This document provides a literature review on dengue fever. It begins with an overview of the results from a search of the Scopus database for articles on "dengue fever", including statistics on annual publications and top authors, affiliations, and countries. It then summarizes a few key recent papers on mathematical modeling of dengue infection and the role of multiple serotypes. These include a 2017 paper estimating potential infection in Tokyo for the 2020 Olympics and papers examining the interactions between antibody response and multiple serotypes. The review concludes by noting continued high levels of research interest in dengue.

1. Literature review
Dengue fever
Keiko Ono, Ph.D.
Updated December 27, 2017
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2. Table of contents
• An overview of the Scopus search results for “dengue fever”
(Scopus is one of the largest databases of scientific literature)
• Update (December 2017)
• Rather et al (2017). Latest review of prevention and control.
• More focused search (with “infection” and “mathematical
modeling”)
• Furuya (2017) on estimating infection in Tokyo 2020
• Research on multiple serotypes, update
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3. A Scopus search was conducted on August 21, 2017
• Searched “dengue fever” in article title, keywords or abstract
• Selected articles and reviews and excluded conference paper,
letter, notes.
• Selected English language only.
• Total 9,041 documents.
• Malaria ==== 79,838 (same conditions as above excluding 2018.
as of September 5)
• Zika 2,099. Tuberculosis 159,000+. Influenza 130,000+. HIV
360,000+. Typhus 4,416
Dengue literature
is much smaller
than that of
Malaria, TB, HIV,
Influenza.
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4. Dengue fever literature by year
(Scopus search, 2017 data as of August)
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5. By source
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6. Top authors
USA
Thailand
Cuba
Singapore
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7. Affiliations
Thailand
Brazil
USA
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8. By country
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9. By subject area
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10. Most cited
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11. An update on December 27, 2017
• Searched “dengue fever” in article title, keywords or abstract
• Selected articles and reviews and excluded conference paper,
letter, notes.
• Selected English language only.
• Total 9,645 documents.
• Total for 2017 was 947 (as of Dec 27) virtually unchanged from 2016
(n=968)
High level of
interest in dengue
continues
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12. Rather, I. A., Parray, H. A., Lone,
J. B., Paek, W. K., Lim, J., Bajpai,
V. K., & Park, Y.-H. (2017).
Prevention and Control
Strategies to Counter Dengue
Virus Infection. Frontiers in
Cellular and Infection
Microbiology, 7(July), 1–8.
http://doi.org/10.3389/fcimb.2017.
00336
For the latest prevention and control strategies…a mini review
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13. Adding “infection” and “mathematical modeling” to title, keyword, abstract.
Total results 56, of which 9 were published in 2017 (below).
• Götz, T., Altmeier, N., Bock, W., Rockenfeller, R., Sutimin, & Wijaya, K. P. (2017). Modeling dengue data from
Semarang, Indonesia. Ecological Complexity, 30, 57–62. http://doi.org/10.1016/j.ecocom.2016.12.010
• Jayasundara, S. D. P., Perera, S. S. N., Malavige, G. N., & Jayasinghe, S. (2017). Mathematical modelling and
a systems science approach to describe the role of cytokines in the evolution of severe dengue. BMC Systems
Biology, 11(1). http://doi.org/10.1186/s12918-017-0415-3
• B., B., & Kasbawati (Eds.). (2017). AIP Conference Proceedings (Vol. 1825). American Institute of Physics Inc.
• Yang, H. M. (2017). The transovarial transmission in the dynamics of dengue infection: Epidemiological
implications and thresholds. Mathematical Biosciences, 286, 1–15. http://doi.org/10.1016/j.mbs.2017.01.006
• Cunha-Neto, E., Rosa, D. S., Harris, P. E., Olson, T., Morrow, A., Ciotlos, S., … Rubsamen, R. M. (2017). An
approach for a synthetic CTL vaccine design against Zika flavivirus using class I and class II epitopes identified
by computer modeling. Frontiers in Immunology, 8(JUN). http://doi.org/10.3389/fimmu.2017.00640
• Sasmal, S. K., Dong, Y., & Takeuchi, Y. (2017). Mathematical modeling on T-cell mediated adaptive immunity in
primary dengue infections. Journal of Theoretical Biology, 429, 229–240.
http://doi.org/10.1016/j.jtbi.2017.06.035
• Obenauer, J. F., Andrew Joyner, T., & Harris, J. B. (2017). The importance of human population characteristics
in modeling Aedes aegypti distributions and assessing risk of mosquito-borne infectious diseases. Tropical
Medicine and Health, 45(1). http://doi.org/10.1186/s41182-017-0078-1
• Furuya, H. (2017). Estimating vector-borne viral infections in the urban setting of the 2020 Tokyo
Olympics, Japan, using mathematical modeling. Tokai Journal of Experimental and Clinical Medicine,
42(4), 160–164.
• Maier, S. B., Huang, X., Massad, E., Amaku, M., Burattini, M. N., & Greenhalgh, D. (2017). Analysis of the
optimal vaccination age for dengue in Brazil with a tetravalent dengue vaccine. Mathematical Biosciences, 294,
15–32. http://doi.org/10.1016/j.mbs.2017.09.004 13

14. Text box
Furuya (2017) is open access@
http://mj-med-u-tokai.com/pdf/420404.pdf
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15. Research on multiple serotypes
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16. Published in
2003. Was cited
8 times in 2017
(total citations:
82)
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17. Rocha, F. P., Rodrigues, H. S., Monteiro, M. T. T., & Torres, D. F. M. (2015).
Coexistence of two dengue virus serotypes and forecasting for Madeira
Island. Operations Research for Health Care, 7, 122–131.
http://doi.org/10.1016/j.orhc.2015.07.003
“The first outbreak of dengue occurred in Madeira Island in 2012,
featuring one virus serotype. Aedes aegypti was the vector of the
disease and it is unlikely that it will be eliminated from the island.
Therefore, a new outbreak of dengue fever can occur and, if it
happens, risk to the population increases if two serotypes coexist. In
this paper, mathematical modeling and numerical simulations are
carried out to forecast what may happen in Madeira Island in such a
scenario.”
Has been cited 0 times. 17

18. Nikin-Beers, R., & Ciupe, S. M. (2015). The role of antibody in enhancing
dengue virus infection. Mathematical Biosciences, 263.
http://doi.org/10.1016/j.mbs.2015.02.004
“Dengue virus has four distinct serotypes whose cross-reactive
immune responses contribute to increased disease severity following
heterologous infections. It was proposed that non-protective cross-
reactive antibodies may play a role in disease enhancement. In this
study we develop a mathematical model of host–virus interaction and
predict the mechanisms responsible for virus expansion and loss
during primary and secondary dengue infections. We use the model
to determine the role of cross-reactive antibodies during dengue
fever and dengue hemorrhagic fever-inducing secondary infections,
and then compare the model to published patient data. We predict
that the cross-reactive antibodies interfere with the non-neutralizing
antibody effects by reducing the phagocyte-mediated removal of
antibody-virus immune complexes.”
Has been cited 5 times. 18

19. ten Bosch, Q. A., Singh, B. K., Hassan, M. R. A., Chadee, D. D., & Michael, E. (2016). The Role of
Serotype Interactions and Seasonality in Dengue Model Selection and Control: Insights from a Pattern
Matching Approach. PLoS Neglected Tropical Diseases, 10(5).
http://doi.org/10.1371/journal.pntd.0004680
“The epidemiology of dengue fever is characterized by highly seasonal, multi-annual
fluctuations, and the irregular circulation of its four serotypes. It is believed that this
behaviour arises from the interplay between environmental drivers and serotype
interactions. The exact mechanism, however, is uncertain.
Constraining mathematical models to patterns characteristic to dengue epidemiology offers
a means for detecting such mechanisms. Here, we used a pattern-oriented modelling
(POM) strategy to fit and assess a range of dengue models, driven by combinations of
temporary cross protective-immunity, cross-enhancement, and seasonal forcing, on their
ability to capture the main characteristics of dengue dynamics. We show that all proposed
models reproduce the observed dengue patterns across some part of the parameter space.
Which model best supports the dengue dynamics is determined by the level of seasonal
forcing. Further, when tertiary and quaternary infections are allowed, the inclusion of
temporary cross-immunity alone is strongly supported, but the addition of cross-
enhancement markedly reduces the parameter range at which dengue dynamics are
produced, irrespective of the strength of seasonal forcing. The implication of these structural
uncertainties on predicted vulnerability to control is also discussed. With ever expanding
spread of dengue, greater understanding of dengue dynamics and control efforts (e.g. a
near-future vaccine introduction) has become critically important. This study highlights the
capacity of multi-level pattern-matching modelling approaches to offer an analytic tool for
deeper insights into dengue epidemiology and control.” © 2016 ten Bosch et al.
Has been cited 4 times.
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20. Marques-Toledo, C. D. A., Degener, C. M., Vinhal, L., Coelho, G.,
Meira, W., Codeço, C. T., & Teixeira, M. M. (2017). Dengue
prediction by the web: Tweets are a useful tool for estimating and
forecasting Dengue at country and city level. PLoS Neglected
Tropical Diseases, 11(7).
http://doi.org/10.1371/journal.pntd.0005729
Citing ten Bosch. Another
paper that got my attention.
Yet another application of
crowdsourcing in
epidemiology and more
broadly public policy.
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