Detection of severe respiratory disease epidemic outbreaks by CUSUM-based overcrowd-severe-respiratory-disease-index model

Computational and Mathematical Methods in Medicine

Volumn 2013, Issue , 2013, Pages

  Polanco, Carlos ^a,b   Castañón González, Jorge Alberto ^a   Macías, Alejandro E ^b   Samaniego, José Lino ^a,c   Buhse, Thomas ^d   Villanueva Martínez, Sebastián ^b  

^a UNIVERSIDAD ANÁHUAC   (Mexico)

^b INSTITUTO NACIONAL DE CIENCIAS MÉDICAS Y NUTRICIÓN SALVADOR ZUBIRÁN   (Mexico)

^c UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

^d CENTRO DE INVESTIGACIONES QUÍMICAS   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

PATIENT MONITORING; PERSONNEL; PULMONARY DISEASES;

CUMULATIVE SUMS; EARLY WARNING; EFFECTIVE ALGORITHMS; HISTORICAL ARCHIVE; HOSPITAL NETWORKS; MEDICAL SCIENCE; STORAGE AREA; VIRTUAL SCENARIO;

EPIDEMIOLOGY;

ALGORITHM; ARTICLE; CLINICAL ASSESSMENT TOOL; CUMULATIVE SUM; EPIDEMIC; GEOGRAPHIC DISTRIBUTION; HEALTH CARE PERSONNEL; HUMAN; INFLUENZA A (H1N1); MATHEMATICAL PARAMETERS; MEXICO; OVERCROWD SEVERE RESPIRATORY DISEASE INDEX; PHYSICIAN; POST HOC ANALYSIS; RESPIRATORY TRACT DISEASE; SEVERE RESPIRATORY DISEASE; HEALTH CARE PLANNING; HEALTH SURVEY; INFLUENZA VIRUS A H1N1; INFLUENZA, HUMAN; ONLINE SYSTEM; PROCEDURES; RESPIRATORY DISTRESS SYNDROME, ADULT; RESPIRATORY TRACT DISEASES; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; ADULT RESPIRATORY DISTRESS SYNDROME; INFLUENZA; METHODOLOGY; STATISTICS;

ALGORITHMS; EPIDEMICS; HEALTH RESOURCES; HUMANS; INFLUENZA A VIRUS, H1N1 SUBTYPE; INFLUENZA, HUMAN; MEXICO; MODELS, STATISTICAL; ONLINE SYSTEMS; PUBLIC HEALTH SURVEILLANCE; RESPIRATORY DISTRESS SYNDROME, ADULT; RESPIRATORY TRACT DISEASES;

EID: 84884246384     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2013/213206     Document Type: Article

References (20)

1. McInerney J. E., Richter A., Strengthening hospital preparedness for chemical, biological, radiological, nuclear, and explosive events: clinicians' opinions regarding physician/physician assistant response and training. American Journal of Disaster Medicine 2011 6 2 73 87 2-s2.0-79960964690
2. Derlet R. W., Richards J. R., Overcrowding in the nation's emergency departments: complex causes and disturbing effects. Annals of Emergency Medicine 2000 35 1 63 68 2-s2.0-0033845904
3. Derlet R. W., Richards J. R., Kravitz R. L., Frequent overcrowding in U.S. Emergency departments. Academic Emergency Medicine 2001 8 2 151 155 2-s2.0-0035146165
4. Yasnoff W. A., Overhage J. M., Humphreys B. L., LaVenture M., A national agenda for public health informatics: summarized recommendations from the 2001 AMIA Spring Congress. Journal of the American Medical Informatics Association 2001 8 6 535 545 2-s2.0-0035185514
5. Polanco-González C., Castañón-González J. A., Buhse T., Samaniego-Mendoza J. L., Arreguín-Nava R., Villanueva- Martínez S., Modified overcrowd index in emergency room. Gaceta Médica de México 2013 149 156
6. Stock R., Mahoney E. R., Gauthier D., Henriksen K., Battles J. B., Keyes M. A., Developing a community-wide electronic shared medication list. Advances in Patient Safety: New Directions and Alternative Approaches 2008 4 Rockville, Md, USA Agency for Healthcare Research and Quality (US) Technology and Medication Safety. http://www.ncbi.nlm.nih.gov/books/NBK43762/
7. Luft H. S., Economic incentives to promote innovation in healthcare delivery. Clinical Orthopaedics and Related Research 2009 467 10 2497 2505 2-s2.0-70349926187 10.1007/s11999-009-0930-7
8. Chen G. J., Feldman S. R., Economic aspect of health care systems: advantage and disadvantage incentives in different systems. Dermatologic Clinics 2000 18 2 211 214 2-s2.0-0033995169
9. Grigg O. A., Farewell V. T., Spiegelhalter D. J., Use of risk-adjusted CUSUM and RSPRT charts for monitoring in medical contexts. Statistical Methods in Medical Research 2003 12 2 147 170 2-s2.0-0037345165
10. Hwang G. M., Mahoney P. J., James J. H., Lin G. C., Berro A. D., Keybl M. A., Goedecke D. M., Mathieu J. J., Wilson T., A model-based tool to predict the propagation of infectious disease via airports. Travel Medicine and Infectious Disease 2012 10 1 32 42 2-s2.0-84858797070 10.1016/j.tmaid.2011.12.003
11. Louz D., Bergmans H. E., Loos B. P., Hoeben R. C., Emergence of viral diseases: mathematical modeling as a tool for infection control, policy and decision making. Critical Reviews in Microbiology 2010 36 3 195 211 2-s2.0-77954738338 10.3109/10408411003604619
12. Fajardo-Dolci G. E., Hernández-Torres F., Sanacruz-Varela J., Epidemiological profile of mortality due to human influenza A (H1N1) in Mexico. Salud Pública de México 2009 51 361 371
13. Serna-Ojeda J. A., Castanon-Gonzalez J. A., Macias-Hernandez A. E., Survey about responsiveness of third level hospitals to a medical disaster: after pandemic influenza in Mexico. Gaceta Médica de México 2012 148 227 235
14. Reyna O. P., Plenge F. O., Benavides J. G., A new virus A-H1N1, a new pandemic: a continuing risk to a globalized humanity. Acta Médica Peruana 2009 26 97 130
15. Paño-Pardo J. R., Viasus D., Pachón J., Campins A., López-Medrano F., Villoslada A., Gutiérrez-Cuadra M., Pumarola T., Del Toro M. D., Oteo J. A., Martínez-Montauti J., Gutiérrez-Aroca J., Segura F., Carratalà J., Pandemic 2009 A(H1N1) infection requiring hospitalization of elderly Spanish adults. Journal of the American Geriatrics Society 2012 60 4 740 744 2-s2.0-84859827808 10.1111/j.1532-5415.2012.03903.x
16. Arino J., Brauer F., Van Den Driessche P., Watmough J., Wu J., Simple models for containment of a pandemic. Journal of the Royal Society Interface 2006 3 8 453 457 2-s2.0-33846856860 10.1098/rsif.2006.0112
17. Brock W. A., Distinguishing random and deterministic systems: abridged version. Journal of Economic Theory 1986 40 1 168 195 2-s2.0-46149128981
18. Polanco C., Samaniego J. L., Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models. Acta Biochimica Polonica 2009 56 1 167 176 2-s2.0-67249124036
19. Sambo F., Montes de Oca M. A., Di Camillo B., Toffolo G., Stützle T., MORE: mixed optimization for reverse engineering'-an application to modeling biological networks response via sparse systems of nonlinear differential equations. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2012 9 1459 1471
20. Resch B., Hidden Markov Models. A tutorial for the course computational intelligence. Signal processing and speech communication laboratory, http://speech.tifr.res.in/tutorials/hmmTutorialBarbaraExercises.pdf