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1.
J Med Internet Res ; 22(9): e22469, 2020 09 17.
Article in English | MEDLINE | ID: covidwho-781824

ABSTRACT

BACKGROUND: Implementing and lifting social distancing (LSD) is an urgent global issue during the COVID-19 pandemic, particularly when the travel ban is lifted to revive international businesses and economies. However, when and whether LSD can be considered is subject to the spread of SARS-CoV-2, the recovery rate, and the case-fatality rate. It is imperative to provide real-time assessment of three factors to guide LSD. OBJECTIVE: A simple LSD index was developed for health decision makers to do real-time assessment of COVID-19 at the global, country, region, and community level. METHODS: Data on the retrospective cohort of 186 countries with three factors were retrieved from a publicly available repository from January to early July. A simple index for guiding LSD was measured by the cumulative number of COVID-19 cases and recoveries, and the case-fatality rate was envisaged. If the LSD index was less than 1, LSD can be considered. The dynamic changes of the COVID-19 pandemic were evaluated to assess whether and when health decision makers allowed for LSD and when to reimplement social distancing after resurgences of the epidemic. RESULTS: After large-scale outbreaks in a few countries before mid-March (prepandemic phase), the global weekly LSD index peaked at 4.27 in March and lasted until mid-June (pandemic phase), during which most countries were affected and needed to take various social distancing measures. Since, the value of LSD has gradually declined to 0.99 on July 5 (postpandemic phase), at which 64.7% (120/186) of countries and regions had an LSD<1 with the decile between 0 and 1 to refine risk stratification by countries. The LSD index decreased to 1 in about 115 days. In addition, we present the results of dynamic changes of the LSD index for the world and for each country and region with different time windows from January to July 5. The results of the LSD index on the resurgence of the COVID-19 epidemic in certain regions and validation by other emerging infectious diseases are presented. CONCLUSIONS: This simple LSD index provides a quantitative assessment of whether and when to ease or implement social distancing to provide advice for health decision makers and travelers.


Subject(s)
Algorithms , Coronavirus Infections/prevention & control , Health Policy , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Policy Making , Social Isolation , Betacoronavirus , Coronavirus Infections/mortality , Coronavirus Infections/transmission , Humans , Pneumonia, Viral/mortality , Pneumonia, Viral/transmission , Retrospective Studies , Travel
2.
Rev Soc Bras Med Trop ; 53: e20200528, 2020.
Article in English | MEDLINE | ID: covidwho-771733

ABSTRACT

INTRODUCTION: The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths. METHODS: The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics. RESULTS: Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases. CONCLUSIONS: The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical & epidemiological characteristics.


Subject(s)
Coronavirus Infections/epidemiology , Disease Outbreaks , Pneumonia, Viral/epidemiology , Public Health Surveillance/methods , Algorithms , Brazil/epidemiology , Humans , Pandemics
3.
PLoS Comput Biol ; 16(5): e1007879, 2020 05.
Article in English | MEDLINE | ID: covidwho-638069

ABSTRACT

In this work, we aim to determine the main factors driving self-initiated behavioral changes during the seasonal flu. To this end, we designed and deployed a questionnaire via Influweb, a Web platform for participatory surveillance in Italy, during the 2017 - 18 and 2018 - 19 seasons. We collected 599 surveys completed by 434 users. The data provide socio-demographic information, level of concerns about the flu, past experience with illnesses, and the type of behavioral changes voluntarily implemented by each participant. We describe each response with a set of features and divide them in three target categories. These describe those that report i) no (26%), ii) only moderately (36%), iii) significant (38%) changes in behaviors. In these settings, we adopt machine learning algorithms to investigate the extent to which target variables can be predicted by looking only at the set of features. Notably, 66% of the samples in the category describing more significant changes in behaviors are correctly classified through Gradient Boosted Trees. Furthermore, we investigate the importance of each feature in the classification task and uncover complex relationships between individuals' characteristics and their attitude towards behavioral change. We find that intensity, recency of past illnesses, perceived susceptibility to and perceived severity of an infection are the most significant features in the classification task and are associated to significant changes in behaviors. Overall, the research contributes to the small set of empirical studies devoted to the data-driven characterization of behavioral changes induced by infectious diseases.


Subject(s)
Influenza, Human/psychology , Seasons , Algorithms , Disease Susceptibility , Female , Humans , Italy , Male , Surveys and Questionnaires
4.
J Phys Chem B ; 124(33): 7093-7101, 2020 08 20.
Article in English | MEDLINE | ID: covidwho-646748

ABSTRACT

For estimating the infection risk from virus-containing airborne droplets, it is crucial to consider the interplay of all relevant physical-chemical effects that affect droplet evaporation and sedimentation times. For droplet radii in the range 70 nm < R < 60 µm, evaporation can be described in the stagnant-flow approximation and is diffusion-limited. Analytical equations are presented for the droplet evaporation rate, the time-dependent droplet size, and the sedimentation time, including evaporation cooling and solute osmotic-pressure effects. Evaporation makes the time for initially large droplets to sediment much longer and thus significantly increases the viral air load. Using recent estimates for SARS-CoV-2 concentrations in sputum and droplet production rates while speaking, a single infected person that constantly speaks without a mouth cover produces a total steady-state air load of more than 104 virions at a given time. In a midsize closed room, this leads to a viral inhalation frequency of at least 2.5 per minute. Low relative humidity, as encountered in airliners and inside buildings in the winter, accelerates evaporation and thus keeps initially larger droplets suspended in air. Typical air-exchange rates decrease the viral air load from droplets with an initial radius larger than 20 µm only moderately.


Subject(s)
Betacoronavirus , Coronavirus Infections/transmission , Pneumonia, Viral/transmission , Speech , Aerosols , Air Microbiology , Algorithms , Diffusion , Humans , Pandemics , Particle Size , Risk Assessment , Water
5.
Korean J Intern Med ; 35(5): 1027-1030, 2020 09.
Article in English | MEDLINE | ID: covidwho-646555

ABSTRACT

Following the coronavirus disease 2019 outbreak in China, more than 10,765 patients tested positive for severe acute respiratory syndrome coronavirus 2 from February 18, 2020 to April 30, 2020 in South Korea. Performing emergency endoscopy is extremely challenging from the clinicians' viewpoint during the viral outbreak. There are no available guidelines for emergency endoscopy in tertiary hospitals during this pandemic. We set up an algorithm as a guide for emergency endoscopy in patients presenting to the emergency room with bleeding, foreign body, or impending cholangitis. From February 18, 2020 to April 30, 2020 of outbreak, 130 patients underwent emergency endoscopy in our center. Owing to the simple and streamlined algorithm for performing emergency endoscopy, no endoscopy-related infection to other patients or medical workers was reported in our center.


Subject(s)
Algorithms , Betacoronavirus , Coronavirus Infections/epidemiology , Emergency Service, Hospital , Endoscopy , Patient Selection , Pneumonia, Viral/epidemiology , Cholangitis/diagnosis , Cholangitis/etiology , Cholangitis/therapy , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Foreign Bodies/diagnosis , Foreign Bodies/etiology , Foreign Bodies/therapy , Gastrointestinal Hemorrhage/diagnosis , Gastrointestinal Hemorrhage/etiology , Gastrointestinal Hemorrhage/therapy , Humans , Infection Control/organization & administration , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Republic of Korea , Retrospective Studies , Tertiary Care Centers
6.
BMC Bioinformatics ; 21(1): 313, 2020 Jul 16.
Article in English | MEDLINE | ID: covidwho-654551

ABSTRACT

BACKGROUND: Drug repurposing aims to detect the new therapeutic benefits of the existing drugs and reduce the spent time and cost of the drug development projects. The synthetic repurposing of drugs may prove to be more useful than the single repurposing in terms of reducing toxicity and enhancing efficacy. However, the researchers have not given it serious consideration. To address the issue, a novel datamining method is introduced and applied to repositioning of drugs for hypertension (HT) which is a serious medical condition and needs some improved treatment plans to help treat it. RESULTS: A novel two-step data mining method, which is based on the If-Then association rules as well as a novel discrete optimization algorithm, was introduced and applied to the synthetic repurposing of drugs for HT. The required data were also extracted from DrugBank, KEGG, and DrugR+ databases. The findings indicated that based on the different statistical criteria, the proposed method outperformed the other state-of-the-art approaches. In contrast to the previously proposed methods which had failed to discover a list on some datasets, our method could find a combination list for all of them. CONCLUSION: Since the proposed synthetic method uses medications in small dosages, it might revive some failed drug development projects and put forward a suitable plan for treating different diseases such as COVID-19 and HT. It is also worth noting that applying efficient computational methods helps to produce better results.


Subject(s)
Antihypertensive Agents/therapeutic use , Coronavirus Infections/drug therapy , Data Mining , Drug Repositioning , Pneumonia, Viral/drug therapy , Algorithms , Betacoronavirus , Databases, Factual , Humans , Machine Learning , Pandemics
8.
Infect Dis Poverty ; 9(1): 130, 2020 Sep 16.
Article in English | MEDLINE | ID: covidwho-768651

ABSTRACT

BACKGROUND: COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn't stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. METHODS: We compared Italy's status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. RESULTS: The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. CONCLUSIONS: Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Algorithms , Betacoronavirus/isolation & purification , China/epidemiology , Coronavirus Infections/transmission , Coronavirus Infections/virology , Disease Outbreaks , Humans , Italy/epidemiology , Models, Statistical , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Prevalence
10.
Medwave ; 20(7): e8008, 2020 Aug 28.
Article in Spanish | MEDLINE | ID: covidwho-740553

ABSTRACT

In December 2019, a new strain of the SARS-CoV-2 coronavirus was reported in Wuhan, China, which produced severe lung involvement and progressed to respiratory distress. To date, more than seventeen million confirmed cases and more than half a million died worldwide from COVID-19. Patients with cardiovascular disease are more susceptible to contracting this disease and presenting more complications. We did a literature search on the association of cardiovascular disease and COVID-19 in databases such as Scopus, PubMed/MEDLINE, and the Cochrane Library. The purpose of this review is to provide updated information for health professionals who care for patients with COVID-19 and cardiovascular disease, given that they have a high risk of complications and mortality. Treatment with angiotensin-converting enzyme inhibitors and receptor blockers is controversial, and there is no evidence not to use these medications in patients with COVID-19. Regarding treatment with hydroxychloroquine associated or not with azithromycin, there is evidence of a higher risk with its use than clinical benefit and decreased mortality. Likewise, patients with heart failure are an important risk group due to their condition per se. Patients with heart failure and COVID-19 are a diagnostic dilemma because the signs of acute heart failure could be masked. On the other hand, in patients with acute coronary syndrome, the initial therapeutic approach could change in the context of the pandemic, although only based on expert opinions. Nonetheless, many controversial issues will be the subject of future research.


Subject(s)
Betacoronavirus , Cardiovascular Diseases/complications , Coronavirus Infections/complications , Pneumonia, Viral/complications , Acute Coronary Syndrome/etiology , Acute Coronary Syndrome/therapy , Algorithms , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , Antiviral Agents/adverse effects , Azithromycin/adverse effects , Coronavirus Infections/drug therapy , Drug Therapy, Combination , Electrocardiography/drug effects , Heart Failure/etiology , Heart Failure/therapy , Humans , Hydroxychloroquine/adverse effects , Hypertension/complications , Hypertension/drug therapy , Pandemics , Peptidyl-Dipeptidase A/metabolism , Pneumonia, Viral/drug therapy , Prognosis , Renin-Angiotensin System/physiology
11.
J Bras Nefrol ; 42(2 suppl 1): 4-8, 2020 Aug 26.
Article in English, Portuguese | MEDLINE | ID: covidwho-740457

ABSTRACT

The Covid-19 pandemic brought several challenges to the healthcare system: diagnosis, treatment and measures to prevent the spread of the disease. With the greater availability and variety of diagnostic tests, it is essential to properly interpret them. This paper intends to help dialysis units concerning the use of clinical criteria and diagnostic tests for decision making regarding the discontinuation of isolation of patients with suspected or confirmed Covid-19, as well as the return to work activities for employees with suspected or confirmed Covid-19.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques/standards , Coronavirus Infections/diagnosis , Nephrology/standards , Pneumonia, Viral/diagnosis , Renal Dialysis , Return to Work , Algorithms , Brazil , Checklist , Clinical Decision-Making , Clinical Laboratory Techniques/methods , Coronavirus Infections/epidemiology , Humans , Occupational Diseases/diagnosis , Pandemics , Patient Isolation , Pneumonia, Viral/epidemiology , Real-Time Polymerase Chain Reaction/methods , Real-Time Polymerase Chain Reaction/standards , Societies, Medical/standards , Urology Department, Hospital/standards
12.
Orphanet J Rare Dis ; 15(1): 228, 2020 08 31.
Article in English | MEDLINE | ID: covidwho-736401

ABSTRACT

During the COVID-19 outbreak, the European Reference Network on Rare Bone Diseases (ERN BOND) coordination team and Italian rare bone diseases healthcare professionals created the "COVID-19 Helpline for Rare Bone Diseases" in an attempt to provide high-quality information and expertise on rare bone diseases remotely to patients and healthcare professionals. The present position statement describes the key characteristics of the Helpline initiative, along with the main aspects and topics that recurrently emerged as central for rare bone diseases patients and professionals. The main topics highlighted are general recommendations, pulmonary complications, drug treatment, trauma, pregnancy, children and elderly people, and patient associations role. The successful experience of the "COVID-19 Helpline for Rare Bone Diseases" launched in Italy could serve as a primer of gold-standard remote care for rare bone diseases for the other European countries and globally. Furthermore, similar COVID-19 helplines could be considered and applied for other rare diseases in order to implement remote patients' care.


Subject(s)
Betacoronavirus , Bone Diseases/complications , Coronavirus Infections/complications , Pneumonia, Viral/complications , Rare Diseases/complications , Remote Consultation/standards , Aged , Algorithms , Bone Diseases/therapy , Child , Coronavirus Infections/prevention & control , Coronavirus Infections/therapy , Female , Humans , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/therapy , Pregnancy , Rare Diseases/therapy , Wounds and Injuries
13.
PLoS One ; 15(8): e0237832, 2020.
Article in English | MEDLINE | ID: covidwho-729563

ABSTRACT

This paper analyses the evolution of COVID-19 in Cameroon over the period March 6-April 2020 using SIR models. Specifically, we 1) evaluate the basic reproduction number of the virus, 2) determine the peak of the infection and the spread-out period of the disease, and 3) simulate the interventions of public health authorities. Data used in this study is obtained from the Cameroonian Public Health Ministry. The results suggest that over the identified period, the reproduction number of COVID-19 in Cameroon is about 1.5, and the peak of the infection should have occurred at the end of May 2020 with about 7.7% of the population infected. Furthermore, the implementation of efficient public health policies could help flatten the epidemic curve.


Subject(s)
Basic Reproduction Number , Coronavirus Infections/epidemiology , Disease Progression , Pneumonia, Viral/epidemiology , Algorithms , Betacoronavirus , Cameroon/epidemiology , Computer Simulation , Coronavirus Infections/prevention & control , Humans , Likelihood Functions , Models, Statistical , Pandemics/prevention & control , Pneumonia, Viral/prevention & control
14.
J Infect Dis ; 222(6): 903-909, 2020 08 17.
Article in English | MEDLINE | ID: covidwho-726096

ABSTRACT

High-throughput molecular testing for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) may be enabled by group testing in which pools of specimens are screened, and individual specimens tested only after a pool tests positive. Several laboratories have recently published examples of pooling strategies applied to SARS-CoV-2 specimens, but overall guidance on efficient pooling strategies is lacking. Therefore we developed a model of the efficiency and accuracy of specimen pooling algorithms based on available data on SAR-CoV-2 viral dynamics. For a fixed number of tests, we estimate that programs using group testing could screen 2-20 times as many specimens compared with individual testing, increase the total number of true positive infections identified, and improve the positive predictive value of results. We compare outcomes that may be expected in different testing situations and provide general recommendations for group testing implementation. A free, publicly-available Web calculator is provided to help inform laboratory decisions on SARS-CoV-2 pooling algorithms.


Subject(s)
Betacoronavirus/isolation & purification , Clinical Laboratory Techniques/methods , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Specimen Handling/methods , Algorithms , Betacoronavirus/genetics , Coronavirus Infections/diagnosis , Humans , Incidence , Pandemics , Pneumonia, Viral/diagnosis , Predictive Value of Tests , RNA, Viral/genetics , RNA, Viral/isolation & purification , Reverse Transcriptase Polymerase Chain Reaction , Sensitivity and Specificity , Viral Load/methods
15.
J Med Internet Res ; 22(7): e20912, 2020 07 30.
Article in English | MEDLINE | ID: covidwho-724770

ABSTRACT

BACKGROUND: Intervention measures have been implemented around the world to mitigate the spread of the coronavirus disease (COVID-19) pandemic. Understanding the dynamics of the disease spread and the effectiveness of the interventions is essential in predicting its future evolution. OBJECTIVE: The aim of this study is to simulate the effect of different social distancing interventions and investigate whether their timing and stringency can lead to multiple waves (subepidemics), which can provide a better fit to the wavy behavior observed in the infected population curve in the majority of countries. METHODS: We have designed and run agent-based simulations and a multiple wave model to fit the infected population data for many countries. We have also developed a novel Pandemic Response Index to provide a quantitative and objective way of ranking countries according to their COVID-19 response performance. RESULTS: We have analyzed data from 18 countries based on the multiple wave (subepidemics) hypothesis and present the relevant parameters. Multiple waves have been identified and were found to describe the data better. The effectiveness of intervention measures can be inferred by the peak intensities of the waves. Countries imposing fast and stringent interventions exhibit multiple waves with declining peak intensities. This result strongly corroborated with agent-based simulations outcomes. We also provided an estimate of how much lower the number of infections could have been if early and strict intervention measures had been taken to stop the spread at the first wave, as actually happened for a handful of countries. A novel index, the Pandemic Response Index, was constructed, and based on the model's results, an index value was assigned to each country, quantifying in an objective manner the country's response to the pandemic. CONCLUSIONS: Our results support the hypothesis that the COVID-19 pandemic can be successfully modeled as a series of epidemic waves (subepidemics) and that it is possible to infer to what extent the imposition of early intervention measures can slow the spread of the disease.


Subject(s)
Communicable Disease Control , Computer Simulation , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Public Health Informatics/methods , Algorithms , Betacoronavirus , Forecasting , Global Health , Humans , Pandemics , Population Dynamics , Quarantine
16.
Semergen ; 46 Suppl 1: 26-34, 2020 Aug.
Article in Spanish | MEDLINE | ID: covidwho-724076

ABSTRACT

Rest homes for the elderly have been particularly hit during the crisis due the current COVID-19 pandemic. At the time of writing this article, more than 17,500 elderly people that lived in Care Homes have died due to coronavirus, more than 66% of the deaths. The infection and mortality rates in the institutionalised population are high. This is due to the advanced age, immune system deficit, and the presence of comorbidities, as well as because there are frail, because they live with other residents and carers in a closed institution, and transmission is easy in the context of a highly contagious and virulent virus. The elderly often have more severe forms of the disease. Atypical presentations are more frequent in the elderly and can delay the diagnosis. The Polymer Chain Reaction (PCR) test in the first 7 days for the detection of SARS-CoV-2 viral RNA is considered the test of reference ('Gold standard'). The criteria for referring to a hospital site from Care Homes should take into account an assessment of comorbidity, the severity, the presence of severe cognitive impairment, and the dependency or necessity of ventilatory support in seriously ill patients. The social-health centres should have contingency plans available in order to offer a response when cases of COVID-19 appear. Isolation during pandemics may have important physical and psychosocial consequences in the residents. It is necessary to reflect and claim a new residential model from a person-centered care approach that seeks the integration of health and social services.


Subject(s)
Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Homes for the Aged , Nursing Homes , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Primary Health Care , Aged , Algorithms , Humans , Pandemics
17.
PLoS One ; 15(8): e0237901, 2020.
Article in English | MEDLINE | ID: covidwho-723873

ABSTRACT

Among the different indicators that quantify the spread of an epidemic such as the on-going COVID-19, stands first the reproduction number which measures how many people can be contaminated by an infected person. In order to permit the monitoring of the evolution of this number, a new estimation procedure is proposed here, assuming a well-accepted model for current incidence data, based on past observations. The novelty of the proposed approach is twofold: 1) the estimation of the reproduction number is achieved by convex optimization within a proximal-based inverse problem formulation, with constraints aimed at promoting piecewise smoothness; 2) the approach is developed in a multivariate setting, allowing for the simultaneous handling of multiple time series attached to different geographical regions, together with a spatial (graph-based) regularization of their evolutions in time. The effectiveness of the approach is first supported by simulations, and two main applications to real COVID-19 data are then discussed. The first one refers to the comparative evolution of the reproduction number for a number of countries, while the second one focuses on French departments and their joint analysis, leading to dynamic maps revealing the temporal co-evolution of their reproduction numbers.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Models, Statistical , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Spatio-Temporal Analysis , Algorithms , Coronavirus Infections/virology , Databases, Factual , Disease Transmission, Infectious/statistics & numerical data , France/epidemiology , Humans , Pandemics , Pneumonia, Viral/virology , Poisson Distribution , Software
18.
IEEE Pulse ; 11(4): 2-7, 2020.
Article in English | MEDLINE | ID: covidwho-721092

ABSTRACT

Qualitative interpretation is a good thing when it comes to reading lung images in the fight against coronavirus 2019 disease (COVID-19), but quantitative analysis makes radiology reporting much more comprehensive. To that end, several research groups have begun looking to artificial intelligence (AI) as a tool for reading and analyzing X-rays and computed tomography (CT) scans, and helping to diagnose and monitor COVID-19.


Subject(s)
Artificial Intelligence , Coronavirus Infections/diagnostic imaging , Lung/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted , Tomography, X-Ray Computed , Algorithms , Betacoronavirus , Humans , Pandemics
19.
Braz J Microbiol ; 51(3): 1109-1115, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-718579

ABSTRACT

COVID-19 has killed more than 500,000 people worldwide and more than 60,000 in Brazil. Since there are no specific drugs or vaccines, the available tools against COVID-19 are preventive, such as the use of personal protective equipment, social distancing, lockdowns, and mass testing. Such measures are hindered in Brazil due to a restrict budget, low educational level of the population, and misleading attitudes from the federal authorities. Predictions for COVID-19 are of pivotal importance to subsidize and mobilize health authorities' efforts in applying the necessary preventive strategies. The Weibull distribution was used to model the forecast prediction of COVID-19, in four scenarios, based on the curve of daily new deaths as a function of time. The date in which the number of daily new deaths will fall below the rate of 3 deaths per million - the average level in which some countries start to relax the stay-at-home measures - was estimated. If the daily new deaths curve was bending today (i.e., about 1250 deaths per day), the predicted date would be on July 5. Forecast predictions allowed the estimation of overall death toll at the end of the outbreak. Our results suggest that each additional day that lasts to bend the daily new deaths curve may correspond to additional 1685 deaths at the end of COVID-19 outbreak in Brazil (R2 = 0.9890). Predictions of the outbreak can be used to guide Brazilian health authorities in the decision-making to properly fight COVID-19 pandemic.


Subject(s)
Coronavirus Infections/epidemiology , Forecasting/methods , Pneumonia, Viral/epidemiology , Algorithms , Brazil/epidemiology , Coronavirus Infections/mortality , Coronavirus Infections/prevention & control , Detergents/supply & distribution , Education/statistics & numerical data , Humans , Least-Squares Analysis , Nonlinear Dynamics , Pandemics/prevention & control , Pneumonia, Viral/mortality , Pneumonia, Viral/prevention & control , Politics , Population Density , Poverty , Socioeconomic Factors , Statistics as Topic , Time Factors , Water Supply/standards
20.
Int J Environ Res Public Health ; 17(16)2020 08 12.
Article in English | MEDLINE | ID: covidwho-717728

ABSTRACT

In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony-tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China-considered the first city to suffer from COVID-19-was chosen as an example of verification; the two-level model and the immune algorithm-ant colony optimization-tabu search (IA-ACO-TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.


Subject(s)
Algorithms , Coronavirus Infections/epidemiology , Medical Waste Disposal/methods , Pneumonia, Viral/epidemiology , Transportation/methods , Urban Population , Betacoronavirus , China/epidemiology , Cities , Humans , Pandemics , Public Health , Transportation/standards
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