A kind of epidemic Forecasting Methodology based on considering quarantine measures
A kind of epidemic Forecasting Methodology based on considering quarantine measures
 CN 101,794,342 B
 Filed: 09/30/2009
 Issued: 09/09/2015
 Est. Priority Date: 09/30/2009
 Status: Active Grant
First Claim
1. , based on the epidemic Forecasting Methodology considering quarantine measures, it is characterized in that, comprise following steps:
 (1) by floating population'"'"'s ratio, epidemic situation statistics, infectious disease basic parameter, epidemic situation controling parameters unbalanced input, variable coefficient Infection Dynamics Model, the development of prediction epidemic situation, namely solve Susceptible population'"'"'s probability distribution density of prediction, latent period crowd'"'"'s probability distribution density, morbidity crowd probability distribution density, accumulative morbidity crowd probability distribution density, shift out crowd'"'"'s probability distribution density;
Wherein,Epidemic situation statistics comprises;
the ratio of susceptible person, the ratio sending out patient, latent period person ratio, the person of shifting out ratio;
Infectious disease basic parameter comprises;
latent period distribution profile, morbidity extended period distribution profile;
Epidemic situation controling parameters is the parameter of control function, comprising;
initially isolation rate, target isolation rate, control measure entryintoforce time, the control efficiency factor;
Described Basic equation group that is nonlinear, variable coefficient Infection Dynamics Model is as follows;
Chinese PRB Reexamination
Abstract
The present invention is directed to virus, in latent period, period of disease, all there is communicable epidemic disease, establish nonlinear, variable coefficient infectious disease forecasting model, propose the epidemic situation control function with model direct correlation, on the basis of prediction, consider control measure, and simulation and forecast is carried out to the effect of different control measure, different control dynamics, epidemic situation is controlled to consider as a continually varying process, one simulation and forecast is carried out to epidemic situation development and control, for decisionmaking section is optimized choice, controls with as far as possible little cost the quantitative information that epidemic situation provides key.The relative error that application the present invention simulates Beijing area SARS in 2003 is 0.98%, predicting the outcome to develop with actual epidemic situation and coincide very well the U.S. and Japan Area Influenza A H1N1, draw the fixing quantity factor that Influenza A H1N1 preliminary development stage is taken precautions against and control epidemic situation spreads, predict the epidemic situation developing state of different control intensity and varying number Susceptible population.
1 Claim

1. , based on the epidemic Forecasting Methodology considering quarantine measures, it is characterized in that, comprise following steps:

(1) by floating population'"'"'s ratio, epidemic situation statistics, infectious disease basic parameter, epidemic situation controling parameters unbalanced input, variable coefficient Infection Dynamics Model, the development of prediction epidemic situation, namely solve Susceptible population'"'"'s probability distribution density of prediction, latent period crowd'"'"'s probability distribution density, morbidity crowd probability distribution density, accumulative morbidity crowd probability distribution density, shift out crowd'"'"'s probability distribution density;
Wherein,Epidemic situation statistics comprises;
the ratio of susceptible person, the ratio sending out patient, latent period person ratio, the person of shifting out ratio;Infectious disease basic parameter comprises;
latent period distribution profile, morbidity extended period distribution profile;Epidemic situation controling parameters is the parameter of control function, comprising;
initially isolation rate, target isolation rate, control measure entryintoforce time, the control efficiency factor;Described Basic equation group that is nonlinear, variable coefficient Infection Dynamics Model is as follows;

Specification(s)