scholarly journals Applying probability-weighted incubation period distributions to traditional wind rose methodology to improve public health investigations of Legionnaires' disease outbreaks

2020 ◽  
Vol 148 ◽  
Author(s):  
D. Bays ◽  
E. Bennett ◽  
T. Finnie
Keyword(s):  
Incubation Period ◽  
Probability Distributions ◽  
Disease Outbreaks ◽  
Disease Outbreak ◽  
Relative Volume ◽  
Wind Rose ◽  
Outbreak Management ◽  
Legionnaires Disease ◽  
Potential Improvement ◽  
And Control

Abstract In the event of a Legionnaires' disease outbreak, rapid location and control of the source of bacteria are crucial for outbreak management and regulation. In this paper, we describe an enhancement of the traditional wind rose for epidemiological use; shifting the focus of measurement from relative frequency of the winds speeds and directions to the relative volume of air carried, whilst also incorporating probability distributions of disease incubation periods to refine identification of the important wind directions during a cases window of exposure, i.e. from which direction contaminated aerosols most likely originated. The probability-weighted wind rose offers a potential improvement over the traditional wind rose by weighting the importance of wind measurements through incorporation of probability of exposure given an individual's time of symptom onset (obtained through knowledge of the incubation period), and by instead focusing on the volume of carrying air which offers better insight into the most probable direction of the source. This then provides a probabilistic distribution of which direction the wind was blowing around the time of infection. We discuss how the probability-weighted wind rose can be implemented during a Legionnaires' disease outbreak, and how outbreak control teams might use it as supportive evidence to identify the most likely direction of the contaminated source from the presumed site of exposure. In addition, this paper discusses how minor adjustments can be made to the method allowing the probability-weighted wind rose to be applied to other non-communicable airborne diseases, providing the disease's probability distribution for the incubation period distribution is well known.

scholarly journals Incubation periods of enteric illnesses in foodborne outbreaks, United States, 1998–2013

2019 ◽  
Vol 147 ◽  
Author(s):  
S. J. Chai ◽  
W. Gu ◽  
K. A. O'Connor ◽  
L. C. Richardson ◽  
R. V. Tauxe
Keyword(s):  
United States ◽  
Incubation Period ◽  
Disease Outbreaks ◽  
Disease Outbreak ◽  
Outbreak Investigation ◽  
Foodborne Disease ◽  
Case Definitions ◽  
Viral Pathogens ◽  
Incubation Periods ◽  
Foodborne Outbreaks

Abstract Early in a foodborne disease outbreak investigation, illness incubation periods can help focus case interviews, case definitions, clinical and environmental evaluations and predict an aetiology. Data describing incubation periods are limited. We examined foodborne disease outbreaks from laboratory-confirmed, single aetiology, enteric bacterial and viral pathogens reported to United States foodborne disease outbreak surveillance from 1998–2013. We grouped pathogens by clinical presentation and analysed the reported median incubation period among all illnesses from the implicated pathogen for each outbreak as the outbreak incubation period. Outbreaks from preformed bacterial toxins (Staphylococcus aureus, Bacillus cereus and Clostridium perfringens) had the shortest outbreak incubation periods (4–10 h medians), distinct from that of Vibrio parahaemolyticus (17 h median). Norovirus, salmonella and shigella had longer but similar outbreak incubation periods (32–45 h medians); campylobacter and Shiga toxin-producing Escherichia coli had the longest among bacteria (62–87 h medians); hepatitis A had the longest overall (672 h median). Our results can help guide diagnostic and investigative strategies early in an outbreak investigation to suggest or rule out specific etiologies or, when the pathogen is known, the likely timeframe for exposure. They also point to possible differences in pathogenesis among pathogens causing broadly similar syndromes.

scholarly journals Characterization of Legionella Species from Watersheds in British Columbia, Canada

mSphere ◽  
2017 ◽  
Vol 2 (4) ◽  
Author(s):  
Michael A. Peabody ◽  
Jason A. Caravas ◽  
Shatavia S. Morrison ◽  
Jeffrey W. Mercante ◽  
Natalie A. Prystajecky ◽  
...  
Keyword(s):  
Relative Abundance ◽  
Human Disease ◽  
Disease Outbreaks ◽  
Water Systems ◽  
Control Measures ◽  
Land Uses ◽  
Temporal Study ◽  
Plumbing Systems ◽  
Legionnaires Disease ◽  
And Control

ABSTRACT Many species of Legionella can cause Legionnaires’ disease, a significant cause of bacterial pneumonia. Legionella in human-made water systems such as cooling towers and building plumbing systems are the primary sources of Legionnaires’ disease outbreaks. In this temporal study of natural aquatic environments, Legionella relative abundance was shown to vary in watersheds associated with different land uses. Analysis of the Legionella sequences detected at these sites revealed highly diverse populations that included potentially novel Legionella species. These findings have important implications for understanding the ecology of Legionella and control measures for this pathogen that are aimed at reducing human disease. Legionella spp. present in some human-made water systems can cause Legionnaires’ disease in susceptible individuals. Although legionellae have been isolated from the natural environment, variations in the organism’s abundance over time and its relationship to aquatic microbiota are poorly understood. Here, we investigated the presence and diversity of legionellae through 16S rRNA gene amplicon and metagenomic sequencing of DNA from isolates collected from seven sites in three watersheds with varied land uses over a period of 1 year. Legionella spp. were found in all watersheds and sampling sites, comprising up to 2.1% of the bacterial community composition. The relative abundance of Legionella tended to be higher in pristine sites than in sites affected by agricultural activity. The relative abundance levels of Amoebozoa, some of which are natural hosts of legionellae, were similarly higher in pristine sites. Compared to other bacterial genera detected, Legionella had both the highest richness and highest alpha diversity. Our findings indicate that a highly diverse population of legionellae may be found in a variety of natural aquatic sources. Further characterization of these diverse natural populations of Legionella will help inform prevention and control efforts aimed at reducing the risk of Legionella colonization of built environments, which could ultimately decrease the risk of human disease. IMPORTANCE Many species of Legionella can cause Legionnaires’ disease, a significant cause of bacterial pneumonia. Legionella in human-made water systems such as cooling towers and building plumbing systems are the primary sources of Legionnaires’ disease outbreaks. In this temporal study of natural aquatic environments, Legionella relative abundance was shown to vary in watersheds associated with different land uses. Analysis of the Legionella sequences detected at these sites revealed highly diverse populations that included potentially novel Legionella species. These findings have important implications for understanding the ecology of Legionella and control measures for this pathogen that are aimed at reducing human disease.

scholarly journals A systematic review on mobile health applications for foodborne disease outbreak management

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Genevie Ntshoe ◽  
Andronica Moipone Shonhiwa ◽  
Nevashan Govender ◽  
Nicola Page
Keyword(s):  
Systematic Review ◽  
Data Collection ◽  
Mobile Health ◽  
Mobile Applications ◽  
Disease Outbreaks ◽  
Disease Outbreak ◽  
Foodborne Disease ◽  
Outbreak Response ◽  
Public Health Action ◽  
Outbreak Management

Abstract Background Foodborne disease outbreaks are common and notifiable in South Africa; however, they are rarely reported and poorly investigated. Surveillance data from the notification system is suboptimal and limited, and does not provide adequate information to guide public health action and inform policy. We performed a systematic review of published literature to identify mobile application-based outbreak response systems for managing foodborne disease outbreaks and to determine the elements that the system requires to generate foodborne disease data needed for public action. Methods Studies were identified through literature searches using online databases on PubMed/Medline, CINAHL, Academic Search Complete, Greenfile, Library, Information Science & Technology. Search was limited to studies published in English during the period January 1990 to November 2020. Search strategy included various terms in varying combinations with Boolean phrases “OR” and “AND”. Data were collected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. A standardised data collection tool was used to extract and summarise information from identified studies. We assessed qualities of mobile applications by looking at the operating system, system type, basic features and functionalities they offer for foodborne disease outbreak management. Results Five hundred and twenty-eight (528) publications were identified, of which 48 were duplicates. Of the remaining 480 studies, 2.9% (14/480) were assessed for eligibility. Only one of the 14 studies met the inclusion criteria and reported on one mobile health application named MyMAFI (My Mobile Apps for Field Investigation). There was lack of detailed information on the application characteristics. However, based on minimal information available, MyMAFI demonstrated the ability to generate line lists, reports and offered functionalities for outbreak verification and epidemiological investigation. Availability of other key components such as environmental and laboratory investigations were unknown. Conclusions There is limited use of mobile applications on management of foodborne disease outbreaks. Efforts should be made to set up systems and develop applications that can improve data collection and quality of foodborne disease outbreak investigations.

scholarly journals A Legionnaires’ Disease Cluster in a Private Building in Italy

2021 ◽  
Vol 18 (13) ◽  
pp. 6922
Author(s):  
Maria Luisa Ricci ◽  
Maria Cristina Rota ◽  
Maria Grazia Caporali ◽  
Antonietta Girolamo ◽  
Maria Scaturro
Keyword(s):  
Severe Pneumonia ◽  
Control Measures ◽  
Health Concern ◽  
Human Consumption ◽  
Domestic Water ◽  
Quality Of Water ◽  
Legionnaires Disease ◽  
Prevention And Control Measures ◽  
Private Homes ◽  
And Control

Legionnaires’ disease (LD) is a severe pneumonia caused by bacteria belonging to the genus Legionella. This is a major public health concern and infections are steadily increasing worldwide. Several sources of infection have been identified, but they have not always been linked to human isolates by molecular match. The well-known Legionella contamination of private homes has rarely been associated with the acquisition of the disease, although some patients never left their homes during the incubation period. This study demonstrated by genomic matching between clinical and environmental Legionella isolates that the source of an LD cluster was a private building. Monoclonal antibodies and sequence-based typing were used to type the isolates, and the results clearly demonstrated the molecular relationship between the strains highlighting the risk of contracting LD at home. To contain this risk, the new European directive on the quality of water intended for human consumption has introduced for the first time Legionella as a microbiological parameter to be investigated in domestic water systems. This should lead to a greater attention to prevention and control measures for domestic Legionella contamination and, consequently, to a possible reduction in community acquired LD cases.

scholarly journals Subcritical Transmission in the Early Stage of COVID-19 in Korea

2021 ◽  
Vol 18 (3) ◽  
pp. 1265
Author(s):  
Yong Sul Won ◽  
Jong-Hoon Kim ◽  
Chi Young Ahn ◽  
Hyojung Lee
Keyword(s):  
Incubation Period ◽  
Early Stage ◽  
Probability Distributions ◽  
Likelihood Estimation ◽  
Contact Tracing ◽  
Statistical Characterization ◽  
Serial Interval ◽  
Imported Cases ◽  
The Mean ◽  
Reporting Delays

While the coronavirus disease 2019 (COVID-19) outbreak has been ongoing in Korea since January 2020, there were limited transmissions during the early stages of the outbreak. In the present study, we aimed to provide a statistical characterization of COVID-19 transmissions that led to this small outbreak. We collated the individual data of the first 28 confirmed cases reported from 20 January to 10 February 2020. We estimated key epidemiological parameters such as reporting delay (i.e., time from symptom onset to confirmation), incubation period, and serial interval by fitting probability distributions to the data based on the maximum likelihood estimation. We also estimated the basic reproduction number (R0) using the renewal equation, which allows for the transmissibility to differ between imported and locally transmitted cases. There were 16 imported and 12 locally transmitted cases, and secondary transmissions per case were higher for the imported cases than the locally transmitted cases (nine vs. three cases). The mean reporting delays were estimated to be 6.76 days (95% CI: 4.53, 9.28) and 2.57 days (95% CI: 1.57, 4.23) for imported and locally transmitted cases, respectively. The mean incubation period was estimated to be 5.53 days (95% CI: 3.98, 8.09) and was shorter than the mean serial interval of 6.45 days (95% CI: 4.32, 9.65). The R0 was estimated to be 0.40 (95% CI: 0.16, 0.99), accounting for the local and imported cases. The fewer secondary cases and shorter reporting delays for the locally transmitted cases suggest that contact tracing of imported cases was effective at reducing further transmissions, which helped to keep R0 below one and the overall transmissions small.

scholarly journals Severe acute respiratory syndrome (SARS) related coronavirus in bats

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Rong Geng ◽  
Peng Zhou
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Current Knowledge ◽  
Disease Outbreaks ◽  
First Century ◽  
Intermediate Hosts ◽  
Human Coronavirus ◽  
Transmission Potential ◽  
Disease Agent ◽  
And Control ◽  
Genomic Similarity

AbstractThree major human coronavirus disease outbreaks, severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and 2019 coronavirus disease (COVID-19), occurred in the twenty-first century and were caused by different coronaviruses (CoVs). All these viruses are considered to have originated from bats and transmitted to humans through intermediate hosts. SARS-CoV-1 and SARS-CoV-2, disease agent of COVID-19, shared around 80% genomic similarity, and thus belong to SARS-related CoVs. As a natural reservoir of viruses, bats harbor numerous other SARS-related CoVs that could potentially infect humans around the world, causing SARS or COVID-19 like outbreaks in the future. In this review, we summarized the current knowledge of CoVs on geographical distribution, genetic diversity, cross-species transmission potential and possible pathogenesis in humans, aiming for a better understanding of bat SARS-related CoVs in the context of prevention and control.

IoT-based Precision Agriculture Platform: A Review

2021 ◽  
Vol 9 (9) ◽  
pp. 1419-1421
Author(s):  
Rutvik Solanki
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Agricultural Sector ◽  
Disease Outbreaks ◽  
Iot Platforms ◽  
High Level ◽  
New Applications ◽  
And Control ◽  
Use Of Internet ◽  
The Internet Of Things

Abstract: Technological advancements such as the Internet of Things (IoT) and Artificial Intelligence (AI) are helping to boost the global agricultural sector as it is expected to grow by around seventy percent in the next two decades. There are sensor-based systems in place to keep track of the plants and the surrounding environment. This technology allows farmers to watch and control farm operations from afar, but it has a few limitations. For farmers, these technologies are prohibitively expensive and demand a high level of technological competence. Besides, Climate change has a significant impact on crops because increased temperatures and changes in precipitation patterns increase the likelihood of disease outbreaks, resulting in crop losses and potentially irreversible plant destruction. Because of recent advancements in IoT and Cloud Computing, new applications built on highly innovative and scalable service platforms are now being developed. The use of Internet of Things (IoT) solutions has enormous promise for improving the quality and safety of agricultural products. Precision farming's telemonitoring system relies heavily on Internet of Things (IoT) platforms; therefore, this article quickly reviews the most common IoT platforms used in precision agriculture, highlighting both their key benefits and drawbacks

scholarly journals Legionnaires' Disease Outbreak at a Resort in Cozumel, Mexico

2016 ◽  
Vol 3 (3) ◽  
Author(s):  
Lee M. Hampton ◽  
Laurel Garrison ◽  
Jessica Kattan ◽  
Ellen Brown ◽  
Natalia A. Kozak-Muiznieks ◽  
...  
Keyword(s):  
United States ◽  
Potable Water ◽  
Water System ◽  
Disease Outbreak ◽  
Community Acquired Pneumonia ◽  
Health Departments ◽  
Medical Providers ◽  
Cozumel Island ◽  
European Working ◽  
Legionnaires Disease

Abstract Background.  A Legionnaires' disease (LD) outbreak at a resort on Cozumel Island in Mexico was investigated by a joint Mexico-United States team in 2010. This is the first reported LD outbreak in Mexico, where LD is not a reportable disease. Methods.  Reports of LD among travelers were solicited from US health departments and the European Working Group for Legionella Infections. Records from the resort and Cozumel Island health facilities were searched for possible LD cases. In April 2010, the resort was searched for possible Legionella exposure sources. The temperature and total chlorine of the water at 38 sites in the resort were measured, and samples from those sites were tested for Legionella. Results.  Nine travelers became ill with laboratory-confirmed LD within 2 weeks of staying at the resort between May 2008 and April 2010. The resort and its potable water system were the only common exposures. No possible LD cases were identified among resort workers. Legionellae were found to have extensively colonized the resort's potable water system. Legionellae matching a case isolate were found in the resort's potable water system. Conclusions.  Medical providers should test for LD when treating community-acquired pneumonia that is severe or affecting patients who traveled in the 2 weeks before the onset of symptoms. When an LD outbreak is detected, the source should be identified and then aggressively remediated. Because LD can occur in tropical and temperate areas, all countries should consider making LD a reportable disease if they have not already done so.

scholarly journals Temporal Evolution of Immunity Distributions in a Population with Waning and Boosting

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
M. V. Barbarossa ◽  
M. Polner ◽  
G. Röst
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Temporal Evolution ◽  
Disease Outbreaks ◽  
Population Level ◽  
Coupled System ◽  
Disease Outbreak ◽  
Periodic Disease ◽  
Evolution Of Immunity

We investigate the temporal evolution of the distribution of immunities in a population, which is determined by various epidemiological, immunological, and demographical phenomena: after a disease outbreak, recovered individuals constitute a large immune population; however, their immunity is waning in the long term and they may become susceptible again. Meanwhile, their immunity can be boosted by repeated exposure to the pathogen, which is linked to the density of infected individuals present in the population. This prolongs the length of their immunity. We consider a mathematical model formulated as a coupled system of ordinary and partial differential equations that connects all these processes and systematically compare a number of boosting assumptions proposed in the literature, showing that different boosting mechanisms lead to very different stationary distributions of the immunity at the endemic steady state. In the situation of periodic disease outbreaks, the waveforms of immunity distributions are studied and visualized. Our results show that there is a possibility to infer the boosting mechanism from the population level immune dynamics.

scholarly journals Complete Genome Sequences of the HistoricalLegionella pneumophilaStrains OLDA and Pontiac

2016 ◽  
Vol 4 (4) ◽  
Author(s):  
Jeffrey W. Mercante ◽  
Shatavia S. Morrison ◽  
Brian H. Raphael ◽  
Jonas M. Winchell
Keyword(s):  
Legionella Pneumophila ◽  
Complete Genome ◽  
Health Department ◽  
Sporadic Case ◽  
Disease Outbreak ◽  
Genome Sequences ◽  
Outbreak Strain ◽  
Legionnaires Disease

Here, we report the complete genome sequences ofLegionella pneumophilaserogroup 1 strains OLDA and Pontiac, which predate the 1976 Philadelphia Legionnaires’ disease outbreak. Strain OLDA was isolated in 1947 from an apparent sporadic case, and strain Pontiac caused an explosive outbreak at a Michigan health department in 1968.

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