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Effects of highly active antiretroviral therapy with nelfinavir in vertically HIV-1 infected children: 3 years of follow-up. Long-term response to nelfinavir in children
Antiretroviral treatment (ART) in children has special features and consequently, results obtained from clinical trials with antiretroviral drugs in adults may not be representative of children. Nelfinavir (NFV) is an HIV-1 Protease Inhibitor (PI) which has become as one of the first choices of PI for ART in children. We studied during a 3-year follow-up period the effects of highly active antiretroviral therapy with nelfinavir in vertically HIV-1 infected children.
Forty-two vertically HIV-infected children on HAART with NFV were involved in a multicentre prospective study. The children were monitored at least every 3 months with physical examinations, and blood sample collection to measure viral load (VL) and CD4+ cell count. We performed a logistic regression analysis to determinate the odds ratio of baseline characteristics on therapeutic failure.
Very important increase in CD4+ was observed and VL decreased quickly and it remained low during the follow-up study. Children with CD4+ <25% at baseline achieved CD4+ >25% at 9 months of follow-up. HIV-infected children who achieved undetectable viral load (uVL) were less than 40% in each visit during follow-up. Nevertheless, HIV-infected children with VL >5000 copies/ml were less than 50% during the follow-up study. Only baseline VL was an important factor to predict VL control during follow-up. Virological failure at defined end-point was confirmed in 30/42 patients. Along the whole of follow-up, 16/42 children stopped HAART with NFV. Baseline characteristics were not associated with therapeutic change.
NFV is a safe drug with a good profile and able to achieve an adequate response in children.
The introduction of highly active antiretroviral therapy (HAART) has lead to a significant decrease in mortality and disease progression in HIV-1 infected children and adolescents
Nelfinavir (NFV) is an HIV-1 Protease Inhibitor (PI). When combined with other antiretroviral drugs, it has been associated with immunologic and virologic responses in antiretroviral therapy-naïve and experienced adults and children with a good tolerance profile
Population and study design
This is a multicentre prospective study on a cohort of 42 vertically HIV-infected children on HAART with NFV recruited between May 1997 to October 2001, and followed-up until October 2004 in 5 Spanish hospitals. This study was conducted according to the declaration of Helsinki and approved by the Ethical Committees of all hospitals involved.
The inclusion criteria were: a) VL >1,000 copies/mL at baseline, b) at least 6 months of follow-up, c) starting HAART for the first time with nelfinavir (25–35 mg/Kg, three times per day), d) having received mono or dual nucleoside therapy before starting HAART. e) No CD4+ cell count and age restrictions. All vertically HIV infected children in Madrid are enrolled in the same cohort, which has 276 patients. We selected those patients who started HAART with NFV, 72 out of 276. Nevertheless, from these 72 infants, 42 had previous treatment and 14 were naïve. We selected only the 42 experienced children in this study.
The children were monitored under a standardized form at least every 3 months with physical examinations, and serial measurements of CD4+ T-cells and VL as described below
VL was measured in plasma using the Amplicor Monitor assay. (Amplicor monitor, Roche Diagnostic Systems, Brandenburg, NJ, USA). The limit of quantification (LOQ) was 400 copies/mL. Adherence was measured by each clinician by pill count methods and interviews with parents or tutors.
Statistical analysis
Analysis of data was performed by on-treatment analysis of observed data. Data from patients who were lost to follow-up were censored during the last visit. Endpoint for therapeutical failure was defined as any of the following: a) failure to reduce VL < 1 log10 during the first 12 weeks of HAART, unless it was < lower LOQ; and b) failure to achieve a VL < LOQ after 24 weeks of HAART. c) change of NRTI or additional NNRTI or PI in HAART regimen during the first 24 months of follow-up, while taking NFV; d) Stop of HAART with NFV during the first 24 months of follow-up. We performed a multivariate logistic regression analysis to determinate the odds ratio (OR) of baseline characteristics (%CD4+, VL, and age at baseline, previous ART protocol, and new drugs in HAART regimen) on therapeutical failure.
Moreover, we also consider as therapeutic failure during the whole follow-up: a) achieve a decrease of 1 log10 VL, unless it was < lower LOQ; b) achieve VL < LOQ. c) change of NRTI or additional NNRTI or PI in HAART; d) stop of HAART with NFV. e) rebound of two consecutive VL ≥ LOQ after achieving a VL < LOQ. This treatment failure was analyzed by Kaplan-Meier method and multivariate Cox regression analyses to assess the hazard ratio (HR) values of baseline characteristics.
All tests were two-tailed with P-values < 0.05 considered significant. Statistical analysis was performed by SPSS 12.0 software (SPSS INC, Chicago, IL, USA).
Characteristics of HIV-1-infected children
During the study period (median: 41 (min: 6; max: 71.3) months), a total of 42 children with previous ART started HAART with NFV (Table
Table 1
Characteristics of clinical, immunological, and virological parameters, and antiretroviral treatment of vertically HIV-1-infected children.
N. of HIV-children
Age (years) (a)
6.7 ± 0.64 (0.5; 16.1)
Male (b)
16 (38.1%)
AIDS diagnosis (CDC) (b)
23 (54.7%)
Baseline CD4 + cell count
% CD4+(a)
23.2 ± 1.8 (0.8; 49.7)
15 – 25% CD4+(b)
13 (22%)
<15 % CD4+(b)
16 (27.1%)
Baseline HIV-RNA level
log10 VL (copies/mL)(a)
4.52 ± 0.11 (3.22; 6.84)
VL >50,000 copies/mL(b)
14 (33.3%)
ART with NRTI prior-HAART (b)
39 (92.9%)
Therapy combined
3 (7.1%)
HAART regimen at baseline (b)
3TC + d4T + NFV
27 (64.3%)
6 (14.3%)
d4T + ddI + NFV
9 (21.49%)
New NRTI on HAART
14 (33.3%)
14 (33.3%)
14 (33.3%)
HAART regimen during follow-up (b)
Global adherence (>90%)
Change of drugs on first line of HAART
9 (21.4%)
Change of NRTI
2 (4.8%)
Adding a NNRTI
4 (9.5%)
Adding a PI
3 (7.1%)
Stop of HAART with NFV
16 (38.1%)
Change of NFV by other PI
12 (28.6%)
Interruption of HAART
4 (9.5%)
Values are expressed as: a) mean ± s.e.m. (min; max), and b) absolute (percentage). VL: viral load; CDC: Center for Disease Control. HAART: highly active antiretroviral therapy.
The HAART protocol used was 2 NRTI plus NFV and 28/42 of children changed NRTI in first line of HAART, because all of them have taken previous NRTI regimens.
Virological and immunological response
A very important increase in CD4+ was observed and VL decreased quickly and sustained (Figure
Figure 1
Summary of viral load (VL) and %CD4+ evolution during follow-up
Summary of viral load (VL) and %CD4+ evolution during follow-up. A: mean of log10 VL (copies/ml) and CD4+ T-cells percentage. B: mean of CD4+ T-cells percentage according to CD4+ at baseline (< or > 25%). C: percentage of HIV-infected children with VL ≤400 copies/ml and VL >5000 copies/ml.
In this follow-up study, 38/42 children achieved a decrease in VL < 1 log10 and 28/42 children achieved uVL anytime during follow-up (Figure
Figure 2
Summary of Kaplan-Meier curves of HIV-infected children on HAART during follow-up
Summary of Kaplan-Meier curves of HIV-infected children on HAART during follow-up. A: to achieve VL <400 copies/ml for the first time or to achieve a decrease of -1 log10 VL. B: rebound of viral load after achieving VL ≤400 copies/ml. C: to change NRTI or additional NNRTI or PI in HAART regimen in the first line of HAART; or stop HAART with nelfinavir.
Only baseline VL and previous ART protocol [Combined therapy (CT) or Mono-therapy (MT)] were important factors to predict VL control during follow-up. The HR of baseline VL to achieve uVL was 0.33 (CI95%: 0.16; 0.68; p = 0.003) per log10 VL at baseline and HR of previous ART protocol (CT vs. MT) to achieve uVL was 0.18 (CI95%: 0.05; 0.69; p = 0.013). HIV-infected children with VL >50,000 copies/mL at baseline had a negative likelihood of 3.34 (CI95%: 1.15; 9.67; p = 0.014) to achieve uVL. After achieving uVL, 17/28 children had a rebound of VL >400 copies/ml with a mean time of 17.7 ± 6.4 months (Figure
Moreover, 19/42 children changed of NRTI or additional NNRTI or PI in HAART regimen in the first line of HAART, with a mean of time of 30.4 ± 1.32 months. Besides, 16/42 children stopped HAART with NFV with a mean of time of 27.4 ± 1.7 months by Kaplan-Meier method (Figure
Endpoint of therapeutical failure
Virological failure at defined end-point was confirmed in 30/42 patients. Besides, 20/42 children had virological failure defined as a reduction in VL <1 log10 during the first 12 weeks of HAART; and 25/42 children had virological failure to achieve a VL < LOQ after 24 weeks of HAART. When these 3 criteria of virological failure were used combined, we only found that baseline VL had a value of OR of 3.76 (CI95%: 1.13; 12.47; p = 0.03) per log10 and VL >50,000 copies/mL at baseline had a value of OR of 8.57 (CI95%: 1.31; 56.3; p = 0.025) to achieve a VL < LOQ after 24 weeks of HAART.
On HAART with NFV, 9/42 children changed of NRTI or additional NNRTI or PI in HAART regimen during the first 24 months of follow-up and 15/42 children stopped HAART with NFV during the first 24 months of follow-up.
Clinical events
Among all patients, one child died and two children developed AIDS during the follow-up. Only four patients experienced side effects; diarrhoea in two patients, rash and hypertransaminasemia in one infant and hypercholesterolemia in other child.
The adherence of the antiretroviral drugs was measured by each paediatrician by examination of the dose taken by each child and through interviews with their parents or tutors. Overall, the adherence was >90% among all the infants included in our study during the follow-up. Besides, HAART with NFV was well tolerated.
Our study reveals that NFV is a safe drug with a good profile and active to achieve an adequate response in HIV-1 infected children. NFV, like other PI, is highly active in vitro, therefore its activity in vivo is limited by their rapid clearance
We recruited 42 infants who were not naïve to antiretroviral drugs. Nevertheless, NFV showed high efficacy in increasing the CD4+ cell count and early decreasing of VL among the three years of follow-up. Our results are similar to other studies which evaluate NFV efficacy among children
The presence of higher virologic failures at the end of our study, 71.4% compared with data published with adults, have been shown in previous analysis because children have higher VL and require longer times to achieve an uVL
During the three years, 45% change the line of HAART and 38% interrupt NFV. These patients have similar characteristics at baseline so the use of a resistance test may have allowed selecting the most appropriate NRTI for each patient. Moreover, at baseline only 1/3 of children included 2 new NRTI in HAART line and 1/3 did not take any new NRTI. High virologic failure at the end of our study is probably due to previous resistance mutations to NRTI. Besides, new NNRTI or PI were added as second HAART line and some patients changed NRTI during the follow-up. However, the global tendency of VL was not improved which could be explained by the appearance of new resistance mutations to NRTI or cross resistance to PI. It is probable that if a resistance assay would have been used to guide changes of ART, virological response would have been higher.
Our study reveals that NFV is safe because only four patients experienced side effects. These results are considerably minor than other studies that reveal gastrointestinal side effects related to the use of NFV in 18% patients
In conclusion, when selecting an antiretroviral combination we need to consider short and long toxicities, as well as the immunologic, virologic and clinical benefit that a patient can achieve. Our results show that NFV is an effective and well tolerate drug for HIV infection among children. However, more studies which include measurements as TDM or resistance test are needed to evaluate the use of this drug in paediatric population.
Competing interests
Potential conflicts of interest: The authors declare that they have no competing interests.
Authors' contributions
SR had primary responsibility for protocol development, patient screening, enrolment, outcome assessment, preliminary data analysis, and contributed to the writing of the manuscript. BL contributed to the writing of the manuscript. JM Bellón participated in analytic framework for the study, and contributed to the writing of the manuscript. RR had primary responsibility for the collecting and recording data, and contributed to the writing of the manuscript. Paediatricians: MIJ, MDG, JL, JTR and MJM were responsible for patient screening, and contributed to the writing of the manuscript. MAMF supervised the design and execution of the study, the final data analyses, and the writing of the manuscript. All authors read and approved the final manuscript.
Financial Support:
Fundación para la Investigación y la Prevención del SIDA en España (FIPSE) (grant 12456/03). Fundación para la Investigación Sanitaria (FIS) del Ministerio de Sanidad y Consumo (PI040883, PI052479, PI052472, PI052411), Plan Nacional de Salud (SAF 2003-09209, SAF-2004-06778), Red Temática Cooperativa de investigación en SIDA (RIS G03/173) of FIS, and Red Temática Cooperativa de investigación en Genética (RIG C03/07) of FIS.
Salvador Resino and Jose María Bellón are supported by a grant of FIS (grant CP04/00090, 01/A016 respectively).
Participating hospitals and sites
Hospital 12 Octubre: J.T. Ramos, P. Carreño, J. Ruiz, J. Clemente. Hospital Gregorio Marañón: J.M. Bellón, M.D. Gurbindo, M.L. Navarro, S. Resino, M.A. Muñoz-Fernández. Hospital La Paz: M.I. Isabel de José, Beatriz Larrú. Hospital Carlos III: P. Martín-Fontelos, M.J. Mellado, J. Villota.
Hospital Virgen del Rocío: J.A. León Leal.
Reduction in mortality with availability of antiretroviral therapy for children with perinatal HIV-1 infection. Italian Register for HIV Infection in Children and the Italian National AIDS Registry
Extensive implementation of highly active antiretroviral therapy shows great effectiveness on the survival and surrogate markers in vertically HIV-infected children.
Nucleoside-analogue reverse-transcriptase inhibitors plus nevirapine, nelfinavir, or ritonavir for pretreated children infected with human immunodeficiency virus type 1
Long-term responses to treatment including ritonavir or nelfinavir in HIV-1-infected children. Pediatric AIDS Group of Switzerland
Pharmacokinetics and pharmacodynamics of nelfinavir administered twice or thrice daily to human immunodeficiency virus type 1-infected children
Pharmacokinetics of nelfinavir and its active metabolite, hydroxy-tert-butylamide, in infants perinatally infected with human immunodeficiency virus type 1
Combination therapy with efavirenz, nelfinavir, and nucleoside reverse- transcriptase inhibitors in children infected with human immunodeficiency virus type 1. Pediatric AIDS Clinical Trials Group 382 Team
Positive virologic outcome after lopinavir/ritonavir salvage therapy in protease inhibitor-experienced HIV-1-infected children. A prospective cohort study
ABT-378/ritonavir plus stavudine and lamivudine for the treatment of antiretroviral-naive adults with HIV-1 infection: 48-week results
Lopinavir-ritonavir versus nelfinavir for the initial treatment of HIV infection
Forty-eight-week evaluation of lopinavir/ritonavir, a new protease inhibitor, in human immunodeficiency virus-infected children
HIV protease inhibitors increase adiponectin levels in HIV-negative men
The metabolic effects of lopinavir/ritonavir in HIV-negative men
Alternative, age- and viral load-related routes of nelfinavir resistance in human immunodeficiency virus type 1-infected children receiving highly active antiretroviral therapy
An MDR1-3435 variant is associated with higher plasma nelfinavir levels and more rapid virologic response in HIV-1 infected children
Predictive markers of clinical outcome in vertically HIV-1 infected infants. A prospective longitudinal study
Protease inhibitor combination therapy, severity of illness, and quality of life among children with perinatally acquired HIV-1 infection
Pre-publication history
The pre-publication history for this paper can be accessed here:


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Nicknames: Dark Angels, Liberators, Hammers
Next to Mal and Count Orzaiz, Nova Vigilance is the most identifiable and visible facet of the Teragen. NV is essentially a nova watchdog group, looking out for novas around the world and seeking retribution in their name. Seen as the counterpart of T2M, the two groups have clashed on a number of occasions. This delights N! and its viewers but worries Utopia and the world governments. Unlike the Primacy, NV is not motivated by any agenda beyond the protection and freedom of all novas. This does not mean keeping the kid gloves on, however. On the contrary, the Terats of NV are firm believers in the lex talionis: an eye for an eye - if you publicly slam novas, expect a demonstration, if you kill or injure a nova, expect the worst, as the Mayor of Tampa discovered.
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8.5/ 10


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- Anne McDonald
- 2 years ago
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3 Guide to METHODS & TOOLS FOR AIRLINE FLIGHT SAFETY ANALYSIS Prepared by: GAIN Working Group B, Analytical Methods and Tools Second Edition June 2003
5 Table of Contents Foreword...v Acknowledgements...vi 1.0 Introduction Purpose of Guide GAIN Overview Working Group B: Analytical Methods and Tools Scope Definitions Review of Methods and Tools Organization of this Guide Changes Made to this Edition of the Guide Guide Update and Feedback Application of Analytical Tools to Airline Flight Safety Types of Airline Flight Safety Data Occurrence Reports Digital Flight Data Safety Audits and Assessments Types of Tools for Airline Flight Safety Analysis Flight Safety Event Reporting and Analysis Systems Flight Data Monitoring Analysis and Visualization Tools Human Factors Analysis Tools Special Purpose Analytical Tools Summary Flight Safety Event Reporting and Analysis Systems Safety Report Management and Analysis Systems...14 Aeronautical Events Reports Organizer (AERO)...14 Aviation Quality Database (AQD)...15 AVSiS...16 British Airways Safety Information System (BASIS)...17 First Launch Safety Report System (SRS)...18 INDICATE Safety Program Descriptive Statistics and Trend Analysis...20 HeliStat...20 Microsoft Excel...21 Statgraphics Plus...22 Page i
6 Table of Contents (continued) Page 4.0 Flight Data Monitoring Analysis and Visualization Tools...24 Aircraft Flight Analysis & Safety Explore (AirFASE)...25 Analysis Ground Station (AGS)...26 Aviation Performance Measuring System (APMS)...26 AVSCAN.flight...27 BASIS Flight Data Tools...28 Cockpit Emulator for Flight Analysis (CEFA)...29 Event Measurement System (EMS)...29 FlightAnalyst...30 FlightTracer...31 FlightViz...31 FltMaster...32 GRAF Vision Flight Data Animator...32 Ground Recovery & Analysis Facility (GRAF) for Windows and PERMIT...33 Line Operations Monitoring System (LOMS)...34 Recovery, Analysis, & Presentation System (RAPS) & Insight...35 Software Analysis for Flight Exceedance (SAFE) Human Factors Analysis Tools...37 Aircrew Incident Reporting System (AIRS)...37 Cabin Procedural Investigation Tool (CPIT)...38 Human Factors Analysis and Classification System (HFACS)...39 Integrated Process for Investigating Human Factors...40 Procedural Event Analysis Tool (PEAT)...41 Ramp Error Decision Aid (REDA)...42 ReVision Special Purpose Analytical Tools Occurrence Investigation and Analysis...46 Investigation Organizer...46 REASON TapRooT Text/Data Mining and Data Visualization...50 Aviation Safety Data Mining Workbench...50 Brio Intelligence FERRET Q...52 NetOwl...53 PolyAnalyst...54 QUORUM Perilog...55 Spotfire...56 ii
7 Table of Contents (continued) Page 6.3 Risk Fault Tree + (Event Tree Module)...59 Fault Tree + (Fault Tree Module)...61 FaultrEASE...62 Markov Latent Effects Tool for Organizational and Operational Safety Assessment...63 Quantitative Risk Assessment System...65 RISKMAN...66 WinNUPRA Analytical Methods Descriptive Statistics and Trend Analysis...68 Characterization/Trend/Threshold Analysis Human Factors Analysis...69 Reason Model Occurrence Investigation and Analysis...70 Integrated Safety Investigation Methodology (ISIM)...70 Multilinear Events Sequencing (MES) Risk Analysis...71 Fault Hazard Analysis (FHA)...71 Failure Mode and Effect Analysis (FMEA) / Failure Modes, Effects, and Criticality Analysis (FMECA)...72 Probabilistic Risk Assessment (PRA)...72 iii
8 Table of Contents (continued) Page Appendices Appendix A: Example Applications of Selected Tools... A-1 Safety Report Management and Analysis Systems A.1 Aviation Quality Database... A-2 A.2 AvSiS...A-14 Descriptive Statistics and Trend Analysis Tools A.3 HeliStat...A-20 A.4 Microsoft Excel...A-25 Flight Data Visualization Tools A.5 FlightTracer... A-32 Human Factors Analysis Tools A.6 Aircrew Incident Reporting System... A-37 A.7 Procedural Event Analysis Tool... A-46 Text/Data Mining Tools A.8 Aviation Safety Data Mining Workbench... A-52 A.9 PolyAnalyst... A-59 Appendix B: Capabilities and Features of Flight Safety Event Reporting and Analysis Systems...B-1 Appendix C: Capabilities and Features of FOQA/Digital Flight Data Analysis Tools...C-1 Appendix D: Methods and Tools Under Development...D-1 Human Factor Analysis Flight Crew Human Factors Integration Tool...D-2 Risk Analysis Aircraft Performance Risk Assessment Model (APRAM)...D-2 Flight Operations Risk Assessment System (FORAS)...D-3 Appendix E: List of Acronyms...E-1 Appendix F: Feedback Form...F-1 iv
9 Foreword This guide to methods and tools useful or potentially useful for airline flight safety analysis is the first in a continuing series that the Global Aviation Information Network (GAIN) Working Group B (Analytical Methods and Tools) plans to issue. In its efforts to increase the awareness of analytical methods and tools in the aviation community, Working Group (WG) B has begun to identify and review analytical methods and tools to support the major segments of aviation, focusing initially on airline flight safety. WG B has also begun to identify and document analytical methods and tools for safety analysis in air traffic management. In the future, the WG plans to address analytical methods and tools to support other aviation segments such as airline maintenance safety, and airport safety. This guide is not a comprehensive inventory of analytical methods and tools that could be used in airline flight safety analysis. Rather, the intent of the WG in this second edition of the Guide is to document an expanded set of methods and tools that appear useful to airlines in particular, as well as other aircraft operators, together with some example applications of how these tools could be applied in flight safety analysis. The group would like to receive feedback on the experience that the aviation community has had with the methods and tools included in this issue as well as suggestions for additional methods and tools with which they are familiar. The reader should view this guide as a living document that will be updated periodically with improved coverage of methods and tools. v
10 Acknowledgements The following GAIN WG B members were primarily responsible for the preparation of this Second Edition of the guide to methods and tools for airline flight safety analysis: Geoff Gosling, Aviation System Planning Consultant Andy Muir, FAA Office of System Safety Christina Hunt, Phaneuf Associates Incorporated (PAI) Grant Schneemann, Abacus Technology Corporation Jean-Jacques Speyer, Airbus WG B members and others who contributed their ideas and comments on this Second Edition of the guide, who assisted in the review and documentation of specific methods and tools, or who conducted an independent review are as follows: Sergei Ananyan, Megaputer Intelligence Incorporated Robert Batson, University of Alabama Jim Blanchard, FleetSecure, LLC Mark Blazy, FAA Office of System Safety Jefferey Bogan, Stransim Aeronautics Corporation David Bristol, Palisade Corporation Tom Chidester, NASA Ames Peter Clapp, Spirent Systems Simon Earthrowl, First Launch Carolyn Edwards, FAA Office of System Safety Tim Fuller, AvSoft Yuri Gawdiak, NASA Sue Glyde, Superstructure Michael Goodfellow, International Air Transport Association Don Gunther, Continental Airlines Keith Hagy, Air Line Pilots Association, International Tamas Igloi, Teledyne Controls Jason Elliot Jones, Decision Systems Incorporated Jeff Julias, Scientech Incorporated Thom Mayer, Austin Digital Incorporated Michael McGreevy, NASA Ames Geoff McIntyre, FAA Office of System Safety Dominique Mineo, CEFA Aviation Mike Moodi, Boeing Commercial Airplane Group Patrick Moylan, Abacus Technology Corporation Zohreh Nazeri, MITRE Corporation Jari Nisula, Airbus Lee Nguyen, FAA Aircraft Certification Service Tom O Kane, formerly of British Airways Michael Poole, Flightscape Incorporated Alexander Pufahl, SimAuthor Incorporated Eddie Rogan, British Airways Alex Richman, AlgoPlus Consulting Shifra Richman, AlgoPlus Consulting Simon Rose, Oak Ridge National Laboratory Edward Skompski, System Improvements Nigel Summerhayes, British Airways Brad Wacker, FAA Office of System Safety Jack Wojciech, formerly of FAA Office of System Safety vi
11 1.0 Introduction 1.1 Purpose of Guide GAIN Guide to Methods & Tools for Airline Flight Safety Analysis The purpose of this guide is to provide information on existing analytical methods and tools that can help the airline community turn their data into valuable information to improve safety. Summaries are presented for 57 methods and tools that can be used to analyze flight safety data including event reports and digital flight data. Global Aviation Information Network (GAIN) Working Group B (Analytical Methods and Tools) hopes that this guide will help increase the awareness of available methods and tools and assist airlines as they consider which tools to incorporate into their safety analysis activities. 1.2 GAIN Overview GAIN is an industry and government initiative to promote and facilitate the voluntary collection and sharing of safety information by and among users in the international aviation community to improve safety. GAIN was first proposed by the Federal Aviation Administration (FAA) in 1996, but has now evolved into an international industry-wide endeavor that involves the participation of professionals from airlines, employee groups, manufacturers, major equipment suppliers and vendors, and other aviation organizations. To date, five world conferences have been held to promote the GAIN concept and share products with the aviation community to improve safety. Through 2003, nearly 900 aviation safety professionals from 49 countries have participated in GAIN. The GAIN organization consists of an industry-led Steering Committee, four working groups, a Program Office, and a Government Support Team. The GAIN Steering Committee is composed of industry stakeholders that set high-level GAIN policy, issue charters to direct the working groups, and guide the program office. The Government Support Team consists of representatives from government organizations that work together to promote and facilitate GAIN in their respective countries. The working groups are interdisciplinary industry and government teams that work GAIN tasks within the action plans established by the Steering Committee. The current GAIN working groups are: Working Group B--Analytical Methods and Tools, Working Group C--Global Information Sharing Systems, and Working Group E--Flt Ops/ATC Ops Safety Information Sharing. The Program Office provides technical and administrative support to the Steering Committee, working groups, and Government Support Team. 1.3 Working Group B: Analytical Methods and Tools Working Group (WG) B was formed in response to the need expressed by many in the aviationuser community for better analytical methods and tools to help convert data into useable safety information. Members of the community have said that the need to manage and analyze everlarger amounts of safety-related data will require the use of increasingly sophisticated tools and techniques. These methods and tools will help safety analysts discover patterns and extract lessons learned in order to identify emerging safety issues and support safety decision-making. Responding to these needs the GAIN Steering Committee chartered WG B to foster the use of 1
12 existing analytical methods and tools and the development of new methods and tools. The WG has four main focus areas: Gather requirements for analytical methods and tools from the aviation-user community Identify and increase awareness of existing methods and tools Assess the usefulness and usability of existing tools in partnership with the aviation community Facilitate the development of enhanced or new analytical tools. This guide was prepared specifically to address the second focus area. 1.4 Scope This document includes methods and tools that are currently used by one or more airlines around the world to analyze flight safety data or information. It also includes methods and tools that are not known to be used by any airlines at present, but that could easily be applied to airline flight safety analysis in the view of GAIN Working Group B. This document pertains to analysis of flight safety issues in an airline, the type of work typically performed by an airline s Flight Safety Department or office performing that function. This document does not consider tools that examine other aviation safety domains, including types of system-wide safety analysis performed by a civil aviation authority or aircraft performance analysis that might be performed by an airframe manufacturer. GAIN Working Group B has prepared a separate document looking at another aviation safety domain, Guide to Methods and Tools for Safety Analysis in Air Traffic Management. In the future, WG B could potentially expand its work to other aviation segments such as airline maintenance safety or airport safety. It should be noted that this guide contains tools that are commercially available, and others that are in the prototype or development phase. Some tools are commonly used while others are infrequently used. Some of the tools are fairly straightforward and easy to use while others are more advanced and may require specialized analytical expertise. Also included are descriptions of methods that have application to flight safety analysis. 1.5 Definitions WG B has adopted the following definitions for distinguishing between methods and tools. Method: An analytical approach or process that may or may not be automated. Tool: A software-based/computerized application of one or more methods. 1.6 Review of Methods and Tools To improve its understanding of the analytical responsibilities, capabilities, and needs of airline flight safety offices, WG B surveyed GAIN Steering Committee members and thirteen airline flight safety offices from around the world. The survey respondents provided information on the 2
13 types of information they collect, tools currently in use, the most useful features of those tools, and gaps in capabilities of current tools. This information was helpful to the WG as it undertook a review in 1999 of methods and tools that are useful or potentially useful for airline flight safety analysis. WG B started its review with a list of over 300 analytical methods and tools from various industries (aviation, nuclear power, chemical, etc.). The initial list was further refined to about 50 methods and tools that were organized into three areas: Flight Safety Event Reporting and Analysis Systems, Flight Data Monitoring Analysis and Visualization Tools, and Specific Purpose Analytical Tools. The first area includes systems that were designed specifically for and are widely used by aviation operators to report and, in some cases, analyze flight safety events. The second area addresses tools that are specifically designed to analyze digitally recorded flight data, namely Flight Data Monitoring and Visualization Tools. The third area represents methods and tools that, for the most part, were not designed for a particular domain but could be used to enhance the analysis of events contained in the safety event reporting systems mentioned above. Since the systems/tools in the Flight Safety Event Reporting and Analysis and Flight Data Monitoring Analysis and Visualization Tools are already being used by airlines, WG B did not conduct a detailed review of these systems/tools. WG B prepared a brief summary of each system/tool and requested the system/tool developer or vendor to complete a standard checklist of the capabilities/features of interest to airlines. WG B also prepared brief summaries of the approximately 30 methods and tools contained in the Specific Purpose Analytical Tools area. In addition, WG B conducted a detailed review involving one or more stages on 14 of these tools that appeared to be the most promising. A more detailed discussion of the three-stage review process for the analytical tools was provided in the first edition of the Guide. For the current edition, the description of each of the tools from the first edition of the Guide was updated in conjunction with the tool developer or vendor, and a description for each new tool was developed in cooperation with the developer or vendor. However, no additional tools were included in the three stage review process. The method and tool information provided in this guide may not reflect the very latest information. A point of contact is provided for each method and tool so that the reader may obtain further information. 1.7 Organization of this Guide The remainder of this Guide is organized into six chapters (2 through 7). Chapter 2 provides an overview of the application of analytical tools to airline flight safety. The next four chapters provide a description of each tool with one chapter for each of the following areas: Flight Safety Event Reporting and Analysis Systems; Flight Data Monitoring Analysis and Visualization Tools; Human Factors Analysis Tools, and Special Purpose Analytical Tools. Chapter 7 describes various analytical methods. This guide also contains six appendices. Examples of the application of selected tools to airline flight safety analysis are contained in Appendix A. The features and capabilities of the Flight Safety Event Reporting and Analysis Systems are contained in Appendix B. The features and 3
14 capabilities of the Flight Data Monitoring Analysis and Visualization Tools are contained in Appendix C. Information on several methods and tools currently under development is provided in Appendix D. Appendix E contains a list of acronyms used in this guide, and Appendix F contains a feedback form. 1.8 Changes Made to this Edition of the Guide The first edition of the Guide to Methods & Tools for Airline Flight Safety Analysis has been distributed to over 400 aviation safety professionals around the world. Additionally, the Guide is available on the GAIN website at where it can be viewed online or downloaded. Encouraged by the feedback received to the first edition of the Guide, WG B has prepared this second edition of the Guide. This edition of the guide incorporates the following changes: A new section, Application of Analytical Tools to Airline Flight Safety Reorganization of the tool categories to reflect the classification of the tools discussed in the new section on the application of analytical tools to airline flight safety Summaries of some additional methods and tools Deletion of several tools that were no longer supported by their developers or subsequent information suggested were outside the scope of this Guide Some examples showing how selected tools can be applied to airline flight safety analysis Deletion of the detailed information on the instructions and scorecards for the tool review that was performed prior to the first edition. The following methods and tools have been added to the Guide since the first edition: Safety Report Management and Analysis Systems First Launch Safety Report System Descriptive Statistics and Trend Analysis Tools HeliStat Flight Data Monitoring Analysis and Visualization Tools AirFASE CEFA FlightAnalyst FlightTracer Human Factors Analysis Tools Cabin Procedural Investigation Tool Ramp Error Decision Aid Occurrence Investigation and Analysis Tools Investigation Organizer REASON 5 Text/Data Mining and Data Visualization Tools PolyAnalyst Brio Intelligence 6 4
15 Risk Analysis Tools Markov Latent Effects Tool for Organizational and Operational Safety Assessment Quantitative Risk Assessment System RISKMAN WinNUPRA Risk Analysis Methods Fault Hazard Analysis Failure Mode and Effect Analysis The following tools that were included in the first edition of the Guide have been removed from this edition: Safety Report Management and Analysis Systems AIRSAFE Flight Data Monitoring Analysis and Visualization Tools Flight Event Analysis Program Flight Data Replay Analysis System Risk Analysis Event Risk Analysis and Safety Management Cost Benefit Analysis Tools Airbus Service Bulletin Cost Benefit Model Boeing Digital Technologies Cost Model A human factors analysis tool previously known as Computer Assisted Debriefing System (CADS) has been renamed and improved by the vendor and is now listed in this edition of the Guide as ReVision. The examples of the application of tools are included in Appendix A, and are intended to provide a better understanding of how the various tools can be used in airline flight safety management. WG B plans to include similar examples of additional tools in future editions of the Guide. 1.9 Guide Update and Feedback WG B plans to update this guide periodically to include information on additional methods and tools as appropriate. The WG encourages readers to provide feedback regarding their experience with any of the methods and tools contained in the guide and to nominate others for possible inclusion. Suggestions for improving the usefulness of this guide are also requested. A feedback form for this purpose is included in Appendix F. 5
16 2.0 Application of Analytical Tools to Airline Flight Safety Managing flight safety in an airline requires the collection of relevant data on safety-related events and then assessing or analyzing that data. This section provides an overview of the basic concepts involved in applying tools to airline flight safety analysis, first by examining the various types of safety-related data that can be collected and then looking at the types of analysis that can be performed on that data. Fundamental to the safety management process is the reporting and investigation of safety related events. Once an event is reported, an airline has a duty to investigate the event, decide what corrective actions may be necessary, and then track the implementation of those actions. Beyond this immediate response, an effective safety management process will also analyze the data from past events, to monitor trends and identify potential safety hazards that require attention. Thus one role of analytical tools is to support the process by which events are reported, investigated, actions are assigned, and the incident is eventually closed. Another role is to support the analysis of information assembled on past events in order to undertake proactive safety management activities. This Guide describes a wide range of analytical tools that have potential use to support airline flight safety management activities, many of which perform quite specialized functions and some of which require the commitment of considerable resources or the development of particular skills to use effectively. As airlines develop their flight safety management process, they will experience the need for more sophisticated tools and hopefully allocate the resources to support their use. At the same time, it should be noted that many of the analytical tools described in this Guide perform the same or similar functions. Thus airlines will generally selected specific tools in the various categories that they judge best meet their needs. These decisions are likely to be influenced by the size of the airline and the resources available to support the flight safety management process, as well as the experience and analytical skills of the flight safety department staff. As an airline acquires more safety-related information on its operations and gains experience with the use of more fundamental tools, it may find the need to perform more sophisticated analysis and make use of wider array of analytical tools. 2.1 Types of Airline Flight Safety Data The types of data collected as part of the airline flight safety management process is fundamental to the selection of analytical tools. The value provided by specific tools depends on the content and quality of the data being analyzed, and the ability to extract useful information from the safety data that is collected depends on the use of appropriate analytical tools. In general, airline flight safety data fall into three broad categories: reports of incidents, events or hazardous situations that occurred in the course of routine operations and generally submitted by operational personnel; detailed data on flight operational performance collected as part of a flight data monitoring (FDM) or flight operational quality assurance program; and the results of safety audits of organizational units or line operations undertaken by suitably trained and experienced personnel from within the airline or from outside agencies. Although not usually considered part of airline flight safety, most airlines also maintain a reporting and audit system for occupational safety and health issues. While this function is 6
17 typically handled by a separate department, relevant events may get reported through the flight safety event reporting process Occurrence Reports Most airlines have some form of safety event reporting system for flight crew, often termed air safety reports. Increasingly airlines are extending this to safety reports from cabin crew and ground personnel as well. Many airlines also have a parallel system for aircraft maintenance personnel, both to report errors in maintenance procedures as well as airworthiness issues that are uncovered in the course of maintenance or other activities. Some airlines have a separate category of hazard reports that describe potential hazards that operational personnel are concerned about, rather than events that have already occurred. An important issue with such reports is whether they are treated as confidential or shared with regulatory agencies. Practice varies in different countries. The United Kingdom Civil Aviation Authority has a Mandatory Occurrence Reporting System that has been in place for many years and provides well-defined protections for those filing reports. In the United States, through a program termed the Aviation Safety Action Program (ASAP), occurrence reports that meet certain requirements are shared with the Federal Aviation Administration, which in turn has agreed not to impose regulatory penalties on either the airline or the personnel filing the report. Some airlines have begun to supplement air safety reports with a confidential human factors reporting system. These reports are designed to address human factors issues in more detail than is typically found in air safety reports, and are typically handled in greater confidence, since they may well address the performance of other members of the flight or cabin crew. Additionally, in order to encourage such reports by crew members and to facilitate an objective and open exchange of safety related information, it is increasingly accepted that these reports must be handled in a non-punitive fashion by both the operator and regulatory authority (if they are shared with the authority). In summary, an airline may have a formal reporting process for some or all of the following types of occurrence report: Air Safety Report (ASR) Cabin Safety Report (CSR) Ground Damage Report (GDR) Confidential Human Factors Report (HFR) Maintenance Error Report Airworthiness Issues Report Hazard Report Occupational Safety and Health Report (OSHR) In the United States, some of the above types of report (typically ASRs, but efforts are underway to extend this to other categories of event reports) may also be classified as ASAP reports. In other countries some types of reports, or more commonly reports for defined types of events, are considered Mandatory Occurrence Reports (MORs), or a similar terminology, and the information is submitted to the regulatory authorities. 7
18 2.1.2 Digital Flight Data Flight data monitoring, often termed Flight Operational Quality Assurance (FOQA) in the United States, collects and analyzes aircraft operational parameters that are recorded on board the aircraft using flight data recorders or quick access recorders (QARs). These can typically record a large number of aircraft flight parameters several times a second for several days at a time, and are downloaded periodically when the aircraft reaches a suitable station or maintenance base. The resulting data is stored in a large database and analyzed with special purpose software to identify anomalous occurrences that exceed defined thresholds, often termed exceedance events, as well as long-term trends in operations. Once the data has been analyzed to identify any such events and trends, the raw data may or may not be preserved. Until recently, the data for each exceedance event was archived. It is a more common practice now to archive data for entire flights. In almost all cases, the data is de-identified to protect the flight crew, although some airlines have established a gatekeeper process that allows the flight safety analysts to obtain follow-up information from the flight crew involved in a particular event Safety Audits and Assessments Safety audits are designed to uncover organizational problems or systemic practices that could have adverse safety implications. They include audits performed by personnel from another airline engaged in a code-share relationship, safety audits undertaken by regulatory agencies, and internal evaluations undertaken within an airline to ensure that airline safety policies and procedures are being followed or to identify safety issues that need to be addressed. These audits tend to focus on organization units within an airline. Another class of audit involves the structured observation of routine flight operations in which specially trained assessment personnel ride in the cockpit on regular flights. This has come to be termed line-oriented safety assessment (LOSA). 2.2 Types of Tools for Airline Flight Safety Analysis This section discusses seven types of analysis tools that can be applied to manage and analyze the various types of flight safety data Flight Safety Event Reporting and Analysis Systems This category of tool forms the basic safety data management and analysis system that supports the flight safety management process and will generally be the first type of analytical tool that an airline will acquire. There are two broad categories of analytical tools that are used for this purpose. The first category comprises special-purpose tools for managing the flight safety event reporting and investigation process and analyzing the information from airline safety reports. The second category consists of tools used to perform trend and statistical analysis of safety report data, but not necessarily to manage the relevant data Safety Report Management and Analysis Systems These systems typically have the capability to store and display a range of different types of safety reports, including ASRs, CSRs, and even audit reports. They typically provide some capability to support the safety event investigation process, record corrective actions that may be assigned to a specific individual and track the status of those actions. This may include the 8
19 ability to automatically send messages or acknowledgements to those who submitted the report or who have been assigned follow-up actions. They also generally provide some level of trend analysis, with the capability to create charts or generate reports that track the rate of occurrence of specific types of events over time, and the ability to select subsets of the underlying data for analysis or display. Other capabilities that are provided by some systems include functions to support the classification of events into predefined categories, to assign risk levels to each event, and to filter the information in the event report database to identify subsets of previous reports that have common characteristics and extract relevant information. These capabilities are fundamental to effective safety management, since the allow flight safety personnel to identify areas of significant risk and track the long-term effectiveness of corrective actions. Having an effective event classification system is essential to be able to perform meaningful trend analysis and information filtering. Risk assessment of each event allows flight safety management personnel to identify those incidents that pose the most serious threat to operational safety and to focus appropriate attention on high-risk events. Some systems are designed with a different module handling each type of report, so that airlines can add the relevant module as they expand the range of reports that they collect, or to allow for the use of different systems to handle different types of report. The extent to which these systems have built-in capabilities to perform trend analysis, generate charts and graphs, or perform other statistical analysis varies. However, most such systems have limited analytical capabilities beyond fairly simple trend analysis, and many airlines find that it is necessary to use the built-in capabilities to select a subset of the data, which is then exported for use with other analysis tools, such as spreadsheet programs or the more advanced tools discussed below. Trend Analysis and General Statistical Analysis Tools These tools provide capabilities to analyze statistical data exported from safety data management systems and present this information in tables and charts for use in reports and presentations. Most such tools are general-purpose analysis tools, such as spreadsheet programs or statistical analysis packages, and are not typically designed for airline flight safety use, but have powerful analytical capabilities that can be adapted to this application. Other tools may be more specialized and designed to work with specific safety databases or safety report management systems. While these tools are often used in conjunction with special-purpose airline safety report management systems, in some cases they may be used to analyze safety report data that is stored in customized databases maintained using general-purpose database management software. Small airlines may even use spreadsheet or statistical analysis programs to store and manage the information submitted on paper safety reports for subsequent analysis using those tools Flight Data Monitoring Analysis and Visualization Tools The next category of tools that many airlines acquire is an FDM and analysis tool. This is essential to be able to make meaningful use of routine aircraft flight data. Typical FDM programs make use of Quick Access Recorders (QAR) to enable a wide range of parameters to be recorded and enable easy removal of data storage media. Associated costs involved with equipping aircraft with QARs can be beyond some organizations budgets. Alternatively, some FDM programs make use of the limited data set available on the Digital Flight Data Recorders, 9
20 or black boxes, required to be installed on every transport aircraft. In either case, an FDM program requires a significant commitment of resources and staff, to equip and maintain aircraft and QARs (or other suitable recorders), to retrieve and download data, and to process and analyze the data. Most FDM tools allow users to specify thresholds that define exceedances and then identify occurrences where the threshold was exceeded in the data. Many of the advanced tools can now archive all flight data and provide trend analyses of large amounts of data. Most tools allow data to be exported to sophisticated animation packages that provide a graphical representation of a flight or incident in question. This can even extend to an external view of the aircraft, showing the nominal and actual flight paths, an interior cockpit view showing the movement of the controls and current state of the instrument displays, and a tower view which can represent a viewpoint of the aircraft from any fixed location on the ground Human Factors Analysis Tools Once an airline has a good event reporting and analysis system in place and has established a flight data monitoring program, the next area that it may wish to address in a more formal way is the analysis of human factors data. Developing a useful human factors reporting capability first requires a suitable source of data to analyze, such as a confidential HFR program or structured follow-up interviews with people filing event reports. In general it will be very difficult to undertake meaningful human factors analysis of event reports that are not structured to address human factors issues. Among the important factors in developing a human factors reporting system are the issues of privacy and interpretation. Privacy is an issue that most safety organizations have experience with addressing, and most commercial human factors analysis tools have capabilities to protect the information involved. The issue of interpretation is more complex. Human factors observations are often not quantitative, but qualitative, and therefore the use of most data processing and analysis techniques may not be valid. Further, the absence of information on a particular issue does not necessarily mean that the issue is not relevant, only that the person filing the report did not think to mention it. The problem of incomplete reporting of human factors data is typically addressed by having a human factors specialist perform follow-up interviews. However, this means that the cost of implementing and operating a reliable human factors reporting system can be significant. Some of the available human factors analysis tools form part of a human factors reporting system that includes the database management functions needed to support the creation and maintenance of the necessary human factors database. Other tools are designed to work with human factors data that may be stored in separate data management systems, such as flight safety event reporting systems Special Purpose Analytical Tools As an airline acquires more safety data and gains experience in the use of the foregoing tools, it may find that it needs additional analytical capacities to make full use of the information contained in the various safety databases. Some of these tools may be integrated into specific products in the three previous categories, such as the flight safety event reporting and analysis systems, but in general they are stand-alone products that are used in conjunction with data that may have to be exported from the data management systems of the other tools. 10
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WALTHALL — Webster County voters overwhelmingly want supervisors to build a new courthouse in Walthall.
The nonbinding election was held yesterday.
County supervisors say they'll use the non-binding referendum vote to help decide what steps should be taken before construction of any kind begins.
The old courthouse in Walthall suffered heavy damage in a fire in January 2013.
County officials say a private adjuster estimated renovation costs to be around $7 million, but an insurance company only wanted to pay $3 million.


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Kathryn joined Pulse in 2006 and has managed Pulse Allied Health since 2010. During her time at Pulse she's worked across all disciplines within the division and has an in-depth knowledge and understanding of each. Kathryn works closely with her experienced management team and is responsible for the leadership and operational running of the division, including resourcing, recruitment and compliance, sales, management and business development. Candidate and client satisfaction are paramount to Kathryn. She believes that the team's honest and transparent approach is one of the many reasons they receive such positive feedback and are recognised and respected by numerous trusts and organisations. The most rewarding part of Kathryn's role is developing her team and their careers.
Shelley has been at Pulse for over 10 years. During this time she's built and now manages a large recruitment and compliance team, responsible for ensuring candidates and their files meet all framework, contract and recruitment regulations. Shelley's committed to providing clients with highly skilled staff that meet and exceed all mandatory compliance and vetting procedures while making sure her candidates are cleared to work as quickly as possible. The most rewarding part of her role is seeing her team succeed, sharing best practice and helping to increase the number of candidates we have working.
James has 10 years' healthcare recruitment experience, joining Pulse in 2010. He manages a team of consultants and resourcers, identifying new opportunities and implementing ideas and processes.James is passionate and knowledgeable about psychology and talking therapies, his clients and candidates value his advice and he's proud that Pulse is seen as the number one agency provider. James believes in always being available to offer candidates advice and feedback. The most rewarding part of his role is developing the team and sharing in their success and achievements.
Simon has over 10 years' recruitment experience. He joined Pulse in 2009 and quickly became the highest performing consultant to specialise in permanent recruitment. Simon's experience and success saw him promoted to Sales Manager and he's now responsible for the ever growing permanent team. He and the team are focused on building long-term relationships with candidates as well as clients. They work hard to really understand their career and life aspirations as well as their experience, matching them to clients' exact requirements. The most rewarding part of Simon's role is seeing the team succeed and knowing it's a result of their expertise and the excellent service they provide.


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Caimon is a Demon Man digimon and name and design is based around the mythological Caim. He is a kind and gentle digimon with a strong sense of justice. He has greater power than normal champion levels and is even said to have the power to control an army of Demon Man digimon.
Digimon Academy
Main Article: Team DigiSavers
|Level: Champion
|Attribute: Virus
|Type: Demon Man Digimon
|Family(s): Nightmare Soldiers
|Digivolves From: Impmon
|Digivolves To: Baalmon
|Appears In: Fan: Digimon Academy
|Partner(s): Fan: Adam Stele
Hell's Abyss- Uses his sword to open an abyss in the ground to take in the opponent.


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by Michael Krieger, Liberty Blitzkrieg:
In yesterday's post, The Death of Mainstream Media, I noted:
At the end of the day, I have concluded that my focus on Hillary as of late (vs. Trump) has as much to with my disgust for the mainstream media as anything else. To see these organs, which have destroyed this country by keeping the people uninformed for decades, now rally around a sickly, corrupt, oligarch coddling politician as the empire enters the collapse stage is simply too much to stomach…
The only positive thing to happen during this election season is the death of mainstream media. With their insufferable propaganda fully exposed, there is no coming back.
Then today, we learned the following from Gallup:
WASHINGTON, D.C. — Americans' trust and confidence in the mass media "to report the news fully, accurately and fairly" has dropped to its lowest level in Gallup polling history, with 32% saying they have a great deal or fair amount of trust in the media. This is down eight percentage points from last year.
Here's a chart.
If that's not a trend, I don't know what is.
Gallup began asking this question in 1972, and on a yearly basis since 1997. Over the history of the entire trend, Americans' trust and confidence hit its highest point in 1976, at 72%, in the wake of widely lauded examples of investigative journalism regarding Vietnam and the Watergate scandal. After staying in the low to mid-50s through the late 1990s and into the early years of the new century, Americans' trust in the media has fallen slowly and steadily. It has consistently been below a majority level since 2007.
While it is clear Americans' trust in the media has been eroding over time, the election campaign may be the reason that it has fallen so sharply this year. With many Republican leaders and conservative pundits saying Hillary Clinton has received overly positive media attention, while Donald Trump has been receiving unfair or negative attention, this may be the prime reason their relatively low trust in the media has evaporated even more. It is also possible that Republicans think less of the media as a result of Trump's sharp criticisms of the press. Republicans who say they have trust in the media has plummeted to 14% from 32% a year ago. This is easily the lowest confidence among Republicans in 20 years.
Meanwhile, if there is any hope for the future, it can be found here.
Older Americans are more likely than younger Americans to say they trust the media, but trust has declined among both age groups this year. Currently, 26% of those aged 18 to 49 (down from 36% last year) and 38% of those aged 50 and older (down from 45%) say they have a great deal or fair amount of trust in the media.
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