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Bias in interpreting results of clinical studies
Bias in performing clinical studies
Attributable risk (AR)
DALY and QALY
Incidence and prevalence
Mortality rates and case-fatality
Relative and absolute risk
Positive and negative predictive value
Sensitivity and specificity
Test precision and accuracy
Modes of infectious disease transmission
Vaccination and herd immunity
Cross sectional study
Placebo effect and masking
Randomized control trial
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Let’s say we want to figure out the risk of dying for people who live in a certain population, like the population of France in 2015, which was around 66.6 million people.
The first way we could do this is by calculating the all-cause mortality rate or death rate.
That’s the total number of deaths from all causes in 1 year divided by the total number of people at risk in the population at mid-year, and typically that’s the number of people at risk of death in the entire population.
For example, in 2015, there were approximately 620,000 deaths.
So, the all-cause mortality rate in France was 620,000 divided by 66.6 million, or 0.0093.
We can express the mortality rate in a few different ways.
First, we could say that the absolute risk of dying from all causes in France in 2015 was 0.0093.
Alternatively, we might express it as a percentage, by multiplying it by 100 - so 0.0093 times 100 equals 0.93%.
Most often though, we express mortality rate in terms of number of deaths per 100,000 people.
So, we multiply the mortality rate - 0.0093 - by 100,000, which is 930.
This means that, in France, there were 930 deaths per 100,000 people in 2015.
Mortality rates can be calculated for any time period, like 1 month, 1 year, or 10 years, but it’s important to specify which time period is used in the calculation, since the rate might be different for different time periods.
For example, a natural disaster - like an earthquake or forest fire - might increase the number of deaths in a certain time period.
Sometimes we’re interested in the mortality rate in a certain subpopulation, like only women or only people who are older than 65 years.
In those situations, we use a specific rate - like an age-specific rate or a gender-specific rate - which is calculated by dividing the number of deaths from all causes in one year by the number of people at risk of death in the subpopulation at mid-year.
For example, there were around 33.9 million women in France in 2015, and 298,000 women who died in that year, so the female-specific mortality rate was 0.0088, or 880 deaths from all causes per 100,000 women in France in 2015.
We can also calculate a cause-specific or disease-specific mortality rate for people with a specific disease, like cancer.
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