Search

Our study indicates sustained transmission (effective reproduction number, 1.3; serial interval, 4.2 days; regional doubling times, 3.3–11.4 days) of the severe acute respiratory syndrome coronavirus 2 Omicron (B.1.1.529) variant (N = 2351) in South Korea (25 November 2021–8 January 2022), implicating insufficient protection through vaccination and supporting nonpharmaceutical control measures.

Epidemiological distributions of the coronavirus disease 2019 (COVID-19), including the intervals from symptom onset to diagnosis, reporting, or death, are important for developing effective disease-control strategies. COVID-19 case data (from 19 January 2020 to 10 January 2022) from a national database maintained by the Korea Disease Control and Prevention Agency and the Central Disease Control Headquarters were analyzed. A joint Bayesian subnational model with partial pooling was used and yielded probability distribution models of key epidemiological distributions in Korea. Serial intervals from before and during the Delta variant’s predominance were estimated. Although the mean symptom-onset-to-report interval was 3.2 days at the national level, it varied across different regions (2.9–4.0 days). Gamma distribution showed the best fit for the onset-to-death interval (with heterogeneity in age, sex, and comorbidities) and the reporting-to-death interval. Log-normal distribution was optimal for ascertaining the onset-to-diagnosis and onset-to-report intervals. Serial interval (days) was shorter before the Delta variant-induced outbreaks than during the Delta variant’s predominance (4.4 vs. 5.2 days), indicating the higher transmission potential of the Delta variant. The identified heterogeneity in region-, age-, sex-, and period-based distributions of the transmission dynamics of COVID-19 will facilitate the development of effective interventions and disease-control strategies.

To identify the temporal change in the possible risk of superspreading events, we estimated the overdispersion parameter in 2 different periods of the coronavirus disease 2019 pandemic. We determined that the possible risk of superspreading events was reduced 90% during the second epidemic period in South Korea.

BACKGROUND Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19’s disease dynamics seemed difficult to predict. External factors, such as internet search data, need to be included in the models to increase their accuracy. However, it remains unclear whether incorporating online search volumes into models leads to better predictive performances for long-term prediction. OBJECTIVE The aim of this study was to analyze whether search engine query data are important variables that should be included in the models predicting new daily COVID-19 cases and deaths in short- and long-term periods. METHODS We used country-level case-related data, NAVER search volumes, and mobility data obtained from Google and Apple for the period of January 20, 2020, to July 31, 2021, in South Korea. Data were aggregated into four subsets: 3, 6, 12, and 18 months after the first case was reported. The first 80% of the data in all subsets were used as the training set, and the remaining data served as the test set. Generalized linear models (GLMs) with normal, Poisson, and negative binomial distribution were developed, along with linear regression (LR) models with lasso, adaptive lasso, and elastic net regularization. Root mean square error values were defined as a loss function and were used to assess the performance of the models. All analyses and visualizations were conducted in SAS Studio, which is part of the SAS OnDemand for Academics. RESULTS GLMs with different types of distribution functions may have been beneficial in predicting new daily COVID-19 cases and deaths in the early stages of the outbreak. Over longer periods, as the distribution of cases and deaths became more normally distributed, LR models with regularization may have outperformed the GLMs. This study also found that models performed better when predicting new daily deaths compared to new daily cases. In addition, an evaluation of feature effects in the models showed that NAVER search volumes were useful variables in predicting new daily COVID-19 cases, particularly in the first 6 months of the outbreak. Searches related to logistical needs, particularly for “thermometer” and “mask strap,” showed higher feature effects in that period. For longer prediction periods, NAVER search volumes were still found to constitute an important variable, although with a lower feature effect. This finding suggests that search term use should be considered to maintain the predictive performance of models. CONCLUSIONS NAVER search volumes were important variables in short- and long-term prediction, with higher feature effects for predicting new daily COVID-19 cases in the first 6 months of the outbreak. Similar results were also found for death predictions.

Introduction Tradeoffs exist between efforts to increase influenza vaccine uptake, including early season vaccination, and potential decreased vaccine effectiveness if protection wanes during influenza season. U.S. older adults increasingly receive vaccination before October. Influenza illness peaks vary from December to April. Methods A Markov model compared influenza likelihood in older adults with (1) status quo vaccination (August–May) to maximize vaccine uptake or (2) vaccination compressed to October–May (to decrease waning vaccine effectiveness impact). The Centers for Disease Control and Prevention data were used for influenza incidence and vaccination parameters. Prior analyses showed that absolute vaccine effectiveness decreased by 6%–11% per month, favoring later season vaccination. However, compressed vaccination could decrease overall vaccine uptake. Influenza incidence was based on average monthly incidence with earlier and later peaks also examined. Influenza strain distributions from two seasons were modeled in separate scenarios. Sensitivity analyses were performed to test result robustness. Data were collected and analyzed in 2018. Results Compressed vaccination would avert ≥11,400 influenza cases in older adults during a typical season if it does not decrease vaccine uptake. However, if compressed vaccination decreases vaccine uptake or there is an early season influenza peak, more influenza can result. In probabilistic sensitivity analyses, compressed vaccination was never favored if it decreased absolute vaccine uptake by >5.5% in any scenario; when influenza peaked early, status quo vaccination was favored. Conclusions Compressed vaccination could decrease waning vaccine effectiveness and decrease influenza cases in older adults. However, this positive effect is negated when early season influenza peaks occur and diminished by decreased vaccine uptake that could occur with shortening the vaccination season.

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 4,240,982 cases and 106,544 deaths as of June 30, 2021. This motivates an investigation of the SARS-CoV-2 transmission dynamics at the national and regional level using case incidence data. Mathematical models are employed to estimate the transmission potential and perform short-term forecasts of the COVID-19 epidemic trajectory in Colombia. Furthermore, geographic heterogeneity of COVID-19 in Colombia is examined along with the analysis of mobility and social media trends, showing that the increase in mobility in July 2020 and January 2021 were correlated with surges in case incidence. The estimation of national and regional reproduction numbers shows sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Moreover, most recent estimates of reproduction number are >1.0 at the national and regional levels as of May 30, 2021. Further, the 30-day ahead short-term forecasts obtained from Richards model present a sustained decline in case counts in contrast to the sub-epidemic and GLM model. Nevertheless, our spatial analysis in Colombia shows distinct variations in incidence rate patterns across different departments that can be grouped into four distinct clusters. Lastly, the correlation of social media trends and adherence to social distancing measures is observed by the fact that a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued.Author summaryAs the COVID-19 pandemic continues to spread across Colombia, studies highlighting the intensity of the pandemic become imperative for appropriate resource allocation and informing public health policies. In this study we utilize mathematical models to infer the transmission dynamics of SARS-CoV-2 at the regional and national level as well as short-term forecast the COVID-19 epidemic trajectory. Moreover, we examine the geographic heterogeneity of the COVID-19 case incidence in Colombia along with the analysis of mobility and social media trends in relation to the observed COVID-19 case incidence in the country. The estimates of reproduction numbers at the national and regional level show sustained disease transmission as of May 30, 2021. Moreover, the 30-day ahead short-term forecasts for the most recent time-period (June 1-June 30, 2021) generated from the mathematical models needs to be interpreted with caution as the Richards model point towards a sustained decline in case incidence contrary to the GLM and sub-epidemic wave model. Nevertheless, the spatial analysis in Colombia shows distinct variations in incidence rate patterns across different departments that can be grouped into four distinct clusters. Lastly, the social media and mobility trends explain the occurrence of case resurgences over the time.

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with Rt

To identify the temporal change in the possible risk of superspreading events, we estimated the overdispersion parameter in 2 different periods of the coronavirus disease 2019 pandemic. We determined that the possible risk of superspreading events was reduced 90% during the second epidemic period in South Korea.

A total of 475,214 COVID-19 cases, including 13,659 deaths, had been recorded in Canada as of 15 December 2020. The daily reports of confirmed cases and deaths in Canada prior to 15 December 2020 were obtained from publicly available sources and used to examine regional variations in case fatality rate (CFR). Based on a factor of underestimation and the duration of time from symptom onset to death, the time-delay adjusted CFR for COVID-19 was estimated in the four most affected provinces (Quebec, Ontario, Alberta, and British Columbia) and nationwide. The model-based adjusted CFR was higher than the crude CFR throughout the pandemic, primarily owing to the incorporation in our estimation of the delay between case reports and deaths. The adjusted CFR in Canada was estimated to be 3.36% nationwide. At the provincial level, the adjusted CFR was the highest in Quebec (5.13%)—where the proportion of deaths among older individuals was also the highest among the four provinces—followed by Ontario (3.17%), British Columbia (1.97%), and Alberta (1.13%). Provincial-level variations in CFR were considerable, suggesting that public health interventions focused on densely populated areas and elderly individuals can ameliorate the mortality burden of the COVID-19 pandemic.

Highlights • South Korea has experienced two spatially heterogenous waves of COVID-19. • Seoul and Gyeonggi Province experienced two waves of COVID-19 in March and June. • In the densely populated Seoul and nearby areas, reproduction numbers exceeded 3.0. • The easing of the social distancing measures resulted in the second wave., Objectives In South Korea, 13,745 cases of coronavirus disease (COVID-19) have been reported as of 19 July, 2020. To examine the spatiotemporal changes in the transmission potential, we present regional estimates of the doubling time and reproduction number (Rt) of COVID-19 in the country. Methods Daily series of confirmed COVID-19 cases in the most affected regions were extracted from publicly available sources. We employed established mathematical and statistical methods to investigate the time-varying reproduction numbers of the COVID-19 in Korea and its doubling time, respectively. Results At the regional level, Seoul and Gyeonggi Province have experienced the first peak of COVID-19 in early March, followed by the second wave in early June, withRt exceeding 3.0 and mean doubling time ranging from 3.6 to 10.1 days. As of 19 July, 2020, Gyeongbuk Province and Daegu are yet to experience a second wave of the disease, where the mean Rt reached 3.5-4.4 and doubling time ranging from 2.8 to 4.6 days during the first wave. Conclusions Our findings support the effectiveness of control measures against COVID-19 in Korea. However, the easing of the restrictions imposed by the government in May 2020 facilitated a second wave in the greater Seoul area.

Objectives In South Korea, 13,745 cases of coronavirus disease (COVID-19) have been reported as of 19 July, 2020. To examine the spatiotemporal changes in the transmission potential, we present regional estimates of the doubling time and reproduction number (Rt) of COVID-19 in the country. Methods Daily series of confirmed COVID-19 cases in the most affected regions were extracted from publicly available sources. We employed established mathematical and statistical methods to investigate the time-varying reproduction numbers of the COVID-19 in Korea and its doubling time, respectively. Results At the regional level, Seoul and Gyeonggi Province have experienced the first peak of COVID-19 in early March, followed by the second wave in early June, with Rt exceeding 3.0 and mean doubling time ranging from 3.6 to 10.1 days. As of 19 July, 2020, Gyeongbuk Province and Daegu are yet to experience a second wave of the disease, where the mean Rt reached 3.5-4.4 and doubling time ranging from 2.8 to 4.6 days during the first wave. Conclusions Our findings support the effectiveness of control measures against COVID-19 in Korea. However, the easing of the restrictions imposed by the government in May 2020 facilitated a second wave in the greater Seoul area. Highlights South Korea has experienced two spatially heterogenous waves of COVID-19. Seoul and Gyeonggi Province experienced two waves of COVID-19 in March and June. In the densely populated Seoul and nearby areas, reproduction numbers exceeded 3.0. The easing of the social distancing measures resulted in the second wave.

BACKGROUND South Korea is among the best-performing countries in tackling the coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding the patterns of risk perception could also facilitate effective risk communication to minimize the impacts of disease spread during this crisis. OBJECTIVE We attempt to explore patterns of community health risk perceptions of COVID-19 in South Korea using internet search data. METHODS Google Trends (GT) and NAVER relative search volumes (RSVs) data were collected using COVID-19–related terms in the Korean language and were retrieved according to time, gender, age groups, types of device, and location. Online queries were compared to the number of daily new COVID-19 cases and tests reported in the Kaggle open-access data set for the time period of December 5, 2019, to May 31, 2020. Time-lag correlations calculated by Spearman rank correlation coefficients were employed to assess whether correlations between new COVID-19 cases and internet searches were affected by time. We also constructed a prediction model of new COVID-19 cases using the number of COVID-19 cases, tests, and GT and NAVER RSVs in lag periods (of 1-3 days). Single and multiple regressions were employed using backward elimination and a variance inflation factor of RESULTS The numbers of COVID-19–related queries in South Korea increased during local events including local transmission, approval of coronavirus test kits, implementation of coronavirus drive-through tests, a face mask shortage, and a widespread campaign for social distancing as well as during international events such as the announcement of a Public Health Emergency of International Concern by the World Health Organization. Online queries were also stronger in women (r=0.763-0.823; Pr=0.726-0.821; Pr=0.701-0.826; Pr=0.706-0.725; Pr=0.704-0.804; Pr=0.705-0.717; P CONCLUSIONS The use of both GT and NAVER RSVs to explore patterns of community health risk perceptions could be beneficial for targeting risk communication from several perspectives, including time, population characteristics, and location.

The dengue vaccine, CYD-TDV (Dengvaxia), has been licensed in 20 countries in Latin America and Southeast Asia beginning in 2015. In April 2018, the World Health Organization (WHO) advised that CYD-TDV should only be administered to individuals with a history of previous dengue virus infection. Using literature-based parameters, a mathematical model of dengue transmission and vaccination was developed to determine the optimal vaccination strategy while considering the effect of antibody-dependent enhancement (ADE). We computed the optimal vaccination rates under various vaccination costs and serological profiles. We observe that the optimal dengue vaccination rates for seropositive individuals are highest at the initial phase of a vaccination program, requiring intense effort at the early phase of an epidemic. The model shows that even in the presence of ADE, vaccination could reduce dengue incidence and provide population benefits. Specifically, optimal vaccination rates increase with a higher proportion of monotypic seropositive individuals, resulting in a higher impact of vaccination. Even in the presence of ADE and with limited vaccine efficacy, our work provides a population-level perspective on the potential merits of dengue vaccination.

Background: In Korea, a total of 10,840 confirmed cases of COVID-19 including 256 deaths have been recorded as of May 9, 2020. The time-delay adjusted case fatality risk (CFR) of COVID-19 in Korea is yet to be estimated. Methods: We obtained the daily series of confirmed cases and deaths in Korea reported prior to May 9, 2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in Daegu, Gyeongsangbuk-do, other regions in Korea, as well as the entire country. Results: Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do, this was partially due to the reporting delay. Our estimates of the risk of death in Gyeongsangbuk-do reached 25.9% (95% Credible Interval (CrI): 19.6%&ndash, 33.6%), 20.8% (95% CrI: 18.1%&ndash, 24.0%) in Daegu, and 1.7% (95% CrI: 1.1%&ndash, 2.5%) in other regions, whereas the national estimate was 10.2% (95% CrI: 9.0%&ndash, 11.5%). Conclusions: The latest estimates of CFR of COVID-19 in Korea are considerably high, even with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings. Geographic differences in the CFR are likely influenced by clusters tied to hospitals and nursing homes.

Background: In Korea, a total of 10,840 confirmed cases of COVID-19 including 256 deaths have been recorded as of May 9, 2020. The time-delay adjusted case fatality risk (CFR) of COVID-19 in Korea is yet to be estimated. Methods: We obtained the daily series of confirmed cases and deaths in Korea reported prior to May 9, 2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in Daegu, Gyeongsangbuk-do, other regions in Korea, as well as the entire country. Results: Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do; this was partially due to the reporting delay. Our estimates of the risk of death in Gyeongsangbuk-do reached 25.9% (95% CrI: 19.6%-33.6%), 20.8% (95% CrI: 18.1%-24.0%) in Daegu and 1.7% (95% CrI: 1.1%-2.5%) in other regions, whereas the national estimate was 10.2% (95% CrI: 9.0%-11.5%). Conclusions: The latest estimates of CFR of COVID-19 in Korea are considerably high, even with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings. Geographic differences in the CFR are likely influenced by clusters tied to hospitals and nursing homes.

Background Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19’s disease dynamics seemed difficult to predict. External factors, such as internet search data, need to be included in the models to increase their accuracy. However, it remains unclear whether incorporating online search volumes into models leads to better predictive performances for long-term prediction. Objective The aim of this study was to analyze whether search engine query data are important variables that should be included in the models predicting new daily COVID-19 cases and deaths in short- and long-term periods. Methods We used country-level case-related data, NAVER search volumes, and mobility data obtained from Google and Apple for the period of January 20, 2020, to July 31, 2021, in South Korea. Data were aggregated into four subsets: 3, 6, 12, and 18 months after the first case was reported. The first 80% of the data in all subsets were used as the training set, and the remaining data served as the test set. Generalized linear models (GLMs) with normal, Poisson, and negative binomial distribution were developed, along with linear regression (LR) models with lasso, adaptive lasso, and elastic net regularization. Root mean square error values were defined as a loss function and were used to assess the performance of the models. All analyses and visualizations were conducted in SAS Studio, which is part of the SAS OnDemand for Academics. Results GLMs with different types of distribution functions may have been beneficial in predicting new daily COVID-19 cases and deaths in the early stages of the outbreak. Over longer periods, as the distribution of cases and deaths became more normally distributed, LR models with regularization may have outperformed the GLMs. This study also found that models performed better when predicting new daily deaths compared to new daily cases. In addition, an evaluation of feature effects in the models showed that NAVER search volumes were useful variables in predicting new daily COVID-19 cases, particularly in the first 6 months of the outbreak. Searches related to logistical needs, particularly for “thermometer” and “mask strap,” showed higher feature effects in that period. For longer prediction periods, NAVER search volumes were still found to constitute an important variable, although with a lower feature effect. This finding suggests that search term use should be considered to maintain the predictive performance of models. Conclusions NAVER search volumes were important variables in short- and long-term prediction, with higher feature effects for predicting new daily COVID-19 cases in the first 6 months of the outbreak. Similar results were also found for death predictions.

Background Annual influenza vaccination is a key to preventing widespread influenza infections. Recent reports of influenza vaccine effectiveness (VE) indicate that vaccination in prior years may reduce VE in the current season, suggesting vaccine interference. The purpose of this study is to evaluate the potential effect of repeat influenza vaccinations in the presence of vaccine interference. Methods Using literature-based parameters, an age-structured influenza equation-based transmission model was used to determine the optimal vaccination strategy, while considering the effect of varying levels of interference. Results The model shows that, even in the presence of vaccine interference, revaccination reduces the influenza attack rate and provides individual benefits. Specifically, annual vaccination is a favored strategy over vaccination in alternate years, as long as the level of residual protection is less than 58% or vaccine interference effect is minimal. Furthermore, the negative impact of vaccine interference may be offset by increased vaccine coverage levels. Conclusions Even in the presence of potential vaccine interference, our work provides a population-level perspective on the potential merits of repeated influenza vaccination. This is because repeat vaccination groups had lower attack rates than groups that omitted the second vaccination unless vaccine interference was at very high, perhaps implausible, levels.

Introduction Decreased live attenuated influenza vaccine (LAIV) effectiveness in the U.S. prompted the Advisory Committee on Immunization Practices in August 2016 to recommend against this vaccine’s use. However, overall influenza uptake increases when LAIV is available and, unlike the U.S., LAIV has retained its effectiveness in other countries. These opposing countercurrents create a dilemma. Methods To examine the potential consequences of the decision to not recommend LAIV, which may result in decreased influenza vaccination coverage in the U.S. population, a Markov decision analysis model was used to examine influenza vaccination options in U.S. children aged 2–8 years. Data were compiled and analyzed in 2016. Results Using recently observed low LAIV effectiveness values, fewer influenza cases will occur if LAIV is not used compared with having LAIV as a vaccine option. However, having the option to use LAIV may be favored if LAIV effectiveness returns to prior levels or if the absence of vaccine choice substantially decreases overall vaccine uptake. Conclusions Continued surveillance of LAIV effectiveness and influenza vaccine uptake is warranted, given their importance in influenza vaccination policy decisions.

The first approved dengue vaccine, CYD-TDV, a chimeric, live-attenuated, tetravalent dengue virus vaccine, was recently licensed in 13 countries, including Brazil. In light of recent vaccine approval, we modeled the cost-effectiveness of potential vaccination policies mathematically based on data from recent vaccine efficacy trials that indicated that vaccine efficacy was lower in seronegative individuals than in seropositive individuals. In our analysis, we investigated several vaccination programs, including routine vaccination, with various vaccine coverage levels and those with and without large catch-up campaigns. As it is unclear whether the vaccine protects against infection or just against disease, our model incorporated both direct and indirect effects of vaccination. We found that in the presence of vaccine-induced indirect protection, the cost-effectiveness of dengue vaccination decreased with increasing vaccine coverage levels because the marginal returns of herd immunity decreases with vaccine coverage. All routine dengue vaccination programs that we considered were cost-effective, reducing dengue incidence significantly. Specifically, a routine dengue vaccination of 9-year-olds would be cost-effective when the cost of vaccination per individual is less than $262. Furthermore, the combination of routine vaccination and large catch-up campaigns resulted in a greater reduction of dengue burden (by up to 93%) than routine vaccination alone, making it a cost-effective intervention as long as the cost per course of vaccination is $255 or less. Our results show that dengue vaccination would be cost-effective in Brazil even with a relatively low vaccine efficacy in seronegative individuals.

Since the first identified individual of 2019 novel coronavirus (COVID-19) infection on Jan 20, 2020 in South Korea, the number of confirmed cases rapidly increased. As of Feb 26, 2020, 1,261 cases of COVID-19 including 12 deaths were confirmed in South Korea. Using the incidence data of COVID-19, we estimate the reproduction number at 1.5 (95% CI: 1.4-1.6), which indicates sustained transmission and support the implementation of social distancing measures to rapidly control the outbreak.

Highlights • We examined control strategies minimizing COVID-19 infection and intervention costs. • Social distancing and testing are considered intervention strategies. • Testing should be intensified in the early phases and after the epidemic peak. • Social distancing should be intensified if prevalence is greater than 15%. • As social distancing relaxes, testing with contact tracing becomes important., The coronavirus disease (COVID-19) has infected more than 24 million individuals, with 825,381 deaths worldwide. Several countries have implemented social distancing and testing policies with contact tracing as a measure to flatten the curve of the ongoing pandemic. Optimizing these control measures is urgent if the substantial societal and economic impacts associated with infection and interventions are considered. To determine the optimal social distancing and testing strategies, we developed a mathematical model of COVID-19 transmission and applied optimal control theory, identifying the best approach to reduce the epidemiological burden of COVID-19 at a minimal cost. The results demonstrate that testing as a standalone optimal strategy does not have a significant effect on the final size of an epidemic, but it would delay the peak of the pandemic. If social distancing is the sole control strategy, it would be optimal to gradually increase the level of social distancing as the incidence curve of COVID-19 grows, and relax the measures after the curve has reached its peak. Compared with a single strategy, combined social distancing and testing strategies are demonstrated to be more efficient at reducing the disease burden, and they can delay the peak of the disease. To optimize these strategies, testing should be maintained at a maximum level in the early phases and after the peak of the epidemic, whereas social distancing should be intensified when the prevalence of the disease is greater than 15%. Accordingly, public health agencies should implement early testing and switch to social distancing when the incidence level begins to increase. After the peak of the pandemic, it would be optimal to gradually relax social distancing and switch back to testing.

Introduction Prior studies showed that live attenuated influenza vaccine (LAIV) is more effective than inactivated influenza vaccine (IIV) in children aged 2–8 years, supporting the Centers for Disease Control and Prevention (CDC) recommendations in 2014 for preferential LAIV use in this age group. However, 2014–2015 U.S. effectiveness data indicated relatively poor effectiveness of both vaccines, leading CDC in 2015 to no longer prefer LAIV. Methods An age-structured model of influenza transmission and vaccination was developed, which incorporated both direct and indirect protection induced by vaccination. Based on this model, the cost effectiveness of influenza vaccination strategies in children aged 2–8 years in the U.S. was estimated. The base case assumed a mixed vaccination strategy where 33.3% and 66.7% of vaccinated children aged 2–8 years receive LAIV and IIV, respectively. Analyses were performed in 2014–2015. Results Using published meta-analysis vaccine effectiveness data (83% LAIV and 64% IIV), exclusive LAIV use would be a cost-effective strategy when vaccinating children aged 2–8 years, whereas IIV would not be preferred. However, when 2014–2015 U.S. effectiveness data (0% LAIV and 15% IIV) were used, IIV was likely to be preferred. Conclusions The cost effectiveness of influenza vaccination in children aged 2–8 years is highly dependent on vaccine effectiveness; the vaccine type with higher effectiveness is preferred. In general, exclusive IIV use is preferred over LAIV use, as long as vaccine effectiveness is higher for IIV than for LAIV.

Initial supply of the coronavirus disease (COVID-19) vaccine may be limited, necessitating its effective use. Herein, an age-structured model of COVID-19 spread in South Korea is parameterized to understand the epidemiological characteristics of COVID-19. The model determines optimal vaccine allocation for minimizing infections, deaths, and years of life lost while accounting for population factors, such as country-specific age distribution and contact structure, and various levels of vaccine efficacy. A transmission-blocking vaccine should be prioritized in adults aged 20–49 years and those older than 50 years to minimize the cumulative incidence and mortality, respectively. A strategy to minimize years of life lost involves the vaccination of adults aged 40–69 years, reflecting the relatively high case-fatality rates and years of life lost in this age group. An incidence-minimizing vaccination strategy is highly sensitive to vaccine efficacy, and vaccines with lower efficacy should be administered to teenagers and adults aged 50–59 years. Consideration of age-specific contact rates and vaccine efficacy is critical to optimize vaccine allocation. New recommendations for COVID-19 vaccines under consideration by the Korean Centers for Disease Control and Prevention are mainly based on a mortality-minimizing allocation strategy.

BackgroundSouth Korea is among the best-performing countries in tackling the coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding the patterns of risk perception could also facilitate effective risk communication to minimize the impacts of disease spread during this crisis.ObjectiveWe attempt to explore patterns of community health risk perceptions of COVID-19 in South Korea using internet search data.MethodsGoogle Trends (GT) and NAVER relative search volumes (RSVs) data were collected using COVID-19–related terms in the Korean language and were retrieved according to time, gender, age groups, types of device, and location. Online queries were compared to the number of daily new COVID-19 cases and tests reported in the Kaggle open-access data set for the time period of December 5, 2019, to May 31, 2020. Time-lag correlations calculated by Spearman rank correlation coefficients were employed to assess whether correlations between new COVID-19 cases and internet searches were affected by time. We also constructed a prediction model of new COVID-19 cases using the number of COVID-19 cases, tests, and GT and NAVER RSVs in lag periods (of 1-3 days). Single and multiple regressions were employed using backward elimination and a variance inflation factor of ResultsThe numbers of COVID-19–related queries in South Korea increased during local events including local transmission, approval of coronavirus test kits, implementation of coronavirus drive-through tests, a face mask shortage, and a widespread campaign for social distancing as well as during international events such as the announcement of a Public Health Emergency of International Concern by the World Health Organization. Online queries were also stronger in women (r=0.763-0.823; PConclusionsThe use of both GT and NAVER RSVs to explore patterns of community health risk perceptions could be beneficial for targeting risk communication from several perspectives, including time, population characteristics, and location.

Background and Objectives “Universal” vaccines that could have multistrain and multiyear effectiveness are being developed. Their potential cost-effectiveness in geriatric populations is unknown. Research Design and Methods A Markov model estimated effects of a theoretical universal influenza vaccine compared with available seasonal vaccines in hypothetical cohorts of U.S. 65+-year olds followed over a 5-year time horizon to capture potential multiyear protection. Outcomes included costs per quality-adjusted life-year gained and influenza cases avoided. Results Using hypothetical universal vaccine parameter values (cost $100, vaccine effectiveness 39%, uptake 64%, effectiveness duration 5 years), universal vaccine was less costly than seasonal influenza vaccination strategies. High-dose trivalent influenza vaccine, compared with universal vaccine, gained 0.0028 quality-adjusted life-years and cost $82 more, or $28,700 per quality-adjusted life-year gained. Other seasonal vaccines were not favorable economically. Five-year influenza risk with universal vaccination was 32.3% under base case assumptions, compared with

Purpose High-dose trivalent inactivated influenza vaccine (HD-IIV3) or recombinant trivalent influenza vaccine (RIV) may increase influenza vaccine effectiveness (VE) in adults with conditions that place them at high risk for influenza complications. This analysis models the public health impact and cost-effectiveness (CE) of these vaccines for 50–64 year-olds. Methods Markov model CE analysis compared 5 strategies in 50–64 year-olds: no vaccination; only standard-dose IIV3 offered (SD-IIV3 only), only quadrivalent influenza vaccine offered (SD-IIV4 only); high-risk patients receiving HD-IIV3, others receiving SD-IIV3 (HD-IIV3 & SD-IIV3); and high-risk patients receiving HD-IIV3, others receiving SD-IIV4 (HD-IIV3 & SD-IIV4). In a secondary analysis, RIV replaced HD-IIV3. Parameters were obtained from U.S. databases, the medical literature and extrapolations from VE estimates. Effectiveness was measured as 3%/year discounted quality adjusted life year (QALY) losses avoided. Results The least expensive strategy was SD-IIV3 only, with total costs of $99.84/person. The SD-IIV4 only strategy cost an additional $0.91/person, or $37,700/QALY gained. The HD-IIV3 & SD-IIV4 strategy cost $1.06 more than SD-IIV4 only, or $71,500/QALY gained. No vaccination and HD-IIV3 & SD-IIV3 strategies were dominated. Results were sensitive to influenza incidence, vaccine cost, standard-dose VE in the entire population and high-dose VE in high-risk patients. The CE of RIV for high-risk patients was dependent on as yet unknown parameter values. Conclusions Based on available data, using high-dose influenza vaccine or RIV in middle-aged, high-risk patients may be an economically favorable vaccination strategy with public health benefits. Clinical trials of these vaccines in this population may be warranted.

Background. There is widespread recognition that interventions targeting “superspreaders” are more effective at containing epidemics than strategies aimed at the broader population. However, little attention has been devoted to determining optimal levels of coverage for targeted vaccination strategies, given the nonlinear relationship between program scale and the costs and benefits of identifying and successfully administering vaccination to potential superspreaders. Methods. We developed a framework for such an assessment derived from a transmission model of seasonal influenza parameterized to emulate typical seasonal influenza epidemics in the US. We used this framework to estimate how the marginal benefit of expanded targeted vaccination changes with the proportion of the target population already vaccinated. Results. The benefit of targeting additional superspreaders varies considerably as a function of both the baseline vaccination coverage and proximity to the herd immunity threshold. The general form of the marginal benefit function starts low, particularly for severe epidemics, increases monotonically until its peak at the point of herd immunity, and then plummets rapidly. We present a simplified transmission model, primarily designed to convey qualitative insight rather than quantitative precision. With appropriate contact data, future work could address more complex population structures, such as age structure and assortative mixing patterns. Our illustrative example highlights the general economic and epidemiological findings of our method but does not address intervention design, policy, and resource allocation issues related to practical implementation of this particular scenario. Conclusions. Our approach offers a means of estimating willingness to pay for search costs associated with targeted vaccination of superspreaders, which can inform policies regarding whether a targeted intervention should be implemented and, if so, up to what levels.

Objectives To compare the cost-effectiveness of four influenza vaccines available in the United States for persons aged 65 and older: trivalent inactivated influenza vaccine (IIV3), quadrivalent inactivated influenza vaccine (IIV4), a more-expensive high-dose IIV3, and a newly approved adjuvanted IIV3. Design Cost-effectiveness analysis using a Markov model and sensitivity analyses. Setting A hypothetical influenza vaccination season modeled according to possible U.S. influenza vaccination policies. Participants Hypothetical cohort of individuals aged 65 and older in the United States. Measurements Cost-effectiveness and public health benefits of available influenza vaccination strategies in U.S. elderly adults. Results IIV3 cost $3,690 per quality-adjusted life year (QALY) gained, IIV4 cost $20,939 more than IIV3 per QALY gained, and high-dose IIV3 cost $31,214 more per QALY than IIV4. The model projected 83,775 fewer influenza cases and 980 fewer deaths with high-dose IIV3 than with the next most-effective vaccine: IIV4. In a probabilistic sensitivity analysis, high-dose IIV3 was the favored strategy if willingness to pay is $25,000 or more per QALY gained. Adjuvanted IIV3 cost-effectiveness depends on its price and effectiveness (neither yet determined in the United States) but could be favored if its relative effectiveness is 15% greater than that of IIV3. Conclusion From economic and public health standpoints, high-dose IIV3 for adults aged 65 years and older is likely to be favored over the other vaccines, based on currently available data. The cost-effectiveness of adjuvanted IIV3 should be reviewed after its effectiveness has been compared with that of other vaccines and its U.S. price is established.

Dengue is one of the most problematic vector-borne diseases in the Philippines, with an estimated 842,867 cases resulting in medical costs of $345 million U.S. dollars annually. In December 2015, the first dengue vaccine, known as chimeric yellow fever virus-dengue virus tetravalent dengue vaccine, was approved for use in the Philippines and is given to children 9 years of age. To estimate the cost-effectiveness of dengue vaccination in the Philippines, we developed an age-structured model of dengue transmission and vaccination. Using our model, we compared two vaccination scenarios entailing routine vaccination programs both with and without catch-up vaccination. Our results indicate that the higher the cost of vaccination, the less cost-effective the dengue vaccination program. With the current dengue vaccination program that vaccinates children 9 years of age, dengue vaccination is cost-effective for vaccination costs up to $70 from a health-care perspective and up to $75 from a societal perspective. Under a favorable scenario consisting of 1 year of catch-up vaccinations that target children 9-15 years of age, followed by regular vaccination of 9-year-old children, vaccination is cost-effective at costs up to $72 from a health-care perspective and up to $78 from a societal perspective. In general, dengue vaccination is expected to reduce the incidence of both dengue fever and dengue hemorrhagic fever /dengue shock syndrome. Our results demonstrate that even at relatively low vaccine efficacies, age-targeted vaccination may still be cost-effective provided the vaccination cost is sufficiently low.

Background Mathematical models of disease transmission and vaccination typically assume that protective vaccine efficacy (i.e. the relative reduction in the transmission rate among vaccinated individuals) is equivalent to direct effectiveness of vaccine. This assumption has not been evaluated. Methods We used dynamic epidemiological models of influenza and measles vaccines to evaluate the common measures of vaccine effectiveness in terms of both the protection of individuals and disease control within populations. We determined how vaccine-mediated reductions in attack rates translate into vaccine efficacy as well as into the common population measures of ‘direct’, ‘indirect’, ‘total’, and ‘overall’ effects of vaccination with examples of compartmental models of influenza and measles vaccination. Results We found that the typical parameterization of vaccine efficacy using direct effectiveness of vaccine can lead to the underestimation of the impact of vaccine. Such underestimation occurs when the vaccine is assumed to offer partial protection to every vaccinated person, and becomes worse when the level of vaccine coverage is low. Nevertheless, estimates of ‘total’, ‘indirect’ and ‘overall’ effectiveness increase with vaccination coverage in the population. Furthermore, we show how the measures of vaccine efficacy and vaccine effectiveness can be correctly calculated. Conclusions Typical parameterization of vaccine efficacy in mathematical models may underestimate the actual protective effect of the vaccine, resulting in discordance between the actual effects of vaccination at the population level and predictions made by models. This work shows how models can be correctly parameterized from clinical trial data.

Limited production capacity and delays in vaccine development are major obstacles to vaccination programs that are designed to mitigate a pandemic influenza. In order to evaluate and compare the impact of various vaccination strategies during a pandemic influenza, we developed an age/risk-structured model of influenza transmission, and parameterized it with epidemiological data from the 2009 H1N1 influenza A pandemic. Our model predicts that the impact of vaccination would be considerably diminished by delays in vaccination and staggered vaccine supply. Nonetheless, prioritizing limited H1N1 vaccine to individuals with a high risk of complications, followed by school-age children, and then preschool-age children, would minimize an overall attack rate as well as hospitalizations and deaths. This vaccination scheme would maximize the benefits of vaccination by protecting the high-risk people directly, and generating indirect protection by vaccinating children who are most likely to transmit the disease.

Background. Antiviral coverage is defined by the proportion of the population that takes antiviral prophylaxis or treatment. High coverage of an antiviral drug has epidemiological and evolutionary repercussions. Antivirals select for drug resistance within the population, and individuals may experience adverse effects. To determine optimal antiviral coverage in the context of an influenza outbreak, we compared 2 perspectives: 1) the individual level (the Nash perspective), and 2) the population level (utilitarian perspective). Methods. We developed an epidemiological game-theoretic model of an influenza pandemic. The data sources were published literature and a national survey. The target population was the US population. The time horizon was 6 months. The perspective was individuals and the population overall. The interventions were antiviral prophylaxis and treatment. The outcome measures were the optimal coverage of antivirals in an influenza pandemic. Results. At current antiviral pricing, the optimal Nash strategy is 0% coverage for prophylaxis and 30% coverage for treatment, whereas the optimal utilitarian strategy is 19% coverage for prophylaxis and 100% coverage for treatment. Subsidizing prophylaxis by $440 and treatment by $85 would bring the Nash and utilitarian strategies into alignment. For both prophylaxis and treatment, the optimal antiviral coverage decreases as pricing of antivirals increases. Our study does not incorporate the possibility of an effective vaccine and lacks probabilistic sensitivity analysis. Our survey also does not completely represent the US population. Because our model assumes a homogeneous population and homogeneous antiviral pricing, it does not incorporate heterogeneity of preference. Conclusions. The optimal antiviral coverage from the population perspective and individual perspectives differs widely for both prophylaxis and treatment strategies. Optimal population and individual strategies for prophylaxis and treatment might be aligned through subsidization.

Although fatal if untreated, human rabies can be prevented through post-exposure prophylaxis (PEP), which involves a course of vaccination and immunoglobulin administered immediately after exposure. However, high costs and frequent lack of rabies vaccine and immunoglobulin lead to about 55,000 deaths per year worldwide. Using data from a detailed study of rabies in Tanzania, we calculate a cost-effectiveness ratio for PEP when the WHO-recommended Essen regimen, a 5-dose intramuscular vaccination schedule, is adopted. Our analyses indicate a cost-effectiveness ratio for PEP of $27/quality-adjusted life year (QALY) from a health care perspective and $32/QALY from a societal perspective in Tanzania. From both perspectives, it is "very cost-effective" to administer PEP to patients bitten by an animal suspected to be rabid. Moreover, PEP remains "very cost-effective" provided that at least 1% of doses are administered to people who were actually exposed to rabies.

The objective of this study is to estimate the cost-effectiveness of mass vaccination of US infants with the recently available rotavirus vaccine, RotaTeq. We developed a dynamic transmission model of rotavirus to incorporate herd immunity into cost-effectiveness analysis. Our study indicates that a rotavirus vaccination program would prevent about 90% of rotavirus incidence, mortality, hospitalization and emergency department visits annually. We conclude that a universal rotavirus vaccine program in the US would cost $77.30 per case averted from the health care and give a net saving of $80.75 per case averted from the societal perspectives, respectively. The cost per QALY gained was found to be $104,610 when we considered child with one caregiver, making the rotavirus vaccination program a cost-effective intervention.

The roles of immigration and vaccination on disease dynamics are explored in a simple setting that considers the possibility of conferred immunity. We focus on SIR and SIS models with a vaccinated class. Conditions for the existence of multiple endemic steady states and a fold bifurcation are discussed.

We model an outbreak of acute haemorrhagic conjunctivitis (AHC) using a simple epidemic model that includes susceptible, infectious, reported, and recovered classes. The model's framework considers the impact of underreporting and behaviour changes on the transmission rate and is applied to a recent epidemic of AHC in Mexico, using a fit to the cumulative number of cases to estimate model parameters, which agree with those derived from clinical studies. The model predicts a 'mean time from symptomatic onset to diagnosis' of 1.43 days (95 per cent CI: 1-2.5) and that the final size of the Mexican epidemic was underreported by 39 per cent. We estimate that a primary infectious case generates approximately 3 secondary cases (R0* = 2.64, SD 0.65). We explore the impact of interventions on the final epidemic size, and estimate a 36 per cent reduction in the transmission rate due to behaviour changes. The effectiveness of the behaviour changes in slowing the epidemic is evident at 21.90 (SD 0.19) days after the first reported case. Results therefore support current public health policy including expeditious announcement of the outbreak and public health information press releases that instruct individuals on avoiding contagion and encourage them to seek diagnosis in hospital clinics.

Rotavirus is the most common cause of severe gastroenteritis in young children worldwide. The introduction of vaccination programs has led to a significant reduction in number of hospitalizations due to rotavirus in North and South American countries. Little work has been done, however, to examine the differential impact of vaccination as a function of strain distribution and strain-specific vaccine efficacy. We developed a two-strain epidemiological model of rotavirus transmission, and used it to examine the effects of a monovalent vaccine (Rotarix) on the qualitative behaviors of infection levels in a population. For contrast, we parameterized our model with strain distribution data from North America and from South America. In all cases, the introduction of the vaccine led to significant decreases in the prevalence of primary infection due to both strains for a decade or more, after which the overall prevalence recovers to near pre-vaccination levels. The prevalence of G1P[8] is significantly higher in North America (73 % of all rotavirus infections) compared to that in South America (34 %). Our model predicts that the introduction of Rotarix might result in major strain replacement in regions such as North America where the prevalence of G1P[8] is relatively high, due to higher efficacy of Rotarix against infection caused by G1P[8], while regions with lower prevalence of G1P[8], such as South America, are not susceptible to major strain replacement.

Optimal control strategies for controlling seasonal influenza transmission in the US are of high interest, because of the significant epidemiological and economic burden of influenza. To evaluate optimal strategies of vaccination and social distancing, we used an age-structured dynamic model of seasonal influenza. We applied optimal control theory to identify the best way of reducing morbidity and mortality at a minimal cost. In combination with the Pontryagins maximum principle, we calculated time-dependent optimal policies of vaccination and social distancing to minimize the epidemiological and economic burden associated with seasonal influenza. We computed optimal age-specific intervention strategies and analyze them under various costs of interventions and disease transmissibility. Our results show that combined strategies have a stronger impact on the reduction of the final epidemic size. Our results also suggest that the optimal vaccination can be achieved by allocating most vaccines to preschool-age children (age under five) followed by young adults (age 20-39) and school age children (age 6-19). We find that the optimal vaccination rates for all age groups are highest at the beginning of the outbreak, requiring intense effort at the early phase of an epidemic. On the other hand, optimal social distancing of clinical cases tends to last the entire duration of an outbreak, and its intensity is relatively equal for all age groups. Furthermore, with higher transmissibility of the influenza virus (i.e. higher R0), the optimal control strategy needs to include more efforts to increase vaccination rates rather than efforts to encourage social distancing. Taken together, public health agencies need to consider both the transmissibility of the virus and ways to encourage early vaccination as well as voluntary social distancing of symptomatic cases in order to determine optimal intervention strategies against seasonal influenza.

Widespread avoidance of the measles-mumps-rubella vaccination (MMR) demonstrates that the effectiveness of vaccination programs can be thwarted by public misperceptions of vaccine risk. By coupling game theory and epidemic models, we examine vaccination choice among populations stratified into vaccine skeptics and vaccine believers. The two behavioral groups are assumed to be heterogeneous with respect to their perceptions of vaccine and infection risks. We demonstrate that the pursuit of self-interest among vaccine skeptics often leads to vaccination levels that are suboptimal for a population, even if complete coverage is achieved among vaccine believers. Furthermore, as the number of vaccine skeptics increases, the probability of infection among vaccine skeptics increases initially, but it decreases once the vaccine skeptics begin receiving the vaccination, if both behavioral groups are vaccinated according to individual self-interest. This research illustrates the importance of public education on vaccine safety and infection risk in order to achieve vaccination levels that are sufficient to maintain herd immunity.

Rotavirus vaccines have shown great potential for reducing the disease burden of the major cause of severe childhood gastroenteritis. The decision regarding whether rotavirus vaccination will be introduced into the national immunization program is currently being reviewed. The conclusions of previous evaluations of rotavirus vaccination cost-effectiveness contradict each other. This is the first analysis to incorporate a dynamic transmission model to assess the cost-effectiveness of rotavirus vaccination in England and Wales. Most previously reported models do not include herd protection, and thus may underestimate the cost-effectiveness of vaccination against rotavirus. We incorporate a dynamic model of rotavirus transmission in England and Wales into a cost-effectiveness analysis to determine the probability that the pentavalent rotavirus vaccination will be cost-effective over a range of full-course vaccine prices. This novel approach allows the cost-effectiveness analysis to include a feasible level of herd protection provided by a vaccination program. Our base case model predicts that pentavalent rotavirus vaccination is likely to be cost-effective in England and Wales at £ 60 per course. In some scenarios the vaccination is predicted to be not only cost-effective but also cost-saving. These savings could be generated within ten years after vaccine introduction. Our budget impact analysis demonstrates that for the realistic base case scenarios, 58-96% of the cost outlay for vaccination will be recouped within the first four years of a program. Our results indicate that rotavirus vaccination would be beneficial to public health and could be economically sound. Since rotavirus vaccination is not presently on the immunization schedule for England and Wales but is currently under review, this study can inform policymakers of the cost-effectiveness and budget impact of implementing a mass rotavirus vaccine strategy.

Widespread avoidance of Measles-Mumps-Rubella vaccination (MMR), with a consequent increase in the incidence of major measles outbreaks, demonstrates that the effectiveness of vaccination programs can be thwarted by the public misperceptions of vaccine risk. By coupling game theory and epidemic models, we examine vaccination choice among populations stratified into two behavioral groups: vaccine skeptics and vaccine believers. The two behavioral groups are assumed to be heterogeneous with respect to their perceptions of vaccine and infection risks. We demonstrate that the pursuit of self-interest among vaccine skeptics often leads to vaccination levels that are suboptimal for a population, even if complete coverage is achieved among vaccine believers. The demand for measles vaccine across populations driven by individual self-interest was found to be more sensitive to the proportion of vaccine skeptics than to the extent to which vaccine skeptics misperceive the risk of vaccine. Furthermore, as the number of vaccine skeptics increases, the probability of infection among vaccine skeptics increases initially, but it decreases once the vaccine skeptics begin receiving the vaccination, if both behavioral groups are vaccinated according to individual self-interest. Our results show that the discrepancy between the coverages of measles vaccine that are driven by self-interest and those driven by population interest becomes larger when the cost of vaccination increases. This research illustrates the importance of public education on vaccine safety and infection risk in order to maintain vaccination levels that are sufficient to maintain herd immunity.

Rubella is a highly contagious childhood disease that causes relatively mild symptoms. However, rubella can result in severe congenital defects, known as congenital rubella syndrome (CRS), if transmitted from a mother to a fetus. Consequently, women have higher incentive to vaccinate against rubella than men do. Within the population vaccination reduces transmission but also increases the average age of infection and possibly the risk of CRS among unvaccinated females. To evaluate how the balance among these factors results in optimal coverage of vaccination, we developed a game theoretic age-structured epidemiological model of rubella transmission and vaccination. We found that high levels of vaccination for both genders are most effective in maximizing average utility across the population by decreasing the risk of CRS and reducing transmission of rubella. By contrast, the demands for vaccines driven by self-interest among males and females are $0\%$ and $100\%$ acceptance, respectively, if the cost of vaccination is relatively low. Our results suggest that the rubella vaccination by males that is likely to be achieved on voluntary basis without additional incentives would have been far lower than the population optimum, if rubella vaccine were offered separately instead of combined with measles and mumps vaccination as the MMR vaccine.

Rotavirus, the most common cause of gastroenteritis among children worldwide, is responsible for approximately 600,000 deaths every year worldwide. Clinical trials of RotaTeq and Rotarix, two commercially generated approved vaccines, have shown a high degree of effectiveness in protecting the most vulnerable individuals against rotavirus infections. RotaTeq and Rotarix are now incorporated into the portfolio of vaccines recommended for regular use by infants in the US and Mexico, respectively. The focus here is to evaluate the impact of vaccine-generated herd immunity, a function of the implementation regimes and coverage policies, on rotavirus transmission dynamics at the population level. In order to evaluate the overall impact of vaccine regimes in the US and Mexico, we develop an age-structured epidemiological model of rotavirus transmission that includes age-specific vaccination rates. This model is parameterized using available epidemiological and vaccine data. Numerical simulations of the parameterized model support the conclusion that reasonable rotavirus vaccination programs can prevent a significant fraction of primary (severe) rotavirus infections in the US and Mexico. Vaccination is likely to have stronger positive impact in Mexico than in the US, because the prevalence of rotavirus infections is higher in Mexico and demographics are distinct in two countries. It is shown that the age distribution of rotavirus cases will shift as a result of vaccination. This shift will be accompanied with decreases in the proportion of primary infections and the change in the distribution of subsequent infections. Effective vaccination regimes tend to increase the average age of both primary and subsequent infections. The observed shifts reduce the average population risk because severity tends to decrease with age.

The recent approval of a rotavirus vaccine in Mexico motivates this study on the potential impact of the use of such a vaccine on rotavirus prevention and control. An age-structured model that describes the rotavirus transmission dynamics of infections is introduced. Conditions that guarantee the local and global stability analysis of the disease-free steady state distribution as well as the existence of an endemic steady state distribution are established. The impact of maternal antibodies on the implementation of vaccine is evaluated. Model results are used to identify optimal age-dependent vaccination strategies. A convergent numerical scheme for the model is introduced but not implemented. This paper is dedicated to Prof. K. P. Hadeler, who continues to push the frontier of knowledge in mathematical biology.

Animal reservoirs for infectious diseases pose ongoing risks to human populations. In this theory of zoonoses, the introduction event that starts an epidemic is assumed to be independent of all preceding events. However, introductions are often concentrated in communities that bridge the ecological interfaces between reservoirs and the general population. In this paper, we explore how the risks of disease emergence are altered by the aggregation of introduction events within bridge communities. In viscous bridge communities, repeated introductions can elevate the local prevalence of immunity. This local herd immunity can form a barrier reducing the opportunities for disease emergence. In some situations, reducing exposure rates counterintuitively increases the emergence hazards because of off-setting reductions in local immunity. Increases in population mixing can also increase emergence hazards, even when average contact rates are conserved. Our theory of bridge communities may help guide prevention and explain historical emergence events, where disruption of stable economic, political or demographic processes reduced population viscosity at ecological interfaces.

Background: Over-prescribing of antibiotics is considered to result in increased morbidity and mortality from drug-resistant organisms. A resulting common wisdom is that it would be better for society if physicians would restrain their prescription of antibiotics. In this view, self-interest and societal interest are at odds, making antibiotic use a classic ‘‘tragedy of the commons’’. Methods and Findings: We developed two mathematical models of transmission of antibiotic resistance, featuring de novo development of resistance and transmission of resistant organisms. We analyzed the decision to prescribe antibiotics as a mathematical game, by analyzing individual incentives and community outcomes. Conclusions: A conflict of interest may indeed result, though not in all cases. Increased use of antibiotics by individuals benefits society under certain circumstances, despite the amplification of drug-resistant strains or organisms. In situations where increased use of antibiotics leads to less favorable outcomes for society, antibiotics may be harmful for the individual as well. For other scenarios, where a conflict between self-interest and society exists, restricting antibody use would benefit society. Thus, a case-by-case assessment of appropriate use of antibiotics may be warranted.

Early observations from countries that have introduced rotavirus vaccination suggest that there may be indirect protection for unvaccinated individuals, but it is unclear whether these benefits will extend to the long term. Transmission dynamic models have attempted to quantify the indirect protection that might be expected from rotavirus vaccination in developed countries, but results have varied. To better understand the magnitude and sources of variability in model projections, we undertook a comparative analysis of transmission dynamic models for rotavirus. We fit five models to reported rotavirus gastroenteritis (RVGE) data from England and Wales, and evaluated outcomes for short- and long-term vaccination effects. All of our models reproduced the important features of rotavirus epidemics in England and Wales. Models predicted that during the initial year after vaccine introduction, incidence of severe RVGE would be reduced 1.8-2.9 times more than expected from the direct effects of the vaccine alone (28-50% at 90% coverage), but over a 5-year period following vaccine introduction severe RVGE would be reduced only by 1.1-1.7 times more than expected from the direct effects (54-90% at 90% coverage). Projections for the long-term reduction of severe RVGE ranged from a 55% reduction at full coverage to elimination with at least 80% coverage. Our models predicted short-term reductions in the incidence of RVGE that exceeded estimates of the direct effects, consistent with observations from the United States and other countries. Some of the models predicted that the short-term indirect benefits may be offset by a partial shifting of the burden of RVGE to older unvaccinated individuals. Nonetheless, even when such a shift occurs, the overall reduction in severe RVGE is considerable. Discrepancies among model predictions reflect uncertainties about age variation in the risk and reporting of RVGE, and the duration of natural and vaccine-induced immunity, highlighting important questions for future research.