Does trade credit spur firm performance? A case study in Vietnam

Purpose: The paper aims to examine the impacts of trade credit on firm performance in Vietnam, representing a small transition economy with high openness environment. Design/Methodology/Aproach: Generalized least squares method of estimation was used to test the hypotheses on a sample of 279 companies listed on Ho Chi Minh City Stock Exchange (HOSE) during the 2012-2018 period, after the global financial crisis. Findings: The research findings support the positive influences of trade credit on firm performance of large businesses through both accounts receivable and trade payables and reversal effects on small business. These results show the advantages of large-scale companies own over the smaller ones in acquiring financing resources and imposing market power on their business partners, which help them optimize the benefits of trade credit. Practical implications: Research results indicate that corporates should increase their business scale to capitalize on the benefits of trade credit, and small-scale businesses should control the cost of trade credit. Originality/Value: The paper contributes to the literature in three main ways. Firstly, our exclusive offers new insights into understanding the behavior of Vietnamese firms, and this would give implications for transition economies in the world. Secondly, the study was carried out in the post-crisis period, with regulatory changes in banking management. Thirdly, this research compensates for the lack of empirical evidence in this field of research.peer-reviewe

Spatiotemporal analysis of historical records (2001-2012) on dengue fever in Vietnam and development of a statistical model for forecasting risk

Background: Dengue fever is the most widespread infectious disease of humans transmitted by Aedes mosquitoes. It is the leading cause of hospitalization and death in children in the Southeast Asia and western Pacific regions. We analyzed surveillance records from health centers in Vietnam collected between 2001–2012 to determine seasonal trends, develop risk maps and an incidence forecasting model. Methods: The data were analyzed using a hierarchical spatial Bayesian model that approximates its posterior parameter distributions using the integrated Laplace approximation algorithm (INLA). Meteorological, altitude and land cover (LC) data were used as predictors. The data were grouped by province (n = 63) and month (n = 144) and divided into training (2001–2009) and validation (2010–2012) sets. Thirteen meteorological variables, 7 land cover data and altitude were considered as predictors. Only significant predictors were kept in the final multivariable model. Eleven dummy variables representing month were also fitted to account for seasonal effects. Spatial and temporal effects were accounted for using Besag-York-Mollie (BYM) and autoregressive (1) models. Their levels of significance were analyzed using deviance information criterion (DIC). The model was validated based on the Theil’s coefficient which compared predicted and observed incidence estimated using the validation data. Dengue incidence predictions for 2010–2012 were also used to generate risk maps. Results: The mean monthly dengue incidence during the period was 6.94 cases (SD 14.49) per 100,000 people. Analyses on the temporal trends of the disease showed regular seasonal epidemics that were interrupted every 3 years (specifically in July 2004, July 2007 and September 2010) by major fluctuations in incidence. Monthly mean minimum temperature, rainfall, area under urban settlement/build-up areas and altitude were significant in the final model. Minimum temperature and rainfall had non-linear effects and lagging them by two months provided a better fitting model compared to using unlagged variables. Forecasts for the validation period closely mirrored the observed data and accurately captured the troughs and peaks of dengue incidence trajectories. A favorable Theil’s coefficient of inequality of 0.22 was generated. Conclusions: The study identified temperature, rainfall, altitude and area under urban settlement as being significant predictors of dengue incidence. The statistical model fitted the data well based on Theil’s coefficient of inequality, and risk maps generated from its predictions identified most of the high-risk provinces throughout the country

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Anal human papillomavirus prevalence and risk factors among men who have sex with men in Vietnam.

OBJECTIVES: Men who have sex with men (MSM) are at risk of human papillomavirus (HPV)-related cancers, while published data are scarce. This study determined HPV prevalence and risk factors in MSM in Vietnam to inform HPV prevention strategies in this key population. METHODS: A cross-sectional study of 799 MSM aged 16-50 years was conducted in Vietnam in 2017-2018. Information was collected on risk behaviours, and knowledge of HPV and anal cancer; rectal swabs were taken to detect anal HPV infection. An in-house polymerase chain reaction and Genoflow HPV array test kit were used for HPV detection and genotyping. RESULTS: The median age of the study participants was 25 years (range 18-52). Overall prevalence of any HPV and HPV16/18 infection was 32.3% and 11.0%, respectively. A higher prevalence of high-risk HPV infection to all 14 types tested was found in Ho Chi Minh City (30.9%) than in Hanoi (18.4%). High-risk HPV infection was associated with inconsistent condom use and history of engaging in sex under the influence of drugs (adjusted odds ratio (aOR), 2.27; 95% CI, 1.48-10.67), as well as having multiple sexual partners (aOR, 1.01; 95% CI, 1.00-1.02). CONCLUSIONS: High-risk anal HPV infections in Vietnamese MSM were significantly associated with risky sexual behaviours. A targeted HPV vaccination strategy would have substantial benefit for MSM in Vietnam

Prevalence and risk factors for human papillomavirus infection among female sex workers in Hanoi and Ho Chi Minh City, Viet Nam: a cross-sectional study

OBJECTIVE: Female sex workers (FSWs) are at high risk of human papillomavirus (HPV) infections and cervical cancer due to their high number of sexual partners. The objectives of this study were to determine the prevalence of HPV and identify risk factors for high-risk HPV infection among FSWs in Hanoi and Ho Chi Minh City (HCMC), Viet Nam. METHODS: A cross-sectional study was conducted in Hanoi and HCMC between December 2017 and May 2018. We surveyed and screened 699 FSWs aged 318 years for HPV infection and abnormal cytology. A multivariable modified Cox regression model was used to determine risk factors for high-risk HPV infection. RESULTS: The overall prevalence of any HPV, high-risk HPV and HPV-16/18 infection in the 699 FSWs was 26.3%, 17.6% and 4.0%, respectively, and were similar in both cities. Multiple infections were identified in 127 participants (69.0%). HPV-52 was the most prevalent (7%), followed by HPV-58 (6%). Abnormal cytology was detected in 91 participants (13.0%). FSWs who are divorced (adjusted prevalence ratio [aPR]: 1.96, 95% confidence interval [CI]: 1.01-3.81), widowed (aPR: 3.26, 95% CI: 1.49-7.12) or living alone (aPR: 1.85, 95% CI: 1.01-3.39) were associated with a higher prevalence of high-risk HPV infection. DISCUSSION: Almost one in five FSWs in Viet Nam are infected with high-risk HPV. This highlights the importance of prevention strategies such as HPV vaccination and screening in this high-risk group

Rifampicin resistant 'Mycobacterium tuberculosis' in Vietnam, 2020–2022

Objective: We conducted a descriptive analysis of multi-drug resistant tuberculosis (MDR-TB) in Vietnam’s two largest cities, Hanoi and Ho Chi Minh city. Methods: All patients with rifampicin resistant tuberculosis were recruited from Hanoi and surrounding provinces between 2020 and 2022. Additional patients were recruited from Ho Chi Minh city over the same time period. Demographic data were recorded from all patients, and samples collected, cultured, whole genome sequenced and analysed for drug resistance mutations. Genomic susceptibility predictions were made on the basis of the World Health Organization’s catalogue of mutations in Mycobacterium tuberculosis associated with drug resistance, version 2. Comparisons were made against phenotypic drug susceptibility test results where these were available. Multivariable logistic regression was used to assess risk factors for previous episodes of tuberculosis. Results: 233/265 sequenced isolates were of sufficient quality for analysis, 146 (63 %) from Ho Chi Minh City and 87 (37 %) from Hanoi. 198 (85 %) were lineage 2, 20 (9 %) were lineage 4, and 15 (6 %) were lineage 1. 17/211 (8 %) for whom HIV status was known were infected, and 109/214 (51 %) patients had had a previous episode of tuberculosis. The main risk factor for a previous episode was HIV infection (odds ratio 5.1 (95 % confidence interval 1.3–20.0); p = 0.021). Sensitivity for predicting first-line drug resistance from whole genome sequencing data was over 90 %, with the exception of pyrazinamide (85 %). For moxifloxacin and amikacin it was 50 % or less. Among rifampicin-resistant isolates, prevalence of resistance to each non-first-line drug was < 20 %. Conclusions: Drug resistance among most MDR-TB strains in Vietnam’s two largest cities is confined largely to first-line drugs. Living with HIV is the main risk factor among patients with MDR-TB for having had a previous episode of tuberculosis

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk-outcome associations. METHODS: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017