Associated Factors of Plasmodium Knowlesi Malaria among Registered Malaria Cases in Terengganu, Malaysia 2011- September 2019 via Vekpro Online Database Faizul Haris Mohd Hatta1, Zaliha Ismail1, Zahir Izuan Azhar1, Nurhuda Ismail1, Norafidah Abdul Rashid2, Ahmad Syaify Berahim2 1 Department of Public Health Medicine, Faculty of Medicine, Universiti Teknologi Mara (UiTM), Selangor, Malaysia 2 Vector Borne Control Unit, Terengganu State Health Department, Terengganu, Malaysia Received ABSTRACT 6th April 2021 Received in revised form th Introduction: Plasmodium knowlesi (P. knowlesi), zoonotic malaria cases had been 27 June 2021 increasing in trend in Terengganu, Malaysia. This study aimed to determine the associated Accepted factors of P. knowlesi malaria among registered malaria cases in Terengganu from 2011 to 28th June 2021 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. Corresponding author: The cases were grouped into P. knowlesi group (P. knowlesi, P. malariae, mixed infection) Associate Professor Dr Zaliha and non-P. knowlesi group (P. falciparum, P. vivax) for comparison of their risk factors. Ismail, Multiple Logistic Regression analysis was used to identify the associated factors. Results: Department of Public Health Medicine, Plasmodium knowlesi group contributed to 187 out of 247 (75.7%) of all malaria cases. Four Faculty of Medicine, factors were found to be significantly associated with P. knowlesi group in the final Universiti Teknologi Mara (UiTM), multivariable logistic regression analysis. Age [AOR=1.04 (95% CI: 1.01,1.08)], Malay race Jalan Hospital, 47000 Sungai Buloh [AOR=39.43 (95% CI: 13.99,111.18)], agriculture and forestry worker [AOR=14.95 (95% CI: Selangor, Malaysia 4.10,54.51)] and Passive Case Detection [AOR=11.70 (95% CI: 2.60,52.63)] were the Email: [email protected] 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. KEYWORDS: Plasmodium knowlesi, zoonosis, malaria, Terengganu INTRODUCTION As human malaria cases in Malaysia have been declining in recent years, zoonotic malaria cases, P. The emerging zoonotic malaria species, P. knowlesi has knowlesi has shown an increase in trend. According to become a new additional challenge to malaria control in the Ministry of Health data, the incidence of P. knowlesi Malaysia. Plasmodium knowlesi is usually transmitted was 854 in 2011 and 4131 in 2018. The number of between non-human primate hosts by Anopheles malaria deaths in Malaysia has also shifted from mosquitoes. However, in a background where the contributed mainly by human malaria to zoonotic parasite, vector, primate host, and humans converge, it malaria, P. knowlesi. In 2010, there were 33 malaria can cause spillover infection to humans in which animal deaths in which 29 (87.9%) were due to human malaria, to human disease transmission occurs [1]. Pig-tailed and 4 (12.1%) were due to P. knowlesi. On the contrary, macaques (Macaca nemestrina), long-tailed macaques in 2018, the number of malaria deaths were 12 cases in (Macaca fascicularis), and banded leaf monkey which were all contributed by P. knowlesi. (Presbytis melalophus) are the natural hosts of P. To date, P. knowlesi infections in humans occur knowlesi [2-4]. only as a result of animal-to-human transmission. There 23 Vol 6(2) (2021) 23-35 | jchs-medicine.uitm.edu.my | eISSN 0127-984X https://doi.org/10.24191/jchs.v6i2.13052 Plasmodium knowlesi Malaria in Terengganu is no proof that natural human-to-human transmission specific background. Although several studies on the has occurred, although it has been confirmed in a risk factors for P. knowlesi had been done previously, laboratory setting [5]. However, the possibility that P. almost all studies related to risk factors were knowlesi being transmitted naturally from human to concentrated in Borneo, East Malaysia. The primary human does exist due to parasite adaptation and change vectors in Borneo are from a different complex of the with time [6, 7]. Hence it is very crucial to recognize Leucosphyrus group of Anopheles (An.) mosquitoes associated factors for P. knowlesi infections among from peninsular Malaysia. Anopheles cracens, from the humans. Dirus Complex, is the primary vector of P. knowlesi in Grigg, Cox, et al. (2017) found that those aged Peninsular Malaysia whereas An. balabacensis and An. 15 years old or older, male, involved in plantation work, latens from the Leucosphyrus Complex are the primary history of sleeping outside or traveling were vectors of P. knowlesi in Sabah and Sarawak, independently associated with increased risk of respectively. symptomatic P. knowlesi infection. The study also Moreover, a study showed that there is likely a compared P. knowlesi infection with other Plasmodium different genetic variant of P. knowlesi for every spp infections. They found that being 15 years old or location reporting P. knowlesi human infections [13]. older, clearing vegetation, farming occupation, and By knowing these, we can postulate that there might be having long grass around the house increased the risk some variation in the associated factors of P. knowlesi for P. knowlesi infection but not for other Plasmodium infections in Terengganu compared to Malaysia spp. infection [8]. Another study in Sabah, Malaysia, Borneo. found a significantly higher median age and a higher However, to date, there is no published data on proportion of males in P. knowlesi cases when the associated factors of P. knowlesi infections in compared to P. vivax or P. falciparum cases [9]. Terengganu or neighboring states. Therefore, the However, a study using microscopically positive specific aims of the study were to determine the factors malaria blood samples confirmed by nested PCR from associated with P. knowlesi by comparing registered P. all Malaysian states found otherwise. There was no knowlesi cases with non-P. knowlesi cases in significant association between age and gender with P. Terengganu via Vekpro Online database and its knowlesi cases when compared to other Plasmodium relationship with rainfall density, relative humidity, and spp. infections [10]. temperature gathered from Malaysian Meteorological Environmental factors such as monthly rainfall Department. and seasonality were positively correlated with notifications of P. knowlesi, whereby, the correlation MATERIALS AND METHODS between the notifications of P. knowlesi occurs two to This study was a cross-sectional study conducted using four months after rainfall and from May to August [11]. two sets of secondary surveillance data. The first data The average monthly rainfall and humidity are set was, data on registered malaria cases in Terengganu significantly associated with the incidence rate ratio of from 2011 to September 2019 retrieved from Vekpro P. knowlesi with a lag time of three months in univariate Online Database and the second data set was weather analysis [12]. data retrieved from the Malaysian Meteorological Terengganu is a state located on the east side of Department. Peninsular Malaysia which consists of eight districts. In Four domains of independent variable namely Terengganu, there has been an increase in P. knowlesi sociodemographic, occupational, disease profile, and cases in recent years. In 2015, there were only six cases, environmental were compared between the P. knowlesi and the number of cases kept on increasing to 38 cases group and non-P. knowlesi group. Most of the data in 2018. The increase in the number of cases should available in this database were based on microscopy alert and prompt the State Health Department as well as reports. Hence, due to the near similarity of P. knowlesi the Ministry of Health to enhance their P. knowlesi and P. malariae under microscopy [14], the two species prevention activities in Terengganu based on their 24 Vol 6(2) (2021) 23-35 | jchs-medicine.uitm.edu.my | eISSN 0127-984X https://doi.org/10.24191/jchs.v6i2.13052 Plasmodium knowlesi Malaria in Terengganu and mixed infections that contain P. knowlesi as one of monthly rainfall density for each meteorological station the parasites were grouped as P. knowlesi group. Other in Terengganu from 2011 to 2019. There was a total of species were categorized as non-P. knowlesi. The 9 meteorological stations in Terengganu, three of them sample size was calculated using OpenEpi Version 3.01 were called principles station where continuous sample size calculator. The proportion method and maintenance of measuring machines was done, and the anticipated frequency of 98% [12] were used. With an other six were auxiliary stations where maintenance attrition rate of 20%, a total of 32 samples should be was done periodically. For this study, data from three sufficient from the calculation. However, all registered principal stations namely Gong Kedak, Kuala malaria cases from 2011 to September 2019 were used Terengganu, and Kerteh were extrapolated to calculate by using universal sampling. The exclusion criteria for the average monthly temperature, average monthly the study were any duplicated cases or cases with the relative humidity, and average monthly rainfall density absence of more than 50% of the study variables. for Terengganu state from 2011 to 2019. The monthly Vekpro Online is an online surveillance average for each variable was then matched to each case database designed for the surveillance of vector-borne by notification but with a lag time of three months as diseases in Malaysia such as Malaria, Filariasis, used in prior research [12]. The seasonality variable Chikungunya, Typhus, and Zika.