Comparison of Dengue Transmission in Lowland and Highland Area: Case Study in Semarang and Malang, Indonesia

Abstract

Dengue is a potentially lethal mosquito-borne disease, regarded as the most dangerous disease in the world. It is also a major health issue in tropical and subtropical countries. Environmental characteristics and sociocultural are factors which play a role in the spread of dengue. Different landscape structure such as lowland and highland areas are possible to give different infection rate on dengue transmission. Semarang and Malang are densely populated areas in Java, which are selected to be our study areas. A mathematical model (SIR-UV) is adapted to describe dengue transmission. Spiral dynamic optimization is applied to convert monthly data to weekly in Malang and estimate the infection rate that minimized the deviation between dengue data and simulation. This method produces a good fitting to the data. We compare the pattern of dengue cases from the simulation in both cities. Furthermore, we identify seasonal variations of the cases via Fourier series of the infection rate. We also investigate the correlation between humidity, infection rate, and dengue cases in Semarang and Malang. It reveals that humidity influences infection rate in 1-3 weeks later and the infection rate produces dengue cases in the next four weeks.

Climate-based dengue model in Semarang, Indonesia: Predictions and descriptive analysis

“…( Yang et al., 2011 ). Parameters μ h and γ were constant, where the values were obtained from the literature ( Fauzi et al., 2019 ; Gotz et al., 2017 ). Parameter bP h = β h , called infection rate, is time-dependent, which is obtained from optimization to minimize the error between the result of model simulation and dengue incidence data.…”

“… Symbol Value References μ h Fauziet al., 2019 , Gotzet al., 2017 μ v 0.8692–0.1590 ⋅ T + 0.01116 ⋅ T 2 − 3.408 ⋅ 10 −4 ⋅ T 3 + 3.809 ⋅ 10 −6 ⋅ T 4 Liu-Helmerssonet al., 2014 , Putra and Nuraini, 2017 , Yanget al., 2011 b 0.0043 ⋅ T + 0.0943 Liu-Helmerssonet al., 2014 , Putra and Nuraini, 2017 , Yanget al., 2011 P v or Liu-Helmerssonet al., 2014 , Putra and Nuraini, 2017 , Yanget al., 2011 β h estimated – γ 1/30 Gotz et al. (2017) S h (0) 56.9 % Andraudet al., 2013 , Fauziet al., 2019 I v (0) 3 ⋅ I h (0) – N s <...>…”

“…Furthermore, Fauzi et al. ( Fauzi et al., 2019 ) compared the pattern of dengue transmission in lowland area and highland area in which Semarang was chosen as the representative of lowland area, and also identified seasonal variations of dengue incidence via a continuous sinusoidal function of infection rate and examined the correlation between humidity-incidence and humidity-infection rate.…”

Spatiotemporal Characterization of Dengue Incidence and Its Correlation to Climate Parameters in Indonesia

“…Additionally, these climate factors contribute to a heightened probability of human-mosquito vector contact, consequently, elevating the transmission of the dengue virus [5]. Each climate parameter influences dengue incidence to a different degree in each area [22][23][24]42]. Determining which climate parameters dominantly influence dengue incidence in Indonesia and the dependency between dengue incidence and climate parameters is essential.…”

Temporal trend and spatial clustering of the dengue fever prevalence in West Java, Indonesia

“…Tropical climate conditions support mosquito growth so the transmission cycle between hosts and vectors is likely to continue with increasing intensity. The seasonal variation between the rainy and dry seasons is associated with the annual variety of dengue incidences [12] . Breeding site expansion during the rainy season determines the abundance of the vector population.…”