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Instituto Nacional de Salud Pública

2004, Number 3

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salud publica mex 2004; 46 (3)

The logistic model for predicting the non-gonoactive Aedes aegypti females

Reyes-Villanueva F, Rodríguez-Pérez MA

Language: English
References: 23
Page: 234-240
PDF size: 140.89 Kb.


ABSTRACT

Objetive. To estimate, using logistic regression, the likelihood of occurrence of a non-gonoactive Aedes aegypti female, previously fed human blood, with relation to body size and collection method. Material and Methods. This study was conducted in Monterrey, Mexico, between 1994 and 1996. Ten samplings of 60 mosquitoes of Ae aegypti femaleswere carried out in three dengue endemic areas: six of biting females, two of emerging mosquitoes, and two of indoor resting females. Gravid females, as well as those with blood in the gut were removed. Mosquitoes were taken to the laboratory and engorged on human blood. After 48 hours, ovaries were dissected to register whether they were gonoactive or non-gonoactive. Wing-length in mm was an indicator for body size. The logistic regression model was used to assess the likelihood of non-gonoactivity, as a binary variable, in relation to wing-length and collection method. Results. Of the 600 females, 164 (27%) remained non-gonoactive, with a wing-length range of 1.9-3.2 mm, almost equal to that of all females (1.8-3.3 mm). The logistic regression model showed a significant likelihood of a female remaining non-gonoactive (Y=1). The collection method did not influence the binary response, but there was an inverse relationship between non-gonoactivity and wing-length. Conclusions. Dengue vector populations from Monterrey, Mexico display a wide-range body size. Logistic regression was a useful tool to estimate the likelihood for an engorgedfemale to remain non-gonoactive. The necessity for a second blood meal is present in any female, but small mosquitoes are more likely to bite again within a 2-day interval, in order to attain egg maturation.


REFERENCES

  1. Sumanochitrapon W, Strickman D, Sithiprasasna R, Kittayapong P, Innis BL. Effect of size and geographic origin of Aedes aegypti on oral infection with dengue-2 virus. Am J Trop Med Hyg 1998;58:283-286.

  2. Martínez-Ibarra JA, Rodríguez MH, Arredondo-Jiménez JI, Yuval B. Influence of plant abundance on nectar feeding by Aedes aegypti (Diptera: Culicidae) in southern México. J Med Entomol 1997;34: 589-593.

  3. Scott TW, Naksathit A, Day JF, Kittayapong P, Edman JD. A fitness advantage for Aedes aegypti and the viruses it transmits when females fed only on human blood. Am J Trop Med Hyg 1997;57:235-239.

  4. Costero A, Edman JD, Clark GG, Scott TW. A life table study of Aedes aegypti (Diptera: Culicidae) in Puerto Rico fed only human blood versus blood plus sugar. J Med Entomol 1998;35:809-813.

  5. Christophers SR. The development of the egg follicle in anophelines. Paludism 1911;2:73-88.

  6. World Health Organization. Manual on practical entomology in malaria. Part II. Methods and techniques. Ginebra WHO; 1975. (WHO Offset Publication 13).

  7. Clements AN. The biology of mosquitoes. Vol. 1. Development, nutrition and reproduction. London: Chapman & Hall; 1992.

  8. MacDonald WW. Aedes aegypti in Malaya. II. Larval and adult biology. Ann Trop Med Parasitol 1956;50:399-414.

  9. Feinsod FM, Spielman A. Nutrient-mediated juvenile hormone secretion in mosquitoes. J Insect Physiol 1980;26:113-117.

  10. Gillies MT. The recognition of age-groups within populations of Anopheles gambiae by the pre-gravid rate and sporozoite rate. Ann Trop Med Parasitol 1954;49:320-325.

  11. Gillies MT. The pre-gravid phase of ovarian development in Anopheles funestus. Ann Trop Med Parasitol 1955;49:320-325.

  12. Washino RK. The physiological ecology of gonotrophic dissociation and related phenomena in mosquitoes. J Med Entomol 1977;13:381-388.

  13. Lyimo EO, Takken W. Effects of adult body size on fecundity and the pre-gravid rate of Anopheles gambiae s.l. females in Tanzania. Med Vet Entomol 1993;7:328-332.

  14. Instituto Nacional de Estadística, Geografía e Informática. Carta Geográfica del Estado de Nuevo León. México DF: Gobierno Federal, Secretaría de Programación y Presupuesto; 1986.

  15. Salas-Luévano M, Reyes-Villanueva F. Variación estacional de las poblaciones de Aedes aegypti en Monterrey, México. Salud Publica Mex 1994;36:385-392.

  16. Xue RD, Edman JD, Scott TW. Age and structure effects on blood meal size and multiple blood feeding by Aedes aegypti (Diptera: Culicidae). J Med Entomol 1995;32:471-474.

  17. Zar JH. Biostatistical analysis. Prentice-Hall; 1974.

  18. Schlotzauer SD, Littel RC. SAS system for elementary analysis. Cary (NC); SAS Institute; 1987.

  19. SAS. Logistic regression examples using the SAS system, version 6. Cary (NC): SAS Institute; 1995.

  20. Hosmer DW, Lemeshow S. Applied logistic regression. John Wiley & Sons; 1989.

  21. Hogg JC, Thompson MC, Hurd H. Comparative fecundity and associated factors for two sibling species of the Anopheles gambiae complex occurring sympatrically in The Gambia. Med Vet Entomol 1996;10:385-391

  22. Naksathit AT, Edman JD, Scott TW. Amounts of glycogen, lipid, and sugar in adult female Aedes aegypti (Diptera: Culicidae) fed sucrose. J Med Entomol 1999,36:8-12.

  23. Hawley WA. The biology of Aedes albopictus. J Am Mosq Control Assoc 1988;(Suppl 1):40.




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