The effectiveness of intervention measures on MERS-CoV transmission by using the contact networks reconstructed from link prediction data.

Introduction: Mitigating the spread of infectious diseases is of paramount concern for societal safety, necessitating the development of effective intervention measures. Epidemic simulation is widely used to evaluate the efficacy of such measures, but realistic simulation environments are crucial for meaningful insights. Despite the common use of contact-tracing data to construct realistic networks, they have inherent limitations. This study explores reconstructing simulation networks using link prediction methods as an alternative approach. Methods: The primary objective of this study is to assess the effectiveness of intervention measures on the reconstructed network, focusing on the 2015 MERS-CoV outbreak in South Korea. Contact-tracing data were acquired, and simulation networks were reconstructed using the graph autoencoder (GAE)-based link prediction method. A scale-free (SF) network was employed for comparison purposes. Epidemic simulations were conducted to evaluate three intervention strategies: Mass Quarantine (MQ), Isolation, and Isolation combined with Acquaintance Quarantine (AQ + Isolation). Results: Simulation results showed that AQ + Isolation was the most effective intervention on the GAE network, resulting in consistent epidemic curves due to high clustering coefficients. Conversely, MQ and AQ + Isolation were highly effective on the SF network, attributed to its low clustering coefficient and intervention sensitivity. Isolation alone exhibited reduced effectiveness. These findings emphasize the significant impact of network structure on intervention outcomes and suggest a potential overestimation of effectiveness in SF networks. Additionally, they highlight the complementary use of link prediction methods. Discussion: This innovative methodology provides inspiration for enhancing simulation environments in future endeavors. It also offers valuable insights for informing public health decision-making processes, emphasizing the importance of realistic simulation environments and the potential of link prediction methods.

Cases of Meningococcal Disease Associated with Travel to Saudi Arabia for Umrah Pilgrimage - United States, United Kingdom, and France, 2024.

Invasive meningococcal disease (IMD), caused by infection with the bacterium Neisseria meningitidis, usually manifests as meningitis or septicemia and can be severe and life-threatening (1). Six serogroups (A, B, C, W, X, and Y) account for most cases (2). N. meningitidis is transmitted person-to-person via respiratory droplets and oropharyngeal secretions. Asymptomatic persons can carry N. meningitidis and transmit the bacteria to others, potentially causing illness among susceptible persons. Outbreaks can occur in conjunction with large gatherings (3,4). Vaccines are available to prevent meningococcal disease. Antibiotic prophylaxis for close contacts of infected persons is critical to preventing secondary cases (2).

Staphylococcus aureus: No ticket for the Paris 2024 Olympic Games!

Athletes are vulnerable to Staphylococcus aureus infections due to skin-to-skin contact and skin abrasions during training and competitions involving sharied sport equipment or toiletries, which promote the spread of the bacteria between athletes and within sport teams. This results not only in higher prevalence of S.aureus carriage among athletes compared to the general population, but also in outbreaks of infections, particularly skin infections, within sports teams. To limit the spread of S. aureus among athletes, a decolonization protocol can be applied when clustered cases of S. aureus infections occur, especially if Panton-Valentine leukocidin-producing strains are implicated. Finally, to avoid exposing athletes to S.aureus transmission/colonization, it is recommended to establish strict and clearly formulated individual and collective hygiene rules and to regularly disinfect shared sports equipment.

Community led health promotion to counter stigma and increase trust amongst priority populations: lessons from the 2022-2023 UK mpox outbreak.

BACKGROUND: Stigma, lack of trust in authorities, and poor knowledge can prevent health-seeking behaviour, worsen physical and mental health, and undermine efforts to control transmission during disease outbreaks. These factors are particularly salient with diseases such as mpox, for which 96% of cases in the 2022-2023 UK outbreak were identified among gay, bisexual, queer and men who have sex with men (MSM). This study explored stigma and health-seeking behaviour in Liverpool through the lens of the recent mpox outbreak. METHODS: Primary sources of data were interviews with national and regional key informants involved in the mpox response, and participatory workshops with priority populations. Workshop recruitment targeted Grindr users (geosocial dating/hookup app) and at risk MSM; immigrant, black and ethnic minority MSM; and male sex workers in Liverpool. Data were analysed using a deductive framework approach, building on the Health Stigma and Discrimination Framework. RESULTS: Key informant interviews (n = 11) and five workshops (n = 15) were conducted. There were prevalent reports of anticipated and experienced stigma due to mpox public health messaging alongside high demand and uptake of the mpox vaccine and regular attendance at sexual health clinics. Respondents believed the limited impact of stigma on health-seeking behaviour was due to actions by the LGBTQ + community, the third sector, and local sexual health clinics. Key informants from the LGBTQ + community and primary healthcare felt their collective action to tackle mpox was undermined by central public health authorities citing under-resourcing; a reliance on goodwill; poor communication; and tokenistic engagement. Mpox communication was further challenged by a lack of evidence on disease transmission and risk. This challenge was exacerbated by the impact of the COVID-19 pandemic on the scientific community, public perceptions of infectious disease, and trust in public health authorities. CONCLUSIONS: The LGBTQ + community and local sexual health clinics took crucial actions to counter stigma and support health seeking behaviour during the 2022-2023 UK mpox outbreak. Lessons from rights based and inclusive community-led approaches during outbreaks should be heeded in the UK, working towards more meaningful and timely collaboration between affected communities, primary healthcare, and regional and national public health authorities.

A comprehensive analysis of non-pharmaceutical interventions and vaccination on Ebolavirus disease outbreak: Stochastic modeling approach.

Ebolavirus disease (EVD) outbreaks have intermittently occurred since the first documented case in the 1970s. Due to its transmission characteristics, large outbreaks have not been observed outside Africa. However, within the continent, significant outbreaks have been attributed to factors such as endemic diseases with similar symptoms and inadequate medical infrastructure, which complicate timely diagnosis. In this study, we employed a stochastic modeling approach to analyze the spread of EVD during the early stages of an outbreak, with an emphasis on inherent risks. We developed a model that considers healthcare workers and unreported cases, and assessed the effect of non-pharmaceutical interventions (NPIs) using actual data. Our results indicate that the implementation of NPIs led to a decrease in the transmission rate and infectious period by 30% and 40% respectively, following the declaration of the outbreak. We also investigated the risks associated with delayed outbreak recognition. Our simulations suggest that, when accounting for NPIs and recognition delays, prompt detection could have resulted in a similar outbreak scale, with approximately 50% of the baseline NPIs effect. Finally, we discussed the potential effects of a vaccination strategy as a follow-up measure after the outbreak declaration. Our findings suggest that a vaccination strategy can reduce both the burden of NPIs and the scale of the outbreak.

Successful Distribution of Tecovirimat During the Peak of the Mpox Outbreak - Los Angeles County, June 2022-January 2023.

Tecovirimat is the first-line antiviral treatment recommended for severe mpox or for persons with mpox who are at risk for severe disease; tecovirimat is available in the United States under an expanded access investigational new drug (IND) protocol. During the 2022-2023 mpox outbreak, local U.S. health jurisdictions facilitated access to tecovirimat. In June 2022, Los Angeles County (LAC) rapidly developed strategies for tecovirimat distribution using existing medical countermeasure distribution networks established by the Public Health Emergency Preparedness Program and the Hospital Preparedness Program, creating a hub and spoke distribution network consisting of 44 hub facilities serving 456 satellite sites across LAC. IND patient intake forms were analyzed to describe mpox patients treated with tecovirimat. Tecovirimat treatment data were matched with case surveillance data to calculate time from specimen collection to patients receiving tecovirimat. Among 2,281 patients with mpox in LAC, 735 (32%) received tecovirimat during June 2022-January 2023. Among treated patients, approximately two thirds (508; 69%) received treatment through community clinics and pharmacies. The median interval from specimen collection to treatment was 2 days (IQR = 0-5 days). Local data collection and analysis helped to minimize gaps in treatment access and facilitated network performance monitoring. During public health emergencies, medical countermeasures can be rapidly deployed across a large jurisdiction using existing distribution networks, including clinics and pharmacies.

The United States Needs A Better Testing Playbook For Future Public Health Emergencies.

The absence of a comprehensive national playbook for developing and deploying testing has hindered the United States' ability to rapidly suppress recent biological emergencies (for example, the COVID-19 pandemic and outbreaks of mpox). We describe here the Testing Playbook for Biological Emergencies, a national testing playbook we developed. It includes a set of decisions and actions for US officials to take at specific times during infectious disease emergencies to implement testing rapidly and to ensure that available testing meets clinical and public health needs. Although the United States had multiple plans at the federal level for responding to pandemic threats, US leaders were unable to quickly and efficiently operationalize those plans to deploy different types of tests during the COVID-19 pandemic in 2020-21, and again during the US mpox outbreak in 2022. The playbook fills a critical gap by providing the necessary specific and adaptable guidance for decision makers to meet this need.

COVID-19 outbreaks in residential aged care facilities: an agent-based modeling study.

Introduction: A disproportionate number of COVID-19 deaths occur in Residential Aged Care Facilities (RACFs), where better evidence is needed to target COVID-19 interventions to prevent mortality. This study used an agent-based model to assess the role of community prevalence, vaccination strategies, and non-pharmaceutical interventions (NPIs) on COVID-19 outcomes in RACFs in Victoria, Australia. Methods: The model simulated outbreaks in RACFs over time, and was calibrated to distributions for outbreak size, outbreak duration, and case fatality rate in Victorian RACFs over 2022. The number of incursions to RACFs per day were estimated to fit total deaths and diagnoses over time and community prevalence.Total infections, diagnoses, and deaths in RACFs were estimated over July 2023-June 2024 under scenarios of different: community epidemic wave assumptions (magnitude and frequency); RACF vaccination strategies (6-monthly, 12-monthly, no further vaccines); additional non-pharmaceutical interventions (10, 25, 50% efficacy); and reduction in incursions (30% or 60%). Results: Total RACF outcomes were proportional to cumulative community infections and incursion rates, suggesting potential for strategic visitation/staff policies or community-based interventions to reduce deaths. Recency of vaccination when epidemic waves occurred was critical; compared with 6-monthly boosters, 12-monthly boosters had approximately 1.2 times more deaths and no further boosters had approximately 1.6 times more deaths over July 2023-June 2024. Additional NPIs, even with only 10-25% efficacy, could lead to a 13-31% reduction in deaths in RACFs. Conclusion: Future community epidemic wave patterns are unknown but will be major drivers of outcomes in RACFs. Maintaining high coverage of recent vaccination, minimizing incursions, and increasing NPIs can have a major impact on cumulative infections and deaths.

Pertussis outbreak in neonates and young infants across Italy, January to May 2024: implications for vaccination strategies.

Since January 2024, Italy experiences a pertussis outbreak, primarily affecting neonates and unvaccinated infants at high risk of severe complications and mortality; 11 major paediatric centres noted 108 hospitalisations and three deaths by 10 May. The outbreak reflects increased circulation of Bordetella pertussis and non-adherence to immunisation recommendations during pregnancy. Public health interventions, including maternal immunisation, vaccination of infants as early as possible and post-exposure prophylaxis, are critical for reducing the burden of pertussis and preventing further mortality.

Analysis of the COVID-19 model with self-protection and isolation measures affected by the environment.

Since the global outbreak of COVID-19, the virus has continuously mutated and can survive in the air for long periods of time. This paper establishes and analyzes a model of COVID-19 with self-protection and quarantine measures affected by viruses in the environment to investigate the influence of viruses in the environment on the spread of the outbreak, as well as to develop a rational prevention and control measure to control the spread of the outbreak. The basic reproduction number was calculated and Lyapunov functions were constructed to discuss the stability of the model equilibrium points. The disease-free equilibrium point was proven to be globally asymptotically stable when $ R_0 < 1 $, and the endemic equilibrium point was globally asymptotically stable when $ R_0 > 1 $. The model was fitted using data from COVID-19 cases in Chongqing between November 1 to November 25, 2022. Based on the numerical analysis, the following conclusion was obtained: clearing the virus in the environment and strengthening the isolation measures for infected people can control the epidemic to a certain extent, but enhancing the self-protection of individuals can be more effective in reducing the risk of being infected and controlling the transmission of the epidemic, which is more conducive to the practical application.

Existence of cholera outbreak, challenges, and way forward on public health interventions to control cholera outbreak in Guraghe Zones, southern Ethiopia, 2023.

Introduction: In Ethiopia, despite major improvements seen in health service delivery system, the country continues to be significantly affected by cholera outbreaks. Cholera remains a significant public health problem among the vulnerable populations living in many resource-limited settings with poor access to safe and clean water and hygiene practices. Recurring cholera outbreaks are an indication of deprived water and sanitation conditions as well as weak health systems, contributing to the transmission and spread of the cholera infection. Objective: To assess the cholera outbreak, its challenges, and the way forward on public health interventions to solve the knowledge and health service delivery gaps related to cholera control in Guraghe Zone, Ethiopia, 2023. Methods: Active surveillance of the cholera outbreak was conducted in all kebeles and town administrative of Guraghe zone from 7/8/2023 to 30/10/2023. A total of 224 cholera cases were detected during the active surveillance method. Data obtained from Guraghe zone offices were exported to SPSS version 25 for additional analysis. The case fatality rate, incidence of the cases, and other descriptive variables were presented and described using figures and tables. Result: A total of 224 cholera cases were detected through an active surveillance system. In this study, the case fatality rate of cholera outbreak was 2.6%. To tackle the cholera outbreak, the Guraghe zone health office collaborated with other stakeholders to prepare four cholera treatment centers. The absence of OCV, inaccessible safe water, low latrine coverage, inappropriate utilization of latrines, and absence of cholera laboratory rapid diagnostics test in Guraghe Zone are barriers to tackling the outbreak. Conclusion: Ethiopia National Cholera Plan targeted eradicating cholera by 2030, 222 cholera outbreak occurred in Guraghe Zone, Ethiopia. To minimize and control cholera mortality rate oral cholera vaccinations should be employed in all areas of the region. Sustainable WASH measures should be guaranteed for the use of safe water and good hygiene practices. Early diagnosis and treatment should be initiated appropriately for those who are infected.

Prospective Spatiotemporal Cluster Detection Using SaTScan: Tutorial for Designing and Fine-Tuning a System to Detect Reportable Communicable Disease Outbreaks.

Staff at public health departments have few training materials to learn how to design and fine-tune systems to quickly detect acute, localized, community-acquired outbreaks of infectious diseases. Since 2014, the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene has analyzed reportable communicable diseases daily using SaTScan. SaTScan is a free software that analyzes data using scan statistics, which can detect increasing disease activity without a priori specification of temporal period, geographic location, or size. The Bureau of Communicable Disease's systems have quickly detected outbreaks of salmonellosis, legionellosis, shigellosis, and COVID-19. This tutorial details system design considerations, including geographic and temporal data aggregation, study period length, inclusion criteria, whether to account for population size, network location file setup to account for natural boundaries, probability model (eg, space-time permutation), day-of-week effects, minimum and maximum spatial and temporal cluster sizes, secondary cluster reporting criteria, signaling criteria, and distinguishing new clusters versus ongoing clusters with additional events. We illustrate how to support health equity by minimizing analytic exclusions of patients with reportable diseases (eg, persons experiencing homelessness who are unsheltered) and accounting for purely spatial patterns, such as adjusting nonparametrically for areas with lower access to care and testing for reportable diseases. We describe how to fine-tune the system when the detected clusters are too large to be of interest or when signals of clusters are delayed, missed, too numerous, or false. We demonstrate low-code techniques for automating analyses and interpreting results through built-in features on the user interface (eg, patient line lists, temporal graphs, and dynamic maps), which became newly available with the July 2022 release of SaTScan version 10.1. This tutorial is the first comprehensive resource for health department staff to design and maintain a reportable communicable disease outbreak detection system using SaTScan to catalyze field investigations as well as develop intuition for interpreting results and fine-tuning the system. While our practical experience is limited to monitoring certain reportable diseases in a dense, urban area, we believe that most recommendations are generalizable to other jurisdictions in the United States and internationally. Additional analytic technical support for detecting outbreaks would benefit state, tribal, local, and territorial public health departments and the populations they serve.

"It's another gay disease": an intersectional qualitative approach contextualizing the lived experiences of young gay, bisexual, and other sexual minoritized men in the United States during the mpox outbreak.

BACKGROUND: The U.S. mpox outbreak in 2022 introduced new and exacerbated existing challenges that disproportionately stigmatize gay, bisexual, and other sexual minoritized men (GBSMM). This study contextualizes the perceptions, susceptibility, and lived experiences of the mpox outbreak among GBSMM in the U.S. using an intersectional framework. METHODS: Between September 2022 to February 2023, we conducted 33 semi-structured qualitative interviews with purposively sampled GBSMM in the Northeast and the South region of the United States on various aspects related to their experience during the mpox outbreak. RESULTS: We identified four themes: (1) understanding and conceptualizations of mpox, (2) mpox vaccine availability and accessibility, (3) mpox vaccine hesitancy and mistrust, and (4) call to action and recommendations. GBSMM collectively discussed the elevated mpox stigmatization and homophobic discourse from mainstream social media and news outlets. GBSMM also discussed the lack of availability of mpox vaccines, unclear procedures to receive the vaccine, and continued mistrust in government, non-government, and other institutions of health that were complicit in anti-LGBTQ + narratives related to mpox. However, they expressed that these challenges may be addressed through more LGTBQ + representation and leveraging ways to empower these communities. CONCLUSION: GBSMM have mpox experiences that are distinct and multifaceted. Effectively addressing mpox and mitigating public health emergencies for GBSMM requires prioritizing destigmatizing communication channels and vaccine distribution strategies by centering their stories and lived experiences to advance health equity.

Predicting seasonal influenza outbreaks with regime shift-informed dynamics for improved public health preparedness.

In this study, we propose a novel approach that integrates regime-shift detection with a mechanistic model to forecast the peak times of seasonal influenza. The key benefit of this approach is its ability to detect regime shifts from non-epidemic to epidemic states, which is particularly beneficial with the year-round presence of non-zero Influenza-Like Illness (ILI) data. This integration allows for the incorporation of external factors that trigger the onset of the influenza season-factors that mechanistic models alone might not adequately capture. Applied to ILI data collected in Korea from 2005 to 2020, our method demonstrated stable peak time predictions for seasonal influenza outbreaks, particularly in years characterized by unusual onset times or epidemic magnitudes.

Machine learning approach as an early warning system to prevent foodborne Salmonella outbreaks in northwestern Italy.

Salmonellosis, one of the most common foodborne infections in Europe, is monitored by food safety surveillance programmes, resulting in the generation of extensive databases. By leveraging tree-based machine learning (ML) algorithms, we exploited data from food safety audits to predict spatiotemporal patterns of salmonellosis in northwestern Italy. Data on human cases confirmed in 2015-2018 (n = 1969) and food surveillance data collected in 2014-2018 were used to develop ML algorithms. We integrated the monthly municipal human incidence with 27 potential predictors, including the observed prevalence of Salmonella in food. We applied the tree regression, random forest and gradient boosting algorithms considering different scenarios and evaluated their predictivity in terms of the mean absolute percentage error (MAPE) and R2. Using a similar dataset from the year 2019, spatiotemporal predictions and their relative sensitivities and specificities were obtained. Random forest and gradient boosting (R2 = 0.55, MAPE = 7.5%) outperformed the tree regression algorithm (R2 = 0.42, MAPE = 8.8%). Salmonella prevalence in food; spatial features; and monitoring efforts in ready-to-eat milk, fruits and vegetables, and pig meat products contributed the most to the models' predictivity, reducing the variance by 90.5%. Conversely, the number of positive samples obtained for specific food matrices minimally influenced the predictions (2.9%). Spatiotemporal predictions for 2019 showed sensitivity and specificity levels of 46.5% (due to the lack of some infection hotspots) and 78.5%, respectively. This study demonstrates the added value of integrating data from human and veterinary health services to develop predictive models of human salmonellosis occurrence, providing early warnings useful for mitigating foodborne disease impacts on public health.

Measures for preventing norovirus outbreaks on campus in economically underdeveloped areas and countries: evidence from rural areas in Western China.

Background: The outbreak of norovirus represents a significant public health emergency within densely populated, impoverished, and underdeveloped areas and countries. Our objective is to conduct an epidemiology study of a norovirus outbreak that occurred in a kindergarten located in rural western China. We aim to raise awareness and garner increased attention towards the prevention and control of norovirus, particularly in economically underdeveloped regions. Methods: Retrospective on-site epidemiological investigation results, including data on school layout, case symptoms, onset time, disposal methods and sample testing results, questionnaire surveys, and case-control study were conducted in a kindergarten to analyze the underlying causes of the norovirus outbreak. Results: A total of 15 cases were identified, with an attack rate of 44.12% (15/34). Among them, 10 cases were diagnosed through laboratory tests, and 5 cases were diagnosed clinically. Vomiting (100%, 15/15) and diarrhea (93.33%, 14/15) were the most common symptoms in the outbreak. Case control study revealed that cases who had close contact (<1 m) with the patient's vomitus (OR = 5.500) and those who had close contact with similar patients (OR = 8.000) had significantly higher ORs compared to the control participants. The current study demonstrated that improper handling of vomitus is positively associated with norovirus outbreak. The absence of standardized disinfection protocols heightens the risk of norovirus outbreaks. Conclusion: To our knowledge, this study represents the first investigation into a norovirus outbreak in rural areas of western China. We aspire that amidst rapid economic development, a greater emphasis will be placed on the prevention and control of infectious diseases in economically underdeveloped areas and countries.