Estimating the malaria transmission of Plasmodium vivax based on serodiagnosis

• Published in: Malaria Journal
• Main Authors: Kim Jung-Yeon, Kim Hyung-Hwan, Na Byoung-Kuk, Kim Yeon-Joo, Sohn Youngjoo, Kim Hyuck, Kim Tong-Soo, Lee Hyeong-Woo
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2012
• Subjects: Arctic medicine. Tropical medicine; RC955-962; Infectious and parasitic diseases; RC109-216; Arctic
• Online Access: https://doi.org/10.1186/1475-2875-11-257; https://doaj.org/article/f1c82b76415049a2adadaa5b24b2e0b6

Abstract Background Plasmodium vivax re-emerged in 1993 and has now become a major public health problem during the summer season in South Korea. The aim of this study was to interpret and understand the meaning of seroepidemiological studies for developing the best malaria control programme in South Korea. Methods Blood samples were collected in Gimpo city, Paju city, Yeoncheon County, Cheorwon County and Goseong County of high risk area in South Korea. Microscopy was performed to identify patients infected with P. vivax . Antibody detection for P. vivax was performed using indirect fluorescent antibody test (IFAT). Results A total of 1,574 blood samples was collected from participants in the study areas and evaluated against three parameters: IFAT positive rate, annual antibody positive index (AAPI), and annual parasite index (API). The IFAT positive rate was 7.24% (n = 114). Of the five study areas, Gimpo had the highest IFAT positive rate (13.68%) and AAPI (4.63). Yeongcheon had the highest API in 2005 (2.06) while Gimpo had the highest API in 2006 (5.00). No correlation was observed between any of the three parameters and study sites' distance from the demilitarized zone (DMZ). Conclusions These results showed that P. vivax antibody levels could provide useful information about the prevalence of malaria in endemic areas. Furthermore, AAPI results for each year showed a closer relationship to API the following year than the API of the same year and thus could be helpful in predicting malaria transmission risks.