HLTH 240b Lecture Notes - Lecture 4: Case Fatality Rate, Cumulative Incidence, Vector Calculus

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18 May 2017

School

Yale University

Department

Global Health Studies

Course

HLTH 240b

Professor

Marney White

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Document Summary

Systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, evaluation of public health practice: serve as early warning system, document impact of intervention, monitor. Cdc outline of tasks for evaluating a surveillance system: describe the public health importance of health event. Three most important categories: total number of cases, incidence, prevalence, preventability. Indices of severity such as the mortality rate and case fatality ration: describe the system to be evaluated, vector analysis: importance is not where disease is reported but potential spread of. Measures of disease and morbidity disease: frequency data. Incidence rate: number of new cases, time specific, people observed throughout defined time period, people are not observed throughout. Have to make adjustments to account for the fact that people are observed for varying lengths. 44-45 in textbook: population specific (per xx# of people, equation (incidence rate per thousand) = (# new cases within time period x 1000)/(# people at risk during that time period)

Related Questions

QUESTION 1 1. The relative importance or burden of a disease within a population will depend on a number of factors including : A. Disease frequency B. Disease severity C. Disease consequences D. All of the above

QUESTION 2 1 . With the epidemiologic transition, there is a reduction in malnutrition and _____ . A. Communicable diseases B. Injuries C. Non-communicable chronic diseases D. Mental health disorders

QUESTION 3 1. A major challenge to developing a burden of disease profile in low and middle-income countries relates to A. Unwillingness to share complete information B. Conflicting disease definitions C. Challenges obtaining information related to cause of death D. All of the above

QUESTION 4 1. The demographic transition describes which of the following changes to society A. Changes in birth and death rates that reflect a modern society B. Declines in mortality followed by a reduction in fertility C. A change in the age structure of the population D. All of the above

QUESTION 5 1. Measures of health status that combine mortality and morbidity data A. Facilitate comparisons both within and across populations B. Help estimate the quantitative health benefits from interventions C. Serve as tools to assist with resource allocation D. All of the above

QUESTION 6 1. The disability-adjusted life year is defined as A. A health gap population summary measure that combines time lost due to disability with that lost due to death B. A measure to compare the gap between the current situation to that of an ideal situation C. A measure that combines the amount of healthy life lost due to morbidity with that lost due to injury. D. Answers B and C

QUESTION 7 1. True or false? A key limitation to mortality-based indicators is that they fail to account for the morbidity caused by disease. True False

QUESTION 8 1. The most widely used composite measure of population health is the DALY, and this epidemiological measure is the sum of morbidity and ________data. A. Years of life lost (YLL) B. Morbidity C. Infant mortality rates (IMR) D. none of the above

QUESTION 9 1. What would be the best source of information on adult and infant mortality (in high income countries)? A. Disease registers B. Vital statistics C. Special survey study D. Hospital clinic statistics

QUESTION 10 1. Which term is best used to describe the proportion of people in a population who have a defined disease at a specific point of time? A. DALY B. Incidence C. Mortality rate D. Prevalence

QUESTION 11 1. Which term is best used to describe new cases of disease occurring in a population? A. DALY B. Incidence C. Mortality rate D. Prevalence

QUESTION 12 1. Which term is used to describe the absence or presence of illness or disease? A. Demography B. Morbidity C. Mortality D. Vitality

QUESTION 13 1. Mortality (death indicators) include: A. Mortality rate B. Infant mortality rate C. Neonatal morality rate D. All of the above

QUESTION 14 1. True or false? The value of life is often implicit in the way resource allocation decisions are made, which suggests that these decisions should be as explicit, open, and transparent as possible. True False

QUESTION 15 1. _________________is projected as the number one leading cause of disease burden in 2030. A. Ischemic heart disease B. Diabetes mellitus C. HIV/AIDS D. Unipolar depression

QUESTION 16 1. Some of the negative aspects of globalization include A. Greater insecurity of employment B. Poorer housing and sanitation due to rapid urbanization C. Greater vulnerability to environmental degradation D. All of the above

QUESTION 17 1. Current concerns about climate change focus on several developments including A. Rising global average land and sea surface temperature B. Increasing frequency of extreme weather conditions C. Both A and B D. None of the above

QUESTION 18 1. True or false? Diseases carried by mosquitoes are especially sensitive to meteorological conditions because they are vulnerable to changes in the ambient temperature. As a result of changing temperatures, infectious diseases such as malaria and dengue have decreased in incidence and geographic range. True False

QUESTION 19 1. True or false? International cooperation of infectious disease control has a long history that includes obligatory reporting of outbreaks of specific diseases. However, compliance with obligatory reporting has been poor due to economic consequences that have often accompanied notification of disease outbreaks. True False

QUESTION 20 1. True or false? Globalization is a relatively new phenomenon that began in the mid-20th century. True False

CASE STUDY

It used to be that epidemiologists at the CDC only knew that you had the flu when you visited your doctor and the doc- tor then reported that information to other agencies. By the time this information made its way to the CDC or state health departments, it was often several days old, which meant that the medical community was always playing catch-up. And of course, your doctor was only aware of your illness if you showed up at his office, not when you decided to tough it out at home. Nowadays, however, before you ever go to the doc- tor, you are likely to search the Internet for âflu symptoms,â tweet your suddenly declining health status, or Instagram yourself lying in bed. Study the case below, which shows how the Internet and social media have impacted the field of epi- demiology, and then answer the questions that follow.

Google Used to Predict Influenza Outbreaksâ2008

In 2008, Google launched Google Flu Trends, an applica- tion that compiles aggregated data from key word searches

for clinical terms, such as thermometer, chest congestion, muscle aches, or flu symptoms. Google reports the data on a website, which then provides an early-warning system for the locations of new flu outbreaks. Because the data are collected from searches performed each day, trends in flu symptoms become apparent much more quickly than when they are based on data reported during office vis- its or in lab reports from physicians around the country. When the CDC compared actual cases over the course of a year with Googleâs findings, the data from the two sources matched.

Initially, Google was only compiling information about flu trends in the United States and Canada. But after the H1N1 virus appeared in Mexico in 2009, the CDC asked Google to go back and look at Internet searches conducted by people in Mexico during that time. Evaluation of the data indicated that Google detected an uptick several days before the CDC did (Figure 23.1).

1,200 1,000 800 600 400 200 0

Influenza activity

1113151719212325272931 2 4 6 8 1012141618202224262830 2

Suspected Confirmed

Mar

Apr

May

Date of illness onset

Intense

High Moderate

Low Minimal

Jul Aug Sep

Oct Nov

Dec Jan

Feb Mar

Apr May Jun

Figure 23.1 2009 Inflenza activity (a) Data from the Centers for Disease Control, based on physical examination by health care providers, shows a peak in influenza cases in late April. (b) Google âFlu Trendsâ shows an influenza peak in February.

No. of cases

Case Study Exercise 23 Morbidity and Mortality Weekly Report 199

Epidemic tracking based on Internet searches reflects what is called collective intelligence. It works because indi- viduals using their personal computers tend to search for terms related to their immediate needs and intentions, and they generally do this before presenting in a doctorâs office or emergency room. The methodology used in the Google search was published in the prestigious science journal Nature, and another independent study has been published about a similar search analysis conducted by Yahoo, showing that it was effective in predicting flu trends.

Some people worry that data collected from Internet searches may compromise individualsâ privacy. However,

Google maintains that Flu Trends cannot be used to iden- tify individual users because the data are anonymous and are aggregated before being presented. Another potential drawback is that this data collection method is less likely to be useful for tracking epidemics in societies having a low percentage of computer ownership, namely, developing countries. However, considering the high stakes involved in identifying an epidemic quickly, Internet search term analy- sis holds great promise for public health. And, unlike most health innovations, itâs free!

3. How might data collected in this way not be representative of a particular population?

4. Explain why the two graphs in Figure 23.1 do not show influenza activity peaking at the same time.

6. In 2013, Google Flu Trends vastly overestimated the number of cases of the flu in the United States. One explanation for this was that there was a greater than usual number of media reports about influenza early in the flu season. Based on your knowledge of how Flu Trends works, explain why Google missed the mark in 2013

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HLTH 240b Lecture Notes - Lecture 4: Case Fatality Rate, Cumulative Incidence, Vector Calculus

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