Intersecting Infections of Public Health Significance Page I Intersecting Infections of Public Health Significance

Total Page:16

File Type:pdf, Size:1020Kb

Intersecting Infections of Public Health Significance Page I Intersecting Infections of Public Health Significance Intersecting Infections of Public Health Significance Page i Intersecting Infections of Public Health Significance The Epidemiology of HIV, Viral Hepatitis, Sexually Transmitted Diseases, and Tuberculosis in King County 2008 Intersecting Infections of Public Health Significance was supported by a cooperative agreement from the Centers for Disease Control and Prevention Published December 2009 Alternate formats of this report are available upon request Intersecting Infections of Public Health Significance Page ii David Fleming, MD, Director Jeffrey Duchin, MD, Director, Communicable Disease Epidemiology & Immunization Program Matthew Golden, MD, MPH, Director, STD Program Masa Narita, MD, Director, TB Program Robert Wood, MD, Director, HIV/AIDS Program Prepared by: Hanne Thiede, DVM, MPH Elizabeth Barash, MPH Jim Kent, MS Jane Koehler, DVM, MPH Other contributors: Amy Bennett, MPH Richard Burt, PhD Susan Buskin, PhD, MPH Christina Thibault, MPH Roxanne Pieper Kerani, PhD Eyal Oren, MS Shelly McKeirnan, RN, MPH Amy Laurent, MSPH Cover design and formatting by Tanya Hunnell The report is available at www.kingcounty.gov/health/hiv For additional copies of this report contact: HIV/AIDS Epidemiology Program Public Health – Seattle & King County 400 Yesler Way, 3rd Floor Seattle, WA 98104 206-296-4645 Intersecting Infections of Public Health Significance Page iii Table of Contents INDEX OF TABLES AND FIGURES ········································································ vi EXECUTIVE SUMMARY ······················································································ 1 I. INTRODUCTION ··························································································· 2 II. DESCRIPTION OF KING COUNTY···································································· 5 III. HUMAN IMMUNODEFICIENCY VIRUS (HIV) ···················································· 7 Background ····································································································· 7 Surveillance systems and reporting requirements ······················································· 7 Clinical aspects ································································································· 7 Transmission···································································································· 8 Prevention······································································································· 8 HIV in King County ···························································································· 9 Findings from case surveillance······································································· 9 Findings from other projects and research studies················································ 14 HIV/AIDS key findings ························································································ 20 IV. HEPATITIS B AND C····················································································· 21 Hepatitis B································································································· 21 Background ····································································································· 21 Surveillance systems and reporting requirements ······················································· 21 Clinical aspects ································································································· 21 Transmission···································································································· 21 Prevention······································································································· 22 Hepatitis B in King County ··················································································· 22 Findings from case surveillance······································································· 22 Findings from other projects and research studies················································ 23 Hepatitis B key findings······················································································· 24 Hepatitis C································································································· 25 Background ····································································································· 25 Surveillance systems and reporting requirements ······················································· 25 Clinical aspects ································································································· 25 Transmission···································································································· 25 Prevention······································································································· 25 Hepatitis C in King County ··················································································· 26 Findings from case surveillance······································································· 26 Findings from other projects and research studies················································ 27 Hepatitis C key findings······················································································· 28 V. SEXUALLY TRANSMITTED DISEASES—GONORRHEA, CHLAMYDIA, SYPHILIS ········· 29 Background ····································································································· 29 Surveillance systems and reporting requirements ······················································· 29 Transmission···································································································· 29 Chlamydia ································································································· 30 Clinical aspects ································································································· 30 Chlamydia in King County ···················································································· 30 Findings from case surveillance······································································· 30 Intersecting Infections of Public Health Significance Page iv V. SEXUALLY TRANSMITTED DISEASES (continued) Gonorrhea··································································································· 31 Clinical Aspects ·································································································· 31 Gonorrhea in King County ····················································································· 31 Findings from case surveillance ······································································· 31 Syphilis······································································································· 34 Clinical Aspects ·································································································· 34 Syphilis in King County ························································································· 34 Findings from case surveillance ······································································· 34 STDs in men who have sex with men (MSM) ····················································· 34 Findings from case surveillance ······································································· 34 Findings from other STD projects and research studies·········································· 35 STD key findings ································································································ 36 VI. TUBERCULOSIS··························································································· 37 Background······································································································· 37 Surveillance systems and reporting requirements························································· 37 Clinical aspects··································································································· 37 Transmission ····································································································· 37 Prevention ········································································································ 37 Tuberculosis in King County··················································································· 37 Findings from case surveillance ······································································· 37 Findings from other projects and research studies················································ 41 Tuberculosis key findings ······················································································ 41 VII. CO-INFECTIONS ························································································ 42 Introduction ······································································································ 42 HIV/hepatitis C ··························································································· 42 Background······································································································· 42 Transmission ····································································································· 42 HIV/HCV co-infection in King County ········································································ 42 Findings from case surveillance ······································································· 42 HIV/HCV co-infection key findings ···········································································
Recommended publications
  • REALM Research Briefing: Vaccines, Variants, and Venitlation
    Briefing: Vaccines, Variants, and Ventilation A Briefing on Recent Scientific Literature Focused on SARS-CoV-2 Vaccines and Variants, Plus the Effects of Ventilation on Virus Spread Dates of Search: 01 January 2021 through 05 July 2021 Published: 22 July 2021 This document synthesizes various studies and data; however, the scientific understanding regarding COVID-19 is continuously evolving. This material is being provided for informational purposes only, and readers are encouraged to review federal, state, tribal, territorial, and local guidance. The authors, sponsors, and researchers are not liable for any damages resulting from use, misuse, or reliance upon this information, or any errors or omissions herein. INTRODUCTION Purpose of This Briefing • Access to the latest scientific research is critical as libraries, archives, and museums (LAMs) work to sustain modified operations during the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. • As an emerging event, the SARS-CoV-2 pandemic continually presents new challenges and scientific questions. At present, SARS-CoV-2 vaccines and variants in the US are two critical areas of focus. The effects of ventilation-based interventions on the spread of SARS-CoV-2 are also an interest area for LAMs. This briefing provides key information and results from the latest scientific literature to help inform LAMs making decisions related to these topics. How to Use This Briefing: This briefing is intended to provide timely information about SARS-CoV-2 vaccines, variants, and ventilation to LAMs and their stakeholders. Due to the evolving nature of scientific research on these topics, the information provided here is not intended to be comprehensive or final.
    [Show full text]
  • STI Screening Timetable
    Patient Education Information from University Health Center’s STI Screening Clinic Page 1 of 1 STI Screening Timetable How long until STI (sexually transmitted infection) screening tests turn positive? How long until STI symptoms might show up? The time between infection and a positive test, or between infection and symptoms, is variable and depends on many factors, including the behavior of the infectious agent, how and where the body is infected, and the state of a person’s immune system and personal health. Many STIs don’t have any symptoms. The incubation period times listed in the chart below are averages only. If you have further questions or concerns, you can schedule an appointment with a clinician at 541-346-2770. STI screening test Window period (time from exposure until Incubation period (time between exposure and screening test turns positive) when symptoms appear) Chlamydia (urine specimen or swab of 1 week most of the time Often no symptoms vagina, rectum, throat) 2 weeks catches almost all 1-3 weeks on average Gonorrhea (urine specimen on swab of 1 week most of the time Often no symptoms, especially vaginal vagina, rectum, throat) 2 weeks catches almost all infections usually within 2-8 days but can be up to 2 weeks Syphilis (blood test, RPR) 1 month catches most Often symptoms too mild to notice 3 months catches almost all 10-90 days average 21 days HIV (oral cheek swab) 1 month catches most Sometimes mild body aches and fever within 1-2 3 months catches almost all weeks then can be months to years HIV (blood test, antigen/antibody
    [Show full text]
  • Incubation Period and Other Epidemiological
    Journal of Clinical Medicine Article Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data 1, 1, 1 1 Natalie M. Linton y , Tetsuro Kobayashi y, Yichi Yang , Katsuma Hayashi , Andrei R. Akhmetzhanov 1 , Sung-mok Jung 1 , Baoyin Yuan 1, Ryo Kinoshita 1 and Hiroshi Nishiura 1,2,* 1 Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan; [email protected] (N.M.L.); [email protected] (T.K.); [email protected] (Y.Y.); katsuma5miff[email protected] (K.H.); [email protected] (A.R.A.); [email protected] (S.-m.J.); [email protected] (B.Y.); [email protected] (R.K.) 2 Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan * Correspondence: [email protected]; Tel.: +81-11-706-5066 These authors contributed equally to this work. y Received: 25 January 2020; Accepted: 10 February 2020; Published: 17 February 2020 Abstract: The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution.
    [Show full text]
  • A Predictive Modelling Framework for COVID-19 Transmission to Inform the Management of Mass Events
    medRxiv preprint doi: https://doi.org/10.1101/2021.05.13.21256857; this version posted May 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . A Predictive Modelling Framework for COVID-19 Transmission to Inform the Management of Mass Events Claire Donnat Freddy Bunbury Department of Statistics Department of Plant Biology University of Chicago, Chicago, USA Carnegie Institution for Science, Stanford, USA [email protected] [email protected] Jack Kreindler Filippos T. Filippidis School of Public Health School of Public Health Imperial College, London, UK Imperial College, London, UK [email protected] [email protected] Austen El-Osta Tõnu Esko Matthew Harris School of Public Health Institute of Genomics School of Public Health Imperial College, London, UK University of Tartu, Tartu, Estonia Imperial College, London, UK [email protected] [email protected] [email protected] Abstract Modelling COVID-19 transmission at live events and public gatherings is essential to evaluate and control the probability of subsequent outbreaks. Model estimates can be used to inform event organizers about the possibility of super-spreading and the predicted efficacy of safety protocols, as well as to communicate to participants their personalised risk so that they may choose whether to attend. Yet, despite the fast-growing body of literature on COVID transmission dynamics, current risk models either neglect contextual information on vaccination rates or disease prevalence or do not attempt to quantitatively model transmission, thus limiting their potential to provide insightful estimates.
    [Show full text]
  • From the COCCI Syndemic to the COVID-19 Pandemic
    Scholars Insight Publishers Journal of Epidemiology and Global Health Research Research Article Open Access From the COCCI Syndemic to the COVID-19 Pandemic: A Cautionary Tale Interaction of Metabolic Syndrome, Obesity, Particulate Matter (PM), SARS-CoV-2 and the inflammatory response Clearfield M*, Gayer G, Wagner A, Stevenson T, Shubrook J and Gugliucci A Touro University College of Osteopathic Medicine, California, USA Corresponding Author: Dr. Clearfield M, Touro University Abstract College of Osteopathic Medicine, California, USA. A narrative review of the literature was conducted to determine E-mail id: [email protected] associations between cardiovascular (CV) risk factors associated with the COCCI syndemic (Cardiovascular disease as a result of the Received Date: March 15, 2021; interactions between obesity, climate change and inflammation) and Accepted Date: May 19, 2021; COVID-19. Published Date: May 21, 2021; The COCCI syndemic consists of two health conditions Publisher: Scholars Insight Online Publishers (dysmetabolic obesity and air pollution) that interact via biologic Citation: Clearfield M*, Gayer G, Wagner A, Stevenson T, pathways admixed with social, economic and ecologic drivers Shubrook J and Gugliucci A “From the COCCI Syndemic to augmenting adverse clinical outcomes in excess of either of these the COVID-19 Pandemic: A Cautionary Tale Interaction of health conditions individually. Metabolic Syndrome, Obesity, Particulate Matter (PM), SARS- The comorbidities noted with COVID-19 are in large part aligned CoV-2 and the inflammatory response”. J Epidemiol Glob Health with those traditional risk factors associated with CVD. In addition, Res. 2021; 1:102 when the traditional CV comorbidities are combined with the Copyright: ©2021 Clearfield M.
    [Show full text]
  • Possible Modes of Transmission of Novel Coronavirus SARS-Cov-2
    Acta Biomed 2020; Vol. 91, N. 3: e2020036 DOI: 10.23750/abm.v91i3.10039 © Mattioli 1885 Reviews / Focus on Possible modes of transmission of Novel Coronavirus SARS-CoV-2: a review Richa Mukhra1, Kewal Krishan1, Tanuj Kanchan2 1 Department of Anthropology (UGC Centre of Advanced Study), Panjab University, Sector-14, Chandigarh, India 2 Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, India. Abstract: Introduction: The widespread outbreak of the novel SARS-CoV-2 has raised numerous questions about the origin and transmission of the virus. Knowledge about the mode of transmission as well as assess- ing the effectiveness of the preventive measures would aid in containing the outbreak of the coronavirus. Presently, respiratory droplets, physical contact and aerosols/air-borne have been reported as the modes of SARS-CoV-2 transmission of the virus. Besides, some of the other possible modes of transmission are being explored by the researchers, with some studies suggesting the viral spread through fecal-oral, conjunctival secretions, flatulence (farts), sexual and vertical transmission from mother to the fetus, and through asymp- tomatic carriers, etc. Aim: The primary objective was to review the present understanding and knowledge about the transmission of SARS-CoV-2 and also to suggest recommendations in containing and preventing the novel coronavirus. Methods: A review of possible modes of transmission of the novel SARS-CoV-2 was conducted based on the reports and articles available in PubMed and ScienceDirect.com that were searched using keywords, ‘transmission’, ‘modes of transmission’, ‘SARS-CoV-2’, ‘novel coronavirus’, and ‘COVID-19’. Articles refer- ring to air-borne, conjunctiva, fecal-oral, maternal-fetal, flatulence (farts), and breast milk transmission were included, while the remaining were excluded.
    [Show full text]
  • Using Proper Mean Generation Intervals in Modeling of COVID-19
    ORIGINAL RESEARCH published: 05 July 2021 doi: 10.3389/fpubh.2021.691262 Using Proper Mean Generation Intervals in Modeling of COVID-19 Xiujuan Tang 1, Salihu S. Musa 2,3, Shi Zhao 4,5, Shujiang Mei 1 and Daihai He 2* 1 Shenzhen Center for Disease Control and Prevention, Shenzhen, China, 2 Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China, 3 Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria, 4 The Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China, 5 Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China In susceptible–exposed–infectious–recovered (SEIR) epidemic models, with the exponentially distributed duration of exposed/infectious statuses, the mean generation interval (GI, time lag between infections of a primary case and its secondary case) equals the mean latent period (LP) plus the mean infectious period (IP). It was widely reported that the GI for COVID-19 is as short as 5 days. However, many works in top journals used longer LP or IP with the sum (i.e., GI), e.g., >7 days. This discrepancy will lead to overestimated basic reproductive number and exaggerated expectation of Edited by: infection attack rate (AR) and control efficacy. We argue that it is important to use Reza Lashgari, suitable epidemiological parameter values for proper estimation/prediction. Furthermore, Institute for Research in Fundamental we propose an epidemic model to assess the transmission dynamics of COVID-19 Sciences, Iran for Belgium, Israel, and the United Arab Emirates (UAE).
    [Show full text]
  • Malaria and COVID-19: Common and Different Findings
    Tropical Medicine and Infectious Disease Viewpoint Malaria and COVID-19: Common and Different Findings Francesco Di Gennaro 1 , Claudia Marotta 1,*, Pietro Locantore 2, Damiano Pizzol 3 and Giovanni Putoto 1 1 Operational Research Unit, Doctors with Africa CUAMM, 35121 Padova, Italy; [email protected] (F.D.G.); [email protected] (G.P.) 2 Institute of Endocrinology, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; [email protected] 3 Italian Agency for Development Cooperation, Khartoum 79371, Sudan; [email protected] * Correspondence: [email protected] or [email protected] Received: 31 July 2020; Accepted: 3 September 2020; Published: 6 September 2020 Abstract: Malaria and COVID-19 may have similar aspects and seem to have a strong potential for mutual influence. They have already caused millions of deaths, and the regions where malaria is endemic are at risk of further suffering from the consequences of COVID-19 due to mutual side effects, such as less access to treatment for patients with malaria due to the fear of access to healthcare centers leading to diagnostic delays and worse outcomes. Moreover, the similar and generic symptoms make it harder to achieve an immediate diagnosis. Healthcare systems and professionals will face a great challenge in the case of a COVID-19 and malaria syndemic. Here, we present an overview of common and different findings for both diseases with possible mutual influences of one on the other, especially in countries with limited resources. Keywords: malaria; SARS-CoV-2; COVID-19; preparedness; Africa; emergency; pandemic 1. Background On 11 March 2020, the WHO declared the outbreak of SARS-CoV-2 to be a pandemic infection.
    [Show full text]
  • Prediction of the Incubation Period for COVID-19 and Future Virus Disease Outbreaks Ayal B
    Gussow et al. BMC Biology (2020) 18:186 https://doi.org/10.1186/s12915-020-00919-9 RESEARCH ARTICLE Open Access Prediction of the incubation period for COVID-19 and future virus disease outbreaks Ayal B. Gussow†, Noam Auslander*†, Yuri I. Wolf and Eugene V. Koonin* Abstract Background: A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. At the time of the COVID-19 pandemic, optimization of quarantine regimes becomes paramount for public health, societal well- being, and global economy. However, biological factors that determine the duration of the virus incubation period remain poorly understood. Results: We demonstrate a strong positive correlation between the length of the incubation period and disease severity for a wide range of human pathogenic viruses. Using a machine learning approach, we develop a predictive model that accurately estimates, solely from several virus genome features, in particular, the number of protein-coding genes and the GC content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2. The predictive approach described here can directly help in establishing the appropriate quarantine durations and thus facilitate controlling future outbreaks. Conclusions: The length of the incubation period in viral diseases strongly correlates with disease severity, emphasizing the biological and epidemiological importance of the incubation period. Perhaps, surprisingly, incubation times of pathogenic RNA viruses can be accurately predicted solely from generic features of virus genomes. Elucidation of the biological underpinnings of the connections between these features and disease progression can be expected to reveal key aspects of virus pathogenesis.
    [Show full text]
  • Sexually Transmitted Infections Treatment Guidelines, 2021
    Morbidity and Mortality Weekly Report Recommendations and Reports / Vol. 70 / No. 4 July 23, 2021 Sexually Transmitted Infections Treatment Guidelines, 2021 U.S. Department of Health and Human Services Centers for Disease Control and Prevention Recommendations and Reports CONTENTS Introduction ............................................................................................................1 Methods ....................................................................................................................1 Clinical Prevention Guidance ............................................................................2 STI Detection Among Special Populations ............................................... 11 HIV Infection ......................................................................................................... 24 Diseases Characterized by Genital, Anal, or Perianal Ulcers ............... 27 Syphilis ................................................................................................................... 39 Management of Persons Who Have a History of Penicillin Allergy .. 56 Diseases Characterized by Urethritis and Cervicitis ............................... 60 Chlamydial Infections ....................................................................................... 65 Gonococcal Infections ...................................................................................... 71 Mycoplasma genitalium .................................................................................... 80 Diseases Characterized
    [Show full text]
  • Chlamydial Genital Infection(Chlamydia Trachomatis)
    Chlamydial Genital Infection (Chlamydia trachomatis) February 2003 1) THE DISEASE AND ITS EPIDEMIOLOGY A. Etiologic Agent Chlamydial genital infection (CGI) is caused by the obligate, intracellular bacterium Chlamydia trachomatis immunotypes D through K. B. Clinical Description and Laboratory Diagnosis A sexually transmitted genital infection that manifests in males primarily as urethritis and in females as mucopurulent cervicitis. Clinical manifestations are difficult to distinguish from gonorrhea. Males may present with a mucopurulent discharges of scanty to moderate quantity, urethral itching and dysuria. Asymptomatic infection may be found in 1%-25% of sexually active men. Possible complications include epididymitis, infertility and Reiter syndrome. Anorectal intercourse may result in chlamydial proctitis. Women frequently present with a mucopurulent endocervical discharge including edema, erythema and easily induced endocervical bleeding. However, most women with endocervical or urethral infections are asymptomatic. Possible complications include salpingitis with subsequent risk of infertility and ectopic pregnancy. Asymptomatic chronic infections of the endometrium and fallopian tubes may lead to the same outcomes. Less frequent manifestations include bartholinitis, urethral syndrome with dysuria and pyuria, perihepatitis (Fitz-Hugh-Curtis syndrome), and proctitis. Infection during pregnancy may result in premature rupture of membranes and preterm delivery and conjunctival and pneumonic infection of the newborn. Laboratory diagnosis is based upon the identification of Chlamydia in intraurethral or endocervical smear by direct immunofluorescence test, enzyme immunoassay, DNA probe, and nucleic acid amplification test (NAAT) or cell culture. NAAT can be used with urine specimens. C. Vectors and Reservoirs Humans. D. Modes of Transmission By sexual contact and through perinatal exposure to the mother’s infected cervix.
    [Show full text]
  • Incubation Periods Impact the Spatial Predictability of Cholera and Ebola Outbreaks in Sierra Leone
    Incubation periods impact the spatial predictability of cholera and Ebola outbreaks in Sierra Leone Rebecca Kahna,1, Corey M. Peaka,1, Juan Fernández-Graciaa,b, Alexandra Hillc, Amara Jambaid, Louisa Gandae, Marcia C. Castrof, and Caroline O. Buckeea,2 aCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115; bInstitute for Cross-Disciplinary Physics and Complex Systems, Universitat de les Illes Balears - Consell Superior d’Investigacions Científiques, E-07122 Palma de Mallorca, Spain; cDisease Control in Humanitarian Emergencies, World Health Organization, CH-1211 Geneva 27, Switzerland; dDisease Control and Prevention, Sierra Leone Ministry of Health and Sanitation, Freetown, Sierra Leone FPGG+89; eCountry Office, World Health Organization, Freetown, Sierra Leone FPGG+89; and fDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA 02115 Edited by Burton H. Singer, University of Florida, Gainesville, FL, and approved January 22, 2020 (received for review July 29, 2019) Forecasting the spatiotemporal spread of infectious diseases during total number of secondary infections by an infectious individual in an outbreak is an important component of epidemic response. a completely susceptible population (i.e., R0) (13, 14). Indeed, the However, it remains challenging both methodologically and with basis of contact tracing protocols during an outbreak reflects the respect to data requirements, as disease spread is influenced by need to identify and contain individuals during the incubation numerous factors, including the pathogen’s underlying transmission period, and the relative effectiveness of interventions such as parameters and epidemiological dynamics, social networks and pop- symptom monitoring or quarantine significantly depends on the ulation connectivity, and environmental conditions.
    [Show full text]