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Morrison, Laura T. R., Benjamin Anderson, Alice Brower, et al. "Macroeconomic impact of Ebola outbreaks in Sub-Saharan Africa and potential mitigation of GDP loss with prophylactic Ebola vaccination programs." PLOS ONE 18, no. 4 (2023): e0283721. http://dx.doi.org/10.1371/journal.pone.0283721.
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Introduction Decisions about prevention of and response to Ebola outbreaks require an understanding of the macroeconomic implications of these interventions. Prophylactic vaccines hold promise to mitigate the negative economic impacts of infectious disease outbreaks. The objective of this study was to evaluate the relationship between outbreak size and economic impact among countries with recorded Ebola outbreaks and to quantify the hypothetical benefits of prophylactic Ebola vaccination interventions in these outbreaks. Methods The synthetic control method was used to estimate the causal impacts of Ebola outbreaks on per capita gross domestic product (GDP) of five countries in sub-Saharan Africa that have previously experienced Ebola outbreaks between 2000 and 2016, where no vaccines were deployed. Using illustrative assumptions about vaccine coverage, efficacy, and protective immunity, the potential economic benefits of prophylactic Ebola vaccination were estimated using the number of cases in an outbreak as a key indicator. Results The impact of Ebola outbreaks on the macroeconomy of the selected countries led to a decline in GDP of up to 36%, which was greatest in the third year after the onset of each outbreak and increased exponentially with the size of outbreak (i.e., number of reported cases). Over three years, the aggregate loss estimated for Sierra Leone from its 2014–2016 outbreak is estimated at 16.1 billion International$. Prophylactic vaccination could have prevented up to 89% of an outbreak’s negative impact on GDP, reducing the outbreak’s impact to as little as 1.6% of GDP lost. Conclusion This study supports the case that macroeconomic returns are associated with prophylactic Ebola vaccination. Our findings support recommendations for prophylactic Ebola vaccination as a core component of prevention and response measures for global health security.
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Heinzerling, Amy, Alyssa Nguyen, Matt Frederick, et al. "Workplaces Most Affected by COVID-19 Outbreaks in California, January 2020–August 2021." American Journal of Public Health 112, no. 8 (2022): 1180–90. http://dx.doi.org/10.2105/ajph.2022.306862.
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Objectives. To describe which industries have the highest burden of COVID-19 outbreaks in California. Methods. We assigned US census industry codes to COVID-19 outbreaks reported to the California Department of Public Health (CDPH) from January 1, 2020, to August 31, 2021, and determined numbers of outbreaks, numbers of outbreak-associated cases, and outbreak incidence levels by industry. We determined characteristics of outbreak-associated cases using individual case data linked to COVID-19 outbreaks. Results. Local health departments reported 19 893 COVID-19 outbreaks and 300 379 outbreak-associated cases to CDPH. The most outbreaks (47.8%) and outbreak-associated cases (54.8%) occurred in the health care and social assistance sector, where outbreak incidence levels were highest in skilled nursing facilities and residential care facilities (1306 and 544 outbreaks per 1000 establishments, respectively). High proportions of outbreaks also occurred in the retail trade (8.6%) and manufacturing (7.9%) sectors. Demographics of outbreak-associated cases varied across industries. Conclusions. Certain California industries, particularly in the health care, manufacturing, and retail sectors, have experienced a high burden of COVID-19 outbreaks during the pandemic. Public Health Implications. Tracking COVID-19 outbreaks by industry may help target prevention efforts, including workforce vaccination. (Am J Public Health. 2022;112(8):1180–1190. https://doi.org/10.2105/AJPH.2022.306862 )
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GARNER, DANISHA, and SOPHIA KATHARIOU. "Fresh Produce–Associated Listeriosis Outbreaks, Sources of Concern, Teachable Moments, and Insights." Journal of Food Protection 79, no. 2 (2016): 337–44. http://dx.doi.org/10.4315/0362-028x.jfp-15-387.
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ABSTRACT Foodborne transmission of Listeria monocytogenes was first demonstrated through the investigation of the 1981 Maritime Provinces outbreak involving coleslaw. In the following two decades, most listeriosis outbreaks involved foods of animal origin, e.g., deli meats, hot dogs, and soft cheeses. L. monocytogenes serotype 4b, especially epidemic clones I, II, and Ia, were frequently implicated in these outbreaks. However, since 2008 several outbreaks have been linked to diverse types of fresh produce: sprouts, celery, cantaloupe, stone fruit, and apples. The 2011 cantaloupe-associated outbreak was one of the deadliest foodborne outbreaks in recent U.S. history. This review discusses produce-related outbreaks of listeriosis with a focus on special trends, unusual findings, and potential paradigm shifts. With the exception of sprouts, implicated produce types were novel, and outbreaks were one-time events. Several involved serotype 1/2a, and in the 2011 cantaloupe-associated outbreak, serotype 1/2b was for the first time conclusively linked to a common-source outbreak of invasive listeriosis. Also in this outbreak, for the first time multiple strains were implicated in a common-source outbreak. In 2014, deployment of whole genome sequencing as part of outbreak investigation validated this technique as a pivotal tool for outbreak detection and speedy resolution. In spite of the unusual attributes of produce-related outbreaks, in all but one of the investigated cases (the possible exception being the coleslaw outbreak) contamination was traced to the same sources as those for outbreaks associated with other vehicles (e.g., deli meats), i.e., the processing environment and equipment. The public health impact of farm-level contamination remains uncharacterized. This review highlights knowledge gaps regarding virulence and other potentially unique attributes of produce outbreak strains, the potential for novel fresh produce items to become unexpectedly implicated in outbreaks, and the key role of good control strategies in the processing environment.
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Risebro, Helen L., Miguel F. Doria, Yvonne Andersson, et al. "Fault tree analysis of the causes of waterborne outbreaks." Journal of Water and Health 5, S1 (2007): 1–18. http://dx.doi.org/10.2166/wh.2007.136.
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Prevention and containment of outbreaks requires examination of the contribution and interrelation of outbreak causative events. An outbreak fault tree was developed and applied to 61 enteric outbreaks related to public drinking water supplies in the EU. A mean of 3.25 causative events per outbreak were identified; each event was assigned a score based on percentage contribution per outbreak. Source and treatment system causative events often occurred concurrently (in 34 outbreaks). Distribution system causative events occurred less frequently (19 outbreaks) but were often solitary events contributing heavily towards the outbreak (a mean % score of 87.42). Livestock and rainfall in the catchment with no/inadequate filtration of water sources contributed concurrently to 11 of 31 Cryptosporidium outbreaks. Of the 23 protozoan outbreaks experiencing at least one treatment causative event, 90% of these events were filtration deficiencies; by contrast, for bacterial, viral, gastroenteritis and mixed pathogen outbreaks, 75% of treatment events were disinfection deficiencies. Roughly equal numbers of groundwater and surface water outbreaks experienced at least one treatment causative event (18 and 17 outbreaks, respectively). Retrospective analysis of multiple outbreaks of enteric disease can be used to inform outbreak investigations, facilitate corrective measures, and further develop multi-barrier approaches.
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ANDERSSON, T., P. BJELKMAR, A. HULTH, J. LINDH, S. STENMARK, and M. WIDERSTRÖM. "Syndromic surveillance for local outbreak detection and awareness: evaluating outbreak signals of acute gastroenteritis in telephone triage, web-based queries and over-the-counter pharmacy sales." Epidemiology and Infection 142, no. 2 (2013): 303–13. http://dx.doi.org/10.1017/s0950268813001088.
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SUMMARYFor the purpose of developing a national system for outbreak surveillance, local outbreak signals were compared in three sources of syndromic data – telephone triage of acute gastroenteritis, web queries about symptoms of gastrointestinal illness, and over-the-counter (OTC) pharmacy sales of antidiarrhoeal medication. The data sources were compared against nine known waterborne and foodborne outbreaks in Sweden in 2007–2011. Outbreak signals were identified for the four largest outbreaks in the telephone triage data and the two largest outbreaks in the data on OTC sales of antidiarrhoeal medication. No signals could be identified in the data on web queries. The signal magnitude for the fourth largest outbreak indicated a tenfold larger outbreak than officially reported, supporting the use of telephone triage data for situational awareness. For the two largest outbreaks, telephone triage data on adult diarrhoea provided outbreak signals at an early stage, weeks and months in advance, respectively, potentially serving the purpose of early event detection. In conclusion, telephone triage data provided the most promising source for surveillance of point-source outbreaks.
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Manning, G., B. Duim, T. Wassenaar, J. A. Wagenaar, A. Ridley, and D. G. Newell. "Evidence for a Genetically Stable Strain ofCampylobacter jejuni." Applied and Environmental Microbiology 67, no. 3 (2001): 1185–89. http://dx.doi.org/10.1128/aem.67.3.1185-1189.2001.
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ABSTRACT The genetic stability of selected epidemiologically linked strains of Campylobacter jejuni during outbreak situations was investigated by using subtyping techniques. Strains isolated from geographically related chicken flock outbreaks in 1998 and from a human outbreak in 1981 were investigated. There was little similarity in the strains obtained from the different chicken flock outbreaks; however, the strains from each of three chicken outbreaks, including strains isolated from various environments, were identical as determined byfla typing, amplified fragment length polymorphism (AFLP) analysis, and pulsed-field gel electrophoresis, which confirmed the genetic stability of these strains during the short time courses of chicken flock outbreaks. The human outbreak samples were compared with strain 81116, which originated from the same outbreak but has since undergone innumerable laboratory passages. Two main AFLP profiles were recognized from this outbreak, which confirmed the serotyping results obtained at the time of the outbreak. The major type isolated from this outbreak (serotype P6:L6) was exemplified by strain 81116. Despite the long existence of strain 81116 as a laboratory strain, the AFLP profile of this strain was identical to the profiles of all the other historical P6:L6 strains from the outbreak, indicating that the genotype has remained stable for almost 20 years. Interestingly, the AFLP profiles of the P6:L6 group of strains from the human outbreak and the strains from one of the recent chicken outbreaks were also identical. This similarity suggests that some clones ofC. jejuni remain genetically stable in completely different environments over long periods of time and considerable geographical distances.
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BROWN, L. G., E. R. HOOVER, C. A. SELMAN, E. W. COLEMAN, and H. SCHURZ ROGERS. "Outbreak characteristics associated with identification of contributing factors to foodborne illness outbreaks." Epidemiology and Infection 145, no. 11 (2017): 2254–62. http://dx.doi.org/10.1017/s0950268817001406.
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SUMMARYInformation on the factors that cause or amplify foodborne illness outbreaks (contributing factors), such as ill workers or cross-contamination of food by workers, is critical to outbreak prevention. However, only about half of foodborne illness outbreaks reported to the United States’ Centers for Disease Control and Prevention (CDC) have an identified contributing factor, and data on outbreak characteristics that promote contributing factor identification are limited. To address these gaps, we analyzed data from 297 single-setting outbreaks reported to CDC's new outbreak surveillance system, which collects data from the environmental health component of outbreak investigations (often called environmental assessments), to identify outbreak characteristics associated with contributing factor identification. These analyses showed that outbreak contributing factors were more often identified when an outbreak etiologic agent had been identified, when the outbreak establishment prepared all meals on location and served more than 150 meals a day, when investigators contacted the establishment to schedule the environmental assessment within a day of the establishment being linked with an outbreak, and when multiple establishment visits were made to complete the environmental assessment. These findings suggest that contributing factor identification is influenced by multiple outbreak characteristics, and that timely and comprehensive environmental assessments are important to contributing factor identification. They also highlight the need for strong environmental health and food safety programs that have the capacity to complete such environmental assessments during outbreak investigations.
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GEORGE, D. B., and A. R. MANGES. "A systematic review of outbreak and non-outbreak studies of extraintestinal pathogenicEscherichia colicausing community-acquired infections." Epidemiology and Infection 138, no. 12 (2010): 1679–90. http://dx.doi.org/10.1017/s0950268810001639.
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SUMMARYA systematic review of outbreak and non-outbreak studies of infections caused by extraintestinal pathogenicEscherichia coli(ExPEC) was conducted. This review examines the epidemiology, seasonality, source or mode of transmission, and temporal changes, based onE. coliserogroup, in ExPEC causing sporadicvs. outbreak-associated infections. Twelve outbreak and 28 non-outbreak studies were identified. The existence of ExPEC outbreaks was well supported. Three of four outbreak reports indicated peak periods during the winter months. Serogroups associated with outbreak infections ranged from 1% to 26% (average 11·4%)vs. (range 1–15%, average 3·5%) for serogroups associated with sporadic infections; the distribution of serogroups also differed for outbreak and non-outbreak infections. Study authors indicated that the outbreaks may have resulted from foodborne transmission, but direct evidence was unavailable. This review provides evidence that the epidemiology of endemicvs. epidemic ExPEC infections differs; however, study reporting quality limited epidemiological inferences.
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Patterson, Kaitlin, Erin McGill, Demy Dam, Anna Bellos, Cameron Mark Coulby, and Rachel McCormick. "Characterising COVID-19 school and childcare outbreaks in Canada in 2021: a surveillance study." BMJ Public Health 2, no. 1 (2024): e000248. http://dx.doi.org/10.1136/bmjph-2023-000248.
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BackgroundIn January 2021, the Public Health Agency of Canada launched the Canadian COVID-19 Outbreak Surveillance System to monitor outbreaks by setting. Schools and childcare centres were identified as settings of interest, as children play a key role in the transmission chain of other respiratory illnesses. This paper describes outbreak trends observed in school and childcare settings from January to December 2021 when many public health measures were in place.MethodsSchool and childcare outbreak data from five jurisdictions were included, representing 76% of the total Canadian population. Epidemiological curves were generated, trends in outbreak settings and cases’ age distribution over time were examined and descriptive statistics on outbreak size were calculated.ResultsIn 2021, most school and childcare outbreaks were in primary schools (42%). Severity was low in school and childcare settings (0.40% of outbreak cases hospitalised, <0.01% of outbreak cases deceased). Most school and childcare outbreaks reported fewer than 10 cases per outbreak. During the start of the 2021–2022 school year (September 2021), there were fewer outbreaks in secondary schools and fewer cases among those aged 12+ years compared with January–June of 2021.ConclusionDuring the study period, there was no observed association between an increase in school and childcare outbreaks and an increase in incidence rates in community case data. Children remain a population of interest for SARS-CoV-2; however, severity in paediatric populations remained low throughout 2021 and the risk of transmission in Canadian schools was low.
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Inkster, T., P. Wright, H. Kane, E. Paterson, S. Dodd, and J. Slorach. "Successive outbreaks of Group A streptococcus (GAS) in care of the elderly settings; lessons learned." Journal of Infection Prevention 13, no. 2 (2011): 38–43. http://dx.doi.org/10.1177/1757177411428367.
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Group A streptococcal (GAS) outbreaks in care of the elderly settings are rare. We describe two successive outbreaks involving care of the elderly patients. The first outbreak involved 18 patients and the second involved six patients and two healthcare workers. We describe the difficulties encountered controlling GAS outbreaks in care of the elderly settings and how the lessons learned from the first outbreak influenced management of the second incident. Stringent infection control measures including isolation until completion of treatment and re-screening for evidence of eradication were required to bring outbreak one under control. These measures were adopted early in outbreak two and we suspect that these measures and the rapid identification of carriers brought this second outbreak under control quickly.
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Curran, Evonne T. "Outbreak Column 9: Endoscopy-related outbreaks." Journal of Infection Prevention 14, no. 4 (2013): 139–44. http://dx.doi.org/10.1177/1757177413490815.
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Benitez-Valladares, David, Axel Kroeger, Gustavo Sánchez Tejeda, and Laith Hussain-Alkhateeb. "Validation of the Early Warning and Response System (EWARS) for dengue outbreaks: Evidence from the national vector control program in Mexico." PLOS Neglected Tropical Diseases 15, no. 12 (2021): e0009261. http://dx.doi.org/10.1371/journal.pntd.0009261.
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Background During 2017, twenty health districts (locations) implemented a dengue outbreak Early Warning and Response System (EWARS) in Mexico, which processes epidemiological, meteorological and entomological alarm indicators to predict dengue outbreaks and triggers early response activities. Out of the 20 priority districts where more than one fifth of all national disease transmission in Mexico occur, eleven districts were purposely selected and analyzed. Nine districts presented outbreak alarms by EWARS but without subsequent outbreaks (“non-outbreak districts”) and two presented alarms with subsequent dengue outbreaks (“outbreak districts”). This evaluation study assesses and compares the impact of alarm-informed response activities and the consequences of failing a timely and adequate response across the outbreak groups. Methods Five indicators of dengue outbreak response (larval control, entomological studies with water container interventions, focal spraying and indoor residual spraying) were quantitatively analyzed across two groups (”outbreak districts” and “non-outbreak districts”). However, for quality control purposes, only qualitative concluding remarks were derived from the fifth response indicator (fogging). Results The average coverage of vector control responses was significantly higher in non-outbreak districts and across all four indicators. In the “outbreak districts” the response activities started late and were of much lower intensity compared to “non-outbreak districts”. Vector control teams at districts-level demonstrated diverse levels of compliance with local guidelines for ‘initial’, ‘early’ and ‘late’ responses to outbreak alarms, which could potentially explain the different outcomes observed following the outbreak alarms. Conclusion Failing timely and adequate response of alarm signals generated by EWARS showed to negatively impact the disease outbreak control process. On the other hand, districts with adequate and timely response guided by alarm signals demonstrated successful records of outbreak prevention. This study presents important operational scenarios when failing or successding EWARS but warrants investigating the effectiveness and cost-effectiveness of EWARS using a more robust designs.
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HOOVER, E. RICKAMER, NICOLE HEDEEN, AMY FREELAND, et al. "Restaurant Policies and Practices Related to Norovirus Outbreak Size and Duration." Journal of Food Protection 83, no. 9 (2020): 1607–18. http://dx.doi.org/10.4315/jfp-20-102.
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ABSTRACT Norovirus is the leading cause of foodborne illness outbreaks in the United States, and restaurants are the most common setting of foodborne norovirus outbreaks. Therefore, prevention and control of restaurant-related foodborne norovirus outbreaks is critical to lowering the burden of foodborne illness in the United States. Data for 124 norovirus outbreaks and outbreak restaurants were obtained from Centers for Disease Control and Prevention surveillance systems and analyzed to identify relationships between restaurant characteristics and outbreak size and duration. Findings showed that restaurant characteristics, policies, and practices were linked with both outbreak size and outbreak duration. Compared with their counterparts, restaurants that had smaller outbreaks had the following characteristics: managers received food safety certification, managers and workers received food safety training, food workers wore gloves, and restaurants had cleaning policies. In addition, restaurants that provided food safety training to managers, served food items requiring less complex food preparation, and had fewer managers had shorter outbreaks compared with their counterparts. These findings suggest that restaurant characteristics play a role in norovirus outbreak prevention and intervention; therefore, implementing food safety training, policies, and practices likely reduces norovirus transmission, leading to smaller or shorter outbreaks. HIGHLIGHTS
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Kang, Hansol, Yvette Khachadourian, Dana Perella, Tiina M. Peritz, Kristen A. Feemster, and Susan E. Coffin. "The burden of gastroenteritis outbreaks in long-term care settings in Philadelphia, 2009–2018." Infection Control & Hospital Epidemiology 41, no. 11 (2020): 1310–14. http://dx.doi.org/10.1017/ice.2020.263.
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AbstractObjective:Gastroenteritis causes significant morbidity and mortality in long-term care facility (LTCF) residents, a growing population within the United States. We set out to better understand gastroenteritis outbreaks in LTCF by identifying outbreak and facility characteristics associated with outbreak incidence as well as outbreak duration and size.Design:We conducted a retrospective cross-sectional study on LTCFs in Philadelphia County from 2009 to 2018. Outbreak characteristics and interventions were extracted from Philadelphia Department of Public Health (PDPH) database and quality data on all LTCFs was extracted from Centers for Medicare and Medicaid Services Nursing Home Compare database.Results:We identified 121 gastroenteritis outbreaks in 49 facilities. Numbers of affected patients ranged from 2 to 211 patients (median patient illness rate, 17%). Staff were reported ill in 94 outbreaks (median staff illness rate, 5%). Outbreak facilities were associated with higher occupancy rates (91% vs 88%; P = .033) and total bed numbers (176 vs 122; P = .071) compared to nonoutbreak facilities. Higher rates of staff illness were associated with prolonged outbreaks (13% vs 4%; P < .001) and higher patient illness rates (9% vs 4%; P = .012). Prolonged outbreaks were associated with lower frequency of cohorting for outbreak management (13% vs 41%; P = .046).Conclusion:This study is the largest published analysis of gastroenteritis outbreaks in LTCFs. Facility characteristics and staff disease activity were associated with more severe outbreaks. Heightened surveillance for gastrointestinal symptoms among staff and increased use of cohorting might reduce the risk of prolonged gastroenteritis outbreaks in LTCF.
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Meima, Abraham, Jane Whelan, Jan Dijks, Nicoline van der Hagen, Marco van Duuren, and Aimée Tjon-A-Tsien. "Introducing a novel “real-time” outbreak alert and notification system to monitor SARS-CoV-2 outbreaks and case fatality in elderly care facilities, the Netherlands, 2020–2022." Journal of Public Health Research 12, no. 1 (2023): 227990362311606. http://dx.doi.org/10.1177/22799036231160634.
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Surveillance systems collating individual-level data may limit timely information sharing during rapidly evolving, infectious disease outbreaks. We present a digital outbreak alert and notification system ( MUIZ) in which institutional-level data are reported, allowing real-time outbreak monitoring in elderly care facilities (ECF). We describe trends in the number of outbreaks, mean case number per outbreak, and case-fatality rate (deaths/recovered + deaths) of SARS-CoV-2 in ECF notified through MUIZ in the Rotterdam area (April 2020-March 2022). Overall, 369 outbreaks were reported from 128 ECF that registered with MUIZ (approximately 85% of all ECF), and 114 (89%) notified at least one SARS-CoV-2 outbreak. Trends were consistent with the concurrent national epidemiology and societal control measures in place. MUIZ is a simple outbreak surveillance tool that was highly adopted and acceptable to users. Dutch PHS regions are increasingly adopting the system and it has potential for adaptation and further development in similar institutional outbreak settings.
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Paphitis, Katherine, Camille Achonu, Sandra Callery, et al. "Beyond flu: Trends in respiratory infection outbreaks in Ontario healthcare settings from 2007 to 2017, and implications for non-influenza outbreak management." Canada Communicable Disease Report 47, no. 56 (2021): 269–75. http://dx.doi.org/10.14745/ccdr.v47i56a04.
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Background: Outbreaks cause significant morbidity and mortality in healthcare settings. Current testing methods can identify specific viral respiratory pathogens, yet the approach to outbreak management remains general. Objectives: Our aim was to examine pathogen-specific trends in respiratory outbreaks, including how attack rates, case fatality rates and outbreak duration differ by pathogen between hospitals and long-term care (LTC) and retirement homes (RH) in Ontario. Methods: Confirmed respiratory outbreaks in Ontario hospitals and LTC/RH reported between September 1, 2007, and August 31, 2017, were extracted from the integrated Public Health Information System (iPHIS). Median attack rates and outbreak duration and overall case fatality rates of pathogen-specific outbreaks were compared in both settings. Results: Over the 10-year surveillance period, 9,870 confirmed respiratory outbreaks were reported in Ontario hospitals and LTC/RH. Influenza was responsible for most outbreaks (32% in LTC/RH, 51% in hospitals), but these outbreaks were shorter and had lower attack rates than most non-influenza outbreaks in either setting. Human metapneumovirus, while uncommon (<4% of outbreaks) had high case fatality rates in both settings. Conclusion: Attack rates and case fatality rates varied by pathogen, as did outbreak duration. Development of specific outbreak management guidance that takes into account pathogen and healthcare setting may be useful to limit the burden of respiratory outbreaks.
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Lewer, Dan, Miranda Mindlin, and Rebecca Cordery. "P243 Could the current outbreak of hepatitis a in men who have sex with men in london have been predicted or prevented?" Sexually Transmitted Infections 93, Suppl 1 (2017): A95.3—A96. http://dx.doi.org/10.1136/sextrans-2017-053232.285.
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IntroductionThe current outbreak of Hepatitis A and the recent Shigella outbreak in men who have sex with men (MSM) highlight the importance of faeco-orally transmitted organisms in this population. This may suggest that outbreaks could be predicted or prevented.MethodsWe compared the age, sex and travel history of notifications of Hepatitis A with notifications of Shigella in South London between January 2010 and November 2016. We also reviewed documentation of previous outbreaks of Hepatitis A in MSM in London.ResultsMale and female cases of Hepatitis A had similar age profiles and a similar proportion reported recent travel. In contrast, Shigella cases peaked in males aged 30–39 with no travel history. Case notes for Hepatitis A notifications since January 2013 suggested fewer than five in MSM. Although this review suggested very few cases in recent years, outbreaks of Hepatitis A among MSM in London were documented in the late 1990s and in 2003. The second outbreak was associated with strains that caused concurrent outbreaks in MSM across Europe. Public health response to these outbreaks recommended health promotion and opportunistic immunisation.DiscussionHepatitis A outbreaks occur sporadically in a transnational population of MSM. Few cases may occur between outbreaks and preventative actions may be deprioritised. However, group immunity is likely to be highest after an outbreak and then wane in the absence of immunisation, increasing the risk of another outbreak. Health promotion and immunisation may be valuable outside of outbreak contexts.
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Octavia, Sophie, Qinning Wang, Mark M. Tanaka, Sandeep Kaur, Vitali Sintchenko, and Ruiting Lan. "Delineating Community Outbreaks of Salmonella enterica Serovar Typhimurium by Use of Whole-Genome Sequencing: Insights into Genomic Variability within an Outbreak." Journal of Clinical Microbiology 53, no. 4 (2015): 1063–71. http://dx.doi.org/10.1128/jcm.03235-14.
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Whole-genome next-generation sequencing (NGS) was used to retrospectively examine 57 isolates from five epidemiologically confirmed community outbreaks (numbered 1 to 5) caused bySalmonella entericaserovar Typhimurium phage type DT170. Most of the human and environmental isolates confirmed epidemiologically to be involved in the outbreaks were either genomically identical or differed by one or two single nucleotide polymorphisms (SNPs), with the exception of those in outbreak 1. The isolates from outbreak 1 differed by up to 12 SNPs, which suggests that the food source of the outbreak was contaminated with more than one strain while each of the other four outbreaks was caused by a single strain. In addition, NGS analysis ruled in isolates that were initially not considered to be linked with the outbreak, which increased the total outbreak size by 107%. The mutation process was modeled by using known mutation rates to derive a cutoff value for the number of SNP difference to determine whether or not a case was part of an outbreak. For an outbreak with less than 1 month ofex vivo/in vivoevolution time, the maximum number of SNP differences between isolates is two or four using the lowest or highest mutation rate, respectively. NGS ofS. Typhimurium significantly increases the resolution of investigations of community outbreaks. It can also inform a more targeted public health response by providing important supplementary evidence that cases of disease are or are not associated with food-borne outbreaks ofS. Typhimurium.
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HEDBERG, C. W., K. L. PALAZZI-CHURAS, V. J. RADKE, C. A. SELMAN, and R. V. TAUXE. "The use of clinical profiles in the investigation of foodborne outbreaks in restaurants: United States, 1982–1997." Epidemiology and Infection 136, no. 1 (2007): 65–72. http://dx.doi.org/10.1017/s0950268807008199.
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SUMMARYImproving the efficiency of outbreak investigation in restaurants is critical to reducing outbreak-associated illness and improving prevention strategies. Because clinical characteristics of outbreaks are usually available before results of laboratory testing, we examined their use for determining contributing factors in outbreaks caused by restaurants. All confirmed foodborne outbreaks reported to the Centers for Disease Control and Prevention (CDC) from 1982 to 1997 were reviewed. Clinical profiles were developed based on outbreak characteristics. We compared the percentage of contributing factors by known agent and clinical profile to their occurrence in outbreaks of unclassified aetiology. In total, 2246 foodborne outbreaks were included: 697 (31%) with known aetiology and 1549 (69%) with aetiology undetermined. Salmonella accounted for 65% of outbreaks with a known aetiology. Norovirus-like clinical profiles were noted in 54% of outbreaks with undetermined aetiology. Improper holding times and temperatures were associated with outbreaks caused by Clostridium perfringens, Bacillus cereus, Staphylococcus aureus, and Salmonella, and also with outbreaks of undetermined aetiology that fitted diarrhoea-toxin and vomiting-toxin clinical profiles. Poor personal hygiene was associated with norovirus, Shigella, and Salmonella, and also with outbreaks that fitted norovirus-like and vomiting-toxin clinical profiles. Contributing factors were similar for outbreaks with known aetiology and for those where aetiology was assigned by corresponding clinical profile. Rapidly categorizing outbreaks by clinical profile, before results of laboratory testing are available, can help identification of factors which contributed to the occurrence of the outbreak and will promote timely and efficient outbreak investigations.
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Ojiambo, P. S., and E. L. Kang. "Modeling Spatial Frailties in Survival Analysis of Cucurbit Downy Mildew Epidemics." Phytopathology® 103, no. 3 (2013): 216–27. http://dx.doi.org/10.1094/phyto-07-12-0152-r.
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Cucurbit downy mildew caused by Pseudoperonospora cubensis is economically the most important disease of cucurbits globally, and the pathogen is disseminated aerially over a large spatial scale. Spatio-temporal spread of the disease was characterized during phase I (low and sporadic disease outbreaks) and II (rapid increase in disease outbreaks) of the epidemic using records collected from sentinel plots from 2008 to 2009 in 23 states in the eastern United States as part of the United States Department of Agriculture Cucurbit Downy Mildew ipmPIPE network. A substantive goal of this study was to explain the pattern of time to disease outbreak using important covariates while accounting for spatially correlated differences in risk of disease outbreak among the states. Survival analyses that accounts for spatial dependence were performed on time to disease outbreak, and posterior median frailties (or random effects) were mapped to identify states with high or low risk for disease outbreak. From February to October, disease occurred in 195 and 172 out of 413 and 556 cases monitored in 2008 and 2009, respectively. Disease outbreaks were spatially aggregated, with a spatial dependence of up to ≈1,025 km where clustering of outbreaks in phase I and II of the epidemic were similar. However, unlike in phase I of the epidemic, space–time point pattern analysis was significant (P < 0.0001) for outbreaks in phase II, during which the highest risk window as estimated by the space–time function was within 1.5 months and 500 km of the initial outbreak. The risk of disease outbreak peaked around July and decreased thereafter until the end of the study period. Spatially correlated analysis of time to disease outbreak indicated the need to incorporate spatial frailties in standard survival analysis models. Evaluation of alternative formulations of the spatial models demonstrated that a Bayesian hierarchical spatially structured frailty model best described time to disease outbreak. This frailty model showed clustering of outbreaks at the state level and indicated that states in the mid-Atlantic region have high spatial frailties and a high risk of downy mildew outbreak.
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Van Bael, Sunshine A., Annette Aiello, Anayansi Valderrama, Enrique Medianero, Mirna Samaniego, and S. Joseph Wright. "General herbivore outbreak following an El Niño-related drought in a lowland Panamanian forest." Journal of Tropical Ecology 20, no. 6 (2004): 625–33. http://dx.doi.org/10.1017/s0266467404001725.
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A severe outbreak of Lepidoptera followed the 1997–98 El Niño Southern Oscillation event, during which the climate in central Panama was unusually dry. The outbreak involved the larvae of at least 12 species of Lepidoptera and occurred at a seasonally dry, deciduous forest site, where extensive background data were available regarding climate, tree species and non-outbreak herbivory levels. Most Lepidoptera were associated with only one or two larval host plant species belonging to the same family, and the majority were monophagous during this study. During the outbreak, caterpillar densities for the major outbreak species averaged 1.6 larvae per young leaf and 0.18 larvae per leaf for leaves of all ages. For canopy trees and lianas, the mean level of leaf damage was 13.8%, ranging from 1–100%. Seven out of 20 tree species sustained most of the damage, with 21–37% of the leaf area consumed. Relative to non-outbreak years, damage levels increased by more than 250% during the outbreak. Single-species outbreaks were observed in other areas with a similar drought, but wetter forests in central Panama did not experience outbreaks during this period. Historically, fewer outbreaks have been reported from tropical forests than from temperate forests, however, similar El Niño-related outbreaks have occurred recently in several other locations throughout the tropics.
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Boulanger, Yan, Dominique Arseneault, Hubert Morin, Yves Jardon, Philip Bertrand, and Charles Dagneau. "Dendrochronological reconstruction of spruce budworm (Choristoneura fumiferana) outbreaks in southern Quebec for the last 400 years1This article is one of a selection of papers from the 7th International Conference on Disturbance Dynamics in Boreal Forests." Canadian Journal of Forest Research 42, no. 7 (2012): 1264–76. http://dx.doi.org/10.1139/x2012-069.
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It is argued that spruce budworm ( Choristoneura fumiferana (Clemens)) (SBW) outbreaks have tended to be more frequent, severe, and spatially synchronized since the beginning of the 20th century. However, few studies have assessed the long-term (>200 years) variations in SBW outbreak dynamics. We reconstructed the SBW outbreak history at the northern limit of the temperate forest in southern Quebec using dendrochronological material from old buildings and five old-growth stands. Our regional tree-ring chronology (1551–1995) represents one of the longest and most replicated insect outbreak reconstructions in North America. Nine potential outbreaks were identified (1976–1991, 1946–1959, 1915–1929, 1872–1903, 1807–1817, 1754–1765, 1706–1717, 1664–1670, and 1630–1638) with three additional uncertain outbreaks (1647–1661, 1606–1619, and 1564–1578). Results suggested that southern Quebec has experienced frequent and synchronized outbreaks throughout the last 400 years. Although outbreak frequency was higher during the 20th century (approximately 30 years) as compared with the 1660–1850 period (approximately 50 years), similar or even higher outbreak frequency might have occurred prior to 1660 (approximately 28 years). We did not find any evidence that the recent outbreak dynamics in southern Quebec is outside its historical range of the last 400 years. Previous studies based on living trees may have underestimated outbreak frequency and synchrony prior to 1900.
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Baker, Arthur W., Nicole Nehls, Iulian Ilieş, James C. Benneyan, and Deverick J. Anderson. "85. Use of Dual Statistical Process Control Charts for Early Detection of Surgical Site Infection Outbreaks at a Community Hospital Network." Open Forum Infectious Diseases 6, Supplement_2 (2019): S4—S5. http://dx.doi.org/10.1093/ofid/ofz359.009.
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Abstract Background We recently showed that the empirical use of a combination of 2 moving average (MA) statistical process control (SPC) charts was highly sensitive and specific for detecting potentially important increases in surgical site infection (SSI) rates. We performed this follow-up study to examine the performance of these same SPC charts when applied to known SSI outbreaks. Methods We retrospectively applied 2 MA SPC charts to all 30 SSI outbreaks investigated from 2007 to 2015 in a network of over 50 community hospitals. These outbreaks were detected via routine SSI surveillance activities that occurred in the network. We reviewed prior outbreak investigation documentation to determine the estimated time of outbreak onset and time of traditional surveillance outbreak detection. The first SPC chart utilized procedure-specific, composite SSI data from the hospital network for its baseline; the baseline for the second chart was calculated from SSI data from the outbreak hospital undergoing analysis. Both charts used rolling baseline windows but varied in baseline window size, rolling baseline lag, and MA window size. SPC chart outbreak detection occurred when either chart had a data point above the upper control limit of 1 standard deviation. Time of SPC detection was compared with both time of outbreak onset and time of traditional surveillance detection. Results With the dual chart approach, SPC detected all 30 outbreaks, including detection of 25 outbreaks (83%) prior to their estimated onset (Figure 1). SPC detection occurred a median of 16 months (interquartile range, 12–21 months) prior to the date of traditional outbreak detection, which never occurred prior to outbreak onset. Both individual SPC charts exhibited at least 90% sensitivity in outbreak detection, but the dual chart approach showed superior sensitivity and speed of detection (Figure 2). Conclusion A strategy that employed optimized, dual MA SPC charts retrospectively detected all SSI outbreaks that occurred over 9 years in a network of community hospitals. SPC outbreak detection occurred earlier than traditional surveillance detection. These optimized SPC charts merit prospective study to evaluate their ability to promote early detection of SSI clusters in real-world scenarios. Disclosures All Authors: No reported Disclosures.
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Lamberga, Kristīne, Arvo Viltrop, Imbi Nurmoja, et al. "The Effectiveness of Protection and Surveillance Zones in Detecting Further African Swine Fever Outbreaks in Domestic Pigs—Experience of the Baltic States." Viruses 16, no. 3 (2024): 334. http://dx.doi.org/10.3390/v16030334.
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In the event of an outbreak of African swine fever (ASF) in pig farms, the European Union (EU) legislation requires the establishment of a restricted zone, consisting of a protection zone with a radius of at least 3 km and a surveillance zone with a radius of at least 10 km around the outbreak. The main purpose of the restricted zone is to stop the spread of the disease by detecting further outbreaks. We evaluated the effectiveness and necessity of the restricted zone in the Baltic States by looking at how many secondary outbreaks were detected inside and outside the protection and surveillance zones and by what means. Secondary outbreaks are outbreaks with an epidemiological link to a primary outbreak while a primary outbreak is an outbreak that is not epidemiologically linked to any previous outbreak. From 2014 to 2023, a total of 272 outbreaks in domestic pigs were confirmed, where 263 (96.7%) were primary outbreaks and 9 (3.3%) were secondary outbreaks. Eight of the secondary outbreaks were detected by epidemiological enquiry and one by passive surveillance. Epidemiological enquiries are legally required investigations on an outbreak farm to find out when and how the virus entered the farm and to obtain information on contact farms where the ASF virus may have been spread. Of the eight secondary outbreaks detected by epidemiological investigations, six were within the protection zone, one was within the surveillance zone and one outside the restricted zone. Epidemiological investigations were therefore the most effective means of detecting secondary outbreaks, whether inside or outside the restricted zones, while active surveillance was not effective. Active surveillance are legally prescribed activities carried out by the competent authorities in the restricted zones. Furthermore, as ASF is no longer a rare and exotic disease in the EU, it could be listed as a “Category B” disease, which in turn would allow for more flexibility and “tailor-made” control measures, e.g., regarding the size of the restricted zone.
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Kauppinen, Ari, Tarja Pitkänen, Haider Al-Hello, et al. "Two Drinking Water Outbreaks Caused by Wastewater Intrusion Including Sapovirus in Finland." International Journal of Environmental Research and Public Health 16, no. 22 (2019): 4376. http://dx.doi.org/10.3390/ijerph16224376.
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Drinking water outbreaks occur worldwide and may be caused by several factors, including raw water contamination, treatment deficiencies, and distribution network failure. This study describes two drinking water outbreaks in Finland in 2016 (outbreak I) and 2018 (outbreak II). Both outbreaks caused approximately 450 illness cases and were due to drinking water pipe breakage and subsequent wastewater intrusion into the distribution system. In both outbreaks, the sapovirus was found in patient samples as the main causative agent. In addition, adenoviruses and Dientamoeba fragilis (outbreak I), and noroviruses, astroviruses, enterotoxigenic and enterohemorragic Escherichia coli (ETEC and EHEC, respectively) and Plesiomonas shigelloides (outbreak II) were detected in patient samples. Water samples were analyzed for the selected pathogens largely based on the results of patient samples. In addition, traditional fecal indicator bacteria and host-specific microbial source tracking (MST) markers (GenBac3 and HF183) were analyzed from water. In drinking water, sapovirus and enteropathogenic E. coli (EPEC) were found in outbreak II. The MST markers proved useful in the detection of contamination and to ensure the success of contaminant removal from the water distribution system. As mitigation actions, boil water advisory, alternative drinking water sources and chlorination were organized to restrict the outbreaks and to clean the contaminated distribution network. This study highlights the emerging role of sapoviruses as a waterborne pathogen and warrants the need for testing of multiple viruses during outbreak investigation.
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Retchless, Adam C., Alex Chen, How-Yi Chang, et al. "Using Neisseria meningitidis genomic diversity to inform outbreak strain identification." PLOS Pathogens 17, no. 5 (2021): e1009586. http://dx.doi.org/10.1371/journal.ppat.1009586.
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Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N. meningitidis isolates collected from 28 outbreaks in the USA during 2010–2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions.
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Mattner, Frauke, Lutz Mattner, Hans Ulrich Borck, and Petra Gastmeier. "Evaluation of the Impact of the Source (Patient Versus Staff) on Nosocomial Norovirus Outbreak Severity." Infection Control & Hospital Epidemiology 26, no. 3 (2005): 268–72. http://dx.doi.org/10.1086/502538.
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AbstractObjective:To study the dependence of infection risk and outbreak size on the type of index case (ie, patient or staff).Methods:Nosocomial outbreaks were reviewed and categorized into those started by patients and those started by staff. Infection risks and outbreak sizes were evaluated taking into account the index case category.Results:Of the 30 nosocomial outbreaks of norovirus with person-to-person transmission, 20 (67%) involved patients as the index cases. Patient-indexed outbreaks affected significantly more patients than did staff-indexed outbreaks (difference in means, 16.25; 95% confidence interval [CI95], 5.1 to 27.0). For the numbers of affected staff, no dependence on the index case category was detectable (difference in means, -1.05; CI95, -9.0 to 6.9). For patients exposed during patient-indexed outbreaks, the risk of acquiring a norovirus infection was approximately 4.8 times as high as the corresponding risk for patients exposed during staff-indexed outbreaks (odds ratio [OR], 4.79; CI95,1.82 to 8.28). The infection risk for exposed staff during patient-indexed outbreaks was approximately 1.5 times as high as the corresponding risk during staff-indexed outbreaks (OR, 1.51; CI95, 0.92 to 2.49).Conclusions:Patient-indexed norovirus outbreaks generally affect more patients than do staff-indexed outbreaks. Staff appear to be similarly affected by both outbreak index category groups. This study demonstrates the importance of obtaining complete outbreak data, including the index case classification as staff or patient, during norovirus outbreak investigations. Such information may be useful for further targeting prevention measures.
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Kanamori, Hajime, Christian M. Parobek, David J. Weber, et al. "Next-Generation Sequencing and Comparative Analysis of Sequential Outbreaks Caused by Multidrug-Resistant Acinetobacter baumannii at a Large Academic Burn Center." Antimicrobial Agents and Chemotherapy 60, no. 3 (2015): 1249–57. http://dx.doi.org/10.1128/aac.02014-15.
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Next-generation sequencing (NGS) analysis has emerged as a promising molecular epidemiological method for investigating health care-associated outbreaks. Here, we used NGS to investigate a 3-year outbreak of multidrug-resistantAcinetobacter baumannii(MDRAB) at a large academic burn center. A reference genome from the index case was generated usingde novoassembly of PacBio reads. Forty-six MDRAB isolates were analyzed by pulsed-field gel electrophoresis (PFGE) and sequenced using an Illumina platform. After mapping to the index case reference genome, four samples were excluded due to low coverage, leaving 42 samples for further analysis. Multilocus sequence types (MLST) and the presence of acquired resistance genes were also determined from the sequencing data. A transmission network was inferred from genomic and epidemiological data using a Bayesian framework. Based on single-nucleotide variant (SNV) differences, this MDRAB outbreak represented three sequential outbreaks caused by distinct clones. The first and second outbreaks were caused by sequence type 2 (ST2), while the third outbreak was caused by ST79. For the second outbreak, the MLST and PFGE results were discordant. However, NGS-based SNV typing detected a recombination event and consequently enabled a more accurate phylogenetic analysis. The distribution of resistance genes varied among the three outbreaks. The first- and second-outbreak strains possessed ablaOXA-23-likegroup, while the third-outbreak strains harbored ablaOXA-40-likegroup. NGS-based analysis demonstrated the superior resolution of outbreak transmission networks for MDRAB and provided insight into the mechanisms of strain diversification between sequential outbreaks through recombination.
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Johnston, Fay, Vicki Krause, Nan Miller, and Lyn Barclay. "Outbreak of influenza B among workers on an oil rig." Communicable Diseases Intelligence 21 (April 16, 1997): 106. https://doi.org/10.33321/cdi.1997.21.23.
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An outbreak of influenza B occurred in December 1996 on an oil rig in Darwin Harbour. The outbreak affected 56% of the workers on the rig. An outbreak in December is outside the usual Australian influenza season of June to September, but is consistent with other tropical regions, where outbreaks can occur throughout the year. Influenza vaccination could prevent similar outbreaks in confined workplaces. Comm Dis Intell 1997;21:106.
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GRAHAM, R. M. A., C. J. DOYLE, and A. V. JENNISON. "Real-time investigation of a Legionella pneumophila outbreak using whole genome sequencing." Epidemiology and Infection 142, no. 11 (2014): 2347–51. http://dx.doi.org/10.1017/s0950268814000375.
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SUMMARYLegionella pneumophila is the main pathogen responsible for outbreaks of Legionnaires' disease, which can be related to contaminated water supplies such as cooling towers or water pipes. We combined conventional molecular methods and whole genome sequence (WGS) analysis to investigate an outbreak of L. pneumophila in a large Australian hospital. Typing of these isolates using sequence-based typing and virulence gene profiling, was unable to discriminate between outbreak and non-outbreak isolates. WGS analysis was performed on isolates during the outbreak, as well as on unlinked isolates from the Public Health Microbiology reference collection. The more powerful resolution provided by analysis of whole genome sequences allowed outbreak isolates to be distinguished from isolates that were temporally and spatially unassociated with the outbreak, demonstrating that this technology can be used in real-time to investigate L. pneumophila outbreaks.
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Polonsky, Jonathan A., Amrish Baidjoe, Zhian N. Kamvar, et al. "Outbreak analytics: a developing data science for informing the response to emerging pathogens." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1776 (2019): 20180276. http://dx.doi.org/10.1098/rstb.2018.0276.
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Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics , an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control‘. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.
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ZHU, Y. F., Y. F. LI, Y. DU, and M. ZENG. "Epidemiological characteristics of breakthrough varicella infection during varicella outbreaks in Shanghai, 2008–2014." Epidemiology and Infection 145, no. 10 (2017): 2129–36. http://dx.doi.org/10.1017/s0950268817000772.
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SUMMARYThe outbreaks of varicella occurring in kindergartens and schools are increasingly notified in Shanghai despite the implementation of one-dose varicella vaccination. We analyzed surveillance data on the notified outbreaks of varicella in Minhang District of Shanghai during 2008–2014. A total of 13 511 varicella cases and 154 outbreaks involving 1558 (11·5%) cases were reported. Annual attack rates of outbreak-associated varicella in outbreak classes were 5·5%–12%. The mean age of the outbreak-associated cases was 8·6 ± 3·1 years. Among 1558 outbreak cases, 660 (42·4%) received one-dose varicella vaccine previously. The proportions of breakthrough varicella infection during outbreaks ranged from 21·5% in 2008 to 86·1% in 2014. Annual breakthrough infection rates in outbreak classes ranged from 5·4% to 7·4%. Breakthrough cases as index cases results in 9·7% of outbreaks, and the average duration of outbreaks was significantly longer in vaccinated cases as index cases than in unvaccinated cases as index cases (11·3 ± 5·8 days vs. 8·6 ± 6·1 days, P < 0·05). The mean time of breakthrough infection since vaccination was 6·2 ± 2·3 years (range 0·6–13·4 years). One-dose varicella vaccination cannot prevent the varicella outbreaks in kindergartens and schools. A second dose of varicella vaccine should be recommended for children.
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Bouchard, Mathieu, and David Pothier. "Spatiotemporal variability in tree and stand mortality caused by spruce budworm outbreaks in eastern Quebec." Canadian Journal of Forest Research 40, no. 1 (2010): 86–94. http://dx.doi.org/10.1139/x09-178.
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We evaluated spruce budworm ( Choristoneura fumiferana (Clem.)) outbreak effects in nine study areas (60–86 ha each) located in the boreal forest of eastern Quebec (Canada). In each area, spruce budworm outbreak effects were measured from vegetation plots, dominant canopy and understory tree age structures, retrospective analysis of aerial photographs, defoliation records, and host tree growth reductions (dendrochronology). Large-scale synchronous outbreaks were detected across the region around the years 1880, 1915, 1950, and 1980. Overall, contrarily to what was expected for a region where host species (balsam fir ( Abies balsamea (L.) Mill.), Picea spp.) content is relatively high, these spruce budworm outbreaks seemed to have a relatively minor influence on stand dynamics, with the exception of the most recent outbreak (1980). This outbreak resulted in major stand mortality in the southern part of the region and favored the establishment of extensive tracts of young even-aged stands with few residual mature trees. This very abrupt increase in outbreak severity compared with earlier outbreaks, perhaps due to climatic or random factors, suggests that historical trends in successive outbreak severity should be extrapolated very cautiously and that the study of several outbreak cycles is needed to establish a range of natural variability that can be used to develop an ecosystem forest management strategy.
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Foster, Monique, Megan Hofmeister, Shaoman Yin, and Paul Weidle. "LB10. Changing Epidemiology of Hepatitis A Virus Infections–– United States, 2007–2017." Open Forum Infectious Diseases 5, suppl_1 (2018): S762—S763. http://dx.doi.org/10.1093/ofid/ofy229.2184.
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Abstract Background Hepatitis A virus (HAV) is primarily spread fecal-orally and causes acute illness including fever, jaundice, and diarrhea. After introduction and widespread use of the hepatitis A vaccine in the United States, infection with HAV decreased and outbreaks typically associated with a common-source were uncommon. Method CDC receives reports of hepatitis A infections from states through the National Notifiable Disease Surveillance System (NNDSS) and/or directly to the viral hepatitis outbreak response team. We analyzed NNDSS hepatitis A data for 2007–2016, and a combination of NNDSS data and cases directly reported to the CDC hepatitis A outbreak response team during 2017; excluding 2017 NNDSS data from the four states that directly reported outbreaks to the outbreak response team to eliminate the potential for double-counting cases. Result During 2007–2011, a total of 10,619 hepatitis A cases were reported; 521 (5%) were associated with outbreaks. Of the 274 outbreak-associated cases for whom clinical data were reported, 102 (37%) were hospitalized and one (0.3%) died. Of the 407 outbreak-associated cases for whom risk exposure data were reported, 210 (52%) were associated with a common source. Comparatively, during 2012–2017, a total of 11,483 hepatitis A cases were reported; 2,323 (20%) were associated with outbreaks. Of the outbreak-associated cases for whom clinical data were reported, 1,306/2,162 (60%) were hospitalized and 43/2,178 (2%) died. Of the outbreak-associated cases for whom risk exposure data were reported, 379/2,188 (17%) were associated with a common source. Conclusion In the United States, outbreaks of hepatitis A infections in the decade prior to 2017 were infrequent and typically associated with a common source. Reported cases associated with hepatitis A outbreaks are increasing, along with concurrent increases in hospitalizations and deaths among persons with outbreak-associated infections. Recent outbreaks indicate a decrease in cases associated with a common-source exposure. Decreasing the susceptible population through adherence to childhood vaccination recommendations and targeted vaccination of recommended at-risk groups can prevent future hepatitis A outbreaks of any transmission pattern. Disclosures All authors: No reported disclosures.
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Chen, Yiqun, Timothy Aldridge, Claire Ferraro, and Fu-Meng Khaw. "COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study." BMJ Open 12, no. 7 (2022): e055643. http://dx.doi.org/10.1136/bmjopen-2021-055643.
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ObjectivesA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic but the rate of outbreak occurrence in the workplace has not previously been assessed. The objectives of this paper are to identify the geographical areas and industrial sectors with a high rate of outbreaks of COVID-19 and to compare infection attack rates by enterprise size and sector in England.MethodsPublic Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, between 18 May and 12 October 2020, were analysed. The workplace outbreak rates by region and sector were calculated, using National Population Database (NPD) with the total number of workplaces as the denominator. The infection attack rates were calculated by enterprise size and sector using PHE Situations of Interest data with the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator and using NPD data with the number employed in that workplace as the denominator.ResultsThe highest attack rate was for outbreaks in close contact services (median 16.5%), followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%). The overall outbreak rate was 66 per 100 000 workplaces. Of the nine English regions, the North West had the highest workplace outbreak rate (155 per 100 000 workplaces). Of the industrial sectors, manufacturers and packers of food had the highest outbreak rate (1672 per 100 000), which was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.ConclusionsEarly identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks can inform interventions to limit transmission of SARS-CoV-2.
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Matthews, Samuel A., David H. Williamson, Roger Beeden, et al. "Protecting Great Barrier Reef resilience through effective management of crown-of-thorns starfish outbreaks." PLOS ONE 19, no. 4 (2024): e0298073. http://dx.doi.org/10.1371/journal.pone.0298073.
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Resilience-based management is essential to protect ecosystems in the Anthropocene. Unlike large-scale climate threats to Great Barrier Reef (GBR) corals, outbreaks of coral-eating crown-of-thorns starfish (COTS; Acanthaster cf. solaris) can be directly managed through targeted culling. Here, we evaluate the outcomes of a decade of strategic COTS management in suppressing outbreaks and protecting corals during the 4th COTS outbreak wave at reef and regional scales (sectors). We compare COTS density and coral cover dynamics during the 3rd and 4th outbreak waves. During the 4th outbreak wave, sectors that received limited to no culling had sustained COTS outbreaks causing significant coral losses. In contrast, in sectors that received timely and sufficient cull effort, coral cover increased substantially, and outbreaks were suppressed with COTS densities up to six-fold lower than in the 3rd outbreak wave. In the Townsville sector for example, despite exposure to comparable disturbance regimes during the 4th outbreak wave, effective outbreak suppression coincided with relative increases in sector-wide coral cover (44%), versus significant coral cover declines (37%) during the 3rd outbreak wave. Importantly, these estimated increases span entire sectors, not just reefs with active COTS control. Outbreaking reefs with higher levels of culling had net increases in coral cover, while the rate of coral loss was more than halved on reefs with lower levels of cull effort. Our results also indicate that outbreak wave progression to adjoining sectors has been delayed, probably via suppression of COTS larval supply. Our findings provide compelling evidence that proactive, targeted, and sustained COTS management can effectively suppress COTS outbreaks and deliver coral growth and recovery benefits at reef and sector-wide scales. The clear coral protection outcomes demonstrate the value of targeted manual culling as both a scalable intervention to mitigate COTS outbreaks, and a potent resilience-based management tool to “buy time” for coral reefs, protecting reef ecosystem functions and biodiversity as the climate changes.
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PECI, A., A. MARCHAND-AUSTIN, A.-J. WINTER, and J. B. GUBBAY. "Optimal number of samples to test for institutional respiratory infection outbreaks in Ontario." Epidemiology and Infection 141, no. 8 (2012): 1781–85. http://dx.doi.org/10.1017/s0950268812002531.
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SUMMARYThe objective of this study was to determine the optimal number of respiratory samples per outbreak to be tested for institutional respiratory outbreaks in Ontario. We reviewed respiratory samples tested for respiratory viruses by multiplex PCR as part of outbreak investigations. We documented outbreaks that were positive for any respiratory viruses and for influenza alone. At least one virus was detected in 1454 (85·2%) outbreaks. The ability to detect influenza or any respiratory virus increased as the number of samples tested increased. When analysed by chronological order of when samples were received at the laboratory, percent positivity of outbreaks testing positive for any respiratory virus including influenza increased with the number of samples tested up to the ninth sample, with minimal benefit beyond the fourth sample tested. Testing up to four respiratory samples per outbreak was sufficient to detect viral organisms and resulted in significant savings for outbreak investigations.
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Rinchen, Sangay, Tandin Zangpo, Sonam Wangchuk, et al. "A Descriptive Comparison of the Epidemiological Characteristics of Delta and Omicron Variant-Driven Outbreaks in Bhutan." Zoonotic Diseases 4, no. 4 (2024): 271–82. http://dx.doi.org/10.3390/zoonoticdis4040023.
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SARS-CoV-2 rapidly mutated, causing different waves of outbreaks worldwide. Bhutan experienced three major outbreaks of COVID-19 before experiencing the outbreak driven by the Omicron variant in January 2022. The data collected by the National Outbreak Investigation and Surveillance Team during the Delta variant-driven outbreak and Omicron outbreak were accessed and analyzed. The data were analyzed using R statistical software. Descriptive analysis was carried out for the entire dataset and the statistical comparison between the two outbreaks was carried out using student’s t-test and Pearson’s chi-square test. During the Delta variant-driven outbreak, a total of 1648 cases were reported, with a daily average of 13 cases. The highest one-day case number reported was 99. On the contrary, within 33 days, a total of 3788 cases were reported with a daily average of 115 cases during the Omicron outbreak. The highest one-day case number reported was 312. The median incubation period was 3 days (range = 0–18 days) and 1 day (range = 0–14 days) during the Delta and Omicron-driven outbreaks, respectively. The number of symptomatic cases was significantly higher during the Delta outbreak (p-value < 0.0001). Of the total cases reported during the Delta outbreak, 1175 (71.3%) had received a single dose of the vaccine, 79 (5%) received two doses, while 394 (24%) were unvaccinated. During the Omicron outbreak, 1957 (52%) cases had received their booster (third dose), 904 (23.8%) received two doses and only 40 (1%) received a single dose of the vaccine. The number of unvaccinated cases was 887 (23.4%), of which 375 (10%) were children below 12 years. Our findings corroborate the enhanced transmissibility of the Omicron variant as reported elsewhere. We report significantly less symptomatic cases during the Omicron outbreak. Further, our data show that the incubation period for the Omicron variant is shorter compared to the Delta variant (p-value < 0.0001).
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Parish, Lindsay A., Eric J. Stavale, Christopher R. Houchens, and Daniel N. Wolfe. "Developing Vaccines to Improve Preparedness for Filovirus Outbreaks: The Perspective of the USA Biomedical Advanced Research and Development Authority (BARDA)." Vaccines 11, no. 6 (2023): 1120. http://dx.doi.org/10.3390/vaccines11061120.
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Outbreaks of viral hemorrhagic fever caused by filoviruses have become more prevalent in recent years, with outbreaks of Ebola virus (EBOV), Sudan virus (SUDV), and Marburg virus (MARV) all occurring in 2022 and 2023. While licensed vaccines are now available for EBOV, vaccine candidates for SUDV and MARV are all in preclinical or early clinical development phases. During the recent outbreak of SUDV virus disease, the Biomedical Advanced Research and Development Authority (BARDA), as part of the Administration for Strategic Preparedness and Response within the U.S. Department of Health and Human Services, implemented key actions with our existing partners to advance preparedness and enable rapid response to the outbreak, while also aligning with global partners involved in the implementation of clinical trials in an outbreak setting. Beyond pre-existing plans prior to the outbreak, BARDA worked with product sponsors to expedite manufacturing of vaccine doses that could be utilized in clinical trials. While the SUDV outbreak has since ended, a new outbreak of MARV disease has emerged. It remains critical that we continue to advance a portfolio of vaccines against SUDV and MARV while also expediting manufacturing activities ahead of, or in parallel if needed, outbreaks.
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AMBROSE, J., L. M. HAMPTON, K. E. FLEMING-DUTRA, et al. "Large outbreak of Legionnaires' disease and Pontiac fever at a military base." Epidemiology and Infection 142, no. 11 (2014): 2336–46. http://dx.doi.org/10.1017/s0950268813003440.
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SUMMARYWe investigated a mixed outbreak of Legionnaires' disease (LD) and Pontiac fever (PF) at a military base to identify the outbreak's environmental source as well as known legionellosis risk factors. Base workers with possible legionellosis were interviewed and, if consenting, underwent testing for legionellosis. A retrospective cohort study collected information on occupants of the buildings closest to the outbreak source. We identified 29 confirmed and probable LD and 38 PF cases. All cases were exposed to airborne pathogens from a cooling tower. Occupants of the building closest to the cooling tower were 6·9 [95% confidence interval (CI) 2·2–22·0] and 5·5 (95% CI 2·1–14·5) times more likely to develop LD and PF, respectively, than occupants of the next closest building. Thorough preventive measures and aggressive responses to outbreaks, including searching for PF cases in mixed legionellosis outbreaks, are essential for legionellosis control.
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Suominen, Kristiina, Anni Vainio, Pirkko Hokkanen, et al. "Multilocus Variable-Number Tandem-Repeat Analysis as an Investigation Tool in Cryptosporidium parvum Outbreaks in Finland and Sweden in 2022." Microorganisms 13, no. 4 (2025): 821. https://doi.org/10.3390/microorganisms13040821.
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Cryptosporidium is a significant cause of foodborne outbreaks. The 60 kDa glycoprotein gene (gp60) is most often used for subtyping Cryptosporidium species but is not always sufficient for defining clusters and infections sources. The Multilocus Variable-Number Tandem-Repeat Analysis (MLVA) scheme has been developed to better differentiate between subtypes. A cryptosporidiosis outbreak, with 35 cases, was detected in Finland in September 2022. At the same time, in Sweden, three cryptosporidiosis outbreaks, with 107 cases, were detected, leading to international collaboration. In both countries, salad mixes were suspected as being the outbreak source. In the Finnish outbreak, the suspected salad mixes were produced in Sweden. In the Swedish outbreaks, salad mixes from two different producers were suspected. Twenty-nine patient samples which were positive for Cryptosporidium parvum (11 from Finland and 18 from Sweden) were sent for MLVA. The Finnish outbreak samples had different gp60 subtypes and MLVA profiles compared to the Swedish samples. In our investigation, MLVA differentiated C. parvum subtypes in more detail than gp60 typing. MLVA suggested no connection between the Finnish and Swedish outbreaks. A traceback investigation supported this conclusion. To detect outbreaks and identify infection sources, the timely subtyping of patient samples is crucial and should be implemented in routine surveillance and outbreak investigations.
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STENE-JOHANSEN, K., P. A. JENUM, T. HOEL, H. BLYSTAD, H. SUNDE, and K. SKAUG. "An outbreak of hepatitis A among homosexuals linked to a family outbreak." Epidemiology and Infection 129, no. 1 (2002): 113–17. http://dx.doi.org/10.1017/s0950268802007069.
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Several outbreaks of hepatitis A occurred in Norway in 1995–8. Molecular epidemiology was used to follow the spread of hepatitis A virus in the population. Distinct strains of hepatitis A virus (HAV) were detected by reverse transcriptase–polymerase chain reaction (RT–PCR) and subsequent sequencing in serum from patients in different communities at risk of infection. Two HAV strains were detected in an outbreak among 26 men having sexual contact with other men. One of these strains was also detected in a geographically limited family outbreak. The family outbreak was first believed to be acquired abroad. The sequence information linked the two outbreaks, and epidemiological and serological analyses revealed the transmission route. This study demonstrates the importance of molecular epidemiology in outbreak investigation, surveillance and monitoring of hepatitis A in the population.
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Branson, David H. "Grasshopper species composition shifts following a severe rangeland grasshopper outbreak." Journal of Orthoptera Research 26 (June 28, 2017): 7–10. https://doi.org/10.3897/jor.26.14542.
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Little is known about how grasshopper species abundances shift during and following severe outbreaks, as sampling efforts usually end when outbreaks subside. Grasshopper densities, species composition and vegetation have infrequently been sampled during and after a severe outbreak in the western U.S., which is needed to better understand the cause of outbreaks and population declines. In this study, grasshopper densities, species composition and vegetation were monitored at a northern mixed rangeland site from 1999 to 2003 where densities reached 130 per m<sup>2</sup> during a severe outbreak. Phoetaliotes nebrascensis (Acrididae: Melanoplinae) comprised 79% of the outbreak in 2000, but declined to 3% by 2003. The dramatic shifts in proportional and actual abundance of P. nebrascensis over a 5 year period illustrate that species dominance can change rapidly, even for a highly dominant outbreak species. The difficulty of fully understanding factors causing shifts in grasshopper populations is illustrated by population declines in all species observed in 2002 and 2003. The data can help predict the intensity and decline of outbreaks and points to the critical importance of long term simultaneous monitoring of grasshopper densities, species composition and vegetation for outbreak prediction.
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Polonsky, Jonathan A., Amrish Baidjoe, Zhian N. Kamvar, et al. "Outbreak analytics: a developing data science for informing the response to emerging pathogens." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1776 (2019): 20180276. https://doi.org/10.5281/zenodo.13510844.
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(Uploaded by Plazi for the Bat Literature Project) Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics , an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
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Polonsky, Jonathan A., Amrish Baidjoe, Zhian N. Kamvar, et al. "Outbreak analytics: a developing data science for informing the response to emerging pathogens." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1776 (2019): 20180276. https://doi.org/10.5281/zenodo.13510844.
Full textAbstract:
(Uploaded by Plazi for the Bat Literature Project) Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics , an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
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Coltart, Cordelia E. M., Benjamin Lindsey, Isaac Ghinai, Anne M. Johnson, and David L. Heymann. "The Ebola outbreak, 2013–2016: old lessons for new epidemics." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1721 (2017): 20160297. http://dx.doi.org/10.1098/rstb.2016.0297.
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Ebola virus causes a severe haemorrhagic fever in humans with high case fatality and significant epidemic potential. The 2013–2016 outbreak in West Africa was unprecedented in scale, being larger than all previous outbreaks combined, with 28 646 reported cases and 11 323 reported deaths. It was also unique in its geographical distribution and multicountry spread. It is vital that the lessons learned from the world's largest Ebola outbreak are not lost. This article aims to provide a detailed description of the evolution of the outbreak. We contextualize this outbreak in relation to previous Ebola outbreaks and outline the theories regarding its origins and emergence. The outbreak is described by country, in chronological order, including epidemiological parameters and implementation of outbreak containment strategies. We then summarize the factors that led to rapid and extensive propagation, as well as highlight the key successes, failures and lessons learned from this outbreak and the response. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.
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Coltart, Cordelia E. M., Benjamin Lindsey, Isaac Ghinai, Anne M. Johnson, and David L. Heymann. "The Ebola outbreak, 2013–2016: old lessons for new epidemics." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1721 (2017): 20160297. https://doi.org/10.5281/zenodo.13530874.
Full textAbstract:
(Uploaded by Plazi for the Bat Literature Project) Ebola virus causes a severe haemorrhagic fever in humans with high case fatality and significant epidemic potential. The 2013–2016 outbreak in West Africa was unprecedented in scale, being larger than all previous outbreaks combined, with 28 646 reported cases and 11 323 reported deaths. It was also unique in its geographical distribution and multicountry spread. It is vital that the lessons learned from the world's largest Ebola outbreak are not lost. This article aims to provide a detailed description of the evolution of the outbreak. We contextualize this outbreak in relation to previous Ebola outbreaks and outline the theories regarding its origins and emergence. The outbreak is described by country, in chronological order, including epidemiological parameters and implementation of outbreak containment strategies. We then summarize the factors that led to rapid and extensive propagation, as well as highlight the key successes, failures and lessons learned from this outbreak and the response.This article is part of the themed issue 'The 2013–2016 West African Ebola epidemic: data, decision-making and disease control'.
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Coltart, Cordelia E. M., Benjamin Lindsey, Isaac Ghinai, Anne M. Johnson, and David L. Heymann. "The Ebola outbreak, 2013–2016: old lessons for new epidemics." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1721 (2017): 20160297. https://doi.org/10.5281/zenodo.13530874.
Full textAbstract:
(Uploaded by Plazi for the Bat Literature Project) Ebola virus causes a severe haemorrhagic fever in humans with high case fatality and significant epidemic potential. The 2013–2016 outbreak in West Africa was unprecedented in scale, being larger than all previous outbreaks combined, with 28 646 reported cases and 11 323 reported deaths. It was also unique in its geographical distribution and multicountry spread. It is vital that the lessons learned from the world's largest Ebola outbreak are not lost. This article aims to provide a detailed description of the evolution of the outbreak. We contextualize this outbreak in relation to previous Ebola outbreaks and outline the theories regarding its origins and emergence. The outbreak is described by country, in chronological order, including epidemiological parameters and implementation of outbreak containment strategies. We then summarize the factors that led to rapid and extensive propagation, as well as highlight the key successes, failures and lessons learned from this outbreak and the response.This article is part of the themed issue 'The 2013–2016 West African Ebola epidemic: data, decision-making and disease control'.
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Kim, Samuel, Kang Sung Lee, Gi Deok Pak, et al. "Spatial and Temporal Patterns of Typhoid and Paratyphoid Fever Outbreaks: A Worldwide Review, 1990–2018." Clinical Infectious Diseases 69, Supplement_6 (2019): S499—S509. http://dx.doi.org/10.1093/cid/ciz705.
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Abstract Background Analyses of the global spatial and temporal distribution of enteric fever outbreaks worldwide are important factors to consider in estimating the disease burden of enteric fever disease burden. Methods We conducted a global literature review of enteric fever outbreak data by systematically using multiple databases from 1 January 1990 to 31 December 2018 and classified them by time, place, diagnostic methods, and drug susceptibility, to illustrate outbreak characteristics including spatial and temporal patterns. Results There were 180 940 cases in 303 identified outbreaks caused by infection with Salmonella enterica serovar Typhi (S. Typhi) and Salmonella enterica serovar Paratyphi A or B (S. Paratyphi). The size of outbreak ranged from 1 to 42 564. Fifty-one percent of outbreaks occurred in Asia, 15% in Africa, 14% in Oceania, and the rest in other regions. Forty-six percent of outbreaks specified confirmation by blood culture, and 82 outbreaks reported drug susceptibility, of which 54% had multidrug-resistant pathogens. Paratyphoid outbreaks were less common compared to typhoid (22 vs 281) and more prevalent in Asia than Africa. Risk factors were multifactorial, with contaminated water being the main factor. Conclusions Enteric fever outbreak burden remains high in endemic low- and middle-income countries and, despite its limitations, outbreak data provide valuable contemporary evidence in prioritizing resources, public health policies, and actions. This review highlights geographical locations where urgent attention is needed for enteric fever control and calls for global action to prevent and contain outbreaks.
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Das, Rinila, Swati Behera, and Kumar Sumit. "A Perspective on Monkeypox Related LGBT Phobia Among the General Public." National Journal of Community Medicine 14, no. 11 (2023): 769–73. http://dx.doi.org/10.55489/njcm.141120233210.
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Due to an upsurge in imported cases in the Western Pacific Region, the World Health Organization has proclaimed monkeypox a Public Health Emergency of International Concern on July 23rd, 2022. The worldwide transmission of human monkeypox disease presents substantial healthcare concern. Similar to previous infectious disease outbreaks, conspiracy theories have also emerged in relation to the 2022 monkeypox outbreak, undermining health behaviors and amplifying the outbreak's impact. Fake news on social media worsens the monkeypox outbreak, silencing healthcare experts. The outbreak has stigmatized monkeypox, putting LGBTQI+ communities at increased risk. Unsurprisingly, the present outbreak is impacting a large number of homosexuals, bisexuals, and men who have sex with men, which may lead to increased discrimination and stigma towards this group, along with increased LGBT phobia among the general population. Such stigmatization lead to healthcare disengagement, increasing morbidity and mortality, significant physical, socio-economic, and psychological consequences for LGBTQ+ community. Monkeypox is manageable if transmission chains are broken, aided by accurate information to dispel outdated myths rooted in fear and sexual bias. A holistic, culturally-sensitive approach is vital to combat current monkeypox-related stigma, requiring government interventions and multi-stakeholder collaboration for a multidisciplinary strategy.