Evaluating the cost-effectiveness of HPV vaccination for adolescent girls in Japan: A comparison of 2-valent, 4-valent, and 9-valent HPV vaccines with consideration of cross-protection.

OBJECTIVE: In April 2023, the Japanese Health Ministry panel approved the inclusion of the 9-valent human papillomavirus (9vHPV) vaccine in the National Immunization Program, alongside the 2-valent (2vHPV) and 4-valent HPV (4vHPV) vaccines. In response to this, we evaluated the cost-effectiveness of these three vaccines for routine immunization of girls aged 12-16 in Japan, considering the cross-protection of 2vHPV and 4vHPV vaccines. METHODS: We constructed an age-structured mathematical model for HPV transmission, aiming to quantify the economic and epidemiological effects of various HPV vaccination strategies over a 70-year period in Japan. We determined incremental costs and quality-adjusted life years (QALYs) for each strategy, applying a 3% annual discount. Univariate and probabilistic sensitivity analyses were conducted to assess the uncertainty of our model results, with all evaluations done in 2023. RESULTS: Our projections indicate that the HPV vaccination program in Japan will significantly reduce the incidence of HPV-related diseases. All HPV vaccination strategies, using the 2vHPV, 4vHPV, and 9vHPV vaccines, were found to be cost-effective compared to no vaccination, with incremental cost-effectiveness ratios of ¥971,447/QALY, ¥1,237,297/QALY, and ¥742,084/QALY, respectively. Direct comparisons between vaccines demonstrated that the 9vHPV vaccination was more cost-effective than the 2vHPV vaccination, whereas 4vHPV vaccination was dominated by 2vHPV vaccination. CONCLUSIONS: Our study validates the cost-effectiveness of implementing the 9vHPV vaccine as the primary option over the 2vHPV or 4vHPV vaccine for girls in Japan. These findings underscore the need to improve the acceptance rate and coverage of HPV vaccinations in the country.

Optimal strategies for social distancing and testing to control COVID-19.

The coronavirus disease (COVID-19) has infected more than 79 million individuals, with 1.7 million 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 given the substantial societal and economic impacts associated with infection and interventions. 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.

Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study.

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.

Optimal strategies for vaccination and social distancing in a game-theoretic epidemiologic model.

For various infectious diseases, vaccination has become a major intervention strategy. However, the importance of social distancing has recently been highlighted during the ongoing COVID-19 pandemic. In the absence of vaccination, or when vaccine efficacy is poor, social distancing may help to curb the spread of new virus strains. However, both vaccination and social distancing are associated with various costs. It is critical to consider these costs in addition to the benefits of these strategies when determining the optimal rates of application of control strategies. We developed a game-theoretic epidemiological model that considers vaccination and social distancing under the assumption that individuals pursue the maximization of payoffs. By using this model, we identified the individually optimal strategy based on the Nash strategy when both strategies are available and when only one strategy is available. Furthermore, we determined the relative costs of control strategies at which individuals preferentially adopt vaccination over social distancing (or vice versa).

Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study.

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 <5. 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; P<.001) and age groups ≤29 years (r=0.726-0.821; P<.001), 30-44 years (r=0.701-0.826; P<.001), and ≥50 years (r=0.706-0.725; P<.001). In terms of spatial distribution, internet search data were higher in affected areas. Moreover, greater correlations were found in mobile searches (r=0.704-0.804; P<.001) compared to those of desktop searches (r=0.705-0.717; P<.001), indicating changing behaviors in searching for online health information during the outbreak. These varied internet searches related to COVID-19 represented community health risk perceptions. In addition, as a country with a high number of coronavirus tests, results showed that adults perceived coronavirus test-related information as being more important than disease-related knowledge. Meanwhile, younger, and older age groups had different perceptions. Moreover, NAVER RSVs can potentially be used for health risk perception assessments and disease predictions. Adding COVID-19-related searches provided by NAVER could increase the performance of the model compared to that of the COVID-19 case-based model and potentially be used to predict epidemic curves. 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.

Does Choice of Influenza Vaccine Type Change Disease Burden and Cost-Effectiveness in the United States? An Agent-Based Modeling Study.

Offering a choice of influenza vaccine type may increase vaccine coverage and reduce disease burden, but it is more costly. This study calculated the public health impact and cost-effectiveness of 4 strategies: no choice, pediatric choice, adult choice, or choice for both age groups. Using agent-based modeling, individuals were simulated as they interacted with others, and influenza was tracked as it spread through a population in Washington, DC. Influenza vaccination coverage derived from data from the Centers for Disease Control and Prevention was increased by 6.5% (range, 3.25%-11.25%), reflecting changes due to vaccine choice. With moderate influenza infectivity, the number of cases averaged 1,117,285 for no choice, 1,083,126 for pediatric choice, 1,009,026 for adult choice, and 975,818 for choice for both age groups. Averted cases increased with increased coverage and were highest for the choice-for-both-age-groups strategy; adult choice also reduced cases in children. In cost-effectiveness analysis, choice for both age groups was dominant when choice increased vaccine coverage by ≥3.25%. Offering a choice of influenza vaccines, with reasonable resultant increases in coverage, decreased influenza cases by >100,000 with a favorable cost-effectiveness profile. Clinical trials testing the predictions made based on these simulation results and deliberation of policies and procedures to facilitate choice should be considered.

Qualitative Effects of Monovalent Vaccination Against Rotavirus: A Comparison of North America and South America.

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.

Population viscosity suppresses disease emergence by preserving local herd immunity.

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.

Assessing the transmission potential of mpox in East Asia during 2022-2023: A focus on Taiwan, China, Japan, and South Korea.

OBJECTIVES: This study aims to estimate the transmission potential of mpox in East Asia, focusing on the hardest hit nations: Taiwan, China, Japan, and South Korea. METHODS: We utilized six phenomenological dynamic growth models to fit the case incidence during the initial 30 epidemic days. The best-fit model was selected to calculate the reproduction number (R t ). Additionally, we used the latest case data and a Bayesian framework to compute the instantaneous effective R t by applying the Cori et al. RESULTS: During the early phase, China demonstrated the highest estimated R t of 2.89 (95% CI: 1.44-3.33); followed by South Korea, 2.18 (95% CI: 0.96-3.57); Japan, 1.73 (95% CI: 0.66-3.94); and Taiwan, 1.36 (95% CI: 0.71-3.30). However, by June 30, 2023, estimated R t dropped below 1.00 in all countries: China at 0.05 (95% credible interval [CrI]: 0.02-0.10), Japan at 0.32 (95% CrI: 0.15-0.59), South Korea at 0.23 (95% CrI: 0.11-0.42), and Taiwan at 0.41 (95% CrI: 0.31-0.53), indicating the potential decline of the outbreak. CONCLUSIONS: Our analysis shows effective containment by each country. It is crucial to sustain effective management to ensure the ultimate eradication of the outbreak.

Cost-effectiveness of the adjuvanted quadrivalent influenza vaccine for older adults in South Korea.

South Korea's National Immunization Program administers the quadrivalent influenza vaccine (QIV) to manage seasonal influenza, with a particular focus on the elderly. After reviewing the safety and immune response triggered by the adjuvanted QIV (aQIV) in individuals aged 65 and older, the Ministry of Food and Drug Safety in Korea approved its use. However, the extensive impact of aQIV on public health is yet to be fully understood. This study assessed the cost-effectiveness of replacing QIV with aQIV in South Korean adults aged 65 years and older. A dynamic transmission model, calibrated with national influenza data, was applied to compare the influence of aQIV and QIV on older adults and the broader population throughout a single influenza season. This study considered both the direct and indirect effects of vaccination on the elderly. We derived the incremental cost-effectiveness ratios (ICERs) from quality-adjusted life-years (QALYs) and costs incurred, validated through a probabilistic sensitivity analysis with 5,000 simulations. Findings suggest that transitioning to aQIV from QIV in the elderly would be cost-effective, particularly if aQIV's efficacy reaches or exceeds 56.1%. With an ICER of $29,267/QALY, considerably lower than the $34,998/QALY willingness-to-pay threshold, aQIV presents as a cost-effective option. Thus, implementing aQIV with at least 56.1% efficacy is beneficial from both financial and public health perspectives in mitigating seasonal influenza in South Korea.

Cost-Effectiveness of Human Papillomavirus Vaccination in the UK: Two Versus Single-Dose of Nonavalent HPV Vaccination.

INTRODUCTION: The UK implemented a single-dose HPV vaccination policy in September 2023, aiming for sustained protection, better vaccine coverage, and reduced healthcare costs. This research assesses the cost-effectiveness of both one-dose and two-dose schedules from a healthcare perspective. METHODS: Using an age-structured dynamic model, the study analyzed long-term health and economic outcomes of these two different vaccination approaches. It focused on the effects of vaccinating 12- to 13-year-olds with the 9-valent HPV vaccine in either single-dose or two-dose regimens from 2023 to 2093. The analysis, conducted in 2023-2024, explored different immunity durations (10, 30 years, or lifetime) and efficacy levels for the single-dose strategy. RESULTS: The study indicated that in the UK, vaccinating 12- to 13-year-olds with a two-dose regimen is not considered cost-effective compared to the single-dose option, assumed to be 90% as effective for 10 years. The incremental cost-effectiveness ratios for two doses ranged from £230,903 to £1,082,916 per quality-adjusted life year (QALY), significantly exceeding the UK's £20,000/QALY willingness-to-pay threshold. Over 70 years, a switch from a two-dose to a single-dose vaccination schedule could potentially lead to savings of over £1,073 million in the healthcare system. Furthermore, the single-dose regimen was cost-effective compared to no vaccination, with an incremental cost-effectiveness ratio below £2,040/QALY. CONCLUSIONS: The study affirms the cost-effectiveness of the UK's single-dose HPV vaccine, in sync with its September 2023 policy shift. The shift not only provides financial benefits but also simplifies vaccine administration, strategically reducing HPV's epidemiological and economic impacts.

Comparative Effects of Bivalent, Quadrivalent, and Nonavalent Human Papillomavirus Vaccines in The Prevention of Genotype-Specific Infection: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Human papillomavirus (HPV) infection is a major global disease burden and the main cause of cervical cancer. Certain HPV genotypes, with are the most common etiologic pathogens and cause a significant disease burden, are being targeted for vaccine development. However, few studies have focused on the comparative effectiveness of the bivalent HPV (2v-HPV), quadrivalent HPV (4v-HPV), and nonavalent HPV (9v-HPV) vaccines against HPV strain-specific infection. This study investigated the comparative effects of these vaccines against genotype-specific infection. MATERIALS AND METHODS: We conducted a pairwise and network meta-analysis of published randomized clinical trials of HPV vaccines according to sex and HPV infection status for nine HPV genotypes (HPV 6/11/16/18/31/33/45/52/58). RESULTS: Overall, 10 randomized controlled trials (12 articles) were included in this study. In the network meta-analysis, no statistically significant differences were observed in the prevention of carcinogenic HPV strains (16/18/31/33/45/52/58) between the 2v-HPV and 4v-HPV vaccines in female HPV infection-naïve populations. However, the 9v-HPV vaccine showed a significantly superior effect compared with 2v-HPV and 4v-HPV vaccines in preventing HPV 31/33/45/52/58 infections. Although 2v-HPV and 4v-HPV vaccines provided some cross-protection against HPV 31/33/45/52/58 infections, the effect was significant only on HPV 31 infection. For HPV 16 and 18, neither statistically significant nor small differences were found in the prevention of HPV infection among the 2v-HPV, 4v-HPV, and 9v-HPV vaccines. CONCLUSION: Our study complements previous understanding of how the effect of HPV vaccines differs according to the HPV genotype. This is important because HPV genotype prevalence varies among countries. We advocate for continued efforts in vaccinating against HPV, while public health agencies should consider the difference in the vaccine effect and HPV genotype prevalence when implementing HPV vaccination in public vaccination programs.

Assessing the cost-effectiveness of annual COVID-19 booster vaccination in South Korea using a transmission dynamic model.

Introduction: We evaluated the cost-effectiveness of South Korea's planned annual coronavirus disease 2019 (COVID-19) booster campaign scheduled for October 2023. Materials and methods: An age-structured mathematical model was used to analyze the public impacts and cost-effectiveness of vaccination across three vaccination strategies: uniform allocation and prioritizing those over 65 or those over 50 years old. We calculated the incremental cost per quality-adjusted life year (QALY) from both healthcare and societal perspectives. The maximum vaccine cost for cost-effectiveness was also identified. Results: Our analysis highlights the cost-effectiveness of South Korea's annual COVID-19 vaccination program in mitigating health and economic impacts. The most cost-effective strategy is uniform vaccine allocation, offering the lowest incremental cost-effectiveness ratio (ICER) at US$ 25,787/QALY. However, with a relatively high attack rate, the strategy prioritizing individuals over 65 years emerges as more cost-effective, lowering the ICER to US$ 13,785/QALY. Prioritizing those over 50 was less cost-effective. All strategies were cost-saving from a societal perspective, with cost-effectiveness being more sensitive to vaccine price than to its effectiveness. Discussion: Our results imply a potential strategy shift in current vaccination plan, with uniform vaccine distribution being more cost-effective than prioritizing older adults. Early estimation of viral transmissibility and vaccine effectiveness is crucial in determining the most cost-effective vaccine allocation approach.

A game dynamic model for vaccine skeptics and vaccine believers: measles as an example.

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.

Erratic flu vaccination emerges from short-sighted behavior in contact networks.

The effectiveness of seasonal influenza vaccination programs depends on individual-level compliance. Perceptions about risks associated with infection and vaccination can strongly influence vaccination decisions and thus the ultimate course of an epidemic. Here we investigate the interplay between contact patterns, influenza-related behavior, and disease dynamics by incorporating game theory into network models. When individuals make decisions based on past epidemics, we find that individuals with many contacts vaccinate, whereas individuals with few contacts do not. However, the threshold number of contacts above which to vaccinate is highly dependent on the overall network structure of the population and has the potential to oscillate more wildly than has been observed empirically. When we increase the number of prior seasons that individuals recall when making vaccination decisions, behavior and thus disease dynamics become less variable. For some networks, we also find that higher flu transmission rates may, counterintuitively, lead to lower (vaccine-mediated) disease prevalence. Our work demonstrates that rich and complex dynamics can result from the interaction between infectious diseases, human contact patterns, and behavior.

Proportion of Pre-Symptomatic Transmission Events Associated with COVID-19 in South Korea.

Pre-symptomatic transmission potentially reduces the effectiveness of symptom-onset-based containment and control strategies for the coronavirus disease (COVID-19). Despite evidence from multiple settings, the proportion of pre-symptomatic transmission varies among countries. To estimate the extent of pre-symptomatic transmission in South Korea, we used individual-level COVID-19 case records from the Korea Disease Control and Prevention Agency and Central Disease Control Headquarters. We inferred the probability of symptom onset per day since infection based on the density distribution of the incubation period to stratify the serial interval distribution in Period 1 (20 January-10 February 2020) and Period 2 (25 July-4 December 2021), without and with expanded testing or implementation of social distancing strategies, respectively. Assuming both no correlation as well as positive and negative correlations between the incubation period and the serial interval, we estimated the proportion of pre-symptomatic transmission in South Korea as 43.5% (accounting for correlation, range: 9.9-45.4%) and 60.0% (56.2-64.1%) without and with expanded testing, respectively, during the Delta variant's predominance. This study highlights the importance of considering pre-symptomatic transmission for COVID-19 containment and mitigation strategies because pre-symptomatic transmission may play a key role in the epidemiology of COVID-19.

Clinical Time Delay Distributions of COVID-19 in 2020-2022 in the Republic of Korea: Inferences from a Nationwide Database Analysis.

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.

Transmission Potential of the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2 in South Korea, 25 November 2021-8 January 2022.

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.

An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020-2021.

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<1.0 as of October 31, 2021. On the forecasting front, the sub-epidemic model performs best at capturing the 30-day ahead COVID-19 trajectory compared to the Richards and generalized logistic growth model. Nevertheless, the spatial variability in the incidence rate patterns across different departments can be grouped into four distinct clusters. As the case incidence surged in July 2020, an increase in mobility patterns was also observed. On the contrary, 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, indicating the pandemic fatigue in the country.

Optimal H1N1 vaccination strategies based on self-interest versus group interest.

BACKGROUND: Influenza vaccination is vital for reducing H1N1 infection-mediated morbidity and mortality. To reduce transmission and achieve herd immunity during the initial 2009-2010 pandemic season, the US Centers for Disease Control and Prevention (CDC) recommended that initial priority for H1N1 vaccines be given to individuals under age 25, as these individuals are more likely to spread influenza than older adults. However, due to significant delay in vaccine delivery for the H1N1 influenza pandemic, a large fraction of population was exposed to the H1N1 virus and thereby obtained immunity prior to the wide availability of vaccines. This exposure affects the spread of the disease and needs to be considered when prioritizing vaccine distribution. METHODS: To determine optimal H1N1 vaccine distributions based on individual self-interest versus population interest, we constructed a game theoretical age-structured model of influenza transmission and considered the impact of delayed vaccination. RESULTS: Our results indicate that if individuals decide to vaccinate according to self-interest, the resulting optimal vaccination strategy would prioritize adults of age 25 to 49 followed by either preschool-age children before the pandemic peak or older adults (age 50-64) at the pandemic peak. In contrast, the vaccine allocation strategy that is optimal for the population as a whole would prioritize individuals of ages 5 to 64 to curb a growing pandemic regardless of the timing of the vaccination program. CONCLUSIONS: Our results indicate that for a delayed vaccine distribution, the priorities that are optimal at a population level do not align with those that are optimal according to individual self-interest. Moreover, the discordance between the optimal vaccine distributions based on individual self-interest and those based on population interest is even more pronounced when vaccine availability is delayed. To determine optimal vaccine allocation for pandemic influenza, public health agencies need to consider both the changes in infection risks among age groups and expected patterns of adherence.