Legionella and legionellosis in touristic-recreational facilities: Influence of climate factors and geostatistical analysis in Southern Italy (2001–2017)

Giglio, Osvalda De; Fasano, Fabrizio; Diella, Giusy; Lopuzzo, Marco; Napoli, Christian; Apollonio, Francesca; Brigida, Silvia; Calia, Carla; Campanale, C.; Marzella, Angelo; Pousis, Chrysovalentinos; Rutigliano, Stefania; Triggiano, Francesco; Caggiano, Giuseppina; Montagna, Maria Teresa

doi:10.1016/j.envres.2019.108721

Cited by 32 publications

(34 citation statements)

References 53 publications

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“…This result was consistent with a research in Ohio which showed that water temperature had an association with Legionella colonization [27]. However, is not consistent with a research in Italy that showed presence of Legionella was not affected by water temperature [32]. Sample collection in this study was carried for a full one year.…”

Section: Discussionsupporting

confidence: 82%

Investigation of Virulence Genes and Biofilm Formation Among Legionella Pneumophila Isolated from Hospital Water Sources

mirkalantari

Hayatimehr

Amirmozafari

et al. 2020

Preprint

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Background: Legionella pneumophila as a ubiquitous bacterium is inherently resistant to chlorine in tap water. It can easily enter water piping systems and get transmitted to immunocompromised populations and cause severe pneumonia. Owing to the fact that its presence in water sources doesn’t necessarily lead to onset of disease; therefore, several factors such as inhaled bacteria dose, virulence factors and diversity of serogroups can be considered as contributing factors. The main aim of current project was to investigate the contamination rate of hospital water systems with Legionella by culture and evaluate presence of major virulence factor genes as well as the ability to form biofilms among the Legionella isolates. Results: Twelve (12%) of the 100 water samples produced positive results in culture method. Additional confirmation was performed by PCR method with specific primers for Legionella genus (16SrRNA) and pneumophila species (mip). Fifty (5%) samples of 12 with positive culture have a colony forming unit higher than 1000cfu/100 ml. Legionella were isolated with a rate of 8%, 3% and 1% from shower heads, oxygen humidifier bottle and water bath, respectively. PCR assay for the virulence genes showed that all 12 (100%) isolates were positive for mip genes, 9 (75%) were positive for dot gene, 8 (66.66%) were positive for hsp, 6(50%) were positive for lvh and 4(33.33%) for rtx. Two of the isolates displayed higher ability to form biofilm in reference to the standard strain.Conclusion: Although the presence of Legionella pneumophila in hospital environment does not necessarily confer a threat to public health; continuous monitoring of water sources should be conducted in order to avoid elevated concentration of this bacterium and visible biofilm formation.

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Section: Discussionsupporting

confidence: 82%

Investigation of Virulence Genes and Biofilm Formation Among Legionella Pneumophila Isolated from Hospital Water Sources

mirkalantari

Hayatimehr

Amirmozafari

et al. 2020

Preprint

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“…For example, Fisman and Dunn et al found the largest effects to be higher relative humidity/precipitation on day 9, but they also detected an effect of wind speed on day 7 [5,21]. With respect to temperature, contradictory results have been reported in the direction of the effect (negative [14,15] and positive [16][17][18][19]) and in the lag. Halsby et al reported a high disease risk at high temperatures (up to 9 weeks delay) with high relative humidity [17].…”

Section: Discussionmentioning

confidence: 99%

Short-term associations between Legionnaires' disease incidence and meteorological variables in Belgium, 2011–2019

et al. 2020

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The number of reported cases with Legionnaires' disease (LD) is increasing in Belgium. Previous studies have investigated the associations between LD incidence and meteorological factors, but the Belgian data remained unexplored. We investigated data collected between 2011 and 2019. Daily exposure data on temperature, relative humidity, precipitation and wind speed was obtained from the Royal Meteorological Institute for 29 weather stations. Case data were collected from the national reference centre and through mandatory notification. Daily case and exposure data were aggregated by province. We conducted a time-stratified case-crossover study. The ‘at risk’ period was defined as 10 to 2 days prior to disease onset. The corresponding days in the other study years were selected as referents. We fitted separate conditional Poisson models for each day in the ‘at risk’ period and a distributed lag non-linear model (DLNM) which fitted all data in one model. LD incidence showed a yearly peak in August and September. A total of 614 cases were included. Given seasonality, a sequence of precipitation, followed by high relative humidity and low wind speed showed a statistically significant association with the number of cases 6 to 4 days later. We discussed the advantages of DLNM in this context.

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“…The Euclidean distance (shortest straight-line distance) was used among each patch, with the 'Inverse distance' spatial relationship parameter, which proportionally weights the influence of neighboring features with respect to the target feature depending on their distance, e.g. the more distant one patch is from another, the lower their mutual influence will be (ESRI 2010, De Giglio et al 2019, Iannella et al 2019a, Sánchez-Martín et al 2019. Considering all these settings, sampling bias is buffered as much as possible, both because of the low relative influence that the HSA gave to the non-sampled patch (based on the Inverse distance parameter) and because of the false positives' detection and correction.…”

Section: Gi* Statistics For Hotspot and Coldspot Analysismentioning

confidence: 99%

“…Despite their scientific accuracy, all these approaches often lack a measure of statistical significance, i.e. the identification of a coldspot or hotspot which significantly differs from its surroundings, based on zonal-statistics (De Giglio et al 2019, Iannella et al 2019a, Sánchez-Martín et al 2019. In this study, we aim at identifying the main hotspots for the conservation of the European stygobitic Crustacea Copepoda Harpacticoida at the groundwater habitat scale addressing our study to available species records.…”

Section: Introductionmentioning

confidence: 99%

Jumping into the grids: mapping biodiversity hotspots in groundwater habitat types across Europe

Iannella

Fiasca

Lorenzo³

et al. 2020

Ecography

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Biodiversity hotspots are routinely identified by grid‐based analyses, despite grids encompassing different habitats, thus hindering the potential to assess which habitat type accounts for the conservation priority assigned to a grid. In this study, we aimed at identifying the main hotspots for the conservation of the European stygobitic Crustacea Copepoda Harpacticoida at the groundwater habitat scale. A multi‐metric approach was used, based on six biodiversity indicators: species richness, endemicity, evolutionary origin, phylogenetic rarity, taxonomic distinctness, habitat specificity. The Hot Spot Analysis, based on the statistics Getis‐Ord Gi*, was used to compare the local to the global average values of each indicator to identify hotspots of conservation. The operational units used to perform the analyses were the groundwater habitat types, in order to gather all the possible patterns of spatial occupancy in terms of habitat variability. Eight biodiversity hotspots of stygobitic Crustacea Harpacticoida were highlighted: 1) the Pyrenees (Spain and France), 2) the Jura Massif (France), 3) the Alpine arc (France, Switzerland and Italy) embracing southward the River Po alluvial plain and the Slovenian External Dinarides, 4) the Central Apennines (Italy), 5) the Carpathian and Balkan mountains in Romania and at the boundary between western Bulgaria and north‐west Macedonia, 6) the Dinaric Alps (from Croatia to Albania), 7) the Sardinia Island, 8) an area in central‐northern Europe embracing Denmark, the Netherlands and Germany. The hotspots showed a clear spatial distribution in southern Europe where they were distributed predominantly south to the 45th parallel, in line to what reiteratively observed in previous studies. Many hotspots embraced more than one habitat type. The adoption of discrete groundwater habitat types as working spatial units rather than grids provided a higher resolution of where the stygobitic harpacticoid species effectively live, with the possibility of intervening more precisely to preserve them and their habitats.

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Legionella and legionellosis in touristic-recreational facilities: Influence of climate factors and geostatistical analysis in Southern Italy (2001–2017)

Cited by 32 publications

References 53 publications

Investigation of Virulence Genes and Biofilm Formation Among Legionella Pneumophila Isolated from Hospital Water Sources

Investigation of Virulence Genes and Biofilm Formation Among Legionella Pneumophila Isolated from Hospital Water Sources

Short-term associations between Legionnaires' disease incidence and meteorological variables in Belgium, 2011–2019

Jumping into the grids: mapping biodiversity hotspots in groundwater habitat types across Europe

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