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The relative importance of maternal and horizontal transmission of small ruminant lentivirus (SRLV), the causative organism in maedi-visna, is poorly understood. Review of the literature shows that maternal transmission is inefficient, infecting only about 10-25 % of the lambs of infected ewes. Theory proves that maternal transmission alone cannot achieve the rates of transmission that would be required to start or maintain an outbreak. Maternal and horizontal transmission are additive in effect, and we use modelling to show that maternal transmission does not amplify or enhance prevalence in the presence of horizontal transmission. Taking steps to avoid maternal transmission by rearing lambs without infected maternal colostrum does have a role in producing a clean flock, but has no significance for the control of a disease outbreak if the conditions for horizontal transmission are present. Efforts to prevent disease by reducing the spread of SRLV must be focussed on minimising horizontal transmission.

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What is already known about this topic?: Since May 2022, a global outbreak of mpox has emerged in more than 100 non-endemic countries. As of December 2023, over 90,000 cases had been reported. The outbreak has predominantly affected men who have sex with men (MSM), with sexual contact identified as the principal mode of transmission. What is added by this report?: Since June 2023, China has faced an occurrence of mpox, predominantly affecting the MSM population. Approximately 90% of those affected reported engaging in homosexual behavior within 21 days prior to symptom onset, a trend that aligns with the global outbreak pattern. The prompt identification of cases, diligent tracing of close contacts, and the implementation of appropriate management strategies have successfully mitigated the spread of mpox virus in China. What are the implications for public health practice?: We propose that mpox is transmitted locally within China. Drawing from our experiences in controlling the virus spread, it is crucial to investigate and formulate effective surveillance and educational strategies. Importantly, we must encourage high-risk populations to promptly seek medical care upon the onset of symptoms.

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Introduction: Residents of long-term care facilities (LTCFs) are at high risk of morbidity and mortality due to COVID-19, especially when new variants of concern (VOC) emerge. To provide intradisciplinary data in order to tailor public health interventions during future epidemics, available epidemiologic and genomic data from Slovenian LTCFs during the initial phases of the COVID-19 pandemic was analyzed. Methods: The first part of the study included SARS-CoV-2 reverse-transcription Real-Time PCR (rtRT-PCR) positive LTCF residents, from 21 facilities with COVID-19 outbreaks occurring in October 2020. The second part of the study included SARS-CoV-2 rtRT-PCR positive LTCF residents and staff between January and April 2021, when VOC Alpha emerged in Slovenia. Next-generation sequencing (NGS) was used to acquire SARS-CoV-2 genomes, and lineage determination. In-depth phylogenetic and mutational profile analysis were performed and coupled with available field epidemiological data to assess the dynamics of SARS-CoV-2 introduction and transmission. Results: 370/498 SARS-CoV-2 positive residents as well as 558/699 SARS-CoV-2 positive residents and 301/358 staff were successfully sequenced in the first and second part of the study, respectively. In October 2020, COVID-19 outbreaks in the 21 LTCFs were caused by intra-facility transmission as well as multiple independent SARS-CoV-2 introductions. The Alpha variant was confirmed in the first LTCF resident approximately 1.5 months after the first Alpha case was identified in Slovenia. The data also showed a slower replacement of existing variants by Alpha in residents compared to staff and the general population. Discussion: Multiple SARS CoV-2 introductions as well as intra-facility spreading impacted disease transmission in Slovenian LTCFs. Timely implementation of control measures aimed at limiting new introductions while controlling in-facility transmission are of paramount importance, especially as new VOCs emerge. Sequencing, in conjunction with epidemiological data, can facilitate the determination of the need for future improvements in control measures to protect LTCF residents from COVID-19 or other respiratory infections.

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Mathematical models are useful for public health planning and response to infectious disease threats. However, different models can provide differing results, which can hamper decision making if not synthesized appropriately. To address this challenge, multi-model hubs convene independent modeling groups to generate ensembles, known to provide more accurate predictions of future outcomes. Yet, these hubs are resource intensive, and how many models are sufficient in a hub is not known. Here, we compare the benefit of predictions from multiple models in different contexts: (1) decision settings that depend on predictions of quantitative outcomes (e.g., hospital capacity planning), where assessments of the benefits of multi-model ensembles have largely focused; and (2) decisions settings that require the ranking of alternative epidemic scenarios (e.g., comparing outcomes under multiple possible interventions and biological uncertainties). We develop a mathematical framework to mimic a multi-model prediction setting, and use this framework to quantify how frequently predictions from different models agree. We further explore multi-model agreement using real-world, empirical data from 14 rounds of U.S. COVID-19 Scenario Modeling Hub projections. Our results suggest that the value of multiple models could be different in different decision contexts, and if only a few models are available, focusing on the rank of alternative epidemic scenarios could be more robust than focusing on quantitative outcomes. Although additional exploration of the sufficient number of models for different contexts is still needed, our results indicate that it may be possible to identify decision contexts where it is robust to rely on fewer models, a finding that can inform the use of modeling resources during future public health crises.

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The raccoon (Procyon lotor) variant of the rabies virus (RRV) is enzootic in the eastern United States and oral rabies vaccination (ORV) is the primary strategy to prevent and control landscape spread. Breaches of ORV management zones occasionally occur, and emergency "contingency" actions may be implemented to enhance local control. Contingency actions are an integral part of landscape-scale wildlife rabies management but can be very costly and routinely involve enhanced rabies surveillance (ERS) around the index case. We investigated two contingency actions in Ohio (2017-2019 and 2018-2021) and one in Virginia (2017-2019) using a dynamic, multi-method occupancy approach to examine relationships between specific management actions and RRV occurrence, including whether ERS was sufficient around the index case. The RRV occupancy was assessed seasonally at 100-km2 grids and we examined relationships across three spatial scales (regional management zone, RRV free regions, and local contingency areas). The location of a grid relative to the ORV management zone was the strongest predictor of RRV occupancy at the regional scale. In RRV free regions, the neighbor effect and temporal variability were most important in influencing RRV occupancy. Parenteral (hand) vaccination of raccoons was important across all three contingency action areas, but more influential in the Ohio contingency action areas where more raccoons were hand vaccinated. In the Virginia contingency action area, ORV strategies were as important in reducing RRV occupancy as a hand vaccination strategy. The management action to trap, euthanize, and test (TET) raccoons was an important method to increase ERS, yet the impacts of TET on RRV occupancy are not clear. The probability of detecting additional cases of RRV was exceptionally high (>0.95) during the season the index case occurred. The probability of detecting RRV through ERS declined in the seasons following initial TET efforts but remained higher after the contingency action compared to the ERS detection probabilities prior to index case incidence. Local RRV cases were contained within one year and eliminated within 2-3 years of each contingency action.

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Fundamental to effective Legionnaires' disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionized pathogen surveillance, but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here, we present a powerful machine learning approach that assigns the geographical source of Legionnaires' disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires' disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance-agreement with epidemiological information. Our multivariate statistical learning approach maximizes the use of genomic variation data and is thus well-suited for supporting Legionnaires' disease outbreak investigations.IMPORTANCEIdentifying the sources of Legionnaires' disease outbreaks is crucial for effective control. Current genomic methods, while useful, often fall short due to the complex ecology and population structure of Legionella pneumophila, the causative agent. Our study introduces a high-performing machine learning approach for more accurate geographical source attribution of Legionnaires' disease outbreaks. Developed using cross-validation on environmental L. pneumophila genomes, our models demonstrate excellent predictive sensitivity and specificity. Importantly, this new approach outperforms traditional methods like phylogenomic trees and core genome multi-locus sequence typing, proving more efficient at leveraging genomic variation data to infer outbreak sources. Our machine learning algorithms, harnessing both core and accessory genomic variation, offer significant promise in public health settings. By enabling rapid and precise source identification in Legionnaires' disease outbreaks, such approaches have the potential to expedite intervention efforts and curtail disease transmission.

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Objectives: The largest mumps outbreak in the United States since 2006 occurred in Arkansas during the 2016-17 school year. An additional dose (third dose) of measles-mumps-rubella vaccine (MMR3) was offered to school children. We evaluated the vaccine effectiveness (VE) of MMR3 compared with two doses of MMR for preventing mumps among school-aged children during the outbreak. Study design: A generalized linear mixed effects model was used to estimate the incremental vaccine effectiveness (VE) of a third dose of MMR compared with two doses of MMR for preventing mumps. Methods: We obtained school enrollment, immunization status and mumps case status from school registries, Arkansas's immunization registry, and Arkansas's mumps surveillance system, respectively. We included students who previously received 2 doses of MMR in schools with ≥1 mumps case after the MMR3 clinic. We used a generalized linear mixed model to estimate VE of MMR3 compared with two doses of MMR. Results: Sixteen schools with 9272 students were included in the analysis. Incremental VE of MMR3 versus a two-dose MMR regimen was 52.7% (95% confidence interval [CI]: -3.6%‒78.4%) overall and in 8 schools with high mumps transmission it was 64.0% (95% CI: 1.2%‒86.9%). MMR3 VE was higher among middle compared with elementary school students (68.5% [95% CI: -30.2%‒92.4%] vs 37.6% [95% CI: -62.5%‒76.1%]); these differences were not statistically significant. Conclusion: Our findings suggest MMR3 provided additional protection from mumps compared with two MMR doses in elementary and middle school settings during a mumps outbreak.

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Background: Numerous individual and organizational factors can influence the spread of SARS-CoV-2 infection in Long Term Care Facilities (LTCFs). A range of outbreak control measures are still implemented in most facilities involving administrations, staff, residents and their families. This study aims to evaluate which measure could influence the transmission of SARS-CoV-2 infection among residents during the period March 2021-June 2022. Methods: We enrolled 3,272 residents aged ≥60 years. The outbreak control measures adopted to prevent or manage the infection included entry regulations, contact-regulating procedures, and virological surveillance of residents and staff. The association between LTCFs' and participants' characteristics with new cases of COVID-19 infections was analyzed using multilevel logistic regression models. Results: In 33.8% of the facilities 261 cases of SARS-CoV-2 infection were reported. Among participant characteristics, gender and age were not associated with SARS-CoV-2 infection, while having received the vaccine booster dose was protective against infection [Odds Ratio (OR) = 0.34, 95% Confidence Interval (CI) 0.12-0.99, p = 0.048]. In addition, the implementation of protected areas for family visits was associated with a significant reduction of the probability of infections (OR = 0.18, 95% CI 0.03-0.98, p = 0.047). Overall, about 66% of the variability in the probability of SARS-CoV-2 infection during the observational period may be due to facility structure characteristics and 34% to the participant characteristics. Conclusions: These data showed that vaccination booster doses and family visit restriction-control are still needed to make the LTCFs safer against SARS-CoV-2 infection.

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BackgroundMeningococcus (Neisseria meningitidis) is the causative bacteria of invasive meningococcal disease (IMD), a major cause of meningitis and sepsis. In 2015-16, an outbreak caused by serogroup C meningococci (MenC), belonging to the hyperinvasive strain ST-11(cc-11), resulted in 62 IMD cases in the region of Tuscany, Italy.AimWe aimed to estimate the key outbreak parameters and assess the impact of interventions used in the outbreak response.MethodsWe developed a susceptible-carrier-susceptible individual-based model of MenC transmission, accounting for transmission in households, schools, discos/clubs and the general community, which was informed by detailed data on the 2015-16 outbreak (derived from epidemiological investigations) and on the implemented control measures.ResultsThe outbreak reproduction number (Re) was 1.35 (95% prediction interval: 1.13-1.47) and the IMD probability was 4.6 for every 1,000 new MenC carriage episodes (95% confidence interval: 1.8-12.2). The interventions, i.e. chemoprophylaxis and vaccination of close contacts of IMD cases as well as age-targeted vaccination, were effective in reducing Re and ending the outbreak. Case-based interventions (including ring vaccination) alone would have been insufficient to achieve outbreak control. The definition of age groups to prioritise vaccination had a critical impact on the effectiveness and efficiency of control measures.ConclusionsOur findings suggest that there are no effective alternatives to widespread reactive vaccination during outbreaks of highly transmissible MenC strains. Age-targeted campaigns can increase the effectiveness of vaccination campaigns. These results can be instrumental to define effective guidelines for the control of future meningococcal outbreaks caused by hypervirulent strains.

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Contact tracing is commonly recommended to control outbreaks of COVID-19, but its effectiveness is unclear. Following PRISMA guidelines, we searched four databases using a range of terms related to contact tracing effectiveness for COVID-19. We found 343 papers; 32 were included. All were observational or modelling studies. Observational studies (n = 14) provided consistent, very-low certainty evidence that contact tracing (alone or in combination with other interventions) was associated with better control of COVID-19 (e.g. in Hong Kong, only 1084 cases and four deaths were recorded in the first 4.5 months of the pandemic). Modelling studies (n = 18) provided consistent, high-certainty evidence that under assumptions of prompt and thorough tracing with effective quarantines, contact tracing could stop the spread of COVID-19 (e.g. by reducing the reproduction number from 2.2 to 0.57). A cautious interpretation indicates that to stop the spread of COVID-19, public health practitioners have 2-3 days from the time a new case develops symptoms to isolate the case and quarantine at least 80% of its contacts.

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Background: Mitigating the risk of nosocomial infection is one of the core functions of healthcare managers in hospital environments. This study aimed to describe the COVID-19 outbreak response in a tertiary healthcare facility in Nigeria. Methods: A qualitative cross-sectional study was conducted among representatives of Heads of Infection Control Committees and units, the Accident and Emergency unit, Family Medicine unit, and Private Suites on the COVID-19 outbreak response at the University College Hospital, Ibadan, Nigeria. Data were analyzed using Colaizzi's phenomenological method. Results: Overall, seven (six physicians and one nurse) HCWs were interviewed; six (71.4%) males and two (28.6%) females. The average age of the key informants was 45 ± 4.73 years. Four themes were identified. Theme one "Essentials of screening protocol and screening area" described the development of screening protocol, and dedication of a triage area. Theme two "Infection prevention and control within consultation premises" detailed adequate spacing; hand hygiene, use of personal protective equipment; environmental sanitation; and waste management. Theme three "Mounting up surveillance in the response activity" specified communication with the Disease Surveillance Unit; and surveillance activities. Theme four "Training and psychosocial support for staff " described staff training, and provision of psychosocial care to infected staff. Conclusion: The COVID-19 outbreak measures implemented by the management of the University College Hospital, Ibadan were aimed at ensuring that the hospital does not get overwhelmed by the surge in COVID-19 cases. In order to improve outbreak response in hospital settings, it is important to undertake training, modify hospital practices, and evaluate implemented measures.

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Global change in the Anthropocene has modified the environment of almost any species on earth, be it through climate change, habitat modifications, pollution, human intervention in the form of mass drug administration (MDA), or vaccination. This can have far-reaching consequences on all organisational levels of life, including eco-physiological stress at the cell and organism level, individual fitness and behaviour, population viability, species interactions and biodiversity. Host-parasite interactions often require highly adapted strategies by the parasite to survive and reproduce within the host environment and ensure efficient transmission among hosts. Yet, our understanding of the system-level outcomes of the intricate interplay of within host survival and among host parasite spread is in its infancy. We shed light on how global change affects host-parasite interactions at different organisational levels and address challenges and opportunities to work towards better-informed management of parasite control. We argue that global change affects host-parasite interactions in wildlife inhabiting natural environments rather differently than in humans and invasive species that benefit from anthropogenic environments as habitat and more deliberate rather than erratic exposure to therapeutic drugs and other control efforts.

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BACKGROUND: In an unparalleled global response, during the COVID-19 pandemic, 90 countries asked 3.9 billion people to stay home. Yet other countries avoided lockdowns and focused on other strategies, like contact tracing. How effective and cost-effective are these strategies? We aimed to provide a comprehensive summary of the evidence on past pandemic controls, with a focus on cost-effectiveness. METHODS: Following PRISMA guidelines, MEDLINE (1946 to April week 2, 2020) and EMBASE (1974 to April 17, 2020) were searched using a range of terms related to pandemic control. Articles reporting on the effectiveness or cost-effectiveness of at least one intervention were included. RESULTS: We found 1653 papers; 62 were included. The effectiveness of hand-washing and face masks was supported by randomized trials. These measures were highly cost-effective. For other interventions, only observational and modelling studies were found. They suggested that (1) the most cost-effective interventions are swift contact tracing and case isolation, surveillance networks, protective equipment for healthcare workers, and early vaccination (when available); (2) home quarantines and stockpiling antivirals are less cost-effective; (3) social distancing measures like workplace and school closures are effective but costly, making them the least cost-effective options; (4) combinations are more cost-effective than single interventions; and (5) interventions are more cost-effective when adopted early. For 2009 H1N1 influenza, contact tracing was estimated to be 4363 times more cost-effective than school closure ($2260 vs. $9,860,000 per death prevented). CONCLUSIONS AND CONTRIBUTIONS: For COVID-19, a cautious interpretation suggests that (1) workplace and school closures are effective but costly, especially when adopted late, and (2) scaling up as early as possible a combination of interventions that includes hand-washing, face masks, ample protective equipment for healthcare workers, and swift contact tracing and case isolation is likely to be the most cost-effective strategy.

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Background: Rubella, although a fairly innocuous disease, is a known cause of severe birth defects in newborn. With number of women in uniform on the rise and they being assigned instructional and medical care duties, adult rubella outbreak in a training centre as in this study poses grave threat to them; besides, having disruption potential for their training. Methods: This study was conducted at an Airmen Training Centre of the Indian Air Force having more than 2500 recruits, in five squadrons. All cases of fever with rash and/or lymphadenopathy were included in the study. The demographic, epidemiological and clinical data of all the cases were analyzed and medical records reviewed. Results: A total of 31 male recruits reported over 5 days. Among those, 21 cases were from a single squadron to which the index belonged. Twelve women officers were doing instructional duties at the time of outbreak though none became infected. Fever with a rash (90.32%) was the commonest presentation, and lymphadenopathy (64.51%) was the most common sign. Attack rate (AR) with-in the squadron most affected was 4.18%, with an overall AR of 1.23%. The case fatality rate of the disease was nil. Conclusion: Till the fully immunized cohort of young recruits start getting enrolled, it will be prudent to introduce rubella vaccine to limit the loss of vital training man-hours and prevent the possibility of congenital rubella syndrome in the women instructors and medical caregivers, working in the line of their duty.

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Epidemic outbreak control often involves a spatially explicit treatment area (quarantine, inoculation, ring cull) that covers the outbreak area and adjacent regions where hosts are thought to be latently infected. Emphasis on space however neglects the influence of treatment timing on outbreak control. We conducted field and in silico experiments with wheat stripe rust (WSR), a long-distance dispersed plant disease, to understand interactions between treatment timing and area interact to suppress an outbreak. Full-factorial field experiments with three different ring culls (outbreak area only to a 25-fold increase in treatment area) at three different disease control timings (1.125, 1.25, and 1.5 latent periods after initial disease expression) indicated that earlier treatment timing had a conspicuously greater suppressive effect than the area treated. Disease spread computer simulations over a broad range of influential epidemic parameter values (R0, outbreak disease prevalence, epidemic duration) suggested that potentially unrealistically large increases in treatment area would be required to compensate for even small delays in treatment timing. Although disease surveillance programs are costly, our results suggest that treatments early in an epidemic disease outbreak require smaller areas to be effective, which may ultimately compensate for the upfront costs of proactive disease surveillance programs.

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Background: Administration of measles virus (MV)-specific IgG as post-exposure prophylaxis (PEP) is known to effectively prevent measles. Since the introduction of active immunization against measles, the levels of MV-specific IgG antibodies in the population have dropped. Therefore, the concentration of MV-specific antibodies in immunoglobulin products derived from human plasma donors has declined as the proportion of vaccinated donors has increased. Literature on the effectiveness of PEP with current available immunoglobulins is limited. Here we examine the effectiveness of 400 mg/kg intravenous immunoglobulin (IVIG) (IgVena®, Kendrion) as PEP in infants during a measles outbreak in Austria, 2019. Methods: After exposure to a highly contagious measles patient, identified infants were evaluated for eligibility for IVIG PEP. Infants were tested for measles maternal antibodies, if the result was expected to be available within 72 h after exposure. IVIG was administered to eligible infants with negative maternal IgG antibody levels (n = 11), infants with protective levels but result beyond 72 h (n = 2) and infants not tested for maternal IgG antibodies (n = 52). Telephone enquiries were made asking for measles infection. Effectiveness was calculated using exact logistic regression. Samples of four out of seven used IVIG batches were tested for MV-neutralizing antibody capacity. Results: In 63 (96.9%) of 65 infants PEP with IVIG was administered. The parents of two infants declined IVIG PEP. None of the infants with IVIG PEP got measles or symptoms suggestive for measles, but both infants who did not receive PEP were infected. Effectiveness of IVIG PEP was calculated to be 99.3% (CI 95%: 88.7-100%). No serious adverse event of IVIG treatment was observed. The investigation on MV-neutralizing antibody capacity showed a geometric mean titer ranging from 10.0 to 12.7 IU/ml, resulting in a 1.57-2.26-fold higher concentration than postulated as minimum level for immunity. Conclusions: Our findings suggest that the used IVIG preparation provided an at least non-inferior protection rate compared to IVIG preparations derived from donors before the global introduction of standard active immunization against measles.

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BackgroundIn the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.AimWe applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.MethodsWe investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.ResultsWe identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.ConclusionsEarly spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.

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The first indigenous outbreak of chikungunya in Taiwan occurred in New Taipei City, northern Taiwan, from August to October 2019. This study identified important containment strategies for controlling the outbreak. The outbreak investigation and ovitrap data were collected from the Department of Health, New Taipei City Government. A geographic information system (GIS) was applied for spatial analysis, and descriptive statistics were used to compute the demographic features and medical visits of confirmed cases. There were 19 residents infected during the outbreak. The source of this outbreak was a mountain trail with abundant Aedes albopictus. The atypical symptoms and lack of a rapid test led to multiple clinical visits by the patients (mean: 2.79; standard deviation: 1.65). The clinical symptoms of chikungunya are very similar to those of dengue fever. We noted that only eight patients were polymerase chain reaction (PCR)-positive in their first blood collection, and an average of 3.13 days between illness onset and PCR-positive results. The improved laboratory panel test, targeted and rapid insecticide spraying at the households and their communities, strict closure of the mountain trail, and ovitrap surveillance for evaluating intervention were important approaches to rapidly contain the outbreak.

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Case isolation and contact tracing are two essential parts of control measures to prevent the spread of COVID-19, however, additional interventions, such as mask wearing, are required. Taiwan successfully contained local COVID-19 transmission after the initial imported cases in the country in early 2020 after applying the above-mentioned interventions. In order to explain the containment of the disease spread in Taiwan and understand the efficiency of different non-pharmaceutical interventions, a mathematical model has been developed. A stochastic model was implemented in order to estimate the effectiveness of mask wearing together with case isolation and contact tracing. We investigated different approaches towards mask usage, estimated the effect of the interventions on the basic reproduction number (R0), and simulated the possibility of controlling the outbreak. With the assumption that non-medical and medical masks have 20% and 50% efficiency, respectively, case isolation works on 100%, 70% of all people wear medical masks, and R0 = 2.5, there is almost 80% probability of outbreak control with 60% contact tracing, whereas for non-medical masks the highest probability is only about 20%. With a large proportion of infectiousness before the onset of symptoms (40%) and the presence of asymptomatic cases, the investigated interventions (isolation of cases, contact tracing, and mask wearing by all people), implemented on a high level, can help to control the disease spread. Superspreading events have also been included in our model in order to estimate their impact on the outbreak and to understand how restrictions on gathering and social distancing can help to control the outbreak. The obtained quantitative results are in agreement with the empirical COVID-19 data in Taiwan.