AIDS, epidemics, and statistics.
Statistical thinking has made significant contributions to our understanding of epidemics. Examples where statistics has played an important role in the Acquired Immunodeficiency Syndrome (AIDS) epidemic include estimating the number of individuals infected with the human immunodeficiency virus, estimating the incubation period of the disease, studying the etiology of the disease, and monitoring and forecasting the course of the epidemic. Some parallels with other epidemics in history are drawn. The AIDS epidemic has also raised important questions about the design of clinical studies and whether classical approaches are sufficiently flexible to provide timely answers to therapeutic questions in a growing epidemic. In a public crisis, there is a sense of urgency and data may be collected with unusual sampling schemes and inherent biases. Attention needs to be paid as much to sampling variation as to systematic sources of bias. Accurate disease surveillance data and methods for analyzing such data are crucial for detecting and monitoring future epidemics. There will almost certainly be new epidemics in the future, either of old diseases resurfacing or of new diseases, and statistical reasoning will continue to play a significant role in addressing the challenges of these public health crises.
Brookmeyer
R
R
Department of Biostatistics, Johns Hopkins University School of Hygiene and Public Health, Baltimore, Maryland 21205, USA.
D000163:Acquired Immunodeficiency Syndrome / Q000453:epidemiology* / Q000209:etiology / Q000517:prevention & control; D001699:Biometry; D002771:Cholera / Q000453:epidemiology / Q000209:etiology; D004196:Disease Outbreaks / Q000706:statistics & numerical data; D004812:Epidemiologic Methods; D005260:Female; D015658:HIV Infections / Q000453:epidemiology / Q000401:mortality; D006801:Humans; D008297:Male; D014481:United States / Q000453:epidemiology