Info
Healthy people 2010 statistical notes / / from the Centers for Disease Control and Prevention/National Center for Health Statistics
| Healthy people 2010 statistical notes / / from the Centers for Disease Control and Prevention/National Center for Health Statistics |
| Pubbl/distr/stampa | Hyattsville, Md., : U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, [2001]- |
| Descrizione fisica | 1 online resource (volumes) |
| Disciplina | 362 |
| Collana | DHHS publication |
| Soggetto topico |
Public health surveillance - United States - Statistical methods
Public Health Population Surveillance Health Status Indicators Public health surveillance - Statistical methods |
| Soggetto genere / forma |
Periodical
Periodicals. |
| Formato | Materiale a stampa  |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
Statistical notes
Healthy people 2000 statistical notes |
| Record Nr. | UNINA-9910592996403321 |
| Hyattsville, Md., : U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, [2001]- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr [[electronic resource]]
| Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr [[electronic resource]] |
| Autore | Fricker Ronald D. <1960-> |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2013 |
| Descrizione fisica | 1 online resource (xvi, 399 pages) : digital, PDF file(s) |
| Disciplina | 363.325/3 |
| Soggetto topico |
Public health surveillance
Public health surveillance - Statistical methods Epidemics - Prevention |
| ISBN |
1-107-23268-6
1-299-25740-2 1-107-33284-2 1-107-33221-4 1-107-33450-0 1-107-33533-7 1-139-04790-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Part I. Introduction to Biosurveillance: 1. Overview; 2. Biosurveillance data; Part II. Situational Awareness: 3. Situational awareness for biosurveillance; 4. Descriptive statistics for displaying the situation; 5. Statistical models for evaluating the situation; Part III. Early Event Detection: 6. Design and performance evaluation; 7. Univariate temporal methods; 8. Multivariate temporal methods; 9. Spatio-temporal methods; Part IV. Putting It All Together: 10. Simulating biosurveillance data; 11. Applying the temporal methods to real data; 12. Comparing methods to better understand and improve; 13. Frontiers, open questions, and future research. |
| Record Nr. | UNINA-9910464958303321 |
Fricker Ronald D. <1960->
|
||
| Cambridge : , : Cambridge University Press, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr [[electronic resource]]
| Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr [[electronic resource]] |
| Autore | Fricker Ronald D. <1960-> |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2013 |
| Descrizione fisica | 1 online resource (xvi, 399 pages) : digital, PDF file(s) |
| Disciplina | 363.325/3 |
| Soggetto topico |
Public health surveillance
Public health surveillance - Statistical methods Epidemics - Prevention |
| ISBN |
1-107-23268-6
1-299-25740-2 1-107-33284-2 1-107-33221-4 1-107-33450-0 1-107-33533-7 1-139-04790-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Part I. Introduction to Biosurveillance: 1. Overview; 2. Biosurveillance data; Part II. Situational Awareness: 3. Situational awareness for biosurveillance; 4. Descriptive statistics for displaying the situation; 5. Statistical models for evaluating the situation; Part III. Early Event Detection: 6. Design and performance evaluation; 7. Univariate temporal methods; 8. Multivariate temporal methods; 9. Spatio-temporal methods; Part IV. Putting It All Together: 10. Simulating biosurveillance data; 11. Applying the temporal methods to real data; 12. Comparing methods to better understand and improve; 13. Frontiers, open questions, and future research. |
| Record Nr. | UNINA-9910789317103321 |
|
Fricker Ronald D. <1960->
|
||
| Cambridge : , : Cambridge University Press, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr [[electronic resource]]
| Introduction to statistical methods for biosurveillance : with an emphasis on syndromic surveillance / / Ronald D. Fricker, Jr [[electronic resource]] |
| Autore | Fricker Ronald D. <1960-> |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2013 |
| Descrizione fisica | 1 online resource (xvi, 399 pages) : digital, PDF file(s) |
| Disciplina | 363.325/3 |
| Soggetto topico |
Public health surveillance
Public health surveillance - Statistical methods Epidemics - Prevention |
| ISBN |
1-107-23268-6
1-299-25740-2 1-107-33284-2 1-107-33221-4 1-107-33450-0 1-107-33533-7 1-139-04790-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine generated contents note: Part I. Introduction to Biosurveillance: 1. Overview; 2. Biosurveillance data; Part II. Situational Awareness: 3. Situational awareness for biosurveillance; 4. Descriptive statistics for displaying the situation; 5. Statistical models for evaluating the situation; Part III. Early Event Detection: 6. Design and performance evaluation; 7. Univariate temporal methods; 8. Multivariate temporal methods; 9. Spatio-temporal methods; Part IV. Putting It All Together: 10. Simulating biosurveillance data; 11. Applying the temporal methods to real data; 12. Comparing methods to better understand and improve; 13. Frontiers, open questions, and future research. |
| Record Nr. | UNINA-9910823266103321 |
|
Fricker Ronald D. <1960->
|
||
| Cambridge : , : Cambridge University Press, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Understanding and using tuberculosis data / / World Health Organization
| Understanding and using tuberculosis data / / World Health Organization |
| Pubbl/distr/stampa | Geneva, Switzerland : , : World Health Organization, , [2014] |
| Descrizione fisica | 1 online resource (205 p.) |
| Disciplina | 614.542 |
| Soggetto topico |
Tuberculosis
Tuberculosis - Epidemiology Public health surveillance - Statistical methods |
| ISBN | 92-4-069325-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Acknowledgements; Introduction; Abbreviations; Chapter 1 Analysis of aggregated TB notification data; 1.1 Aggregated notification data: what are they?; 1.2 Assessment and assurance of the quality of aggregated TB notification data; Data validation at data entry; Data validation after data entry; 1.3 Analysis of aggregate data; Rationale for analysis of trends; 1.4 Examples of analysis of trends; Notifications by time; Notifications by age; Notifications by sex; Notifications by place; Notifications by place and time; reasons for changes in notification rates over time
1.5 Limitations of aggregated notification data1.6 Summary; References; Annex 1 TB surveillance data quality standards with examples; Chapter 2 Analysis of case-based TB notification data; 2.1 Case-based notification data: what they are and why are they important; Steps in case-based data analyses; 2.2 Developing an analytic plan; 2.3 Preparing the dataset; Data cleaning; Addressing missing data; Identifying outliers; De-duplication of datasets; Re-coding variables linking datasets Sex Age (years) (Original, Continuous Variable Age Group (Recoded, Categorical Variable 0-25 years=1 26-50 years=2 >50 years=3 Height (m) (Original, Continuous Variable) Weight (kg) (Original, Continuous Variable) BMIFinalizing the dataset; 2.4 Data analysis: conducting and interpreting descriptive analyses; Univariate and bivariate analyses; Rates and trends; Other descriptive analyses; Other types of information used for further examination of data; 2.5 Data analysis: conducting and interpreting more complex analyses; 2.6 Communicating findings; 2.7 Conclusion; References Annex 2 Analytic plan exampleAnnex 3 Example of multivariable analysis to assess risk factors for loss to follow-up; Chapter 3 Using genotyping data for outbreak investigations; 3.1 Genotyping data: an overview; Introduction; Purpose and uses of genotyping; Intended audience; 3.2 Preparation of data; Differentiating TB strains; Identifying and naming clusters; 3.3 Analysing outbreaks; Excluding false-positive cases; Epidemiological links; Drug resistance patterns; Previous episodes of TB; Presenting epidemiological links between cases; 3.4 Analysing large clusters Displaying time, person and place3.5 Limitations of genotyping data; 3.6 Special considerations for genotyping in high TB burden settings; 3.7 Conclusion: using genotyping data for public health; References; Chapter 4 Analysis of factors driving the TB epidemic; 4.1 Ecological analysis; What can be explained with ecological analysis?; 4.2 TB incidence; 4.3 Using ecological analysis to understand TB epidemics; 4.4 Conceptual framework for ecological analysis; What if certain key information is unavailable for all domains?; How should we prioritize the domains and indicators to include? What if there are no data on something that experts deem as important? |
| Record Nr. | UNINA-9910787054303321 |
| Geneva, Switzerland : , : World Health Organization, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Understanding and using tuberculosis data / / World Health Organization
| Understanding and using tuberculosis data / / World Health Organization |
| Pubbl/distr/stampa | Geneva, Switzerland : , : World Health Organization, , [2014] |
| Descrizione fisica | 1 online resource (205 p.) |
| Disciplina | 614.542 |
| Soggetto topico |
Tuberculosis
Tuberculosis - Epidemiology Public health surveillance - Statistical methods |
| ISBN | 92-4-069325-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Acknowledgements; Introduction; Abbreviations; Chapter 1 Analysis of aggregated TB notification data; 1.1 Aggregated notification data: what are they?; 1.2 Assessment and assurance of the quality of aggregated TB notification data; Data validation at data entry; Data validation after data entry; 1.3 Analysis of aggregate data; Rationale for analysis of trends; 1.4 Examples of analysis of trends; Notifications by time; Notifications by age; Notifications by sex; Notifications by place; Notifications by place and time; reasons for changes in notification rates over time
1.5 Limitations of aggregated notification data1.6 Summary; References; Annex 1 TB surveillance data quality standards with examples; Chapter 2 Analysis of case-based TB notification data; 2.1 Case-based notification data: what they are and why are they important; Steps in case-based data analyses; 2.2 Developing an analytic plan; 2.3 Preparing the dataset; Data cleaning; Addressing missing data; Identifying outliers; De-duplication of datasets; Re-coding variables linking datasets Sex Age (years) (Original, Continuous Variable Age Group (Recoded, Categorical Variable 0-25 years=1 26-50 years=2 >50 years=3 Height (m) (Original, Continuous Variable) Weight (kg) (Original, Continuous Variable) BMIFinalizing the dataset; 2.4 Data analysis: conducting and interpreting descriptive analyses; Univariate and bivariate analyses; Rates and trends; Other descriptive analyses; Other types of information used for further examination of data; 2.5 Data analysis: conducting and interpreting more complex analyses; 2.6 Communicating findings; 2.7 Conclusion; References Annex 2 Analytic plan exampleAnnex 3 Example of multivariable analysis to assess risk factors for loss to follow-up; Chapter 3 Using genotyping data for outbreak investigations; 3.1 Genotyping data: an overview; Introduction; Purpose and uses of genotyping; Intended audience; 3.2 Preparation of data; Differentiating TB strains; Identifying and naming clusters; 3.3 Analysing outbreaks; Excluding false-positive cases; Epidemiological links; Drug resistance patterns; Previous episodes of TB; Presenting epidemiological links between cases; 3.4 Analysing large clusters Displaying time, person and place3.5 Limitations of genotyping data; 3.6 Special considerations for genotyping in high TB burden settings; 3.7 Conclusion: using genotyping data for public health; References; Chapter 4 Analysis of factors driving the TB epidemic; 4.1 Ecological analysis; What can be explained with ecological analysis?; 4.2 TB incidence; 4.3 Using ecological analysis to understand TB epidemics; 4.4 Conceptual framework for ecological analysis; What if certain key information is unavailable for all domains?; How should we prioritize the domains and indicators to include? What if there are no data on something that experts deem as important? |
| Record Nr. | UNINA-9910814459903321 |
| Geneva, Switzerland : , : World Health Organization, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
