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Titolo:
QUANTIFYING THE INTRINSIC TRANSMISSION DYNAMICS OF TUBERCULOSIS
Autore:
PORCO TC; BLOWER SM;
Indirizzi:
SAN FRANCISCO DEPT PUBL HLTH,25 VAN NESS AVE,SUITE 710 SAN FRANCISCO CA 94102 UNIV CALIF SAN FRANCISCO,DEPT MICROBIOL & IMMUNOL SAN FRANCISCO CA 94143
Titolo Testata:
Theoretical population biology (Print)
fascicolo: 2, volume: 54, anno: 1998,
pagine: 117 - 132
SICI:
0040-5809(1998)54:2<117:QTITDO>2.0.ZU;2-3
Fonte:
ISI
Lingua:
ENG
Soggetto:
SENSITIVITY ANALYSIS; EXOGENOUS REINFECTION; COMPUTER-MODELS; INPUT VARIABLES; EPIDEMICS; DISEASE;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
60
Recensione:
Indirizzi per estratti:
Citazione:
T.C. Porco e S.M. Blower, "QUANTIFYING THE INTRINSIC TRANSMISSION DYNAMICS OF TUBERCULOSIS", Theoretical population biology (Print), 54(2), 1998, pp. 117-132

Abstract

Previously we have formulated transmission models of untreated tuberculosis epidemics ( Blower et al., Nature, Medicine 1 (1995), 815-821);in this paper, we present time-dependent uncertainty and sensitivity analyses in order to quantitatively understand the transmission dynamics of tuberculosis epidemics in the absence of treatment. The time-dependent uncertainty analysis enabled us to evaluate the variability in the epidemiological outcome variables of the model during the progression of a tuberculosis epidemic. Calculated values (from the uncertainty analysis) for the disease incidence, disease prevalence, and mortality rates were approximately consistent with historical data. The time-dependent sensitivity analysis revealed that only a few of the model'sinput parameters significantly affected the severity of a tuberculosis epidemic; these parameters were the disease reactivation rate, the fraction of infected individuals who develop tuberculosis soon after infection, the number of individuals that an infectious individual infects per year, the disease death rate, and the population recruitment rate. Our analysis demonstrates that it is possible to improve our understanding of the behavior of tuberculosis epidemics by applying time-dependent uncertainty and sensitivity analysis to a transmission model, (C) 1998 Academic Press.

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Documento generato il 04/04/20 alle ore 02:48:31