logistic Models , Male , Middle Aged , Patient Admission/statistics & numerical data , Prognosis , Prospective Studies , Reproducibility of Results , Respiration, Artificial/statistics & numerical data , Severity of Illness Index , United Kingdom/epidemiology
9.
JMIR Mhealth Uhealth ; 8(7): e17216, 2020 07 09.
Article in English | MEDLINE | ID: covidwho-1177909

ABSTRACT

BACKGROUND: Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. OBJECTIVE: This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. METHODS: The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. RESULTS: The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (P=.02) and ROM of flexion (P=.004) and internal rotation (P=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (P=.03). CONCLUSIONS: This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. TRIAL REGISTRATION: Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t.


Subject(s)
Home Care Services , Internet , Stroke Rehabilitation/methods , Stroke/physiopathology , Telerehabilitation , Upper Extremity/physiopathology , Wearable Electronic Devices , Aged , Chronic Disease , Exercise Therapy/statistics & numerical data , Humans , Machine Learning , Middle Aged , Mobile Applications , Models, Theoretical , Prospective Studies , Survivors , Treatment Outcome
10.
Health Aff (Millwood) ; 39(10): 1792-1798, 2020 10.
Article in English | MEDLINE | ID: covidwho-1177766

ABSTRACT

Motor vehicle crashes remain the leading cause of adolescent mortality and injury in the United States. For young drivers, crash risk peaks immediately after licensure and declines during the next two years, making the point of licensure an important safety intervention opportunity. Legislation in Ohio established a unique health-transportation partnership among the State of Ohio, Children's Hospital of Philadelphia, and Diagnostic Driving, Inc., to identify underprepared driver license applicants through a virtual driving assessment system. The system, a computer-based virtual driving test, exposes drivers to common serious crash scenarios to identify critical skill deficits and is delivered in testing centers immediately before the on-road examination. A pilot study of license applicants who completed it showed that the virtual driving assessment system accurately predicted which drivers would fail the on-road examination and provided automated feedback that informed drivers on their skill deficits. At this time, the partnership's work is informing policy changes around integrating the virtual driving assessment system into licensing and driver training with the aim of reducing crashes in the first months of independent driving. The system can be developed to identify deficits in safety-critical skills that lead to crashes in new drivers and to address challenges that the coronavirus disease 2019 pandemic has introduced to driver testing and training.


Subject(s)
Automobile Driving/legislation & jurisprudence , Coronavirus Infections/prevention & control , Licensure/legislation & jurisprudence , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Safety Management/organization & administration , User-Computer Interface , Adolescent , Coronavirus Infections/epidemiology , Feasibility Studies , Female , Humans , Male , Motor Vehicles/statistics & numerical data , Ohio , Pandemics/statistics & numerical data , Philadelphia , Pilot Projects , Pneumonia, Viral/epidemiology , Transportation/methods , Young Adult
13.
J Zhejiang Univ Sci B ; 22(4): 253-284, 2021 Apr 15.
Article in English | MEDLINE | ID: covidwho-1175477

ABSTRACT

Since it was first recognized in bacteria and archaea as a mechanism for innate viral immunity in the early 2010s, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) has rapidly been developed into a robust, multifunctional genome editing tool with many uses. Following the discovery of the initial CRISPR/Cas-based system, the technology has been advanced to facilitate a multitude of different functions. These include development as a base editor, prime editor, epigenetic editor, and CRISPR interference (CRISPRi) and CRISPR activator (CRISPRa) gene regulators. It can also be used for chromatin and RNA targeting and imaging. Its applications have proved revolutionary across numerous biological fields, especially in biomedical and agricultural improvement. As a diagnostic tool, CRISPR has been developed to aid the detection and screening of both human and plant diseases, and has even been applied during the current coronavirus disease 2019 (COVID-19) pandemic. CRISPR/Cas is also being trialed as a new form of gene therapy for treating various human diseases, including cancers, and has aided drug development. In terms of agricultural breeding, precise targeting of biological pathways via CRISPR/Cas has been key to regulating molecular biosynthesis and allowing modification of proteins, starch, oil, and other functional components for crop improvement. Adding to this, CRISPR/Cas has been shown capable of significantly enhancing both plant tolerance to environmental stresses and overall crop yield via the targeting of various agronomically important gene regulators. Looking to the future, increasing the efficiency and precision of CRISPR/Cas delivery systems and limiting off-target activity are two major challenges for wider application of the technology. This review provides an in-depth overview of current CRISPR development, including the advantages and disadvantages of the technology, recent applications, and future considerations.


Subject(s)
CRISPR-Cas Systems , Gene Editing/methods , Genetic Therapy , Plant Breeding , Clustered Regularly Interspaced Short Palindromic Repeats , Crops, Agricultural/genetics , Humans , Nobel Prize
14.
J Acoust Soc Am ; 149(1): 652, 2021 01.
Article in English | MEDLINE | ID: covidwho-1175125

ABSTRACT

Confinement due to the COVID-19 pandemic drastically reduced human activities. Underwater soundscape variations are discussed in this study, comparing a typical and confinement day in a coastal lagoon near a popular tourist city in Mexico. Recording devices were located at 2 m in depth and 430 m away from the main promenade-a two-way avenue for light vehicle traffic-where main tourist infrastructure is located. The nearby marine environment is habitat to birds and dolphins as well as fish and invertebrates of commercial importance. Medium and small boats usually transit the area. The main underwater sound level reduction was measured at low frequencies (10-2000 Hz) because of the decrease in roadway noise. Vessel traffic also decreased by almost three quarters, although the level reduction due to this source was less noticeable. As typical day levels in the roadway noise band can potentially mask fish sounds and affect other low frequency noise-sensitive marine taxa, this study suggests that comprehensive noise analysis in coastal marine environments should consider the contribution from nearby land sources.


Subject(s)
/epidemiology , Environmental Monitoring/methods , Motor Vehicles , Noise/adverse effects , Quarantine/trends , Animals , Fishes/physiology , Humans , Mexico/epidemiology , Oceans and Seas/epidemiology , Sound Spectrography/methods , Sound Spectrography/trends
15.
Health Secur ; 19(1): 31-43, 2021.
Article in English | MEDLINE | ID: covidwho-1174869

ABSTRACT

In this paper, we investigate how message construction, style, content, and the textual content of embedded images impacted message retransmission over the course of the first 8 months of the coronavirus disease 2019 (COVID-19) pandemic in the United States. We analyzed a census of public communications (n = 372,466) from 704 public health agencies, state and local emergency management agencies, and elected officials posted on Twitter between January 1 and August 31, 2020, measuring message retransmission via the number of retweets (ie, a message passed on by others), an important indicator of engagement and reach. To assess content, we extended a lexicon developed from the early months of the pandemic to identify key concepts within messages, employing it to analyze both the textual content of messages themselves as well as text included within embedded images (n = 233,877), which was extracted via optical character recognition. Finally, we modelled the message retransmission process using a negative binomial regression, which allowed us to quantify the extent to which particular message features amplify or suppress retransmission, net of controls related to timing and properties of the sending account. In addition to identifying other predictors of retransmission, we show that the impact of images is strongly driven by content, with textual information in messages and embedded images operating in similar ways. We offer potential recommendations for crafting and deploying social media messages that can "cut through the noise" of an infodemic.


Subject(s)
Information Dissemination/methods , Public Health Informatics/methods , Social Media/statistics & numerical data , Communication , Humans , Social Marketing
16.
JMIR Public Health Surveill ; 6(3): e19831, 2020 07 30.
Article in English | MEDLINE | ID: covidwho-1172930

ABSTRACT

Before the coronavirus disease (COVID-19), 1 in 3 women and girls, globally, were victimized by an abusive partner in intimate relationships. However, the current pandemic has amplified cases of domestic violence (DV) against women and girls, with up to thrice the prevalence in DV cases compared to the same time last year. Evidence of the adverse effects of the pandemic on DV is still emerging, even as violence prevention strategies are iteratively being refined by service providers, advocacy agencies, and survivors to meet stay-at-home mandates. Emotional and material support for survivors is a critical resource increasingly delivered using digital and technology-based modalities, which offer several advantages and challenges. This paper rapidly describes current DV mitigation approaches using digital solutions, signaling emerging best practices to support survivors, their children, and abusers during stay-at-home advisories. Some examples of technology-based strategies and solutions are presented. An immediate priority is mapping out current digital solutions in response to COVID-19-related DV and outlining issues with uptake, coverage, and meaningful use of digital solutions.


Subject(s)
Coronavirus Infections/epidemiology , Domestic Violence/prevention & control , Intimate Partner Violence/prevention & control , Pandemics , Pneumonia, Viral/epidemiology , Telemedicine/methods , Coronavirus Infections/prevention & control , Domestic Violence/statistics & numerical data , Female , Global Health/statistics & numerical data , Humans , Intimate Partner Violence/statistics & numerical data , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Prevalence , Social Support , Survivors/psychology
17.
JMIR Public Health Surveill ; 6(3): e19354, 2020 07 17.
Article in English | MEDLINE | ID: covidwho-1172926

ABSTRACT

BACKGROUND: Coronavirus disease (COVID-19) is a novel viral illness that has rapidly spread worldwide. While the disease primarily presents as a respiratory illness, gastrointestinal symptoms such as diarrhea have been reported in up to one-third of confirmed cases, and patients may have mild symptoms that do not prompt them to seek medical attention. Internet-based infodemiology offers an approach to studying symptoms at a population level, even in individuals who do not seek medical care. OBJECTIVE: This study aimed to determine if a correlation exists between internet searches for gastrointestinal symptoms and the confirmed case count of COVID-19 in the United States. METHODS: The search terms chosen for analysis in this study included common gastrointestinal symptoms such as diarrhea, nausea, vomiting, and abdominal pain. Furthermore, the search terms fever and cough were used as positive controls, and constipation was used as a negative control. Daily query shares for the selected symptoms were obtained from Google Trends between October 1, 2019 and June 15, 2020 for all US states. These shares were divided into two time periods: pre-COVID-19 (prior to March 1) and post-COVID-19 (March 1-June 15). Confirmed COVID-19 case numbers were obtained from the Johns Hopkins University Center for Systems Science and Engineering data repository. Moving averages of the daily query shares (normalized to baseline pre-COVID-19) were then analyzed against the confirmed disease case count and daily new cases to establish a temporal relationship. RESULTS: The relative search query shares of many symptoms, including nausea, vomiting, abdominal pain, and constipation, remained near or below baseline throughout the time period studied; however, there were notable increases in searches for the positive control symptoms of fever and cough as well as for diarrhea. These increases in daily search queries for fever, cough, and diarrhea preceded the rapid rise in number of cases by approximately 10 to 14 days. The search volumes for these terms began declining after mid-March despite the continued rises in cumulative cases and daily new case counts. CONCLUSIONS: Google searches for symptoms may precede the actual rises in cases and hospitalizations during pandemics. During the current COVID-19 pandemic, this study demonstrates that internet search queries for fever, cough, and diarrhea increased prior to the increased confirmed case count by available testing during the early weeks of the pandemic in the United States. While the search volumes eventually decreased significantly as the number of cases continued to rise, internet query search data may still be a useful tool at a population level to identify areas of active disease transmission at the cusp of new outbreaks.


Subject(s)
Coronavirus Infections/diagnosis , Gastrointestinal Diseases/epidemiology , Pandemics , Pneumonia, Viral/diagnosis , Public Health Surveillance/methods , Search Engine/statistics & numerical data , Coronavirus Infections/epidemiology , Humans , Pneumonia, Viral/epidemiology , United States/epidemiology
18.
BMC Infect Dis ; 20(1): 820, 2020 Nov 10.
Article in English | MEDLINE | ID: covidwho-916970

ABSTRACT

BACKGROUND: Respiratory infections are a serious threat to human health. So, rapid detection of all respiratory pathogens can facilitate prompt treatment and prevent the deterioration of respiratory disease. Previously published primers and probes of the TaqMan array card (TAC) for respiratory pathogens are not sensitive to Chinese clinical specimens. This study aimed to develop and improve the TAC assay to detect 28 respiratory viral and bacterial pathogens in a Chinese population. METHODS: To improve the sensitivity, we redesigned the primers and probes, and labeled the probes with minor groove binders. The amplification efficiency, sensitivity, and specificity of the primers and probes were determined using target-gene containing standard plasmids. The detection performance of the TAC was evaluated on 754 clinical specimens and the results were compared with those from conventional methods. RESULTS: The performance of the TAC assay was evaluated using 754 clinical throat swab samples and the results were compared with those from gold-standard methods. The sensitivity and specificity were 95.4 and 96.6%, respectively. The lowest detection limit of the TAC was 10 to 100 copies/µL. CONCLUSIONS: TAC is an efficient, accurate, and high-throughput approach to detecting multiple respiratory pathogens simultaneously and is a promising tool for the identification of pathogen outbreaks.


Subject(s)
Bacteria/genetics , Real-Time Polymerase Chain Reaction/methods , Respiratory Tract Infections/diagnosis , Viruses/genetics , China/epidemiology , DNA Primers , Data Accuracy , Humans , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/virology , Sensitivity and Specificity
19.
PLoS Comput Biol ; 16(9): e1007836, 2020 09.
Article in English | MEDLINE | ID: covidwho-962642

ABSTRACT

Early warning signals (EWS) identify systems approaching a critical transition, where the system undergoes a sudden change in state. For example, monitoring changes in variance or autocorrelation offers a computationally inexpensive method which can be used in real-time to assess when an infectious disease transitions to elimination. EWS have a promising potential to not only be used to monitor infectious diseases, but also to inform control policies to aid disease elimination. Previously, potential EWS have been identified for prevalence data, however the prevalence of a disease is often not known directly. In this work we identify EWS for incidence data, the standard data type collected by the Centers for Disease Control and Prevention (CDC) or World Health Organization (WHO). We show, through several examples, that EWS calculated on simulated incidence time series data exhibit vastly different behaviours to those previously studied on prevalence data. In particular, the variance displays a decreasing trend on the approach to disease elimination, contrary to that expected from critical slowing down theory; this could lead to unreliable indicators of elimination when calculated on real-world data. We derive analytical predictions which can be generalised for many epidemiological systems, and we support our theory with simulated studies of disease incidence. Additionally, we explore EWS calculated on the rate of incidence over time, a property which can be extracted directly from incidence data. We find that although incidence might not exhibit typical critical slowing down properties before a critical transition, the rate of incidence does, presenting a promising new data type for the application of statistical indicators.


Subject(s)
Communicable Diseases/epidemiology , Computational Biology/methods , Models, Statistical , Public Health Surveillance/methods , Communicable Disease Control , Humans , Incidence , Prevalence
20.
MMWR Morb Mortal Wkly Rep ; 70(14): 523-527, 2021 Apr 09.
Article in English | MEDLINE | ID: covidwho-1173073

ABSTRACT

Approximately 375,000 deaths during 2020 were attributed to COVID-19 on death certificates reported to CDC (1). Concerns have been raised that some deaths are being improperly attributed to COVID-19 (2). Analysis of International Classification of Diseases, Tenth Revision (ICD-10) diagnoses on official death certificates might provide an expedient and efficient method to demonstrate whether reported COVID-19 deaths are being overestimated. CDC assessed documentation of diagnoses co-occurring with an ICD-10 code for COVID-19 (U07.1) on U.S. death certificates from 2020 that had been reported to CDC as of February 22, 2021. Among 378,048 death certificates listing U07.1, a total of 357,133 (94.5%) had at least one other ICD-10 code; 20,915 (5.5%) had only U07.1. Overall, 97.3% of 357,133 death certificates with at least one other diagnosis (91.9% of all 378,048 death certificates) were noted to have a co-occurring diagnosis that was a plausible chain-of-event condition (e.g., pneumonia or respiratory failure), a significant contributing condition (e.g., hypertension or diabetes), or both. Overall, 70%-80% of death certificates had both a chain-of-event condition and a significant contributing condition or a chain-of-event condition only; this was noted for adults aged 18-84 years, both males and females, persons of all races and ethnicities, those who died in inpatient and outpatient or emergency department settings, and those whose manner of death was listed as natural. These findings support the accuracy of COVID-19 mortality surveillance in the United States using official death certificates. High-quality documentation of co-occurring diagnoses on the death certificate is essential for a comprehensive and authoritative public record. Continued messaging and training (3) for professionals who complete death certificates remains important as the pandemic progresses. Accurate mortality surveillance is critical for understanding the impact of variants of SARS-CoV-2, the virus that causes COVID-19, and of COVID-19 vaccination and for guiding public health action.


Subject(s)
/mortality , Death Certificates , International Classification of Diseases , Public Health Surveillance/methods , Adolescent , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Reproducibility of Results , United States/epidemiology , Young Adult
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