scholarly journals Media Reports as a Source for Monitoring Impact of Influenza on Hospital Care

10.2196/14627 ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. e14627
Author(s):  
Daphne FM Reukers ◽  
Sierk D Marbus ◽  
Hella Smit ◽  
Peter Schneeberger ◽  
Gé Donker ◽  
...  
Keyword(s):  
Content Analysis ◽  
Real Time ◽  
Hospital Admissions ◽  
Monitoring Program ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Suitable Alternative ◽  
Hospital Capacity ◽  
Media Reports ◽  
The Impact

Background The Netherlands, like most European countries, has a robust influenza surveillance system in primary care. However, there is a lack of real-time nationally representative data on hospital admissions for complications of influenza. Anecdotal information about hospital capacity problems during influenza epidemics can, therefore, not be substantiated. Objective The aim of this study was to assess whether media reports could provide relevant information for estimating the impact of influenza on hospital capacity, in the absence of hospital surveillance data. Methods Dutch news articles on influenza in hospitals during the influenza season (week 40 of 2017 until week 20 of 2018) were searched in a Web-based media monitoring program (Coosto). Trends in the number of weekly articles were compared with trends in 5 different influenza surveillance systems. A content analysis was performed on a selection of news articles, and information on the hospital, department, problem, and preventive or response measures was collected. Results The trend in weekly news articles correlated significantly with the trends in all 5 surveillance systems, including severe acute respiratory infections (SARI) surveillance. However, the peak in all 5 surveillance systems preceded the peak in news articles. Content analysis showed hospitals (N=69) had major capacity problems (46/69, 67%), resulting in admission stops (9/46, 20%), postponement of nonurgent surgical procedures (29/46, 63%), or both (8/46, 17%). Only few hospitals reported the use of point-of-care testing (5/69, 7%) or a separate influenza ward (3/69, 4%) to accelerate clinical management, but most resorted to ad hoc crisis management (34/69, 49%). Conclusions Media reports showed that the 2017/2018 influenza epidemic caused serious problems in hospitals throughout the country. However, because of the time lag in media reporting, it is not a suitable alternative for near real-time SARI surveillance. A robust SARI surveillance program is important to inform decision making.

scholarly journals Media Reports as a Source for Monitoring Impact of Influenza on Hospital Care: Qualitative Content Analysis (Preprint)

2019 ◽  
Author(s):  
Daphne FM Reukers ◽  
Sierk D Marbus ◽  
Hella Smit ◽  
Peter Schneeberger ◽  
Gé Donker ◽  
...  
Keyword(s):  
Content Analysis ◽  
Real Time ◽  
Hospital Admissions ◽  
Monitoring Program ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Suitable Alternative ◽  
Hospital Capacity ◽  
Media Reports ◽  
The Impact

BACKGROUND The Netherlands, like most European countries, has a robust influenza surveillance system in primary care. However, there is a lack of real-time nationally representative data on hospital admissions for complications of influenza. Anecdotal information about hospital capacity problems during influenza epidemics can, therefore, not be substantiated. OBJECTIVE The aim of this study was to assess whether media reports could provide relevant information for estimating the impact of influenza on hospital capacity, in the absence of hospital surveillance data. METHODS Dutch news articles on influenza in hospitals during the influenza season (week 40 of 2017 until week 20 of 2018) were searched in a Web-based media monitoring program (Coosto). Trends in the number of weekly articles were compared with trends in 5 different influenza surveillance systems. A content analysis was performed on a selection of news articles, and information on the hospital, department, problem, and preventive or response measures was collected. RESULTS The trend in weekly news articles correlated significantly with the trends in all 5 surveillance systems, including severe acute respiratory infections (SARI) surveillance. However, the peak in all 5 surveillance systems preceded the peak in news articles. Content analysis showed hospitals (N=69) had major capacity problems (46/69, 67%), resulting in admission stops (9/46, 20%), postponement of nonurgent surgical procedures (29/46, 63%), or both (8/46, 17%). Only few hospitals reported the use of point-of-care testing (5/69, 7%) or a separate influenza ward (3/69, 4%) to accelerate clinical management, but most resorted to ad hoc crisis management (34/69, 49%). CONCLUSIONS Media reports showed that the 2017/2018 influenza epidemic caused serious problems in hospitals throughout the country. However, because of the time lag in media reporting, it is not a suitable alternative for near real-time SARI surveillance. A robust SARI surveillance program is important to inform decision making.

scholarly journals Real-time estimation of the influenza-associated excess mortality in Hong Kong

2019 ◽  
Vol 147 ◽  
Author(s):  
Jessica Y. Wong ◽  
Edward Goldstein ◽  
Vicky J. Fang ◽  
Benjamin J. Cowling ◽  
Peng Wu
Keyword(s):  
Hong Kong ◽  
Real Time ◽  
Excess Mortality ◽  
Time Estimation ◽  
Surveillance Data ◽  
Control Measures ◽  
Influenza Surveillance ◽  
Mortality Data ◽  
Real Time Estimation ◽  
The Impact

Abstract Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

scholarly journals Characteristics of hospitalizations with influenza diagnosis, France, 2012-2017

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
M Pivette ◽  
V de Lauzun ◽  
N Nicolay ◽  
A Scanff ◽  
B Hubert
Keyword(s):  
Length Of Stay ◽  
Diagnosis Related Groups ◽  
Laboratory Data ◽  
Incidence Rates ◽  
H3n2 Virus ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Age Group ◽  
Hospital System ◽  
The Impact

Abstract Background Seasonal influenza surveillance in France is based on several data sources (ambulatory data, emergency department and intensive care unit (ICU) admissions, laboratory data, mortality). However, the data do not provide a complete measure of the impact of the epidemics on the hospital system. The objective of the study was to describe the characteristics of influenza hospitalizations from the French national hospital discharge database (PMSI) between 2012 and 2017 and to precise the burden of influenza by age group and by season. Methods All hospitalizations in metropolitan France with at least one ICD-10 code related to influenza (J09, J10, J11) as a principal, related or associated diagnosis between 1 July 2012 to 30 June 2017 were extracted from the PMSI. For each season, the total number of hospitalizations, admissions to ICU, incidence and lethality rates, lengths of stay and classification in diagnosis-related groups were described by age group. Results During the 5 seasons, 91 255 hospitalizations with an influenza-diagnosis were identified. The incidence varied significantly between seasons, from 12.7/100 000 in 2013-2014 to 45.9/100 000 in 2016-2017. A high number of cases was observed in elderlies in 2014-2015 and 2016-2017, marked by the circulation of A (H3N2) virus. The proportion of hospitalizations with an admission in ICU was 10%, and was higher in the 40-79 age group (19%). Lethality increased steadily with age, from 0.5% under 20 years to 10% in 80 years and older. Length of stay also increased with age. Significant regional disparities were observed, with higher incidence rates in South-Eastern France each season. Conclusions The analysis of influenza hospitalizations from the PMSI provides important elements on influenza burden, not available in the current surveillance systems. An annual analysis, stratified by age group, would provide an indicator of the impact of the epidemics on hospital system at the end of each influenza season. Key messages Important influenza incidence variations were observed between seasons by age groups. Severity and impact of influenza (mortality, ICU, length of stay) varied significantly by age group.

scholarly journals Implementation of Real-Time Laboratory-Based Influenza Surveillance System, Thailand

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Phunlerd Piyaraj ◽  
Nira Pet-hoi ◽  
Chaiyos Kunanusont ◽  
Supanee Sangiamsak ◽  
Somsak Wankijcharoen ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Influenza Virus ◽  
Real Time ◽  
Surveillance System ◽  
Influenza A ◽  
Medical Services ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Private Hospitals ◽  
Influenza A H1n1

Objective: We describe the Bangkok Dusit Medical Services Surveillance System (BDMS-SS) and use of surveillance efforts for influenza as an example of surveillance capability in near real-time among a network of 20 hospitals in the Bangkok Dusit Medical Services group (BDMS).Introduction: Influenza is one of the significant causes of morbidity and mortality globally. Previous studies have demonstrated the benefit of laboratory surveillance and its capability to accurately detect influenza outbreaks earlier than syndromic surveillance.1-3 Current laboratory surveillance has an approximately 4-week lag due to laboratory test turn-around time, data collection and data analysis. As part of strengthening influenza virus surveillance in response to the 2009 influenza A (H1N1) pandemic, the real-time laboratory-based influenza surveillance system, the Bangkok Dusit Medical Services Surveillance System (BDMS-SS), was developed in 2010 by the Bangkok Health Research Center (BHRC). The primary objective of the BDMS-SS is to alert relevant stakeholders on the incidence trends of the influenza virus. Type-specific results along with patient demographic and geographic information were available to physicians and uploaded for public health awareness within 24 hours after patient nasopharyngeal swab was collected. This system advances early warning and supports better decision making during infectious disease events.2 The BDMS-SS operates all year round collecting results of all routinely tested respiratory clinical samples from participating hospitals from the largest group of private hospitals in Thailand.Methods: The BDMS has a comprehensive network of laboratory, epidemiologic, and early warning surveillance systems which represents the largest body of information from private hospitals across Thailand. Hospitals and clinical laboratories have deployed automatic reporting mechanisms since 2010 and have effectively improved timeliness of laboratory data reporting. In April 2017, the capacity of near real-time influenza surveillance in BDMS was found to have a demonstrated and sustainable capability.Results: From October 2010 to April 2017, a total of 482,789 subjects were tested and 86,110 (17.8%) cases of influenza were identified. Of those who tested positive for influenza they were aged <2 years old (4.6%), 2-4 year old (10.9%), 5-14 years old (29.8%), 15-49 years old (41.9%), 50-64 years old (8.3%) and >65 years old (3.7%). Approximately 50% of subjects were male and female. Of these, 40,552 (47.0%) were influenza type B, 31,412 (36.4%) were influenza A unspecified subtype, 6,181 (7.2%) were influenza A H1N1, 4,001 (4.6%) were influenza A H3N2, 3,835 (4.4%) were influenza A seasonal and 196 (0.4%) were respiratory syncytial virus (RSV).The number of influenza-positive specimens reported by the real-time influenza surveillance system were from week 40, 2015 to week 39, 2016. A total of 117,867 subjects were tested and 17,572 (14.91%) cases tested positive for the influenza virus (Figure 1). Based on the long-term monitoring of collected information, this system can delineate the epidemiologic pattern of circulating viruses in near real-time manner, which clearly shows annual peaks in winter dominated by influenza subtype B in 2015-1016 season. This surveillance system helps to provide near real-time reporting, enabling rapid implementation of control measures for influenza outbreaks.Conclusions: This surveillance system was the first real-time, daily reporting surveillance system to report on the largest data base of private hospitals in Thailand and provides timely reports and feedback to all stakeholders. It provides an important supplement to the routine influenza surveillance system in Thailand. This illustrates a high level of awareness and willingness among the BDMS hospital network to report emerging infectious diseases, and highlights the robust and sensitive nature of BDMS’s surveillance system. This system demonstrates the flexibility of the surveillance systems in BDMS to evaluate to emerging infectious disease and major communicable diseases. Through participation in the Thailand influenza surveillance network, BDMS can more actively collaborate with national counterparts and use its expertise to strengthen global and regional surveillance capacity in Southeast Asia, in order to secure advances for a world safe and secure from infectious disease. Furthermore, this system can be quickly adapted and used to monitor future influenzas pandemics and other major outbreaks of respiratory infectious disease, including novel pathogens.

Real-Time Multimedia Policy Analysis of Using Video and Audio Recognition from Radio, TV, and User-Generated Content

2014 ◽  
pp. 248-271
Author(s):  
T. Netousek ◽  
H. Gugumuk ◽  
C. Beleznai
Keyword(s):  
Content Analysis ◽  
Real Time ◽  
Multimedia Data ◽  
Multimedia Content ◽  
Use Case ◽  
Multimedia Content Analysis ◽  
Quality Of Living ◽  
Video And Audio ◽  
Changes Over Time ◽  
The Impact

Real-Time Multimedia Content Analysis opens up exciting possibilities for accessing opinion-oriented arguments about regulations and dynamic policy changes. In this chapter, the authors present common methodologies and core technologies to analyse multimedia content from a practitioner's viewpoint, highlighting their primary impact, best practices, current limitations, and future trends. They illustrate the impact of multimedia content analysis within a governance-oriented applied context based on two use cases: one use case addresses the task regarding the improvement of certain KPIs (Key Performance Indicators) for the quality of living in a city by performing real-time analytics of TV news in order to assess public opinion and how it changes over time with respect to certain events or incidents; the second use case addresses search and data exploration within multimedia data to reveal certain correlations across space and time in order to retrieve meaningful information from unstructured sources of data, information which can effectively contribute to meeting the concrete needs of citizens.

scholarly journals The use of syndromic surveillance to monitor the incidence of arthropod bites requiring healthcare in England, 2000–2013: a retrospective ecological study

2016 ◽  
Vol 144 (11) ◽  
pp. 2251-2259 ◽  
Author(s):  
S. NEWITT ◽  
A. J. ELLIOT ◽  
R. MORBEY ◽  
H. DURNALL ◽  
M. E. PIETZSCH ◽  
...  
Keyword(s):  
Climate Change ◽  
Real Time ◽  
Syndromic Surveillance ◽  
Ecological Study ◽  
Health Impact ◽  
Extreme Weather Events ◽  
Surveillance Systems ◽  
Out Of Hours ◽  
Baseline Incidence ◽  
The Impact

SUMMARYClimate change experts predict the number of nuisance-biting arthropods in England will increase but there is currently no known surveillance system in place to monitor or assess the public health impact of arthropod bites. This retrospective ecological study utilized arthropod bites requiring healthcare from five national real-time syndromic surveillance systems monitoring general practitioner (GP) consultations (in-hours and out-of-hours), emergency department (ED) attendances and telephone calls to remote advice services to determine baseline incidence in England between 2000 and 2013 and to assess the association between arthropod bites and temperature. During summer months (weeks 20–40) we estimated that arthropod bites contribute a weekly median of ~4000 GP consultations, 750 calls to remote advice services, 700 ED and 1300 GP out-of-hours attendances. In all systems, incidence was highest during summer months compared to the rest of the year. Arthropod bites were positively associated with temperature with incidence rate ratios (IRRs) that ranged between systems from 1·03 [95% confidence interval (CI) 1·01–1·06] to 1·14 (95% CI 1·11–1·16). Using syndromic surveillance systems we have established and described baseline incidence of arthropod bites and this can now be monitored routinely in real time to assess the impact of extreme weather events and climate change.

scholarly journals Impact of influenza vaccination programmes among the elderly population on primary care, Portugal, Spain and the Netherlands: 2015/16 to 2017/18 influenza seasons

2019 ◽  
Vol 24 (45) ◽  
Author(s):  
Ausenda Machado ◽  
Clara Mazagatos ◽  
Frederika Dijkstra ◽  
Irina Kislaya ◽  
Alin Gherasim ◽  
...  
Keyword(s):  
Primary Care ◽  
The Netherlands ◽  
Influenza Vaccine ◽  
Influenza Vaccination ◽  
Vaccination Programme ◽  
Vaccine Coverage ◽  
The Elderly ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
The Impact

Background To increase the acceptability of influenza vaccine, it is important to quantify the overall benefits of the vaccination programme. Aim To assess the impact of influenza vaccination in Portugal, Spain and the Netherlands, we estimated the number of medically attended influenza-confirmed cases (MAICC) in primary care averted in the seasons 2015/16 to 2017/18 among those ≥ 65 years. Methods We used an ecological approach to estimate vaccination impact. We compared the number of observed MAICC (n) to the estimated number that would have occurred without the vaccination programme (N). To estimate N, we used: (i) MAICC estimated from influenza surveillance systems, (ii) vaccine coverage, (iii) pooled (sub)type-specific influenza vaccine effectiveness estimates for seasons 2015/16 to 2017/18, weighted by the proportion of virus circulation in each season and country. We estimated the number of MAICC averted (NAE) and the prevented fraction (PF) by the vaccination programme. Results The annual average of NAE in the population ≥ 65 years was 33, 58 and 204 MAICC per 100,000 in Portugal, Spain and the Netherlands, respectively. On average, influenza vaccination prevented 10.7%, 10.9% and 14.2% of potential influenza MAICC each season in these countries. The lowest PF was in 2016/17 (4.9–6.1%) with an NAE ranging from 24 to 69 per 100,000. Conclusions Our results suggest that influenza vaccination programmes reduced a substantial number of MAICC. Together with studies on hospitalisations and deaths averted by influenza vaccination programmes, this will contribute to the evaluation of the impact of vaccination strategies and strengthen public health communication.

Metropolitan Councils

2019 ◽  
pp. 252-270
Author(s):  
Innocent Chirisa ◽  
Gift Mhlanga ◽  
Buhle Dube ◽  
Liaison Mukarwi
Keyword(s):  
Content Analysis ◽  
Regional Development ◽  
Regional Planning ◽  
New Paradigm ◽  
Local Authorities ◽  
Urban And Regional Planning ◽  
Media Reports ◽  
Urban And Regional Development ◽  
Impact Of Urbanization ◽  
The Impact

Although no traction in the envisioned direction has been observed since the adoption of the concept of “metropolitan councils” in the Constitution of Zimbabwe (Amendment No. 20 of 2013), there is much potential, scope, and sense in the idea to spur urban and regional development under the impact of urbanization in the country and beyond. In the Constitution of Zimbabwe, Section 269, Harare and Bulawayo Metropolitan are the only regions due for metropolitan councils. The present study seeks to unravel three critical aspects surrounding the concept metropolitan councils as a new paradigm for urban and regional planning and development in Zimbabwe. The study is based on archival methods, which make use of existing documents including the Constitution of Zimbabwe amendment No.20, media reports, reports and plans, by local authorities, among others. Textual and content analysis have been applied to decipher and pigeonhole into different issues towards clustering them into meaningful themes, hence molding the debate of the chapter.

scholarly journals The impact of social and physical distancing measures on COVID-19 activity in England: findings from a multi-tiered surveillance system

2021 ◽  
Vol 26 (11) ◽  
Author(s):  
Jamie Lopez Bernal ◽  
Mary A Sinnathamby ◽  
Suzanne Elgohari ◽  
Hongxin Zhao ◽  
Chinelo Obi ◽  
...  
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Web Search ◽  
Healthcare Services ◽  
Onset Date ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Population Surveys ◽  
Levels Of Care ◽  
The Impact

Background A multi-tiered surveillance system based on influenza surveillance was adopted in the United Kingdom in the early stages of the coronavirus disease (COVID-19) epidemic to monitor different stages of the disease. Mandatory social and physical distancing measures (SPDM) were introduced on 23 March 2020 to attempt to limit transmission. Aim To describe the impact of SPDM on COVID-19 activity as detected through the different surveillance systems. Methods Data from national population surveys, web-based indicators, syndromic surveillance, sentinel swabbing, respiratory outbreaks, secondary care admissions and mortality indicators from the start of the epidemic to week 18 2020 were used to identify the timing of peaks in surveillance indicators relative to the introduction of SPDM. This timing was compared with median time from symptom onset to different stages of illness and levels of care or interactions with healthcare services. Results The impact of SPDM was detected within 1 week through population surveys, web search indicators and sentinel swabbing reported by onset date. There were detectable impacts on syndromic surveillance indicators for difficulty breathing, influenza-like illness and COVID-19 coding at 2, 7 and 12 days respectively, hospitalisations and critical care admissions (both 12 days), laboratory positivity (14 days), deaths (17 days) and nursing home outbreaks (4 weeks). Conclusion The impact of SPDM on COVID-19 activity was detectable within 1 week through community surveillance indicators, highlighting their importance in early detection of changes in activity. Community swabbing surveillance may be increasingly important as a specific indicator, should circulation of seasonal respiratory viruses increase.

Model predictions and evaluation of possible control strategies for the 2009 A/H1N1v influenza pandemic in Italy

2010 ◽  
Vol 139 (1) ◽  
pp. 68-79 ◽  
Author(s):  
M. AJELLI ◽  
S. MERLER ◽  
A. PUGLIESE ◽  
C. RIZZO
Keyword(s):  
Control Strategies ◽  
Influenza Pandemic ◽  
Mitigation Measures ◽  
Epidemiological Surveillance ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Policy Makers ◽  
Modelling Analysis ◽  
Model Predictions ◽  
The Impact

SUMMARYWe describe the real-time modelling analysis conducted in Italy during the early phases of the 2009 A/H1N1v influenza pandemic in order to estimate the impact of the pandemic and of the related mitigation measures implemented. Results are presented along with a comparison with epidemiological surveillance data which subsequently became available. Simulated epidemics were fitted to the estimated number of influenza-like syndromes collected within the Italian sentinel surveillance systems and showed good agreement with the timing of the observed epidemic. On the basis of the model predictions, we estimated the underreporting factor of the influenza surveillance system to be in the range 3·3–3·7 depending on the scenario considered. Model prediction suggested that the epidemic would peak in early November. These predictions have proved to be a valuable support for public health policy-makers in planning interventions for mitigating the spread of the pandemic.

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