In the Republic of Korea, public health centers conduct vector mosquito control in accordance with infectious disease prevention laws. However, most public health centers have traditionally conducted periodic, uniform vector control across their respective regions without considering specific information on vector occurrence. In 2021, The Korea Diseases Control and Prevention Agency(KDCA) launched a control project to shift the paradigm toward mosquito control strategy based on mosquito surveillance data. In 2024, 18 local public health centers will participate in this project, which will progressively expanding so that it can be used countrywide. Local public health centers evaluate mosquito monitoring data using data gathered from Daily Mosquito Monitoring System(DMS), which enables them to pinpoint the best times and locations for vector control. Vector control activities carried out by local public health centers are computerized utilizing Vector Control Geographic Information System(VCGIS). Using the new control strategy with mosquito surveillance, the number of mosquito occurrences, number of control activities, and amount of insecticides have decreased compared to the periodic control activities. Based on mosquito surveillance data, it is anticipated that evidence-based mosquito vector control will offer a more efficient and effective means of mosquito control.

Epidemiological research to investigate the spatial characteristics of poultry farms confirmed with avian influenza (AI) infection can help increase the efficacy of AI surveillance as well as AI control strategies. The spatial characteristics of poultry farms confirmed with AI infection can provide insights on effective AI-surveillance and AI-control strategies to policymakers by providing a visualization of the geographical pattern of AI distribution. The goal of the current study was to investigate the spatial characteristics of the risk of a farm being AI-positive by using data from routine AI-surveillance performed during the period 2014–2015. To achieve this goal, we applied a spatial model because it improves the estimation of the relative risk by taking into account spatial dependence between epidemiological units. The results revealed there was a lack of dependency between districts in the risk of a farm being AI-positive. The estimates for the spatial autocorrelation coefficient in the spatial model for chicken farms were 0.006 in 2014 (p = 0.9496) and -0.064 in 2015 (p = 0.6052) and for duck farms were -0.066 in 2014 (p = 0.4380) and 0.047 in 2015. Likewise, Moran’s I statistic estimates for chicken farms were 0.0243 in 2014 (p = 0.3183) and -0.0174 in 2015 (p = 0.5657) and for duck farms were -0.0342 in 2014 (p = 0.6678) and -0.0230 in 2015.

Currently food-borne disease is being increased at outdoor food services including hotels and restaurants. Speedy and convenient practical monitoring techniques to determine hygienic conditions are needed. This study was designed to verify correlation of direct ATP (Adenosine Tri-Phosphate) examination method using ATP bioluminescence and surveillance with check-list by inspector. Hygienic status of personal hygiene (hands), kitchen utensils (knives, chopping boards, kitchen towels, cap openers, food storage containers, and blade of slice machines), facilities and equipments (refrigerator handles, worktables, and sinks) in five major hotels in Seoul were examined. The result of personal hygiene of hotels was relatively better than other inspection items (46.6 points in personal hygiene, 40.2 points in kitchen utensils, 40.3 points in facilities & equipments). In ATP inspection, kitchen utensils and facilities & equipments were relatively clean comparing with personal hands data (40.8 ± 6.77 RLU/cm²). After correlation analysis of surveillance in hygienic status points and ATP value, all results showed negative and high correlation. The surveillance data and ATP results investigating personal hygiene, kitchen utensils and facilities & equipments were highly correlated. The ATP examination method which shows real-time identification could be considered as an appropriate method to alternate current check-list dependent safety management in food services including hotels.