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  1. Ng CFS, Seposo XT, Moi ML, Tajudin MABA, Madaniyazi L, Sahani M
    Int J Infect Dis, 2020 Dec;101:409-411.
    PMID: 33075527 DOI: 10.1016/j.ijid.2020.10.027
    The first wave of COVID-19 epidemic began in late January in Malaysia and ended with a very small final size. The second wave of infections broke out in late February and grew rapidly in the first 3 weeks. Authorities in the country responded quickly with a series of control strategies collectively known as the Movement Control Order (MCO) with different levels of intensity matching the progression of the epidemic. We examined the characteristics of the second wave and discussed the key control strategies implemented in the country. In the second wave, the epidemic doubled in size every 3.8 days (95% confidence interval [CI]: 3.3, 4.5) in the first month and decayed slowly after that with a halving time of approximately 3 weeks. The time-varying reproduction number Rt peaked at 3.1 (95% credible interval: 2.7, 3.5) in the 3rd week, declined sharply thereafter and stayed below 1 in the last 3 weeks of April, indicating low transmissibility approximately 3 weeks after the MCO. Experience of the country suggests that adaptive triggering of distancing policies combined with a population-wide movement control measure can be effective in suppressing transmission and preventing a rebound.
  2. Tajudin MABA, Khan MF, Mahiyuddin WRW, Hod R, Latif MT, Hamid AH, et al.
    Ecotoxicol Environ Saf, 2019 Apr 30;171:290-300.
    PMID: 30612017 DOI: 10.1016/j.ecoenv.2018.12.057
    Rapid urbanisation in Malaysian cities poses risks to the health of residents. This study aims to estimate the relative risk (RR) of major air pollutants on cardiovascular and respiratory hospitalisations in Kuala Lumpur. Daily hospitalisations due to cardiovascular and respiratory diseases from 2010 to 2014 were obtained from the Hospital Canselor Tuanku Muhriz (HCTM). The trace gases, PM10 and weather variables were obtained from the Department of Environment (DOE) Malaysia in consistent with the hospitalisation data. The RR was estimated using a Generalised Additive Model (GAM) based on Poisson regression. A "lag" concept was used where the analysis was segregated into risks of immediate exposure (lag 0) until exposure after 5 days (lag 5). The results showed that the gases could pose significant risks towards cardiovascular and respiratory hospitalisations. However, the RR value of PM10 was not significant in this study. Immediate effects on cardiovascular hospitalisations were observed for NO2 and O3 but no immediate effect was found on respiratory hospitalisations. Delayed effects on cardiovascular and respiratory hospitalisations were found with SO2 and NO2. The highest RR value was observed at lag 4 for respiratory admissions with SO2 (RR = 1.123, 95% CI = 1.045-1.207), followed by NO2 at lag 5 for cardiovascular admissions (RR = 1.025, 95% CI = 1.005-1.046). For the multi-pollutant model, NO2 at lag 5 showed the highest risks towards cardiovascular hospitalisations after controlling for O3 8 h mean lag 1 (RR = 1.026, 95% CI = 1.006-1.047), while SO2 at lag 4 showed highest risks towards respiratory hospitalisations after controlling for NO2 lag 3 (RR = 1.132, 95% CI = 1.053-1.216). This study indicated that exposure to trace gases in Kuala Lumpur could lead to both immediate and delayed effects on cardiovascular and respiratory hospitalisations.
  3. Tajudin MABA, Madaniyazi L, Seposo X, Sahani M, Tobías A, Latif MT, et al.
    Int J Epidemiol, 2024 Jun 12;53(4).
    PMID: 39096096 DOI: 10.1093/ije/dyae102
    BACKGROUND: Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events.

    METHODS: We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex.

    RESULTS: We analyzed 210 960 respiratory and 178 952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions.

    CONCLUSIONS: Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.

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