Mouse models of lung-specific SARS-CoV-2 infection with moderate pathological traits.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has been a global health concern since 2019. The viral spike protein infects the host by binding to angiotensin-converting enzyme 2 (ACE2) expressed on the cell surface, which is then processed by type II transmembrane serine protease. However, ACE2 does not react to SARS-CoV-2 in inbred wild-type mice, which poses a challenge for preclinical research with animal models, necessitating a human ACE2 (hACE2)-expressing transgenic mouse model. Cytokeratin 18 (K18) promoter-derived hACE2 transgenic mice [B6.Cg-Tg(K18-ACE2)2Prlmn/J] are widely used for research on SARS-CoV-1, MERS-CoV, and SARS-CoV-2. However, SARS-CoV-2 infection is lethal at ≥105 PFU and SARS-CoV-2 target cells are limited to type-1 alveolar pneumocytes in K18-hACE2 mice, making this model incompatible with infections in the human lung. Hence, we developed lung-specific SARS-CoV-2 infection mouse models with surfactant protein B (SFTPB) and secretoglobin family 1a member 1 (Scgb1a1) promoters. After inoculation of 105 PFU of SARS-CoV-2 to the K18-hACE2, SFTPB-hACE2, and SCGB1A1-hACE2 models, the peak viral titer was detected at 2 days post-infection and then gradually decreased. In K18-hACE2 mice, the body temperature decreased by approximately 10°C, body weight decreased by over 20%, and the survival rate was reduced. However, SFTPB-hACE2 and SCGB1A1-hACE2 mice showed minimal clinical signs after infection. The virus targeted type I pneumocytes in K18-hACE2 mice; type II pneumocytes in SFTPB-hACE2 mice; and club, goblet, and ciliated cells in SCGB1A1-hACE2 mice. A time-dependent increase in severe lung lesions was detected in K18-hACE2 mice, whereas mild lesions developed in SFTPB-hACE2 and SCGB1A1-hACE2 mice. Spleen, small intestine, and brain lesions developed in K18-hACE2 mice but not in SFTPB-hACE2 and SCGB1A1-hACE2 mice. These newly developed SFTPB-hACE2 and SCGB1A1-hACE2 mice should prove useful to expand research on hACE2-mediated respiratory viruses.

Comparison of the pathogenesis of SARS-CoV-2 infection in K18-hACE2 mouse and Syrian golden hamster models.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, causes life-threatening disease. This novel coronavirus enters host cells via the respiratory tract, promoting the formation of severe pulmonary lesions and systemic disease. Few animal models can simulate the clinical signs and pathology of COVID-19 patients. Diverse preclinical studies using K18-hACE2 mice and Syrian golden hamsters, which are highly permissive to SARS-CoV-2 in the respiratory tract, are emerging; however, the systemic pathogenesis and cellular tropism of these models remain obscure. We intranasally infected K18-hACE2 mice and Syrian golden hamsters with SARS-CoV-2, and compared the clinical features, pathogenesis, cellular tropism and infiltrated immune-cell subsets. In K18-hACE2 mice, SARS-CoV-2 persistently replicated in alveolar cells and caused pulmonary and extrapulmonary disease, resulting in fatal outcomes. Conversely, in Syrian golden hamsters, transient SARS-CoV-2 infection in bronchial cells caused reversible pulmonary disease, without mortality. Our findings provide comprehensive insights into the pathogenic spectrum of COVID-19 using preclinical models.

Risk Assessment of Importation and Local Transmission of COVID-19 in South Korea: Statistical Modeling Approach.

BACKGROUND: Despite recent achievements in vaccines, antiviral drugs, and medical infrastructure, the emergence of COVID-19 has posed a serious threat to humans worldwide. Most countries are well connected on a global scale, making it nearly impossible to implement perfect and prompt mitigation strategies for infectious disease outbreaks. In particular, due to the explosive growth of international travel, the complex network of human mobility enabled the rapid spread of COVID-19 globally. OBJECTIVE: South Korea was one of the earliest countries to be affected by COVID-19. In the absence of vaccines and treatments, South Korea has implemented and maintained stringent interventions, such as large-scale epidemiological investigations, rapid diagnosis, social distancing, and prompt clinical classification of severely ill patients with appropriate medical measures. In particular, South Korea has implemented effective airport screenings and quarantine measures. In this study, we aimed to assess the country-specific importation risk of COVID-19 and investigate its impact on the local transmission of COVID-19. METHODS: The country-specific importation risk of COVID-19 in South Korea was assessed. We investigated the relationships between country-specific imported cases, passenger numbers, and the severity of country-specific COVID-19 prevalence from January to October 2020. We assessed the country-specific risk by incorporating country-specific information. A renewal mathematical model was employed, considering both imported and local cases of COVID-19 in South Korea. Furthermore, we estimated the basic and effective reproduction numbers. RESULTS: The risk of importation from China was highest between January and February 2020, while that from North America (the United States and Canada) was high from April to October 2020. The R0 was estimated at 1.87 (95% CI 1.47-2.34), using the rate of α=0.07 for secondary transmission caused by imported cases. The Rt was estimated in South Korea and in both Seoul and Gyeonggi. CONCLUSIONS: A statistical model accounting for imported and locally transmitted cases was employed to estimate R0 and Rt. Our results indicated that the prompt implementation of airport screening measures (contact tracing with case isolation and quarantine) successfully reduced local transmission caused by imported cases despite passengers arriving from high-risk countries throughout the year. Moreover, various mitigation interventions, including social distancing and travel restrictions within South Korea, have been effectively implemented to reduce the spread of local cases in South Korea.

Establishment of multicenter COVID-19 therapeutics preclinical test system in Republic of Korea.

Throughout the recent COVID-19 pandemic, South Korea led national efforts to develop vaccines and therapeutics for SARS-CoV-2. The project proceeded as follows: 1) evaluation system setup (including Animal Biosafety Level 3 (ABSL3) facility alliance, standardized nonclinical evaluation protocol, and laboratory information management system), 2) application (including committee review and selection), and 3) evaluation (including expert judgment and reporting). After receiving 101 applications, the selection committee reviewed pharmacokinetics, toxicity, and efficacy data and selected 32 final candidates. In the nonclinical efficacy test, we used golden Syrian hamsters and human angiotensin-converting enzyme 2 transgenic mice under a cytokeratin 18 promoter to evaluate mortality, clinical signs, body weight, viral titer, neutralizing antibody presence, and histopathology. These data indicated eight new drugs and one repositioned drug having significant efficacy for COVID-19. Three vaccine and four antiviral drugs exerted significant protective activities against SARS-CoV-2 pathogenesis. Additionally, two anti-inflammatory drugs showed therapeutic effects on lung lesions and weight loss through their mechanism of action but did not affect viral replication. Along with systematic verification of COVID-19 animal models through large-scale studies, our findings suggest that ABSL3 multicenter alliance and nonclinical evaluation protocol standardization can promote reliable efficacy testing against COVID-19, thus expediting medical product development.

Corrigendum: Mouse models of lung-specific SARS-CoV-2 infection with moderate pathological traits.

[This corrects the article DOI: 10.3389/fimmu.2022.1055811.].

Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.

South Korea implemented interventions to curb the spread of the novel coronavirus disease 2019 (COVID-19) pandemic with discovery of the first case in early 2020. Mathematical modeling designed to reflect the dynamics of disease transmission has been shown to be an important tool for responding to COVID-19. This study aimed to review publications on the structure, method, and role of mathematical models focusing on COVID-19 transmission dynamics in Korea. In total, 42 papers published between August 7, 2020 and August 21, 2022 were studied and reviewed. This study highlights the construction and utilization of mathematical models to help craft strategies for predicting the course of an epidemic and evaluating the effectiveness of control strategies. Despite the limitations caused by a lack of available epidemiological and surveillance data, modeling studies could contribute to providing scientific evidence for policymaking by simulating various scenarios.

Mouse models of lung-specific SARS-CoV-2 infection with moderate pathological traits

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has been a global health concern since 2019. The viral spike protein infects the host by binding to angiotensin-converting enzyme 2 (ACE2) expressed on the cell surface, which is then processed by type II transmembrane serine protease. However, ACE2 does not react to SARS-CoV-2 in inbred wild-type mice, which poses a challenge for preclinical research with animal models, necessitating a human ACE2 (hACE2)-expressing transgenic mouse model. Cytokeratin 18 (K18) promoter-derived hACE2 transgenic mice [B6.Cg-Tg(K18-ACE2)2Prlmn/J] are widely used for research on SARS-CoV-1, MERS-CoV, and SARS-CoV-2. However, SARS-CoV-2 infection is lethal at ≥105 PFU and SARS-CoV-2 target cells are limited to type-1 alveolar pneumocytes in K18-hACE2 mice, making this model incompatible with infections in the human lung. Hence, we developed lung-specific SARS-CoV-2 infection mouse models with surfactant protein B (SFTPB) and secretoglobin family 1a member 1 (Scgb1a1) promoters. After inoculation of 105 PFU of SARS-CoV-2 to the K18-hACE2, SFTPB-hACE2, and SCGB1A1-hACE2 models, the peak viral titer was detected at 2 days post-infection and then gradually decreased. In K18-hACE2 mice, the body temperature decreased by approximately 10°C, body weight decreased by over 20%, and the survival rate was reduced. However, SFTPB-hACE2 and SCGB1A1-hACE2 mice showed minimal clinical signs after infection. The virus targeted type I pneumocytes in K18-hACE2 mice;type II pneumocytes in SFTPB-hACE2 mice;and club, goblet, and ciliated cells in SCGB1A1-hACE2 mice. A time-dependent increase in severe lung lesions was detected in K18-hACE2 mice, whereas mild lesions developed in SFTPB-hACE2 and SCGB1A1-hACE2 mice. Spleen, small intestine, and brain lesions developed in K18-hACE2 mice but not in SFTPB-hACE2 and SCGB1A1-hACE2 mice. These newly developed SFTPB-hACE2 and SCGB1A1-hACE2 mice should prove useful to expand research on hACE2-mediated respiratory viruses.

Temporal Transcriptome Analysis of SARS-CoV-2-Infected Lung and Spleen in Human ACE2-Transgenic Mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and potentially fatal virus. So far, most comprehensive analyses encompassing clinical and transcriptional manifestation have concentrated on the lungs. Here, we confirmed evident signs of viral infection in the lungs and spleen of SARS-CoV-2-infected K18-hACE2 mice, which replicate the phenotype and infection symptoms in hospitalized humans. Seven days post viral detection in organs, infected mice showed decreased vital signs, leading to death. Bronchopneumonia due to infiltration of leukocytes in the lungs and reduction in the spleen lymphocyte region were observed. Transcriptome profiling implicated the meticulous regulation of distress and recovery from cytokine-mediated immunity by distinct immune cell types in a time-dependent manner. In lungs, the chemokine-driven response to viral invasion was highly elevated at 2 days post infection (dpi). In late infection, diseased lungs, post the innate immune process, showed recovery signs. The spleen established an even more immediate line of defense than the lungs, and the cytokine expression profile dropped at 7 dpi. At 5 dpi, spleen samples diverged into two distinct groups with different transcriptome profile and pathophysiology. Inhibition of consecutive host cell viral entry and massive immunoglobulin production and proteolysis inhibition seemed that one group endeavored to survive, while the other group struggled with developmental regeneration against consistent viral intrusion through the replication cycle. Our results may contribute to improved understanding of the longitudinal response to viral infection and development of potential therapeutics for hospitalized patients affected by SARS-CoV-2.

Modeling Incorporating the Severity-Reducing Long-term Immunity: Higher Viral Transmission Paradoxically Reduces Severe COVID-19 During Endemic Transition.

Natural infection with severe acute respiratory syndrome-coronavirus-2 or vaccination induces virus-specific immunity protecting hosts from infection and severe disease. While the infection-preventing immunity gradually declines, the severity-reducing immunity is relatively well preserved. Here, based on the different longevity of these distinct immunities, we develop a mathematical model to estimate courses of endemic transition of coronavirus disease 2019 (COVID-19). Our analysis demonstrates that high viral transmission unexpectedly reduces the rates of progression to severe COVID-19 during the course of endemic transition despite increased numbers of infection cases. Our study also shows that high viral transmission amongst populations with high vaccination coverages paradoxically accelerates the endemic transition of COVID-19 with reduced numbers of severe cases. These results provide critical insights for driving public health policies in the era of 'living with COVID-19.'

Laboratory information management system for COVID-19 non-clinical efficacy trial data.

BACKGROUND: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. RESULTS: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. CONCLUSIONS: This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.

Forecasting COVID-19 cases by assessing control-intervention effects in Republic of Korea: a statistical modeling approach

The Coronavirus disease of 2019 (COVID-19) is an ongoing public health concern worldwide. COVID-19 infections continue to occur and thus, it is important to assess the effects of various public health measures. This study aims to forecast COVID-19 cases by geographical area in Korea, based on the effects of different control-intervention intensities (CII). Methods involved estimating the effective reproduction number (Rt) by Korean geographical area using the SEIHR model, and the instantaneous reproduction number using statistical model, comparing the epidemic curves and high-, intermediate-, and low-intensity control interventions. Here, short-term four-week forecasts by geographical area were conducted. The mean of delayed instantaneous reproduction number was estimated at 1.36, 1.03, and 0.93 for the low-, intermediate-, and high-intensity control interventions, respectively, in the capital area of Korea from July 16, 2020, to March 4, 2021. The COVID-19 cases were forecasted with an accuracy rate of 11.28%, 13.62%, and 20.19% MAPE in Korea, including both the capital and non-capital areas. High-intensity control measures significantly reduced the reproduction number to be less than one. The proposed model forecasted COVID-19 transmission dynamics with good accuracy and interpretability. High-intensity control intervention, active case detection, and isolation efforts should be maintained to control the pandemic.

Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea.

The COVID-19 pandemic has been spreading worldwide with more than 246 million confirmed cases and 5 million deaths across more than 200 countries as of October 2021. There have been multiple disease clusters, and transmission in South Korea continues. We aim to analyze COVID-19 clusters in Seoul from 4 March to 4 December 2020. A branching process model is employed to investigate the strength and heterogeneity of cluster-induced transmissions. We estimate the cluster-specific effective reproduction number Reff and the dispersion parameter κ using a maximum likelihood method. We also compute Rm as the mean secondary daily cases during the infection period with a cluster size m. As a result, a total of 61 clusters with 3088 cases are elucidated. The clusters are categorized into six groups, including religious groups, convalescent homes, and hospitals. The values of Reff and κ of all clusters are estimated to be 2.26 (95% CI: 2.02-2.53) and 0.20 (95% CI: 0.14-0.28), respectively. This indicates strong evidence for the occurrence of superspreading events in Seoul. The religious groups cluster has the largest value of Reff among all clusters, followed by workplaces, schools, and convalescent home clusters. Our results allow us to infer the presence or absence of superspreading events and to understand the cluster-specific characteristics of COVID-19 outbreaks. Therefore, more effective suppression strategies can be implemented to halt the ongoing or future cluster transmissions caused by small and sporadic clusters as well as large superspreading events.

The age-standardized incidence, mortality, and case fatality rates of COVID-19 in 79 countries: a cross-sectional comparison and their correlations with associated factors.

OBJECTIVES: During the coronavirus disease 2019 (COVID-19) pandemic, crude incidence and mortality rates have been widely reported; however, age-standardized rates are more suitable for comparisons. In this study, we estimated and compared the age-standardized incidence, mortality, and case fatality rates (CFRs) among countries and investigated the relationship between these rates and factors associated with healthcare resources: gross domestic product per capita, number of hospital beds per population, and number of doctors per population. METHODS: The incidence, mortality, and CFRs of 79 countries were age-standardized using the World Health Organization standard population. The rates for persons 60 years or older were also calculated. The relationships among the rates were analysed using trend lines and coefficients of determination (R2). Pearson correlation coefficients between the rates and the healthcare resource-related factors were calculated. RESULTS: The countries with the highest age-standardized incidence, mortality, and CFRs were Czechia (14,253 cases/100,000), Mexico (182 deaths/100,000), and Mexico (6.7%), respectively. The R2 between the incidence and mortality rates was 0.852 for all ages and 0.945 for those 60 years or older. The healthcare resources-related factors were associated positively with incidence rates and negatively with CFRs, with weaker correlations among the elderly. CONCLUSIONS: Compared to age-standardized rates, crude rates showed greater variation among countries. Medical resources may be important in preventing COVID-19-related deaths; however, considering the small variation in fatality among the elderly, preventive measures such as vaccination are more important, especially for the elderly population, to minimize the mortality rates.

Rapid transmission of coronavirus disease 2019 within a religious sect in South Korea: A mathematical modeling study.

Rapid transmission of coronavirus disease 2019 (COVID-19) was observed in the Shincheonji Church of Jesus, a religious sect in South Korea. The index case was confirmed on February 18, 2020 in Daegu City, and within two weeks, 3081 connected cases were identified. Doubling times during these initial stages (i.e., February 18 - March 2) of the outbreak were less than 2 days. A stochastic model fitted to the time series of confirmed cases suggests that the basic reproduction number (R0) of COVID-19 was 8.5 [95% credible interval (CrI): 6.3, 10.9] among the church members, whereas (R0 = 1.9 [95% CrI: 0.4, 4.4]) in the rest of the population of Daegu City. The model also suggests that there were already 4 [95% CrI: 2, 11] undetected cases of COVID-19 on February 7 when the index case reportedly presented symptoms. The Shincheonji Church cluster is likely to be emblematic of other outbreak-prone populations where R0 of COVID-19 is higher. Understanding and subsequently limiting the risk of transmission in such high-risk places is key to effective control.

Public responses to COVID-19 case disclosure and their spatial implications.

We study how the public changes their mobility and retail spending patterns as precautionary responses to the disclosed location of COVID-19 cases. To look into the underlying mechanisms, we investigate how such change varies spatially and whether there is any spatial spillover or substitution. We use the daily data of cell phone-based mobility and credit card transactions between February 10 and May 31 in both 2019 and 2020 in Seoul, South Korea, and employ the empirical approach analyzing the year-over-year percent change for the mobility and consumption outcomes. Results report that one additional COVID-19 case within the last 14 days decreased nonresident inflow and retail spending by 0.40 and 0.65 percentage points, respectively. Then, we also find evidence of spatial heterogeneity: the mobility and retail performances of neighborhoods with higher residential population density were more resilient to COVID-19 case information while neighborhoods with higher levels of land-use diversity and retail agglomeration experienced a greater localized demand shock. This heterogeneity is not negligible. For example, one additional COVID-19 case in neighborhoods in the bottom 20% for population density led to a decline of 1.2 percentage points in retail spending, while other neighborhoods experienced a less negative impact. Finally, we find a significant spatial spillover effect of disclosed COVID-19 information instead of spatial substitution. One additional COVID-19 case in geographically adjacent areas within the last 14 days reduced nonresident inflow and retail spending in the subject neighborhood by 0.06 and 0.09 percentage points, respectively.

Subcritical Transmission in the Early Stage of COVID-19 in Korea.

While the coronavirus disease 2019 (COVID-19) outbreak has been ongoing in Korea since January 2020, there were limited transmissions during the early stages of the outbreak. In the present study, we aimed to provide a statistical characterization of COVID-19 transmissions that led to this small outbreak. We collated the individual data of the first 28 confirmed cases reported from 20 January to 10 February 2020. We estimated key epidemiological parameters such as reporting delay (i.e., time from symptom onset to confirmation), incubation period, and serial interval by fitting probability distributions to the data based on the maximum likelihood estimation. We also estimated the basic reproduction number (R0) using the renewal equation, which allows for the transmissibility to differ between imported and locally transmitted cases. There were 16 imported and 12 locally transmitted cases, and secondary transmissions per case were higher for the imported cases than the locally transmitted cases (nine vs. three cases). The mean reporting delays were estimated to be 6.76 days (95% CI: 4.53, 9.28) and 2.57 days (95% CI: 1.57, 4.23) for imported and locally transmitted cases, respectively. The mean incubation period was estimated to be 5.53 days (95% CI: 3.98, 8.09) and was shorter than the mean serial interval of 6.45 days (95% CI: 4.32, 9.65). The R0 was estimated to be 0.40 (95% CI: 0.16, 0.99), accounting for the local and imported cases. The fewer secondary cases and shorter reporting delays for the locally transmitted cases suggest that contact tracing of imported cases was effective at reducing further transmissions, which helped to keep R0 below one and the overall transmissions small.

Assessment of Social Distancing for Controlling COVID-19 in Korea: An Age-Structured Modeling Approach.

The outbreak of the novel coronavirus disease 2019 (COVID-19) occurred all over the world between 2019 and 2020. The first case of COVID-19 was reported in December 2019 in Wuhan, China. Since then, there have been more than 21 million incidences and 761 thousand casualties worldwide as of 16 August 2020. One of the epidemiological characteristics of COVID-19 is that its symptoms and fatality rates vary with the ages of the infected individuals. This study aims at assessing the impact of social distancing on the reduction of COVID-19 infected cases by constructing a mathematical model and using epidemiological data of incidences in Korea. We developed an age-structured mathematical model for describing the age-dependent dynamics of the spread of COVID-19 in Korea. We estimated the model parameters and computed the reproduction number using the actual epidemiological data reported from 1 February to 15 June 2020. We then divided the data into seven distinct periods depending on the intensity of social distancing implemented by the Korean government. By using a contact matrix to describe the contact patterns between ages, we investigated the potential effect of social distancing under various scenarios. We discovered that when the intensity of social distancing is reduced, the number of COVID-19 cases increases; the number of incidences among the age groups of people 60 and above increases significantly more than that of the age groups below the age of 60. This significant increase among the elderly groups poses a severe threat to public health because the incidence of severe cases and fatality rates of the elderly group are much higher than those of the younger groups. Therefore, it is necessary to maintain strict social distancing rules to reduce infected cases.

Epidemiological characteristics of and containment measures for COVID-19 in Busan, Korea.

OBJECTIVES: To describe and evaluate epidemiological investigation results and containment measures implemented in Busan, where 108 cases were confirmed with coronavirus disease 2019 (COVID-19) between February 21, 2020 and March 24, 2020. METHODS: Any individual who tested positive for COVID-19 was classified as a confirmed case. Measures were taken to identify the source of infection and trace and quarantine contacts. Serial intervals were estimated and the effective reproduction number was computed. RESULTS: Of the total 18,303 COVID-19 tests performed between January 16, 2020 and March 24, 2020 in Busan, 108 yielded positive results (positive test rate, 0.6%). All confirmed cases were placed in isolation at hospitals. Of the 108 confirmed cases, 59 (54.6%) were female. The most common age group was 20-29 years with 37 cases (34.3%). Regarding symptoms at the time of diagnosis, cough (n=38, 35.2%) and fever (n=34, 31.5%) were most common; 12 cases (11.1%) were asymptomatic. The source of infection was identified in 99 cases (91.7%). A total of 3,223 contacts were identified and quarantined. Household contacts accounted for 196, and the household secondary attack rate was 8.2% (95% confidence interval [CI], 4.7 to 12.9). The mean serial interval was estimated to be 5.54 days (95% CI, 4.08 to 7.01). After February 26, (Rt) remained below 1 in Busan. CONCLUSIONS: The early containment strategy implemented in Busan shows that control is possible if outbreaks are of limited scope. In preparation for future outbreaks, public health and healthcare systems should be re-examined and put in a ready state.