Author:
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
World Health Organization, 2010. Dengue and Dengue Hemorrhagic Fever Fact Sheet. Available at: http://www.who.int/mediacentre/factsheets/fs117/en/index.html. Accessed July 2010.
-
2.
MacKenzie JS, Gubler DJ, Peterson LR, 2004. Emerging flaviviruses: the spread and resurgence of Japanese encephalitis, West Nile, and dengue viruses. Nat Med 12: s98–s109.
-
3.
McKenzie FE, 2000. Why model malaria? Parasitol Today 16: 511–516.
-
4.
McKenzie FE, Samba EM, 2004. The role of mathematical modeling in evidence-based malaria control. Am J Trop Med Hyg 71: 94–96.
-
6.
Chitnis N, Hyman JM, Cushing JM, 2008. Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model. Bull Math Biol 70: 1272–1296.
-
7.
Focks DA, Daniels E, Haile DG, Keesling JE, 1995. A simulation model of the epidemiology of urban dengue fever: literature analysis, model development, preliminary validation, and samples of simulation results. Am J Trop Med Hyg 53: 489–506.
-
8.
Focks DA, Haile DG, Daniels E, Mount GA, 1993. Dynamic life table model for Aedes aegypti (Diptera, Culicidae): analysis of the literature and model development. J Med Entomol 30: 1003–1017.
-
9.
Blower SM, Dowlatabadi H, 1994. Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example. Int Stat Rev 62: 229–243.
-
10.
Morrison AC, Minnick SL, Rocha C, Forshey BM, Stoddard ST, Getis A, Focks DA, Russell KL, Olson JG, Blair PJ, Watts DM, Sihuincha M, Scott TW, Kochel TJ, 2010. Epidemiology of dengue virus in Iquitos, Peru 1999 to 2005: interepidemic and epidemic patterns of transmission. PLoS Negl Trop Dis 4: e670.
-
11.
Morrison AC, Gray K, Getis A, Astete H, Sihuincha M, Focks D, Watts D, Stancil JD, Olson JG, Blair P, Scott TW, 2004. Temporal and geographic patterns of Aedes aegypti (Diptera: Culicidae) production in Iquitos, Peru. J Med Entomol 41: 1123–1142.
-
12.
Pan American Health Organization, 1998. Health in the Americas, Vol. II. Washington, DC: PAHO Scientific Publication.
-
13.
Kendall BE, Briggs CJ, Murdoch WW, Turchin P, Ellner SP, McCauley E, Nisbet RM, Wood SN, 1999. Why do populations cycle? A synthesis of statistical and mechanistic modeling approaches. Ecology 80: 1789–1805.
-
14.
Bartley LM, Donnelly CA, Garnett GP, 2002. The seasonal pattern of dengue in endemic areas: mathematical models of mechanisms. Trans R Soc Trop Med Hyg 96: 387–397.
-
15.
de Moor PP, Steffens FE, 1970. Computer-simulated model of an arthropod-borne virus transmission cycle, with special reference to chikungunya virus. Trans R Soc Trop Med Hyg 64: 927–934.
-
16.
Hancock PA, Godfray HCJ, 2007. Application of the lumped age-class technique to studying the dynamics of malaria-mosquito-human interactions. Malar J 6: 98.
-
17.
Jetten TH, Martens WJM, Takken W, 1996. Model simulations to estimate malaria risk under climate change. J Med Entomol 33: 361–371.
-
18.
Massad E, Forattini OP, 1998. Modelling the temperature sensitivity of some physiological parameters of epidemiologic significance. Ecosyst Health 4: 119–129.
-
19.
Ruan SG, Xiao DM, Beier JC, 2008. On the delayed Ross-Macdonald model for malaria transmission. Bull Math Biol 70: 1098–1114.
-
20.
Scott TW, McLean RG, Francy DB, Card CS, 1983. A simulation model for the vector-host transmission system of a mosquito-borne avian virus, Turlock (Bunyaviridae). J Med Entomol 20: 625–640.
-
21.
Yé Y, Sauerborn R, Séraphin S, Hoshen M, 2007. Using modelling to assess the risk of malarial infection during the dry season, on a local scale in an endemic area of rural Burkina Faso. Ann Trop Med Parasitol 101: 375–389.
-
22.
Supriatna AK, Soewono E, van Gils SA, 2008. A two-age-classes dengue transmission model. Math Biosci 216: 114–121.
-
23.
Codeco CT, Luz PM, Struchiner CJ, 2004. Risk assessment of yellow fever urbanization in Rio de Janeiro, Brazil. Trans R Soc Trop Med Hyg 98: 702–710.
-
24.
Freeman J, Laserson KF, Petralanda I, Spielman A, 1999. Effect of chemotherapy on malaria transmission among Yanomani Amerindians: simulated consequences of placebo treatment. Am J Trop Med Hyg 60: 774–780.
-
25.
Ruiz D, Poveda G, Vélez ID, Quiñones ML, Rúa GL, Velásquez LE, Zuluaga JS, 2006. Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System. Malar J 5: 66.
-
26.
Santos LBL, Costa MC, Pinho STR, Andrade RFS, Barreto FR, Teixeira MG, Barreto ML, 2009. Periodic forcing in a three-level cellular automata model for a vector-transmitted disease. Phys Rev E Stat Nonlin Soft Matter Phys 80: 016102.
-
27.
Shaman J, 2007. Amplification due to spatial clustering in an individual-based model of mosquito-avian arbovirus transmission. Trans R Soc Trop Med Hyg 101: 469–483.
-
28.
Harrington LC, Buonaccorsi JP, Edman JD, Costero A, Kittayapong P, Clark GG, Scott TW, 2001. Analysis of survival of young and old Aedes aegypti (Diptera: Culicidae) from Puerto Rico and Thailand. J Med Entomol 38: 537–547.
-
29.
Harrington LC, Vermeylen F, Jones JJ, Kitthawee S, Sithiprasasna R, Edman JD, Scott TW, 2008. Age-dependent survival of the dengue vector Aedes aegypti (Diptera: Culicidae) demonstrated by simultaneous release-recapture of different age cohorts. J Med Entomol 45: 307–313.
-
30.
Styer LM, Carey JR, Wang JL, Scott TW, 2007. Mosquitoes do senesce: departure from the paradigm of constant mortality. Am J Trop Med Hyg 76: 111–117.
-
31.
Styer LM, Minnick SL, Sun AK, Scott TW, 2007. Mortality and reproductive dynamics of Aedes aegypti (Diptera: Culicidae) fed human blood. Vector Borne Zoonotic Dis 7: 86–98.
-
32.
Muir LE, Kay BH, 1998. Aedes aegypti survival and dispersal estimated by mark-release-recapture in northern Australia. Am J Trop Med Hyg 58: 277–282.
-
33.
Futami K, Sonye G, Akweywa P, Kaneko S, Minakawa N, 2008. Diving behavior in Anopheles gambiae (Diptera: Culicidae): avoidance of a predacious wolf spider (Araneae: Lycosidae) in relation to life stage and water depth. J Med Entomol 45: 1050–1056.
-
34.
Lee DK, Bhatkar AP, Vinson SB, Olson JK, 1994. Impact of foraging red imported fire ants (Solenopsis invicta) (Hymenoptera, Formicidae) on Psorophora columbiae eggs. J Am Mosq Control Assoc 10: 163–173.
-
35.
Roitberg BD, Mondor EB, Tyerman JGA, 2003. Pouncing spider, flying mosquito: blood acquisition increases predation risk in mosquitoes. Behav Ecol 14: 736–740.
-
36.
Ellis AM, 2008. Incorporating density dependence into the oviposition preference —offspring performance hypothesis. J Anim Ecol 77: 247–256.
-
37.
Legros M, Lloyd AL, Huang Y, Gould F, 2009. Density-dependent intraspecific competition in the larval stage of Aedes aegypti (Diptera: Culicidae): revisiting the current paradigm. J Med Entomol 46: 409–419.
-
38.
Leonard PM, Juliano SA, 1995. Effect of leaf litter on fitness and population performance of the tree hole mosquito Aedes triseriatus. Ecol Entomol 20: 125–136.
-
39.
Reiskind MH, Zarrabi AA, Lounibos LP, 2010. Invasive leaf resources alleviate density dependence in the invasive mosquito, Aedes albopictus. Biol Invasions 12: 2319–2328.
-
40.
Aldemir A, Bedir H, Demirci B, Alten B, 2010. Biting activity of mosquito species (Diptera: Culicidae) in the Turkey–Armenia border area, Ararat Valley, Turkey. J Med Entomol 47: 22–27.
-
41.
Rodríguez M, Pérez L, Caicedo JC, Prieto G, Arroyo JA, Kaur H, Suárez-Mutis M, de La Hoz F, Lines J, Alexander N, 2009. Composition and biting activity of Anopheles (Diptera: Culicidae) in the Amazon region of Colombia. J Med Entomol 46: 307–315.
-
42.
Afolabi BM, Amajoh CN, Adewole TA, Salako LA, 2006. Seasonal and temporal variations in the population and biting habit of mosquitoes on the Atlantic coast of Lagos, Nigeria. Med Princ Pract 15: 200–208.
-
43.
Barnard DR, Posey KH, Smith D, Schreck CE, 1998. Mosquito density, biting rate and cage size effects on repellent tests. Med Vet Entomol 12: 39–45.
-
44.
Michael E, Ramaiah KD, Hoti SL, Barker G, Paul MR, Yuvaraj J, Das PK, Grenfell BT, Bundy DA, 2001. Quantifying mosquito biting patterns on humans by DNA fingerprinting of bloodmeals. Am J Trop Med Hyg 65: 722–728.
-
45.
Scott TW, Clark GG, Lorenz LH, Amerasinghe PH, Reiter P, Edman JD, 1993. Detection of multiple blood-feeding in Aedes aegypti (Diptera, Culicidae) during a single gonotrophic cycle using a histologic technique. J Med Entomol 30: 94–99.
-
46.
Scott TW, Githeko AK, Fleisher A, Harrington LC, Yan G, 2006. DNA profiling of human blood in anophelines from lowland and highland sites in western Kenya. Am J Trop Med Hyg 75: 231–237.
-
47.
Xu C, Legros M, Gould F, Lloyd AL, 2010. Understanding uncertainties in model-based predictions of Aedes aegypti population dynamics. PLoS Negl Trop Dis 4: e830.
-
48.
Chowell G, Diaz-Dueñas P, Miller JC, Alcazar-Velazco A, Hyman JM, Fenimore PW, Castillo-Chavez C, 2007. Estimation of the reproduction number of dengue fever from spatial epidemic data. Math Biosci 208: 571–589.
| Past two years | Past Year | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 55 | 55 | 21 |
| Full Text Views | 389 | 109 | 0 |
| PDF Downloads | 135 | 29 | 0 |
Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control
Alicia M. Ellis
Alicia M. Ellis
Department of Entomology, University of California Davis, Davis, California; Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Department of Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, Florida; Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, Florida
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Andres J. Garcia
Andres J. Garcia
Department of Entomology, University of California Davis, Davis, California; Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Department of Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, Florida; Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, Florida
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Dana A. Focks
Dana A. Focks
Department of Entomology, University of California Davis, Davis, California; Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Department of Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, Florida; Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, Florida
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Amy C. Morrison
Amy C. Morrison
Department of Entomology, University of California Davis, Davis, California; Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Department of Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, Florida; Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, Florida
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Thomas W. Scott
Thomas W. Scott
Department of Entomology, University of California Davis, Davis, California; Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Department of Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, Florida; Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, Florida
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Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority.
Author Notes
Authors' addresses: Alicia M. Ellis and Thomas W. Scott, Department of Entomology, University of California Davis, Davis, CA, and the Fogarty International Center, National Institutes of Health, Bethesda, MD, E-mails: alicia.m.ellis@gmail.com and twscott@caes.ucdavis.edu. Andres J. Garcia, Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, FL, E-mail: andygarcia@gmail.com. Dana A. Focks, Department of Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, FL, E-mail: DAFocks@id-analysis.com. Amy C. Morrison, Department of Entomology, University of California Davis, Davis, CA, and Naval Medical Research Center Detachment, Washington, DC, E-mail: amy.aegypti@gmail.com.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
World Health Organization, 2010. Dengue and Dengue Hemorrhagic Fever Fact Sheet. Available at: http://www.who.int/mediacentre/factsheets/fs117/en/index.html. Accessed July 2010.
-
2.
MacKenzie JS, Gubler DJ, Peterson LR, 2004. Emerging flaviviruses: the spread and resurgence of Japanese encephalitis, West Nile, and dengue viruses. Nat Med 12: s98–s109.
-
3.
McKenzie FE, 2000. Why model malaria? Parasitol Today 16: 511–516.
-
4.
McKenzie FE, Samba EM, 2004. The role of mathematical modeling in evidence-based malaria control. Am J Trop Med Hyg 71: 94–96.
-
6.
Chitnis N, Hyman JM, Cushing JM, 2008. Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model. Bull Math Biol 70: 1272–1296.
-
7.
Focks DA, Daniels E, Haile DG, Keesling JE, 1995. A simulation model of the epidemiology of urban dengue fever: literature analysis, model development, preliminary validation, and samples of simulation results. Am J Trop Med Hyg 53: 489–506.
-
8.
Focks DA, Haile DG, Daniels E, Mount GA, 1993. Dynamic life table model for Aedes aegypti (Diptera, Culicidae): analysis of the literature and model development. J Med Entomol 30: 1003–1017.
-
9.
Blower SM, Dowlatabadi H, 1994. Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example. Int Stat Rev 62: 229–243.
-
10.
Morrison AC, Minnick SL, Rocha C, Forshey BM, Stoddard ST, Getis A, Focks DA, Russell KL, Olson JG, Blair PJ, Watts DM, Sihuincha M, Scott TW, Kochel TJ, 2010. Epidemiology of dengue virus in Iquitos, Peru 1999 to 2005: interepidemic and epidemic patterns of transmission. PLoS Negl Trop Dis 4: e670.
-
11.
Morrison AC, Gray K, Getis A, Astete H, Sihuincha M, Focks D, Watts D, Stancil JD, Olson JG, Blair P, Scott TW, 2004. Temporal and geographic patterns of Aedes aegypti (Diptera: Culicidae) production in Iquitos, Peru. J Med Entomol 41: 1123–1142.
-
12.
Pan American Health Organization, 1998. Health in the Americas, Vol. II. Washington, DC: PAHO Scientific Publication.
-
13.
Kendall BE, Briggs CJ, Murdoch WW, Turchin P, Ellner SP, McCauley E, Nisbet RM, Wood SN, 1999. Why do populations cycle? A synthesis of statistical and mechanistic modeling approaches. Ecology 80: 1789–1805.
-
14.
Bartley LM, Donnelly CA, Garnett GP, 2002. The seasonal pattern of dengue in endemic areas: mathematical models of mechanisms. Trans R Soc Trop Med Hyg 96: 387–397.
-
15.
de Moor PP, Steffens FE, 1970. Computer-simulated model of an arthropod-borne virus transmission cycle, with special reference to chikungunya virus. Trans R Soc Trop Med Hyg 64: 927–934.
-
16.
Hancock PA, Godfray HCJ, 2007. Application of the lumped age-class technique to studying the dynamics of malaria-mosquito-human interactions. Malar J 6: 98.
-
17.
Jetten TH, Martens WJM, Takken W, 1996. Model simulations to estimate malaria risk under climate change. J Med Entomol 33: 361–371.
-
18.
Massad E, Forattini OP, 1998. Modelling the temperature sensitivity of some physiological parameters of epidemiologic significance. Ecosyst Health 4: 119–129.
-
19.
Ruan SG, Xiao DM, Beier JC, 2008. On the delayed Ross-Macdonald model for malaria transmission. Bull Math Biol 70: 1098–1114.
-
20.
Scott TW, McLean RG, Francy DB, Card CS, 1983. A simulation model for the vector-host transmission system of a mosquito-borne avian virus, Turlock (Bunyaviridae). J Med Entomol 20: 625–640.
-
21.
Yé Y, Sauerborn R, Séraphin S, Hoshen M, 2007. Using modelling to assess the risk of malarial infection during the dry season, on a local scale in an endemic area of rural Burkina Faso. Ann Trop Med Parasitol 101: 375–389.
-
22.
Supriatna AK, Soewono E, van Gils SA, 2008. A two-age-classes dengue transmission model. Math Biosci 216: 114–121.
-
23.
Codeco CT, Luz PM, Struchiner CJ, 2004. Risk assessment of yellow fever urbanization in Rio de Janeiro, Brazil. Trans R Soc Trop Med Hyg 98: 702–710.
-
24.
Freeman J, Laserson KF, Petralanda I, Spielman A, 1999. Effect of chemotherapy on malaria transmission among Yanomani Amerindians: simulated consequences of placebo treatment. Am J Trop Med Hyg 60: 774–780.
-
25.
Ruiz D, Poveda G, Vélez ID, Quiñones ML, Rúa GL, Velásquez LE, Zuluaga JS, 2006. Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System. Malar J 5: 66.
-
26.
Santos LBL, Costa MC, Pinho STR, Andrade RFS, Barreto FR, Teixeira MG, Barreto ML, 2009. Periodic forcing in a three-level cellular automata model for a vector-transmitted disease. Phys Rev E Stat Nonlin Soft Matter Phys 80: 016102.
-
27.
Shaman J, 2007. Amplification due to spatial clustering in an individual-based model of mosquito-avian arbovirus transmission. Trans R Soc Trop Med Hyg 101: 469–483.
-
28.
Harrington LC, Buonaccorsi JP, Edman JD, Costero A, Kittayapong P, Clark GG, Scott TW, 2001. Analysis of survival of young and old Aedes aegypti (Diptera: Culicidae) from Puerto Rico and Thailand. J Med Entomol 38: 537–547.
-
29.
Harrington LC, Vermeylen F, Jones JJ, Kitthawee S, Sithiprasasna R, Edman JD, Scott TW, 2008. Age-dependent survival of the dengue vector Aedes aegypti (Diptera: Culicidae) demonstrated by simultaneous release-recapture of different age cohorts. J Med Entomol 45: 307–313.
-
30.
Styer LM, Carey JR, Wang JL, Scott TW, 2007. Mosquitoes do senesce: departure from the paradigm of constant mortality. Am J Trop Med Hyg 76: 111–117.
-
31.
Styer LM, Minnick SL, Sun AK, Scott TW, 2007. Mortality and reproductive dynamics of Aedes aegypti (Diptera: Culicidae) fed human blood. Vector Borne Zoonotic Dis 7: 86–98.
-
32.
Muir LE, Kay BH, 1998. Aedes aegypti survival and dispersal estimated by mark-release-recapture in northern Australia. Am J Trop Med Hyg 58: 277–282.
-
33.
Futami K, Sonye G, Akweywa P, Kaneko S, Minakawa N, 2008. Diving behavior in Anopheles gambiae (Diptera: Culicidae): avoidance of a predacious wolf spider (Araneae: Lycosidae) in relation to life stage and water depth. J Med Entomol 45: 1050–1056.
-
34.
Lee DK, Bhatkar AP, Vinson SB, Olson JK, 1994. Impact of foraging red imported fire ants (Solenopsis invicta) (Hymenoptera, Formicidae) on Psorophora columbiae eggs. J Am Mosq Control Assoc 10: 163–173.
-
35.
Roitberg BD, Mondor EB, Tyerman JGA, 2003. Pouncing spider, flying mosquito: blood acquisition increases predation risk in mosquitoes. Behav Ecol 14: 736–740.
-
36.
Ellis AM, 2008. Incorporating density dependence into the oviposition preference —offspring performance hypothesis. J Anim Ecol 77: 247–256.
-
37.
Legros M, Lloyd AL, Huang Y, Gould F, 2009. Density-dependent intraspecific competition in the larval stage of Aedes aegypti (Diptera: Culicidae): revisiting the current paradigm. J Med Entomol 46: 409–419.
-
38.
Leonard PM, Juliano SA, 1995. Effect of leaf litter on fitness and population performance of the tree hole mosquito Aedes triseriatus. Ecol Entomol 20: 125–136.
-
39.
Reiskind MH, Zarrabi AA, Lounibos LP, 2010. Invasive leaf resources alleviate density dependence in the invasive mosquito, Aedes albopictus. Biol Invasions 12: 2319–2328.
-
40.
Aldemir A, Bedir H, Demirci B, Alten B, 2010. Biting activity of mosquito species (Diptera: Culicidae) in the Turkey–Armenia border area, Ararat Valley, Turkey. J Med Entomol 47: 22–27.
-
41.
Rodríguez M, Pérez L, Caicedo JC, Prieto G, Arroyo JA, Kaur H, Suárez-Mutis M, de La Hoz F, Lines J, Alexander N, 2009. Composition and biting activity of Anopheles (Diptera: Culicidae) in the Amazon region of Colombia. J Med Entomol 46: 307–315.
-
42.
Afolabi BM, Amajoh CN, Adewole TA, Salako LA, 2006. Seasonal and temporal variations in the population and biting habit of mosquitoes on the Atlantic coast of Lagos, Nigeria. Med Princ Pract 15: 200–208.
-
43.
Barnard DR, Posey KH, Smith D, Schreck CE, 1998. Mosquito density, biting rate and cage size effects on repellent tests. Med Vet Entomol 12: 39–45.
-
44.
Michael E, Ramaiah KD, Hoti SL, Barker G, Paul MR, Yuvaraj J, Das PK, Grenfell BT, Bundy DA, 2001. Quantifying mosquito biting patterns on humans by DNA fingerprinting of bloodmeals. Am J Trop Med Hyg 65: 722–728.
-
45.
Scott TW, Clark GG, Lorenz LH, Amerasinghe PH, Reiter P, Edman JD, 1993. Detection of multiple blood-feeding in Aedes aegypti (Diptera, Culicidae) during a single gonotrophic cycle using a histologic technique. J Med Entomol 30: 94–99.
-
46.
Scott TW, Githeko AK, Fleisher A, Harrington LC, Yan G, 2006. DNA profiling of human blood in anophelines from lowland and highland sites in western Kenya. Am J Trop Med Hyg 75: 231–237.
-
47.
Xu C, Legros M, Gould F, Lloyd AL, 2010. Understanding uncertainties in model-based predictions of Aedes aegypti population dynamics. PLoS Negl Trop Dis 4: e830.
-
48.
Chowell G, Diaz-Dueñas P, Miller JC, Alcazar-Velazco A, Hyman JM, Fenimore PW, Castillo-Chavez C, 2007. Estimation of the reproduction number of dengue fever from spatial epidemic data. Math Biosci 208: 571–589.
| Past two years | Past Year | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 55 | 55 | 21 |
| Full Text Views | 389 | 109 | 0 |
| PDF Downloads | 135 | 29 | 0 |