Mathematical Models for Dengue Fever


Mathematical Models for Dengue Fever
Zeitraum: 01.01.2015 - 31.12.2016
Status: abgeschlossen

Dengue fever is a viral mosquito-borne infection which in recent years has become a major international public health concern. In the recent years, mathematical modeling has become an interesting tool for the understanding of infectious diseases epidemiology and dynamics. A series of deterministic and nowadays also stochastic models have been proposed to describe the host population. Multi-strain dynamics, such as dengue epidemiology are generally modelled with extended SIR-type models. Since no medication is available to cure Dengue, one has to control the disease transmission by controlling the mosquito population as the disease vector. Two different strategies are usually applied in tropical countries like Indonesia: disseminating chemicals to kill eggs and larvae or fumigation of the adult mosquitoes. Mathematical tools from optimal control can help to simulate, predict and improve the effectiveness of such counter mosquito campaigns. The German project partner has gained in the past years experience in optimal control applied to extended SIR-type models especially for vector based diseases. The Portuguese group focusses on both deterministic and stochastic modeling for multi-strain epidemics, vector dynamics as well as data analysis. In a nutshell, the projects aims to combine the complementary expertises of both groups to be able to answer optimization questions for involved models for Dengue epidemics. Both groups have access to field data from different countries. Combining these data sets can be particularly helpful for the validating the models and estimating so far unknown or inexact parameters. In the proposed project we plan a series of workshops and mutual exchange visits to combine the research efforts of both groups in Koblenz and Lisbon. The obtained results will be documented by publications and will be presented in conferences.


gefördert vom DAAD aus Mitteln des Bundesministeriums für Bildung und Forschung (BMBF), Projekt ID 57128360


Dr. Nico Stollenwerk, Centro de Mathematica e Aplicacoes Fundamentais, Universidade de Lisboa




Ganegoda, Naleen; Götz, Thomas; Wijaya, Karunia Putra (2021): An age-dependent model for dengue transmission: Analysis and comparison to field data. In: Journal of Applied Mathematics and Computation. Bd. 388. S. 125538.


Schäfer, Moritz; Götz, Thomas (2020): Modelling Dengue Fever Epidemics in Jakarta. In: International Journal of Applied and Computational Mathematics. Bd. 6. Nr. 84.


Ganegoda, Naleen; Götz, Thomas; Wijaya, Karunia Putra (2019): An Age-Dependent Model for Dengue Transmission: Analysis and Comparison to Field Data from Semarang, Indonesia. In: ArXiv e-prints. Nr. 1908.09256.

Fakhruddin, Muhammad; Putra, Prama Setia; Wijaya, Karunia Putra; Sopaheluwakan, Ardhasena; Satyaningsih, Ratna; Komalasari, Kurnia Endah; Mamenun, ; Sumiati, ; Indratno, Sapto Wahyu; Nuraini, Nuning; Götz, Thomas; Soewono, Edy (2019): Assessing the interplay between dengue incidence and weather in Jakarta via a clustering integrated multiple regression model. In: Ecological Complexity. Bd. 39. S. 100768.

Suandi, Dani; Wijaya, Karunia Putra; Apri, Mochamad; Sidarto, Kuntjoro Adji; Syafruddin, Din; Götz, Thomas; Soewono, Edy (2019): A one-locus model describing the evolutionary dynamics of resistance against insecticide in Anopheles mosquitoes. In: Applied Mathematics and Computation. Bd. 359. S. 90-106.

Heidrich, Peter; Götz, Thomas (2019): Modelling Dengue with the SIR Model. In: Progress in Industrial Mathematics at ECMI 2018. Springer. Bd. 30. S. 175-182.


Chavez, Jospeh Paez; Götz, Thomas; Siegmund, Stefan; Wijaya, Karunia Putra (2017): An SIR-Dengue transmission model with seasonal effects and impulsive control. In: Mathematical biosciences. S. 1-15.

Wijaya, Karunia Putra; Sutimin, ; Soewono, Edy; Götz, Thomas (2017): On The Existence Of A Nontrivial Equilibrium In Relation To The Basic Reproductive Number. In: Int. J. Appl. Math. Comput. Sci.. Bd. 27. Nr. 3. S. 623-636.


Stollenwerk, Nico; Götz, Thomas; Mateus, Luis; Wijaya, Karunia Putra; Willems, David; Skwara, Urszula; Marguta, Romona; Ghaffari, Peyman; Aguiiar, Maira (2016): Modelling spatial connectivity in epidemiological systems, dengue fever in Thailand on networks from radiation models. In: AIP Conference Proceedings International Conference of Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015). AIP Publishing. Bd. 1738. S. 390011-4.

Götz, Thomas; Altmeier, Nicole; Bock, Wolfgang; Rockenfeller, Robert; Sutimin, ; Wijaya, Karunia Putra (2016): Modeling dengue data from Semarang, Indonesia. In: Ecological Complexity.


Götz, Thomas; Rockenfeller, Robert; Wijaya, Karunia Putra (2015): Optimization problems in epidemiology, biomechanics & medicine. In: International Journal of Advances in Engineering Sciences and Applied Mathematics. S. 25-32.

(2015): Symposium On Biomathematics (Symomath 2014). Götz, Thomas; Suryanto, Agus: AIP Publishing. Bd. 1651.

Wijaya, Karunia Putra; Götz, Thomas; Soewono, Edy (2015): Advances in mosquito dynamics modeling. In: Math. Meth. Appl. Sci..


Wijaya, Karunia Putra; Götz, Thomas; Soewono, Edy (2014): An optimal control model of mosquito reduction management in a dengue endemic region. In: International Journal of Biomathematics. S. 1450056.


Wijaya, Karunia Putra; Götz, Thomas; Soewono, Edy; Nuraini, Nuning (2013): Temephos spraying and thermal fogging efficacy on Aedes aegypti in homogeneous urban residences. In: Bd. 39S. S. 48--56.


Aldila, Dipo; Götz, Thomas; Soewono, Edy (2012): An optimal control problem arising from a dengue disease transmission model. In: Mathematical biosciences.


  • Tammy Volz, Mathematical Models for Commuter Flows (in German), B.Ed.-Thesis, U Koblenz 2015
  • Nicole Altmeier, Modeling and Simulation of Dengue Dynamics (in German), M.Ed.-Thesis, U Koblenz 2016
  • Christian Banyai, Time-Space Models in Mathematical Epiemiology (in German), M.Ed.-Thesis, U Koblenz, 2017
  • Dominik Pelikan, Korrelation von Denguefällen und meteorologischen Daten (in German), B.Ed.-Thesis, U Koblenz, 2017