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1.
Comput Math Methods Med ; 2021: 2689000, 2021.
Article in English | MEDLINE | ID: covidwho-1566408

ABSTRACT

We have studied one of the most common distributions, namely, Lindley distribution, which is an important continuous mixed distribution with great ability to represent different systems. We studied this distribution with three parameters because of its high flexibility in modelling life data. The parameters were estimated by five different methods, namely, maximum likelihood estimation, ordinary least squares, weighted least squares, maximum product of spacing, and Cramér-von Mises. Simulation experiments were performed with different sample sizes and different parameter values. The different methods were compared on the generated data by mean square error and mean absolute error. In addition, we compared the methods for real data, which represent COVID-19 data in Iraq/Anbar Province.


Subject(s)
COVID-19/epidemiology , Public Health Informatics/methods , Algorithms , Computer Simulation , Humans , Iraq , Least-Squares Analysis , Likelihood Functions , Models, Statistical , Public Health Informatics/standards , SARS-CoV-2 , Statistics as Topic
2.
BMJ Open ; 10(9): e040487, 2020 09 10.
Article in English | MEDLINE | ID: covidwho-760256

ABSTRACT

OBJECTIVE: To evaluate the quality of information regarding the prevention and treatment of COVID-19 available to the general public from all countries. DESIGN: Systematic analysis using the 'Ensuring Quality Information for Patients' (EQIP) Tool (score 0-36), Journal of American Medical Association (JAMA) benchmark (score 0-4) and the DISCERN Tool (score 16-80) to analyse websites containing information targeted at the general public. DATA SOURCES: Twelve popular search terms, including 'Coronavirus', 'COVID-19 19', 'Wuhan virus', 'How to treat coronavirus' and 'COVID-19 19 Prevention' were identified by 'Google AdWords' and 'Google Trends'. Unique links from the first 10 pages for each search term were identified and evaluated on its quality of information. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: All websites written in the English language, and provides information on prevention or treatment of COVID-19 intended for the general public were considered eligible. Any websites intended for professionals, or specific isolated populations, such as students from one particular school, were excluded, as well as websites with only video content, marketing content, daily caseload update or news dashboard pages with no health information. RESULTS: Of the 1275 identified websites, 321 (25%) were eligible for analysis. The overall EQIP, JAMA and DISCERN scores were 17.8, 2.7 and 38.0, respectively. Websites originated from 34 countries, with the majority from the USA (55%). News Services (50%) and Government/Health Departments (27%) were the most common sources of information and their information quality varied significantly. Majority of websites discuss prevention alone despite popular search trends of COVID-19 treatment. Websites discussing both prevention and treatment (n=73, 23%) score significantly higher across all tools (p<0.001). CONCLUSION: This comprehensive assessment of online COVID-19 information using EQIP, JAMA and DISCERN Tools indicate that most websites were inadequate. This necessitates improvements in online resources to facilitate public health measures during the pandemic.


Subject(s)
Coronavirus Infections , Internet/standards , Pandemics , Pneumonia, Viral , Public Health Informatics , Betacoronavirus , COVID-19 , Consumer Health Information/standards , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/therapy , Data Accuracy , Humans , Needs Assessment , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/therapy , Public Health Informatics/methods , Public Health Informatics/standards , Public Health Informatics/trends , SARS-CoV-2
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