Medical technology has seen impressive success in the past decades, generating novel clinical data at an unexpected rate. Even though numerous physiological models have been developed, their clinical application is limited. The major reason for this lies in the difficulty of finding and interpreting the model parameters, because most problems are ill-posed and do not have unique solutions. On the one hand the reason for this lies in the information deficit of the data, which is the result of finite measurement precision and contamination by artifacts and noise and on the other hand on data mining procedures that cannot sufficiently treat the statistical nature of the data. Within this work we introduce a population based parameter estimation method that is able to reveal structural parameters that can be used for patient-specific modeling. In contrast to traditional approaches this method produces a distribution of physiologically interpretable models defined by patient-specific parameters and model states. On the basis of these models we identify disease specific classes that correspond to clinical diagnoses, which enable a probabilistic assessment of human health condition on the basis of a broad patient population. In an ongoing work this technique is used to identify arterial stenosis and aneurisms from anomalous patterns in parameter space. We think that the information-based approach will provide a useful link between mathematical models and clinical diagnoses and that it will become a constituent in medicine in near future.
{"title":"Statistical parameter estimation and signal classification in cardiovascular diagnosis","authors":"S. Bernhard, K. A. Zoukra, C. Schütte","doi":"10.2495/EHR110401","DOIUrl":"https://doi.org/10.2495/EHR110401","url":null,"abstract":"Medical technology has seen impressive success in the past decades, generating novel clinical data at an unexpected rate. Even though numerous physiological models have been developed, their clinical application is limited. The major reason for this lies in the difficulty of finding and interpreting the model parameters, because most problems are ill-posed and do not have unique solutions. On the one hand the reason for this lies in the information deficit of the data, which is the result of finite measurement precision and contamination by artifacts and noise and on the other hand on data mining procedures that cannot sufficiently treat the statistical nature of the data. Within this work we introduce a population based parameter estimation method that is able to reveal structural parameters that can be used for patient-specific modeling. In contrast to traditional approaches this method produces a distribution of physiologically interpretable models defined by patient-specific parameters and model states. On the basis of these models we identify disease specific classes that correspond to clinical diagnoses, which enable a probabilistic assessment of human health condition on the basis of a broad patient population. In an ongoing work this technique is used to identify arterial stenosis and aneurisms from anomalous patterns in parameter space. We think that the information-based approach will provide a useful link between mathematical models and clinical diagnoses and that it will become a constituent in medicine in near future.","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123617453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Popov, H. Lauzon, M. N. Haque, F. Leroi, R. Gospavic
Food-borne listeriosis, caused by Listeria monocytogenes (Lm), is relatively rare but the relatively high rate of fatality (20–30%) compared to other food-borne microbial pathogens such as Salmonella makes it a serious disease. The foodstuff is recognised as the primary route of transmission for human exposure. A wide variety of food or raw material may become contaminated with Lm but the majority of listeriosis cases are related to ready-to-eat (RTE) food. The important factor related to food-borne listeriosis is that Lm can grow under low (refrigerated) temperatures when given sufficient time. Therefore, RTE products with long shelf life are under risk with respect to growth of Lm to critical concentrations. A stochastic model for the growth of Lm with the inhibiting effect of lactic acid bacteria (LAB) in cold smoked salmon (CSS) was developed. An existing deterministic model for the growth of Lm was adapted by adding the Winner stochastic process in order to simulate the growth of Lm. The Poisson distribution is used to represent the initial count (occurrence) of Lm. A deterministic model for growth of LAB is used and the inhibiting effects of Lm and LAB on each other are taken into account. The Beta-Poisson model is used for estimating the dose response. The model has been tested during field trials with CSS performed in August 2010. The salmon was slaughtered in Norway and transported to France where it was processed. The model, implemented within the QMRA module, indicated that growth of Lm would occur in the CSS samples investigated. However, the
{"title":"Evaluation of QMRA performance for Listeria monocytogenes in cold smoked salmon","authors":"V. Popov, H. Lauzon, M. N. Haque, F. Leroi, R. Gospavic","doi":"10.2495/EHR110181","DOIUrl":"https://doi.org/10.2495/EHR110181","url":null,"abstract":"Food-borne listeriosis, caused by Listeria monocytogenes (Lm), is relatively rare but the relatively high rate of fatality (20–30%) compared to other food-borne microbial pathogens such as Salmonella makes it a serious disease. The foodstuff is recognised as the primary route of transmission for human exposure. A wide variety of food or raw material may become contaminated with Lm but the majority of listeriosis cases are related to ready-to-eat (RTE) food. The important factor related to food-borne listeriosis is that Lm can grow under low (refrigerated) temperatures when given sufficient time. Therefore, RTE products with long shelf life are under risk with respect to growth of Lm to critical concentrations. A stochastic model for the growth of Lm with the inhibiting effect of lactic acid bacteria (LAB) in cold smoked salmon (CSS) was developed. An existing deterministic model for the growth of Lm was adapted by adding the Winner stochastic process in order to simulate the growth of Lm. The Poisson distribution is used to represent the initial count (occurrence) of Lm. A deterministic model for growth of LAB is used and the inhibiting effects of Lm and LAB on each other are taken into account. The Beta-Poisson model is used for estimating the dose response. The model has been tested during field trials with CSS performed in August 2010. The salmon was slaughtered in Norway and transported to France where it was processed. The model, implemented within the QMRA module, indicated that growth of Lm would occur in the CSS samples investigated. However, the","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125190703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Eglīte, I. Vanadziņš, L. Matisāne, M. Bake, D. Sprūdža, Ž. Martinsone, I. Mārtiņsone, J. Reste, J. Cīrule, A. Seile
The aim of study was to analyse work conditions and occupational morbidity in Latvia during a 15-year period for recommendations to employment policy programmes. The study included the analysis of the database of occupational risk factor measurements in more than 7000 enterprises and companies performed in period 1995–2010 by the Laboratory of Hygiene and Occupational Diseases of the Institute of Occupational Safety and Environmental Health of Riga Stradins University. The analysis of registered occupational diseases according to the data from the Latvian State Registry of Occupational diseases run by the Centre of Occupational and Radiation Medicine of Pauls Stradins Clinical University Hospital for the same period was performed. Occupational diseases in Latvia are diagnosed and coded in accordance with the International Classification of Diseases. Results of measurements showed that for one third of measured occupational risk factors values exceeded recommended limits. The traditional work risk factors (chemical, physical, biological etc.) have been partly replaced by new risks (ergonomic and psychosocial factors). The results of the study indicated that the following enterprises form a major risk group of non-compliance with legislation regarding occupational health and safety: small enterprises; enterprises of private and non-governmental sectors; enterprises of different industries (construction, metal processing and wood processing). The number of firstly diagnosed occupational diseases and patients has gradually increased. The total number of firstly diagnosed and registered occupational patients per 100,000 employees was 11.2 in 1995 and 140.5 in 2009. The structure of
{"title":"Work conditions and occupational morbidity in Latvia","authors":"M. Eglīte, I. Vanadziņš, L. Matisāne, M. Bake, D. Sprūdža, Ž. Martinsone, I. Mārtiņsone, J. Reste, J. Cīrule, A. Seile","doi":"10.2495/EHR110201","DOIUrl":"https://doi.org/10.2495/EHR110201","url":null,"abstract":"The aim of study was to analyse work conditions and occupational morbidity in Latvia during a 15-year period for recommendations to employment policy programmes. The study included the analysis of the database of occupational risk factor measurements in more than 7000 enterprises and companies performed in period 1995–2010 by the Laboratory of Hygiene and Occupational Diseases of the Institute of Occupational Safety and Environmental Health of Riga Stradins University. The analysis of registered occupational diseases according to the data from the Latvian State Registry of Occupational diseases run by the Centre of Occupational and Radiation Medicine of Pauls Stradins Clinical University Hospital for the same period was performed. Occupational diseases in Latvia are diagnosed and coded in accordance with the International Classification of Diseases. Results of measurements showed that for one third of measured occupational risk factors values exceeded recommended limits. The traditional work risk factors (chemical, physical, biological etc.) have been partly replaced by new risks (ergonomic and psychosocial factors). The results of the study indicated that the following enterprises form a major risk group of non-compliance with legislation regarding occupational health and safety: small enterprises; enterprises of private and non-governmental sectors; enterprises of different industries (construction, metal processing and wood processing). The number of firstly diagnosed occupational diseases and patients has gradually increased. The total number of firstly diagnosed and registered occupational patients per 100,000 employees was 11.2 in 1995 and 140.5 in 2009. The structure of","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129512683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. K. Macpherson, S. Neti, M. Averbach, P. A. Macpherson, C. Chutakositkanon
There has been considerable research and speculation that if the brain is under stress then it could affect the heart and lead to heart disease. The purpose of the present research was to examine the inverse problem of whether the heart could potentially cause undesirable reactions in the brain. One method to evaluate for underlying coronary artery disease is to perform stress testing. Often, myocardial stress is achieved by the patient walking on a treadmill while being monitored. In patients who are unable to exercise, pharmacologic stress testing is performed, either with vasodilatory agents (e.g. adenosine) or dobutamine, which is a pro-inotropic and chronotropic drug. During dobutamine infusion, the heart rate increases, but there is a negligible increase in blood pressure. Five patients who were undergoing dobutamine stress testing were instrumented with the standard 19 electrode EEG sensors to record brain activity. It was found that all patients showed resonance in the brain activity at frequencies around 10Hz. The signal strengths and the electrode locations where a resonance varied between patients. The one location where all of the patients showed resonance was at T5-O1; towards the back of the head and for this location, all patients showed an EEG resonance frequency at approximately 10Hz. Further analysis of the EEG data is needed to appreciate the consequences of this neurocardilogical phenomenon.
{"title":"Dominant EEG frequencies of patients undergoing dobutamine stress test","authors":"A. K. Macpherson, S. Neti, M. Averbach, P. A. Macpherson, C. Chutakositkanon","doi":"10.2495/EHR110281","DOIUrl":"https://doi.org/10.2495/EHR110281","url":null,"abstract":"There has been considerable research and speculation that if the brain is under stress then it could affect the heart and lead to heart disease. The purpose of the present research was to examine the inverse problem of whether the heart could potentially cause undesirable reactions in the brain. One method to evaluate for underlying coronary artery disease is to perform stress testing. Often, myocardial stress is achieved by the patient walking on a treadmill while being monitored. In patients who are unable to exercise, pharmacologic stress testing is performed, either with vasodilatory agents (e.g. adenosine) or dobutamine, which is a pro-inotropic and chronotropic drug. During dobutamine infusion, the heart rate increases, but there is a negligible increase in blood pressure. Five patients who were undergoing dobutamine stress testing were instrumented with the standard 19 electrode EEG sensors to record brain activity. It was found that all patients showed resonance in the brain activity at frequencies around 10Hz. The signal strengths and the electrode locations where a resonance varied between patients. The one location where all of the patients showed resonance was at T5-O1; towards the back of the head and for this location, all patients showed an EEG resonance frequency at approximately 10Hz. Further analysis of the EEG data is needed to appreciate the consequences of this neurocardilogical phenomenon.","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125383043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A mathematical model of the pregnant myometrial fasciculus is proposed. It is based on real anatomical and physiological data of its structure and function. The model reproduces electromechanical wave phenomena in the myometrium under normal physiological conditions and after application of different classes of
{"title":"A dynamic model of the pregnant myometrial fasciculus","authors":"R. Miftahof, N. Akhmadeev","doi":"10.2495/EHR110341","DOIUrl":"https://doi.org/10.2495/EHR110341","url":null,"abstract":"A mathematical model of the pregnant myometrial fasciculus is proposed. It is based on real anatomical and physiological data of its structure and function. The model reproduces electromechanical wave phenomena in the myometrium under normal physiological conditions and after application of different classes of","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114983846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ground-level ozone (O3) is one of the most harmful air pollutants due to its adverse effects on human health, agricultural crops, biodiversity and materials. Ozone is a secondary air pollutant and interacts with meteorological variables as well as with many other air pollutants such as nitric oxide (NO), nitrogen dioxide (NO2), particles (PM2.5), and carbon monoxide (CO). This paper intends to investigate the relationship of ozone with these air pollutants and lagged ozone (previous day ozone) at a roadside monitoring site in Leeds UK. A quantile regression approach has been applied, which is suitable for the non-normal ozone distribution and capable of handling nonlinearities in the associations of ozone with its predictors; as it examines the entire distribution of the variables rather than a single measure of central tendency (mean or median). Our results show that lagged ozone has positive, whereas NO, NO2 and CO have negative associations with ozone. PM2.5 is negatively correlated with ozone at lower quantiles (below 0.6) and the relationship becomes positive at upper quantiles (0.6 and above), perhaps indicating more complex interactions. Also, it is shown that the effect of explanatory variables on ozone concentrations is a function of quantiles and hence the behaviour and interaction of the covariates with ozone change at different regimes of ozone concentrations, information which is normally hidden in the traditional regression models. Further statistical analysis demonstrates that for some air pollutants the nature of relationship (negative or positive) between ozone and its predictors remains unchanged and only the strength changes, for others nature and strength both change at different quantiles. The study explores the impacts of traffic-related air pollutants on ground level ozone concentrations and suggests the use of quantile regression
{"title":"An investigation into the association of ozone with traffic-related air pollutants using a quantile regression approach","authors":"S. Munir, Haibo Chen, K. Ropkins","doi":"10.2495/EHR110031","DOIUrl":"https://doi.org/10.2495/EHR110031","url":null,"abstract":"Ground-level ozone (O3) is one of the most harmful air pollutants due to its adverse effects on human health, agricultural crops, biodiversity and materials. Ozone is a secondary air pollutant and interacts with meteorological variables as well as with many other air pollutants such as nitric oxide (NO), nitrogen dioxide (NO2), particles (PM2.5), and carbon monoxide (CO). This paper intends to investigate the relationship of ozone with these air pollutants and lagged ozone (previous day ozone) at a roadside monitoring site in Leeds UK. A quantile regression approach has been applied, which is suitable for the non-normal ozone distribution and capable of handling nonlinearities in the associations of ozone with its predictors; as it examines the entire distribution of the variables rather than a single measure of central tendency (mean or median). Our results show that lagged ozone has positive, whereas NO, NO2 and CO have negative associations with ozone. PM2.5 is negatively correlated with ozone at lower quantiles (below 0.6) and the relationship becomes positive at upper quantiles (0.6 and above), perhaps indicating more complex interactions. Also, it is shown that the effect of explanatory variables on ozone concentrations is a function of quantiles and hence the behaviour and interaction of the covariates with ozone change at different regimes of ozone concentrations, information which is normally hidden in the traditional regression models. Further statistical analysis demonstrates that for some air pollutants the nature of relationship (negative or positive) between ozone and its predictors remains unchanged and only the strength changes, for others nature and strength both change at different quantiles. The study explores the impacts of traffic-related air pollutants on ground level ozone concentrations and suggests the use of quantile regression","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129987843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Departamento de Petrologia e Metalogenia Instituto de Geociencias e Ciencias Exatas-UNESP, Rio Claro
地球科学和精确科学研究所岩石学和成矿系- unesp，里约热内卢Claro
{"title":"Groundwater quality on a waste disposal area due to sand mining activities in São Paulo State, Brazil","authors":"D. Bonotto, E. G. Oliveira","doi":"10.2495/EHR110251","DOIUrl":"https://doi.org/10.2495/EHR110251","url":null,"abstract":"Departamento de Petrologia e Metalogenia Instituto de Geociencias e Ciencias Exatas-UNESP, Rio Claro","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133052724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A descriptive study was developed to monitor air fungal contamination in one Portuguese maternity. Sixty air samples were collected through impaction method. Air sampling was performed in food storage facilities, kitchen, food plating, canteen, pharmacy, sterilization areas, genecology wards, intensive care unit, operating rooms, urgency and also, outside premises, since this was the place regarded as reference. Besides air samples, forty three samples were collected by swabbing the surfaces using a 10 by 10 cm square stencil. Simultaneously, temperature, relative humidity and particles counting (PM10) were registered. Twenty three species of fungi were identified in air, being the two most commonly isolated the genera Penicillium (41,5%) and Cladosporium (28,4%). Regarding yeasts, only Rhodotorula sp. (45,2%), Trichosporon mucoides (51,6%) and Cryptococcus neoformans (3,2%) were found. Thirteen species of fungi were identified in surfaces, being the most frequent the Penicillium genus (91,6%). Concerning yeasts found in surfaces, four species were identified being Rhodotorula sp. (29,1%) the most frequent. There was no coincidence between prevailing genera indoors and outside premises. Moreover, some places presented fungal species different from the ones isolated outside. In the inside environment, Aspergillus species were isolated in air and surfaces. There was no significant relationship (p>0,05) between fungal contamination and the studied environmental variables.
{"title":"Assessment of fungal contamination in a Portuguese maternity unit","authors":"C. Viegas, R. Sabino, C. Veríssimo, L. Rosado","doi":"10.2495/EHR110121","DOIUrl":"https://doi.org/10.2495/EHR110121","url":null,"abstract":"A descriptive study was developed to monitor air fungal contamination in one Portuguese maternity. Sixty air samples were collected through impaction method. Air sampling was performed in food storage facilities, kitchen, food plating, canteen, pharmacy, sterilization areas, genecology wards, intensive care unit, operating rooms, urgency and also, outside premises, since this was the place regarded as reference. Besides air samples, forty three samples were collected by swabbing the surfaces using a 10 by 10 cm square stencil. Simultaneously, temperature, relative humidity and particles counting (PM10) were registered. Twenty three species of fungi were identified in air, being the two most commonly isolated the genera Penicillium (41,5%) and Cladosporium (28,4%). Regarding yeasts, only Rhodotorula sp. (45,2%), Trichosporon mucoides (51,6%) and Cryptococcus neoformans (3,2%) were found. Thirteen species of fungi were identified in surfaces, being the most frequent the Penicillium genus (91,6%). Concerning yeasts found in surfaces, four species were identified being Rhodotorula sp. (29,1%) the most frequent. There was no coincidence between prevailing genera indoors and outside premises. Moreover, some places presented fungal species different from the ones isolated outside. In the inside environment, Aspergillus species were isolated in air and surfaces. There was no significant relationship (p>0,05) between fungal contamination and the studied environmental variables.","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124888251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many countries were not prepared for a pandemic on June 11, 2009, when the World Health Organization (WHO) declared an Influenza Pandemic. Although Pandemic Influenza Preparedness Planning activity for 2011 has declined compared to 2009, we cannot take preparedness planning off the radar due to future potential pandemics. Unless countries develop model Pandemic Influenza Preparedness Plans, the consequences of being unprepared could be devastating to all of humankind. This study identified Critical Success Factors (CSFs) necessary at all levels (local, state, and national) to achieve model Pandemic Influenza Preparedness Planning. Pandemic Influenza Preparedness Planning involves developing a plan in the event of the emergence of an influenza virus that causes serious illness and is spread easily and is sustainable among humans. Once the WHO issues a pandemic influenza alert, all countries should be prepared. Data was collected through surveys, interviews, and benchmarking methods. The goal of identifying CSFs is to provide those factors to countries as well as authorities on a local, state, and national level in order to develop model Pandemic Influenza Preparedness Plans. Several CSFs were identified, they included the following: strong leadership support, plan development, having logical response plans, exercising plans, clear operations and implementation policies, adequate budget/resources, effective
{"title":"The development of a model of pandemic preparedness planning utilizing critical success factors from the United States and the European Union.","authors":"Y. Draine, J. Johnson, M. Levy, W. Sumrall","doi":"10.2495/EHR110091","DOIUrl":"https://doi.org/10.2495/EHR110091","url":null,"abstract":"Many countries were not prepared for a pandemic on June 11, 2009, when the World Health Organization (WHO) declared an Influenza Pandemic. Although Pandemic Influenza Preparedness Planning activity for 2011 has declined compared to 2009, we cannot take preparedness planning off the radar due to future potential pandemics. Unless countries develop model Pandemic Influenza Preparedness Plans, the consequences of being unprepared could be devastating to all of humankind. This study identified Critical Success Factors (CSFs) necessary at all levels (local, state, and national) to achieve model Pandemic Influenza Preparedness Planning. Pandemic Influenza Preparedness Planning involves developing a plan in the event of the emergence of an influenza virus that causes serious illness and is spread easily and is sustainable among humans. Once the WHO issues a pandemic influenza alert, all countries should be prepared. Data was collected through surveys, interviews, and benchmarking methods. The goal of identifying CSFs is to provide those factors to countries as well as authorities on a local, state, and national level in order to develop model Pandemic Influenza Preparedness Plans. Several CSFs were identified, they included the following: strong leadership support, plan development, having logical response plans, exercising plans, clear operations and implementation policies, adequate budget/resources, effective","PeriodicalId":370021,"journal":{"name":"WIT Transactions on Biomedicine and Health","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129002987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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