METHODS: COVID-19 data on cases, deaths, testing, and vaccinations were extracted from the Our World in Data (OWID) COVID-19 data repository for all the ten ASEAN countries. Comparative time-trends of the epidemiology of COVID-19 using the incidence rate, cumulative case fatality rate (CFR), delay-adjusted case fatality rate, cumulative mortality rate (MR), test positivity rate (TPR), cumulative testing rate (TR) and vaccination rate was carried out.
RESULTS: Over the study period, a total of 12,720,661 cases and 271,475 deaths was reported within the ASEAN region. Trends of daily per capita cases were observed to peak between July and September 2021 for the ASEAN region. The cumulative case fatality rate (CFR) in Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam, was of 0.9% (N=68), 2.2% (N=2,610), 3.5% (N=142,889), 0.1% (N=36), 1.2% (N=27,700), 4.0% (N=18,297), 1.6% (N=40,424), 0.1% (N=215), 1.7% (N=18,123), and 2.6% (N=21,043), respectively. CFR was consistently highest between January-June 2020. The cumulative mortality rate (MR) was 9.5, 13.7, 51.4, 0.2, 80.3, 32.4, 34.5, 1.6, 23.9 and 19.7 per 100,000 population, respectively. The cumulative test positivity rate (TPR) was 8.4%, 16.9%, 4.6%, 7.5%, 11.1%, 12.9%, 0.5%, 11.7%, and 3.6%, with the cumulative testing rate (TR) at 25.0, 90.1, 27.4, 917.7, 75.8, 177.8, 3303.3, 195.2, and 224.9 tests per 1,000 population in Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam, respectively. The percentage of population that completed vaccinations (VR) was 44.5%, 65.3%, 18.5%, 28.2%, 61.8%, 6.8%, 19.2%, 76.8%, 22.7%, and 10% in Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam, respectively.
CONCLUSION: In 2020, most countries in ASEAN had higher case fatality rates but lower mortalities per population when compared to the third quarter of 2021 where higher mortalities per population were observed. Low testing rates have been one of the factors leading to high test positivity rates. Slow initiation of vaccination programs was found to be the key factor leading to high incidence and case fatality rate in most countries in ASEAN. Effective public health measures were able to interrupt the transmission of this novel virus to some extent. Increasing preparedness capacity within the ASEAN region is critical to ensure that any future similar outbreaks can be dealt with collectively.
OBJECTIVE: To examine the associations of change in body mass index (BMI), waist circumference, and percent fat mass with change in intraocular pressure (IOP) in a large sample of Korean adults.
DESIGN, SETTING AND PARTICIPANTS: Cohort study of 274,064 young and middle age Korean adults with normal fundoscopic findings who attended annual or biennial health exams from January 1, 2002 to Feb 28, 2010 (577,981 screening visits).
EXPOSURES: BMI, waist circumference, and percent fat mass.
MAIN OUTCOME MEASURE(S): At each visit, IOP was measured in both eyes with automated noncontact tonometers.
RESULTS: In multivariable-adjusted models, the average increase in IOP (95% confidence intervals) over time per interquartile increase in BMI (1.26 kg/m2), waist circumference (6.20 cm), and percent fat mass (3.40%) were 0.18 mmHg (0.17 to 0.19), 0.27 mmHg (0.26 to 0.29), and 0.10 mmHg (0.09 to 0.11), respectively (all P < 0.001). The association was stronger in men compared to women (P < 0.001) and it was only slightly attenuated after including diabetes and hypertension as potential mediators in the model.
CONCLUSIONS AND RELEVANCE: Increases in adiposity were significantly associated with an increase in IOP in a large cohort of Korean adults attending health screening visits, an association that was stronger for central obesity. Further research is needed to understand better the underlying mechanisms of this association, and to establish the role of weight gain in increasing IOP and the risk of glaucoma and its complications.
Methods: Malaysian COVID-19 data was extracted from 16 March 2020 up to 31 May 2021. We estimated the following epidemiological indicators: 7-day incidence rates, 7-day mortality rates, case fatality rates, test positive ratios, testing rates and the time-varying reproduction number (Rt).
Findings: Between 16 March 2020 and 31 May 2021, Malaysia has reported 571,901 cases and 2,796 deaths. Malaysia's average 7-day incidence rate was 26•6 reported infections per 100,000 population (95% CI: 17•8, 38•1). The average test positive ratio and testing rate were 4•3% (95% CI: 1•6, 10•2) and 0•8 tests per 1,000 population (95% CI: <0•1, 3•7), respectively. The case fatality rates (CFR) was 0•6% (95% CI: <0•1, 3•7). Among the 2,796 cases who died, 87•3% were ≥ 50 years.
Interpretation: The public health response was successful in the suppression of COVID-19 transmission or the first half of 2020. However, a state election and outbreaks in institutionalised populations have been the catalyst for more significant community propagation. This rising community transmission has continued in 2021, leading to increased incidence and strained healthcare systems. Calibrating NPI based on epidemiological indicators remain critical for us to live with the virus. (243 words).
Funding: This study is part of the COVID-19 Epidemiological Analysis and Strategies (CEASe) Project with funding from the Ministry of Science, Technology and Innovation (UM.0000245/HGA.GV).
METHODS: A cohort study was conducted among laboratory-confirmed dengue patients aged >18 y in the central region of Peninsular Malaysia from May 2016 to November 2017. We collected demographic, clinical history, physical examination and laboratory examination information using a standardized form. Dengue severity (DS) was defined as either dengue with warning signs or severe dengue. Participants underwent daily follow-up, during which we recorded their vital signs, warning signs and full blood count results. Incidence of DS was modeled using mixed-effects logistic regression. Changes in platelet count and hematocrit were modeled using mixed-effects linear regression. The final multivariable models were adjusted for age, gender, ethnicity and previous dengue infection.
RESULTS: A total of 173 patients were enrolled and followed up. The mean body mass index (BMI) was 37.4±13.75 kg/m2. The majority of patients were Malay (65.9%), followed by Chinese (17.3%), Indian (12.7%) and other ethnic groups (4.1%). A total of 90 patients (52.0%) were male while 36 patients (20.8%) had a previous history of dengue infection. BMI was significantly associated with DS (adjusted OR=1.17; 95% CI 1.04 to 1.34) and hematocrit (%) (aβ=0.09; 95% CI 0.01 to 0.16), but not with platelet count (x103/µL) (aβ=-0.01; 95% CI -0.84 to 0.81). In the dose response analysis, we found that as BMI increases, the odds of DS, hematocrit levels and platelet levels increase during the first phase of dengue fever.
CONCLUSION: Higher BMI and higher hematocrit levels were associated with higher odds of DS. Among those with high BMI, the development of DS was observed during phase one of dengue fever instead of during phase two. These novel results could be used by clinicians to help them risk-stratify dengue patients for closer monitoring and subsequent prevention of severe dengue complications.