Myocarditis and Pericarditis Post-mRNA COVID-19 Vaccination: Insights from a Pharmacovigilance Perspective.

Concerns remain regarding the rare cardiovascular adverse events, myocarditis and pericarditis (myo/pericarditis), particularly in younger individuals following mRNA COVID-19 vaccination. Our study aimed to comprehensively assess potential safety signals related to these cardiac events following the primary and booster doses, with a specific focus on younger populations, including children as young as 6 months of age. Using the Vaccine Adverse Events Reporting System (VAERS), the United States national passive surveillance system, we conducted a retrospective pharmacovigilance study analyzing spontaneous reports of myo/pericarditis. We employed both frequentist and Bayesian methods and conducted subgroup analyses by age, sex, and vaccine dose. We observed a higher reporting rate of myo/pericarditis following the primary vaccine series, particularly in males and mainly after the second dose. However, booster doses demonstrated a lower number of reported cases, with no significant signals detected after the fourth or fifth doses. In children and young adults, we observed notable age and sex differences in the reporting of myo/pericarditis cases. Males in the 12-17 and 18-24-year-old age groups had the highest number of cases, with significant signals for both males and females after the second dose. We also identified an increased reporting for a spectrum of cardiovascular symptoms such as chest pain and dyspnea, which increased with age, and were reported more frequently than myo/pericarditis. The present study identified signals of myo/pericarditis and related cardiovascular symptoms after mRNA COVID-19 vaccination, especially among children and adolescents. These findings underline the importance for continued vaccine surveillance and the need for further studies to confirm these results and to determine their clinical implications in public health decision-making, especially for younger populations.

Risk of myocarditis and pericarditis in mRNA COVID-19-vaccinated and unvaccinated populations: a systematic review and meta-analysis.

OBJECTIVE: To summarise the available evidence on the risk of myocarditis and/or pericarditis following mRNA COVID-19 vaccination, compared with the risk among unvaccinated individuals in the absence of COVID-19 infection. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Electronic databases (Medline, Embase, Web of Science and WHO Global Literature on Coronavirus Disease), preprint repositories (medRxiv and bioRxiv), reference lists and grey literature were searched from 1 December 2020 until 31 October 2022. STUDY SELECTION: Epidemiological studies of individuals of any age who received at least one dose of an mRNA COVID-19 vaccine, reported a risk of myo/pericarditis and compared the risk of myo/pericarditis to individuals who did not receive any dose of an mRNA COVID-19 vaccine. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently conducted screening and data extraction. The rate of myo/pericarditis among vaccinated and unvaccinated groups was recorded, and the rate ratios were calculated. Additionally, the total number of individuals, case ascertainment criteria, percentage of males and history of SARS-CoV-2 infection were extracted for each study. Meta-analysis was done using a random-effects model. RESULTS: Seven studies met the inclusion criteria, of which six were included in the quantitative synthesis. Our meta-analysis indicates that within 30-day follow-up period, vaccinated individuals were twice as likely to develop myo/pericarditis in the absence of SARS-CoV-2 infection compared to unvaccinated individuals, with a rate ratio of 2.05 (95% CI 1.49-2.82). CONCLUSION: Although the absolute number of observed myo/pericarditis cases remains quite low, a higher risk was detected in those who received mRNA COVID-19 vaccinations compared with unvaccinated individuals in the absence of SARS-CoV-2 infection. Given the effectiveness of mRNA COVID-19 vaccines in preventing severe illnesses, hospitalisations and deaths, future research should focus on accurately determining the rates of myo/pericarditis linked to mRNA COVID-19 vaccines, understanding the biological mechanisms behind these rare cardiac events and identifying those most at risk.

A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing.

A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.

Risk of Myocarditis and Pericarditis among Young Adults following mRNA COVID-19 Vaccinations.

There have been reports of cases of myocarditis and pericarditis as rare complications following mRNA COVID-19 vaccinations among young adults. While most reported cases are mild, this potential vaccine safety signal should be closely monitored. Using data from the CDC and the Vaccine Adverse Event Reporting System (VAERS), we calculated the combined reporting rate of myocarditis and pericarditis stratified by age group, sex, vaccine dose, and manufacturer, and compared these rates to the crude background incidence rates. Compared to the general population prior to the administration of the first COVID-19 vaccines in December 2020, we identified a higher-than-expected reporting rate of myocarditis and pericarditis following mRNA vaccination; the risk was higher after a second vaccine dose, higher in males than in females, and decreased with age. The highest risk was seen in males 12-17 years of age with approximately 6 cases per 100,000 second doses. Our findings suggest an increased risk of myocarditis and pericarditis in young males following a second dose of an mRNA COVID-19 vaccine. Since these findings are based on safety signals derived from passive surveillance data, confirmatory epidemiological studies should be undertaken.

The use of categorical regression in the assessment of the risks of nutrient deficiency and excess

Exposure-response assessment methods have shifted towards more quantitative approaches, with health risk assessors exploring more statistically driven techniques. These assessments, however, usually rely on one critical health effect from a single key study. Categorical regression addresses this limitation by incorporating data from all relevant studies ­ including human, animal, and mechanistic studies ­ thereby including a broad spectrum of health endpoints and exposure levels for exposure-response analysis in an objective manner. Categorical regression requires the establishment of ordered response categories corresponding to increasingly severe adverse health outcomes and the availability of a comprehensive database that summarizes all data on different outcomes from different studies, including the exposure or dose at which these out-comes are observed and their severity. It has found application in the risk assessment of essential nutrients and trace metals. Since adverse effects may arise from either deficient or excess exposure, the exposure-response curve is U-shaped, which provides a basis for determining optimal intake levels that minimize the joint risks of deficiency and excess. This article provides an overview of the use of categorical regression fit exposure-response models incorporating data from multiple evidence streams. An extension of categorical regression that permits the simultaneous analysis of excess and deficiency toxicity data is presented and applied to comprehensive databases on copper and manganese. Future applications of cat-egorical regression will be able to make greater use of diverse data sets developed using new approach methodologies, which can be expected to provide valuable information on toxic responses of varying severity.

Horizon scanning for South African biodiversity: A need for social engagement as well as science.

A horizon scan was conducted to identify emerging and intensifying issues for biodiversity conservation in South Africa over the next 5-10 years. South African biodiversity experts submitted 63 issues of which ten were identified as priorities using the Delphi method. These priority issues were then plotted along axes of social agreement and scientific certainty, to ascertain whether issues might be "simple" (amenable to solutions from science alone), "complicated" (socially agreed upon but technically complicated), "complex" (scientifically challenging and significant levels of social disagreement) or "chaotic" (high social disagreement and highly scientifically challenging). Only three of the issues were likely to be resolved by improved science alone, while the remainder require engagement with social, economic and political factors. Fortunately, none of the issues were considered chaotic. Nevertheless, strategic communication, education and engagement with the populace and policy makers were considered vital for addressing emerging issues.

Conditional validation sampling for consistent risk estimation with binary outcome data subject to misclassification.

PURPOSE: Misclassification of a binary outcome can introduce bias in estimation of the odds-ratio associated with an exposure of interest in pharmacoepidemiology research. It has been previously demonstrated that utilizing information from an internal randomly selected validation sample can help mitigate this bias. METHODS: Using a Monte Carlo simulation-based approach, we study the properties of misclassification bias-adjusted odds-ratio estimators in a contingency table setting. We consider two methods of internal validation sampling; namely, simple random sampling and sampling conditional on the original (possibly incorrect) outcome status. Additional simulation studies are conducted to investigate these sampling approaches in a multi-table setting. RESULTS: We demonstrate that conditional validation sampling, across a range of subsampling fractions, can produce better estimates than those based on an unconditional simple random sample. This approach allows for greater flexibility in the chosen categorical composition of the validation data, as well as the potential for obtaining a more efficient estimator of the odds-ratio. We further demonstrate that this relationship holds for the Mantel-Haenszel misclassification bias-adjusted odds-ratio in stratified samples. Recommendations for the choice of validation subsampling fraction are also provided. CONCLUSIONS: Careful consideration when choosing the sampling scheme used to draw internal validation samples can improve the properties of the outcome misclassification bias-adjusted odds-ratio estimator in a (multiple) contingency table.

Perceptions of impact: Invasive alien plants in the urban environment.

Many alien plant species are introduced to urban areas to create, augment or restore ecosystem services (ES). However, many of these species spread beyond original plantings, sometimes causing negative effects on existing ES or creating novel ecosystem disservices (EDS). An understanding of the perceptions of urban residents regarding invasive alien plants (IAPs) and the ES and EDS they provide is needed for the effective prioritisation of IAP management efforts in cities. Using the city of Cape Town, South Africa as a case study, we conducted questionnaire-based surveys (online and face-to-face) to determine the perceptions of urban residents regarding IAPs and their capacity to provide ES and EDS. Most urban residents perceive IAPs negatively (i.e. agreeing that they create EDS), but many recognise their importance in providing ES. Although most residents are not opposed to the management of IAPs, such actions are not perceived as a high priority relative to other environmental problems. Socio-demographic variables such as age, education, environmental awareness, and ethnicity shape urban residents' perceptions of IAPs. Older, more educated respondents were more likely to perceive IAPs negatively, while respondents with greater environmental awareness were aware of the benefits provided by IAPs. This study highlights the need to integrate public perceptions into the planning and management of IAPs and emphasises the importance of including ES assessments into the decision-making process, particularly in urban areas.

A multi-criterion approach for prioritizing areas in urban ecosystems for active restoration following invasive plant control.

Resources for biodiversity conservation and invasive plant management are limited, and restoring invaded vegetation is labour-intensive and expensive. Managers must prioritize their actions to achieve their goals efficiently and effectively. They must distinguish between areas that require only the removal of invasive alien plants ("passive restoration") from those that require additional restoration measures ("active restoration"). This study used a multi-criterion approach (Analytical Hierarchical Process) to develop a framework for identifying areas that require active restoration, and then to prioritize these areas for active restoration. The South African city of Cape Town is used as a test case to illustrate the utility of the framework. Framework criteria selected in determining the need for active restoration included: dominant alien species invading the area, density of invasion, duration of invasion, indigenous vegetation cover, adjacent land use, level of disturbance, size of the area, aspect, soil texture, soil depth and erodibility, slope and vegetation type. In deciding which areas to prioritize for active restoration, factors such as vegetation conservation status, selection in a regional conservation plan and connectivity function were assessed. Importance in ecosystem functioning (by providing a diversity of habitats and soil conservation) and the delivery of ecosystem service benefits were also considered. The resulting framework provides an objective tool for prioritizing sites for active restoration.

Correction to: Managing Urban Plant Invasions: a Multi-Criteria Prioritization Approach.

The original version of the article unfortunately contained an error with the figure captions. The appropriate captions for Fig. 3-6 are published accordingly. The original article has been corrected.

Managing Urban Plant Invasions: a Multi-Criteria Prioritization Approach.

Alien plant invasions in urban areas can have considerable impact on biodiversity and ecosystem services (ES). Managing urban plant invasions is particularly challenging given the complex interactions between ecological, economic and social elements that exist in the urban milieu. Strategic landscape-scale insights are crucial for guiding management, as are tactical site-scale perspectives to plan and coordinate control efforts on the ground. Integrating these requirements to enhance management efficiency is a major challenge. Decision-support models have considerable potential for guiding and informing management strategies when problems are complex. This study uses multi-criteria decision tools to develop a prioritization framework for managing invasive alien plants (IAPs) in urban areas at landscape and local scales. We used the Analytic Hierarchy Process (AHP; a multi-criteria decision support model) to develop and rank criteria for prioritising IAP management in the City of Cape Town (CoCT), South Africa. Located within a global biodiversity hotspot, Cape Town has a long history of alien plant introductions and a complex socio-political make-up, creating a useful system to explore the challenges associated with managing urban plant invasions. To guide the prioritization of areas for IAP management across the CoCT, a stakeholder workshop was held to identify a goal and criteria for consideration, and to assess the relative importance given to each criterion in IAP management. Workshop attendees were drawn from multiple disciplines involved with different aspects of IAP research and management: government departments, scientists and researchers, and managers with a diverse set of skills and interests. We selected spatial datasets and applied our multi-criteria decision analysis in a Geographic Information System (GIS) to develop a landscape-scale prioritization map. To address issues relevant in an urban setting, we also modified an existing IAP management framework to develop a tactical (site-level) prioritization scheme for guiding on-the-ground control operations. High-priority sites for IAP management were identified at landscape- and local scales across the study area. Factors related to safety and security emerged as pivotal features for setting spatially-explicit priorities for management. The approach applied in this study can be useful for managers in all urban settings to guide the selection and prioritization of areas for IAP management.

A validation sampling approach for consistent estimation of adverse drug reaction risk with misclassified right-censored survival data.

Patient electronic health records, viewed as continuous-time right-censored survival data, can be used to estimate adverse drug reaction risk. Temporal outcome misclassification may occur as a result of errors in follow-up. These errors can be due to a failure to observe the incidence time of the adverse event of interest (due to misdiagnosis or nonreporting, etc) or an actual misdiagnosis of a competing adverse event. As the misclassifying event is often unobservable in the original data, we apply an internal validation sampling approach to produce consistent estimation in the presence of such errors. We introduce a univariate survival model and a cause-specific hazards model in which misclassification may also manifest as a diagnosis of an alternate adverse health outcome other than that of interest. We develop a method of maximum likelihood estimation of the model parameters and establish consistency and asymptotic normality of the estimators using standard results. We also conduct simulation studies to numerically investigate the finite sample properties of these estimators and the impact of ignoring the misclassification error.

Modeling U-Shaped Exposure-Response Relationships for Agents that Demonstrate Toxicity Due to Both Excess and Deficiency.

Essential elements such as copper and manganese may demonstrate U-shaped exposure-response relationships due to toxic responses occurring as a result of both excess and deficiency. Previous work on a copper toxicity database employed CatReg, a software program for categorical regression developed by the U.S. Environmental Protection Agency, to model copper excess and deficiency exposure-response relationships separately. This analysis involved the use of a severity scoring system to place diverse toxic responses on a common severity scale, thereby allowing their inclusion in the same CatReg model. In this article, we present methods for simultaneously fitting excess and deficiency data in the form of a single U-shaped exposure-response curve, the minimum of which occurs at the exposure level that minimizes the probability of an adverse outcome due to either excess or deficiency (or both). We also present a closed-form expression for the point at which the exposure-response curves for excess and deficiency cross, corresponding to the exposure level at which the risk of an adverse outcome due to excess is equal to that for deficiency. The application of these methods is illustrated using the same copper toxicity database noted above. The use of these methods permits the analysis of all available exposure-response data from multiple studies expressing multiple endpoints due to both excess and deficiency. The exposure level corresponding to the minimum of this U-shaped curve, and the confidence limits around this exposure level, may be useful in establishing an acceptable range of exposures that minimize the overall risk associated with the agent of interest.

Modeling U-shaped dose-response curves for manganese using categorical regression.

INTRODUCTION: Manganese is an essential nutrient which can cause adverse effects if ingested to excess or in insufficient amounts, leading to a U-shaped exposure-response relationship. Methods have recently been developed to describe such relationships by simultaneously modeling the exposure-response curves for excess and deficiency. These methods incorporate information from studies with diverse adverse health outcomes within the same analysis by assigning severity scores to achieve a common response metric for exposure-response modeling. OBJECTIVE: We aimed to provide an estimate of the optimal dietary intake of manganese to balance adverse effects from deficient or excess intake. METHODS: We undertook a systematic review of the literature from 1930 to 2013 and extracted information on adverse effects from manganese deficiency and excess to create a database on manganese toxicity following oral exposure. Although data were available for seven different species, only the data from rats was sufficiently comprehensive to support analytical modelling. The toxicological outcomes were standardized on an 18-point severity scale, allowing for a common analysis of all available toxicological data. Logistic regression modelling was used to simultaneously estimate the exposure-response profile for dietary deficiency and excess for manganese and generate a U-shaped exposure-response curve for all outcomes. RESULTS: Data were available on the adverse effects of 6113 rats. The nadir of the U-shaped joint response curve occurred at a manganese intake of 2.70mg/kgbw/day with a 95% confidence interval of 2.51-3.02. The extremes of both deficient and excess intake were associated with a 90% probability of some measurable adverse event. CONCLUSION: The manganese database supports estimation of optimal intake based on combining information on adverse effects from systematic review of published experiments. There is a need for more studies on humans. Translation of our results from rats to humans will require adjustment for interspecies differences in sensitivity to manganese.

Navigating complexity through knowledge coproduction: Mainstreaming ecosystem services into disaster risk reduction.

Achieving the policy and practice shifts needed to secure ecosystem services is hampered by the inherent complexities of ecosystem services and their management. Methods for the participatory production and exchange of knowledge offer an avenue to navigate this complexity together with the beneficiaries and managers of ecosystem services. We develop and apply a knowledge coproduction approach based on social-ecological systems research and assess its utility in generating shared knowledge and action for ecosystem services. The approach was piloted in South Africa across four case studies aimed at reducing the risk of disasters associated with floods, wildfires, storm waves, and droughts. Different configurations of stakeholders (knowledge brokers, assessment teams, implementers, and bridging agents) were involved in collaboratively designing each study, generating and exchanging knowledge, and planning for implementation. The approach proved useful in the development of shared knowledge on the sizable contribution of ecosystem services to disaster risk reduction. This knowledge was used by stakeholders to design and implement several actions to enhance ecosystem services, including new investments in ecosystem restoration, institutional changes in the private and public sector, and innovative partnerships of science, practice, and policy. By bringing together multiple disciplines, sectors, and stakeholders to jointly produce the knowledge needed to understand and manage a complex system, knowledge coproduction approaches offer an effective avenue for the improved integration of ecosystem services into decision making.

Natural hazards in a changing world: a case for ecosystem-based management.

Communities worldwide are increasingly affected by natural hazards such as floods, droughts, wildfires and storm-waves. However, the causes of these increases remain underexplored, often attributed to climate changes or changes in the patterns of human exposure. This paper aims to quantify the effect of climate change, as well as land cover change, on a suite of natural hazards. Changes to four natural hazards (floods, droughts, wildfires and storm-waves) were investigated through scenario-based models using land cover and climate change drivers as inputs. Findings showed that human-induced land cover changes are likely to increase natural hazards, in some cases quite substantially. Of the drivers explored, the uncontrolled spread of invasive alien trees was estimated to halve the monthly flows experienced during extremely dry periods, and also to double fire intensities. Changes to plantation forestry management shifted the 1:100 year flood event to a 1:80 year return period in the most extreme scenario. Severe 1:100 year storm-waves were estimated to occur on an annual basis with only modest human-induced coastal hardening, predominantly from removal of coastal foredunes and infrastructure development. This study suggests that through appropriate land use management (e.g. clearing invasive alien trees, re-vegetating clear-felled forests, and restoring coastal foredunes), it would be possible to reduce the impacts of natural hazards to a large degree. It also highlights the value of intact and well-managed landscapes and their role in reducing the probabilities and impacts of extreme climate events.

Mapping ecological processes and ecosystem services for prioritizing restoration efforts in a semi-arid Mediterranean river basin.

Semi-arid Mediterranean regions are highly susceptible to desertification processes which can reduce the benefits that people obtain from healthy ecosystems and thus threaten human wellbeing. The European Union Biodiversity Strategy to 2020 recognizes the need to incorporate ecosystem services into land-use management, conservation, and restoration actions. The inclusion of ecosystem services into restoration actions and plans is an emerging area of research, and there are few documented approaches and guidelines on how to undertake such an exercise. This paper responds to this need, and we demonstrate an approach for identifying both key ecosystem services provisioning areas and the spatial relationship between ecological processes and services. A degraded semi-arid Mediterranean river basin in north east Spain was used as a case study area. We show that the quantification and mapping of services are the first step required for both optimizing and targeting of specific local areas for restoration. Additionally, we provide guidelines for restoration planning at a watershed scale; establishing priorities for improving the delivery of ecosystem services at this scale; and prioritizing the sub-watersheds for restoration based on their potential for delivering a combination of key ecosystem services for the entire basin.

Statistical methods for active pharmacovigilance, with applications to diabetes drugs.

Pharmacovigilance aims to identify adverse drug reactions using postmarket surveillance data under real-world conditions of use. Unlike passive pharmacovigilance, which is based on largely voluntary (and hence incomplete) spontaneous reports of adverse drug reactions with limited information on patient characteristics, active pharmacovigilance is based on electronic health records containing detailed information about patient populations, thereby allowing consideration of modifying factors such as polypharmacy and comorbidity, as well as sociodemographic characteristics. With the present shift toward active pharmacovigilance, statistical methods capable of addressing the complexities of such data are needed. We describe four such methods here, and demonstrate their application in the analysis of a large retrospective cohort of diabetics taking anti-hyperglycemic medications that may increase the risk of adverse cardiovascular events.

A simple technique to enhance the humoral immune response to intracellular protein antigens in genetic immunizations.

A simple technique to enhance the humoral immune response to intracellular protein antigens in genetic immunizations is demonstrated in mice. In this approach, the intracellular protein is intentionally secreted from expressing cells as a chimeric protein, comprising an N-terminal secreted protein fused to the intracellular protein antigen. Using the Leishmania chagasi Ldccys1 cysteine protease (411CP) as an example of an intracellular protein antigen and both human and murine granulocyte colony stimulating factor (GMCSF) as examples of N-terminal secretion competent fusion partners in chimeric proteins, a humoral response in plasmid DNA immunized mice could only be detected by Western blotting when the expressed 411CP was secreted.

Outlier detection for a hierarchical Bayes model in a study of hospital variation in surgical procedures.

One of the most important aspects of profiling healthcare providers or services is constructing a model that is flexible enough to allow for random variation. At the same time, we wish to identify those institutions that clearly deviate from the usual standard of care. Here, we propose a hierarchical Bayes model to study the choice of surgical procedure for rectal cancer using data previously analysed by Simons et al.(1) Using hospitals as random effects, we construct a computationally simple graphical method for determining hospitals that are outliers; that is, they differ significantly from other hospitals of the same type in terms of surgical choice.