Managing Patients with Immune-Mediated Inflammatory Diseases on Disease-Modifying Antirheumatic Drug Therapy in a COVID-19 Endemic World: A Narrative Review and Expert Insights (preprint)

During the coronavirus disease 2019 (COVID-19) pandemic, individuals with immune-mediated inflammatory diseases (IMIDs), such as systemic lupus erythematosus and rheumatoid arthritis, face a heightened risk of infection and severe outcomes due to immunological alterations resulting from their underlying conditions and immunosuppressive treatments. Even as the pandemic has transitioned to an endemic state, it remains crucial to recognize that these patients continue to be at risk. In this narrative review, we analyzed existing literature to explore the impact of IMIDs, clinical risk factors, and the influence of immunosuppressive therapies on COVID-19-related risks and outcomes. Notably, certain disease-modifying antirheumatic drugs (DMARDs), like rituximab, are associated with worse COVID-19 outcomes, and rituximab-treated patients show impaired immune responses to COVID-19 vaccination. Additionally, we outline the diverse effects of glucocorticoids on COVID-19 outcomes and management. To highlight real-life challenges faced by clinicians caring for patients with IMIDs, we present an illustrative scenario that underscores the importance of effective vaccination, timely boosting, and additional mitigation strategies against COVID-19. Given the clinical heterogeneity and diverse disease states within IMIDs, it is crucial to understand the ongoing implications and risks associated with COVID-19 in these patients, to guide the implementation of appropriate measures and optimize care and outcomes in the current endemic era.

Perceptions of COVID-19 Vaccination among Organ Transplant Recipients (preprint)

Understanding vaccine hesitancy in organ transplant recipients (OTR) is critical, given clear, alt-hough attenuated, benefits from vaccination. Adult OTR were surveyed regarding vaccine-related values and a novel outcome variable called Vaccine Acceptance Composite Score (VACS) was built as the average Likert score of 7 domains of vaccination confidence. Of 46 OTR included (93.5% kidney transplant recipients), 32.6% were female, 13.3% Black, 6.77% Hispan-ic/Latino/a/x; median age was 58 years. Patients were most concerned about COVID-19 vac-cine-associated risks (46.3%), its potential effect on allograft (47.6%) and motives of government officials involved with vaccine policy (55.6%). Politically conservative patients were likely to have a significantly lower VACS, while those who lived with someone ≥65 had a higher VACS. The VACS was not significantly associated with race, income, religious beliefs, comorbidities, COVID-19 history, or influenza vaccination status. Higher VACS was significantly associated with ≥3 and ≥4 COVID-19 immunizations. This study highlighted political beliefs and elderly household members as correlates of vaccine acceptance among OTR. The VACS may be a useful tool to help standardize multifaceted analyses in vaccination-focused behavioral research, as well as identify individuals and groups at risk for vaccine hesitancy, who may benefit from tai-lored outreach and educational interventions.

Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategy (preprint)

The widespread use of social media has led to a surge in popularity for automated methods of analyzing public opinion. Supervised methods are adept at text categorization, yet the dynamic nature of social media discussions poses a continual challenge for these techniques due to the constant shifting of the focus. On the other hand, traditional unsupervised methods for extracting themes from public discourse, such as topic modeling, often reveal overarching patterns that might not capture specific nuances. Consequently, a significant portion of research into social media discourse still depends on labor-intensive manual coding techniques and a human-in-the-loop approach, which are both time-consuming and costly. In this work, we study the problem of discovering arguments associated with a specific theme. We propose a generic LLMs-in-the-Loop strategy that leverages the advanced capabilities of Large Language Models (LLMs) to extract latent arguments from social media messaging. To demonstrate our approach, we apply our framework to contentious topics. We use two publicly available datasets: (1) the climate campaigns dataset of 14k Facebook ads with 25 themes and (2) the COVID-19 vaccine campaigns dataset of 9k Facebook ads with 14 themes. Furthermore, we analyze demographic targeting and the adaptation of messaging based on real-world events.

Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach (preprint)

The risk of contracting SARS-CoV-2 via human milk-feeding is virtually non-existent. Adverse effects of COVID-19 vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Herein we aimed to determine if compositional changes in milk occur following infection or vaccination, including any evidence of vaccine components. Using an extensive multi-omics approach, we found that compared to unvaccinated individuals SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 hours for the mRNA-based Moderna vaccine (8 changed proteins), 3 days for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Together, our data provide evidence of only minimal changes in milk composition due to COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

Completeness of the COVID-19 Vaccination Schedule among Persons Experiencing Homelessness in Brazil (preprint)

Almost four years after COVID-19 was declared a global health emergency, equitable distribution of the vaccine remains a challenge, especially among homeless people, the fastest growing population in Brazil. Therefore, we sought to identify the factors associated with completion of the COVID-19 vaccination schedule among homeless people in Brazil. Materials and Methods: We carried out a cross-sectional study in the capital cities of Brazil's Federative Units, considering people living on the streets as the target population. We used a sequential inclusion approach, with individual interviews conducted by trained professionals, using a validated questionnaire. We used descriptive statistics to analyze the data and a binary logistic regression model to identify factors associated with homeless individuals who completed the COVID-19 vaccination schedule. Results: It was identified that the highest density of homeless people and indicators related to COVID-19 is located in the Northeast, Southeast and South regions of Brazil. The primary data sample consisted of 1,392 participants, predominantly male (n: 961; 69.0%), with an average age of 38.3±15.2 years, belonging to the black/brown race/color (n: 1,097; 78.8%), with an elementary school education (n: 1,060; 76.1%). The factors associated with completing the vaccination schedule were: receiving government aid (OR: 1.58; 95%CI: 1.09 - 2.30), visits from Health Agents from the Street Clinic (OR: 3.19; 95%CI: 1.95 - 5.36), history of COVID-19 (OR: 5.77; 95%CI: 3.17 - 11.15), support for mandatory vaccination against COVID-19 (OR: 3.76; 95%CI: 2.48 - 5.76), trust in the efficacy of vaccines (OR: 3.92; 95%CI: 2.63 - 5.89), seeking information from NGOs, street clinics, community leaders (OR: 1.91; 95%CI: 1.01 - 3.88) and trust in the Federal Government's statements on vaccines (OR: 1.57; 95%CI: 1.06 - 2.31).Conclusion: The study advances knowledge by highlighting the completeness of the COVID-19 vaccination schedule among the homeless population. The source of information proved to be one of the determinants of completeness, and the Unified Health System played a leading role in raising awareness among homeless people, notably through its strategy of street clinics, when available. The evidence points to the importance of affirmative and inclusive actions that guarantee access to the vaccine for homeless people.

Deaths averted by COVID-19 vaccination in select Latin American and Caribbean Countries: a modelling study (preprint)

BackgroundThe COVID-19 pandemic has had a significant impact on global health, with millions of lives lost worldwide. Vaccination has emerged as a crucial strategy in mitigating the impact of the disease. This study aims to estimate the number of deaths averted through vaccination in LAC during the first year and a half of vaccination rollout (January 2021 - May 2022). MethodsPublicly available data on COVID-19 deaths and vaccination rates were used to estimate the total number of deaths averted via vaccination in LAC. Using estimates for number of deaths, number of vaccinated, and vaccine effectiveness, a counterfactual estimated number of deaths observed without vaccination was calculated. Vaccine effectiveness estimates were obtained from published studies. The analysis focused on 17 countries in LAC and considered adults aged 18 years and above. FindingsAfter accounting for underreporting, the analysis estimated that over 1.49 million deaths were caused by COVID-19 in the selected countries during the study period. Without vaccination, the model estimated that between 2.10 and 4.11 million COVID-19 deaths would have occurred. Consequently, vaccination efforts resulted in approximately 610,000 to 2.61 million deaths averted. InterpretationThis study represents the first large-scale, multi-center estimate of population-level vaccine impact on COVID-19 mortality in LAC. The findings underscore the substantial impact of timely and widespread vaccination in averting COVID-19 deaths. These results provide crucial support for vaccination programs aimed at combating epidemic infectious diseases in the region and future pandemics. FundingThis study was funded by the Pan-American Health Organization (PAHO).

SARS-CoV-2 Antigen Rapid Detection Tests: test performance during the COVID-19 pandemic and the impact of COVID-19 vaccination (preprint)

IntroductionDuring the COVID-19 pandemic, SARS-CoV-2 antigen rapid detection tests (RDTs) emerged as point-of-care diagnostics in addition to the RT-qPCR as the gold standard for SARS-CoV-2 diagnostics. Facing the course of the COVID-19 pandemic to an endemic characterised by several SARS-CoV-2 virus variants of concern (VOC) and an increasing public COVID-19 vaccination rate the aim of the study was to investigate the long-term test performance of SARS-CoV-2 RDT in large-scale, clinical screening use during and its influencing factors, above all SARS-CoV-2 VOC and COVID-19 vaccination. MethodsIn a prospective performance assessment conducted at a single centre tertiary care hospital, RDTs from three manufacturers (NADAL(R), Panbio, MEDsan(R)) were compared to RT-qPCR among individuals aged [≥] 6 month. The evaluation involved the determination of standardised viral load from oropharyngeal swabs as well as the evaluation of their influencing factors, especially the COVID-19 vaccination, for detecting SARS-CoV-2 in a clinical point-of-care environment spanning from 12 November 2020 to 30 June 2023 among patients, staff, and visitors of the hospital. ResultsAmong the 78,798 RDT/RT-qPCR tandems analysed, 2,016 (2.6%) tandems tested positive for SARS-CoV-2, with an overall sensitivity of 34.5% (95% CI 32.4-36.6%). A logistic regression revealed that typical COVID-19 symptoms significantly declined over the course of the study and throughout the COVID-19 pandemic, and that among the vaccinated, significantly fewer presented with an infection exhibiting typical symptoms. The employed lasso regression model indicated that only higher viral load and typical COVID-19 symptoms significantly increase the likelihood of a positive RDT result in the case of a SARS-CoV-2 infection directly. ConclusionOur findings indicate that only viral load and COVID-19 symptoms directly influence RDT performance while the obtained effects of COVID-19 vaccination and Omicron VOC both reducing RDT performance were mediated by these two factors. RDTs remain an adequate diagnostic tool for detecting SARS-CoV-2 in individuals showing respiratory symptoms. RDTs show promise beyond SARS-CoV-2, proving adaptable for detecting other pathogens like Influenza and RSV, highlighting their ongoing importance in infection control and prevention efforts.

SIR-RL: Reinforcement Learning for Optimized Policy Control during Epidemiological Outbreaks in Emerging Market and Developing Economies (preprint)

The outbreak of COVID-19 has highlighted the intricate interplay between public health and economic stability on a global scale. This study proposes a novel reinforcement learning framework designed to optimize health and economic outcomes during pandemics. The framework leverages the SIR model, integrating both lockdown measures (via a stringency index) and vaccination strategies to simulate disease dynamics. The stringency index, indicative of the severity of lockdown measures, influences both the spread of the disease and the economic health of a country. Developing nations, which bear a disproportionate economic burden under stringent lockdowns, are the primary focus of our study. By implementing reinforcement learning, we aim to optimize governmental responses and strike a balance between the competing costs associated with public health and economic stability. This approach also enhances transparency in governmental decision-making by establishing a well-defined reward function for the reinforcement learning agent. In essence, this study introduces an innovative and ethical strategy to navigate the challenge of balancing public health and economic stability amidst infectious disease outbreaks.

Clustering Analysis of US COVID-19 Rates, Vaccine Participation, and Socioeconomic Factors (preprint)

The COVID-19 pandemic has presented unprecedented challenges worldwide, with its impact varying significantly across different geographic and socioeconomic contexts. This study employs a clustering analysis to examine the diversity of responses to the pandemic within the United States, aiming to provide nuanced insights into the effectiveness of various strategies. We utilize an unsupervised machine learning approach, specifically K-Means clustering, to analyze county-level data that includes variables such as infection rates, death rates, demographic profiles, and socio-economic factors. Our analysis identifies distinct clusters of counties based on their pandemic responses and outcomes, facilitating a detailed examination of "high-performing" and "lower-performing" groups. These classifications are informed by a combination of COVID-specific datasets and broader socio-economic data, allowing for a comprehensive understanding of the factors that contribute to differing levels of pandemic impact. The findings underscore the importance of tailored public health responses that consider local conditions and capabilities. Additionally, this study introduces an innovative visualization tool that aids in hypothesis testing and further research, enhancing the ability of policymakers and public health officials to deploy more effective and targeted interventions in future health crises.

COVID-19 vaccines as boosters or first doses: Simulating scenarios to minimize infections and deaths. (preprint)

Public health authorities face the issue of optimal vaccine distribution during spread of pandemics. In this paper, we study the optimal way to distribute a finite stock of COVID-19 doses between first or second doses for unvaccinated individuals and third doses (booster shots) for fully vaccinated individuals. We introduce a novel compartmental model that accommodates for vaccinated populations. This Booster model is implemented to simulate two prototypes of populations: one with a highly infected and highly vaccinated proportion, and another with a low infected and vaccinated percentage. We namely use sample data from Russia and Djibouti respectively. Our findings show that, to minimize the deaths for the first type of populations, around one quarter of the vaccines should be employed as booster shots and the rest as first and second doses. On the other hand, the second type of populations can minimize their number of deaths by mainly focusing on administering the initial two doses, rather than giving any booster shots. The novel Booster model allows us to study the effect of the third dose on a community and provides a useful tool to draw public policies on the distribution of vaccines during pandemics.

Antibody Responses to SARS-Cov-2 among Health Care Workers of a Tertiary Hospital in North-Eastern, Tanzania (preprint)

BackgroundHealth Care Workers (HCWs) have been playing crucial role in treating patient with COVID-19. They have a higher occupational risk of contracting the disease than the general population, and a greater chance of them transmitting the disease to vulnerable patients under their care. Given their scarcity and low COVID-19 vaccine acceptance in Africa, it is essential that HCWs are seroprotected and their exposure to COVID-19 minimized. This study was therefore designed to determine IgG antibody response to SARS-CoV-2 among HCWs in North Eastern, Tanzania. MethodologyThis was a cross-sectional study carried out among 273 HCWs at Kilimanjaro Christian Medical Centre (KCMC), a tertiary, zonal referral hospital in Tanzanias North Eastern region. Stratified sampling was used to select study participants. Data were obtained from each consenting participant using a validated questionnaire. Blood samples were collected for SARS-CoV-2 IgG antibodies quantification by using an indirect ELISA test. RedCap software was used to enter and manage data. Statistical analysis was done by using STATA statistical software version 15 and GraphPad Prism v 9.0. A p-value of < 0.05 was considered the cut-off for statistical significance. ResultsAmong 273 HCWS only 37.9 % reported to have received COVID-19 vaccine. Except for one person, all of the participants had SARS-CoV-2 IgG antibody concentrations that were positive, with 64.5% of them having strong seropositivity. Female gender, allied health professionals, active smoking, COVID-19 patient interactions, COVID-19 vaccination receptivity, and adherence to recommended hand hygiene were found to be significant predictors of variation of median SARS-CoV-2 antibody concentration. The usage of personal protective equipment, history of previously testing PCR positive for COVID-19, the number of COVID-19 patient exposure and age were found to cause no significant variation in median antibody concentration among participants. ConclusionsThis study reports a high seroprevalence of SARS-CoV-2 antibodies among healthcare workers in Kilimanjaro Christian Medical Centre. This suggests that HCWs have significant exposure to SARS-CoV-2 despite the low rate of vaccination acceptance even among HCWs. We recommend a strengthened Infectious Prevention and Control (IPC) in hospitals through provision of technical leadership and coordination according to WHO guidelines. We also recommend continued conduction of seroprevalence studies to estimate the magnitude and trends of SARS-CoV-2 infections in different populations in Tanzania. A better understanding of the past, current, and future transmission patterns of infectious pathogens is critical for preparedness and response planning, and to inform the optimal implementation of existing and novel interventions under the current and changing climate.

Effectiveness of the 2023-2024 Omicron XBB.1.5-containing mRNA COVID-19 vaccine (mRNA-1273.815) in preventing COVID-19-related hospitalizations and medical encounters among adults in the United States: An interim analysis (preprint)

Background/ObjectivesCOVID-19 continues to pose a significant burden that impacts public health and the healthcare system as the SARS-CoV-2 virus continues to evolve. Regularly updated vaccines are anticipated to boost waning immunity and provide protection against circulating variants. This study evaluated vaccine effectiveness (VE) of mRNA-1273.815, a 2023-2024 Omicron XBB.1.5-containing mRNA COVID-19 vaccine, at preventing COVID-19-related hospitalizations and any medically attended COVID-19 in adults [≥]18 years, overall, and by age and underlying medical conditions. MethodsThis retrospective cohort study used the Veradigm Network EHR linked to claims data to identify US adults [≥]18 years of age who received the mRNA-1273.815 vaccine (exposed) matched 1:1 to individuals who did not receive a 2023-2024 updated COVID-19 vaccine (unexposed). Patients in the unexposed cohort were randomly matched to eligible mRNA-1273.815 recipients. Inverse probability of treatment weighting was used to adjust for differences between the two cohorts. The exposed cohort was vaccinated between September 12, 2023, and December 15, 2023, and individuals in both cohorts were followed up for COVID-19-related hospitalizations and medically attended COVID-19 until December 31, 2023. A Cox regression model was used to estimate the hazard ratio (HR). VE of the mRNA-1273.815 vaccine in preventing COVID-19-related hospitalizations and any medically attended COVID-19 was estimated as 100*(1-HR). Subgroup analyses were performed for adults [≥]50, adults [≥]65, and individuals with underlying medical conditions associated with severe COVID-19 outcomes. ResultsOverall, 859,335 matched pairs of mRNA-1273.815 recipients and unexposed adults were identified. The mean age was 63 years, and 80% of the study population was [≥]50 years old. 61.5% of the mRNA-1273.815 cohort and 66.4% of the unexposed cohort had an underlying medical condition. Among the overall adult population ([≥]18 years), VE was 60.2% (53.4-66.0%) against COVID-19-related hospitalization and 33.1% (30.2%-35.9%) against medically attended COVID-19 over a median follow-up of 63 (IQR: 44-78) days. VE estimates by age and underlying medical conditions were similar. ConclusionsThese results demonstrate the significant protection provided by mRNA-1273.815 against COVID-19-related hospitalizations and any medically attended COVID-19 in adults 18 years and older, regardless of their vaccination history, and support CDC recommendations for vaccination with the 2023-2024 Omicron XBB.1.5-containing COVID-19 vaccine to prevent COVID-19-related outcomes, including hospitalizations.

Timing and Depth Selection for Sedated Gastroscopy After SARS-CoV-2 Infection—A Retrospective Cohort Study (preprint)

Background Sedated gastroscopy is a crucial procedure for patients with upper respiratory infections. SARS-CoV-2-infected patients are more susceptible to anesthesia-related complications, such as edema, pharyngeal mucosa congestion, laryngospasm, and pulmonary infections.Methods We retrospectively analyzed a total of 386 patients who underwent sedated gastroscopy at the Affiliated Hospital of Qingdao University during the SARS-CoV-2 infection period. The patients were divided into three groups based on SARS-CoV-2 status: Negative (N), Two-week post-SARS-CoV-2 infection (T), and Three-week post-SARS-CoV-2 infection (Th) groups. Based on the anesthesia method, patients were divided into mild/moderate sedation and deep sedation/general anesthesia groups. Additionally, patients were categorized into groups based on COVID-19 severity and vaccination status. We recorded the laryngeal mucosal conditions, the occurrence rates of adverse reactions such as coughing, laryngospasm, and transient oxygen desaturation during the examination, as well as the satisfaction of patients and endoscopists were recorded.Results The T group displayed a significantly higher occurrence rate of adverse reactions when compared to the N and Th group, with decreased satisfaction levels of patients and endoscopists. In the T group, the occurrence rate of adverse reactions was higher in mild to moderate sedation than in deep sedation/general anesthesia methods, while patient and endoscopist satisfaction was lower. In the Th group, there was no statistically significant difference in the examination success rate or patient satisfaction between the mild/moderate sedation and deep sedation/general anesthesia methods; however, endoscopist satisfaction was lower with mild/moderate sedation method than deep sedation/general anesthesia method. There was a significant difference in the gastroscopy success rates of patients with different COVID-19 classifications. A significant difference was observed in the gastroscopy success rates among patients with different vaccination statuses.Conclusions Sedated gastroscopy post-three weeks of SARS-CoV-2 infection is safe. Moreover, using a deep sedation/general anesthesia method for sedated gastroscopy in SARS-CoV-2-infected patients within three weeks is significantly safer.

Comprehensive Overview of Broadly Neutralizing Antibodies against SARS-COV-2 Variants (preprint)

Currently, SARS-CoV-2 has evolved into various variants, including the numerous highly mutated Omicron sub-lineages, significantly increasing immune evasion ability. The development raises concerns about possibly diminished effectiveness of available vaccines and antibody-based therapeutics. Here, we describe those representative categories of broadly neutralizing antibodies (bnAbs) that retain prominent effectiveness against emerging variants including Omicron sub-lineages. The molecular characteristics, epitope conservation, and resistance mechanisms of these antibodies are further detailed, aiming to offer suggestion or direction for the development of therapeutic antibodies, and facilitate the vaccine design with broad-spectrum potential.

COVID‐19 Vaccine Motivation and Hesitancy among a Sample of African American, Afro‐Caribbean, and African Respondents in the United States (preprint)

Understanding the motivations and decisions behind COVID-19 vaccine acceptance is crucial for designing targeted public health interventions to address vaccine hesitancy. We conducted a qualitative analysis to explore COVID-19 vaccine acceptance among diverse ethnic subgroups of Black Americans in the United States. This study investigates the responses of 79 African American, Afro-Caribbean, and African respondents over the age of 18 in Washington State and Texas between 2021-2022. Qualitative responses were analyzed by content category and ethnic subgroup. Of the 79 responses, 60 expressed favorable perceptions, 16 unfavorable, and 3 neutral. Dominant categories among participants in favor of the vaccine included personal health (26), concern for health of family/or community members (13), and desire to protect others (11). Among the 42 vaccinated African American respondents, the primary motivation was personal health (20). The 12 unvaccinated African American respondents cited fear of side-effects as the dominate motivation. Caribbean respondents cited family or elders as motivation for their decision. African respondents were nearly unanimous in taking the vaccine (13/16), citing trust in healthcare, protecting friends and family, and personal health as reasons. Community and personal relationships were critical decision-making factors in accepting the COVID-19 vaccine with African Americans having the strongest hesitancy.

N-protein vaccine Convacell(R) is effective against COVID-19: phase 3, randomized, double-blind, placebo-controlled clinical trial (preprint)

We have developed a Convacell(R), a COVID-19 vaccine based on the conservative viral nucleocapsid (N) protein. The N protein is evolutionary conservative and is abundantly expressed on the surface of infected cells, allowing anti-N immune response generated by Convacell(R) to rapidly clear infected cells and provide long-lasting protection against COVID-19. Convacell(R) has been demonstrated to be safe and highly immunogenic, creating immune responses lasting over a year, in phase I/II and IIb clinical trials. Phase IIb clinical trial has also demonstrated that a single dose vaccination regimen with Convacell(R) is sufficient to provide an immune response. Here we report the finding of the phase III clinical trial of Convacell(R). Two groups of volunteers from Russia have been either vaccinated with a single dose of Convacell(R) or injected with placebo, and then monitored for incidence of COVID-19 and adverse effects. Anti-N antibody titers at admission were also analyzed, to take into account for potential effects of previous virus encounters. Disease incidence over 6 months results indicate an overall vaccine efficacy of 85.2% (95% confidence interval: 67.4-93.3%). Additionally, Convacell(R) has shown a good safety profile. Overall, Convacell(R) demonstrated highly desirable qualities and good performance as a vaccine and can be considered as valuable COVID-19 preventative measure.