Associated factors of plasmodium knowlesi malaria among registered malaria cases in Terengganu, Malaysia 2011- September 2019 via Vekpro Online Database / Faizul Haris Mohd Hatta ... [et al.]

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 Dat...

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Main Authors: Mohd Hatta, Faizul Haris (Author), Ismail, Zaliha (Author), Azhar, Zahir Izuan (Author), Ismail, Nurhuda (Author), Abdul Rashid, Norafidah (Author), Berahim, Ahmad Syaify (Author)
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Published: Faculty of Medicine, 2021-09.
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001 repouitm_70283
042 |a dc 
100 1 0 |a Mohd Hatta, Faizul Haris  |e author 
700 1 0 |a Ismail, Zaliha  |e author 
700 1 0 |a Azhar, Zahir Izuan  |e author 
700 1 0 |a Ismail, Nurhuda  |e author 
700 1 0 |a Abdul Rashid, Norafidah  |e author 
700 1 0 |a Berahim, Ahmad Syaify  |e author 
245 0 0 |a Associated factors of plasmodium knowlesi malaria among registered malaria cases in Terengganu, Malaysia 2011- September 2019 via Vekpro Online Database / Faizul Haris Mohd Hatta ... [et al.] 
260 |b Faculty of Medicine,   |c 2021-09. 
500 |a https://ir.uitm.edu.my/id/eprint/70283/1/70283.pdf 
520 |a 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. Conclusions: 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. 
546 |a en 
690 |a Communicable diseases and public health 
690 |a Infectious and parasitic diseases 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/70283/ 
787 0 |n https://doi.org/10.24191/jchs.v6i2.13052 
856 4 1 |u https://ir.uitm.edu.my/id/eprint/70283/  |z Link Metadata