Health Statistics

Summary: "Surveillance data collected in vital registration and TB notification systems provide essential information about the TB epidemic and programmatic efforts to control the disease at both national and local levels. Analysis of these data can help programme managers and other staff to track the level of and trends in TB disease burden, detect outbreaks of disease and identify ways to improve existing TB prevention, diagnostic and treatment services. This book provides practical guidance on the analysis and use of such surveillance data, and is suitable for a wide range of people engaged in TB control. It was produced as a major collaborative effort as part of the work of the WHO's Global Task Force on TB Impact Measurement."-- back 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
1.3. Analysis of aggregate data
1.4. Examples of analysis of trends
1.5. Limitations of aggregated notification data
1.6. 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
2.2. Developing an analytic plan
2.3. Preparing the dataset
2.4. Data analysis: conducting and interpreting descriptive analyses
2.5. Data analysis: conducting and interpreting more complex analyses
2.6. Communicating findings
2.7. Conclusion
References
Annex 2. Analytic plan example
Annex 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
3.2. Preparation of data
3.3. Analysing outbreaks
3.4. Analysing large clusters
3.5. 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
4.2. TB incidence
4.3. Using ecological analysis to understand TB epidemics
4.4. Conceptual framework for ecological analysis
4.5. Preparing your data for analysis
4.6. Case studies
4.7. Conclusion
References
Annex 4. Which types of data should be investigated as part of TB ecological analyses?
Annex 5. Detailed conceptual framework on how factors influence TB burden
Chapter 5. Drug-resistant TB: analysis of burden and response
5.1. Methodology
5.2. Estimation of the burden of drug-resistant TB and time analysis
5.3. Monitoring programme effectiveness
5.4. Conclusion
References
Chapter 6. HIV-associated TB: analysis of burden and response
6.1. Introduction to HIV-associated TB
6.2. Analysis of programme data
References
Chapter 7. Estimating TB mortality using vital registration and mortality survey data
7.1. Sources of mortality data
7.2. Monitoring TB mortality among HIV-negative individuals
7.3. Monitoring TB mortality among people living with HIV
7.4. Mortality to notification ratio
7.5. MDR-TB mortality
References
Chapter 8. Combining surveillance and survey data to estimate TB burden
8.1. TB incidence
8.2. TB prevalence
8.3. TB mortality and case fatality ratio
References
Epilogue.

Summary: Contains statistics on end stage renal disease (ESRD) such as life expenctancy following transplant, survival rates, prevalence and costs of ESRD therapy, international comparisons of ESRD, and treatment modalitites such as dialysis and hemodialysis.