Outbreak Scenarios Research Articles

Editorial: Coronavirus disease 2019 (COVID-19) - advances in epidemiology, diagnostics, treatments, host-directed therapies, pathogenesis, vaccines, and ongoing challenges.

Editorial: Coronavirus disease 2019 (COVID-19) - advances in epidemiology, diagnostics, treatments, host-directed therapies, pathogenesis, vaccines, and ongoing challenges.

Immunotherapeutics for Ebola Virus Disease: Hope on the Horizon.

Ebola virus disease (EVD) remains among the biggest public health threats in Africa, even though recently a vaccine was approved for human use. However, in outbreak situations treatment strategies are needed in combination with vaccination campaigns to impact and stop the spread of the disease. Here, we discuss the development of the immunotherapeutics against EDV both targeting the virus itself and bolstering the immunological environment of the host at both the pre-clinical and clinical level. The early development of antibody therapy in preclinical settings and the early pitfalls in the implementation of this therapeutic strategy are discussed. We also consider the advancement of the production, modulation, and specificity of the antibody treatment that garnered increased success in preclinical studies to the point that it was warranted to test them in a clinical setting. Initial clinical trials in an outbreak scenario proved difficult to definitively confirm the efficacy of the implemented treatment. Upon further modification and with the experiences from the challenging outbreak conditions in mind, the PALM clinical trial demonstrated efficacy of an antibody cocktail which recently received approval for human use.

Outbreak detection for temporal contact data

Epidemic spreading is a widely studied process due to its importance and possibly grave consequences for society. While the classical context of epidemic spreading refers to pathogens transmitted among humans or animals, it is straightforward to apply similar ideas to the spread of information (e.g., a rumor) or the spread of computer viruses. This paper addresses the question of how to optimally select nodes for monitoring in a network of timestamped contact events between individuals. We consider three optimization objectives: the detection likelihood, the time until detection, and the population that is affected by an outbreak. The optimization approach we use is based on a simple greedy approach and has been proposed in a seminal paper focusing on information spreading and water contamination. We extend this work to the setting of disease spreading and present its application with two example networks: a timestamped network of sexual contacts and a network of animal transports between farms. We apply the optimization procedure to a large set of outbreak scenarios that we generate with a susceptible-infectious-recovered model. We find that simple heuristic methods that select nodes with high degree or many contacts compare well in terms of outbreak detection performance with the (greedily) optimal set of nodes. Furthermore, we observe that nodes optimized on past periods may not be optimal for outbreak detection in future periods. However, seasonal effects may help in determining which past period generalizes well to some future period. Finally, we demonstrate that the detection performance depends on the simulation settings. In general, if we force the simulator to generate larger outbreaks, the detection performance will improve, as larger outbreaks tend to occur in the more connected part of the network where the top monitoring nodes are typically located. A natural progression of this work is to analyze how a representative set of outbreak scenarios can be generated, possibly taking into account more realistic propagation models.

Deep Learning-Based Potential Ligand Prediction Framework for COVID-19 with Drug-Target Interaction Model.

To fight against the present pandemic scenario of COVID-19 outbreak, medication with drugs and vaccines is extremely essential other than ventilation support. In this paper, we present a list of ligands which are expected to have the highest binding affinity with the S-glycoprotein of 2019-nCoV and thus can be used to make the drug for the novel coronavirus. Here, we implemented an architecture using 1D convolutional networks to predict drug–target interaction (DTI) values. The network was trained on the KIBA (Kinase Inhibitor Bioactivity) dataset. With this network, we predicted the KIBA scores (which gives a measure of binding affinity) of a list of ligands against the S-glycoprotein of 2019-nCoV. Based on these KIBA scores, we are proposing a list of ligands (33 top ligands based on best interactions) which have a high binding affinity with the S-glycoprotein of 2019-nCoV and thus can be used for the formation of drugs.

Analytic Decision Gaming: A Tool for Crisis Response and Clinical Reasoning

Issue: Medical education traditionally focuses on basic science during the first two years of medical school. To “flip” this model, the Penn State College of Medicine has introduced and inquiry-based educational strategy that introduces students to the challenges of patient care immediately upon their arrival. To engage students in a process to promote clinical reasoning, we have modified an Analytic Decision Game (ADG) called “EpiCentre” to address a notional public health crisis facing Centre County, Pennsylvania.
 Methods: In phase 1 of the activity, students are provided with materials describing the ethnography and infrastructure of Centre County. Students are divided into three communities (teams) to create a strength, weakness, threat, opportunity (SWOT) analysis of local healthcare capabilities. In phase 2 of the activity, students meet with a standardized patient presenting with a targeted medical complaint. They are pushed to think about their approach to taking a medical history and asked to generate a differential diagnosis. In phases 3 and 4, students are faced with the challenge of triaging a number of patients with similar medical complaints and create a plan to deal with a likely outbreak scenario.
 Findings: Students have found the EpiCentre activity to be worthwhile in multiple contexts. They have been able to develop an initial approach to medical history taking and creating a differential diagnosis. They have formulated an approach to the recognition and control of a potential public health crisis. An additional benefit of the exercise has been the overarching theme of teamwork. Students begin the activity (occurring in the first few weeks after arrival to medical school) as relative strangers and quickly develop a sense of camaraderie and mission focus.
 Conclusions: The EpiCentre ADG has been a successful activity to introduce medical students to Centre County in the context of healthcare infrastructure, an approach to medical history taking, disaster planning, clinical reasoning and team-building.
 Implications: EpiCentre derives from an interprofessional collaboration between the College of Medicine and the College of Information Sciences and Technology. It represents one of potentially limitless opportunities to engage students and faculty from multiple disciplines to address challenges of public health within the academic setting.

Outbreak investigation of lumpy skin disease in dairy farms at Barishal, Bangladesh

Lumpy skin disease is explained as a significant cattle disease affecting cattle of many parts of the world. An outbreak was experienced in different parts of Bangladesh including Barishal for the first time in the last quarter of 2019. This investigation was carried out to know the outbreak scenario of the disease in southern part of Bangladesh. A total of 726 cattle were included in this study covering 50 dairy farms of Barishal region from September 2019 to December 2019. Morbidity rate was found 21% (CI: 18-24%) and mortality was 1% (CI: 1-2%) in the outbreak area. Young animals (24%) and pregnant animals (70%) were significantly more susceptible compared to aged animals (17%) and non-pregnant animals (15%), respectively. Moreover, male and crossbred cattle were slightly more prone to the infection in comparison to their counterparts. About 45% of the affected animals showed nodular and remaining 55% had edematous lesions. Almost 90% of the affected animals were treated with NSAID followed by antibiotics, antihistaminic, steroid drugs and antiviral drugs where only 20% of the affected animals were treated by authorized veterinary personnel. This was the first epidemiological investigation in the mentioned outbreak area which may serve as a baseline for LSD research in the location needed for developing effective control strategy.

Panic-Buying Behaviour During the Covid-19 Outbreak: A Cross-Cultural Psychological Study


 
 
 The Covid-19 outbreak has had a major impact across the globe. Tourism, education, health, and economies are all affected by this pandemic. One major impact on the economic sector is the emergence of ‘panic-buying’. This study examines panic-buying in cross-cultural psychological studies. The researchers conducted a literature review on previous studies related to panic-buying behaviours during both the Covid-19 outbreak and similar scenarios prior to Covid-19. The researchers provide an explanation on how panic-buying behaviour can occur. The researchers also compare panic-buying with similar behaviours such as impulsive and compulsive buying.
 Keywords: Panic buying, Pandemic, Covid-19, Cross-cultural psychological studies
 
 

A Study

Chikungunya, an infection which is difficult to treat, took a toll on Delhi in year 2016. In that scenario, detection and prevention of vector-borne diseases outbreak in Delhi have been a major cause of concern for government. For analyzing this epidemic outbreak, the authors have utilized the unstructured data generated through Twitter. Twitter is a social media platform that generates vast amount of epidemic-related information every day. This information is used to analyze the effect of epidemic outbreak in Delhi region. In this paper, the authors discussed an associated study of various machine learning techniques for analyzing and mining social media information. In this, the authors have also categorized and explore the steps involved in social media textual data to provide a pictorial view of the ongoing outbreak. Finally, the article discussed the challenges faced for mining social media data.

On Coexistence with COVID-19: Estimations and Perspectives.

Given the harsh reality faced by the global effort to contain coronavirus disease 2019 (COVID-19) and the virtual impossibility of its worldwide eradication in the foreseeable future, global human coexistence with fast mutating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have to occur, for the time being, irrespective of the wishes and aspirations of our people. Therefore, for China, the risk associated with small to medium scale outbreaks induced by imported cases and the corresponding need to continuously and promptly suppress domestic infections would persist for a certain period of time. However, such reality would not imply that we can deviate from our existing effective COVID-Zero strategy on entry-exit quarantine measures and community non-pharmaceutical interventions (NPIs) containment measures and embrace certain “open-up” strategies without reservation, resting solely on the hypothesis of the success of herd immunity induced by vaccination advocated by certain western countries. In this article, we found that even in a highly underestimated outbreak scenario under the most optimistic assumptions, once China adopts the control and prevention strategies of some typical western countries, the number of the daily new confirmed cases in China would likely rise up to hundreds of thousands of cases, and among which >10,000 cases would present with severe symptoms. Particularly, the number of standing severe cases would exceed the peak number nationwide in early 2020 within 1–2 days, which would have a devastating impact on the medical system of China and cause a great disaster within the nation.

Risk-Averse Multi-Stage Stochastic Programming to Optimizing Vaccine Allocation and Treatment Logistics for Effective Epidemic Response

Existing compartmental-logistics models in epidemics control are limited in terms of optimizing the allocation of vaccines and treatment resources under a risk-averse objective. In this paper, we present a data-driven, mean-risk, multi-stage, stochastic epidemics-vaccination-logistics model that evaluates various disease growth scenarios under the Conditional Value-at-Risk (CVaR) risk measure to optimize the distribution of treatment centers, resources, and vaccines, while minimizing the total expected number of infections, deaths, and close contacts of infected people under a limited budget. We integrate a new ring vaccination compartment into a Susceptible-Infected-Treated-Recovered-Funeral-Burial epidemics-logistics model. Our formulation involves uncertainty both in the vaccine supply and the disease transmission rate. Here, we also consider the risk of experiencing scenarios that lead to adverse outcomes in terms of the number of infected and dead people due to the epidemic. Combining the risk-neutral objective with a risk measure allows for a trade-off between the weighted expected impact of the outbreak and the expected risks associated with experiencing extremely disastrous scenarios. We incorporate human mobility into the model and develop a new method to estimate the migration rate between each region when data on migration rates is not available. We apply our multi-stage stochastic mixed-integer programming model to the case of controlling the 2018-2020 Ebola Virus Disease (EVD) in the Democratic Republic of the Congo (DRC) using real data. Our results show that increasing the risk-aversion by emphasizing potentially disastrous outbreak scenarios reduces the expected risk related to adverse scenarios at the price of the increased expected number of infections and deaths over all possible scenarios. We also find that isolating and treating infected individuals are the most efficient ways to slow the transmission of the disease, while vaccination is supplementary to primary interventions on reducing the number of infections. Furthermore, our analysis indicates that vaccine acceptance rates affect the optimal vaccine allocation only at the initial stages of the vaccine rollout under a tight vaccine supply.

The association of previous influenza vaccination and coronavirus disease-2019

ABSTRACT Studies have shown similarities in the structure of influenza and coronaviruses, in their binding receptors and in patterns of immune responses; and that influenza vaccine can induce cross-immunity. We examined the association of previous influenza vaccination and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, resulting in coronavirus disease-2019 (COVID-19), among 715,164 members of a health maintenance organization. In a multivariate regression model, the odds ratios for SARS-CoV-2 infection among individuals vaccinated for influenza in 2018–2019, 2019–2020, and in both seasons, compared to non-vaccinated individuals, were 0.82 (95% CI 0.68–0.99, p = .048), 0.79 (95% CI 0.67–0.98, p = .005), and 0.76 (95% CI 0.61–0.97, p = .004), respectively. Based on our findings, administration of influenza vaccine before the influenza season is highly recommended to reduce the burden of influenza, which is critical in scenarios of outbreaks of both influenza and SARS-CoV-2 infections, and also regarding its association with reduced rate of COVID-19.

An outbreak of Lumpy skin disease in Dairy herds of Pabna and Sirajganj districts, Bangladesh

Lumpy skin diseases (LSD) is an economically important emerging viral disease of cattle. An outbreak of LSD was experienced in different parts of Bangladesh including Sirajganj between the last half of 2019 to first quarter of 2020. This investigation was carried out to know the outbreak scenario of the disease in the Pabna and Sirajganj districts of Bangladesh. The LSD was diagnosed based on the clinical signs and data were collected from 97 dairy farms of two affected regions through a preformed questionnaire. A total of 886 animals were examined from those farms which includes milking cows, dry cows, heifer, calves and bulls. High fever, enlargement of superficial lymphnode and nodule on different parts of the body were most frequently encountered clinical signs during the investigation. One hundred and ninety seven animals were found positive and showed obvious signs of LSD in mild, moderate and severe form. The proportionate prevalence was 22.2% (95%CI 19.5-25.1%) which is quite similar to the other scientific findings. The morbidity rate was slightly high in the Pabna district (22.6%; 95% CI 19.4-26.1%) than in the Sirajganj(21.3%; 95% CI 16.6- 26.8%). The morbidity rate was higher in the female cattle’s (24.9%; 95% CI 20.3-29.8%) compare to the males 15.3% (95% CI 8.4-24.7%). Due to the more number of vectors prevalence of LSD was high in autumn (26.4%) and late autumn (36.5%) than the other seasons. Though most of the farmers rely on the veterinarians for the treatment of this disease but some of them were reluctant due to the treatment cost. So it’s important to focus on the prevention of LSD rather than the treatment.

A Review on Janapadoddhvamsa with special reference to current scenario of COVID-19 outbreak

Covid-19 is a new pandemic disease, which is caused by the virus knows as Coronavirus SARS-CoV-2. It is called SARS-CoV-2 because it is genetically related to each other, but the disease is different, so the ICTV announced this name on 11 February 2020. Its common signs and symptoms are infection which includes the respiratory symptoms, the fever, the cough, the shortness of breath, and the breathing difficulties. And In all of the severe cases, the infection which can cause pneumonia, and severe acute respiratory syndrome (SARS), kidney failure and its even cause death also. It is all communicable diseases and in the Ayurvedic literature s the communicable diseases are mentioned under the Janapadoddhvamsa and the Aupasargik Ragas. Its causative agents and methods of prevention have been already clearly explained in Janapadoddhvamsa. So, to manage Janapadoddhvamsa it is advised to take the usage of Rasayana therapy, Panchkarama procedures, Sadvrit Paalan (code of right conducts) and Aachara Rasyana it means the behavioural therapy, Dhupan Karma (Fumigation) and Vaad Chikitsa (Sound therapy). And the effort has been made to find the possible Ayurvedic comparison to the current outbreak of COVID-19. It is indicated under Pranavaha Srotasa (respiratory system) diseases in kashyap Samhita, which is based on the cardinal signs and symptoms, and the system which is involved. Also aims to provide information among the Rasayana Aushadi which can be cooperated in day to day life as an immune modulator along with Vyadhihara Chikitsa. So, the effort which is made to compile the knowledge of Janapadoddhvamsa, so, it should be applied for the betterment human life and maybe also provides the answer to the challenge of COVID-19.

Impact of a Coronavirus Epidemic on China’s Public Debt Ratio Growth

Public opinion in the economic profession is strongly preoccupied with the expected negative economic effects of the coronavirus epidemic. Among the consequences, special attention is paid to the increase in the gross debt of the states. Indeed, based on conventional economic knowledge, it is clear to everyone that the economic downturn and the increase in government sector expenditure will directly lead to a sharp rise in government debt. The study aims to predict an increase in China’s government debt ratio using a macroeconomic model. The study will quantify the rate of increase in China’s public debt based on four theoretically possible scenarios for the course of the coronavirus epidemic. I am aware that it is difficult to apply conventional economic knowledge to China’s state-capitalist system. This is explained by the fact that the theories of the socialist economic model do not apply to China either. At the same time, the functioning of China's economy is closer to that of market-based economies, but the country's structure as a whole cannot be integrated into this framework either. But models describing the economic development of developing national economies cannot be applied to the country either. Nonetheless, I attempt to use conventional economic economics to attempt to quantify the impact of the coronavirus epidemic on China’s sovereign debt ratio. China’s public debt growth rates calculated under different outbreak scenarios are different, but none show an increase that would call into question the financing of China’s public debt.

Identifying septic pollution exposure routes during a waterborne norovirus outbreak - A new application for human-associated microbial source tracking qPCR

In June 2017, the Pennsylvania Department of Health (PADOH) was notified of multiple norovirus outbreaks associated with 179 ill individuals who attended separate events held at an outdoor venue and campground over a month period. Epidemiologic investigations were unable to identify a single exposure route and therefore unable to determine whether there was a persistent contamination source to target for exposure mitigation. Norovirus was detected in a fresh recreational water designated swimming area and a drinking water well. A hydrogeological site evaluation suggested a nearby septic leach field as a potential contamination source via ground water infiltration. Geological characterization revealed a steep dip of the bedrock beneath the septic leach field toward the well, providing a viral transport pathway in a geologic medium not previously documented as high risk for viral ground water contamination. The human-associated microbial source tracking (MST) genetic marker, HF183, was used as a microbial tracer to demonstrate the hydrogeological connection between the malfunctioning septic system, drinking water well, and recreational water area. Based on environmental investigation findings, venue management and local public health officials implemented a series of outbreak prevention strategies including discontinuing the use of the contaminated well, issuing a permit for a new drinking water well, increasing portable toilet and handwashing station availability, and promoting proper hand hygiene. Despite the outbreaks at the venue and evidence of ground water contamination impacting nearby recreational water and the drinking water well, no new norovirus cases were reported during a large event one week after implementing prevention practices. This investigation highlights a new application for human-associated MST methods to trace hydrological connections between multiple fecal pollutant exposure routes in an outbreak scenario. In turn, pollutant source information can be used to develop effective intervention practices to mitigate exposure and prevent future outbreaks associated with human fecal contaminated waters.

SARS-CoV-2, the other face to SARS-CoV and MERS-CoV: Future predictions

Coronavirus disease 2019 (COVID-19) outbreak is proving to be an unprecedented disaster that lays its dark shadow on global health, economics and personal freedom. Severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS) epidemics provide scientific data that is useful in better understanding and resolution of COVID-19. Similarities among SARS-CoV, MERS-CoV and SARS-CoV-2 have been investigated in the light of available data. SARS-CoV, MERS-CoV and SARS-CoV-2 evolved in bats and have positive-sense RNA genomes of 27.9 kb, 30.1 kb and 29.9 kb, respectively. Molecular and serological tools used for diagnosis of SARS and MERS patients resemble COVID-19 diagnostic tools. Stability and longevity data of SARS and MERS epidemics contribute in the current pandemic precaution policies. Trials to produce vaccines for SARS-CoV and MERS-CoV failed, therefore different strategies were employed for SARS-CoV2 vaccines production and during the past period antiviral agents, Convalescent plasma and monoclonal antibodies provide potential treatments for sever patients. The mortality rate caused by the SARS-CoV and MERS-CoV reached 15% and 37%, respectively. The first declarations about mortality rate of SARS-CoV-2 was around 2–4% but now this rate differed globally and reached more than 13% in some countries. A realistic COVID-19 outbreak scenario suggest that the pandemic might last for three years with fluctuation in the number of infected cases, unless vaccination process goes faster and/or antiviral drug is discovered.

Management of bacteriological specimens of patients suffering from coronavirus disease 2019 (COVID-19)

Management of bacteriological specimens of patients suffering from coronavirus disease 2019 (COVID-19)

Quantitative microbial risk assessment (QMRA) of occupational exposure to SARS-CoV-2 in wastewater treatment plants

The current global Severe Acute Respiratory Syndrome- Coronavirus-2 (SARS-CoV-2) epidemic has heightened calls for studies to evaluate respiratory exposure for wastewater treatment workers. In this global first study, we assess occupational health risks to wastewater treatment plant (WWTP) operators from inhalation of aerosolized SARS-CoV-2 using a Quantitative Microbiological Risk Assessment (QMRA) framework. The following considerations were used to develop the QMRA and assess the illness risks to workers: a) the proportion of the population who are infected and thus responsible for shedding SARS-CoV-2 into raw wastewater; b) the concentration of SARS-CoV-2 in raw and treated wastewater; c) the volume of aerosolized water inhaled by a WWTP operator during work; d) humidity and temperature-dependent viability of coronaviruses in aerosolized waste water; e) estimation of the amount, frequency, and duration of exposure; and f) exposure doses. The variables were then fed into an exponential dose response model to estimate the risks in three scenarios representing low-grade, moderate and aggressive outbreaks. These scenarios were designed on the assumption of 0.03%, 0.3% and 3% of the wastewater-generating population being infected with SARS-CoV-2. In terms of averaged-out illness risk profiles, the individual illness risks for low grade, moderate and aggressive outbreak scenarios respectively are 0.036, 0.32 and 3.21 illness cases per 1000 exposed WWTP operators. Our study suggests that the risk of accidental occupational exposure to SARS-CoV-2 in raw wastewater, via inhalation at the WWTP environment, is negligible, particularly when less than 0.3% of the population served by the plant are actively infected.

Immunogenicity and Protective Efficacy of a Non-Living Anthrax Vaccine versus a Live Spore Vaccine with Simultaneous Penicillin-G Treatment in Cattle.

Sterne live spore vaccine (SLSV) is the current veterinary anthrax vaccine of choice. Unlike the non-living anthrax vaccine (NLAV) prototype, SLSV is incompatible with concurrent antibiotics use in an anthrax outbreak scenario. The NLAV candidates used in this study include a crude recombinant protective antigen (CrPA) and a purified recombinant protective antigen (PrPA) complemented by formalin-inactivated spores and Emulsigen-D®/Alhydrogel® adjuvants. Cattle were vaccinated twice (week 0 and 3) with NLAVs plus penicillin-G (Pen-G) treatment and compared to cattle vaccinated twice with SLSV alone and with Pen-G treatment. The immunogenicity was assessed using ELISA against rPA and FIS, toxin neutralisation assay (TNA) and opsonophagocytic assay. The protection was evaluated using an in vivo passive immunisation mouse model. The anti-rPA IgG titres for NLAVs plus Pen-G and SLSV without Pen-G treatment showed a significant increase, whereas the titres for SLSV plus Pen-G were insignificant compared to pre-vaccination values. A similar trend was measured for IgM, IgG1, and IgG2 and TNA titres (NT50) showed similar trends to anti-rPA titres across all vaccine groups. The anti-FIS IgG and IgM titres increased significantly for all vaccination groups at week 3 and 5 when compared to week 0. The spore opsonising capacity increased significantly in the NLAV vaccinated groups including Pen-G treatment and the SLSV without Pen-G but much less in the SLSV group with Pen-G treatment. Passive immunization of A/J mice challenged with a lethal dose of 34F2 spores indicated significant protective capacity of antibodies raised in the SLSV and the PrPA + FIS + adjuvants vaccinated and Pen-G treated groups but not for the NLAV with the CrPA + FIS + adjuvants and the SLSV vaccinated and Pen-G treated group. Our findings indicate that the PrPA + FIS + Emulsigen-D®/Alhydrogel® vaccine candidate may provide the same level of antibody responses and protective capacity as the SLSV. Advantageously, it can be used concurrently with Penicillin-G in an outbreak situation and as prophylactic treatment in feedlots and valuable breeding stocks.

Siblings’ Precautions and Parents’ Decolonization to Control Methicillin-Resistant Staphylococcus aureus in a Neonatal Intensive Care Unit (NICU)

Background: Following the first reports of the emergence of methicillin-resistant Staphylococcus aureus (MRSA) in the 1970s, several measures to prevent its transmission were introduced in hospitals. However, controversy continues regarding the best approach to prevent and control MRSA, especially in neonatal intensive care units (NICUs). Objective: To report the reduction of colonization and primary central venous catheter–related bloodstream infection (CRBSI) caused by MRSA through surveillance, decolonization, and adoption of best practices in intravenous catheter care. Methods: Quasi-experimental, nonrandomized, before-and-after intervention study conducted in a 70-bed NICU in a private maternity hospital in Brazil. Period studied comprehended between August 2018 and May 2019 (period 1 - preintervention) and June to December 2019 (period II - postintervention). At the end of period 1, several measures were implanted to control and prevent colonization and CRBSI in the unit. The following measures were implemented: incentive to hand hygiene; best practices training on medication preparation and central catheter manipulation; systematic screening of colonized patients with nasal and umbilical swabs; contact precautions for colonized newborn (NB); contact precautions for twins of a colonized NB even when they had a negative swab; decolonization of patients with nasal mupirocin and chlorohexidine (oral preparation) for oral hygiene; concurrent linen change at the end of the patient’s decolonization; decolonization of parents of colonized siblings with chlorohexidine bath and nasal mupirocin; environmental organization; intensification of cleaning and disinfection of equipment and articles; cohort of patients and workers; isolation and precautions compliance audit; professional investigation and decolonization and universal chlorhexidine bath for newborns. Results: In periods I and II, the positivity rates of the collected swabs were 4.14% and 0.75% (P < .0001), respectively, with a peak of positivity of 11.8% in January. Also, 12 episodes of CRBSI were documented in period I (incidence, 2.9%) versus no episode in period 2, with a significant difference in incidence rate between the 2 periods (P = .002). Conclusion: The innovative measures were effective for eradicating the outbreak when instituted together with recognized good practices. In an outbreak scenario is difficult to define the isolated impact of each measure, although, parents’ decolonization to prevent the colonization of other siblings and contact precautions for twins of colonized NB seemed to improve the results.Funding: NoneDisclosures: None