Estimating COVID-19 Prevalence and Infection Control Practices Among US Dentists
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Estimating the Instantaneous Asymptomatic Proportion with a Simple Approach: Exemplified with the Publicly Available COVID-19 Surveillance Data in Hong Kong
ORIGINAL RESEARCH published: 03 May 2021 doi: 10.3389/fpubh.2021.604455 Estimating the Instantaneous Asymptomatic Proportion With a Simple Approach: Exemplified With the Publicly Available COVID-19 Surveillance Data in Hong Kong Chunyu Li 1†, Shi Zhao 2,3*†, Biao Tang 4,5, Yuchen Zhu 1, Jinjun Ran 6, Xiujun Li 1*‡ and Daihai He 7*‡ 1 2 Edited by: Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China, JC 3 Catherine Ropert, School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China, Chinese University of 4 Federal University of Minas Hong Kong (CUHK) Shenzhen Research Institute, Shenzhen, China, School of Mathematics and Statistics, Xi’an Jiaotong 5 Gerais, Brazil University, Xi’an, China, Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, ON, Canada, 6 School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Reviewed by: Hong Kong, China, 7 Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China Mohammad Javanbakht, Baqiyatallah University of Medical Sciences, Iran Background: The asymptomatic proportion is a critical epidemiological characteristic Changjing Zhuge, that modulates the pandemic potential of emerging respiratory virus, which may vary Beijing University of Technology, China *Correspondence: depending on the nature of the disease source, population characteristics, source–host Daihai He interaction, and environmental factors. [email protected] Xiujun Li Methods: We developed a simple likelihood-based framework to estimate the [email protected] instantaneous asymptomatic proportion of infectious diseases. Taking the COVID-19 Shi Zhao epidemics in Hong Kong as a case study, we applied the estimation framework [email protected] to estimate the reported asymptomatic proportion (rAP) using the publicly available † These authors share first authorship surveillance data. -
Globalization and Infectious Diseases: a Review of the Linkages
TDR/STR/SEB/ST/04.2 SPECIAL TOPICS NO.3 Globalization and infectious diseases: A review of the linkages Social, Economic and Behavioural (SEB) Research UNICEF/UNDP/World Bank/WHO Special Programme for Research & Training in Tropical Diseases (TDR) The "Special Topics in Social, Economic and Behavioural (SEB) Research" series are peer-reviewed publications commissioned by the TDR Steering Committee for Social, Economic and Behavioural Research. For further information please contact: Dr Johannes Sommerfeld Manager Steering Committee for Social, Economic and Behavioural Research (SEB) UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR) World Health Organization 20, Avenue Appia CH-1211 Geneva 27 Switzerland E-mail: [email protected] TDR/STR/SEB/ST/04.2 Globalization and infectious diseases: A review of the linkages Lance Saker,1 MSc MRCP Kelley Lee,1 MPA, MA, D.Phil. Barbara Cannito,1 MSc Anna Gilmore,2 MBBS, DTM&H, MSc, MFPHM Diarmid Campbell-Lendrum,1 D.Phil. 1 Centre on Global Change and Health London School of Hygiene & Tropical Medicine Keppel Street, London WC1E 7HT, UK 2 European Centre on Health of Societies in Transition (ECOHOST) London School of Hygiene & Tropical Medicine Keppel Street, London WC1E 7HT, UK TDR/STR/SEB/ST/04.2 Copyright © World Health Organization on behalf of the Special Programme for Research and Training in Tropical Diseases 2004 All rights reserved. The use of content from this health information product for all non-commercial education, training and information purposes is encouraged, including translation, quotation and reproduction, in any medium, but the content must not be changed and full acknowledgement of the source must be clearly stated. -
FORMULAS from EPIDEMIOLOGY KEPT SIMPLE (3E) Chapter 3: Epidemiologic Measures
FORMULAS FROM EPIDEMIOLOGY KEPT SIMPLE (3e) Chapter 3: Epidemiologic Measures Basic epidemiologic measures used to quantify: • frequency of occurrence • the effect of an exposure • the potential impact of an intervention. Epidemiologic Measures Measures of disease Measures of Measures of potential frequency association impact (“Measures of Effect”) Incidence Prevalence Absolute measures of Relative measures of Attributable Fraction Attributable Fraction effect effect in exposed cases in the Population Incidence proportion Incidence rate Risk difference Risk Ratio (Cumulative (incidence density, (Incidence proportion (Incidence Incidence, Incidence hazard rate, person- difference) Proportion Ratio) Risk) time rate) Incidence odds Rate Difference Rate Ratio (Incidence density (Incidence density difference) ratio) Prevalence Odds Ratio Difference Macintosh HD:Users:buddygerstman:Dropbox:eks:formula_sheet.doc Page 1 of 7 3.1 Measures of Disease Frequency No. of onsets Incidence Proportion = No. at risk at beginning of follow-up • Also called risk, average risk, and cumulative incidence. • Can be measured in cohorts (closed populations) only. • Requires follow-up of individuals. No. of onsets Incidence Rate = ∑person-time • Also called incidence density and average hazard. • When disease is rare (incidence proportion < 5%), incidence rate ≈ incidence proportion. • In cohorts (closed populations), it is best to sum individual person-time longitudinally. It can also be estimated as Σperson-time ≈ (average population size) × (duration of follow-up). Actuarial adjustments may be needed when the disease outcome is not rare. • In an open populations, Σperson-time ≈ (average population size) × (duration of follow-up). Examples of incidence rates in open populations include: births Crude birth rate (per m) = × m mid-year population size deaths Crude mortality rate (per m) = × m mid-year population size deaths < 1 year of age Infant mortality rate (per m) = × m live births No. -
Statistical Guidance on Reporting Results from Studies Evaluating Diagnostic Tests Document Issued On: March 13, 2007
Guidance for Industry and FDA Staff Statistical Guidance on Reporting Results from Studies Evaluating Diagnostic Tests Document issued on: March 13, 2007 The draft of this document was issued on March 12, 2003. For questions regarding this document, contact Kristen Meier at 240-276-3060, or send an e-mail to [email protected]. U.S. Department of Health and Human Services Food and Drug Administration Center for Devices and Radiological Health Diagnostic Devices Branch Division of Biostatistics Office of Surveillance and Biometrics Contains Nonbinding Recommendations Preface Public Comment Written comments and suggestions may be submitted at any time for Agency consideration to the Division of Dockets Management, Food and Drug Administration, 5630 Fishers Lane, Room 1061, (HFA-305), Rockville, MD, 20852. Alternatively, electronic comments may be submitted to http://www.fda.gov/dockets/ecomments. When submitting comments, please refer to Docket No. 2003D-0044. Comments may not be acted upon by the Agency until the document is next revised or updated. Additional Copies Additional copies are available from the Internet at: http://www.fda.gov/cdrh/osb/guidance/1620.pdf. You may also send an e-mail request to [email protected] to receive an electronic copy of the guidance or send a fax request to 240-276-3151 to receive a hard copy. Please use the document number 1620 to identify the guidance you are requesting. Contains Nonbinding Recommendations Table of Contents 1. Background....................................................................................................4 -
Estimated HIV Incidence and Prevalence in the United States
Volume 26, Number 1 Estimated HIV Incidence and Prevalence in the United States, 2015–2019 This issue of the HIV Surveillance Supplemental Report is published by the Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services, Atlanta, Georgia. Estimates are presented for the incidence and prevalence of HIV infection among adults and adolescents (aged 13 years and older) based on data reported to CDC through December 2020. The HIV Surveillance Supplemental Report is not copyrighted and may be used and reproduced without permission. Citation of the source is, however, appreciated. Suggested citation Centers for Disease Control and Prevention. Estimated HIV incidence and prevalence in the United States, 2015–2019. HIV Surveillance Supplemental Report 2021;26(No. 1). http://www.cdc.gov/ hiv/library/reports/hiv-surveillance.html. Published May 2021. Accessed [date]. On the Web: http://www.cdc.gov/hiv/library/reports/hiv-surveillance.html Confidential information, referrals, and educational material on HIV infection CDC-INFO 1-800-232-4636 (in English, en Español) 1-888-232-6348 (TTY) http://wwwn.cdc.gov/dcs/ContactUs/Form Acknowledgments Publication of this report was made possible by the contributions of the state and territorial health departments and the HIV surveillance programs that provided surveillance data to CDC. This report was prepared by the following staff and contractors of the Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC: Laurie Linley, Anna Satcher Johnson, Ruiguang Song, Sherry Hu, Baohua Wu, H. -
2019 Maryland STI Annual Report
November 2020 Dear Marylanders, The Maryland Department of Health (MDH) Center for STI Prevention (CSTIP) is pleased to present the 2019 Maryland STI Annual Report. Under Maryland law, health care providers and laboratories must report all laboratory-confirmed cases of chlamydia, gonorrhea, and syphilis to the state health department or the local health department where a patient resides. Other STIs, such as herpes, trichomoniasis, and human papillomavirus (HPV), also affect sexual and reproductive health, but these are not reportable infections and therefore cannot be tracked and are not included in this report. CSTIP epidemiologists collect, interpret and disseminate population-level data based on the reported cases of chlamydia, gonorrhea, syphilis and congenital syphilis, to inform state and local health officials, health care providers, policymakers and the public about disease trends and their public health impact. The data include cases, rates, and usually, Maryland’s national rankings for each STI, which are calculated once all states’ STI data are reported to the Centers for Disease Control and Prevention (CDC). The CDC then publishes these data, including state-by-state rankings, each fall for the prior year. The 2019 report is not expected to be released until early 2021 because of COVID-related lags in reporting across the country. The increases in STIs observed in Maryland over the past 10 years mirrors those occurring nationwide, and the increasing public health, medical and economic burden of STIs are cause for deep concern. The causes for these increases are likely multi-factorial. According to CDC, data suggest contributing factors include: Substance use, poverty, stigma, and unstable housing, all of which can reduce access to prevention and care Decreased condom use among vulnerable groups Shrinking public health resources over years resulting in clinic closures, reduced screening, staff loss, and reduced patient follow-up and linkage to care services Stemming the tide of STIs requires national, state and local collaboration. -
Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem
Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem Charles F. Manski Francesca Molinari The Institute for Fiscal Studies Department of Economics, UCL cemmap working paper CWP20/20 Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem Charles F. Manski Department of Economics and Institute for Policy Research, Northwestern University and Francesca Molinari Department of Economics, Cornell University April 26, 2020, forthcoming in the Journal of Econometrics Abstract As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Illinois, New York, and Italy is substantially lower than reported. Acknowledgements: We thank Yizhou Kuang for able research assistance. We thank Mogens Fosgerau, Michael Gmeiner, Valentyn Litvin, John Pepper, Jörg Stoye, Elie Tamer, and an anonymous reviewer for helpful comments. We are grateful for the opportunity to present this work at an April 13, 2020 virtual seminar at the Institute for Policy Research, Northwestern University. -
Understanding Relative Risk, Odds Ratio, and Related Terms: As Simple As It Can Get Chittaranjan Andrade, MD
Understanding Relative Risk, Odds Ratio, and Related Terms: As Simple as It Can Get Chittaranjan Andrade, MD Each month in his online Introduction column, Dr Andrade Many research papers present findings as odds ratios (ORs) and considers theoretical and relative risks (RRs) as measures of effect size for categorical outcomes. practical ideas in clinical Whereas these and related terms have been well explained in many psychopharmacology articles,1–5 this article presents a version, with examples, that is meant with a view to update the knowledge and skills to be both simple and practical. Readers may note that the explanations of medical practitioners and examples provided apply mostly to randomized controlled trials who treat patients with (RCTs), cohort studies, and case-control studies. Nevertheless, similar psychiatric conditions. principles operate when these concepts are applied in epidemiologic Department of Psychopharmacology, National Institute research. Whereas the terms may be applied slightly differently in of Mental Health and Neurosciences, Bangalore, India different explanatory texts, the general principles are the same. ([email protected]). ABSTRACT Clinical Situation Risk, and related measures of effect size (for Consider a hypothetical RCT in which 76 depressed patients were categorical outcomes) such as relative risks and randomly assigned to receive either venlafaxine (n = 40) or placebo odds ratios, are frequently presented in research (n = 36) for 8 weeks. During the trial, new-onset sexual dysfunction articles. Not all readers know how these statistics was identified in 8 patients treated with venlafaxine and in 3 patients are derived and interpreted, nor are all readers treated with placebo. These results are presented in Table 1. -
Ethics of Vaccine Research
COMMENTARY Ethics of vaccine research Christine Grady Vaccination has attracted controversy at every stage of its development and use. Ethical debates should consider its basic goal, which is to benefit the community at large rather than the individual. accines truly represent one of the mira- include value, validity, fair subject selection, the context in which it will be used and Vcles of modern science. Responsible for favorable risk/benefit ratio, independent acceptable to those who will use it. This reducing morbidity and mortality from sev- review, informed consent and respect for assessment considers details about the pub- eral formidable diseases, vaccines have made enrolled participants. Applying these princi- lic health need (such as the prevalence, bur- substantial contributions to global public ples to vaccine research allows consideration den and natural history of the disease, as health. Generally very safe and effective, vac- of some of the particular challenges inherent well as existing strategies to prevent or con- cines are also an efficient and cost-effective in testing vaccines (Box 1). trol it), the scientific data and possibilities way of preventing disease. Yet, despite their Ethically salient features of clinical vac- (preclinical and clinical data, expected brilliant successes, vaccines have always been cine research include the fact that it involves mechanism of action and immune corre- controversial. Concerns about the safety and healthy subjects, often (or ultimately) chil- lates) and the likely use of the vaccine (who untoward effects of vaccines, about disturb- dren and usually (at least when testing effi- will use and benefit from it, safety, cost, dis- ing the natural order, about compelling indi- cacy) in very large numbers. -
Disease Incidence, Prevalence and Disability
Part 3 Disease incidence, prevalence and disability 9. How many people become sick each year? 28 10. Cancer incidence by site and region 29 11. How many people are sick at any given time? 31 12. Prevalence of moderate and severe disability 31 13. Leading causes of years lost due to disability in 2004 36 World Health Organization 9. How many people become sick each such as diarrhoeal disease or malaria, it is common year? for individuals to be infected repeatedly and have several episodes. For such conditions, the number The “incidence” of a condition is the number of new given in the table is the number of disease episodes, cases in a period of time – usually one year (Table 5). rather than the number of individuals affected. For most conditions in this table, the figure given is It is important to remember that the incidence of the number of individuals who developed the illness a disease or condition measures how many people or problem in 2004. However, for some conditions, are affected by it for the first time over a period of Table 5: Incidence (millions) of selected conditions by WHO region, 2004 Eastern The Mediter- South- Western World Africa Americas ranean Europe East Asia Pacific Tuberculosisa 7.8 1.4 0.4 0.6 0.6 2.8 2.1 HIV infectiona 2.8 1.9 0.2 0.1 0.2 0.2 0.1 Diarrhoeal diseaseb 4 620.4 912.9 543.1 424.9 207.1 1 276.5 1 255.9 Pertussisb 18.4 5.2 1.2 1.6 0.7 7.5 2.1 Measlesa 27.1 5.3 0.0e 1.0 0.2 17.4 3.3 Tetanusa 0.3 0.1 0.0 0.1 0.0 0.1 0.0 Meningitisb 0.7 0.3 0.1 0.1 0.0 0.2 0.1 Malariab 241.3 203.9 2.9 8.6 0.0 23.3 2.7 -
Prevalence and Determinants of Vaccine Hesitancy and Vaccines Recommendation Discrepancies Among General Practitioners in French-Speaking Parts of Belgium
Article Prevalence and Determinants of Vaccine Hesitancy and Vaccines Recommendation Discrepancies among General Practitioners in French-Speaking Parts of Belgium Cathy Gobert 1, Pascal Semaille 2, Thierry Van der Schueren 3 , Pierre Verger 4 and Nicolas Dauby 1,5,6,* 1 Department of Infectious Diseases, CHU Saint-Pierre, Université Libre de Bruxelles (ULB), 1000 Bruxelles, Belgium; [email protected] 2 Department of General Medicine, Université Libre de Bruxelles (ULB), 1070 Bruxelles, Belgium; [email protected] 3 Scientific Society of General Practice, 1060 Bruxelles, Belgium; [email protected] 4 Southeastern Health Regional Observatory (ORS PACA), 13005 Marseille, France; [email protected] 5 School of Public Health, Université Libre de Bruxelles (ULB), 1070 Bruxelles, Belgium 6 Institute for Medical Immunology, Université Libre de Bruxelles (ULB), 1070 Bruxelles, Belgium * Correspondence: [email protected] Abstract: General practitioners (GPs) play a critical role in patient acceptance of vaccination. Vaccine hesitancy (VH) is a growing phenomenon in the general population but also affects GPs. Few data exist on VH among GPs. The objectives of this analysis of a population of GPs in the Belgian Wallonia-Brussels Federation (WBF) were to: (1) determine the prevalence and the features of VH, (2) identify the correlates, and (3) estimate the discrepancy in vaccination’s behaviors between the GPs’ children and the recommendations made to their patients. An online survey was carried out Citation: Gobert, C.; Semaille, P.; Van among the population of general practitioners practicing in the WBF between 7 January and 18 der Schueren, T.; Verger, P.; Dauby, N. March 2020. A hierarchical cluster analysis was carried out based on various dimensions of vaccine Prevalence and Determinants of hesitancy: perception of the risks and the usefulness of vaccines as well as vaccine recommendations Vaccine Hesitancy and Vaccines for their patients. -
EPI Case Study 1 Incidence, Prevalence, and Disease
EPIDEMIOLOGY CASE STUDY 1: Incidence, Prevalence, and Disease Surveillance; Historical Trends in the Epidemiology of M. tuberculosis STUDENT VERSION 1.0 EPI Case Study 1: Incidence, Prevalence, and Disease Surveillance; Historical Trends in the Epidemiology of M. tuberculosis Estimated Time to Complete Exercise: 30 minutes LEARNING OBJECTIVES At the completion of this Case Study, participants should be able to: ¾ Explain why denominators are necessary when comparing changes in morbidity and mortality over time ¾ Distinguish between incidence rates and prevalence ratios ¾ Calculate and interpret cause-specific morbidity and mortality rates ¾ Describe how changes in mortality or morbidity could be due to an artifact rather than a real change ASPH EPIDEMIOLOGY COMPETENCIES ADDRESSED C. 3. Describe a public health problem in terms of magnitude, person, place, and time C. 6. Apply the basic terminology and definitions of epidemiology C. 7. Calculate basic epidemiology measures C. 9. Draw appropriate inference from epidemiologic data C. 10. Evaluate the strengths and limitations of epidemiologic reports ASPH INTERDISCIPLINARY/CROSS-CUTTING COMPETENCIES ADDRESSED F.1. [Communication and Informatics] Describe how the public health information infrastructure is used to collect, process, maintain, and disseminate data J.1. [Professionalism] Discuss sentinel events in the history and development of the public health profession and their relevance for practice in the field L.2. [Systems Thinking] Identify unintended consequences produced by changes made to a public health system This material was developed by the staff at the Global Tuberculosis Institute (GTBI), one of four Regional Training and Medical Consultation Centers funded by the Centers for Disease Control and Prevention. It is published for learning purposes only.