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SummaryBackgroundDuring the first two years of the COVID-19 pandemic, the circulation of seasonal influenza viruses was unprecedentedly low. This led to concerns that the lack of immune stimulation to influenza viruses combined with waning antibody titres could lead to increased susceptibility to influenza in subsequent seasons, resulting in larger and more severe epidemics.MethodsWe analyzed historical influenza virus epidemiological data from 2003-2019 to assess the historical frequency of near-absence of seasonal influenza virus circulation and its impact on the size and severity of subsequent epidemics. Additionally, we measured haemagglutination inhibition-based antibody titres against seasonal influenza viruses using longitudinal serum samples from 165 healthy adults, collected before and during the COVID-19 pandemic, and estimated how antibody titres against seasonal influenza waned during the first two years of the pandemic.FindingsLow country-level prevalence of influenza virus (sub)types over one or more years occurred frequently before the COVID-19 pandemic and had relatively small impacts on subsequent epidemic size and severity. Additionally, antibody titres against seasonal influenza viruses waned negligibly during the first two years of the pandemic.InterpretationThe commonly held notion that lulls in influenza virus circulation, as observed during the COVID-19 pandemic, will lead to larger and/or more severe subsequent epidemics might not be fully warranted, and it is likely that post-lull seasons will be similar in size and severity to pre-lull seasons.FundingEuropean Research Council, Netherlands Organization for Scientific Research, Royal Dutch Academy of Sciences, Public Health Service of Amsterdam.Research in contextEvidence before this studyDuring the first years of the COVID-19 pandemic, the incidence of seasonal influenza was unusually low, leading to widespread concerns of exceptionally large and/or severe influenza epidemics in the coming years. We searched PubMed and Google Scholar using a combination of search terms (i.e., “seasonal influenza”, “SARS-CoV-2”, “COVID-19”, “low incidence”, “waning rates”, “immune protection”) and critically considered published articles and preprints that studied or reviewed the low incidence of seasonal influenza viruses since the start of the COVID-19 pandemic and its potential impact on future seasonal influenza epidemics. We found a substantial body of work describing how influenza virus circulation was reduced during the COVID-19 pandemic, and a number of studies projecting the size of future epidemics, each positing that post-pandemic epidemics are likely to be larger than those observed pre-pandemic. However, it remains unclear to what extent the assumed relationship between accumulated susceptibility and subsequent epidemic size holds, and it remains unknown to what extent antibody levels have waned during the COVID-19 pandemic. Both are potentially crucial for accurate prediction of post-pandemic epidemic sizes.Added value of this studyWe find that the relationship between epidemic size and severity and the magnitude of circulation in the preceding season(s) is decidedly more complex than assumed, with the magnitude of influenza circulation in preceding seasons having only limited effects on subsequent epidemic size and severity. Rather, epidemic size and severity are dominated by season-specific effects unrelated to the magnitude of circulation in the preceding season(s). Similarly, we find that antibody levels waned only modestly during the COVID-19 pandemic.Implications of all the available evidenceThe lack of changes observed in the patterns of measured antibody titres against seasonal influenza viruses in adults and nearly two decades of epidemiological data suggest that post-pandemic epidemic sizes will likely be similar to those observed pre-pandemic, and challenge the commonly held notion that the widespread concern that the near-absence of seasonal influenza virus circulation during the COVID-19 pandemic, or potential future lulls, are likely to result in larger influenza epidemics in subsequent years.

In this article, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for constructing multivariate distributions. Our multivariate COM-Poisson (MultCOMP) model has desirable features such as (i) it admits a flexible covariance matrix allowing for both negative and positive nondiagonal entries; (ii) it overcomes the limitation of the existing bivariate COM-Poisson distributions in the literature that do not have COM-Poisson marginals; (iii) it allows for the analysis of multivariate counts and is not just limited to bivariate counts. Inferential challenges are presented by the likelihood specification as it depends on a number of intractable normalizing constants involving the model parameters. These obstacles motivate us to propose Bayesian inferential approaches where the resulting doubly intractable posterior is handled with via the noisy exchange algorithm or the Grouped Independence Metropolis–Hastings algorithm. Numerical experiments based on simulations are presented to illustrate the proposed Bayesian approach. We demonstrate the potential of the MultCOMP model through a real data application on the numbers of goals scored by the home and away teams in the English Premier League from 2018 to 2021. Here, our interest is to assess the effect of a lack of crowds during the COVID-19 pandemic on the well-known home team advantage. A MultCOMP model fit shows that there is evidence of a decreased number of goals scored by the home team, not accompanied by a reduced score from the opponent. Hence, our analysis suggests a smaller home team advantage in the absence of crowds, which agrees with the opinion of several football experts. Supplementary materials for this article are available online.

Respiratory viruses such as influenza do not typically cause viremia; however, SARS-CoV-2 has been detected in the blood of COVID-19 patients with mild and severe symptoms. Detection of SARS-CoV-2 in blood raises questions about its role in pathogenesis as well as transfusion safety concerns. Blood donor reports of symptoms or a diagnosis of COVID-19 after donation (post-donation information, PDI) preceded or coincided with increased general population COVID-19 mortality. Plasma samples from 2,250 blood donors who reported possible COVID-19-related PDI were tested for the presence of SARS-CoV-2 RNA. Detection of RNAemia peaked at 9%-15% of PDI donors in late 2020 to early 2021 and fell to approximately 4% after implementation of widespread vaccination in the population. RNAemic donors were 1.2- to 1.4-fold more likely to report cough or shortness of breath and 1.8-fold more likely to report change in taste or smell compared with infected donors without detectable RNAemia. No infectious virus was detected in plasma from RNAemic donors; inoculation of permissive cell lines produced less than 0.7-7 plaque-forming units (PFU)/mL and in susceptible mice less than 100 PFU/mL in RNA-positive plasma based on limits of detection in these models. These findings suggest that blood transfusions are highly unlikely to transmit SARS-CoV-2 infection.

Long COVID, a type of post-acute sequelae of SARS-CoV-2 (PASC), has been associated with sustained elevated levels of immune activation and inflammation. However, the mechanisms that drive this inflammation remain unknown. Inflammation during acute coronavirus disease 2019 could be exacerbated by microbial translocation (from the gut and/or lung) to blood. Whether microbial translocation contributes to inflammation during PASC is unknown. We did not observe a significant elevation in plasma markers of bacterial translocation during PASC. However, we observed higher levels of fungal translocation - measured as β-glucan, a fungal cell wall polysaccharide - in the plasma of individuals experiencing PASC compared with those without PASC or SARS-CoV-2-negative controls. The higher β-glucan correlated with higher inflammation and elevated levels of host metabolites involved in activating N-methyl-d-aspartate receptors (such as metabolites within the tryptophan catabolism pathway) with established neurotoxic properties. Mechanistically, β-glucan can directly induce inflammation by binding to myeloid cells (via Dectin-1) and activating Syk/NF-κB signaling. Using a Dectin-1/NF-κB reporter model, we found that plasma from individuals experiencing PASC induced higher NF-κB signaling compared with plasma from negative controls. This higher NF-κB signaling was abrogated by piceatannol (Syk inhibitor). These data suggest a potential targetable mechanism linking fungal translocation and inflammation during PASC.

AbstractThe pandemic outbreak of coronavirus disease 2019 (COVID-19) has created health challenges in all parts of the world. Understanding the entry mechanism of this virus into host cells is essential for effective treatment of COVID-19 disease. This virus can bind to various cell surface molecules or receptors, such as angiotensin-converting enzyme 2 (ACE2), to gain cell entry. Respiratory failure and pulmonary edema are the most important causes of mortality from COVID-19 infections. Cytokines, especially proinflammatory cytokines, are the main mediators of these complications. For normal respiratory function, a healthy air–blood barrier and sufficient blood flow to the lungs are required. In this review, we first discuss airway epithelial cells, airway stem cells, and the expression of COVID-19 receptors in the airway epithelium. Then, we discuss the suggested molecular mechanisms of endothelial dysfunction and blood vessel damage in COVID-19. Coagulopathy can be caused by platelet activation leading to clots, which restrict blood flow to the lungs and lead to respiratory failure. Finally, we present an overview of the effects of immune and non-immune cells and cytokines in COVID-19-related respiratory failure.

Abstract Background: Tuberculosis (TB) represents a significant public health threat in India. Adherence to antitubercular therapy (ATT) is the key to reducing the burden of this infectious disease. Suboptimal adherence to ATT and lack of demonstrated feasibility of current strategies for monitoring ATT adherence highlights the need for alternative adherence monitoring systems.Methods: A quantitative survey was conducted to assess the acceptance of and willingness to use a digital pill system (DPS) as a tool for monitoring ATT adherence among stakeholders directly involved in the management of patients with TB in India. Participants reviewed a video explaining the DPS and completed a survey, which covered sociodemographics, degree of involvement with TB patients, initial impressions of the DPS, and perceived challenges for deploying the technology in India. Participants were also asked to interpret mock DPS adherence data.Results: The mean age was 34.3 (SD=7.3), and participants (N=50) were predominantly male (70%). The sample comprised internists (52%) and pulmonologists (30%), with a median of four years’ experience (IQR 3,6) in the management of TB patients. No participants had previously used a DPS, but some reported prior awareness of the technology (22%). Most reported that they would recommend use of a DPS to patients on ATT (76%), and that they would use a DPS in both the intensive and continuation phases of TB management (64%). The majority viewed the DPS (82%) as a useful alternative to directly observed therapy-short course (DOTS), particularly given the ongoing COVID-19 pandemic. Participants reported that a DPS would be most effective in patients at risk of nonadherence (64%), as well as those with past nonadherence (64%). Perceived barriers to DPS implementation included lack of patient willingness (92%), cost (86%), and infrastructure constraints (66%). The majority of participants were able to accurately interpret patterns of adherence (80%), suboptimal adherence (90%), and frank nonadherence (82%) when provided with mock DPS data.Conclusions: DPS are viewed as an acceptable, feasible, and useful technology for monitoring ATT adherence by stakeholders directly involved in TB management. Future investigations should explore patient acceptance of DPS and pilot demonstration of the system in the TB context.

Abstract Background Alabama is one of seven priority states for the National Ending the HIV Epidemic Initiative due to a large rural burden of disease. Mental health (MH) and substance use disorders (SUD) represent obstacles to HIV care in rural areas lacking Medicaid expansion and infrastructure. Evidence-informed technologies, such as telehealth, may enhance SUD and MH services but remain understudied in rural regions. Methods We conducted a readiness assessment using a mixed methods approach to explore opportunities for enhanced SUD and MH screening using electronic patient reported outcomes (ePROs) and telehealth at five Ryan White HIV/AIDS Program-funded clinics in AL. Clinic providers and staff from each site (N = 16) completed the Organizational Readiness to Implement Change (ORIC) assessment and interviews regarding existing services and readiness to change. People with HIV from each site (PLH, N = 18) completed surveys on the acceptability and accessibility of technology for healthcare. Results Surveys and interviews revealed that all clinics screen for depression annually by use of the Patient Health Questionnaire-9 (PHQ9). SUD screening is less frequent and unstandardized. Telehealth is available at all sites, with three of the five sites beginning services due to the COVID-19 pandemic; however, telehealth for MH and SUD services is not standardized across sites. Results demonstrate an overall readiness to adopt standardized screenings and expand telehealth services beyond HIV services at clinics. There were several concerns including Wi-Fi access, staff capacity, and patients’ technological literacy. A sample of 18 people with HIV (PWH), ages 18 to 65 years, participated in surveys; all demonstrated adequate technology literacy. A majority had accessed telehealth and were not concerned about it being too complicated or limiting communication. There were some concerns around lack of in-person interaction and lack of a physical exam and high-quality care with telehealth. Conclusion This study of PWH and the clinics that serve them reveals opportunities to expand SUD and MH services in rural regions using technology. Areas for improvement include implementing routine SUD screening, expanding telehealth while maintaining opportunities for in-person interaction, and using standardized ePROs that are completed by patients, in order to minimize stigma and bias.

Abstract Background Syringe service programs (SSPs) provide essential harm reduction and prevention services for people who inject drugs in the USA, where SSP coverage is expanding. During the COVID-19 pandemic, US SSPs underwent unprecedented shifts in operational procedures (e.g., closures of physical sites, staff redeployment into pandemic response efforts). Given the critical role of US SSP workers in the pandemic, we sought to explore the occupational experiences and well-being of SSP staff to inform future emergency response efforts. Methods From July–October 2020, we conducted semi-structured interviews with staff members of four SSPs in diverse regions of Massachusetts. Trained interviewers administered qualitative interviews virtually. Interviews were coded in NVivo v12 and thematic analysis identified common occupational experiences and related impacts on staff well-being in the context of the COVID-19 pandemic. Results Among 18 participants, 12 (67%) had client-facing roles such as harm reduction specialists and six (33%) worked in program management or leadership. We found that staff were frequently anxious about SARS-CoV-2 transmission, which contributed to staff turnover. SSPs rapidly adapted and expanded their services to meet increasing client needs during the pandemic (e.g., food distribution, COVID-19 testing), leading to staff overexertion. Simultaneously, public health measures such as physical distancing led to staff concerns about reduced social connections with clients and coworkers. Through these challenges, SSPs worked to protect staff well-being by implementing flexible and tangible COVID-19-related policies (e.g., paid sick leave), mental health resources, and frequent communication regarding pandemic-related operational changes. Conclusion SSPs in the USA adapted to the COVID-19 pandemic out of necessity, resulting in operational changes that threatened staff well-being. Despite the protective factors revealed in some narratives, our findings suggest that during prolonged, complex public health emergencies, SSPs may benefit from enhanced occupational supports to prevent burnout and promote wellness for this essential public health workforce.

We conducted a retrospective observational study using remote wearable and mobile application data to evaluate whether US public holidays or Daylight Saving Time transitions were associated with significant changes in sleep behaviors, including sleep duration, sleep onset and offset, and the consistency of sleep timing, as well as changes in the point prevalence of alcohol use. These metrics were analyzed using objective, high resolution sleep-wake data (10,350,760 sleep episodes) and 5,777,008 survey responses of 24,250 US subscribers (74.5% male; mean age of 37.6 ± 9.8 years) to the wrist-worn biometric device platform, WHOOP (Boston, Massachusetts, United States), who were active users during 1 May 2020, through 1 May 2021. Compared to baseline, statistically significant differences in sleep and alcohol measures were found on most DST transitions, US public holidays, and their eves. For example, New Year’s Eve corresponded with a sleep consistency decrease of 13.8 ± 0.3%, a sleep onset delay of 88.9 ± 3.2 min (00:01 vs. 22:33 baseline) later, a sleep offset delay of 78.1 ± 3.1 min (07:56 vs. 06:39), and an increase in the prevalence of alcohol consumption, with more than twice as many participants having reported alcohol consumption [+138.0% ± 6.7 (74.2% vs. 31.2%)] compared to baseline. In this analysis of a non-random sample of mostly male subscribers conducted during the COVID-19 pandemic, the majority of US public holidays and holiday eves were associated with sample-level increases in sleep duration, decreases in sleep consistency, later sleep onset and offset, and increases in the prevalence of alcohol consumption. Future work would be warranted to explore the generalizability of these findings and their public health implications, including in more representative samples and over longer time intervals.

Understanding how best to estimate state-level policy effects is important, and several unanswered questions remain, particularly about the ability of statistical models to disentangle the effects of concurrently enacted policies. In practice, many policy evaluation studies do not attempt to control for effects of co-occurring policies, and this issue has not received extensive attention in the methodological literature to date. In this study, we utilized Monte Carlo simulations to assess the impact of co-occurring policies on the performance of commonly-used statistical models in state policy evaluations. Simulation conditions varied effect sizes of the co-occurring policies and length of time between policy enactment dates, among other factors. Outcome data (annual state-specific opioid mortality rate per 100,000) were obtained from 1999-2016 National Vital Statistics System (NVSS) Multiple Cause of Death mortality files, thus yielding longitudinal annual state-level data over 18 years from 50 states. When co-occurring policies are ignored (i.e., omitted from the analytic model), our results demonstrated that high relative bias (>85%) arises, particularly when policies are enacted in rapid succession. Moreover, as expected, controlling for all co-occurring policies will effectively mitigate the threat of confounding bias; however, effect estimates may be relatively imprecise (i.e., larger variance) when policies are enacted in near succession. Our findings highlight several key methodological issues regarding co-occurring policies in the context of opioid-policy research yet also generalize more broadly to evaluation of other state-level policies, such as policies related to firearms or COVID-19, showcasing the need to think critically about co-occurring policies that are likely to influence the outcome when specifying analytic models. Health Serv Outcomes Res Method (2022)