Evaluating infectious disease outbreak potential and mitigation effectiveness on cruise ships.

The cruise ship sector is a major part of the tourism industry, and an estimated over 30 million passengers are transformed worldwide each year. Cruise ships bring diverse populations into proximity for many days, facilitating the transmission of respiratory illnesses. The objective of this study is to develop a modeling framework to inform the development of viable disease risk management policies and measures to control disease outbreaks on cruises. Our model, parameterized and calibrated using the data of the COVID-19 outbreak on the Diamond Princess cruise ship in 2020, is used to assess the impact of the mitigation measures such as mask wearing, vaccination, on-board and pre-traveling testing measures. Our results indicate mask wearing in public places as the cheapest and most affordable measure can drop the number of cumulative confirmed cases by almost 50%. This measure along with the vaccination by declining the number of the cumulative confirmed cases by more than 94% is the most effective measure to control outbreaks on cruises. According to our findings, outbreaks are more predominant in the passenger population than the crew members, however, the protection measures are more beneficial if they are applied by both crew members and passengers. Regarding the testing measure, pre-traveling testing is more functional than the on-board testing to control outbreaks on cruises.

Population mobility, well-mixed clustering and disease spread: a look at COVID-19 Spread in the United States and preventive policy insights.

The epidemiology of pandemics is classically viewed using geographical and political borders; however, these artificial divisions can result in a misunderstanding of the current epidemiological state within a given region. To improve upon current methods, we propose a clustering algorithm which is capable of recasting regions into well-mixed clusters such that they have a high level of interconnection while minimizing the external flow of the population towards other clusters. Moreover, we analyze and identify so-called core clusters, clusters that retain their features over time (temporally stable) and independent of the presence or absence of policy measures. In order to demonstrate the capabilities of this algorithm, we use USA county-level cellular mobility data to divide the country into such clusters. Herein, we show a more granular spread of SARS-CoV-2 throughout the first weeks of the pandemic. Moreover, we are able to identify areas (groups of counties) that were experiencing above average levels of transmission within a state, as well as pan-state areas (clusters overlapping more than one state) with very similar disease spread. Therefore, our method enables policymakers to make more informed decisions on the use of public health interventions within their jurisdiction, as well as guide collaboration with surrounding regions to benefit the general population in controlling the spread of communicable diseases.

Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup.

The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.

Influenza vaccine in chronic obstructive pulmonary disease among elderly male veterans.

BACKGROUND: Prior studies have established those elderly patients with chronic obstructive pulmonary disease (COPD) are at elevated risk for developing influenza-associated complications such as hospitalization, intensive-care admission, and death. This study sought to determine whether influenza vaccination could improve survival among elderly patients with COPD. MATERIALS/METHODS: This study included Veterans (age ≥ 65 years) diagnosed with COPD that received care at the United States Veterans Health Administration (VHA) during four influenza seasons, from 2012-2013 to 2015-2016. We linked VHA electronic medical records and Medicare administrative files to Centers for Disease Control and Prevention National Death Index cause of death records as well as influenza surveillance data. A multivariable time-dependent Cox proportional hazards model was used to compare rates of mortality of recipients of influenza vaccination to those who did not have records of influenza vaccination. We estimated hazard ratios (HRs) adjusted for age, gender, race, socioeconomic status, comorbidities, and healthcare utilization. RESULTS: Over a span of four influenza seasons, we included 1,856,970 person-seasons of observation where 1,199,275 (65%) had a record of influenza vaccination and 657,695 (35%) did not have a record of influenza vaccination. After adjusting for comorbidities, demographic and socioeconomic characteristics, influenza vaccination was associated with reduced risk of death during the most severe periods of influenza seasons: 75% all-cause (HR = 0.25; 95% CI: 0.24-0.26), 76% respiratory causes (HR = 0.24; 95% CI: 0.21-0.26), and 82% pneumonia/influenza cause (HR = 0.18; 95% CI: 0.13-0.26). A significant part of the effect could be attributed to "healthy vaccinee" bias as reduced risk of mortality was also found during the periods when there was no influenza activity and before patients received vaccination: 30% all-cause (HR = 0.70; 95% CI: 0.65-0.75), 32% respiratory causes (HR = 0.68; 95% CI: 0.60-0.78), and 51% pneumonia/influenza cause (HR = 0.49; 95% CI: 0.31-0.78). However, as a falsification study, we found that influenza vaccination had no impact on hospitalization due to urinary tract infection (HR = 0.97; 95% CI: 0.80-1.18). CONCLUSIONS: Among elderly patients with COPD, influenza vaccination was associated with reduced risk for all-cause and cause-specific mortality.

"Hot-spotting" to improve vaccine allocation by harnessing digital contact tracing technology: An application of percolation theory.

Vaccinating individuals with more exposure to others can be disproportionately effective, in theory, but identifying these individuals is difficult and has long prevented implementation of such strategies. Here, we propose how the technology underlying digital contact tracing could be harnessed to boost vaccine coverage among these individuals. In order to assess the impact of this "hot-spotting" proposal we model the spread of disease using percolation theory, a collection of analytical techniques from statistical physics. Furthermore, we introduce a novel measure which we call the efficiency, defined as the percentage decrease in the reproduction number per percentage of the population vaccinated. We find that optimal implementations of the proposal can achieve herd immunity with as little as half as many vaccine doses as a non-targeted strategy, and is attractive even for relatively low rates of app usage.

Large-scale frequent testing and tracing to supplement control of Covid-19 and vaccination rollout constrained by supply.

Non-pharmaceutical interventions (NPI) were implemented all around the world in the fight against COVID-19: Social distancing, shelter-in-place, mask wearing, etc. to mitigate transmission, together with testing and contact-tracing to identify, isolate and treat the infected. The majority of countries have relied on the former measures, followed by a ramping up of their testing and tracing capabilities. We present here the cases of South Korea, Italy, Canada and the United States, as a look back to lessons that can be drawn for controlling the pandemic, specifically through the means of testing and tracing. By fitting a disease transmission model to daily case report data in each of the four countries, we first show that their combination of social-distancing and testing/tracing have had a significant impact on the evolution of their first wave of pandemic curves. We then consider the hypothetical scenario where the only NPI measures implemented past the first pandemic wave consisted of isolating individuals due to repeated, country-scale testing and contact tracing, as a mean of lifting social distancing measures without a resurgence of COVID-19. We give estimates on the average isolation rates needed to occur in each country. We find that testing and tracing each individual of a country, on average, every 4.5 days (South Korea), 5.7 days (Canada), 6 days (Italy) and 3.5 days (US), would have been sufficient to mitigate their second pandemic waves. We also considered the situation in Canada to see how a frequent large-scale asymptomatic testing and contact tracing could have been used in combination with vaccination rollout to reduce the infection in the population. This could offer an alternative approach towards preventing and controlling an outbreak when vaccine supply is limited, while testing capacity has been increasingly enhanced.

Laboratory-confirmed influenza infection and acute myocardial infarction among United States senior Veterans.

BACKGROUND: Previous studies established an association between laboratory-confirmed influenza infection (LCI) and hospitalization for acute myocardial infarction (AMI) but not causality. We aimed to explore the underlying mechanisms by adding biological mediators to an established study design used by earlier studies. METHODS: With data on biomarkers, we used a self-controlled case-series design to evaluate the effect of LCI on hospitalization for AMI among Veterans Health Administration (VHA) patients. We included senior Veterans (age 65 years and older) with LCI between 2010 through 2015. Patient-level data from VHA electronic medical records were used to capture laboratory results, hospitalizations, and baseline patient characteristics. We defined the "risk interval" as the first 7 days after specimen collection and the "control interval" as 1 year before and 1 year after the risk interval. More importantly, using mediation analysis, we examined the role of abnormal white blood cell (WBC) and platelet count in the relationship between LCI and AMI to explore the thrombogenic nature of this association, thus potential causality. RESULTS: We identified 391 hospitalizations for AMI that occurred within +/-1 year of a positive influenza test, of which 31 (31.1 admissions/week) occurred during the risk interval and 360 (3.5/per week) during the control interval, resulting in an incidence ratio (IR) for AMI admission of 8.89 (95% confidence interval [CI]: 6.16-12.84). In stratified analyses, AMI risk was significantly elevated among patients with high WBC count (IR, 12.43; 95% CI: 6.99-22.10) and high platelet count (IR, 15.89; 95% CI: 3.59-70.41). CONCLUSION: We confirmed a significant association between LCI and AMI. The risk was elevated among those with high WBC or platelet count, suggesting a potential role for inflammation and platelet activation in the underlying mechanism.

High-dose influenza vaccination and mortality among predominantly male, white, senior veterans, United States, 2012/13 to 2014/15.

IntroductionIt is unclear whether high-dose influenza vaccine (HD) is more effective at reducing mortality among seniors.AimThis study aimed to evaluate the relative vaccine effectiveness (rVE) of HD. MethodsWe linked electronic medical record databases in the Veterans Health Administration (VHA) and Medicare administrative files to examine the rVE of HD vs standard-dose influenza vaccines (SD) in preventing influenza/pneumonia-associated and cardiorespiratory mortality among VHA-enrolled veterans 65 years or older during the 2012/13, 2013/14 and 2014/15 influenza seasons. A multivariable Cox proportional hazards model was performed on matched recipients of HD vs SD, based on vaccination time, location, age, sex, ethnicity and VHA priority level. ResultsAmong 569,552 person-seasons of observation, 207,574 (36%) were HD recipients and 361,978 (64%) were SD recipients, predominantly male (99%) and white (82%). Pooling findings from all three seasons, the adjusted rVE estimate of HD vs SD during the high influenza periods was 42% (95% confidence interval (CI): 24-59) against influenza/pneumonia-associated mortality and 27% (95% CI: 23-32) against cardiorespiratory mortality. Residual confounding was evident in both early and late influenza periods despite matching and multivariable adjustment. Excluding individuals with high 1-year predicted mortality at baseline reduced the residual confounding and yielded rVE of 36% (95% CI: 10-62) and 25% (95% CI: 12-38) against influenza/pneumonia-associated and cardiorespiratory mortality, respectively. These were confirmed by results from two-stage residual inclusion estimations.DiscussionThe HD was associated with a lower risk of influenza/pneumonia-associated and cardiorespiratory death in men during the high influenza period.

Assessing the prior event rate ratio method via probabilistic bias analysis on a Bayesian network.

BACKGROUND: Unmeasured confounders are commonplace in observational studies conducted using real-world data. Prior event rate ratio (PERR) adjustment is a technique shown to perform well in addressing such confounding. However, it has been demonstrated that, in some circumstances, the PERR method actually increases rather than decreases bias. In this work, we seek to better understand the robustness of PERR adjustment. METHODS: We begin with a Bayesian network representation of a generalized observational study, which is subject to unmeasured confounding. Previous work evaluating PERR performance used Monte Carlo simulation to calculate joint probabilities of interest within the study population. Here, we instead use a Bayesian networks framework. RESULTS: Using this streamlined analytic approach, we are able to conduct probabilistic bias analysis (PBA) using large numbers of combinations of parameters and thus obtain a comprehensive picture of PERR performance. We apply our methodology to a recent study that used the PERR in evaluating elderly-specific high-dose (HD) influenza vaccine in the US Veterans Affairs population. That study obtained an HD relative effectiveness of 25% (95% CI: 2%-43%) against influenza- and pneumonia-associated hospitalization, relative to standard-dose influenza vaccine. In this instance, we find that the PERR-adjusted result is more like to underestimate rather than to overestimate the relative effectiveness of the intervention. CONCLUSIONS: Although the PERR is a powerful tool for mitigating the effects of unmeasured confounders, it is not infallible. Here, we develop some general guidance for when a PERR approach is appropriate and when PBA is a safer option.

Analysis of relative effectiveness of high-dose versus standard-dose influenza vaccines using an instrumental variable method.

BACKGROUND: Observational studies of the relative effectiveness of influenza vaccines are essential for public health decision making. Their estimates, however, are subject to bias due to unmeasured confounders. Instrumental variable (IV) methods can control for observed and unobserved confounders. METHODS: We used linked electronic medical record databases in the Veterans Health Administration (VHA) as well as Medicare administrative files to examine the relative vaccine effectiveness (rVE) of high-dose influenza vaccine (HD) versus standard-dose influenza vaccines (SD) in preventing hospitalizations among VHA-enrolled Veterans ≥65 years of age during 5 influenza seasons (2010-2011 through 2014-2015). Using multivariable IV Poisson regression modeling to address unmeasured confounding and bias, we analyzed the data by each season and through longitudinal analysis of all five seasons. FINDINGS: We included 3,638,924 person-influenza seasons of observation where 158,636 (4%) were among HD vaccine recipients and 3,480,288 (96%) were among SD vaccine recipients. Of the 1,728,562 Veterans, 1,702,824 (98.5%) were male and 1,299,412 (75%) were non-Hispanic white. Based on the longitudinal analysis of all five seasons, the IV-adjusted rVE estimate of HD vs. SD was 10% (95% CI, 8-12%) against all-cause hospitalization; 18% (95% CI, 15-21%) against cardiorespiratory-associated hospitalization; and 14% (95% CI, 6-22%) against influenza/pneumonia-associated hospitalization. The findings by season were similar. INTERPRETATION: Our analysis of VHA clinical data collected from approximately 1.7 million Veterans 65 years and older during five seasons demonstrates that high-dose influenza vaccine is more effective than standard-dose influenza vaccines in preventing influenza- or pneumonia-associated hospitalizations, cardiorespiratory hospitalizations, and all-cause hospitalizations.

Relative Vaccine Effectiveness of High-Dose Versus Standard-Dose Influenza Vaccines Among Veterans Health Administration Patients.

Background: We examined whether a high-dose inactivated influenza vaccine was more efficacious in preventing hospitalizations than a standard-dose vaccine in the Veterans Health Administration (VHA) senior population. Methods: This study estimated the relative vaccine effectiveness (rVE) of high dose versus standard dose using a retrospective cohort of VHA patients 65 years of age or older in the 2015-2016 influenza season. To adjust for measured confounders, we matched each high-dose recipient with up to 4 standard-dose recipients vaccinated at the same location within a 2-week period and having 2 or more pre-existing medical comorbidities. We used the previous event rate ratio method (PERR), a type of difference-in-differences analysis, to adjust for unmeasured confounders. Results: We evaluated 104965 standard-dose and 125776 high-dose recipients; matching decreased the population to 49091 standard-dose and 24682 high-dose recipients. The matched, PERR-adjusted rVE was 25% (95% confidence interval [CI], 2%-43%) against influenza- or pneumonia-associated hospitalization, 7% (95% CI, -2% to 14%) against all-cause hospitalization, 14% (95% CI, -8% to 32%) against influenza- or pneumonia-associated outpatient visit, 5% (95% CI, 2%-8%) against all-cause outpatient visit, and 38% (95% CI, -5% to 65%) against laboratory-confirmed influenza. Conclusions: In protecting senior VHA patients against influenza- or pneumonia-associated hospitalization, a high-dose influenza vaccine is more effective than a standard-dose vaccine.

Review of seasonal influenza in Canada: Burden of disease and the cost-effectiveness of quadrivalent inactivated influenza vaccines.

In the 2015/16 influenza season, the Canadian National Advisory Committee on Immunization (NACI) recommended vaccination with quadrivalent inactivated influenza vaccine (QIV) for infants aged 6-23 months and trivalent inactivated influenza vaccines (TIVs) or QIVs in adults. The objective of this review (GSK study identifier: HO-13-14054) is to examine the epidemiology and disease burden of influenza in Canada and the economic benefits of vaccination. To inform this review, we performed a systematic literature search of relevant Canadian literature and National surveillance data. Influenza B viruses from phylogenetically-distinct lineages (B/Yamagata and B/Victoria) co-circulate in Canada, and are an important cause of influenza complications. Modeling studies, including those postdating the search suggest that switching from TIV to QIV in Canada reduces the burden of influenza and would likely be cost-effective. However, more robust real-world outcomes data is required to inform health policy decision makers on appropriate influenza vaccination strategies for Canada.

Cost-effectiveness of seasonal quadrivalent versus trivalent influenza vaccination in the United States: A dynamic transmission modeling approach.

Trivalent inactivated influenza vaccines (IIV3s) protect against 2 A strains and one B lineage; quadrivalent versions (IIV4s) protect against an additional B lineage. The objective was to assess projected health and economic outcomes associated with IIV4 versus IIV3 for preventing seasonal influenza in the US. A cost-effectiveness model was developed to interact with a dynamic transmission model. The transmission model tracked vaccination, influenza cases, infection-spreading interactions, and recovery over 10 y (2012-2022). The cost-effectiveness model estimated influenza-related complications, direct and indirect costs (2013-2014 US$), health outcomes, and cost-effectiveness. Inputs were taken from published/public sources or estimated using regression or calibration. Outcomes were discounted at 3% per year. Scenario analyses tested the reliability of the results. Seasonal vaccination with IIV4 versus IIV3 is predicted to reduce annual influenza cases by 1,973,849 (discounted; 2,325,644 undiscounted), resulting in 12-13% fewer cases and influenza-related complications and deaths. These reductions are predicted to translate into 18,485 more quality-adjusted life years (QALYs) accrued annually for IIV4 versus IIV3. Increased vaccine-related costs ($599 million; 5.7%) are predicted to be more than offset by reduced influenza treatment costs ($699 million; 12.2%), resulting in direct medical cost saving annually ($100 million; 0.6%). Including indirect costs, savings with IIV4 are predicted to be $7.1 billion (5.6%). Scenario analyses predict IIV4 to be cost-saving in all scenarios tested apart from low infectivity, where IIV4 is predicted to be cost-effective. In summary, seasonal influenza vaccination in the US with IIV4 versus IIV3 is predicted to improve health outcomes and reduce costs.

Cost-effectiveness evaluation of quadrivalent influenza vaccines for seasonal influenza prevention: a dynamic modeling study of Canada and the United Kingdom.

BACKGROUND: The adoption of quadrivalent influenza vaccine (QIV) to replace trivalent influenza vaccine (TIV) in immunization programs is growing worldwide, thus helping to address the problem of influenza B lineage mismatch. However, the price per dose of QIV is higher than that of TIV. In such circumstances, cost-effectiveness analyses provide important and relevant information to inform national health recommendations and implementation decisions. This analysis assessed potential vaccine impacts and cost-effectiveness of a country-wide switch from TIV to QIV, in Canada and the UK, from a third-party payer perspective. METHODS: An age-stratified, dynamic four-strain transmission model which incorporates strain interaction, transmission-rate seasonality and age-specific mixing in the population was used. Model input data were obtained from published literature and online databases. In Canada, we evaluated a switch from TIV to QIV in the entire population. For the UK, we considered two strategies: Children aged 2-17 years who receive the live-attenuated influenza vaccine (LAIV) switch to the quadrivalent formulation (QLAIV), while individuals aged > 18 years switch from TIV to QIV. Two different vaccination uptake scenarios in children (UK1 and UK2, which differ in the vaccine uptake level) were considered. Health and cost outcomes for both vaccination strategies, and the cost-effectiveness of switching from TIV/LAIV to QIV/QLAIV, were estimated from the payer perspective. For Canada and the UK, cost and outcomes were discounted using 5 % and 3.5 % per year, respectively. RESULTS: Overall, in an average influenza season, our model predicts that a nationwide switch from TIV to QIV would prevent 4.6 % influenza cases, 4.9 % general practitioner (GP) visits, 5.7 % each of emergency room (ER) visits and hospitalizations, and 6.8 % deaths in Canada. In the UK (UK1/UK2), implementing QIV would prevent 1.4 %/1.8 % of influenza cases, 1.6 %/2.0 % each of GP and ER visits, 1.5 %/1.9 % of hospitalizations and 4.3 %/4.9 % of deaths. Discounted incremental cost-utility ratios of $7,961 and £7,989/£7,234 per quality-adjusted life-year (QALY) gained are estimated for Canada and the UK (UK1/UK2), both of which are well within their respective cost-effectiveness threshold values. CONCLUSIONS: Switching from TIV to QIV is expected to be a cost-effective strategy to further reduce the burden of influenza in both countries.

Gas disks to gas giants: simulating the birth of planetary systems.

The ensemble of now more than 250 discovered planetary systems displays a wide range of masses, orbits and, in multiple systems, dynamical interactions. These represent the end point of a complex sequence of events, wherein an entire protostellar disk converts itself into a small number of planetary bodies. Here, we present self-consistent numerical simulations of this process, which produce results in agreement with some of the key trends observed in the properties of the exoplanets. Analogs to our own solar system do not appear to be common, originating from disks near the boundary between barren and (giant) planet-forming.