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1.
BMC Public Health ; 22(1): 82, 2022 01 13.
Article in English | MEDLINE | ID: covidwho-1736380

ABSTRACT

BACKGROUND: Antigen tests for SARS-CoV-2 offer advantages over nucleic acid amplification tests (NAATs, such as RT-PCR), including lower cost and rapid return of results, but show reduced sensitivity. Public health organizations recommend different strategies for utilizing NAATs and antigen tests. We sought to create a framework for the quantitative comparison of these recommended strategies based on their expected performance. METHODS: We utilized a decision analysis approach to simulate the expected outcomes of six testing algorithms analogous to strategies recommended by public health organizations. Each algorithm was simulated 50,000 times in a population of 100,000 persons seeking testing. Primary outcomes were number of missed cases, number of false-positive diagnoses, and total test volumes. Outcome medians and 95% uncertainty ranges (URs) were reported. RESULTS: Algorithms that use NAATs to confirm all negative antigen results minimized missed cases but required high NAAT capacity: 92,200 (95% UR: 91,200-93,200) tests (in addition to 100,000 antigen tests) at 10% prevalence. Selective use of NAATs to confirm antigen results when discordant with symptom status (e.g., symptomatic persons with negative antigen results) resulted in the most efficient use of NAATs, with 25 NAATs (95% UR: 13-57) needed to detect one additional case compared to exclusive use of antigen tests. CONCLUSIONS: No single SARS-CoV-2 testing algorithm is likely to be optimal across settings with different levels of prevalence and for all programmatic priorities. This analysis provides a framework for selecting setting-specific strategies to achieve acceptable balances and trade-offs between programmatic priorities and resource constraints.


Subject(s)
COVID-19 , SARS-CoV-2 , Algorithms , COVID-19 Testing , Decision Support Techniques , Humans , Nucleic Acid Amplification Techniques , Sensitivity and Specificity
2.
Sci Rep ; 12(1): 1849, 2022 02 03.
Article in English | MEDLINE | ID: covidwho-1671632

ABSTRACT

India is a hotspot of the COVID-19 crisis. During the first wave, several lockdowns (L) and gradual unlock (UL) phases were implemented by the government of India (GOI) to curb the virus spread. These phases witnessed many challenges and various day-to-day developments such as virus spread and resource management. Twitter, a social media platform, was extensively used by citizens to react to these events and related topics that varied temporally and geographically. Analyzing these variations can be a potent tool for informed decision-making. This paper attempts to capture these spatiotemporal variations of citizen reactions by predicting and analyzing the sentiments of geotagged tweets during L and UL phases. Various sentiment analysis based studies on the related subject have been done; however, its integration with location intelligence for decision making remains a research gap. The sentiments were predicted through a proposed hybrid Deep Learning (DL) model which leverages the strengths of BiLSTM and CNN model classes. The model was trained on a freely available Sentiment140 dataset and was tested over manually annotated COVID-19 related tweets from India. The model classified the tweets with high accuracy of around 90%, and analysis of geotagged tweets during L and UL phases reveal significant geographical variations. The findings as a decision support system can aid in analyzing citizen reactions toward the resources and events during an ongoing pandemic. The system can have various applications such as resource planning, crowd management, policy formulation, vaccination, prompt response, etc.


Subject(s)
COVID-19/prevention & control , Communicable Disease Control/methods , Decision Support Techniques , Deep Learning , Social Media , Spatio-Temporal Analysis , COVID-19/epidemiology , Datasets as Topic , Decision Making , Female , Health Policy , Health Resources , Humans , India/epidemiology , Male , Pandemics , Vaccination
3.
Sci Rep ; 11(1): 23261, 2021 12 01.
Article in English | MEDLINE | ID: covidwho-1545638

ABSTRACT

The most promising way to prevent the explosive spread of COVID-19 infection is to achieve herd immunity through vaccination. It is therefore important to motivate those who are less willing to be vaccinated. To address this issue, we conducted an online survey of 6232 Japanese people to investigate age- and gender-dependent differences in attitudes towards COVID-19 vaccination and the underlying psychological processes. We asked participants to read one of nine different messages about COVID-19 vaccination and rate their willingness to be vaccinated. We also collected their 17 social personality trait scores and demographic information. We found that males 10-20 years old were least willing to be vaccinated. We also found that prosocial traits are the driving force for young people, but the motivation in older people also depends on risk aversion and self-interest. Furthermore, an analysis of 9 different messages demonstrated that for young people (particularly males), the message emphasizing the majority's intention to vaccinate and scientific evidence for the safety of the vaccination had the strongest positive effect on the willingness to be vaccinated, suggesting that the "majority + scientific evidence" message nudges young people to show their prosocial nature in action.


Subject(s)
COVID-19/psychology , Evidence-Based Medicine , Health Knowledge, Attitudes, Practice , Immunity, Herd , SARS-CoV-2/isolation & purification , Social Behavior , Vaccination/psychology , Adolescent , Adult , COVID-19/prevention & control , COVID-19/virology , COVID-19 Vaccines , Decision Support Techniques , Female , Humans , Male , Middle Aged , Motivation , Surveys and Questionnaires , Vaccination/adverse effects , Young Adult
4.
JAMA Netw Open ; 4(11): e2131455, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1520138

ABSTRACT

Importance: This randomized clinical trial examines the feasibility and acceptability of a decision-making tool for increasing patient interest in individualized recommendations for preventive care services. Objective: To pilot a tool to help patients compare life expectancy gains from evidence-based preventive services. Design, Setting, and Participants: This randomized clinical trial examined patient and physician responses to a pilot decision tool incorporating personalized risk factors at 3 US primary care clinics between 2017 and 2020. Eligible patients were between ages 45 to 70 years with 2 or more high-risk factors. Patients were followed-up after 1 year. Interventions: The gain in life expectancy associated with guideline adherence to each recommended preventive service was estimated. Personalized estimates incorporating risk factors in electronic health records were displayed in a physician-distributed visual aid. During development, physicians discussed individualized results with patients using shared decision-making (SDM). During the trial, patients were randomized to receive individualized recommendations or usual care (nonmasked, parallel, 1:1 ratio). Main Outcomes and Measures: Primary outcome was patient interest in individualized recommendations, assessed by survey. Secondary outcomes were use of SDM, decisional comfort, readiness to change, and preventive services received within 1 year. Results: The study enrolled 104 patients (31 development, 39 intervention, 34 control), of whom 101 were included in analysis (mean [SD] age, 56.5 [5.3] years; 73 [72.3%] women; 80 [79.2%] Black patients) and 20 physicians. Intervention patients found the tool helpful and wanted to use it again, rating it a median 9 of 10 (IQR, 8-10) and 10 of 10 (8-10), respectively. Compared with the control group, intervention patients more often correctly identified the service least likely (18 [46%] vs 0; P = .03) to improve their life expectancy. A greater number of patients also identified the service most likely to improve their life expectancy (26 [69%] vs 10 [30%]; P = .07), although this result was not statistically significant. Intervention patients reported greater mean [SD] improvement in SDM (4.7 [6.9] points) and near-term readiness to change (13.8 points for top-3-ranked recommendations). Point estimates indicated that patients in the intervention group experienced greater, although non-statistically significant, reductions in percentage of body weight (-2.96%; 95% CI, -8.18% to 2.28%), systolic blood pressure (-6.42 mm Hg; 95% CI, -16.12 to 3.27 mm Hg), hemoglobin A1c (-0.68%; 95% CI, -1.82% to 0.45%), 10-year atherosclerotic cardiovascular disease risk score (-1.20%; 95% CI, -3.65% to 1.26%), and low-density lipoprotein cholesterol (-8.46 mg/dL; 95% CI, -26.63 to 9.70 mg/dL) than the control group. Nineteen of 20 physicians wanted to continue using the decision tool in the future. Conclusions and Relevance: In this clinical trial, an individualized preventive care decision support tool improved patient understanding of primary prevention and demonstrated promise for improved shared decision-making and preventive care utilization. Trial Registration: ClinicalTrials.gov Identifier: NCT03023813.


Subject(s)
Decision Making , Decision Support Techniques , Physician-Patient Relations , Preventive Medicine/methods , Aged , Attitude of Health Personnel , Evidence-Based Medicine , Female , Guideline Adherence , Humans , Life Expectancy , Male , Middle Aged , Physicians/psychology , Pilot Projects
5.
Anticancer Res ; 41(11): 5821-5825, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1503030

ABSTRACT

AIM: Anastomotic leakage (AL) in left-sided colorectal cancer is a serious complication, with an incidence rate of 6-18%. We developed a novel predictive model for AL in colorectal surgery with double-stapling technique (DST) anastomosis using auto-artificial intelligence (AI). PATIENTS AND METHODS: A total of 256 patients who underwent curative surgery for left-sided colorectal cancer between 2017 and 2021 were included. In addition to conventional clinicopathological factors, we included the type of circular stapler using DST, conventional double-row circular stapler (DCS) or EEA™ circular stapler with Tri-Staple™ technology, 28 mm Medium/Thick (Covidien, New Haven, CT, USA) which had triple-row circular stapler (TCS) as a covariate. Auto-AI software Prediction One (Sony Network Communications Inc.) was used to predict AL with 5-fold cross validation. Predictive accuracy was assessed using the area under the receiver operating characteristic curve. Prediction One also evaluated the 'importance of variables' (IOV) using a method based on permutation feature importance. RESULTS: The area under the curve of the AI model was 0.766. The type of circular stapler used was the most influential factor contributing to AL (IOV=0.551). CONCLUSION: This auto-AI predictive model demonstrated an improvement in accuracy compared to the conventional model. It was suggested that use of a TCS may contribute to a reduction in the AL rate.


Subject(s)
Anastomotic Leak/etiology , Colectomy/adverse effects , Colorectal Neoplasms/surgery , Decision Support Techniques , Machine Learning , Surgical Stapling/adverse effects , Aged , Anastomotic Leak/diagnosis , Databases, Factual , Female , Humans , Male , Predictive Value of Tests , Retrospective Studies , Risk Assessment , Risk Factors , Surgical Staplers , Surgical Stapling/instrumentation , Time Factors , Treatment Outcome
7.
Ann Intern Med ; 174(11): 1563-1571, 2021 11.
Article in English | MEDLINE | ID: covidwho-1378494

ABSTRACT

BACKGROUND: Effective vaccines, improved testing technologies, and decreases in COVID-19 incidence prompt an examination of the choices available to residential college administrators seeking to safely resume in-person campus activities in fall 2021. OBJECTIVE: To help college administrators design and evaluate customized COVID-19 safety plans. DESIGN: Decision analysis using a compartmental epidemic model to optimize vaccination, testing, and other nonpharmaceutical interventions depending on decision makers' preferences, choices, and assumptions about epidemic severity and vaccine effectiveness against infection, transmission, and disease progression. SETTING: U.S. residential colleges. PARTICIPANTS: Hypothetical cohort of 5000 persons (students, faculty, and staff) living and working in close proximity on campus. MEASUREMENTS: Cumulative infections over a 120-day semester. RESULTS: Under base-case assumptions, if 90% coverage can be attained with a vaccine that is 85% protective against infection and 25% protective against asymptomatic transmission, the model finds that campus activities can be resumed while holding cumulative cases below 5% of the population without the need for routine, asymptomatic testing. With 50% population coverage using such a vaccine, a similar cap on cumulative cases would require either daily asymptomatic testing of unvaccinated persons or a combination of less frequent testing and resumption of aggressive distancing and other nonpharmaceutical prevention policies. Colleges returning to pre-COVID-19 campus activities without either broad vaccination coverage or high-frequency testing put their campus population at risk for widespread viral transmission. LIMITATION: Uncertainty in data, particularly vaccine effectiveness (preventive and transmission); no distinguishing between students and employees; and assumes limited community intermixing. CONCLUSION: Vaccination coverage is the most powerful tool available to residential college administrators seeking to achieve a safe return to prepandemic operations this fall. Given the breadth of potential outcomes in the face of uncontrollable and uncertain factors, even colleges with high vaccination rates should be prepared to reinstitute or expand testing and distancing policies on short notice. PRIMARY FUNDING SOURCE: National Institute on Drug Abuse.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Disease Transmission, Infectious/prevention & control , Universities/organization & administration , COVID-19/epidemiology , Decision Support Techniques , Humans , Incidence , Mass Screening , Pandemics , Risk Assessment , SARS-CoV-2 , United States/epidemiology
9.
J Drugs Dermatol ; 20(8): 868-873, 2021 Aug 01.
Article in English | MEDLINE | ID: covidwho-1359537

ABSTRACT

The Symposium on Hidradenitis Suppurativa Advances (SHSA) is a joint meeting of the United States Hidradenitis Suppurativa Foundation (HSF) and the Canadian Hidradenitis Suppurativa Foundation (CHSF). This annual cross-disciplinary meeting brings together experts from around the world in an opportunity to discuss the most recent advances in the study of hidradenitis suppurativa (HS). The fifth annual meeting was held virtually on 9-11 October 2020. A record 347 attendees, including 79 people with HS, from 20 different countries attended. Key take-home points included: Clinicians can optimize each visit by listening, provide education, and discuss treatments; a patient decision aid for HS (HS-PDA) is a freely available tool (www.informed-decisions.org); COVID-19 severity in HS patients was not different for patients treated with/without a biologic; comorbidity screening recommendations will be published soon; neutrophil extracellular traps (NETs) may play a role in HS; memory B cells, T helper 1 cytokines, and interleukin 1 signaling contributes to HS pathogenesis and are targets for new therapies; novel therapies are showing promise including a new JAK1 inhibitor (INCB054707) and brodalumab; and HS-specific outcome measures have emerged to better monitor disease severity, flare, and progression including a patient reported measure (HiSQOL) and an HS-specific investigator global assessment. J Drugs Dermatol. 2021;20(8):868-873. doi:10.36849/JDD.5836.


Subject(s)
Hidradenitis Suppurativa , COVID-19 , Canada , Comorbidity , Congresses as Topic , Cytokines , Decision Support Techniques , Disease Progression , Extracellular Traps , Hidradenitis Suppurativa/diagnosis , Hidradenitis Suppurativa/therapy , Humans , Patient Reported Outcome Measures , Severity of Illness Index
10.
Drug Des Devel Ther ; 15: 3349-3378, 2021.
Article in English | MEDLINE | ID: covidwho-1352763

ABSTRACT

Dalbavancin is a novel, long-acting lipoglycopeptide characterized by a long elimination half-life coupled with excellent in vitro activity against multidrug-resistant Gram-positives. Although it is currently approved only for the treatment of acute bacterial skin and skin structure infections, an ever-growing amount of evidence supports the efficacy of dalbavancin as a long-term therapy in osteomyelitis, prosthetic joint infections, endocarditis, and bloodstream infections. This article provides a critical reappraisal of real-world use of dalbavancin for off-label indications. A search strategy using specific keywords (dalbavancin, osteomyelitis, endocarditis, long-term suppressive therapy, bloodstream infection, pharmacokinetic/pharmacodynamic profile) until April 2021 was performed on the PubMed-MEDLINE database. As for other novel antibiotics, a conundrum between approved indications and potential innovative therapeutic uses has emerged for dalbavancin as well. The promising efficacy in challenging scenarios (i.e., osteomyelitis, endocarditis, prosthetic joint infections), coupled with the unique pharmacokinetic/pharmacodynamic properties, makes dalbavancin a valuable alternative to daily in-hospital intravenous or outpatient antimicrobial regimens in the treatment of long-term Gram-positive infections. This makes dalbavancin valuable in the current COVID-19 scenario, in which hospitalization and territorial medicine empowerment are unavoidable.


Subject(s)
Ambulatory Care , Anti-Bacterial Agents/therapeutic use , COVID-19 , Gram-Positive Bacterial Infections/drug therapy , Off-Label Use , Patient Participation , Teicoplanin/analogs & derivatives , Algorithms , Anti-Bacterial Agents/adverse effects , Anti-Bacterial Agents/pharmacokinetics , Clinical Decision-Making , Decision Support Techniques , Gram-Positive Bacterial Infections/diagnosis , Gram-Positive Bacterial Infections/microbiology , Humans , Teicoplanin/adverse effects , Teicoplanin/pharmacokinetics , Teicoplanin/therapeutic use , Treatment Outcome
11.
Am J Epidemiol ; 190(8): 1681-1688, 2021 08 01.
Article in English | MEDLINE | ID: covidwho-1337251

ABSTRACT

We evaluated whether randomly sampling and testing a set number of individuals for coronavirus disease 2019 (COVID-19) while adjusting for misclassification error captures the true prevalence. We also quantified the impact of misclassification error bias on publicly reported case data in Maryland. Using a stratified random sampling approach, 50,000 individuals were selected from a simulated Maryland population to estimate the prevalence of COVID-19. We examined the situation when the true prevalence is low (0.07%-2%), medium (2%-5%), and high (6%-10%). Bayesian models informed by published validity estimates were used to account for misclassification error when estimating COVID-19 prevalence. Adjustment for misclassification error captured the true prevalence 100% of the time, irrespective of the true prevalence level. When adjustment for misclassification error was not done, the results highly varied depending on the population's underlying true prevalence and the type of diagnostic test used. Generally, the prevalence estimates without adjustment for misclassification error worsened as the true prevalence level increased. Adjustment for misclassification error for publicly reported Maryland data led to a minimal but not significant increase in the estimated average daily cases. Random sampling and testing of COVID-19 are needed with adjustment for misclassification error to improve COVID-19 prevalence estimates.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/epidemiology , Decision Support Techniques , Statistics as Topic/methods , Bayes Theorem , COVID-19/classification , Humans , Maryland/epidemiology , Prevalence , SARS-CoV-2 , Selection Bias
12.
Aging (Albany NY) ; 13(14): 17961-17977, 2021 07 19.
Article in English | MEDLINE | ID: covidwho-1318481

ABSTRACT

We intend to evaluate the differences of the clinical characteristics, cytokine profiles and immunological features in patients with different severity of COVID-19, and to develop novel nomograms based on inflammatory cytokines or lymphocyte subsets for the differential diagnostics for severe or critical and non-severe COVID-19 patients. We retrospectively studied 254 COVID-19 patients, 90 of whom were severe or critical patients and 164 were non-severe patients. Severe or critical patients had significantly higher levels of inflammatory cytokines than non-severe patients as well as lower levels of lymphocyte subsets. Significantly positive correlations between cytokine profiles were observed, while they were all significantly negatively correlated with lymphocyte subsets. Two effective nomograms were developed according to two multivariable logistic regression cox models based on inflammatory cytokine profiles and lymphocyte subsets separately. The areas under the receiver operating characteristics of two nomograms were 0.834 (95% CI: 0.779-0.888) and 0.841 (95% CI: 0.756-0.925). The bootstrapped-concordance indexes of two nomograms were 0.834 and 0.841 in training set, and 0.860 and 0.852 in validation set. Calibration curves and decision curve analyses demonstrated that the nomograms were well calibrated and had significantly more clinical net benefits. Our novel nomograms can accurately predict disease severity of COVID-19, which may facilitate the identification of severe or critical patients and assist physicians in making optimized treatment suggestions.


Subject(s)
COVID-19/diagnosis , Cytokines/blood , Decision Support Techniques , Inflammation Mediators/blood , Lymphocyte Subsets/immunology , Nomograms , Aged , Biomarkers/blood , COVID-19/blood , COVID-19/immunology , COVID-19/therapy , Clinical Decision-Making , Female , Humans , Lymphocyte Count , Male , Middle Aged , Predictive Value of Tests , Reproducibility of Results , Retrospective Studies , Risk Assessment , Risk Factors , Severity of Illness Index , Up-Regulation
13.
Sci Rep ; 11(1): 14108, 2021 07 08.
Article in English | MEDLINE | ID: covidwho-1303785

ABSTRACT

While the effectiveness of lockdowns to reduce Coronavirus Disease-2019 (COVID-19) transmission is well established, uncertainties remain on the lifting principles of these restrictive interventions. World Health Organization recommends case positive rate of 5% or lower as a threshold for safe reopening. However, inadequate testing capacity limits the applicability of this recommendation, especially in the low-income and middle-income countries (LMICs). To develop a practical reopening strategy for LMICs, in this study, we first identify the optimal timing of safe reopening by exploring accessible epidemiological data of 24 countries during the initial COVID-19 surge. We find that a safe opening can occur two weeks after the crossover of daily infection and recovery rates while maintaining a negative trend in daily new cases. Epidemiologic SIRM model-based example simulation supports our findings. Finally, we develop an easily interpretable large-scale reopening (LSR) index, which is an evidence-based toolkit-to guide/inform reopening decision for LMICs.


Subject(s)
COVID-19/prevention & control , Communicable Disease Control/methods , Decision Support Techniques , Developing Countries , Quarantine/methods , COVID-19/epidemiology , COVID-19/transmission , Computer Simulation , Humans , Income
14.
Medicine (Baltimore) ; 100(16): e25506, 2021 Apr 23.
Article in English | MEDLINE | ID: covidwho-1294821

ABSTRACT

BACKGROUND: In recent years, more and more reports are focused on the application of traditional Chinese medicine injection (TCMJ) for the treatment of viral pneumonia. There are about 200 million cases of viral pneumonia worldwide every year, half of which are children. At present, many kinds of TCMJ are created for the treatment of viral pneumonia in children, with good therapeutic effects. However, there are many kinds of TCMJ, and the treatment advantages are different, thus bringing difficulties to the selection of clinical drugs. In order to provide evidence-based evidence support for the clinical selection of TCMJ for the treatment of viral pneumonia in children, this study selected the commonly used TCMJ for clinical treatment of viral pneumonia for meta-analysis to evaluate its efficacy. METHODS: The Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wanfang Data, Viper information databases, Cochran library Web of Science, PubMed, MEDLINE and EMBASE will be searched. The literature will be searched, with language restriction in English and Chinese. The related reference will be retrieved as well. Two reviewers will independently extract data and perform quality assessment of included studies. Review Manager 5.3 will be applied to conduct this meta-analysis. RESULTS: The results of this systematic review and meta-analysis will be published in a peer-reviewed journal once we finish this study. CONCLUSIONS: This study provides reliable evidence-based evidence for the efficacy of TCMJ in the treatment of viral pneumonia in children. ETHICS AND DISSEMINATION: We will not be allowed to publish private information from individuals. This kind of systematic review should not harm the rights of participants. No ethical approval was required. The results can be published in peer-reviewed journals or at relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/795MB.


Subject(s)
Drugs, Chinese Herbal/administration & dosage , Evidence-Based Medicine/methods , Pneumonia, Viral/drug therapy , Child , Clinical Decision-Making , Decision Support Techniques , Humans , Injections , Lung/diagnostic imaging , Meta-Analysis as Topic , Pneumonia, Viral/diagnosis , Pneumonia, Viral/virology , Systematic Reviews as Topic , Treatment Outcome
15.
Value Health ; 24(8): 1150-1157, 2021 08.
Article in English | MEDLINE | ID: covidwho-1274352

ABSTRACT

OBJECTIVES: Immunization programs in low-income and middle-income countries (LMICs) are faced with an ever-growing number of vaccines of public health importance recommended by the World Health Organization, while also financing a greater proportion of the program through domestic resources. More than ever, national immunization programs must be equipped to contextualize global guidance and make choices that are best suited to their setting. The CAPACITI decision-support tool has been developed in collaboration with national immunization program decision makers in LMICs to structure and document an evidence-based, context-specific process for prioritizing or selecting among multiple vaccination products, services, or strategies. METHODS: The CAPACITI decision-support tool is based on multi-criteria decision analysis, as a structured way to incorporate multiple sources of evidence and stakeholder perspectives. The tool has been developed iteratively in consultation with 12 countries across Africa, Asia, and the Americas. RESULTS: The tool is flexible to existing country processes and can follow any type of multi-criteria decision analysis or a hybrid approach. It is structured into 5 sections: decision question, criteria for decision making, evidence assessment, appraisal, and recommendation. The Excel-based tool guides the user through the steps and document discussions in a transparent manner, with an emphasis on stakeholder engagement and country ownership. CONCLUSIONS: Pilot countries valued the CAPACITI decision-support tool as a means to consider multiple criteria and stakeholder perspectives and to evaluate trade-offs and the impact of data quality. With use, it is expected that LMICs will tailor steps to their context and streamline the tool for decision making.


Subject(s)
Decision Support Techniques , Health Policy , Health Priorities , Immunization Programs/economics , Technology Assessment, Biomedical , Vaccines/economics , Africa , Asia , Developing Countries , Humans , Public Health , Stakeholder Participation , State Medicine/economics , Vaccination/economics , World Health Organization
16.
BMC Med Inform Decis Mak ; 21(1): 151, 2021 05 06.
Article in English | MEDLINE | ID: covidwho-1224881

ABSTRACT

BACKGROUND: Despite the proven value of multicriteria decision analysis in the health field, there is a lack of studies focused on prioritising victims in the Emergency Medical Service, EMS. With this, and knowing that the decision maker needs a direction on which choice may be the most appropriate, based on different and often conflicting criteria. The current work developed a new model for prioritizing victims of SAMU/192, based on the multicriteria decision methodology, taking into account the scarcity of resources. METHODS: An expert panel and a discussion group were formed, which defined the limits of the problem, and identified the evaluation criteria for choosing a victim, amongst four alternatives illustrated from hypothetical scenarios of emergency situations-clinical and traumatic diseases of absolute priority. For prioritization, an additive mathematical method was used that aggregates criteria in a flexible and interactive version, FITradeoff. RESULTS: The structuring of the problem led the researchers to identify twenty-five evaluation criteria, amongst which ten were essential to guide decisions. As a result, in the simulation of prioritization of four requesting victims in view of the availability of only one ambulance, the proposed model supported the decision by suggesting the prioritization of one of the victims. CONCLUSIONS: This work contributed to the prioritization of victims using multicriteria decision support methodology. Selecting and weighing the criteria in this study indicated that the protocols that guide regulatory physicians do not consider all the criteria for prioritizing victims in an environment of scarcity of resources. Finally, the proposed model can support crucial decision based on a rational and transparent decision-making process that can be applied in other EMS.


Subject(s)
Decision Support Techniques , Emergency Medical Services , Brazil , Humans
17.
West J Emerg Med ; 22(3): 592-598, 2021 Mar 24.
Article in English | MEDLINE | ID: covidwho-1266877

ABSTRACT

INTRODUCTION: The clinical presentation of coronavirus disease 2019 (COVID-19) overlaps with many other common cold and influenza viruses. Identifying patients with a higher probability of infection becomes crucial in settings with limited access to testing. We developed a prediction instrument to assess the likelihood of a positive polymerase chain reaction (PCR) test, based solely on clinical variables that can be determined within the time frame of an emergency department (ED) patient encounter. METHODS: We derived and prospectively validated a model to predict SARS-CoV-2 PCR positivity in patients visiting the ED with symptoms consistent with the disease. RESULTS: Our model was based on 617 ED visits. In the derivation cohort, the median age was 36 years, 43% were men, and 9% had a positive result. The median time to testing from the onset of initial symptoms was four days (interquartile range [IQR]: 2-5 days, range 0-23 days), and 91% of all patients were discharged home. The final model based on a multivariable logistic regression included a history of close contact (adjusted odds ratio [AOR] 2.47, 95% confidence interval [CI], 1.29-4.7); fever (AOR 3.63, 95% CI, 1.931-6.85); anosmia or dysgeusia (AOR 9.7, 95% CI, 2.72-34.5); headache (AOR 1.95, 95% CI, 1.06-3.58), myalgia (AOR 2.6, 95% CI, 1.39-4.89); and dry cough (AOR 1.93, 95% CI, 1.02-3.64). The area under the curve (AUC) from the derivation cohort was 0.79 (95% CI, 0.73-0.85) and AUC 0.7 (95% CI, 0.61-0.75) in the validation cohort (N = 379). CONCLUSION: We developed and validated a clinical tool to predict SARS-CoV-2 PCR positivity in patients presenting to the ED to assist with patient disposition in environments where COVID-19 tests or timely results are not readily available.


Subject(s)
COVID-19/diagnosis , Decision Support Techniques , Adult , COVID-19/physiopathology , Emergency Service, Hospital/statistics & numerical data , Female , Humans , Male , Odds Ratio , Polymerase Chain Reaction , Prospective Studies , ROC Curve , SARS-CoV-2 , Time Factors
18.
Allergy Asthma Proc ; 42(4): 301-309, 2021 07 24.
Article in English | MEDLINE | ID: covidwho-1242273

ABSTRACT

Background: Most U.S. patient and health care provider surveys with regard to nasal allergy treatments were conducted before sublingual immunotherapy (SLIT)-tablets and allergy immunotherapy (AIT) shared decision-making tools were available. Objective: Patient and health care provider surveys with regard to current perceptions of nasal allergy burden, symptoms, and treatments were conducted to compare with previous surveys and provide insight into the use of SLIT-tablets and AIT shared decision-making tools. Methods: From November-December 2019, adults (N = 510) diagnosed with nasal allergies and health care providers (N = 304) who treated nasal allergies in the United States completed surveys with regard to nasal allergy management. Results: Of the patient respondents, 42% reported that their symptoms were only somewhat controlled and 48% had avoided activities because of their nasal allergies. In all, 38% were using only over-the-counter (OTC) medications for treatment, and 42%, 7%, and 8% had ever received subcutaneous immunotherapy (SCIT), sublingual allergy drops, or SLIT-tablets, respectively; 56% and 85% reported that they had never discussed SCIT or SLIT, respectively, with their health care provider. Of the health care provider respondents, 45%, 58%, and 20% were very likely to discuss OTC medications, SCIT, or SLIT, respectively. Allergists were more inclined to discuss SCIT with their patients than other health care providers (82% versus 33%, respectively). Most allergists (67%) and other health care providers (62%) reported that they did not use an AIT shared decision-making tool, primarily because of unawareness. Conclusion: The patients with nasal allergies continued to report inadequate symptom control and activity impairment. SLIT-tablets and AIT shared decision-making tools were underused. In the coronavirus disease 2019 era, social distancing may limit office visits, which impacts SCIT administration and prompts increased use of telemedicine and a possible advantage for at-home-administered SLIT-tablets over SCIT.


Subject(s)
Allergy and Immunology/trends , COVID-19 , Decision Making, Shared , Decision Support Techniques , Desensitization, Immunologic/trends , Nonprescription Drugs/therapeutic use , Practice Patterns, Physicians'/trends , Rhinitis, Allergic/therapy , Telemedicine/trends , Adolescent , Adult , Aged , Health Care Surveys , Humans , Middle Aged , Physical Distancing , Prognosis , Rhinitis, Allergic/diagnosis , Sublingual Immunotherapy/trends , Time Factors , United States , Young Adult
19.
Int J Environ Res Public Health ; 18(10)2021 May 14.
Article in English | MEDLINE | ID: covidwho-1234699

ABSTRACT

The actual coronavirus disease 2019 (COVID-19) pandemic has led to the limit of emergency systems worldwide, leading to the collapse of health systems, police, first responders, as well as other areas. Various ways of dealing with this world crisis have been proposed from many aspects, with fuzzy multi-criteria decision analysis being a method that can be applied to a wide range of emergency systems and professional groups, aiming to confront several associated issues and challenges. The purpose of this critical review was to discuss the basic principles, present current applications during the first pandemic wave, and propose future implications of this methodology. For this purpose, both primary sources, such as scientific articles, and secondary ones, such as bibliographic indexes, web pages, and databases, were used. The main search engines were PubMed, SciELO, and Google Scholar. The method was a systematic literature review of the available literature regarding the performance of the fuzzy multi-criteria decision analysis of emergency systems in the COVID-19 pandemic. The results of this study highlight the importance of the fuzzy multi-criteria decision analysis method as a beneficial tool for healthcare workers and first responders' emergency professionals to face this pandemic as well as to manage the created uncertainty and its related risks.


Subject(s)
COVID-19 , Pandemics , Decision Support Techniques , Health Personnel , Humans , SARS-CoV-2
20.
JAMA Netw Open ; 4(5): e2110071, 2021 05 03.
Article in English | MEDLINE | ID: covidwho-1227701

ABSTRACT

Importance: Nursing homes and other long-term care facilities have been disproportionately impacted by the COVID-19 pandemic. Strategies are urgently needed to reduce transmission in these high-risk populations. Objective: To evaluate COVID-19 transmission in nursing homes associated with contact-targeted interventions and testing. Design, Setting, and Participants: This decision analytical modeling study developed an agent-based susceptible-exposed-infectious (asymptomatic/symptomatic)-recovered model between July and September 2020 to examine SARS-CoV-2 transmission in nursing homes. Residents and staff of a simulated nursing home with 100 residents and 100 staff split among 3 shifts were modeled individually; residents were split into 2 cohorts based on COVID-19 diagnosis. Data were analyzed from September to October 2020. Exposures: In the resident cohorting intervention, residents who had recovered from COVID-19 were moved back from the COVID-19 (ie, infected with SARS-CoV-2) cohort to the non-COVID-19 (ie, susceptible and uninfected with SARS-CoV-2) cohort. In the immunity-based staffing intervention, staff who had recovered from COVID-19 were assumed to have protective immunity and were assigned to work in the non-COVID-19 cohort, while susceptible staff worked in the COVID-19 cohort and were assumed to have high levels of protection from personal protective equipment. These interventions aimed to reduce the fraction of people's contacts that were presumed susceptible (and therefore potentially infected) and replaced them with recovered (immune) contacts. A secondary aim of was to evaluate cumulative incidence of SARS-CoV-2 infections associated with 2 types of screening tests (ie, rapid antigen testing and polymerase chain reaction [PCR] testing) conducted with varying frequency. Main Outcomes and Measures: Estimated cumulative incidence proportion of SARS-CoV-2 infection after 3 months. Results: Among the simulated cohort of 100 residents and 100 staff members, frequency and type of testing were associated with smaller outbreaks than the cohorting and staffing interventions. The testing strategy associated with the greatest estimated reduction in infections was daily antigen testing, which reduced the mean cumulative incidence proportion by 49% in absence of contact-targeted interventions. Under all screening testing strategies, the resident cohorting intervention and the immunity-based staffing intervention were associated with reducing the final estimated size of the outbreak among residents, with the immunity-based staffing intervention reducing it more (eg, by 19% in the absence of testing) than the resident cohorting intervention (eg, by 8% in the absence of testing). The estimated reduction in transmission associated with these interventions among staff varied by testing strategy and community prevalence. Conclusions and Relevance: These findings suggest that increasing the frequency of screening testing of all residents and staff, or even staff alone, in nursing homes may reduce outbreaks in this high-risk setting. Immunity-based staffing may further reduce spread at little or no additional cost and becomes particularly important when daily testing is not feasible.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Homes for the Aged , Nursing Homes , Personnel Staffing and Scheduling/organization & administration , Adaptive Immunity , Aged , COVID-19/diagnosis , COVID-19/virology , COVID-19 Nucleic Acid Testing , COVID-19 Serological Testing , Decision Support Techniques , Humans , Personal Protective Equipment , Viral Load , Vulnerable Populations
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