Skip to main content

Advertisement

SpringerLink
Log in

Impact of combined vector-control and vaccination strategies on transmission dynamics of dengue fever: a model-based analysis

  • Published:
Health Care Management Science Aims and scope Submit manuscript

Abstract

Dengue fever is a vector-borne disease prevalent in tropical and subtropical regions. It is an important public health problem with a considerable and often under-valued disease burden in terms of frequency, cost and quality-of-life. Recent literature reviews have documented the development of mathematical models of dengue fever both to identify important characteristics for future model development as well as to assess the impact of dengue control interventions. Such reviews highlight the importance of short-term cross-protection; antibody-dependent enhancement; and seasonality (in terms of both favourable and unfavourable conditions for mosquitoes). The compartmental model extends work by Bartley (2002) and combines the following factors: seasonality, age-structure, consecutive infection by all four serotypes, cross-protection and immune enhancement, as well as combined vector-host transmission. The model is used to represent dengue transmission dynamics using parameters appropriate for Thailand and to assess the potential impact of combined vector-control and vaccination strategies including routine and catch-up vaccination strategies on disease dynamics. When seasonality and temporary cross-protection between serotypes are included, the model is able to approximate the observed incidence of dengue fever in Thailand. We find vaccination to be the most effective single intervention, albeit with imperfect efficacy (30.2 %) and limited duration of protection. However, in combination, control interventions and vaccination exhibit a marked impact on dengue fever transmission. This study shows that an imperfect vaccine can be a useful weapon in reducing disease spread within the community, although it will be most effective when promoted as one of several strategies for combating dengue fever transmission.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. WHO (2011) Working to overcome the global impact of neglected tropical diseases Update 2011. WHO/HTM/NTD/2011.3 (World Health Organization)

  2. Gubler DJ (1998) Dengue and dengue hemorrhagic fever. Clin Microbiol Rev 11(3):480–496

    Google Scholar 

  3. Gubler DJ (2002) Epidemic dengue/dengue hemorrhagic fever as a public health, social and economic problem in the 21st century. Trends Microbiol 10(2):100–103

    Article  Google Scholar 

  4. WHO (2009) Dengue: Guidelines for Diagnosis, Treatment, Prevention and Control. WHO/HTM/NTD/DEN/2009.1 (World Health Organization)

  5. Wearing HJ, Rohani P (2006) Ecological and immunological determinants of dengue epidemics. Proc Natl Acad Sci U S A 103(31):11802–11807

    Article  Google Scholar 

  6. Halstead SB (2004) Antibody-dependent enhancement of infection: a mechanism for indirect virus entry into cells. Cellular Receptor for Animal Viruses, Cold Spring Harbor Laboratory Press 28:493–516. 0-87969-429-7/94 (Chapter 25)

    Google Scholar 

  7. WHO (2007) Report of the Scientific Working Group meeting on dengue. (World Health Organization). Available: http://apps.who.int/tdr/svc/publications/tdr-research-publications/swgreport-dengue. Accessed March 20, 2013.

  8. Halstead SB (2007) Dengue Lancet 370(9599):1644–1652

    Article  Google Scholar 

  9. Aguiar M, Stollenwerk N, Kooi BW (2009) Torus bifurcations, isolas and chaotic attractors in a simple dengue model with ADE and temporary cross immunity (Chapter 3). Int J Comput Math 86:1867–1877

    Article  Google Scholar 

  10. Aguiar M et al (2011) The role of seasonality and import in a minimalistic multi-strain dengue model capturing differences between primary and secondary infections: complex dynamics and its implications for data analysis (Chapter 4). J Theor Biol 289:181–196

    Article  Google Scholar 

  11. WHO (2012) Dengue and severe dengue - Fact sheet N°117, http://www.who.int/mediacentre/factsheets/fs117/en/ (Accessed 2012-03-27)

  12. Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen AG, Sankoh O, Myers MF, George DB, Jaenisch T, Wint GR, Simmons CP, Scott TW, Farrar JJ, Hay SI (2013) The global distribution and burden of dengue. Nature 496(7446):504–507

    Article  Google Scholar 

  13. Gubler DJ, Wilson ML (2005) The global resurgence of vector-borne diseases: lessons learned from successful and failed adaptation, Integration of public health with adaptation to climate change: lessons learned and new directions. In: Ebi KL, Smith J, Burton I (eds) Taylor and Francis, London, pp 44–59

  14. Asia-Pacific Dengue Program Managers Meeting [proceedings] (2008) World Health Organization Western Pacific Region: National Environment Agency

  15. Kongnuy R, Pongsumpun P (2011) Mathematical Modeling for Dengue Transmission with the Effect of Season. World Academy of Science, Engineering and Technology 51

  16. Lambrechts L, Paaijmans KP, Fansiri T, Carrington LB, Kramer LD, Thomas MB, Scott TW (2011) Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti. PNAS 108(18):7460–7465

    Article  Google Scholar 

  17. Massad E, Coutinho FA (2011) The cost of dengue control. Lancet 377(9778):1630

    Article  Google Scholar 

  18. Guzmán MG, Kouri G (2002) Dengue: an update. Lancet Infect Dis 2(1):33–42

    Article  Google Scholar 

  19. Sabchareon A, Wallace D, Sirivichayakul C, Limkittikul K, Chanthavanich P, Suvannadabba S, Jiwariyavej V, Dulyachai W, Pengsaa K, Wartel TA, Moureau A, Saville M, Bouckenooghe A, Viviani S, Tornieporth NG, Lang J (2012) Protective efficacy of the recombinant, live-attenuated, CYD tetravalent dengue vaccine in Thai schoolchildren: a randomised, controlled phase 2b trial. Lancet 380(9853):1559–1567

    Article  Google Scholar 

  20. WHO (2011) Regional Office for South-East Asia. Comprehensive Guidelines for Prevention and Control of Dengue and Dengue Haemorrhagic Fever; Revised and expanded edition. (SEARO Technical Publication Series No. 60)

  21. Morrison AC, Zielinski-Gutierrez E, Scott TW, Rosenberg R (2008) Defining challenges and proposing solutions for control of the virus vector Aedes aegypti. PLoS Med 18:5(3)

    Google Scholar 

  22. Derouich M, Boutayeb A, Twizell EH (2003) A model of dengue fever. Biomed Eng Online 2:4

    Article  Google Scholar 

  23. Derouich M, Boutayeb A (2006) Dengue fever: Mathematical modelling and computer simulation. Appl Math Comput 177:528–544

    Article  Google Scholar 

  24. 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(4):387–397

    Article  Google Scholar 

  25. 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(5):489–506

    Google Scholar 

  26. Nagao Y, Koelle K (2008) Decreases in dengue transmission may act to increase the incidence of dengue hemorrhagic fever. Proc Natl Acad Sci U S A 105(6):2238–2243

    Article  Google Scholar 

  27. Esteva L, Vargas C (1998) Analysis of a dengue disease transmission model. Math Biosci 150(2):131–151

    Article  Google Scholar 

  28. Chikaki E, Ishikawa H (2009) A dengue transmission model in Thailand considering sequential infections with all four serotypes. J Infect Dev Ctries 3(9):711–722

    Article  Google Scholar 

  29. Otero M, Barmak DH, Dorso CO, Solari HG, Natiello MA (2011) Modeling dengue outbreaks. Math Biosci 232(2):87–95

    Article  Google Scholar 

  30. Newton EAC, Reiter P (1992) A model of the transmission of dengue fever with an evaluation of the impact of ultralow volume (ULV) insecticide applications of dengue epidemics. Am J Trop Med Hyg 47:709–720

    Google Scholar 

  31. Burattini MN, Chen M, Chow A, Coutinho FA, Goh KT, Lopez LF, Ma S, Massad E (2008) Modelling the control strategies against dengue in Singapore. Epidemiol Infect 136(3):309–319

    Article  Google Scholar 

  32. Derouich M (2009) Dengue Fever: A Mathematical Model with Immunization Program in Handbook of Research on Systems Biology Applications in Medicine. Editor Andriani Daskalaki (Max Planck Institute for Molecular Genetics, Germany)

  33. Luz PM, Codeco CT, Medlock J, Struchiner CJ, Valle D et al (2009) Impact of insecticide interventions on the abundance and resistance profile of Aedes aegypti. Epidemiol Infect 137(8):1203–1215

    Article  Google Scholar 

  34. Yang HM, Ferreira CP (2008) Assessing the effects of vector control on dengue transmission. Appl Math Comput 198:401–413

    Article  Google Scholar 

  35. Rodrigues HS, Monteiro MTT, Torres DFM, Zinober A (2010a) Control of Dengue disease: a case study in Cape Verde. Proc. 10th International Conference on Mathematical Methods in Science and Engineering, Almerıa, pp 26–30

    Google Scholar 

  36. Rodrigues HS, Monteiro MTT, Torres DFM (2010b) Insecticide control in a Dengue epidemics model. In: Simos T (ed) Numerical Analysis and Applied Mathematics. AIP Conf. Proc, 1281 pp 979–982

  37. Oki M, Sunahara T, Hashizume M, Yamamoto T (2011) Optimal timing of insecticide fogging to minimize dengue cases: modeling dengue transmission among various seasonalities and transmission intensities. PLoS Negl Trop Dis 5(10):e1367

    Article  Google Scholar 

  38. Coudeville L, Garnett GP (2012) Transmission dynamics of the four dengue serotypes in southern Vietnam and the potential impact of vaccination. PLoS One 7(12):e51244

    Article  Google Scholar 

  39. Amaku M, Coutinho FAM, Raimundo SM, Lopez LF, Burrattini MN, Massad E. A Comparative Analysis of the Relative Efficacy of Vector-Control Strategies against Dengue Fever. Manuscript under review. http://arxiv.org/abs/1302.1166.

  40. Chao DL, Halstead SB, Halloran ME, Longini IM Jr (2012) Controlling dengue with vaccines in Thailand. PLoS Negl Trop Dis 6(10):e1876

    Article  Google Scholar 

  41. Barmak DH, Dorso CO, Otero M, Solari HG (2013) Modelling interventions during a dengue outbreak. Epidemiol Infect 26:1–17

    Google Scholar 

  42. Boccia TM, Burattini MN, Coutinho FA, Massad E (2013) Will people change their vector-control practices in the presence of an imperfect dengue vaccine? Epidemiol Infect 5:1–9

    Google Scholar 

  43. Nishiura H (2006) Mathematical and statistical analyses of the spread of dengue. Dengue Bull 30:51–67, Table 1, p53

    Google Scholar 

  44. Johansson MA, Hombach J, Cummings DAT (2011) Models of the impact of dengue vaccines: A review of current research and potential approaches. Vaccine 29(35):5860–5868

    Article  Google Scholar 

  45. Andraud M, Hens N, Marais C, Beutels P (2012) Dynamic epidemiological models for dengue transmission: a systematic review of structural approaches. PLoS One 7(11):e49085

    Article  Google Scholar 

  46. Bureau of Epidemiology (2008) Ministry of Public Health, Thailand

  47. Wichmann O, Yoon IK, Vong S, Limkittikul K, Gibbons RV, Mammen MP, Ly S, Buchy P, Sirivichayakul C, Buathong R, Huy R, Letson GW, Sabchareon A (2011) Dengue in Thailand and Cambodia: an assessment of the degree of underrecognized disease burden based on reported cases. PLoS Negl Trop Dis 5(3):e996

    Article  Google Scholar 

  48. Undurraga EA, Halasa YA, Shepard DS (2013) Use of expansion factors to estimate the burden of dengue in Southeast Asia: a systematic analysis. PLoS Negl Trop Dis 7(2):e2056

    Article  Google Scholar 

  49. Luz PM, Vanni T, Medlock J, Paltiel AD, Galvani AP (2011) Dengue vector control strategies in an urban setting: an economic modelling assessment. Lancet 377(9778):1673–1680

    Article  Google Scholar 

  50. Anderson RM, May RM (1991) Infectious Diseases of Humans, Dynamics and Control. Oxford University Press, Oxford

    Google Scholar 

  51. Coutinho FAB, Burattini MN, Lopez LF, Massad E (2005) An approximate threshold condition for non-autonomous system: An application to a vector-borne infection. Math Comput Simul 70:149–158

    Article  Google Scholar 

  52. Coutinho FAB, Burattini MN, Lopez LF, Massad E (2006) Threshold conditions for a nonautonomous epidemic system describing the population dynamics of dengue. Bull Math Biol 68(8):2263–2282

    Article  Google Scholar 

  53. Berkeley Madonna 8.02 (2009)

  54. Gubler DJ, Kuno G (eds) (2001) Dengue and dengue hemorrhagic fever. CABI Publishing, Wallingford, UK 425–62

  55. Chang MS et al (2011) Challenges and future perspective for dengue vector control in the Western Pacific Region. W Pac Surveill Response J 2(2):9–16

    Google Scholar 

  56. McCall PJ, Kittayapong P (2006) Control of dengue vectors: tools and strategies. Working paper for the Scientific Working Group on Dengue Research, convened by the Special Programme for Research and Training in Tropical Diseases, Geneva, 1–5

  57. Nathan MB, Focks DA, Kroeger A (2006) Pupal/demographic surveys to inform dengue-vector control. Ann Trop Med Parasitol 100(Suppl 1):S1–S3

    Article  Google Scholar 

  58. Focks D, Alexander N. Multicountry study of Aedes aegypti pupal productivity survey methodology: findings and recommendations. TDR/IRM/Den /06.1 Copyright © World Health Organization on behalf of the Special Programme for Research and Training in Tropical Diseases, 2006.

  59. Tun-Lin W, Lenhart A, Nam VS, Rebollar-Téllez E, Morrison AC, Barbazan P, Cote M, Midega J, Sanchez F, Manrique-Saide P, Kroeger A, Nathan MB, Meheus F, Petzold M (2009) Reducing costs and operational constraints of dengue vector control by targeting productive breeding places: a multi-country non-inferiority cluster randomized trial. Trop Med Int Health 14(9):1143–1153

    Article  Google Scholar 

  60. WHO HELI (2013) Better environmental management for control of dengue. Health and Environment Linkages Initiative (HELI) - Accessed 15 June/2013: http://www.who.int/heli/risks/vectors/denguecontrol/en/

  61. Marcombe S, Mathieu RB, Pocquet N, Riaz MA, Poupardin R, Sélior S, Darriet F, Reynaud S, Yébakima A, Corbel V, David JP, Chandre F (2012) Insecticide resistance in the dengue vector Aedes aegypti from Martinique: distribution, mechanisms and relations with environmental factors. PLoS One 7(2):e30989

    Article  Google Scholar 

  62. Ranson H, Joseph Burhani J, Nongkran, Lumjuan N, Black WC (2010) Insecticide resistance in dengue vectors. TropIKA.net vol.1 no.1 Jan./Mar. 2010

  63. Yellow fever Fact sheet N°100 (2013). Accessed 30 June 2013: http://www.who.int/mediacentre/factsheets/fs100/en/

  64. Nam VS, Thi Yen N, Minh Duc H, Cong Tu T, Trong Thang V, Le Hoang N, Hoang San L, Le Loan L, Que Huong VT, Kim Khanh LH, Thuy Trang HT, Lam LZ, Kutcher SC, Aaskov JG, Jeffery JA, Ryan PA, Kay BH (2012) Community-based control of Aedes aegypti by using Mesocyclops in southern Vietnam. Am J Trop Med Hyg 86(5):850–859

    Article  Google Scholar 

  65. Vu SN, Nguyen TY, Kay BH, Marten GG, Reid JW (1998) Eradication of Aedes aegypti from a village in Vietnam, using copepods and community participation. Am J Trop Med Hyg 59(4):657–660

    Google Scholar 

  66. Vu SN, Nguyen TY, Tran VP, Truong UN, Le QM, Le VL, Le TN, Bektas A, Briscombe A, Aaskov JG, Ryan PA, Kay BH (2005) Elimination of dengue by community programs using Mesocyclops(Copepoda) against Aedes aegypti in central Vietnam. Am J Trop Med Hyg 72(1):67–73

    Google Scholar 

  67. Cattand P, Desjeux P, Guzmán MG, Jannin J, Kroeger A, Médici A, Musgrove P, Nathan MB, Shaw A, Schofield CJ (2006) Tropical Diseases Lacking Adequate Control Measures: Dengue, Leishmaniasis, and African Trypanosomiasis. Disease Control Priorities in Developing Countries, 2nd edn. Oxford University Press, New York, pp 451–466. doi:10.1596/978-0-821-36179-5/Chpt-23

    Google Scholar 

  68. Lloyd AL, Zhang J, Root AM (2007) Stochasticity and heterogeneity in host-vector models. J R Soc Interface 4(16):851–863

    Article  Google Scholar 

  69. Woolhouse ME, Dye C, Etard JF, Smith T, Charlwood JD, Garnett GP, Hagan P, Hii JL, Ndhlovu PD, Quinnell RJ, Watts CH, Chandiwana SK, Anderson RM (1997) Heterogeneities in the transmission of infectious agents: implications for the design of control programs. Proc Natl Acad Sci U S A 94(1):338–342

    Article  Google Scholar 

  70. De Benedictis J, Chow-Shaffer E, Costero A, Clark GG, Edman JD, Scott TW (2003) Identification of the people from whom engorged Aedes aegypti took blood meals in Florida, Puerto Rico, using polymerase chain reaction-based DNA profiling. Am J Trop Med Hyg 68(4):437–446

    Google Scholar 

  71. Rahmandad H, Sterman J (2008) Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models. Manag Sci 54(5):998–1014

    Article  Google Scholar 

  72. Jacintho LFO, Batista AFM, Ruas TL, Marietto MGB, Silva FA (2010) An agent-based model for the spread of the Dengue fever: a swarm platform simulation approach. An agent-based model for the spread of the Dengue fever: a swarm platform simulation approach. SpringSim ‘10: Proceedings of the 2010 Spring Simulation Multiconference

  73. Brandeau ML, Zaric GS, Richter A (2003) Resource-allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis. J Health Econ 22:575–598

    Article  Google Scholar 

  74. For 1970–2000, Thailand, source: United Nations

  75. Luz PM, Lima-Camara TN, Bruno RV, Castro MG, Sorgine MH, Lourenço-de-Oliveira R, Peixoto AA (2011) Potential impact of a presumed increase in the biting activity of dengue-virus-infected Aedes aegypti (Diptera: Culicidae) females on virus transmission dynamics. Mem Inst Oswaldo Cruz 106(6):755–758

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to thank Julie Roiz for her expert insights into infectious disease modelling and Eduardo Massad for his patient answering of queries related to his work in dengue modelling.

Author information

Authors and Affiliations

  1. Mathematics, University of Southampton, Highfield Southampton, SO17 1BJ, UK

    Gerhart Knerer & Christine S. M. Currie

  2. Faculty of Business and Law, University of Southampton, Highfield Southampton, SO17 1BJ, UK

    Sally C. Brailsford

Authors
  1. Gerhart Knerer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christine S. M. Currie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sally C. Brailsford
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gerhart Knerer.

Appendix

Appendix

Table 5 Parameter notation, value and source
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Knerer, G., Currie, C.S.M. & Brailsford, S.C. Impact of combined vector-control and vaccination strategies on transmission dynamics of dengue fever: a model-based analysis. Health Care Manag Sci 18, 205–217 (2015). https://doi.org/10.1007/s10729-013-9263-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10729-013-9263-x

Keywords

Search

Navigation