System dynamic model of leptospirosis control in demak, indonesia, 2014

Anggun P. Djati, Tri Ramadhani, Nova Pramestuti, Dwi Priyanto, Tri Handayani, Tri Edhi Budhi Soesilo

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Cases of leptospirosis persist in Demak District of Indonesia every year. It’s needed a mix method (epidemiology, ecology, and system thinking approach) to analyze and to choose the best intervention based on time series data. The study located in Demak, Jawa Tengah on May to November, 2014. Based on an existing model that formulated by time series data for six years (2007 – 2013), leptospirosis control was simulated using a system dynamics method. The simulation was based on seven pre-defined scenarios. The software used to assist the completion of the dynamic model was Powersim version 2.5 for Windows. Predictions extended over 5 years. The model predicted that, if the intervention was biological control and included rodent control, the leptospirosis cases could be prevented up to 20.7%. Wound care could prevent up to 1.6% of the disease. Efforts to prevent direct contact between healthy humans and urine of infected rodents had the strongest impact on reducing leptospirosis in this model, as this could decrease cases by up to 98.14%. Domestic waste management as a source of rodent food in households reduced the predicted number of leptospirosis cases by 1.8%. A combination of the prevention of contact between healthy humans with contaminated water, wound care, biological and mechanical rodent control, and domestic waste management together resulted in a predicted incidence of 0.45% leptospirosis cases per year. The model was a useful tool to predict the efficiency of leptospirosis control under various intervention scenarios.

Original languageEnglish
Pages (from-to)753-764
Number of pages12
JournalIndian Journal of Public Health Research and Development
Issue number3
Publication statusPublished - 1 Mar 2019


  • Control
  • Interventions
  • Leptospirosis
  • Scenarios
  • System dynamic model


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