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Comparative analysis of dengue versus chikungunya outbreaks in Costa Rica

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Abstract

For decades, dengue virus has been a cause of major public health concern in Costa Rica, due to its landscape and climatic conditions that favor the circumstances in which the vector, Aedes aegypti, thrives. The emergence and introduction throughout tropical and subtropical countries of the chikungunya virus, as of 2014, challenged Costa Rican health authorities to provide a correct diagnosis since it is also transmitted by the same vector and infected hosts may share similar symptoms. We study the 2015–2016 dengue and chikungunya outbreaks in Costa Rica while establishing how point estimates of epidemic parameters for both diseases compare to one another. Longitudinal weekly incidence reports of these outbreaks signal likely misdiagnosis of infected individuals: underreporting of chikungunya cases, while overreporting cases of dengue. Our comparative analysis is formulated with a single-outbreak deterministic model that features an undiagnosed class. Additionally, we also used a genetic algorithm in the context of weighted least squares to calculate point estimates of key model parameters and initial conditions, while formally quantifying misdiagnosis.

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References

  1. Center for Disease Control: Dengue. http://www.cdc.gov/dengue/ (2017). Accessed Jan 2017

  2. Harris, E., Videa, E., Prez, L., Sandoval, E., Tllez, Y., Perez, M.L., Delgado, M.A.: Clinical, epidemiologic, and virologic features of dengue in the 1998 epidemic in Nicaragua. Am. J. Trop. Med. Hyg. 63(1), 5–11 (2000)

    Article  Google Scholar 

  3. Mir, D., Romero, H., de Carvalho, L.M.F., Bello, G.: Spatiotemporal dynamics of DENV-2 Asian-American genotype lineages in the Americas. PLoS ONE 9(6), e98519 (2014)

    Article  Google Scholar 

  4. Center for Disease Control: Chikungunya virus. http://www.cdc.gov/chikungunya/ (2017). Accessed Jan 2017

  5. Costa Rica’s Department of Health and Human Services (“Ministerio de Salud de Costa Rica”), health surveillance (“Vigilancia de la salud”), analysis of health status (“Analisis de situacion de salud”). https://www.ministeriodesalud.go.cr (2016). Accessed Nov 2016

  6. Futami, K., Valderrama, A., Baldi, M., Minakawa, N., Marin Rodriguez, R., Chaves, L.F.: New and common haplotypes shape genetic diversity in Asian tiger mosquito populations from Costa Rica and Panamá. J. Econ. Entomol. 108, 761–768 (2015)

    Article  Google Scholar 

  7. Chahar, H.S., Bharaj, P., Dar, L., Guleria, R., Kabra, S.K., Broor, S.: Co-infections with chikungunya virus and dengue virus in Delhi, India. Emerg. Infect. Dis. 15(7), 1077–80 (2009)

    Article  Google Scholar 

  8. Hapaurachchi, H.A.C., Bandara, K.B.A.T., Hapugoda, M.D., Williams, S., Abeyewickreme, W.: Laboratory confirmation of dengue and chikungunya co-infection. Ceylon Med. J. 53(3), 104–105 (2008)

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

    Article  MATH  Google Scholar 

  10. Murillo, D., Holechek, S.A., Murillo, A.L., Sanchez, F., Castillo-Chavez, C.: Vertical transmission in a two-strain model of dengue fever. Lett. Biomath. 1(2), 249–271 (2014)

    Article  Google Scholar 

  11. Pawelek, K.A., Niehaus, P., Salmeron, C., Hager, E.J., Hunt, G.J.: Modeling dynamics of Culex pipiens complex populations and assessing abatement strategies for West Nile virus. PLoS ONE 9(9), e108452 (2014)

    Article  Google Scholar 

  12. Sanchez, F., Engman, M., Harrington, L., Castillo-Chavez, C.: Models for dengue transmission and control. Contemp. Math. 410, 311 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  13. Sanchez, F., Murillo, D., Castillo-Chavez, C.: Change in host behavior and its impact on the transmission dynamics of dengue. In: BIOMAT 2011 (pp. 191–203). World Scientific (2012)

  14. Chowell, G., Sanchez, F.: Climate-based descriptive models of dengue fever: the 2002 epidemic in Colima, Mexico. J. Environ. Health 68(10), 40 (2006)

    Google Scholar 

  15. Chaves, L.F., Scott, T.W., Morrison, A.C., Takada, T.: Hot temperatures can force delayed mosquito outbreaks via sequential changes in Aedes aegypti demographic parameters in autocorrelated environments. Acta Trop. 129, 15–24 (2014)

    Article  Google Scholar 

  16. Chaves, L.F., Morrison, A.C., Kitron, U.D., Scott, T.W.: Nonlinear impacts of climatic variability on the density-dependent regulation of an insect vector of disease. Glob. Change Biol. 18, 457–468 (2012)

    Article  Google Scholar 

  17. Reiner, R.C., Perkins, T.A., Barker, C.M., Niu, T., Chaves, L.F., Ellis, A.M., George, D.B., Le Menach, A., Pulliam, J.R.C., Bisanzio, D., Buckee, C., Chiyaka, C., Cummings, D.A.T., Garcia, A.J., Gatton, M.L., Gethring, P.W., Hartley, D.M., Johnston, G., Klein, E.Y., Michael, E., Lindsay, S.W., Lloyd, A.L., Pigott, D.M., Reisen, W.K., Ruktanonchai, N., Singh, B.K., Tatem, A.J., Kitron, U., Hay, S.I., Scott, T.W., Smith, D.L.: A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970–2010. J. R. Soc. Interface 10, 20120921 (2013)

    Article  Google Scholar 

  18. Hethcote, H.: The mathematics of infectious diseases. SIAM Rev. 42, 599–653 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  19. Chaves, L.F., Pascual, M.: Comparing models for early warning systems of neglected tropical diseases. PLoS Negl. Trop. Dis. 1, e33 (2007)

    Article  Google Scholar 

  20. Banks, H.T., Hu, S., Thompson, W.C.: Modeling and inverse problems in the presence of uncertainty. CRC Press, Boca Raton (2014)

    MATH  Google Scholar 

  21. Chowell, G., Ammon, C.E., Hengartner, N.W., Hyman, J.M.: Transmission dynamics of the great influenza pandemic of 1918 in Geneva, Switzerland: assessing the effects of hypothetical interventions. J. Theor. Biol. 241(2), 193–204 (2006)

    Article  MathSciNet  Google Scholar 

  22. Chowell, G., Castillo-Chavez, C., Fenimore, P.W., Kribs-Zaleta, C.M., Arriola, L., Hyman, J.M.: Model parameters and outbreak control for SARS. Emerg. Infect. Dis. 10(7), 1258–1263 (2004)

    Article  Google Scholar 

  23. Holland, J.: Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control and artificial intelligence. MIT Press, Cambridge (1992)

    Google Scholar 

  24. Scrucca, L.: GA: a package for genetic algorithms in R. J. Stat. Softw. 53(4), 1–37 (2013)

    Article  Google Scholar 

  25. Byrd, R.H., Lu, P., Nocedal, J., Zhu, C.: A limited memory algorithm for bound constrained optimization. SIAM J. Sci. Comput. 16(5), 1190–1208 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  26. Manore, C.A., Hickmann, K.S., Xu, S., Wearing, H.J., Hyman, J.M.: Comparing dengue and chikungunya emergence and endemic transmission in A. aegypti and A. albopictus. J. Theor. Biol. 356, 174–191 (2014)

    Article  MathSciNet  Google Scholar 

  27. Chastel, C.: Eventual role of asymptomatic cases of dengue for the introduction and spread of dengue viruses in non-endemic regions. Front. Physiol. 3, 70 (2012)

    Article  Google Scholar 

  28. Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716–723 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  29. Burnham, K.P., Anderson, D.R.: Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd edn. Springer, Berlin (2002)

    MATH  Google Scholar 

  30. Arriola, L., Hyman, J.M.: Sensitivity analysis for uncertainty quantification in mathematical models. In: Chowell, G., et al. (eds.) Mathematical and Statistical Estimation Approaches in Epidemiology. Springer, Berlin (2009)

    Google Scholar 

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Acknowledgements

A. C.-A. thanks the support of the scholarship program Preparation of Data Driven Mathematical Scientists for the Workforce, housed by East Tennessee State University.

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Authors and Affiliations

  1. Escuela de Matematica, Universidad de Costa Rica, Ciudad Universitaria Rodrigo Facio, San Jose, 2060, Costa Rica

    Fabio Sanchez & Luis A. Barboza

  2. Department of Mathematics and Statistics, East Tennessee State University, P.O. Box 70663, Johnson City, TN, 37614-0663, USA

    David Burton & Ariel Cintrón-Arias

Authors
  1. Fabio Sanchez
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  2. Luis A. Barboza
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  3. David Burton
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  4. Ariel Cintrón-Arias
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Correspondence to Fabio Sanchez.

Additional information

D. Burton was partially funded by National Science Foundation Grant Number DUE-1356397. This article belongs to the Special Issue: Demographic and temporal heterogeneity in infectious disease epidemiology.

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Sanchez, F., Barboza, L.A., Burton, D. et al. Comparative analysis of dengue versus chikungunya outbreaks in Costa Rica. Ricerche mat 67, 163–174 (2018). https://doi.org/10.1007/s11587-018-0362-3

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  • DOI: https://doi.org/10.1007/s11587-018-0362-3

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