METHODS: Two newly colonised colonies of Ae. albopictus from the wild were used for the study. One colony was naturally infected with Wolbachia while in the other Wolbachia was removed by tetracycline treatment. Both colonies were orally infected with dengue virus-infected fresh blood meal. Dengue virus load was measured using quantitative RT-PCR at four-time intervals in the salivary glands, midguts and ovaries.
RESULTS: Wolbachia did not significantly affect Malaysian Ae. albopictus dengue infection or the dissemination rate for all four dengue virus serotypes. Malaysian Ae. albopictus had the highest replication kinetics for DENV-1 and the highest salivary gland and midgut infection rate for DENV-4.
CONCLUSION: Wolbachia, which naturally exists in Malaysian Ae. albopictus, does not significantly affect dengue virus replication. Malaysian Ae. albopictus is susceptible to dengue virus infections and capable of transmitting dengue virus, especially DENV-1 and DENV-4. Removal of Wolbachia from Malaysian Ae. albopictus would not reduce their susceptibility status.
OBJECTIVE: To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.
EVIDENCE REVIEW: The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.
FINDINGS: In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.
CONCLUSIONS AND RELEVANCE: In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.
METHODS: COVID-19 samples that tested positive by reverse transcription polymerase chain reaction and with cycle threshold values <30 were obtained throughout Malaysia. Sequencing of SARS-CoV-2 complete genomes was performed using Illumina, Oxford Nanopore, or Ion Torrent platforms. A total of 6163 SARS-CoV-2 complete genome sequences were generated over the surveillance period. All sequences were submitted to the Global Initiative on Sharing All Influenza Data database.
RESULTS: From June 2021 to January 2022, Malaysia experienced the fourth wave of COVID-19 dominated by the Delta variant of concern, including the original B.1.617.2 lineage and descendant AY lineages. The B.1.617.2 lineage was identified as the early dominant circulating strain throughout the country but over time, was displaced by AY.59 and AY.79 lineages in Peninsular (west) Malaysia, and the AY.23 lineage in east Malaysia. In December 2021, pilgrims returning from Saudi Arabia facilitated the introduction and spread of the BA.1 lineage (Omicron variant of concern) in the country.
CONCLUSION: The changing trends of circulating SARS-CoV-2 lineages were identified, with differences observed between west and east Malaysia. This initiative highlighted the importance of leveraging research expertise in the country to facilitate pandemic response and preparedness.
METHODS: We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state's pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy.
RESULTS: A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram's sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 - 0·92) respectively.
CONCLUSION: Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions.
METHODS: This retrospective observational study included 185 families of paediatric COVID-19 cases from 1 February 2020 to 31 December 2020. We identified the index case for each household and gathered the socio-demographic, epidemiological investigation results and risk factors for household transmission from medical case records. The secondary attack rate was calculated, and logistic regression analyses were used to identify risk factors associated with secondary household transmission of SARS-CoV-2.
RESULTS: Of the 848 household contacts, 466 acquired secondary infections, resulting in a secondary attack rate of 55%. The median age of the secondary cases was 12 years. Female household contacts and household contacts who slept in the same room with the index case were significantly associated with increased risk for COVID-19. Other independent risk factors associated with higher transmission risk in the household included an index case who was symptomatic, a household index case aged greater than 18 years and a male household index case.
CONCLUSIONS: High rates of household transmission of COVID-19 were found, indicating households were a major setting of transmission of SARS-CoV-2. Our data provide insight into the risk factors for household transmission of SARS-CoV-2 in Malaysia.