ANALYSIS OF THE BASIC REPRODUCTION NUMBER FROM THE INITIAL GROWTH PHASE OF THE OUTBREAK IN DISEASES CAUSED BY VECTORS

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Citações na Scopus
Tipo de produção
conferenceObject
Data de publicação
2014
Título da Revista
ISSN da Revista
Título do Volume
Editora
WORLD SCIENTIFIC PUBL CO PTE LTD
Citação
BIOMAT 2013: INTERNATIONAL SYMPOSIUM ON MATHEMATICAL AND COMPUTATIONAL BIOLOGY, p.340-351, 2014
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
The basic reproduction number, R-0, is defined as the expected number of secondary cases of a disease produced by a single infection in a completely susceptible population. The value of R-0 can be estimated in several ways, for example, of the stability analysis of a compartmental model, through the matrix of next generation, etc. In this work we studied the method for estimating R-0 from the initial growth phase of the outbreak. Some authors proposed different methods for estimating the value of (R)0 using the initial growth phase of the outbreak without assuming exponential growth of cases, which is suggested in most studies. We used the method proposed by Macdonald and studied by Massad et. al.(2010)(1) and the method proposed by Nishiura(2010)(2). Massad et. al.(2010)(1) studied the basic reproduction number proposed by Macdonald's, which it was divided in two components: the vector-to-human component (TV-H) and the human-to-vector component (TH-V), R-0 is the product of those two components. Nishiura(2010)(2) presented a correction of the actual reproduction number (R-a), he showed through this correction that the basic reproduction number and actual reproduction number are equal, then he offered a framework for estimating R-0. Our objective is to evaluate which technique best estimates the basic reproduction number applying them to diseases caused by vectors, in this particular case we used data of dengue.
Palavras-chave
basic reproduction number, dengue, mathematical model
Referências
  1. Aldstadt J, 2012, TROP MED INT HEALTH, V17, P1076, DOI 10.1111/j.1365-3156.2012.03040.x
  2. van den Driessche P, 2002, MATH BIOSCI, V180, P29, DOI 10.1016/S0025-5564(02)00108-6
  3. [Anonymous], 2008, MS, V7
  4. Bennett SN, 2003, MOL BIOL EVOL, V20, P1650, DOI 10.1093/milbev/msg182
  5. Chowell G, 2008, PHYS LIFE REV, V5, P50, DOI 10.1016/j.plrev.2007.12.001
  6. Coura J.R., 2005, GUANABARA KOOGAN
  7. Coutinho FAB, 2006, B MATH BIOL, V68, P2263, DOI 10.1007/s11538-006-9108-6
  8. DIEKMANN O, 1990, J MATH BIOL, V28, P365
  9. Favier C., 2006, TROP MED INT HEALTH, VII, P343
  10. Gubler D. J., 1995, EMERGING INFECT DIS, V1
  11. Guzman A, 2010, INT J ANTIMICROB AG, V36, pS40, DOI 10.1016/j.ijantimicag.2010.06.018
  12. Heffernan JM, 2005, J ROY SOC INTERFACE, V2, P281, DOI 10.1098/rsif.2005.0042
  13. Lopez LF, 2002, CR BIOL, V325, P1073, DOI 10.1016/S1631-0691(02)01534-2
  14. MACDONALD G, 1952, Trop Dis Bull, V49, P813
  15. Massad E, 2003, REV SAUDE PUBL, V37, P477, DOI [10.1590/S0034-89102003000400013, 10.1590/s0034-89102003000400013]
  16. Massad E, 2010, TROP MED INT HEALTH, V15, P120, DOI 10.1111/j.1365-3156.2009.02413.x
  17. Nishiura N., 2010, J ENV RES PUBLIC HLT, V7, P291
  18. Roberts MG, 2003, P ROY SOC B-BIOL SCI, V270, P1359, DOI 10.1098/rspb.2003.2339
  19. Teixeira MG, 2009, BMJ-BRIT MED J, V339, DOI 10.1136/bmj.b4338
  20. White LF, 2008, STAT MED, V27, P2999, DOI 10.1002/sim.3136
  21. White PJ, 2006, AIDS, V20, P1898, DOI 10.1097/01.aids.0000244213.23574.fa