Harvard University Initiative for Global Health Global Health Challenges Social Analysis 76: Lecture 3.

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Harvard University Initiative for Global Health Global Health Challenges Social Analysis 76: Lecture 3

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health Core Measurements Understanding health problems and how health systems respond to these problems is based on some core health and health system measurements. Controversies and alternative interpretations over these measurements underlie a major fraction of global health debates.

Harvard University Initiative for Global Health sceptic 1. person inclined to doubt accepted opinions. Oxford English Dictionary

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health Definition of Mortality Rate (deaths in an age group in a year) (population in an age group at the midpoint of the year)

Harvard University Initiative for Global Health Commonly Reported Probabilities of Death 1q0 – infant mortality ‘rate’, the probability of death between birth and exact age 1. 5q0 – child mortality, the probability of death between birth and exact age 5. 45q15 – adult mortality, the probability of death between age 15 and exact age 60 conditional on being alive at age 15.

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health 250 Years of Child and Adult Mortality

Harvard University Initiative for Global Health Coverage of Death Registration. Mortality Data (1995 Onwards) by Cause Available in WHO

Harvard University Initiative for Global Health Alternative Mortality Measurement Methods Complete birth histories Sibling survival Household deaths in the last 12 months Demographic surveillance systems

Harvard University Initiative for Global Health 5Q0:India Child Mortality

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health International Classification of Diseases and Injuries First revision 1893 Now maintained by WHO and revised every years, current version is 10 th revision Comparisons overtime complicated by changing understanding of disease causation and classification

Harvard University Initiative for Global Health

Variation in Medical Culture and Cause of Death Attribution In addition to changes in the classification system, different countries and regions within countries appear to vary in how the same clinical entity is assigned a cause of death.

Harvard University Initiative for Global Health Rank of the 50 US States According to Cardiovascular Diseases and Ischaemic Heart Disease

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health Definition of Incidence Rate (the number of new cases of a disease) (person-time of observation)

Harvard University Initiative for Global Health Definition of Prevalence Rate (number of individuals with a disease) (population)

Harvard University Initiative for Global Health Approximate Relationship Between Prevalence and Incidence Prevalence=Incidence*Duration

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health Key Issues Diagnostic technology – the impact of test characteristics on the interpretation of results Interpreting data collected at health facilities – the problem of selection bias and coverage Using population surveys – biomarkers and self- reports

Harvard University Initiative for Global Health Diagnostic Test Characteristics

Harvard University Initiative for Global Health Test Sensitivity The proportion of those with the disease who will test positive Sensitivity = A/(A+B)

Harvard University Initiative for Global Health Test Specificity The proportion of those without the disease who will test negative Specificity = D/(C+D)

Harvard University Initiative for Global Health Surveys and Test Characteristics Imagine a test for HIV that is 98% sensitive and 95% specific. If the survey finds 10% of the population test positive, what is the true prevalence? Answer: 5.4%

Harvard University Initiative for Global Health True Prevalence p(0.98) + (1-p)(1-0.95) = 0.10 p(0.93) = 0.05 p = 0.054

Harvard University Initiative for Global Health Facility Based Data Collection For medium duration conditions in highly resourced health systems can be used for incidence measurement Can be very useful for epidemic or outbreak surveillance Global Outbreak and Response Network and SARS

Harvard University Initiative for Global Health Cases

Self-reported and Measured Height, Males and Females,

Harvard University Initiative for Global Health Self-reported and Measured Weight, Males and Females,

Harvard University Initiative for Global Health Core Health and Health System Measurements Core Health and Health System Measurements Definitions of Mortality Rates and Probabilities Definitions of Mortality Rates and Probabilities Measuring Mortality Measuring Mortality Causes of Death Causes of Death Definitions of Incidence and Prevalence Definitions of Incidence and Prevalence Measuring Diseases and Risk Factors Measuring Diseases and Risk Factors The Politics of Measurement The Politics of Measurement

Harvard University Initiative for Global Health Three Questions to Ask When Politics and Measurement Intersect 1.What is the primary source of information and what biases are expected? 2.Have known biases been corrected and is there an explicit data audit trail? 3.Will someone who could have influenced the primary data collection or corrections for known bias stand to gain or lose from this result?