New York City (NYC) was the epicenter of the early US COVID-19 pandemic. From March to May 2020, overburdened healthcare centers precipitated an emergent need for non-traditional facilities to meet patient care demands. Given travel restrictions and NYC\'s underutilized tourist infrastructure, hotels were available to support emergency response needs. This article describes the process by which NYC\'s non-medical COVID-19 hotel programs were selected, mobilized, and operated, including lessons learned. NYC agencies and organizations collaborated, creating an interagency initiative that activated hotels to provide safe isolation and quarantine spaces for those diagnosed with or exposed to COVID-19, aiming to reduce community spread, increase capacity for NYC\'s strained healthcare system, and mitigate interagency redundancy. Interagency groups addressed hotel challenges, including infection prevention and control; behavioral health, intellectual, and developmental disorders; social determinants of health; and coordination, operations, and planning. NYC\'s COVID-19 hotel program successfully supported overburdened hospitals by providing alternate locations for non-inpatient COVID-19 individuals. Community engagement required a methodical approach, balancing quality assurance with efficient access. An interagency coordinating body developed and shared clinical criteria for hotel admissions, infection prevention and control (IPC) procedures, and discharge plans, enhancing the program\'s ability to scale and address complex needs. Lessons learned from this program can be applied for smoother implementation of similar programs in the future.

With increasing awareness of water sinks as potential sources of outbreaks and transmission of multi-drug resistant (MDR) bacteria in intensive care units (ICUs), there is growing interest in water-free patient care systems. This systematic review reviewed and synthesized available evidence on the effectiveness of sink removal with or without water-free activities in the ICU environment to reduce water-borne healthcare-associated infections. We searched five databases (PubMed, MEDLINE, Scopus, Web of Science and Embase) for studies published from 1st January 1980 to 2nd April 2024 that examined water-less or water-free activities in the ICU to reduce healthcare-associated infections and patient colonization. Of 2075 articles, seven quasi-experimental studies (total: 332 patient beds) met the study selection criteria. Six of these seven studies (85.7%) were based in adult ICUs; one (14%) was in a neonatal ICU. Five of seven sites (71.4%) implemented water-less interventions after an outbreak. Water-free alternatives used included water-less bath products (six of seven; 85.7%), bottled water for consumption (three of seven; 42.9%), oral care (three of seven; 42.9%) and dissolving of oral medication (four of seven; 57.1%), designated \'contaminated\' sink outside of patient and medication preparation areas for disposal of wastewater (four of seven; 57.1%). Implicated pathogens studied included MDR Gram-negative bacteria (four of seven; 57.1%), MDR Pseudomonas aeruginosa only (two of seven; 28.6%), and pulmonary non-tuberculous mycobacterium (NTB) (one of seven; 14.3%). Five of seven (71.4%) studies reported outbreak cessation. Preliminary evidence, from a limited number of studies of which the majority were conducted in an outbreak setting, suggest that sink removal and other water-free interventions in the ICU helped terminate outbreaks involving taps and decrease hospital-onset respiratory isolation of pulmonary NTB.

In 2021 and 2022, there were noted to be clusters of pediatric acute hepatitis of unknown origin (AHUO) occurring across the globe. While there was not necessarily a global increase in cases, understanding the pattern of liver injury in AHUO is crucial to properly identify cases of this unexplained phenomenon, especially since it occurred simultaneously with a global resurgence of COVID-19. The objective of this study was to contrast the patterns in liver-relevant biochemical data from COVID-19 patients and AHUO. Studies reporting liver chemistries for cases of AHUO and COVID-19 were identified by a systematic review and search of the literature. For each case, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, direct bilirubin, and international normalized ratio (INR) levels were extracted as available. These were normalized to multiples of the upper limit of normal by patient age. There were statistically significant greater elevations of ALT and AST in patients with AHUO than in those with COVID-19. Only a subset of patients with COVID-19 had an AST or ALT greater than the normal range. INR elevation could be substantial for both conditions but was also statistically higher in the AHUO group. Liver chemistry changes were not statistically correlated with age. The pattern of liver chemistry changes between AHUO and COVID-19 have some distinctions, which suggests that AHUO is not a phenomenon driven primarily by SARS-CoV-2 infection alone. Differentiating AHUO and COVID-19 would be challenging based on patterns of liver chemistry changes alone.

In April 2022, the World Health Organization (WHO) declared a global outbreak of acute hepatitis of unknown etiology (AHUE) with a high risk of severe outcomes, for which various etiologies have been proposed by the literature. This study examines primary reports of pediatric AHUE cases and summarizes the proposed etiologies. This systematic review collected and evaluated published peer-reviewed articles, official data, and clinical reports of AHUE cases that met the WHO working case definition. 19 hypothesized etiologies for AHUE were identified from 36 sources, which fell into eight categories. While human adenovirus (HAdV) infection, viral infection, and immune-mediated responses were commonly suspected as causes of AHUE, no definitive etiology or epidemiological link has been established. However, recent evidence implicates adeno-associated virus-2 (AAV2) as a likely significant contributor. Conducting a comprehensive literature review following outbreaks is necessary for developing responsive strategies and protocols.

The world has seen numerous infectious disease outbreaks in the past decade. In many cases these outbreaks have had considerable perinatal health consequences including increased risk of preterm delivery (e.g., influenza, measles, and COVID-19), and the delivery of low birth weight or small for gestational age babies (e.g., influenza, COVID-19). Furthermore, severe perinatal outcomes including perinatal and infant death are a known consequence of multiple infectious diseases (e.g., Ebola virus disease, Zika virus disease, pertussis, and measles). In addition to vaccination during pregnancy (where possible), pregnant women, are provided some level of protection from the adverse effects of infection through community-level application of evidence-based transmission-control methods. This review demonstrates that it takes almost 2 years for the perinatal impacts of an infectious disease outbreak to be reported. However, many infectious disease outbreaks between 2010 and 2020 have no associated pregnancy data reported in the scientific literature, or pregnancy data is reported in the form of case-studies only. This lack of systematic data collection and reporting has a negative impact on our understanding of these diseases and the implications they may have for pregnant women and their unborn infants. Monitoring perinatal health is an essential aspect of national and global healthcare strategies as perinatal life has a critical impact on early life mortality as well as possible effects on later life health. The unpredictable nature of emerging infections and the potential for adverse perinatal outcomes necessitate that we thoroughly assess pregnancy and perinatal health implications of disease outbreaks and their public health interventions in tandem with outbreak response efforts. Disease surveillance programs should incorporate perinatal health monitoring and health systems around the world should endeavor to continuously collect perinatal health data in order to quickly update pregnancy care protocols as needed.

Domestic violence is a public health issue that has a long-term and irreversible effect on the victims. There are vulnerable groups like children, women, and elders. The problem becomes worse for these populations in the time of catastrophic events including disease pandemics. However, few attempts have been made to systematically review the prevalence and pattern of domestic violence during these times all over the world.
An initial search of PubMed will be followed by CINAHL, Scopus, Google Scholar, Embase, and ProQuest Health. The titles and abstracts of studies will be reviewed, and full-text articles will be selected if the inclusion criteria are met. Studies that meet the eligibility criteria will then be assessed by two independent reviewers. Full-text articles will be selected if the inclusion criteria are met. A standardized critical appraisal checklist for studies reporting prevalence data will be used to assess the methodological quality, and a standardized data extraction tool will be used. The results from the included studies will be analysed using the JBI SUMARI software.
This systematic review will provide solid evidence on the magnitude of domestic violence of any forms during catastrophic disease outbreaks including the current pandemic, COVID-19.
PROSPERO CRD42020192255 .

Pasteurization kills harmful microorganisms found in milk. While consumption of unpasteurized milk and its products is discouraged due to increased risk of infections, some individuals prefer unpasteurized dairy products. Our objective was to estimate the burden of illness from outbreaks arising from consumption of unpasteurized and pasteurized dairy products in Canada and the United States.
We conducted a systematic review of dairy-associated outbreaks in Canada and the USA from 2007 onward. We searched MEDLINE, Embase, Cochrane Library, TRIP Database for guidelines, and North American government agency websites up to October 2020. We included outbreak reports where the pathogenic microbe was confirmed in both the patient and the dairy product through laboratory testing.
Thirty-two disease outbreaks were linked to dairy consumption. Twenty outbreaks involving unpasteurized products resulted in 449 confirmed cases of illness, 124 hospitalizations, and five deaths. Twelve outbreaks involving pasteurized products resulted in 174 confirmed cases of illness, 134 hospitalizations, 17 deaths, and seven fetal losses. Listeria accounted for 10 out of 12 outbreaks from pasteurized products from 2007 through 2020.
Public warnings about the risk of unpasteurized dairy consumption need to continue and pregnant women and immunocompromised hosts need to be made aware of foods at high risk of contamination with Listeria.
RéSUMé: OBJECTIF: La pasteurisation tue les micro-organismes dangereux contenus dans le lait. Même si la consommation du lait non pasteurisé et ses produits fût déconseillée en raison d’un risque accru d’infection, certaines personnes préfèrent des produits laitiers non pasteurisés. Notre objectif était d’évaluer le fardeau de maladie des éclosions résultant de la consommation des produits laitiers non pasteurisés et pasteurisés au Canada et aux États-Unis. MéTHODE: Nous avons mené une revue systématique des éclosions liées aux produits laitiers au Canada et aux États-Unis depuis 2007. Nous avons cherché dans MEDLINE, Embase, Cochrane Library, TRIP Database et les sites web des agences gouvernementales Nord-Américaines pour la période 2007 jusqu’au mois d’octobre 2020. Nous avons inclus des rapports d’éclosion lorsque les essais en laboratoire ont confirmé la présence du microbe pathogène dans le patient ainsi que dans le produit laitier. RéSULTATS: Trente-deux éclosions étaient liées à la consommation des produits laitiers. Les produits non pasteurisés étaient impliqués dans 20 éclosions, avec 449 cas de maladie confirmés, 124 hospitalisations et 5 morts. Les produits pasteurisés étaient impliqués dans 12 éclosions, avec 174 cas de maladie confirmés, 134 hospitalisations, 17 morts et sept morts fœtales. Listeria comptait pour 10 des 12 éclosions des produits pasteurisés de 2007 à 2020. CONCLUSION: Les avis publics au sujet du risque de la consommation des produits laitiers non pasteurisés devraient continuer et les femmes enceintes et les hôtes immunodéprimés devraient être informés de la nourriture à haut risque de la contamination avec Listeria.

OBJECTIVE: Identifying and describing components of existent governmental reporting systems of NO aiming at informing the design of the implementation of NO reporting systems in countries where they were not fully established.
METHODS: A systematic search was carried out on PubMed, Embase, and the Latin American and Caribbean Health Sciences Literature database. We included studies published from January 2007 to June 2019 describing NO governmental reporting systems. Additionally, we included studies from the list of references in the identified papers, to gather more information about NO reporting systems. We also reviewed documents published in the governmental health department\'s websites, such as outbreak management guidelines and surveillance protocols, provided they were cited in the papers.
RESULTS: NO reporting systems were reported in France (Alsace Region), Germany, Norway, England, USA (New York State; New York City), Australia (Victoria State), Sweden (Skane Region), Ireland, Scotland (Lothian Region), and Canada (Winnipeg; Ontario). These systems vary according to the type of targeted NO event, such as gastroenteritis, influenza-like illness, invasive group A streptococcal disease or all-HAI NO. Germany, Norway, New York City, New York State, Ireland, Winnipeg, and Ontario have established a mandatory reporting for NO.
CONCLUSIONS: There is high variability among countries regarding governmental NO reporting systems. This may hinder opportune inter and intra-countries communication concerning NO of potential international public health relevance.

Machine learning (ML) methods can be leveraged to prevent the spread of deadly infectious disease outbreak (e.g., COVID-19). This can be done by applying machine learning methods in predicting and detecting the deadly infectious disease. Most reviews did not discuss about the machine learning algorithms, datasets and performance measurements used for various applications in predicting and detecting the deadly infectious disease. In contrast, this paper outlines the literature review based on two major ways (e.g., prediction, detection) to limit the spread of deadly disease outbreaks. Hence, this study aims to investigate the state of the art, challenges and future works of leveraging ML methods to detect and predict deadly disease outbreaks according to two categories mentioned earlier. Specifically, this study provides a review on various approaches (e.g., individual and ensemble models), types of datasets, parameters or variables and performance measures used in the previous works. The literature review included all articles from journals and conference proceedings published from 2010 through 2020 in Scopus indexed databases using the search terms Predicting Disease Outbreaks and/or Detecting Disease using Machine Learning. The findings from this review focus on commonly used machine learning approaches, challenges and future works to limit the spread of deadly disease outbreaks through preventions and detections.

Background: The spreading of health-related rumors can profoundly put society at risk, and the investigation of strategies and methods can efficiently prevent the dissemination of hazardous rumor is necessary, especially during a public health emergency including disease outbreaks. In this article we review the studies that implicated the surveillance system in identifying rumors and discuss the different aspects of current methods in this field. Methods: We searched PubMed, EMBASE, Scopus, and Web of Science databases for relevant publications in English from 2000 to 2020. The PICOS approach was used to select articles, and two reviewers extracted the data. Findings were categorized as a source of rumors, type of systems, data collection, and data transmission methods. The quality of the articles was assessed using the Mixed Method Appraisal Tool (MMAT) checklist. Results: Five studies that presented the methods used for rumor detection in different outbreaks were included in the critical appraisal process. Findings were grouped into four categories: source of rumors, type of systems, data collection, and data transmission methods. The source of rumors in most studies was media, including new social and traditional media. The most used data collection methods were human-computer interaction technique, and automatic and manual methods each were discussed in one study. Also, the data transmission method was asynchronous in the majority of studies. Conclusion: Based on our findings, the most common rumor detection systems used in the outbreaks were manual and/or human-computer methods which are considered to be time-consuming processes. Due to the ever-increasing amount of modern social media platforms and the fast-spreading of misinformation in the times of outbreaks, developing the automatically and real-time tools for rumor detection is a vital need.