AbstractAn epidemic curve is a graph in which the number of new cases of an outbreak disease is plotted against time. Epidemic curves are ordinarily constructed after the disease outbreak is over. However, a good estimate of the epidemic curve early in an outbreak would be invaluable to health care officials. Currently, techniques for predicting the severity of an outbreak are very limited. As far as predicting the number of future cases, ordinarily epidemiologists simply make an educated guess as to how many people might become affected. We develop a model for estimating an epidemic curve early in an outbreak, and we show results of experiments testing its accuracy
A Bayesian network is developed to embed the probabilistic reasoning dependencies of the demographic...
Epidemic outbreak detection is an important problem in public health and the development of reliable...
© Alexander Eugene ZarebskiInfluenza inflicts a substantial burden on society but accurate and timel...
AbstractAn epidemic curve is a graph in which the number of new cases of an outbreak disease is plot...
Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thou...
Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thou...
Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thou...
An epidemic curve is a graphic depiction of the number of outbreak cases by date of illness onset, o...
When an outbreak of an infectious disease occurs, public health officials need to understand the dyn...
Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequ...
Epidemic curves are used by decision makers and the public to infer the trajectory of the COVID-19 p...
BACKGROUND: Fast changes in human demographics worldwide, coupled with increased mobility, and modif...
Background. Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great co...
Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The ...
We assess how presymptomatic infection affects predictability of infectious disease epidemics. We fo...
A Bayesian network is developed to embed the probabilistic reasoning dependencies of the demographic...
Epidemic outbreak detection is an important problem in public health and the development of reliable...
© Alexander Eugene ZarebskiInfluenza inflicts a substantial burden on society but accurate and timel...
AbstractAn epidemic curve is a graph in which the number of new cases of an outbreak disease is plot...
Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thou...
Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thou...
Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thou...
An epidemic curve is a graphic depiction of the number of outbreak cases by date of illness onset, o...
When an outbreak of an infectious disease occurs, public health officials need to understand the dyn...
Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequ...
Epidemic curves are used by decision makers and the public to infer the trajectory of the COVID-19 p...
BACKGROUND: Fast changes in human demographics worldwide, coupled with increased mobility, and modif...
Background. Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great co...
Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The ...
We assess how presymptomatic infection affects predictability of infectious disease epidemics. We fo...
A Bayesian network is developed to embed the probabilistic reasoning dependencies of the demographic...
Epidemic outbreak detection is an important problem in public health and the development of reliable...
© Alexander Eugene ZarebskiInfluenza inflicts a substantial burden on society but accurate and timel...