Associated Factors of Plasmodium Knowlesi Malaria among Registered Malaria Cases in Terengganu, Malaysia 2011- September 2019 via Vekpro Online Database

• Main Authors: Faizul Haris Hatta (Author), Zaliha Ismail (Author), Zahir Izuan Azhar (Author), Nurhuda Ismail (Author), Norafidah Abdul Rashid (Author), Ahmad Syaify Berahim (Author)
• Format: Book
• Published: UiTM Press, 2021-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 0127-984X; 10.24191/jchs.v6i2.13052
• Keywords: Public aspects of medicine; RA1-1270; Medicine (General); R5-920
• Source: Journal of Clinical and Health Sciences, Vol 6, Iss 2, p 23-35 (2021)

Introduction: Plasmodium knowlesi (P. knowlesi), zoonotic malaria cases had been increasing in trend in Terengganu, Malaysia. This study aimed to determine the associated factors of P. knowlesi malaria among registered malaria cases in Terengganu from 2011 to September 2019 via the Vekpro Online Database. Methods: A cross-sectional study was conducted using registered malaria cases in Terengganu from 2011 to September 2019 extracted from the Vekpro Online database and secondary weather data from the Malaysian Meteorological Department. A total sample of 247 malaria cases [(P. knowlesi (n=187), P. falciparum (n=23), P. vivax (n=37), P. malariae (n=4), mixed infection (n=3)] were analysed. The cases were grouped into P. knowlesi group (P. knowlesi, P. malariae, mixed infection) and non-P. knowlesi group (P. falciparum, P. vivax) for comparison of their risk factors. Multiple Logistic Regression analysis was used to identify the associated factors. Results: Plasmodium knowlesi group contributed to 187 out of 247 (75.7%) of all malaria cases. Four factors were found to be significantly associated with P. knowlesi group in the final multivariable logistic regression analysis. Age [AOR=1.04 (95% CI: 1.01,1.08)], Malay race [AOR=39.43 (95% CI: 13.99,111.18)], agriculture and forestry worker [AOR=14.95 (95% CI: 4.10,54.51)] and Passive Case Detection [AOR=11.70 (95% CI: 2.60,52.63)] were the significant associated factors. Conclusion: Identified significant associated factors and characteristics of the high-risk group for P. knowlesi infection can help medical and health front liners in Terengganu in early diagnosis and prompt treatment of the cases. The factors also will help in the planning and development of health interventions in targeting P. knowlesi infection.