3 resultados para surveillance systems
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
The emergency of infection by highly pathogenic avian influenza virus (HPAI) subtype H5N1 has focused the attention of the world scientific community, requiring the prompt provision of effective control systems for early detection of the circulation of low pathogenic influenza H5 viruses (LPAI) in populations of wild birds to prevent outbreaks of highly pathogenic (HPAI) in populations of domestic birds with possible transmission to humans. The project stems from the aim to provide, through a preliminary analysis of data obtained from surveillance in Italy and Europe, a preliminary study about the virus detection rates and the development of mathematical models, an objective assessment of the effectiveness of avian influenza surveillance systems in wild bird populations, and to point out guidelines to support the planning process of the sampling activities. The results obtained from the statistical processing quantify the sampling effort in terms of time and sample size required, and simulating different epidemiological scenarios identify active surveillance as the most suitable for endemic LPAI infection monitoring in wild waterfowl, and passive surveillance as the only really effective tool in early detecting HPAI H5N1 circulation in wild populations. Given the lack of relevant information on H5N1 epidemiology, and the actual finantial and logistic constraints, an approach that makes use of statistical tools to evaluate and predict monitoring activities effectiveness proves to be of primary importance to direct decision-making and make the best use of available resources.
Resumo:
Salmonella and Campylobacter are common causes of human gastroenteritis. Their epidemiology is complex and a multi-tiered approach to control is needed, taking into account the different reservoirs, pathways and risk factors. In this thesis, trends in human gastroenteritis and food-borne outbreak notifications in Italy were explored. Moreover, the improved sensitivity of two recently-implemented regional surveillance systems in Lombardy and Piedmont was evidenced, providing a basis for improving notification at the national level. Trends in human Salmonella serovars were explored: serovars Enteritidis and Infantis decreased, Typhimurium remained stable and 4,[5],12:i:-, Derby and Napoli increased, suggesting that sources of infection have changed over time. Attribution analysis identified pigs as the main source of human salmonellosis in Italy, accounting for 43–60% of infections, followed by Gallus gallus (18–34%). Attributions to pigs and Gallus gallus showed increasing and decreasing trends, respectively. Potential bias and sampling issues related to the use of non-local/non-recent multilocus sequence typing (MLST) data in Campylobacter jejuni/coli source attribution using the Asymmetric Island (AI) model were investigated. As MLST data become increasingly dissimilar with increasing geographical/temporal distance, attributions to sources not sampled close to human cases can be underestimated. A combined case-control and source attribution analysis was developed to investigate risk factors for human Campylobacter jejuni/coli infection of chicken, ruminant, environmental, pet and exotic origin in The Netherlands. Most infections (~87%) were attributed to chicken and cattle. Individuals infected from different reservoirs had different associated risk factors: chicken consumption increased the risk for chicken-attributed infections; animal contact, barbecuing, tripe consumption, and never/seldom chicken consumption increased that for ruminant-attributed infections; game consumption and attending swimming pools increased that for environment-attributed infections; and dog ownership increased that for environment- and pet-attributed infections. Person-to-person contacts around holiday periods were risk factors for infections with exotic strains, putatively introduced by returning travellers.
Resumo:
Legionella is a Gram-negative bacterium that represent a public health issue, with heavy social and economic impact. Therefore, it is mandatory to provide a proper environmental surveillance and risk assessment plan to perform Legionella control in water distribution systems in hospital and community buildings. The thesis joins several methodologies in a unique workflow applied for the identification of non-pneumophila Legionella species (n-pL), starting from standard methods as culture and gene sequencing (mip and rpoB), and passing through innovative approaches as MALDI-TOF MS technique and whole genome sequencing (WGS). The results obtained, were compared to identify the Legionella isolates, and lead to four presumptive novel Legionella species identification. One of these four new isolates was characterized and recognized at taxonomy level with the name of Legionella bononiensis (the 64th Legionella species). The workflow applied in this thesis, help to increase the knowledge of Legionella environmental species, improving the description of the environment itself and the events that promote the growth of Legionella in their ecological niche. The correct identification and characterization of the isolates permit to prevent their spread in man-made environment and contain the occurrence of cases, clusters, or outbreaks. Therefore, the experimental work undertaken, could support the preventive measures during environmental and clinical surveillance, improving the study of species often underestimated or still unknown.