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PubMed1978

Salmonellosis associated with homemade ice cream. An outbreak report and summary of outbreaks in the United States in 1966 to 1976.

During the period 1966 to 1976, 22 outbreaks with 292 individual cases of salmonellosis associated with the consumption of homemade ice cream were reported to the Center for Disease Control. Salmonella typhimurium accounted for 45% of the outbreaks. The source of eggs used was known in 13 outbreaks, and all were ungraded farm- or home-produced eggs, a potential source of salmonellae. In 11 outbreaks, the method of preparation was known, and in all, the ice-cream custard had not been cooked before freezing.

Adolescent↗
PubMed2026

The 2026 Bundibugyo Ebola Outbreak: A Warning for Global Preparedness for Future Epidemics.

Dear Editor, The 2026 Bundibugyo Ebolavirus (BDBV) outbreak has once again demonstrated that the threat of emerging diseases remains a major global health challenge. The outbreak, first detected in the Democratic Republic of Congo (DRC) and spread to Uganda, is not only a regional crisis but also a test of the world's preparedness for pathogens with epidemic potential. Unlike Zaire Ebolavirus (EBOV), which has benefited from effective vaccines and treatments in recent years, BDBV still lacks a licensed vaccine or specific treatment[1]. As of June 6, a total of 515 laboratory-confirmed cases and 91 deaths have been reported in DRC, while Uganda has reported 19 laboratory-confirmed cases and two deaths. The occurrence of unexplained deaths among both the community and healthcare workers, along with prior reports of an unidentified hemorrhagic fever, suggest that the outbreak has been likely originated in March 2026 or even earlier. Accordingly, the virus is believed to have spread unnoticed for several weeks before being identified through genomic sequencing in mid-May 2026[2]. The resurgence of Ebola in Africa results from a complex interaction of environmental, social, and political factors. Deforestation, the development of mining activities, the expansion of agriculture, and increased human contact with wildlife have elevated the likelihood of spillovers from wildlife reservoirs, particularly fruit bats, which are considered the most likely natural hosts of ebolaviruses. Moreover, weak disease surveillance systems and limited access to health services have delayed the identification of early cases. The similarity of the initial symptoms of Ebola to other endemic diseases in the region, such as malaria, makes early diagnosis difficult and provides ample opportunity for transmission to spread. Insecurity, misinformation, attacks on healthcare facilities, and armed conflict in the region have also posed serious challenges to the implementation of contact tracing programs and rapid response to the epidemic[3,4]. One of the most critical challenges highlighted by this outbreak is the weakness of diagnostic capacities in the affected areas. The initial 2007 outbreak of BDBV proved that delayed lab confirmation paralyzes public health responses[5]. Now, dealing with a much larger outbreak in 2026, the persistence of this challenge highlights a dangerous failure to invest in diagnostic infrastructure over the last 19 years. Many health facilities do not have access to molecular laboratories, rapid sample transport systems, and biosafety infrastructure[6]. These limitations delay the diagnosis and isolation of patients, thus perpetuating disease transmission. Investment in the development of mobile laboratories, rapid point-of-care diagnostic tests, and digital reporting systems can dramatically reduce the time to diagnosis and response to an outbreak. The BDBV outbreak shows that laboratory preparedness must be considered an essential part of global health security. Furthermore, the early detection of emerging pathogens depends not only on diagnostic technologies but also on the expertise of local scientists who are able to recognize unusual epidemiological and laboratory patterns. During the current outbreak, suspected Ebola cases initially tested negative using common diagnostic tests (designed for Zaire Ebola Virus), which delayed the identification of the BDBV. Specifically, field-based diagnostics in Bunia were calibrated exclusively to detect the EBOV responsible for recent Congolese outbreaks. Consequently, patient samples collected throughout late April and early May yielded negative results, requiring cross-country transport to Kinshasa for genomic confirmation[2]. This experience revealed a major vulnerability in outbreak preparedness: diagnostic tools designed for known threats may be ineffective in detecting less common or unexpected pathogens. Therefore, strengthening local scientific capacities, developing genomic surveillance, and expanding access to flexible and adaptable diagnostic platforms should be considered as a top priority for global health security. The lack of a licensed vaccine for BDBV was one of the most significant challenges of this epidemic. While the rVSV-ZEBOV vaccine has played a significant role in controlling Zaire ebolavirus, there is no licensed vaccine for BDBV. In response to this outbreak, efforts to develop mRNA-based vaccines, adenoviral vectors, rVSV-based vaccines, and multipotent vaccines have been accelerated[7]. However, the experience of this epidemic has shown that the development of medical products for rare diseases continues to face financial and investment constraints. This challenge highlights the need for sustained support from governments and international institutions for research and development of pathogens with epidemic potential. The 2026 Bundibugyo outbreak provides several key lessons for the global community. First, early detection and rapid diagnosis are the most important factors in containing the epidemic. The 19-year interval between the 2007 BDBV outbreak and the 2026 outbreak underscores persistent shortcomings in investment toward decentralized, pan-ebolavirus diagnostic infrastructure, with diagnostic delays hindering timely outbreak identification in both instances. Second, the trust and active participation of local communities are as important as medical interventions. Additionally, the rapid cross-border transmission dynamics between the DRC and Uganda demonstrate that blanket travel restrictions and border closures are impractical. As communities in the Great Lakes region routinely cross national borders for trade and healthcare, coordinated regional surveillance and timely information sharing are likely to be more effective than broad border closures in mitigating disease transmission[8]. Third, the protection of health workers must be a priority in preparedness plans. Fourth, a "One Health" approach is essential for simultaneous monitoring of humans, animals, and the environment. Although BDBV is not a new pathogen, the lack of licensed medical interventions and limited investment in research reflect many of the vulnerabilities associated with the concept of "Disease X."[9]. Unlike Zaire Ebola Virus, for which licensed vaccines and monoclonal antibody therapies are available, BDBV forces public health responses to rely almost entirely on non-pharmaceutical interventions such as isolation and infection control[10]. This gap reflects the structural inequity in global health research and development funding, with pathogens affecting resource-limited regions receiving insufficient attention until they spark an international emergency[2]. The BDBV outbreak proves that global epidemic preparedness cannot be pathogen-selective; it requires proactive investment in broad-spectrum countermeasures and resilient frontline health systems[8]. In conclusion, the 2026 BDBV outbreak is a serious wake-up call for the global health system. The epidemic revealed that gaps in surveillance systems, diagnostic capacities, vaccine development, and preparedness for emerging diseases persist. Investing in health infrastructure, developing Pan-Ebolavirus vaccines, strengthening laboratories, expanding the One-Health approach, and supporting research on emerging zoonotic pathogens must be at the top of global health security priorities. Otherwise, the BDBV outbreak may be just a prelude to larger crises to come.

Ebolavirus↗
PubMed2026

Waterborne norovirus outbreaks in China, 2000-2022: a systematic review.

In China, waterborne transmission is a relatively rare route for norovirus outbreaks; however, once it occurs, the outbreaks tend to be large in scale, prolonged in duration, and difficult to control. This systematic review characterizes the epidemiological features of such outbreaks in China. We searched the WANFANG, CNKI, PubMed, and Web of Science databases for literature on waterborne norovirus outbreaks published up to November 2023. From 2000 to 2022, a total of 112 outbreaks were reported in China among the 97 articles included. These outbreaks involved approximately 19,796 cases and 565,485 exposures, median of 98 cases per outbreak, with a median attack rate of 6.09 %. Most outbreaks occurred in southern regions, particularly in coastal provinces, with schools (59, 52.68 %) and towns or villages (25, 22.52 %) being the most common settings. The highest number of outbreaks was reported in February and the lowest in July, with an average of 8.25 outbreaks per month. Higher attack rates were associated with outbreaks occurring in winter, in primary schools, and in southern regions of the Qinling-Huaihe line. Contamination of barreled water and self-provided wells was the primary risk factor for waterborne norovirus outbreaks. Although waterborne transmission is a relatively rare route for norovirus outbreaks in China, it can cause large-scale outbreaks in a short period. Consequently, it is still necessary to enhance protection of water sources, rigorous water quality monitoring, and public health education on water sanitation.

Humans↗
PubMed2026

Mapping High-Rate Clusters of Animal Contact-Related Human Salmonella enterica Single-State Outbreaks in the United States, 2009-2022: A Spatial Epidemiological Approach to Inform Public Health Surveillance.

INTRODUCTION: Nontyphoidal Salmonella enterica (NTS) is a major zoonotic enteric pathogen. Animal contact-related NTS outbreaks have increased in the United States over the last decade. Geospatial analysis can identify locations with elevated risk of NTS outbreaks where public health authorities can focus their NTS prevention and intervention efforts. METHODS: We analysed NTS outbreak data reported from individual states to the Centers for Disease Control via the National Outbreak Reporting System between 2009 and 2022 across the continental contiguous United States. A geospatial analytical framework that included disease mapping, spatial interpolation, and global and local clustering methods was applied to identify regions with high NTS outbreak rates. Given that the study period (2009-2022) included the COVID-19 pandemic, an interrupted time series negative binomial model was used to assess changes in NTS incidence before and after 2020. RESULTS: A total of 104 NTS single-state outbreaks were reported to the National Outbreak Reporting System (NORS) during the study period. The mean annual incidence rate was 0.02 NTS outbreaks per million person-years. The primary animal contact categories associated with outbreaks were mammals (cattle, pigs, sheep, and horses), birds (backyard chickens, ducklings, and turkeys), and reptiles (turtles and lizards). Exposure settings included farms, fairgrounds, agricultural feed stores, veterinary clinics, dairy/agricultural settings, and residential settings. The local cluster detection methods consistently identified areas with significantly high NTS animal contact-related outbreak rates in the Mountain West, Midwest, and Northeast of the US. The interrupted time series analysis indicated a reduction in incidence following the onset of the COVID-19 pandemic (IRR = 0.03; p = 0.06). CONCLUSION: NTS animal contact-related single-state outbreaks revealed distinct spatial clustering across the United States, with higher risks in the Mountain West, Midwest, and Northeast. Diversity of animal-contact sources and exposure settings depicted complex transmission dynamics of NTS. A decline in reported NTS outbreaks was observed after the COVID-19 pandemic. Focused prevention and control programs are needed in high-risk areas to mitigate the burden of NTS outbreaks.

United States↗
PubMed1992

Outbreaks of human enteric adenovirus types 40 and 41 in Houston day care centers.

OBJECTIVE: Human enteric adenovirus (EAd) types 40 and 41 cause diarrhea in young children, but little is known about their association with outbreaks of diarrhea in the child care setting. This study evaluated EAd as a cause of outbreaks of diarrhea among infants and toddlers in day care centers. DESIGN: Stool specimens were collected weekly regardless of symptoms during four periods from January 1986 to April 1991, from children 6 to 24 months of age enrolled in prospective studies of diarrhea in day care centers. All diarrhea stool specimens were tested for bacterial enteropathogens, rotavirus, and Giardia lamblia. A total of 131 outbreaks occurred during the study. No etiologic agent was identified in 77 outbreaks. Stool specimens from 75 of these 77 outbreaks and from another 21 outbreaks of diarrhea with a known cause were evaluated for EAd with a monoclonal antibody-based enzyme immunoassay. RESULTS: A total of 4402 stool specimens from 613 children from these 96 outbreaks was tested for EAd. The virus was detected in specimens collected during 10 outbreaks, 3 of which occurred in 1986, 3 in 1988, 1 in 1989, 1 in 1990, and 2 in 1991. Of 249 children, 94 (38%) in these 10 EAd outbreaks were infected with EAd. In 51 children (54%) the infection was symptomatic and in 43 (46%) it was asymptomatic. Outbreaks lasted 7 to 44 days (mean 24.5 days). Duration of EAd excretion ranged from 1 to 14 days (mean 3.9 days), with excretion occurring from 7 days (mean 2.6) before diarrhea began to 11 days (mean 5.3 days) after diarrhea stopped. CONCLUSION: Enteric adenovirus types 40 and 41 are an important cause of outbreaks of diarrhea among children attending day care centers, often involve children in more than one room, and frequently produce asymptomatic infection.

Adenovirus Infections, Human↗
PubMed2026

Applicability of Nanopore-only whole-genome sequencing for Pseudomonas aeruginosa outbreak investigation in the ICU setting: a multicentric study.

UNLABELLED: Pseudomonas aeruginosa outbreaks frequently occur in intensive care units (ICUs). In particular, ICU patients requiring mechanical ventilation are vulnerable to P. aeruginosa ventilator-associated pneumonia, which is associated with high morbidity and mortality. Fast and accurate genotyping during the early stage is crucial to document and manage P. aeruginosa outbreaks at the ICU. In this study, we have evaluated the applicability of Oxford Nanopore whole-genome sequencing (WGS) for outbreak investigation and antimicrobial resistance (AMR) prediction. To evaluate whether a Nanopore-only WGS workflow was able to reproduce Illumina-confirmed transmission clusters, 19 P. aeruginosa isolates from ICUs at UZ Brussels (Belgium) that were previously sequenced with Illumina were sequenced using a Nanopore-only workflow based on the latest V14 chemistry, followed by bioinformatic analysis via BugSeq and MBioSEQ Ridom Typer. Although both bioinformatic platforms showed high concordance between Illumina and Nanopore data, MBioSEQ Ridom Typer yielded the lowest allelic distance (maximum one cgMLST allele), confirming all outbreak clusters. When applying the Nanopore-only workflow to longitudinally collected isolates, low genetic heterogeneity (maximum three cgMLST alleles) was observed between isolates from the same patient. WGS and subsequent outbreak analysis of 65 respiratory P. aeruginosa isolates collected from 38 different ICU patients across six Belgian hospitals during a 9-month period showed no intra- or inter-hospital transmission. When the Nanopore-only WGS data were used to predict AMR, there was high categorical agreement (95%) between AMR genotype and phenotype. These findings highlight the potential of Nanopore WGS as a rapid and accurate tool for outbreak investigation of P. aeruginosa. IMPORTANCE: In recent years, Nanopore sequencing has found its way to clinical laboratories because of its affordability, scalability, and, most importantly, its ability to obtain sequencing results in near-real time. However, despite improved raw read accuracies with the latest generation R10.4.1 flow cells, the question remains whether the achieved accuracy is sufficient for accurate bacterial outbreak investigation, particularly in high-risk settings such as intensive care units (ICUs). In this study, we show that Nanopore-only whole-genome sequencing (WGS) is able to match Illumina-only WGS in terms of accuracy for Pseudomonas aeruginosa outbreak investigation in the ICU setting, although important sequence type-dependent and even strain-specific methylation issues need to be resolved in order to guarantee this accuracy. By providing a fast and accurate workflow for reliable P. aeruginosa outbreak investigation, this study could pave the way for large-scale implementation of Nanopore-only WGS, leading to faster outbreak response times.

Humans↗
PubMed2022

A deep learning approach to real-time HIV outbreak detection using genetic data.

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

Humans↗
PubMed1977

Foodborne disease outbreaks of chemical etiology in the United States, 1970-1974.

In the United States between 1970 and 1974 there was an increase each year both in the absolute number of foodborne diseases outbreaks of chemical etiology reported to the Center for Disease Control and in the proportion of these outbreaks in the total reported foodborne disease outbreaks. Nearly half (48.9%) of these foodborne disease outbreaks of chemical origin were caused by toxic fish or shellfish. Of the rest, 16.5% were caused by poisonous mushrooms, 10.9% by heavy metal poisoning, 7.2% by excessive use in food of monosodium glutamate (the etiologic agent of Chinese Restaurant Syndrome) and 16.5% by miscellaneous chemicals. Practices that contributed to the occurrence of these outbreaks included the inadvertent selection for consumption of toxic fish, shellfish, or mushrooms, storage of fish at improper temperatures, storage of acidic liquids in metal containers, and addition of excessive amounts of monosodium glutamate to foods. Commercially-processed foods were responsible for outbreaks of scombroid fish poisoning, shellfish poisoning, and heavy metal poisoning. Because outbreaks of chemical etiology due to contaminated commercial products do occur, prompt recognition and reporting of outbreaks to public health personnel are essential so that epidemiologic investigations can be conducted and effective control measures promptly initiated.

Animals↗
PubMed1992

[Outbreaks of acute gastroenteritis caused by small round structured viruses in Tokyo].

Of 34 non-bacterial gastroenteritis outbreaks which occurred at day-care centers, kindergartens, elementary and secondary schools in Tokyo during the period from February 1985 to June 1991, 28 outbreaks from which small round structured viruses (SRSV) were detected in the patients' stool specimens by electron microscopy were subjected to an epidemiological investigation. The outbreaks tended to occur frequently in the cold season; twenty-two (79%) of these outbreaks from November through April. Though detailed epidemiological informations was not obtained from all outbreaks, the common source of infection were presumed to be present in many of the outbreaks, judged from the incidence as to time course of patients. Food doubted to be incriminated as transmission vehicles in these outbreaks was served at schools, kindergartens, and lodgings. In some outbreaks, SRSV was detected from stool specimens of food handlers, or they were seroconverted to SRSV, suggesting that food was incriminated as a transmission vehicle. The symptoms of patients differ slightly from age to age: in the age range of 0 to 6 years, vomiting 90%, fever 41% and diarrhea 32%; in the 6 to 12 year-olds, nausea 61%, vomiting 48%, abdominal pain 65%, diarrhea 20% and fever 29%; and in the 12 to 15 year-olds, nausea 69%, vomiting 42%, abdominal pain 60%, diarrhea 30% and fever 34%. The lower the age of patient vomiting was more frequently observed. In these lower age groups, the frequency of nausea and vomiting tended to exceed that of diarrhea.

Adolescent↗
PubMed2026

Whole-genome sequencing links a Salmonella Newport ST164 outbreak on Fernando de Noronha to prior circulation in the Brazilian poultry supply chain.

Foodborne outbreaks at geographically isolated tourist destinations pose distinctive One Health challenges, combining limited local surveillance capacity, complex intercontinental supply chains, and high visitor turnover. In May 2021, a diarrheal outbreak linked to a gastronomic festival in Fernando de Noronha, that is a remote UNESCO World Heritage island off northeastern Brazil, was attributed to Salmonella enterica serovar Newport ST164. We applied an integrated genomic approach and epidemiological investigation to propose a transmission chain contextualizing and refining case definition of the S. Newport epidemic clone within national and international diversity. Whole-genome sequencing (WGS), SNP-based phylogenomic, pangenome analysis, Salmonella pathogenicity island (SPI) profiling, and resistome characterization was performed on 17 epidemiologically attributed outbreak isolates and 68 contextual genomes from Brazil, France, the United Kingdom, and the United States. The SNP analysis identified a 13 genome clonal core with less than 20 different SNPs demonstrating the possible connection between 9 patient isolates, 2 food isolates, and 2 food handler isolates, consistent with the involvement of colonised kitchen staff in cross-contamination of the ready-to-eat mussel dish. Three poultry isolates in 2020 from a mainland producer, ∼2180 km from Fernando de Noronha, differed only 13 to 17 Core-SNPs from the outbreak core, suggesting prior lineage circulation in the supply chain. Pangenome analysis also supports this evidence revealing near-complete genomic overlap of 4544 shared genes within the 5745 gene clusters (99.9%) between outbreak and non-outbreak backgrounds that mostly differentiate by a defense/prophage-associated accessory module. The resistome comprised intrinsic efflux determinants without acquired resistance and showed 35.3% of intermediate ciprofloxacin susceptibility. This One Health based study provides a WGS genomic reconstruction of a S. Newport ST164 outbreak at a remote tourist island, supporting the possibility of circulation from poultry-associated mainland reservoirs and findings consistent with cross-contamination at a gastronomic seafood festival.

Brazil↗
PubMed1977

Serotypes of Bacillus cereus from outbreaks of food poisoning and from routine foods.

A provisional serotyping scheme was used to type cultures of Bacillus cereus from 84 outbreaks of food poisoning in seven countries; 283 of the 337 (84%) cultures tested were typable. In 35 of the 61 outbreaks associated with a vomiting-type syndrome, foods, clinical specimens or both yielded H-serotype 1 only. Type 1 strains together with other sterotypes were isolated in seven outbreaks. In 14 outbreaks types 3, 4, 5, 8 or a mixture of serotypes were present. Untypable strains were isolated in five outbreaks. Two of the nine diarrhoeal-type outbreaks yielded serotype 1 only. Types 2, 6, 8, 9, 10 and a mixture of type 12 and an untypable strain appeared to be responsible for one outbreak each. Although 16 of the 18 recognized serotypes were present among cultures of B. cereus from various routine foods, only 156 of the 400 (39%) isolates tested were typable.

Australia↗
PubMed1992

Investigation of an outbreak of methicillin-resistant Staphylococcus aureus in patients with skin disease using DNA restriction patterns.

OBJECTIVE: To investigate an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) among patients using chromosomal typing of the isolates. DESIGN: Comparison of epidemiological and clinical data to endonuclease restriction fragmentation analysis (RFA) of the MRSA isolates associated with an outbreak. Total DNA from the MRSA isolates was restricted with HINDIII and HAEIII for typing. SETTING: Tertiary care academic medical center. METHODS: An epidemiological investigation of an outbreak of MRSA among patients in private rooms was evaluated by routine infection control methods. The MRSA isolates from blood cultures of 7 patients and the nares of a nurse were collected during the outbreak. MRSA isolates from 23 patients not associated with the outbreak also were collected. The total DNA of the MRSA isolates were restricted with HINDIII and HAEIII and electrophoresed on 0.6% agarose gels. RESULTS: MRSA from 4 of the 7 bacteremic patients and the nurse on the outbreak unit had the same endonuclease restriction pattern. The patients were linked in that they were compromised by severe psoriasis or skin ulcers, were on the unit during the same period, and had oatmeal baths in a common bathtub. Of 50 staff members screened, the nurse was the only person detected as colonized by the strain. The other 3 patients on the unit as well as the 23 patients in other locations not associated with the outbreak had MRSA isolates with different RFA patterns. The use of the bathtub was discontinued and further transmission of MRSA was stopped. CONCLUSIONS: A comparison of the relatedness of MRSA by RFA demonstrated the uniqueness of the epidemiologically linked isolates and the utility of the RFA technique in the performance of routine infection control investigations.

Bacterial Typing Techniques↗
PubMed2026

Responding to a protracted tuberculosis outbreak: lessons from multiple rounds of investigation in a Chinese boarding school.

PURPOSE: This study analysed a multi-semester pulmonary tuberculosis (PTB) cluster outbreak in a Chinese boarding school to provide evidence for future epidemic control. METHODS: Contacts were screened via symptoms, infection tests and chest radiography. Screening expanded progressively from close contacts to same-floor contacts, then all students and staff. Whole-genome sequencing (WGS) with single nucleotide polymorphism (SNP) and bioinformatics analysis was used for lineage classification, transmission clustering (&#x2264;12 SNPs defining a cluster) and drug resistance prediction. RESULTS: From 2020 to 2022, 20 students were diagnosed with PTB, half laboratory-confirmed. Most cases clustered in class 16 and were epidemiologically linked to the primary case (case 0), who had household PTB exposure. Case 0 and case 1 had diagnostic delays exceeding 3 and 6&#xa0;months, respectively. WGS of five isolates (case 1, 3, 4, 9 and 10) collected over three semesters showed all belonged to lineage 2 and differed by &#x2264;12 SNPs, confirming the same transmission chain. The infection rate in class 16 (46.34%) was significantly higher than other case classes (19.05%) and classes without cases (8.27%) (&#x3c7;2&#xa0;=&#xa0;61.169, p&#xa0;<&#xa0;0.001). No new cases were detected during a one-year follow-up of students involved in the outbreak after the final round of screening, nor among household contacts of all cases followed up to the present. CONCLUSIONS: Lack of entry health examinations facilitated the outbreak. Delayed diagnosis, incomplete contact screening and absence of preventive treatment led to cross-semester persistence. The infection rate disparity confirms class 16 as the outbreak epicentre. Improving community case management, extending contact follow-up and enhancing cluster outbreak measures are recommended to prevent future outbreaks.

Humans↗
PubMed2025

Incorporating Epidemiological Data into the Genomic Analysis of Partially Sampled Infectious Disease Outbreaks.

Pathogen genomic data are increasingly being used to investigate transmission dynamics in infectious disease outbreaks. Combining genomic data with epidemiological data should substantially increase our understanding of outbreaks, but this is highly challenging when the outbreak under study is only partially sampled, so that both genomic and epidemiological data are missing for intermediate links in the transmission chains. Here, we present a new dynamic programming algorithm to perform this task efficiently. We implement this methodology into the well-established TransPhylo framework to reconstruct partially sampled outbreaks using a combination of genomic and epidemiological data. We use simulated datasets to show that including epidemiological data can improve the accuracy of the inferred transmission links compared with inference based on genomic data only. This also allows us to estimate parameters specific to the epidemiological data (such as transmission rates between particular groups), which would otherwise not be possible. We then apply these methods to two real-world examples. First, we use genomic data from an outbreak of tuberculosis in Argentina, for which data was also available on the HIV status of sampled individuals, in order to investigate the role of HIV coinfection in the spread of this tuberculosis outbreak. Second, we use genomic and geographical data from the 2003 epidemic of avian influenza H7N7 in the Netherlands to reconstruct its spatial epidemiology. In both cases, we show that incorporating epidemiological data into the genomic analysis allows us to investigate the role of epidemiological properties in the spread of infectious diseases.

Humans↗
PubMed2025

Temporal reconstruction of a Salmonella Enteritidis ST11 outbreak in New Zealand.

Outbreaks caused by Salmonella Enteritidis are commonly linked to eggs and poultry meat internationally, but this serovar had never been detected in Aotearoa New Zealand (NZ) poultry prior to 2021. Locally designated genomic cluster Salmonella Enteritidis_2019_C_01, was implicated in a 2019 outbreak associated with a restaurant in Auckland. Four Enteritidis_2019_C_01 sub-clusters have since been identified, two retrospectively, in the Auckland region. Authorities initiated a formal outbreak investigation after genomically indistinguishable S. Enteritidis was isolated from the NZ poultry production environment. This study analysed 231&#x2009;S. Enteritidis genomes obtained from the outbreak using Bayesian phylodynamic tools to gain insight into the outbreak's dynamics and origin. We used Bayesian integrated coalescent epoch plots to estimate the change of the Enteritidis ST11 population size over time and marginal structured coalescent approximation to estimate transmission between poultry producers. We investigated human and poultry isolates to elucidate the time and location of the most recent common ancestor of the outbreak and transmission pathways. The median most recent common ancestor was estimated to be February 2019. We found evidence of amplification and spread of strain Enteritidis_2019_C_01 within the poultry industry, as well as transmission events throughout the production chain. The intervention by the public health and food safety authorities coincided with a drop in the effective population size of the S. Enteritidis ST11 as well as notified human cases. This information is crucial for understanding and preventing the transmission of S. Enteritidis in NZ poultry to ensure poultry meat and eggs are safe for consumption.

Salmonella enteritidis↗
PubMed1976

Detection of Serratia outbreaks in hospital.

Infections due to Serratia marcescens were studied in 23 different hospitals. A retrospective study was done in 4 hospitals; all isolates were compared by serological typing, antibiograms, bacteriocin production, and bacteriocin sensitivity. 2 of the hospitals were having cross-infection problems due to antibiotic-resistant strains, but the other 2 had little or no cross-infection. Outbreaks were studied in 19 other hospitals. 9 of these outbreaks were classified as "common source" since contaminated "sterile solutions" were incriminated as the cause in each. One hospital had a "pseudo-outbreak," in which Serratia from E.D.T.A. blood-collecting tubes contaminated blood-cultures as they were collected. All 10 of these strains from common-source outbreaks were generally sensitive to antibiotics. Outbreaks in 9 other hospitals resulted from cross-infection and were caused by strains which were very resistant to antibiotics. Guidelines for detecting outbreaks are given and control measures are suggested.

Alabama↗
PubMed2026

Interspecies Exchange of Mobile Genetic Elements During a Plant Disease Outbreak.

Outbreak sequencing provides insight into the origin and evolutionary processes acting on emerging pathogens. Sequencing a historic multihost outbreak of Ralstonia spp. in Martinique shows the outbreak was caused by two lineages that diverged at separate times from mainland populations. One lineage (Ralstonia pseudosolanacearum I-18) was originally introduced from Asia to South America, where it became well established prior to its dissemination to Martinique, where it retains a signature of specialization on solanaceous hosts. The novel lineage first identified during the outbreak (Ralstonia solanacearum IIB-4NPB) arose from a mainland population endemic to the Americas prior to its arrival in Martinique, where host-range expansion was observed. In contrast to minor changes in secreted effector protein repertoires, the emergent R. solanacearum IIB-4NPB acquired a novel integrative and conjugative element (ICERsoRUN1145). After identifying all Ralstonia spp. ICEs and mapping their spatial and phylogenetic distribution among Ralstonia spp. sampled during the outbreak, we found closely related ICEs circulating in mainland populations of R. pseudosolanacearum, indicating likely exchange between introduced and endemic Ralstonia spp. The family of ICEs in Ralstonia (ICERs) has a conserved bipartite structure and display a striking pattern of functional specialization in each cargo gene insertion hotspot: the first hotspot is a target for metabolic gene acquisition, and the second is a target for defense element acquisition. This work provides unparalleled phylogenetic and spatial resolution of an unusual outbreak and highlights the role of horizontal transfer in shaping the ecological success of an emerging pathogen.

Plant Diseases↗