Prediction of Malaria vector mosquito abundance using meteorological and geographical factor in South Korea

• 발행기관: 한국예방수의학회
• 저자명: Ju Young Kim Kyung-Duk Min
• 간행물 정보: 『Journal of Preventive Veterinary Medicine』Vol.48, No.4, 274~278쪽, 전체 5쪽
• 주제분류: 의약학 > 기타의약학
• 파일형태: PDF
• 발행일자: 2024.12.31

국문 초록

Malaria remains a significant public health issue, particularly in regions such as the Korean Demilitarized Zone (DMZ). Effective malaria control and prevention require precise prediction of mosquito density across both monitored and unmonitored areas. This study aimed to develop predictive models to estimate the abundance of malaria vector mosquitoes by integrating meteorological and geographical data. Data from mosquito surveillance sites and NASA MODIS land cover datasets acquired between 2009 and 2022 were utilized. Two predictive models, the Gradient Boosted Model (GBM) and Principal Component Regression (PCR), were employed and evaluated. Model performance was assessed using the coefficient of determination (R²). Results showed that PCR outperformed GBM in predictive accuracy, suggesting that PCR is more robust in handling multicollinearity among variables. However, both models did not show practically-usable level of prediction performance. This study provides a preliminary but foundational framework for extending predictive modeling to broader regions, thereby supporting malaria prevention efforts through improved risk mapping.

목차

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재료 및 방법

결 과

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감사의 글

REFERENCES

키워드

Malaria Spatial interpolation Mosquito Meteorological factor Geographical factor

참고문헌

• WIREs Comput Stat
• Geocarto Int
• BMC Public Health
• Glob Health Action
• Public Health Wkly Rep
• Int J Environ Res Public Health
• Environ Sci Pollut Res
• Parasites Vectors
• Osong Public Health Res Perspect
• EcoHealth
• Am J Trop Med Hyg