Design and interpretation of vaccine field studies

Effectiveness of enterovirus A71 vaccine against pediatric HFMD and disease profile of post-vaccination infection

BACKGROUND

Vaccination has been proven effective against infection with enterovirus A71 (EV-A71) in clinical trials, but vaccine effectiveness in real-world situations remains incompletely understood. Furthermore, it is not clear whether previous vaccination will result in symptom attenuation among post-vaccinated cases.

METHODS

Based on long-term data extracted from the only designed referral hospital for infectious diseases, we used a test-negative case-control design and multivariate logistic regression models to analyze the effectiveness of EV-A71 vaccine against hand, foot and mouth disease (HFMD). And then, generalized linear regression models were used to evaluate the associations between prior vaccination and disease profiles.

RESULTS

We selected 4883 inpatients for vaccine efficacy estimations and 2188 inpatients for disease profile comparisons. Vaccine effectiveness against EV-A71-induced HFMD for complete vaccination was 63.4 % and 51.7 % for partial vaccination. The vaccine effectiveness was higher among cases received the first dose within 12 months. No protection was observed against coxsackievirus (CV) A6-, CV-A10- or CV-A16-associated HFMD among children regardless of vaccination status. Completely vaccinated cases had shorter hospital stay and disease course compared to unvaccinated cases (P < 0.05).

CONCLUSIONS

These findings reiterate the need to continue the development of a multivalent vaccine or combined vaccines, and have implications for introducing optimized vaccination strategies.

The effectiveness of vaccination for preventing hospitalisation with COVID-19 in regional Queensland: a data linkage study

OBJECTIVE

To estimate the effectiveness of vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for protecting people in a largely coronavirus disease 2019 (COVID-19)-naïve regional population from hospitalisation with symptomatic COVID-19.

DESIGN

Retrospective cohort study; analysis of positive SARS-CoV-2 polymerase chain reaction (PCR) test results linked with Central Queensland hospitals admissions data and Australian Immunisation Register data.

SETTING, PARTICIPANTS

Adult residents of Central Queensland, 1 January - 31 March 2022.

MAIN OUTCOME MEASURES

Vaccine effectiveness (1 - relative risk of hospitalisation for vaccinated and unvaccinated people) with respect to protecting against hospitalisation with symptomatic COVID-19 after primary vaccination course only (two doses of an approved SARS-CoV-2 vaccine) and after a booster vaccine dose.

RESULTS

Positive SARS-CoV-2 test results were recorded during 1 January - 31 March 2022 for 9682 adults, 7244 of whom had been vaccinated (75%); 5929 people were aged 40 years or younger (62%), 5180 were women (52%). Forty-seven people were admitted to hospital with COVID-19 (0.48%), four required intensive care (0.04%); there were no in-hospital deaths. Vaccine effectiveness was 69.9% (95% confidence interval [CI], 44.3-83.8%) for people who had received only a primary vaccination course and 81.8% (95% CI, 39.5-94.5%) for people who had also received a booster. Of the 665 Aboriginal and Torres Strait Islander adults with positive SARS-CoV-2 test results, 401 had been vaccinated (60%). Six Indigenous people were hospitalised with symptomatic COVID-19 (0.9%); vaccine effectiveness was 69.4% (95% CI, -56.5% to 95.8%) for Indigenous people who had received a primary vaccination course only or the primary course and a booster.

CONCLUSION

The hospitalisation rate for Central Queensland people with PCR-confirmed Omicron variant SARS-CoV-2 infections during the first quarter of 2022 was low, indicating the protection afforded by vaccination and the value of booster vaccine doses.

The need for a clinical case definition in test-negative design studies estimating vaccine effectiveness

Test negative studies have been used extensively for the estimation of COVID-19 vaccine effectiveness (VE). Such studies are able to estimate VE against medically-attended illness under certain assumptions. Selection bias may be present if the probability of participation is associated with vaccination or COVID-19, but this can be mitigated through use of a clinical case definition to screen patients for eligibility, which increases the likelihood that cases and non-cases come from the same source population. We examined the extent to which this type of bias could harm COVID-19 VE through systematic review and simulation. A systematic review of test-negative studies was re-analysed to identify studies ignoring the need for clinical criteria. Studies using a clinical case definition had a lower pooled VE estimate compared with studies that did not. Simulations varied the probability of selection by case and vaccination status. Positive bias away from the null (i.e., inflated VE consistent with the systematic review) was observed when there was a higher proportion of healthy, vaccinated non-cases, which may occur if a dataset contains many results from asymptomatic screening in settings where vaccination coverage is high. We provide an html tool for researchers to explore site-specific sources of selection bias in their own studies. We recommend all groups consider the potential for selection bias in their vaccine effectiveness studies, particularly when using administrative data.

Effectiveness of the strain 919 bovine ephemeral fever virus vaccine in the face of a real-world outbreak: A field study in Israeli dairy herds

Bovine ephemeral fever virus (BEFV) is a globally spread arthropod-borne RNA virus that has significant economic impacts on the cattle industry. A live attenuated commercial BEF vaccine, based on the Australian BEFV strain 919, is widely used in Israel and other countries. A previous study has suggested the high effectiveness of this vaccine (ULTRAVAC BEF VACCINE™ from Zoetis®), but anecdotal reports of high BEF morbidity among vaccinated dairy herds in Israel casted doubt on these findings. To resolve this uncertainty, a randomized controlled field vaccine effectiveness study was conducted in Israel during a BEF outbreak which occurred in 2021. Eleven dairy herds were enrolled and monitored for BEF-associated morbidity and rumination alteration patterns using electronic monitoring tags (HR Tags, SCR® Dairy, Netanya, Israel). Four of the herds were naturally infected with BEFV during the outbreak, resulting in a total of 120 vaccinated and 311 unvaccinated subjects that were included in the effectiveness study. A mixed-effect Cox proportional hazard regression model was used to calculate the overall hazard ratio between vaccinated and unvaccinated cattle. This analysis demonstrated an average vaccine effectiveness of 60 % (95 % CI = 38 %-77 %) for preventing clinical disease. In addition, a non-statistically significant trend (p = 0.1) towards protection from mortality was observed, with no observation of mortality among the vaccinated groups compared to 2.61 % mortality (7/311) among the unvaccinated subjects. One hundred and thirty vaccinated and unvaccinated calves from affected and non-affected herds and with different status of morbidity were sampled and analysed by serum-neutralization test. The highest titers of BEFV-neutralizing antibodies were found in subjects that were both vaccinated and clinically affected, indicating a booster effect after vaccination. The results of the study provide evidence for the moderate effectiveness of the ULTRAVAC BEF VACCINE™ for the prevention of BEF.

Testing Whether Higher Contact Among the Vaccinated Can Be a Mechanism for Observed Negative Vaccine Effectiveness

Evidence from early observational studies suggested negative vaccine effectiveness (${V}_{Eff}$) for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant. Since true ${V}_{Eff}$ is unlikely to be negative, we explored how differences in contact among vaccinated persons (e.g., potentially from the implementation of vaccine mandates) could lead to observed negative ${V}_{Eff}$. Using a susceptible-exposed-infectious-recovered (SEIR) transmission model, we examined how vaccinated-contact heterogeneity, defined as an increase in the contact rate only between vaccinated individuals, interacted with 2 mechanisms of vaccine efficacy: vaccine efficacy against susceptibility ($V{E}_S$) and vaccine efficacy against infectiousness ($V{E}_I$), to produce underestimated and in some cases, negative measurements of ${V}_{Eff}$. We found that vaccinated-contact heterogeneity led to negative estimates when $V{E}_I$, and especially $V{E}_S$, were low. Moreover, we determined that when contact heterogeneity was very high, ${V}_{Eff}$ could still be underestimated given relatively high vaccine efficacies (0.7), although its effect on ${V}_{Eff}$ was strongly reduced. We also found that this contact heterogeneity mechanism generated a signature temporal pattern: The largest underestimates and negative measurements of ${V}_{Eff}$ occurred during epidemic growth. Overall, our research illustrates how vaccinated-contact heterogeneity could have feasibly produced negative measurements during the Omicron period and highlights its general ability to bias observational studies of ${V}_{Eff}$.

Vaccine efficacy at a point in time

Vaccine trials are generally designed to assess efficacy on clinical disease. The vaccine effect on infection, while important both as a proxy for transmission and to describe a vaccine's entire effects, requires frequent (e.g., twice a week) longitudinal sampling to capture all infections. Such sampling may not always be feasible. A logistically easy approach is to collect a sample to test for infection at a regularly scheduled visit. Such point or cross-sectional sampling does not permit estimation of classic vaccine efficacy on infection, as long duration infections are sampled with higher probability. Building on work by Rinta-Kokko and others (2009) and Lipsitch and Kahn (2021), we evaluate proxies of the vaccine effect on transmission at a point in time; the vaccine efficacy on prevalent infection and on prevalent viral load, VE$_{\rm PI}$ and VE$_{\rm PVL}$, respectively. Longer infections with higher viral loads should have more transmission potential and prevalent vaccine efficacy naturally captures this aspect. We demonstrate how these parameters obtain from an underlying proportional hazards model for infection and allow for waning efficacy on infection, duration, and viral load. We estimate these parameters based on regression models with either repeated cross-sectional sampling or frequent longitudinal sampling. We evaluate the methods by simulation and analyze a phase III vaccine trial with polymerase chain reaction (PCR) cross-sectional sampling for subclinical infection.

Revisiting assumptions in test-negative studies for estimating vaccine effectiveness: the need for a clinical case definition

Test negative studies have been used extensively for the estimation of COVID-19 vaccine effectiveness (VE). Such studies are able to estimate VE against medically-attended illness under certain assumptions. Selection bias may be present if the probability of participation is associated with vaccination or COVID-19, but this can be mitigated through use of a clinical case definition to screen patients for eligibility, which increases the likelihood that cases and non-cases come from the same source population. We examined the extent to which this type of bias could harm COVID-19 VE through systematic review and simulation. A systematic review of test-negative studies was re-analysed to identify studies ignoring the need for clinical criteria. Studies using a clinical case definition had a lower pooled VE estimate compared with studies that did not. Simulations varied the probability of selection by case and vaccination status. Positive bias away from the null (i.e., inflated VE consistent with the systematic review) was observed when there was a higher proportion of healthy, vaccinated non-cases, which may occur if a dataset contains many results from asymptomatic screening in settings where vaccination coverage is high. We provide an html tool for researchers to explore site-specific sources of selection bias in their own studies. We recommend all group consider the potential for selection bias in their vaccine effectiveness studies, particularly when using administrative data.

Comparative Effectiveness of COVID-19 Vaccines in Preventing Infections and Disease Progression from SARS-CoV-2 Omicron BA.5 and BA.2, Portugal

We estimated comparative primary and booster vaccine effectiveness (VE) of SARS-CoV-2 Omicron BA.5 and BA.2 lineages against infection and disease progression. During April-June 2022, we implemented a case-case and cohort study and classified lineages using whole-genome sequencing or spike gene target failure. For the case-case study, we estimated the adjusted odds ratios (aORs) of vaccination using a logistic regression. For the cohort study, we estimated VE against disease progression using a penalized logistic regression. We observed no reduced VE for primary (aOR 1.07 [95% CI 0.93-1.23]) or booster (aOR 0.96 [95% CI 0.84-1.09]) vaccination against BA.5 infection. Among BA.5 case-patients, booster VE against progression to hospitalization was lower than that among BA.2 case-patients (VE 77% [95% CI 49%-90%] vs. VE 93% [95% CI 86%-97%]). Although booster vaccination is less effective against BA.5 than against BA.2, it offers substantial protection against progression from BA.5 infection to severe disease.

A novel method to jointly estimate transmission rate and decay rate parameters in environmental transmission models

In environmental transmission, pathogens transfer from one individual to another via the environment. It is a common transmission mechanism in a wide range of host-pathogen systems. Incorporating environmental transmission in dynamic transmission models is crucial for gauging the effect of interventions, as extrapolating model results to new situations is only valid when the mechanisms are modelled correctly. The challenge in environmental transmission models lies in not jointly identifiable parameters for pathogen shedding, decay, and transmission dynamics. To solve this unidentifiability issue, we present a stochastic environmental transmission model with a novel scaling method for shedding rate parameter and a novel estimation method that distinguishes transmission rate and decay rate parameters. The core of our scaling and estimation method is calculating exposure and relating exposure to infection risks. By scaling shedding rate parameter, we standardize exposure to pathogens contributed by one infectious individual present during one time interval to one. The standardized exposure leads to a standard definition of transmission rate parameter applicable to scenarios with different decay rate parameters. Hence, we unify direct transmission (large decay rate) and environmental transmission in a continuous manner. More importantly, our exposure-based estimation method can correctly estimate back the transmission rate and the decay rate parameters, while the commonly used trajectory-based method failed. The reason is that exposure-based method gives the correct weight to infection data from previous observation periods. The correct estimation from exposure-based method will lead to more reliable predictions of intervention impact. Using the effect of disinfection as an example, we show how incorrectly estimated parameters may lead to incorrect conclusions about the effectiveness of interventions. This illustrates the importance of correct estimation of transmission rate and decay rate parameters for extrapolating environmental transmission models and predicting intervention effects.

Estimating Waning of Vaccine Effectiveness: A Simulation Study

BACKGROUND

Developing accurate and reliable methods to estimate vaccine protection is a key goal in immunology and public health. While several statistical methods have been proposed, their potential inaccuracy in capturing fast intraseasonal waning of vaccine-induced protection needs to be rigorously investigated.

METHODS

To compare statistical methods for estimating vaccine effectiveness (VE), we generated simulated data using a multiscale, agent-based model of an epidemic with an acute viral infection and differing extents of VE waning. We apply a previously proposed framework for VE measures based on the observational data richness to assess changes of vaccine-induced protection over time.

RESULTS

While VE measures based on hard-to-collect information (eg, the exact timing of exposures) were accurate, usually VE studies rely on time-to-infection data and the Cox proportional hazards model. We found that its extension using scaled Schoenfeld residuals, previously proposed for capturing VE waning, was unreliable in capturing both the degree of waning and its functional form and identified the mathematical factors contributing to this unreliability. We showed that partitioning time and including a time-vaccine interaction term in the Cox model significantly improved estimation of VE waning, even in the case of dramatic, rapid waning. We also proposed how to optimize the partitioning scheme.

CONCLUSIONS

While appropriate for rejecting the null hypothesis of no waning, scaled Schoenfeld residuals are unreliable for estimating the degree of waning. We propose a Cox-model-based method with a time-vaccine interaction term and further optimization of partitioning time. These findings may guide future analysis of VE waning data.

Factors influencing estimated effectiveness of COVID-19 vaccines in non-randomised studies

Non-randomised studies assessing COVID-19 vaccine effectiveness need to consider multiple factors that may generate spurious estimates due to bias or genuinely modify effectiveness. These include pre-existing immunity, vaccination misclassification, exposure differences, testing, disease risk factor confounding, hospital admission decision, treatment use differences, and death attribution. It is useful to separate whether the impact of each factor admission decision, treatment use differences, and death attribution. Steps and measures to consider for improving vaccine effectiveness estimation include registration of studies and of analysis plans; sharing of raw data and code; background collection of reliable information; blinded assessment of outcomes, e.g. death causes; using maximal/best information in properly-matched studies, multivariable analyses, propensity analyses, and other models; performing randomised trials, whenever possible, for suitable questions, e.g. booster doses or comparative effectiveness of different vaccination strategies; living meta-analyses of vaccine effectiveness; better communication with both relative and absolute metrics of risk reduction and presentation of uncertainty; and avoidance of exaggeration in communicating results to the general public.

Prioritizing interventions for preventing COVID-19 outbreaks in military basic training

Like other congregate living settings, military basic training has been subject to outbreaks of COVID-19. We sought to identify improved strategies for preventing outbreaks in this setting using an agent-based model of a hypothetical cohort of trainees on a U.S. Army post. Our analysis revealed unique aspects of basic training that require customized approaches to outbreak prevention, which draws attention to the possibility that customized approaches may be necessary in other settings, too. In particular, we showed that introductions by trainers and support staff may be a major vulnerability, given that those individuals remain at risk of community exposure throughout the training period. We also found that increased testing of trainees upon arrival could actually increase the risk of outbreaks, given the potential for false-positive test results to lead to susceptible individuals becoming infected in group isolation and seeding outbreaks in training units upon release. Until an effective transmission-blocking vaccine is adopted at high coverage by individuals involved with basic training, need will persist for non-pharmaceutical interventions to prevent outbreaks in military basic training. Ongoing uncertainties about virus variants and breakthrough infections necessitate continued vigilance in this setting, even as vaccination coverage increases.

Estimating conditional vaccine effectiveness

Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness for a more severe outcome conditional on a less severe outcome is the protection offered against the severe outcome (e.g. death) among those who already sustained the less severe outcome (e.g. documented infection). The concept applies also to the protection offered by previous infection rather than vaccination. Formulas and a nomogram are provided here for calculating conditional effectiveness. Illustrative examples are presented from recent vaccine effectiveness studies, including situations where effectiveness for different outcomes changed at different pace over time. E(death | documented infection) is the percent decrease in the case fatality rate and E(death | infection) is the percent decrease in the infection fatality rate (IFR). Conditional effectiveness depends on many factors and should not be misinterpreted as a causal effect estimate. However, it may be used for better personalized communication of the benefits of vaccination, considering also IFR and epidemic activity in public health decision-making and communication.

Confidence interval estimation for vaccine efficacy against COVID-19

This article focuses on the construction of a confidence interval for vaccine efficacy against contagious coronavirus disease-2019 (COVID-19) in a fixed number of events design. Five different approaches are presented, and their performance is investigated in terms of the two-sided coverage probability, non-coverage probability at the lower tail, and expected confidence interval width. Furthermore, the effect of under-sensitivity of diagnosis tests on vaccine efficacy estimation was evaluated. Except for the exact conditional method, the non-coverage probability of the remaining methods may exceed the nominal significance level, e.g., 5%, even for a large number of total confirmed COVID-19 cases. The narrower confidence interval width from the Bayesian, approximate Poisson, and mid-P methods are on the cost of increased instability of coverage probability. When the sensitivity of diagnosis test in the vaccine group is lower than that in the placebo group, the reported vaccine efficacy tends to be overly optimistic. The exact conditional method is preferable to other methods in COVID-19 vaccine efficacy trials when the total number of cases reaches 60; otherwise, mid-p method can be used to obtain a narrower interval width.

Assessing vaccine effectiveness against severe COVID-19 disease caused by omicron variant. Report from a meeting of the World Health Organization

Vaccine effectiveness is lower and wanes faster against infection and symptomatic disease caused by the omicron variant of SARS-CoV-2 than was observed with previous variants. Vaccine effectiveness against severe omicron disease, on average, is higher, but has shown variability, including rapid apparent waning, in some studies. Assessing vaccine effectiveness against omicron severe disease using hospital admission as a measure of severe disease has become more challenging because of omicron's attenuated intrinsic severity and its high prevalence of infection. Many hospital admissions likely occur among people with incidental omicron infection or among those with infection-induced exacerbation of chronic medical conditions. To address this challenge, the World Health Organization held a virtual meeting on March 15, 2022, to review evidence from several studies that assessed Covid-19 vaccine effectiveness against severe omicron disease using several outcome definitions. Data was shown from studies in South Africa, the United States, the United Kingdom and Qatar. Several approaches were proposed that better characterize vaccine protection against severe Covid-19 disease caused by the omicron variant than using hospitalization of omicron-infected persons to define severe disease. Using more specific definitions for severe respiratory Covid-19 disease, such as indicators of respiratory distress (e.g. oxygen requirement, mechanical ventilation, and ICU admission), showed higher vaccine effectiveness than against hospital admission. Second, vaccine effectiveness against progression from omicron infection to hospitalization, or severe disease, also showed higher vaccine protection. These approaches might better characterize vaccine performance against severe Covid-19 disease caused by omicron, as well as future variants that evade humoral immunity, than using hospitalization with omicron infection as an indicator of severe disease.

A Systematic Review of Coronavirus Disease 2019 Vaccine Efficacy and Effectiveness Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection and Disease

Billions of doses of coronavirus disease 2019 (COVID-19) vaccines have been administered globally, dramatically reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence and severity in some settings. Many studies suggest vaccines provide a high degree of protection against infection and disease, but precise estimates vary and studies differ in design, outcomes measured, dosing regime, location, and circulating virus strains. In this study, we conduct a systematic review of COVID-19 vaccines through February 2022. We included efficacy data from Phase 3 clinical trials for 15 vaccines undergoing World Health Organization Emergency Use Listing evaluation and real-world effectiveness for 8 vaccines with observational studies meeting inclusion criteria. Vaccine metrics collected include protection against asymptomatic infection, any infection, symptomatic COVID-19, and severe outcomes including hospitalization and death, for partial or complete vaccination, and against variants of concern Alpha, Beta, Gamma, Delta, and Omicron. We additionally review the epidemiological principles behind the design and interpretation of vaccine efficacy and effectiveness studies, including important sources of heterogeneity.

Herd immunity and epidemic size in networks with vaccination homophily

We study how the herd immunity threshold and the expected epidemic size depend on homophily with respect to vaccine adoption. We find that the presence of homophily considerably increases the critical vaccine coverage needed for herd immunity and that strong homophily can push the threshold entirely out of reach. The epidemic size monotonically increases as a function of homophily strength for a perfect vaccine, while it is maximized at a nontrivial level of homophily when the vaccine efficacy is limited. Our results highlight the importance of vaccination homophily in epidemic modeling.

Health-Economic Value of Vaccination Against Group A Streptococcus in the United States

BACKGROUND

Vaccines are needed to reduce the burden of group A Streptococcus (GAS). We assessed the potential health-economic value of GAS vaccines achievable through prevention of invasive disease and acute upper respiratory infections in the United States.

METHODS

We estimated annual incidence of invasive GAS disease and associated costs incurred from hospitalization and management of long-term sequelae, as well as productivity losses resulting from acute illness, long-term disability, and mortality. We also estimated healthcare and productivity costs associated with GAS pharyngitis, sinusitis, and acute otitis media. We estimated costs averted by prevention of invasive disease and acute upper respiratory infections for vaccines with differing efficacy profiles; our base case considered vaccines meeting the World Health Organization Preferred Product Profile (WHO-PPP) with a 6-year average duration of protection.

RESULTS

Costs of invasive GAS disease and acute upper respiratory infections totaled $6.08 (95% confidence interval [CI], $5.33-$6.86) billion annually. Direct effects of vaccines meeting WHO-PPP characteristics and administered at ages 12 and 18 months would avert $609 (95% CI, $558-$663) million in costs annually, primarily by preventing noninvasive disease; with an additional dose at age 5 years, averted costs would total $869 (95% CI, $798-$945) million annually. Adult vaccination at age 65 years would avert $326 (95% CI, $271-$387) million in annual costs associated with invasive GAS disease. Indirect effects of vaccination programs reducing incidence of GAS diseases across all ages by 20% would avert roughly $1 billion in costs each year.

CONCLUSIONS

The economic burden of GAS is substantial. Our findings should inform prioritization of GAS vaccine development and evaluation.

Challenges of evaluating and modelling vaccination in emerging infectious diseases

Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.

Association Between mRNA Vaccination and COVID-19 Hospitalization and Disease Severity

Importance

A comprehensive understanding of the benefits of COVID-19 vaccination requires consideration of disease attenuation, determined as whether people who develop COVID-19 despite vaccination have lower disease severity than unvaccinated people.

Objective

To evaluate the association between vaccination with mRNA COVID-19 vaccines-mRNA-1273 (Moderna) and BNT162b2 (Pfizer-BioNTech)-and COVID-19 hospitalization, and, among patients hospitalized with COVID-19, the association with progression to critical disease.

Design, Setting, and Participants

A US 21-site case-control analysis of 4513 adults hospitalized between March 11 and August 15, 2021, with 28-day outcome data on death and mechanical ventilation available for patients enrolled through July 14, 2021. Date of final follow-up was August 8, 2021.

Exposures

COVID-19 vaccination.

Main Outcomes and Measures

Associations were evaluated between prior vaccination and (1) hospitalization for COVID-19, in which case patients were those hospitalized for COVID-19 and control patients were those hospitalized for an alternative diagnosis; and (2) disease progression among patients hospitalized for COVID-19, in which cases and controls were COVID-19 patients with and without progression to death or mechanical ventilation, respectively. Associations were measured with multivariable logistic regression.

Results

Among 4513 patients (median age, 59 years [IQR, 45-69]; 2202 [48.8%] women; 23.0% non-Hispanic Black individuals, 15.9% Hispanic individuals, and 20.1% with an immunocompromising condition), 1983 were case patients with COVID-19 and 2530 were controls without COVID-19. Unvaccinated patients accounted for 84.2% (1669/1983) of COVID-19 hospitalizations. Hospitalization for COVID-19 was significantly associated with decreased likelihood of vaccination (cases, 15.8%; controls, 54.8%; adjusted OR, 0.15; 95% CI, 0.13-0.18), including for sequenced SARS-CoV-2 Alpha (8.7% vs 51.7%; aOR, 0.10; 95% CI, 0.06-0.16) and Delta variants (21.9% vs 61.8%; aOR, 0.14; 95% CI, 0.10-0.21). This association was stronger for immunocompetent patients (11.2% vs 53.5%; aOR, 0.10; 95% CI, 0.09-0.13) than immunocompromised patients (40.1% vs 58.8%; aOR, 0.49; 95% CI, 0.35-0.69) (P < .001) and weaker at more than 120 days since vaccination with BNT162b2 (5.8% vs 11.5%; aOR, 0.36; 95% CI, 0.27-0.49) than with mRNA-1273 (1.9% vs 8.3%; aOR, 0.15; 95% CI, 0.09-0.23) (P < .001). Among 1197 patients hospitalized with COVID-19, death or invasive mechanical ventilation by day 28 was associated with decreased likelihood of vaccination (12.0% vs 24.7%; aOR, 0.33; 95% CI, 0.19-0.58).

Conclusions and Relevance

Vaccination with an mRNA COVID-19 vaccine was significantly less likely among patients with COVID-19 hospitalization and disease progression to death or mechanical ventilation. These findings are consistent with risk reduction among vaccine breakthrough infections compared with absence of vaccination.

Estimating Vaccine Efficacy Against Transmission via Effect on Viral Load

Determining policies to end the SARS-CoV-2 pandemic will require an understanding of the efficacy and effectiveness (hereafter, efficacy) of vaccines. Beyond the efficacy against severe disease and symptomatic and asymptomatic infection, understanding vaccine efficacy against virus transmission, including efficacy against transmission of different viral variants, will help model epidemic trajectory and determine appropriate control measures. Recent studies have proposed using random virologic testing in individual randomized controlled trials to improve estimation of vaccine efficacy against infection. We propose to further use the viral load measures from these tests to estimate efficacy against transmission. This estimation requires a model of the relationship between viral load and transmissibility and assumptions about the vaccine effect on transmission and the progress of the epidemic. We describe these key assumptions, potential violations of them, and solutions that can be implemented to mitigate these violations. Assessing these assumptions and implementing this random sampling, with viral load measures, will enable better estimation of the crucial measure of vaccine efficacy against transmission.

COVID-19 vaccines that reduce symptoms but do not block infection need higher coverage and faster rollout to achieve population impact

Trial results for two COVID-19 vaccines suggest at least 90% efficacy against symptomatic disease (VEDIS). It remains unknown whether this efficacy is mediated by lowering SARS-CoV-2 infection susceptibility (VESUSC) or development of symptoms after infection (VESYMP). We aim to assess and compare the population impact of vaccines with different efficacy profiles (VESYMP and VESUSC) satisfying licensure criteria. We developed a mathematical model of SARS-CoV-2 transmission, calibrated to data from King County, Washington. Rollout scenarios starting December 2020 were simulated with combinations of VESUSC and VESYMP resulting in up to 100% VEDIS. We assumed no reduction of infectivity upon infection conditional on presence of symptoms. Proportions of cumulative infections, hospitalizations and deaths prevented over 1 year from vaccination start are reported. Rollouts of 1 M vaccinations (5000 daily) using vaccines with 50% VEDIS are projected to prevent 23-46% of infections and 31-46% of deaths over 1 year. In comparison, vaccines with 90% VEDIS are projected to prevent 37-64% of infections and 46-64% of deaths over 1 year. In both cases, there is a greater reduction if VEDIS is mediated mostly by VESUSC. The use of a "symptom reducing" vaccine will require twice as many people vaccinated than a "susceptibility reducing" vaccine with the same 90% VEDIS to prevent 50% of the infections and death over 1 year. Delaying the start of the vaccination by 3 months decreases the expected population impact by more than 50%. Vaccines which prevent COVID-19 disease but not SARS-CoV-2 infection, and thereby shift symptomatic infections to asymptomatic infections, will prevent fewer infections and require larger and faster vaccination rollouts to have population impact, compared to vaccines that reduce susceptibility to infection. If uncontrolled transmission across the U.S. continues, then expected vaccination in Spring 2021 will provide only limited benefit.

Beyond the new normal: Assessing the feasibility of vaccine-based suppression of SARS-CoV-2

As the COVID-19 pandemic drags into its second year, there is hope on the horizon, in the form of SARS-CoV-2 vaccines which promise disease suppression and a return to pre-pandemic normalcy. In this study we critically examine the basis for that hope, using an epidemiological modeling framework to establish the link between vaccine characteristics and effectiveness in bringing an end to this unprecedented public health crisis. Our findings suggest that a return to pre-pandemic social and economic conditions without fully suppressing SARS-CoV-2 will lead to extensive viral spread, resulting in a high disease burden even in the presence of vaccines that reduce risk of infection and mortality. Our modeling points to the feasibility of complete SARS-CoV-2 suppression with high population-level compliance and vaccines that are highly effective at reducing SARS-CoV-2 infection. Notably, vaccine-mediated reduction of transmission is critical for viral suppression, and in order for partially-effective vaccines to play a positive role in SARS-CoV-2 suppression, complementary biomedical interventions and public health measures must be deployed simultaneously.

Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines

Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. Although traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here, we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, nonspecific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance, if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.

Indirect effects of 13-valent pneumococcal conjugate vaccine on pneumococcal carriage in children hospitalised with acute respiratory infection despite heterogeneous vaccine coverage: an observational study in Lao People's Democratic Republic

Introduction

Empiric data on indirect (herd) effects of pneumococcal conjugate vaccines (PCVs) in settings with low or heterogeneous PCV coverage are limited. The indirect effects of PCV, which benefits both vaccinated and non-vaccinated individuals, are mediated by reductions in vaccine-type (VT) carriage (a prerequisite for disease). The aim of this study among hospitalised children in Lao People’s Democratic Republic (Lao PDR) is to determine the effectiveness of a 13-valent PCV (PCV13) against VT pneumococcal nasopharyngeal carriage (direct effects) and the association between village-level PCV13 coverage and VT carriage (indirect effects).

Methods

Pneumococcal nasopharyngeal carriage surveillance commenced in December 2013, shortly after PCV13 introduction (October 2013). We recruited and swabbed children aged 2–59 months admitted to hospital with acute respiratory infection. Pneumococci were detected using lytA quantitative real-time PCR and serotyped using microarray. PCV13 status and village-level PCV13 coverage were determined using written immunisation records. Associations between both PCV13 status and village-level PCV13 coverage and VT carriage were calculated using generalised estimating equations, controlling for potential confounders.

Results

We enrolled 1423 participants and determined PCV13 coverage for 368 villages (269 863 children aged under 5 years). By 2017, median village-level vaccine coverage reached 37.5%, however, the IQR indicated wide variation among villages (24.1–56.4). Both receipt of PCV13 and the level of PCV13 coverage were independently associated with a reduced odds of VT carriage: adjusted PCV13 effectiveness was 38.1% (95% CI 4.1% to 60.0%; p=0.032); and for each per cent increase in PCV13 coverage, the estimated odds of VT carriage decreased by 1.1% (95% CI 0.0% to 2.2%; p=0.056). After adjustment, VT carriage decreased from 20.0% to 12.8% as PCV13 coverage increased from zero to 60% among under 5.

Conclusions

Despite marked heterogeneity in PCV13 coverage, we found evidence of indirect effects in Lao PDR. Individual vaccination with PCV13 was effective against VT carriage.

Identification of causal intervention effects under contagion

Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment - such as a vaccine - given to one individual may affect the infection outcomes of others. Epidemiologists have proposed causal estimands to quantify effects of interventions under contagion using a two-person partnership model. These simple conceptual models have helped researchers develop causal estimands relevant to clinical evaluation of vaccine effects. However, many of these partnership models are formulated under structural assumptions that preclude realistic infectious disease transmission dynamics, limiting their conceptual usefulness in defining and identifying causal treatment effects in empirical intervention trials. In this paper, we propose causal intervention effects in two-person partnerships under arbitrary infectious disease transmission dynamics, and give nonparametric identification results showing how effects can be estimated in empirical trials using time-to-infection or binary outcome data. The key insight is that contagion is a causal phenomenon that induces conditional independencies on infection outcomes that can be exploited for the identification of clinically meaningful causal estimands. These new estimands are compared to existing quantities, and results are illustrated using a realistic simulation of an HIV vaccine trial.

Mathematical Quantification of Transmission in Experiments: FMDV Transmission in Pigs Can Be Blocked by Vaccination and Separation

Quantitative understanding of transmission with and without control measures is important for the control of infectious diseases because it helps to determine which of these measures (or combinations thereof) will be effective to reduce transmission. In this paper, the statistical methods used to estimate transmission parameters are explained. To show how these methods can be used we reviewed literature for papers describing foot-and-mouth disease virus (FMDV) transmission in pigs and we used the data to estimate transmission parameters. The analysis showed that FMDV transmits very well when pigs have direct contact. Transmission, however, is reduced when a physical barrier separates infected and susceptible non-vaccinated pigs. Vaccination of pigs can prevent infection when virus is administered by a single intradermal virus injection in the bulb of the heel, but it cannot prevent infection when pigs are directly exposed to either non-vaccinated or vaccinated FMDV infected pigs. Physical separation combined with vaccination is observed to block transmission. Vaccination and separation can make a significant difference in the estimated number of new infections per day. Experimental transmission studies show that the combined effect of vaccination and physical separation can significantly reduce transmission (R < 1), which is a very relevant result for the control of between-farm transmission.

Assessment of the Potential of Vaccination to Combat Antibiotic Resistance in Gonorrhea: A Modeling Analysis to Determine Preferred Product Characteristics

BACKGROUND

Gonorrhea incidence is increasing rapidly in many countries, while antibiotic resistance is making treatment more difficult. Combined with evidence that two meningococcal vaccines are likely partially protective against gonorrhea, this has renewed interest in a gonococcal vaccine, and several candidates are in development. Key questions are how protective and long-lasting a vaccine needs to be, and how to target it. We assessed vaccination's potential impact and the feasibility of achieving the World Health Organization's (WHO) target of reducing gonorrhea incidence by 90% during 2018-2030, by comparing realistic vaccination strategies under a range of scenarios of vaccine efficacy and duration of protection, and emergence of extensively-resistant gonorrhea.

METHODS

We developed a stochastic transmission-dynamic model, incorporating asymptomatic and symptomatic infection and heterogeneous sexual behavior in men who have sex with men (MSM). We used data from England, which has a comprehensive, consistent nationwide surveillance system. Using particle Markov chain Monte Carlo methods, we fitted to gonorrhea incidence in 2008-2017, then used Bayesian forecasting to examine an extensive range of scenarios.

RESULTS

Even in the worst-case scenario of untreatable infection emerging, the WHO target is achievable if all MSM attending sexual health clinics receive a vaccine offering ≥ 52% protection for ≥ 6 years. A vaccine conferring 31% protection (as estimated for MeNZB) for 2-4 years could reduce incidence in 2030 by 45% in the worst-case scenario, and by 75% if > 70% of resistant gonorrhea remains treatable.

CONCLUSIONS

Even a partially-protective vaccine, delivered through a realistic targeting strategy, could substantially reduce gonorrhea incidence, despite antibiotic resistance.

Challenges for the evaluation of digital health solutions-A call for innovative evidence generation approaches

The field of digital health, and its meaning, has evolved rapidly over the last 20 years. For this article we followed the most recent definition provided by FDA in 2020. Emerging solutions offers tremendous potential to positively transform the healthcare sector. Despite the growing number of applications, however, the evolution of methodologies to perform timely, cost-effective and robust evaluations have not kept pace. It remains an industry-wide challenge to provide credible evidence, therefore, hindering wider adoption. Conventional methodologies, such as clinical trials, have seldom been applied and more pragmatic approaches are needed. In response, several academic centers such as researchers from the Institute of Global Health Innovation at Imperial College London have initiated a digital health clinical simulation test bed to explore new approaches for evidence gathering relevant to solution type and maturity. The aim of this article is to: (1) Review current research approaches and discuss their limitations; (2) Discuss challenges faced by different stakeholders in undertaking evaluations; and (3) Call for new approaches to facilitate the safe and responsible growth of the digital health sector.

Evaluating strategies to improve rotavirus vaccine impact during the second year of life in Malawi

Rotavirus vaccination has substantially reduced the incidence of rotavirus-associated gastroenteritis (RVGE) in high-income countries, but vaccine impact and estimated effectiveness are lower in low-income countries for reasons that are poorly understood. We used mathematical modeling to quantify rotavirus vaccine impact and investigate reduced vaccine effectiveness, particularly during the second year of life, in Malawi, where vaccination was introduced in October 2012 with doses at 6 and 10 weeks. We fitted models to 12 years of prevaccination data and validated the models against postvaccination data to evaluate the magnitude and duration of vaccine protection. The observed rollout of vaccination in Malawi was predicted to lead to a 26 to 77% decrease in the overall incidence of moderate-to-severe RVGE in 2016, depending on assumptions about waning of vaccine-induced immunity and heterogeneity in vaccine response. Vaccine effectiveness estimates were predicted to be higher among 4- to 11-month-olds than 12- to 23-month-olds, even when vaccine-induced immunity did not wane, due to differences in the rate at which vaccinated and unvaccinated individuals acquire immunity from natural infection. We found that vaccine effectiveness during the first and second years of life could potentially be improved by increasing the proportion of infants who respond to vaccination or by lowering the rotavirus transmission rate. An additional dose of rotavirus vaccine at 9 months of age was predicted to lead to higher estimated vaccine effectiveness but to only modest (5 to 16%) reductions in RVGE incidence over the first 3 years after introduction, regardless of assumptions about waning of vaccine-induced immunity.

Measuring vaccine effectiveness against persistent HPV infections: a comparison of different statistical approaches

BACKGROUND

Persistent high-risk human papillomavirus (HPV) infection is endorsed by the World Health Organization as an intermediate endpoint for evaluating HPV vaccine effectiveness/efficacy. There are different approaches to estimate the vaccine effectiveness/efficacy against persistent HPV infections.

METHODS

We performed a systematic literature search in Pubmed to identify statistical approaches that have been used to estimate the vaccine effectiveness/efficacy against persistent HPV infections. We applied these methods to data of a longitudinal observational study to assess their performance and compare the obtained vaccine effectiveness (VE) estimates.

RESULTS

Our literature search identified four approaches: the conditional exact test for comparing two independent Poisson rates using a binomial distribution, Generalized Estimating Equations for Poisson regression, Prentice Williams and Peterson total time (PWP-TT) and Cox proportional hazards regression. These approaches differ regarding underlying assumptions and provide different effect measures. However, they provided similar effectiveness estimates against HPV16/18 and HPV31/33/45 persistent infections in a cohort of young women eligible for routine HPV vaccination (range VE 93.7-95.1% and 60.4-67.7%, respectively) and seemed robust to violations of underlying assumptions.

CONCLUSIONS

As the rate of subsequent infections increased in our observational cohort, we recommend PWP-TT as the optimal approach to estimate the vaccine effectiveness against persistent HPV infections in young women. Confirmation of our findings should be undertaken by applying these methods after longer follow-up in our study, as well as in different populations.

Using pneumococcal carriage studies to monitor vaccine impact in low- and middle-income countries

Pneumococcal disease is a leading cause of childhood mortality, globally. The pneumococcal conjugate vaccine (PCV) has been introduced to many countries worldwide. However there are few studies evaluating PCV impacts in low- and middle-income countries (LMIC) because measuring the impact of PCV on pneumococcal disease in LMICs is challenging. We review the role of pneumococcal carriage studies for the evaluation of PCVs in LMICs and discuss optimal methods for conducting these studies. Fifteen carriage studies from 13 LMICs quantified the effects of PCV on carriage, and identified replacement carriage serotypes in the post-PCV era. Ten studies reported on the indirect effects of PCV on carriage. Results can be used to inform cost-effectiveness evaluations, guide policy decisions on dosing and product, and monitor equity in program implementation. Critically, we highlight gaps in our understanding of serotype replacement disease in LMICs and identify priorities for research to address this gap.

Introduction of Vaccinomics to Develop Personalized Vaccines in Light of Changes in the Usage of Hantaan Virus Vaccine (Hantavax®) in Korea

The Ministry of Food and Drug Safety of Korea made an official announcement in March 2018 that the total number of inoculations of Hantaan virus vaccine (Hantavax^®) would change from 3 to 4. Some aspects of this decision remain controversial. Based on the characteristics of Hantaan virus (HTNV) and its role in the pathogenesis of hemorrhagic fever with renal syndrome, it might be difficult to develop an effective and safe HTNV vaccine through the isolate-inactivate-inject paradigm. With the development of high-throughput ‘omics’ technologies in the 21st century, vaccinomics has been introduced. While the goal of vaccinomics is to develop equations to describe and predict the immune response, it could also serve as a tool for developing new vaccine candidates and individualized approaches to vaccinology. Thus, the possibility of applying the innovative field of vaccinomics to develop a more effective and safer HTNV vaccine should be considered.

Assessing Vaccine Herd Protection by Killed Whole-Cell Oral Cholera Vaccines Using Different Study Designs

The population level effectiveness of a vaccine may arise as the result of direct protection of vaccinees and vaccine herd protection, which may protect non-vaccinees, vaccinees, or both. Indirect, total, enhanced, and overall vaccine protection are measures of vaccine herd protection. The level of population level effectiveness induced by a vaccine is driven by several factors, including known vaccine-induced protective efficacy, the magnitude, and distribution of vaccine coverage at a point in time and the extent to which different groups mix with one another in the community. Data on vaccine herd protection are valuable in understanding the importance and cost-effectiveness in deploying the e vaccine in public health program. Killed whole-cell (WC) oral cholera vaccines (OCVs) have been evaluated for herd protection in various study settings, leveraging geographic information system (GIS) tools for the analyses. This article provides a brief description of the herd protective effects of killed WC OCVs measured using various study deigns that include (a) individually randomized, controlled clinical trials, (b) cluster randomized clinical trials, (c) observational cohort studies, and (d) observational case-control studies. In all of the study designs, significant herd protection was observed in unvaccinated persons as well as in the community as a whole. The findings of these studies suggest that using killed WC OCV as a public health tool for controlling cholera is impactful and cost-effective.

Vaccination history as a confounder of studies of influenza vaccine effectiveness

BACKGROUND

Vaccination history may confound estimates of influenza vaccine effectiveness (VE) when two conditions are present: (1) Influenza vaccination is associated with vaccination history and (2) vaccination modifies the risk of natural infection in the following seasons, either due to persisting vaccination immunity or due to lower previous risk of natural infection.

METHODS

Analytic arguments are used to define conditions for confounding of VE estimates by vaccination history. Simulation studies, both with accurate and inaccurate assessment of current and previous vaccination status, are used to explore the potential magnitude of these biases when using different statistical models to address confounding by vaccination history.

RESULTS

We found a potential for substantial bias of VE estimates by vaccination history if infection- and/or vaccination-derived immunity persisted from one season to the next and if vaccination uptake in individuals was seasonally correlated. Full adjustment by vaccination history, which is usually not feasible, resulted in unbiased VE estimates. Partial adjustment, i.e. only by prior season's vaccination status, significantly reduced confounding bias. Misclassification of vaccination status, which can also lead to substantial bias, interferes with the adjustment of VE estimates for vaccination history.

CONCLUSIONS

Confounding by vaccination history may bias VE estimates, but even partial adjustment by only the prior season's vaccination status substantially reduces confounding bias. Misclassification of vaccination status may compromise VE estimates and efforts to adjust for vaccination history.

Herd immunity alters the conditions for performing dose schedule comparisons: an individual-based model of pneumococcal carriage

Background

There is great interest in the use of reduced dosing schedules for pneumococcal conjugate vaccines, a strategy premised on maintaining an acceptable level of protection against disease and carriage of the organism. We asked about the practicality of measuring differential effectiveness against carriage in a population with and without widespread use of the vaccine for infants.

Methods

We adapted an existing transmission-dynamic, individual-based stochastic model fitted to the prevaccine epidemiology of pneumococcal carriage in the United States, and compared the observed vaccine-type carriage prevalence in different arms of a simulated trial with one, two, or three infant doses plus a 12-month booster. Using these simulations, we calculated vaccine efficacy that would be estimated at different times post-enrollment in the trial and calculated required sample sizes to see a difference in carriage prevalence.

Results

In a pneumococcal conjugate vaccine (PCV)-naïve population, the difference in vaccine-type (VT) pneumococcal carriage prevalence between trial arms was less than 7% and varied with sampling time. In a population already receiving routine PCV administration, VT pneumococcal prevalence is nearly indistinguishable between trial arms. Relative efficacy of different dosing schedules was strongly dependent on the time between enrollment and sampling, with maximal prevalence differences reached 1–3 years post-enrollment. Moreover, vaccine efficacy estimates were typically slightly higher in trials in communities already receiving vaccination. Despite this, much larger sample sizes—by more than an order of magnitude—are required for a vaccine trial conducted in a population receiving routine PCV administration as compared to in a PCV-naïve population.

Conclusions

These findings highlight some underappreciated aspects of clinical trials of pneumococcal conjugate vaccines with efficacy endpoints, such as the context- and time-dependence of efficacy estimates. They support the wisdom of conducting comparative dose schedule trials of conjugate vaccine effects on carriage in vaccine-naïve populations.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-3833-6) contains supplementary material, which is available to authorized users.

Measurement of Vaccine Direct Effects Under the Test-Negative Design

Test-negative designs are commonplace in assessments of influenza vaccination effectiveness, estimating this value from the exposure odds ratio of vaccination among individuals treated for acute respiratory illness who test positive for influenza virus infection. This approach is widely believed to recover the vaccine direct effect by correcting for differential health-care-seeking behavior among vaccinated and unvaccinated persons. However, the relationship of the measured odds ratio to true vaccine effectiveness is poorly understood. We derived the odds ratio under circumstances of real-world test-negative studies. The odds ratio recovers the vaccine direct effect when 2 conditions are met: 1) Individuals' vaccination decisions are uncorrelated with exposure or susceptibility to the test-positive or test-negative conditions, and 2) vaccination confers "all-or-nothing" protection (whereby certain individuals have no protection while others are perfectly protected). Biased effect-size estimates arise if either condition is unmet. Such bias might suggest misleading associations of vaccine effectiveness with time since vaccination or the force of infection of influenza. The test-negative design could also fail to correct for differential health-care-seeking behavior among vaccinated and unvaccinated persons without stringent criteria for enrollment and testing. Our findings demonstrate a need to reassess how data from test-negative studies can inform policy decisions.

Observational studies and the difficult quest for causality: lessons from vaccine effectiveness and impact studies

Although randomized placebo-controlled trials (RCT) are critical to establish efficacy of vaccines at the time of licensure, important remaining questions about vaccine effectiveness (VE)-used here to include individual-level measures and population-wide impact of vaccine programmes-can only be answered once the vaccine is in use, from observational studies. However, such studies are inherently at risk for bias. Using a causal framework and illustrating with examples, we review newer approaches to detecting and avoiding confounding and selection bias in three major classes of observational study design: cohort, case-control and ecological studies. Studies of influenza VE, especially in seniors, are an excellent demonstration of the challenges of detecting and reducing such bias, and so we use influenza VE as a running example. We take a fresh look at the time-trend studies often dismissed as 'ecological'. Such designs are the only observational study design that can measure the overall effect of a vaccination programme [indirect (herd) as well as direct effects], and are in fact already an important part of the evidence base for several vaccines currently in use. Despite the great strides towards more robust observational study designs, challenges lie ahead for evaluating best practices for achieving robust unbiased results from observational studies. This is critical for evaluation of national and global vaccine programme effectiveness.

Waning protection of influenza vaccination during four influenza seasons, 2011/2012 to 2014/2015

BACKGROUND

Concerns have been raised about intraseasonal waning of the protection conferred by influenza vaccination.

METHODS

During four influenza seasons, we consecutively recruited individuals aged 18years or older who had received seasonal influenza vaccine and were subsequently admitted to the hospital for influenza infection, asassessed by reverse transcription polymerase chain reaction. We estimated the adjusted odds ratio (aOR) of influenza infection by date of vaccination, defined by tertiles, as early, intermediate or late vaccination. We used a test-negative approach with early vaccination as reference to estimate the aOR of hospital admission with influenza among late vaccinees. We conducted sensitivity analyses by means of conditional logistic regression, Cox proportional hazards regression, and using days between vaccination and hospital admission rather than vaccination date.

RESULTS

Among 3615 admitted vaccinees, 822 (23%) were positive for influenza. We observed a lower risk of influenza among late vaccinees during the 2011/2012 and 2014/2015A(H3N2)-dominant seasons: aOR=0.68 (95% CI: 0.47-1.00) and 0.69 (95% CI: 0.50-0.95). We found no differences in the risk of admission with influenza among late versus early vaccinees in the 2012/2013A(H1N1)pdm09-dominant or 2013/2014B/Yamagata lineage-dominant seasons: aOR=1.18 (95% CI: 0.58-2.41) and 0.98 (95% CI: 0.56-1.72). When we restricted our analysis to individuals aged 65years or older, we found a statistically significant lower risk of admission with influenza among late vaccinees during the 2011/2012 and 2014/2015A(H3N2)-dominant seasons: aOR=0.61 (95% CI: 0.41-0.91) and 0.69 (95% CI: 0.49-0.96). We observed 39% (95% CI: 9-59%) and 31% (95% CI: 5-50%) waning of vaccine effectiveness among participants aged 65years or older during the two A(H3N2)-dominant seasons. Similar results were obtained in the sensitivity analyses.

CONCLUSION

Waning of vaccine protection was observed among individuals aged 65years old or over in two A(H3N2)-dominant influenza seasons.

Effectiveness of Early Measles, Mumps, and Rubella Vaccination Among 6-14-Month-Old Infants During an Epidemic in the Netherlands: An Observational Cohort Study

Background

Routinely, the first measles, mumps, and rubella (MMR) vaccine dose is given at 14 months of age in the Netherlands. However, during a measles epidemic in 2013-2014, MMR vaccination was also offered to 6-14-month-olds in municipalities with <90% MMR vaccination coverage. We studied the effectiveness of the early MMR vaccination schedule.

Methods

Parents of all infants targeted for early MMR vaccination were asked to participate. When parent(s) suspected measles, their infant's saliva was tested for measles-specific antibodies. The vaccine effectiveness (VE) against laboratory-confirmed and self-reported measles was estimated using Cox regression, with VE calculated as 1 minus the hazard ratio.

Results

Three vaccinated and 10 unvaccinated laboratory-confirmed cases occurred over observation times of 106631 and 23769 days, respectively. The unadjusted VE against laboratory-confirmed measles was 94% (95% confidence interval [CI], 79%-98%). After adjustment for religion and sibling's vaccination status, the VE decreased to 71% (-72%-95%). For self-reported measles, the unadjusted and adjusted VE was 67% (40%-82%) and 43% (-12%-71%), respectively.

Conclusions

Infants vaccinated between 6 and 14 months of age had a lower risk of measles than unvaccinated infants. However, part of the effect was caused by herd immunity, since vaccinated infants were more likely to be surrounded by other vaccinated individuals.

Review: Capripoxvirus Diseases: Current Status and Opportunities for Control

Lumpy skin disease, sheeppox and goatpox are high-impact diseases of domestic ruminants with a devastating effect on cattle, sheep and goat farming industries in endemic regions. In this article, we review the current geographical distribution, economic impact of an outbreak, epidemiology, transmission and immunity of capripoxvirus. The special focus of the article is to scrutinize the use of currently available vaccines to investigate the resource needs and challenges that will have to be overcome to improve disease control and eradication, and progress on the development of safer and more effective vaccines. In addition, field evaluation of the efficacy of the vaccines and the genomic database available for poxviruses are discussed.

Effect of high-valency pneumococcal conjugate vaccines on invasive pneumococcal disease in children in SpIDnet countries: an observational multicentre study

BACKGROUND

The Streptococcus pneumoniae Invasive Disease network (SpIDnet) actively monitors populations in nine sites in seven European countries for invasive pneumococcal disease. Five sites use 13-valent pneumococcal conjugate vaccine (PCV13) alone and four use the ten-valent PCV (PCV10) and PCV13. Vaccination uptake is greater than 90% in six sites and 67-78% in three sites. We measured the effects of introducing high-valency PCVs on the incidence of invasive pneumococcal disease in children younger than 5 years.

METHODS

We compared the incidence of invasive pneumococcal disease in each of the 4 years after the introduction of PCV13 alone or PCV10 and PCV13 with the average incidence during the preceding period of heptavalent PCV (PCV7) use, overall and by serotype category. We calculated incidence rate ratios (IRRs) and 95% CIs for each year and pooled the values for all sites in a random effects meta-analysis.

FINDINGS

4 years after the introduction of PCV13 alone or PCV10 and PCV13, the pooled IRR was 0·53 (95% CI 0·43-0·65) for invasive pneumococcal disease in children younger than 5 years caused by any serotype, 0·16 (0·07-0·40) for disease caused by PCV7 serotypes, 0·17 (0·07-0·42) for disease caused by 1, 5, and 7F serotypes, and 0·41 (0·25-0·69) for that caused by 3, 6A and 19A serotypes. We saw a similar pattern when we restricted the analysis to sites where only PCV13 was used. The pooled IRR for invasive pneumococcal disease caused by non-PCV13 serotypes was 1·62 (1·09-2·42).

INTERPRETATION

The incidence of invasive pneumococcal disease caused by all serotypes decreased due to a decline in the incidence of vaccine serotypes. By contrast, that of invasive pneumococcal disease caused by non-PCV13 serotypes increased, which suggests serotype replacement. Long-term surveillance will be crucial to monitor the further effects of PCV10 and PCV13 vaccination programmes in young children.

FUNDING

European Centre for Disease Prevention and Control, Czech National Institute of Public Health, French National Agency for Public Health, Irish Health Services Executive, Norwegian Institute of Public Health, Public Health Agency of Catalonia, Public Health Department of Community of Madrid, Navarra Hospital Complex, Public Health Institute of Navarra, CIBER Epidemiology and Public Health, Institute of Health Carlos III, Public Health Agency of Sweden, and NHS Scotland.

Oral Vaccination of Free-Living Badgers (Meles meles) with Bacille Calmette Guérin (BCG) Vaccine Confers Protection against Tuberculosis

A field trial was conducted to investigate the impact of oral vaccination of free-living badgers against natural-transmitted Mycobacterium bovis infection. For a period of three years badgers were captured over seven sweeps in three zones and assigned for oral vaccination with a lipid-encapsulated BCG vaccine (Liporale-BCG) or with placebo. Badgers enrolled in Zone A were administered placebo while all badgers enrolled in Zone C were vaccinated with BCG. Badgers enrolled in the middle area, Zone B, were randomly assigned 50:50 for treatment with vaccine or placebo. Treatment in each zone remained blinded until the end of the study period. The outcome of interest was incident cases of tuberculosis measured as time to seroconversion events using the BrockTB Stat-Pak lateral flow serology test, supplemented with post-mortem examination. Among the vaccinated badgers that seroconverted, the median time to seroconversion (413 days) was significantly longer (p = 0.04) when compared with non-vaccinated animals (230 days). Survival analysis (modelling time to seroconversion) revealed that there was a significant difference in the rate of seroconversion between vaccinated and non-vaccinated badgers in Zones A and C throughout the trial period (p = 0.015). For badgers enrolled during sweeps 1–2 the Vaccine Efficacy (VE) determined from hazard rate ratios was 36% (95% CI: -62%– 75%). For badgers enrolled in these zones during sweeps 3–6, the VE was 84% (95% CI: 29%– 97%). This indicated that VE increased with the level of vaccine coverage. Post-mortem examination of badgers at the end of the trial also revealed a significant difference in the proportion of animals presenting with M. bovis culture confirmed lesions in vaccinated Zone C (9%) compared with non-vaccinated Zone A (26%). These results demonstrate that oral BCG vaccination confers protection to badgers and could be used to reduce incident rates in tuberculosis-infected populations of badgers.

Mathematical Modeling Tools to Study Preharvest Food Safety

This article provides an overview of the emerging field of mathematical modeling in preharvest food safety. We describe the steps involved in developing mathematical models, different types of models, and their multiple applications. The introduction to modeling is followed by several sections that introduce the most common modeling approaches used in preharvest systems. We finish the chapter by outlining potential future directions for the field.

Bayesian estimation of vaccine efficacy

Protective vaccine efficacy, VES, is measured as one minus the incidence rate ratio (IRR) or the relative risk (RR) in the vaccinated group compared with the unvaccinated group. In this paper, we systematically present Bayesian estimation of protective vaccine efficacy based on the Poisson and binomial distributions. We also propose a new tool, the vaccine efficacy acceptability curve, to represent the uncertainty for the estimate of the vaccine efficacy graphically. It is very useful, especially when there is no universal agreement on the acceptable vaccine efficacy. The vaccine efficacy acceptability curve is defined as the posterior probability that the measure of vaccine efficacy VES ≥ k for each acceptable value k. When a vaccine is highly efficacious, the number of vaccinated susceptibles being infected is likely to be very small or even zero. Then the assumptions of normality and log-normality of IRR or RR usually do not hold well. Although frequentist exact methods provide good estimates of the confidence interval, they are overly conservative and are computationally difficult to extend to estimate the vaccine efficacy acceptability curve. In this paper, our focus is on Bayesian estimation of protective vaccine efficacy, its highest probability density credible set, and the vaccine efficacy acceptability curve through Markov chain Monte Carlo (MCMC) methods. We illustrate the methods using the data from two pertussis vaccine studies and the H. influenza Type B preventive trial.

Integrating Transgenic Vector Manipulation with Clinical Interventions to Manage Vector-Borne Diseases

Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication) can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted). We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences—consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even modest perturbations induced by weak interventions can exhibit strong, albeit transient, epidemiological effects. This, together with our finding that under some conditions combining strategies could have transient adverse epidemiological effects suggests that a relatively long time horizon may be necessary to discern the efficacy of alternative intervention strategies.

Despite decades of attempted vector control, several vector-borne diseases remain endemic. Recent high-profile studies suggest that candidate vaccines, particularly for dengue, may be less than completely effective as public health interventions. Nevertheless, the epidemiological consequences of using other novel approaches (e.g., transgenic strategies to reduce or replace vector populations) remain highly uncertain. Faced with unclear prospects of any one strategy succeeding in isolation, there is increasing interest in designing a comprehensive public health response to manage vector-borne diseases. Here we use a relatively simple model to study how combining vaccines, transgenic vector manipulation and antimicrobial medications can facilitate disease management. We explain why the epidemiological consequences for combining strategies are not expected to merely sum their effects. Contrary to the prevailing assumption that comprehensive disease management always yields public health benefits, we find integrating transgenic vector manipulation with clinical interventions can, in some cases, temporarily exacerbate the adverse consequences of any one strategy failing. These results highlight the need for system-specific modeling efforts aimed at assessing whether our conclusions apply to specific vector-borne diseases. We outline the implications for proceeding with public health responses integrating currently available products, as well as assessing their efficacy.