ABSTRACT
Vaccines against SARS-CoV-2, the virus that causes COVID-19, showed high efficacy against symptomatic illness caused by the ancestral strain. Yet recent variants such as Omicron and its sublineages substantially escape vaccine-induced neutralizing antibodies. In response, bivalent mRNA booster vaccines updated to better match the BA.4-5 lineages have been made available. Yet the reactogenicity of these vaccines might negatively impact willingness to receive the booster immunization. While serious side effects following vaccination are rare, mRNA vaccines frequently lead to mild adverse events such as injection site pain, lymphadenopathy, myalgia, and fever. Over-the-counter analgesics might mitigate some of these mild adverse events, but animal models of SARS-CoV-2 infection have shown that non-steroidal anti-inflammatory drugs (NSAIDs) substantially reduce antiviral antibody responses, which are the best correlates of protection against COVID-19. It remains unknown whether these same inhibitory effects are seen in humans after mRNA vaccination. We surveyed 6,010 individuals who received COVID-19 vaccines regarding analgesic use and correlated these results with Spike-specific antibody levels. We found no negative impact of analgesic use on antibody levels, and in fact observed slightly elevated concentrations of anti-Spike antibodies in individuals who used painkillers. Logistic regression analyses demonstrated a higher proportion of those experiencing fatigue and muscle aches between NSAID users and those not taking pain medication, suggesting that the elevated antibody levels were likely associated with inflammation and mild adverse events rather than analgesic use per se. Together, our results suggest no detriment to painkiller use to alleviate symptoms after vaccination against COVID-19.
Subject(s)
Pain , Fever , Lymphatic Diseases , Inflammation , Myalgia , COVID-19 , FatigueABSTRACT
Background Surgical Site Infections (SSIs) following craniotomy may be affected by extensive head vasculature. Attentive post-operative wound care to keep hair away, cleanse skin, and remove incisional clots that provide nutrients for organisms may help prevent SSIs. Methods In 2018, 72% of craniotomy SSIs at an academic medical center were related to post-operative wound disruption, drainage, and compromised wound healing. These SSIs involved Gram-positive organisms, consistent with skin flora. In January 2019, a post-operative wound care protocol developed by neurosurgical nurse and wound care specialists, and the infection prevention program was initiated, involving 1) soft bands to keep the incision clear of hair, and 2) 2% chlorhexidine gluconate (CHG) cloths to clean the incision and the proximal 6-inches of any drains, remove incisional clots, and clean adjacent skin and hair within 2 inches of the incision. Twice-weekly photos were taken of post-operative craniotomy wounds with protocol lapses and real-time feedback was provided to the bedside nurse, wound care nurse, and surgeon from February 2019-February 2020. Due to the Coronavirus Disease 2019 pandemic (COVID-19), the program progressively lapsed until January 2021, when it was reinstated. SSI rates were compared during the periods with and without the intervention using a chi-square test. Results Baseline Craniotomy SSI rate prior to January 2019 was 3.8% (5/133, SIR=2.6) and 1.7% (16/952, SIR=1.1) during the first intervention period. During COVID-19 surge, SSIs increased to 3.6% (5/140, SIR=2.3) without the intervention, and were restored to a lower rate, 1.6% (2/128, SIR=0.9) after the intervention was reinstituted. SSI rates were lower in intervention (1.7% (18/1080)) versus non-intervention periods (3.7% (10/273)), p=0.04. Conclusions A post-operative inpatient craniotomy wound care protocol involving hair care, incisional CHG cleansing and clot removal, plus photo documentation and feedback for protocol adherence was associated with SSI reduction.
ABSTRACT
Background The ongoing COVID-19 pandemic has placed an unprecedented health and economic burden on countries at all levels of socioeconomic development, emphasizing the need to evaluate the most effective vaccination strategy in multiple, diverse environments. The high reported efficacy, low cost, and long shelf-life of the ChAdOx1 nCoV-19 vaccine positions it well for evaluation in different settings. Methods Using data from the ongoing ChAdOx1 nCoV-19 clinical trials, an individual-based model was constructed to predict the 6-month population-level impact of vaccine deployment. A detailed probabilistic sensitivity analysis (PSA) was developed to evaluate the importance of epidemiological, demographic, immunological, and logistical factors in determining vaccine effectiveness. Using representative countries, logistical plans for vaccination rollout at various levels of vaccine availability and delivery speed, conditional on vaccine efficacy profiles (efficacy of the booster dose, time interval between doses, and relative efficacy of the first dose) were explored.Findings and Interpretation Our results highlight how expedient vaccine delivery to high-risk groups is critical in mitigating COVID-19 disease and mortality. In scenarios where the number of vaccine doses available is insufficient for high-risk groups (those aged more than 65 years) to receive two vaccine doses, administration of a single dose of vaccine is optimal. This effect is consistent even when vaccine efficacy after one dose is just 75% of the levels achieved after two doses. These findings offer a nuanced perspective of the critical drivers of COVID-19 vaccination effectiveness and can inform optimal allocation strategies. These are relevant to high-income countries with a large high-risk group population as well as to low-income countries with younger populations, where the cost and logistical challenges of procuring and delivering two doses for each citizen represent a significant challenge.
Subject(s)
COVID-19ABSTRACT
Thailand is facing the dilemma of which groups to prioritise for the limited first tranche of vaccinations in 2021. A mathematical modelling analysis was performed to compare the potential short-term impact of allocating the available doses to either the high-risk group (over 65-year-olds) or the high incidence group (aged 20-39). Vaccinating the high incidence group with a vaccine with sufficiently high protection against infection (more than 50%) could provide enough herd effects to delay the expected epidemic peak, resulting in fewer deaths within the 12-month time horizon compared to vaccinating the same number of the high-risk group. After 12 months, if no further vaccination or other interventions were deployed, this strategy would lead to more deaths. With the right vaccine efficacy profile, targeting the high incidence groups could be a viable short-term component of the Thai vaccination strategy. These results and emerging evidence on vaccines and susceptibility suggest prioritisation guidelines should be more nuanced.
Subject(s)
COVID-19ABSTRACT
Accurate knowledge of accurate levels of prior population exposure has critical ramifications for preparedness plans of subsequent SARS-CoV-2 epidemic waves and vaccine prioritization strategies. Serological studies can be used to estimate levels of past exposure and thus position populations in their epidemic timeline. To circumvent biases introduced by decaying antibody titers over time, population exposure estimation methods should account for seroreversion, to reflect that changes in seroprevalence measures over time are the net effect of increases due to recent transmission and decreases due to antibody waning. Here, we present a new method that combines multiple datasets (serology, mortality, and virus positivity ratios) to estimate seroreversion time and infection fatality ratios and simultaneously infer population exposure levels. The results indicate that the average time to seroreversion is six months, and that true exposure may be more than double the current seroprevalence levels reported for several regions of England.
Subject(s)
Encephalitis, ArbovirusABSTRACT
Background During the first months of the COVID-19 pandemic, Iran reported high numbers of infections and deaths in the Middle East region. In the following months, the burden of this infection decreased significantly, possibly due to the impact of a package of interventions. We modeled the dynamics of COVID-19 infection in Iran to quantify the impacts of these interventions.Methods We used a modified susceptible–exposed–infected–recovered (SEIR) model to model the COVID-19 epidemic in Iran, from 21 January to 21 September 2020, using Markov chain Monte Carlo simulation to calculate 95% uncertainty intervals (UI). We used the model to assess the effectiveness of physical distancing measures and self-isolation under different scenarios. We also estimated the control reproductive number (Rc), using our mathematical model and epidemiologic data.Results If no non-pharmaceutical interventions (NPIs) were applied, there could have been a cumulative number of 51,800,000 (95% UI: 19,100,000–77,600,000) COVID-19 infections and 266,000 (95% UI: 119,000–476,000) deaths by September 21 2020. If physical distancing interventions, such as school/border closures and self-isolation interventions, had been introduced a week earlier than they were actually launched, a 30% reduction in the number of infections and deaths could have been achieved by September 21 2020. The observed daily number of deaths showed that the Rc was one or more than one almost every day during the analysis period.Conclusions Our models suggest that the NPIs implemented in Iran between 21 January and 21 September 2020 had significant effects on the spread of the COVID-19 epidemic. Therefore, we recommend that these interventions are considered when designing future control programs, while simultaneously considering innovative approaches that can minimize harmful economic impacts on the community and the state. Our study also showed that the timely implementation of NPIs showed a profound effect on further reductions in the numbers of infections and deaths. This highlights the importance of forecasting and early detection of future waves of infection and of the need for effective preparedness and response capabilities.
Subject(s)
COVID-19 , DeathABSTRACT
Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.
Subject(s)
COVID-19 , Cognition DisordersABSTRACT
The widespread occurrence of SARS-CoV-2 has had a profound effect on society and a vaccine is currently being developed. Angiotensin-converting enzyme 2 (ACE2) is the primary host cell receptor that interacts with the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Although pneumonia is the main symptom in severe cases of SARS-CoV-2 infection, the expression levels of ACE2 in the lung is low, suggesting the presence of another receptor for the spike protein. In order to identify the additional receptors for the spike protein, we screened a receptor for the SARS-CoV-2 spike protein from the lung cDNA library. We cloned L-SIGN as a specific receptor for the N-terminal domain (NTD) of the SARS-CoV-2 spike protein. The RBD of the spike protein did not bind to L-SIGN. In addition, not only L-SIGN but also DC-SIGN, a closely related C-type lectin receptor to L-SIGN, bound to the NTD of the SARS-CoV-2 spike protein. Importantly, cells expressing L-SIGN and DC-SIGN were both infected by SARS-CoV-2. Furthermore, L-SIGN and DC-SIGN induced membrane fusion by associating with the SARS-CoV-2 spike protein. Serum antibodies from infected patients and a patient-derived monoclonal antibody against NTD inhibited SARS-CoV-2 infection of L-SIGN or DC-SIGN expressing cells. Our results highlight the important role of NTD in SARS-CoV-2 dissemination through L-SIGN and DC-SIGN and the significance of having anti-NTD neutralizing antibodies in antibody-based therapeutics.
Subject(s)
Pneumonia , Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
SARS-CoV-2 is a coronavirus that sparked the current COVID-19 pandemic. To stop the shattering effect of COVID-19, effective and safe vaccines, and antiviral therapies are urgently needed. To facilitate the preclinical evaluation of intervention approaches, relevant animal models need to be developed and validated. Rhesus macaques (Macaca mulatta) and cynomolgus macaques (Macaca fascicularis) are widely used in biomedical research and serve as models for SARS-CoV-2 infection. However, differences in study design make it difficult to compare and understand potential species-related differences. Here, we directly compared the course of SARS-CoV-2 infection in the two genetically closely-related macaque species. After inoculation with a low passage SARS-CoV-2 isolate, clinical, virological, and immunological characteristics were monitored. Both species showed slightly elevated body temperatures in the first days after exposure while a decrease in physical activity was only observed in the rhesus macaques and not in cynomolgus macaques. The virus was quantified in tracheal, nasal, and anal swabs, and in blood samples by qRT-PCR, and showed high similarity between the two species. Immunoglobulins were detected by various enzyme-linked immunosorbent assays (ELISAs) and showed seroconversion in all animals by day 10 post-infection. The cytokine responses were highly comparable between species and computed tomography (CT) imaging revealed pulmonary lesions in all animals. Consequently, we concluded that both rhesus and cynomolgus macaques represent valid models for evaluation of COVID-19 vaccine and antiviral candidates in a preclinical setting.
Subject(s)
COVID-19 , Lung DiseasesABSTRACT
The COVID-19 pandemic is a widespread and deadly public health crisis. The pathogen SARS-CoV-2 replicates in the lower respiratory tract and causes fatal pneumonia. Although tremendous efforts have been put into investigating the pathogeny of SARS-CoV-2, the underlying mechanism of how SARS-CoV-2 interacts with its host is largely unexplored. Here, by comparing the genomic sequences of SARS-CoV-2 and human, we identified five fully conserved elements in SARS-CoV-2 genome, which were termed as "human identical sequences (HIS)". HIS are also recognized in both SARS-CoV and MERS-CoV genome. Meanwhile, HIS-SARS-CoV-2 are highly conserved in the primate. Mechanically, HIS-SARS-CoV-2 RNA directly binds to the targeted loci in human genome and further interacts with host enhancers to activate the expression of adjacent and distant genes, including cytokines gene and angiotensin converting enzyme II (ACE2), a well-known cell entry receptor of SARS-CoV-2, and hyaluronan synthase 2 (HAS2), which further increases hyaluronan formation. Noteworthily, hyaluronan level in plasma of COVID-19 patients is tightly correlated with severity and high risk for acute respiratory distress syndrome (ARDS) and may act as a predictor for the progression of COVID-19. HIS antagomirs, which downregulate hyaluronan level effectively, and 4-Methylumbelliferone (MU), an inhibitor of hyaluronan synthesis, are potential drugs to relieve the ARDS related ground-glass pattern in lung for COVID-19 treatment. Our results revealed that unprecedented HIS elements of SARS-CoV-2 contribute to the cytokine storm and ARDS in COVID-19 patients. Thus, blocking HIS-involved activating processes or hyaluronan synthesis directly by 4-MU may be effective strategies to alleviate COVID-19 progression.
Subject(s)
Respiratory Distress Syndrome , Pneumonia , Severe Acute Respiratory Syndrome , Dissociative Identity Disorder , COVID-19ABSTRACT
Motivation: In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Results: Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19. Availability: https://neo4covid19.ncats.io . Keywords: SARS-CoV-2, COVID-19, network pharmacology, graph database, Neo4j, data integration, drug repositioning