MATERIALS AND METHODS: Chest radiographs of patients confirmed with COVID-19 in Hospital Tawau, Sabah, Malaysia were retrospectively analyzed by two radiologists. The radiographic pattern, distribution among subgroups and evolution of the disease over time were determined.
RESULTS: Among the 82 patients studied, 65 (79.3%) were males. Mean age of our cohorts was 37 ± 15 years. Baseline chest radiographs were abnormal in 37 patients (45.1%). Over half (52.9%) of the symptomatic patients had abnormal baseline radiograph. Among the children, patients with comorbidities, and patients 60 years of age and above, the abnormal radiographs were 14.3%, 71.4% and 69.3% respectively. Ground glass opacities were the commonest abnormal radiographic feature (35.4%), were peripherally located (35.4%) with predilection for the lower zones (29.3%). Most radiographic abnormalities were multifocal (20.7%) and frequently located in the left lung (19.5%). Radiographic recovery was observed in 15 of 18 patients (83%). Computed tomography (CT) scan demonstrated greater extent of the disease than observed in radiographs of the same patient.
CONCLUSIONS: COVID-19 pneumonia presented with a specific radiographic pattern in our cohort of patients, comprising of ground glass opacities in peripheral and basilar distribution, affecting a single lung field and was observed in both symptomatic and asymptomatic patients. Chest radiograph is a useful adjunct screening tool, and in combination with clinical and epidemiological assessment may facilitate in early diagnosis of COVID-19 pneumonia.
METHODS: We performed a prospective study of consecutive adults with NAFLD who were scheduled for a liver biopsy at a tertiary hospital in Malaysia. Patients underwent VLFF and CAP measurements on the same day as their liver biopsy. Histopathology analyses of liver biopsy specimens were reported according to the Nonalcoholic Steatohepatitis Clinical Research Network scoring system. Stereologic analysis was performed using grid-point counting method combined with the Delesse principle.
RESULTS: We analyzed data from 97 patients (mean age 57.0 ± 10.1 years; 44.33% male; 91.8% obese; 95.9% centrally obese). Based on histopathology analysis, the area under receiver operating characteristic curve (AUROC) for VLFF in detection of steatosis grade ≥S2 was 0.92 and for CAP the AUROC was 0.65 (P < .001). Based on stereological analysis, the AUROC for VLFF for detection of steatosis grade ≥S2 was 0.92 and for CAP the AUROC was 0.63, (P = .002); for identification of steatosis grade S3, the AUROC for VLFF was 0.92 and for CAP the AUROC was 0.68 (P < .001).
CONCLUSIONS: In a prospective study of patients with NAFLD undergoing liver biopsy analysis, we found VLFF to more accurately determine grade of hepatic steatosis than CAP.
METHODS: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class.
RESULTS: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60% tree cover) whereas the Dirus Complex was predicted to occur in areas with 10-100% tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas.
CONCLUSIONS: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.
METHODOLOGY/PRINCIPAL FINDINGS: A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines).
CONCLUSIONS/SIGNIFICANCE: We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.