Juni Wijayanti Puspita, Farida, Muhammad Fakhruddin, Nuning Nuraini, Rifky Fauzi, Sapto Wahyu Indratno, Edy Soewono
Dengue is one of the most rapidly spreading diseases, especially in tropical and subtropical countries, including Indonesia. This disease is transmitted by Aedes aegypti and Aedes albopictus mosquitoes which are predominant in the human environment. The high transmission of the dengue virus generally occurs in urban and semi-urban areas, considering that the aspects contributing to the transmission of dengue are mobility and high population density. As the capital city of Central Sulawesi Province with high mobility, Palu City has the highest distribution of dengue cases and is included in the category of dengue endemic areas. Interestingly, Palu is included in the non-seasonal zone, which is associated with the irregularity of the dengue outbreak every year. Here, we study the irregular dengue epidemic in Palu. We propose to use the cumulative generator operator to derive a solution for the SEIR-SI model describing the spread of dengue in Palu. The linear combination of the eight-logistic model was chosen to fit the weekly cumulative data of dengue cases from 2014 to 2016. The time-varying effective (or instantaneous) reproduction number (REff) is obtained as an early warning to detect the infection trend with one week time-lag from REff. The result is vital for the weekly control and prevention of dengue transmission based on only the weekly infection data. © 2023 Elsevier B.V.
Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, 40132, Indonesia; Mathematics Department, School of Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia; Center of Mathematical Modeling and Simulation, Institut Teknologi Bandung, Jawa Barat, Bandung, 40132, Indonesia; Department of Mathematics, Institut Teknologi Sumatera, Jl. Terusan Ryacudu, Lampung, Lampung Selatan, 35365, Indonesia; Statistics Research Division, Institut Teknologi Bandung, Jawa Barat, Bandung, 40132, Indonesia; University Center of Excellence on Artificial Intelligence for Vision, Natural Language Processing & Big Data Analytics (U-CoE Al-VLB), Institut Teknologi Bandung, Jawa Barat, Bandung, 40132, Indonesia
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