Weighted Markov chains for forecasting and analysis in Incidence of infectious diseases in jiangsu Province, China

Journal of Biomedical Research

Volumn 24, Issue 3, 2010, Pages 207-214

  Peng, Zhihang ^a   Bao, Changjun ^b   Zhao, Yang ^a   Yi, Honggang ^a   Xia, Letian ^c   Yu, Hao ^a   Shen, Hongbing ^a   Chen, Feng ^a  

^a NANJING MEDICAL UNIVERSITY   (China)

^b JIANGSU PROVINCIAL CENTER FOR DISEASE CONTROL AND PREVENTION   (China)

^c HOHAI UNIVERSITY   (China)

Author keywords

Forecasting and analysis; Infectious diseases; Markov chain Monte Carlo; Sequential cluster; Weighted Markov chains

Indexed keywords

ARTICLE; CANCER PATIENT; CHINA; CLINICAL DECISION MAKING; CLUSTER ANALYSIS; CORRELATION COEFFICIENT; DISEASE COURSE; FORECASTING; HEPATITIS B; HEPATITIS B VIRUS; HUMAN; INCIDENCE; INFECTION; LIVER CANCER; LIVER CIRRHOSIS; MAJOR CLINICAL STUDY; MONTE CARLO METHOD; PRIORITY JOURNAL; PROBABILITY; STOCHASTIC MODEL; UNCERTAINTY;

EID: 78549236167     PISSN: 16748301     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1674-8301(10)60030-9     Document Type: Article

References (39)

1. Ross SM Stochastic Processes 1991, John Wiley& Sons, Inc., New York.
2. Bharucha-Reid AT Elements of the Theory of Markov Processes and Their Applications 1960, McGraw- Hill Book Company, Inc.
3. Lange K Numerical Analysis for Statisticians 1999, Springer - Verlag, Inc.
4. Crommelin DT, Vanden-Eijnden E Fitting time series by continuous-time Markov chains: A quadratic programming approach. J Computational Physics 2006, 217:782-805.
5. Serva M, Fulco UL, Gléria IM, Lyra ML, Petroni F, Viswanathan GM A Markov model of financial returns. Physica A 2006, 363:393-403.
6. Takahashi K, Morikawa K, Myreshka, Takeda D, Mizuno A Inventory control for a MARKOVIAN remanufacturing system with stochastic decomposition process. Int J Production Economics 2007, 108:416-425.
7. Deslauriers A, L'Ecuyer P, Pichitlamken J, Ingolfsson A, Avramidis AN Markov chain models of a telephone call center with call blending. Computers Operations Res 2007, 34:1616-1645.
8. Chan GK, Asgarpoor S Optimum maintenance policy with Markov processes. Electric Power Systems Res 2006, 76:452-456.
9. Jaskiewicz A, Nowak AS On the optimality equation for average cost Markov control processes with Feller transition probabilities. J Math Anal Appl 2006, 316:495-509.
10. Lee H, Chen S Why use Markov-switching models in exchange rate prediction. Economic Modelling 2006, 23:662-668.
11. Silos P Assessing Markov chain approximations: A minimal econometric approach. J Econom Dynamics Control 2006, 30:1063-1079.
12. Mode CJ, Sleeman CK. Stochastic Processes in Epidemiology. World Scientific, Singapore 2004.
13. Zhou Y, Shao Y, Ruan Y, Xu J, Ma Z, Mei C, et al. Modeling and prediction of HIV in China: Transmission rates structured by infection ages. Mathematical Biosci Engineer 2008, 5:403-418.
14. Yakowitz S, Blount M, Gani J Computing marginal expectations for large compartmentalized models with application to AIDS evolution in a prison system. J Mathematics Appl Med Biol 1996, 13:223-244.
15. Zhang W, Chaloner K, Cowles MK, Zhang Y, Stapleton JT A Bayesian analysis of doubly censored data using a hierarchical Cox model. Statist. Med 2008, 27:529-542.
16. Islam MA Multistate survival models for transitions and reverse transitions: an application to contraceptive use date. J Roy Statistical Society A 1994, 157:441-455.
17. Janardan KG On a distribution associated with a stochastic process in Ecology. Biomet J 2002, 44:510-522.
18. Boher JM, Pujol JL, Grenier J, Daurès JP Markov model and markers of small cell lung cancer: Assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis. Brit J Cancer 1999, 79:1419-1427.
19. Trajstman AC A Markov chain model for Newcastle disease and its relevance to the intracerebral pathogenicity index. Biomet J 2002, 44:43-57.
20. Wang P, Puterman ML Analysis of longitudinal data of epileptic seizure counts: A two state hidden Markov regression approach. Biomet J 2001, 43:941-962.
21. Hendriks JC, Craib KJ, Veugelers PJ, Van Druten HA, Coutinho RA, Schechter MT, et al. Secular trends in the survival of HIV-infected homosexual men in Amsterdam and Vancouver estimated from a death-included CD4-staged Markov model. Int J Epidemiol 2000, 29:565-572.
22. Sommen C, Alioum A, Commenges D A multistate approach for estimating the incidence of human immunodeficiency virus by using HIV and AIDS French surveillance data. Statist Med 2009, 28:1554-1568.
23. Becker NG Analysis of Infectious Disease Data 1942, Chapman and Hall, London & New York.
24. Volz E, Meyers LA Epidemic thresholds in dynamic contact networks. J Roy Soc, Interface/the Royal Society 2009, 6:233-241.
25. Kretzschmar M, Jager JC, Reinking DP, Van Zessen G, Brouwers H The basic reproduction ratio R0 for a sexually transmitted disease in a pair formation model with two types of pairs. Math Biosci 1994, 124:181-205.
26. Johnson DE Applied Multivariate Methods for Data Analysts 2005, Higher Education Press, Beijing.
27. DeRisi JL, Iyer VR, Brown PQ Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 1997, 278:680-686.
28. Lander ES Array of hope. Nature Genet 1999, 21:3-4.
29. Quackenbush J Computational analysis of microarray data. Nat Rev Genet 2001, 2:418-427.
30. Chiang CL An Introduction to Stochastic Processes and their Application 1980, Krieger Publishing Company, New York. E. Robert (Ed.).
31. Iseacson DL, Madsen RW Markov Chains Theory and Applications 1976, John Wiley and Sons, Inc., New York.
32. Lu Y, Fang J Advanced Medical Statistics 2003, World Scientific, Singapore.
33. Freedman D Markov Chains 1983, Springer - Verlag.
34. Kendall WS, Montana G Small sets and Markov transition densities. Stochastic Processes and their Applications 2002, 99:177-194.
35. Bartlett MS Measles periodicity and community size. J Roy Statistical Soc 1957, 120:48-70.
36. Mitavskiy B, Cannings C Estimating the ratios of the stationary distribution values for Markov chains modeling evolutionary algorithms. Evolutionary Computation 2009, 17:343-377.
37. Heffernan JM, Wahl LM Natural variation in HIV infection: Monte Carlo estimates that include CD8 effector cells. J Theoret Biol 2006, 243:191-204.
38. Chib S, Winkelmann R Markov chain Monte Carlo analysis of correlated count data. J Business Econc Statistics 2001, 19:428-435.
39. Covington TR, Robinan Gentry P, Van Landingham CB, Anderson ME, Kester JE, Clewell HJ The use of Markov chain Monte Carlo uncertainty analysis to support a Public Health Goal for perchloroethylene. Reg Toxicol Pharmacol 2007, 47:1-18.