Factors affecting quality management at the Thai national institute of health.

PURPOSE: The purpose of this paper is to confirm and examine organization-related factors that could affect quality management at the Thai national reference laboratory known as National Institute of Health. DESIGN/METHODOLOGY/APPROACH: The authors invited 340 laboratory staff members to complete a questionnaire that enquired about their skills, opinions, perceptions, leadership, work environment, organizational culture and organizational commitment in relation to quality management. Confirmatory factor analysis (CFA) and multiple linear regression were used to analyze the data. FINDINGS: In total, 65 percent of institute members responded to the questionnaire. CFA revealed that all factors were related to quality management. Three factors, leadership, organizational commitment and work environment, significantly affected quality management, but organizational culture did not. RESEARCH LIMITATIONS/IMPLICATIONS: Other data types should be collected for an in-depth understanding, i.e. focus groups or in-depth interviews. A longitudinal study could also enhance quality management understanding to see how each variable changes over time. ORIGINALITY/VALUE: Analyzing quality management through confirmatory factor and regression analysis showed that the four analyzed variables are statistically significant in relation to quality management at the laboratory. Managers could apply this information to revise the current policy.

Dengue diversity across spatial and temporal scales: Local structure and the effect of host population size.

A fundamental mystery for dengue and other infectious pathogens is how observed patterns of cases relate to actual chains of individual transmission events. These pathways are intimately tied to the mechanisms by which strains interact and compete across spatial scales. Phylogeographic methods have been used to characterize pathogen dispersal at global and regional scales but have yielded few insights into the local spatiotemporal structure of endemic transmission. Using geolocated genotype (800 cases) and serotype (17,291 cases) data, we show that in Bangkok, Thailand, 60% of dengue cases living <200 meters apart come from the same transmission chain, as opposed to 3% of cases separated by 1 to 5 kilometers. At distances <200 meters from a case (encompassing an average of 1300 people in Bangkok), the effective number of chains is 1.7. This number rises by a factor of 7 for each 10-fold increase in the population of the "enclosed" region. This trend is observed regardless of whether population density or area increases, though increases in density over 7000 people per square kilometer do not lead to additional chains. Within Thailand these chains quickly mix, and by the next dengue season viral lineages are no longer highly spatially structured within the country. In contrast, viral flow to neighboring countries is limited. These findings are consistent with local, density-dependent transmission and implicate densely populated communities as key sources of viral diversity, with home location the focal point of transmission. These findings have important implications for targeted vector control and active surveillance.