ABSTRACT
Objective To create a model based on meteorological data to predict the regions at risk of schistosomiasis during the flood season, so as to provide insights into the surveillance and forecast of schistosomiasis. Methods An interactive schistosomiasis forecast system was created using the open-access R software. The schistosomiasis risk index was used as a basic parameter, and the species distribution model of Oncomelania hupensis snails was generated according to the cumulative rainfall and temperature to predict the probability of O. hupensis snail distribution, so as to identify the regions at risk of schistosomiasis transmission during the flood season. Results The framework of the web page was built using the Shiny package in the R program, and an interactive and visualization system was successfully created to predict the distribution of O. hupensis snails, containing O. hupensis snail surveillance site database, meteorological and environmental data. In this system, the snail distribution area may be displayed and the regions at risk of schistosomiasis transmission may be predicted using the species distribution model. This predictive system may rapidly generate the schistosomiasis transmission risk map, which is simple and easy to perform. In addition, the regions at risk of schistosomiasis transmission were predicted to be concentrated in the middle and lower reaches of the Yangtze River during the flood period. Conclusions A schistosomiasis forecast system is successfully created, which is accurate and rapid to utilize meteorological data to predict the regions at risk of schistosomiasis transmission during the flood period.
ABSTRACT
BACKGROUND@#International Health Regulations controls international travel including human movement, disease vector, and imported items to prevent the spread of dengue, especially in seaports, airports, and border crossing posts. This study aimed to determine dengue Transovarial Transmission Index (TTI) and distribution of dengue virus in the areas around Adisucipto Airport of Yogyakarta, Indonesia.@*METHODS@#The study was a descriptive analytic study with cross sectional design, conducted by mapping the spread of the dengue virus and identifying TTI in Adisucipto Airport. A total of 145 ovitraps were installed in both perimeter and buffer areas of the airport. Positive Ovitrap Index (OI), TTI, and serotype of dengue virus were examined. The TTI was identified using immunocytochemistry immunoperoxidase streptavidin biotin complex (IISBC) method in mosquito head squash preparations.@*RESULTS@#OI in the buffer area was 32 (45.1%), whereas OI in the perimeter area was 24 (32.4%). The TTI in the buffer and perimeter areas were 21 (18.3%) and 11 (18.9%), respectively. The TTI was found greater in the Aedes aegypti population compared to the Aedes albopictus population, both in the perimeter area (20% versus 16.7%) and the buffer area (20.3% versus 16.1%). Dengue virus serotype-2 (DENV-2) and dengue virus serotype-3 (DENV-3) were predominantly found in Ae. aegypti and Ae. albopictus.@*CONCLUSIONS@#Buffer areas of Adisucipto Airport of Yogyakarta have higher risk as breeding sites for Aedes spp., predominantly DENV-2 and DENV-3 serotypes. High OI shows that the areas are likely to have higher risk of developing dengue outbreak.