Exposure to air pollution in epidemiological studies in Kuwait: A systematic review (preprint)

Objective To systematically review the epidemiological studies of human exposure to air pollution in Kuwait. Methods Specific keywords related to air pollution and health effects in Kuwait were systematically searched using PubMed and BASE search engines for published research in English language from the year 1990 up to June 2020. Non eligible studies were those which published in non-English studies, studies on animals, plants, exposure to pollutants other that air pollutants, studies related to oil fires caused by Iraqi invasion to Kuwait in 1991. After duplicates were removed, titles and abstracts of eligible studies were screened and full text of publications meeting the inclusion criteria was read. Non-epidemiological studies were included only to compare their numbers to the epidemiological studies, and to help in future studies. Results Total of 85 studies including epidemiological and non-epidemiological studies, only 8 of them found to be an epidemiological study, which 4 of them concerned with mortality and 3 with morbidity, and 1 with both morbidity and mortality. Two of these studies concern with respiratory disease, 1 of them concerned with atopic dermatitis and was the only study measured indoors (i.e. house), and 1 study concerned with rheumatoid arthritis. One study measured ETS, 4 studies measured dust, 2 studies measured PM10 and PM2.5, and 1 study measured NO2, SO2, O3, CO. All studies found that exposure to air pollution has adverse effect on health problems (i.e. respiratory problems, atopic dermatitis, rheumatoid arthritis) and mortality except one study found no significant correlation between exposure to air pollution (i.e. dust) and mortality. Conclusion Epidemiological studies related to human exposure to air pollution in Kuwait are underestimated and insufficient, there are extremely limited studies that cannot be compared to each other. Since currently Kuwait have many major constructions in major roads in and out the capital which alters the air pollution, adding to that the new study which found that the new current global epidemic namely coronavirus COVID-19 is correlated to air pollution (i.e. NO2), new researches need to be done measuring the different pollutants in both indoor and outdoor exposure examining different health problems, these researches need to be done during and after these circumstances for comparison.

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: a nationwide test-negative case-control study in the Netherlands (preprint)

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modelled ambient concentrations of PM10, PM2.5,  NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017-2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5,  NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health.

Functional assessment of cell entry and receptor use for merbecoviruses (preprint)

The merbecovirus subgenus of coronaviruses includes Middle East Respiratory Syndrome Coronavirus (MERS-CoV), which is a zoonotic respiratory pathogen that transmits from dromedary camels to humans and causes severe respiratory disease. Viral discovery efforts have uncovered hundreds of merbecoviruses in different species across multiple continents, but few of these viruses have been isolated or studied under laboratory conditions, leaving basic questions regarding their threat to humans unresolved. Viral entry into host cells is considered an early and critical step for transmission between hosts. In this study, a scalable approach to assessing novel merbecovirus cell entry was developed and used to measure receptor use across the entire merbecovirus subgenus. Merbecoviruses are sorted into four clades based on the receptor binding domain of the spike glycoprotein. Receptor tropism is clade-specific, with only one clade using DPP4 and multiple clades using ACE2, including the entire HKU5 cluster of bat coronaviruses.

Plasma bioactive adrenomedullin predicts mortality and need for dialysis in critical COVID-19 (preprint)

COVID-19 is a severe respiratory disease affecting millions worldwide, causing significant morbidity and mortality. Adrenomedullin (bio-ADM) is a vasoactive hormone regulating the endothelial barrier and has been associated with COVID-19 mortality and other adverse events. This prospective cohort study included 119 consecutive patients with verified SARS-CoV-2infection admitted to the intensive care unit (ICU). Bio-ADM was retrospectively analysed from plasma on ICU admission, day2, and day 7. Information on comorbidities, adverse events and mortality was collected. The primary outcome was 90-daymortality, and secondary outcomes were markers of disease severity. The association between bio-ADM and outcomes was analysed using survival analysis, logistic regression and receiver operating characteristics curves. Bio-ADM predicts 90-daymortality with an area under the receiver operating Curve (AUC) of 0.66, 0.68, and 0.70 for sampling on admission, day 2 and day 7. Age alone predicted 90-day mortality with an AUC of 0.78. The AUCs for age combined with bio-ADM were 0.81, 0.81,and 0.82 (n.s.). Bio-ADM predicted the need for renal replacement therapy with AUCs of 0.77, 0.82, and 0.81. Bio-ADM on ICU admission, day 2 and day 7 predicted 90-day mortality and dialysis needs, which highlights the importance of bio-ADM inCOVID-19 pathophysiology. Bio-ADM could be used to triage patients with a risk of adverse outcomes and as a potential target for clinical interventions

Estimating the impact of public health interventions on COVID mortality in the United States using reductions in influenza mortality as an indicator of non-pharmaceutical infection control (preprint)

Background: Non-pharmaceutical interventions (NPIs) for control of COVID include a range of methods from masks to closures of schools and businesses with the efficacy of any individual strategy contingent on which other NPIs are employed and the extent of compliance with those strategies. In the case of a public health intervention, one typically looks at historical data for comparison, but, because COVID is a new disease, we have no such data. However, we do have extensive historical data for influenza, a respiratory disease with similar modes of transmission. Influenza incidence and mortality dropped dramatically during the COVID pandemic, almost certainly because of these NPIs. The extent of that drop provides an indirect measure of the efficacy of COVID NPIs in stopping the transmission of respiratory infections. This study evaluates the association of influenza mortality reduction (IMR) during the pandemic with age-adjusted COVID mortality among US states, adjusting for mortality prior to the introduction of NPIs and vaccination rates, while taking into account the impact of population density on NPI effectiveness. Results A simple linear model with pre-intervention COVID mortality, IMR, vaccination rate, and population density explained 70% of the state-to-state variability in age adjusted COVID mortality. The resulting model suggests that NPIs prevented 831,000 COVID related deaths in the United States over the course of the pandemic. Conclusions These results provide strong evidence that IMR is an accurate indicator of the efficacy of NPIs in controlling transmission of respiratory infections, including COVID. This analysis suggests that NPIs together with vaccination prevented an estimated 2.15 million COVID related deaths and full intervention could have prevented over 700,000 more.  

Sputum production and salivary microbiome in COVID-19 patients reveals oral-lung axis (preprint)

Objective: SARS-CoV-2 is a severe respiratory disease that primarily targets the lungs and was the leading cause of death worldwide during the pandemic. Investigating the intricate interplay between the oral microbiome and inflammatory cytokines during the acute phase of infection is crucial for understanding host immune responses. This study aimed to explore the relationship between the oral microbiome and cytokines in COVID-19 patients, specifically examining those with and without sputum production. Methods: Saliva and blood samples from 50 COVID-19 patients were subjected to 16S ribosomal RNA gene sequencing to analyze the oral microbiome. Additionally, 65 saliva and serum cytokines were assessed using Luminex multiplex analysis. The Mann-Whitney test compared cytokine levels between individuals with and without sputum production. Results: Our study revealed significant differences in the membership (Jaccard dissimilarity: p=0.016) and abundance (PhILR dissimilarity: p=0.048; metagenomeSeq) of salivary microbial communities between COVID-19 patients with and without sputum production. Seven bacterial genera, including Prevotella, Streptococcus, Actinomyces, Atopobium, Filifactor, Leptotrichia, and Selenomonas, were present in statistically higher proportions of patients with sputum production (p<0.05, Fisher's exact test). Eight bacterial genera, including Prevotella, Megasphaera, Stomatobaculum, Leptotrichia, Veillonella, Actinomyces, Atopobium, and Corynebacteria were significantly more abundant in the sputum-producing group, while Lachnoacaerobaculum was notably more prevalent in the non-sputum-producing group (p<0.05, ANCOM-BC).We observed a significant positive correlation between salivary IFN-gamma (Interferon-gamma) and Eotaxin2/CCL24 (chemokine ligand 24) with sputum production. Conversely, negative correlations were noted in serum MCP3/CCL7 (monocyte-chemotactic protein 3/Chemokine ligand 7), MIG/CXCL9 (Monokine induced by gamma/Chemokine ligand 9), IL1 beta (interleukin 1 beta), and SCF (stem cell factor) with sputum production (p<0.05, Mann-Whitney test). Conclusion: Substantial distinctions in salivary microbial communities were evident between COVID-19 patients with and without sputum production, emphasizing the notable impact of sputum production on the oral microbiome and cytokine levels during the acute phase of infection.

Prognostic factors for mortality, ICU, MIS-C and hospital admission due to SARS-CoV-2 in paediatric patients: A systematic review and meta-analysis (preprint)

ABSTRACT Background: There is a paucity of data on the factors associated with severe COVID-19 disease, especially in children. This systematic review and meta-analysis aim to identify the risk factors for acute adverse outcomes of COVID-19 within paediatric populations, using the recruitment setting as a proxy of initial disease severity. Methods: A systematic review and meta-analysis were performed representing published evidence from the start of the pandemic up to 14 February 2022. Our primary outcome was the identification of risk factors for adverse outcomes, stratified by recruitment setting (community, hospital). No geographical restrictions were imposed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to evaluate the certainty in the body of evidence for each meta-analysis. In anticipation of significant clinical and methodological heterogeneity in the meta-analyses, we fitted logistic regression models with random effects. Findings: Our review identified 47 studies involving 94,210 paediatric cases of COVID-19. Infants up to 3 months were more likely to be hospitalised than older children. Gender and ethnicity were not associated with an increased likelihood of adverse outcomes among children within the community setting. Concerning comorbidities, having at least one pre-existing disease increased the odds of hospitalisation. Concerning BMI, underweight children and severely obese were noted to have an increased likelihood of hospital admission. The presence of metabolic disorders and children with underlying cardiovascular diseases, respiratory disorders, neuromuscular disorders and neurologic conditions were also more likely to be hospitalised. Concerning underlying comorbidities, paediatric hospitalised patients with congenital/genetic disease, those obese, with malignancy, cardiovascular diseases and respiratory disease were associated with higher odds of being admitted to ICU or ventilated. Interpretation: Our findings suggest that age, male, gender, and paediatric comorbidities increased the likelihood of hospital and ICU admission. Obesity, malignancy, and respiratory and cardiovascular disorders were among the most important risk factors for hospital and ICU admission among children with COVID-19. The extent to which these factors were linked to actual severity or where the application of cautious preventive care is an area in which further research is needed.

Changes of respiratory pathogen and clinical features of in acute exacerbation of chronic obstructive pulmonary disease after COVID-19 pandemic (preprint)

Respiratory infections are common causes of acute exacerbation of chronic obstructive lung disease (AECOPD). We explored whether the pathogens causing AECOPD and clinical features changed from before to after the coronavirus disease 2019 (COVID-19) outbreak. We reviewed the medical records of patients hospitalized with AECOPD at four university hospitals between January 2017 and December 2018 and between January 2021 and December. We evaluated 1,180 patients with AECOPD for whom medication histories were available. After the outbreak, the number of patients hospitalized with AECOPD was almost 44% lower compared with before the outbreak. Patients hospitalized with AECOPD after the outbreak were younger (75 vs. 77 years, p = 0.003) and more often stayed at home (96.6% vs. 88.6%, p < 0.001) than patients of AECOPD before the outbreak. Hospital stay was longer after the outbreak than before the outbreak (10 vs. 8 days. p < 0.001). After the COVID-19 outbreak, the identification rates of S. pneumoniae (15.3 vs. 6.2%, p < 0.001) and Hemophilus influenzae (6.4 vs. 2.4%, p = 0.002) decreased, whereas the identification rates of P. aeruginosa (9.4 vs. 13.7%, p = 0.023), Klebsiella pneumoniae (5.3 vs. 9.8%, p = 0.004), and methicillin-resistant Staphylococcus aureus (1.0 vs. 2.8%, p = 0.023) increased. After the outbreak, the identification rate of influenza A decreased (10.4 vs. 1.0%, p = 0.023). After the outbreak, the number of patients hospitalized with AECOPD was lower and the identification rates of community-transmitted pathogens tended to decrease, whereas the rates of pathogens capable of chronic colonization tended to increase. During the period of large-scale viral outbreaks that require quarantine, patients with AECOPD should consider treatment against strains that can colonize chronic respiratory disease rather than community acquired pathogens.

A Systematic Review of the Epidemiology of Human Respiratory Viruses in Indonesia (preprint)

Viral pathogens greatly contribute to higher respiratory disease burden among individuals living in low-to-middle income countries (LMICs). In Indonesia, influenza-like illness (ILI) and severe acute respiratory infection (SARI) surveillance networks have been established to better understand the epidemiology of viral respiratory disease; however, due to limited resources and operational capacity, data from these systems are sparse. Here, we summarize the results of a literature review conducted to identify published articles related to human respiratory viruses in Indonesia. We identified 66 scientific articles, published between 1998 and 2021. Of these, 21 (31.8%) studied influenza A or B, 17 (25.8%) studied influenza H5N1, 19 (28.8%) studied coronaviruses, 5 (7.6 %) studied RSV, and 2 (3.0 %) studied enterovirus. Our findings show that large numbers of studies in Indonesia were primarily conducted in response to viral respiratory disease outbreaks, but with limited epidemiological data. We also identified gaps in information regarding the geographical distribution of viral respiratory disease burden, as studies were more highly concentrated in populated cities, such as Jakarta, Java, and Bali. This review highlights the need for more robust surveillance of ILI and SARI cases throughout Indonesia, as well as allocation of more resources for viral respiratory disease etiology and epidemiological studies.

Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China (preprint)

Objective: To analyze the demographic characteristics and patterns of medication use among patients in fever clinics (FCs) during the COVID-19 outbreak in China and provide information for COVID-19 treatment. Method: Various-grade general hospitals in China were selected, and patient information was extracted during the initial wave of the COVID-19 epidemic. Demographic characteristics were analyzed, including visit time, age, sampling morbidity rate, and disease distribution. Prescription information from the FC database was extracted to analyze drug use and the rationality of the medication. Result: Between September 1 and December 31, 2022, 41,445 patients received treatment at FCs in 11 included hospitals. After the relaxation of COVID-19 control measures, there was a rapid increase in the number of daily patient visits (peaking >1,000 people/day, with a growth rate of 158.8%). The highest sampling morbidity rate was observed among individuals over 85 years old (>100 person-times/million population), followed by children (60-94 person-times/million population). Respiratory system diseases (39,295 cases) were the most diagnosed, with respiratory system infections (21,201 cases) and fever (15,132 cases) the most common. The proportion and frequency of use of essential national drugs were 34.3% and 73.1%, respectively, while those for the drugs recommended in the national COVID-19 treatment guidelines were 6.1% and 43.2%, respectively. Ibuprofen, acetaminophen, and Lianhua Qingwen had the highest frequency of drug use. The most prescribed drugs by cost were immunoglobulin, azivudine, and cefoperazone sulbactam. The water-electrolyte balance regulator drugs, respiratory system drugs, anti-infective drugs, and traditional Chinese patent drugs were the most frequently used. In contrast, immunomodulators, anti-infectives, and Chinese patent drugs had the largest monetary amounts. There was a significant difference in medication rationality between different hospital grades (P<0.001), with tertiary teaching hospitals having the highest rate. Conclusion: Strict epidemic control measures and the role of FCs played a crucial role in controlling the spread of the COVID-19 epidemic. Patients treated in FCs predominantly suffered from respiratory diseases, with older patients and children identified as high-risk populations. Physicians often choose national guidelines, essential drugs, and traditional Chinese for COVID-19 treatment. Tertiary teaching hospitals played a crucial role during the epidemic outbreak.

Pulmonary function trajectories in COVID-19 survivors with- and without pre-existing respiratory disease at three and twelve months after hospital discharge (preprint)

A significant proportion of COVID-19 survivors still experience a reduced diffusion capacity three and twelve months after discharge. We aimed to compare pulmonary function trajectories between hospitalized COVID-19 patients with pre-existing respiratory disease (PRD) and patients without pre-existing respiratory disease (Non-PRD) at three and twelve months after hospital discharge. This single-centre retrospective cohort study included COVID-19 patients admitted to the VieCuriMedical Centre (Venlo, the Netherlands) between February and December 2020 that were invited to the outpatient clinic at three and twelve months after discharge. During this visit, pulmonary function tests were performed and impairments were based on lower limit of normal. Data of 239 patients were analysed (65% male, 66±10 years, and 26% with a history of respiratory disease). Three months after discharge, 49% and 64% of the Non-PRD patients (n=177) and PRD patients (n=62) had a low diffusion capacity, respectively. This improved over time in Non-PRD patients (p=0.003), but not in PRD patients (p=0.250). A low diffusion capacity was still observed in 34% and 57% of the Non-PRD and PRD group, respectively, twelve months after discharge. Pulmonary function impairments, mainly a reduced diffusion capacity, are observed among hospitalized COVID-19 patients with PRD and Non-PRD, at three and twelve months follow-up. Although diffusion capacity impairments restore over time in Non-PRD patients, poor recovery was observed among PRD patients.

An AI-enabled Bias-Free Respiratory Disease Diagnosis Model using Cough Audio: A Case Study for COVID-19 (preprint)

Cough-based diagnosis for Respiratory Diseases (RDs) using Artificial Intelligence (AI) has attracted considerable attention, yet many existing studies overlook confounding variables in their predictive models. These variables can distort the relationship between cough recordings (input data) and RD status (output variable), leading to biased associations and unrealistic model performance. To address this gap, we propose the Bias Free Network (RBFNet), an end to end solution that effectively mitigates the impact of confounders in the training data distribution. RBFNet ensures accurate and unbiased RD diagnosis features, emphasizing its relevance by incorporating a COVID19 dataset in this study. This approach aims to enhance the reliability of AI based RD diagnosis models by navigating the challenges posed by confounding variables. A hybrid of a Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) networks is proposed for the feature encoder module of RBFNet. An additional bias predictor is incorporated in the classification scheme to formulate a conditional Generative Adversarial Network (cGAN) which helps in decorrelating the impact of confounding variables from RD prediction. The merit of RBFNet is demonstrated by comparing classification performance with State of The Art (SoTA) Deep Learning (DL) model (CNN LSTM) after training on different unbalanced COVID-19 data sets, created by using a large scale proprietary cough data set. RBF-Net proved its robustness against extremely biased training scenarios by achieving test set accuracies of 84.1%, 84.6%, and 80.5% for the following confounding variables gender, age, and smoking status, respectively. RBF-Net outperforms the CNN-LSTM model test set accuracies by 5.5%, 7.7%, and 8.2%, respectively

Tracking COVID-19 in England and Wales: Insights from Virus Watch - a prospective community cohort study (preprint)

BackgroundVirus Watch is a prospective community cohort study of COVID-19 of 28{square},527 households in England and Wales designed to estimate the incidence of PCR-confirmed COVID-19 in those with respiratory presentations and examine symptom profiles and transmission of COVID-19 in relation to population movement and behaviour. The Office for National Statistics (ONS) COVID-19 infection survey (CIS) was the largest regular survey of COVID-19 infections and antibodies in the UK and included 227,797 households. In this analysis, we aimed to compare incidence rate estimates from the two studies to understand differences in estimates from the two study designs. MethodsWe used the Virus Watch prospective community cohort study to estimate the overall SARS-CoV-2 incidence rate and incidence rate by age in England and Wales from June 2020 to February 2023. Virus Watch data consisted of self-reported laboratory COVID-19 test results and linkage to the Second Generation Surveillance System, the UK national database for COVID-19 testing. We compared our findings with modelled incidence rates from ONS CIS using 3-day rolling Pearsons correlation to measure synchrony. Results58,628 participants were recruited into the Virus Watch study between June 2020 and March 2022, of whom 52,526 (90%) were reported to be living in England and 1,532 (2.6%) in Wales. COVID-19 incidence rates were initially similar across age groups until the Delta wave when rates increased at different magnitudes. During the Omicron BA.1, the 0-14 age group had the highest incidence rates, which shifted to the 25-44 age group with Omicron BA.2, 4, and 5 dominance. We found strong synchrony between Virus Watch and ONS CIS COVID-19 incidence estimates for England and Wales, both with and without the incorporation of linked national testing data into the Virus Watch study. In particular, the magnitude and trend of Virus Watch- and ONS-estimated rates for England were generally consistent, although Virus Watch-estimated peaks of infection during the Omicron BA.1 and 2 waves were found to be lower than estimates from the ONS. ConclusionOur findings suggest that the Virus Watch research approach is a low-cost and effective method for on-going surveillance of COVID-19 regardless of the availability of national testing in the UK. Similar approaches can also be utilised by low-resource settings to provide accurate incidence rate estimates to better monitor and respond to COVID-19 as well as other acute respiratory diseases in the future.

Establishment of a real-time recombinase-aided isothermal amplification (RT-RAA) assay for the rapid detection of bovine respiratory syncytial virus (preprint)

Background Bovine respiratory syncytial virus (BRSV) is a major cause of bovine respiratory disease, resulting in significant losses to the cattle industry. For rapid detection of BRSV, reverse transcription recombinase polymerase amplification assays targeting the F gene were developed by integrating the fluorescence detection platform (RT-RAA).Results The developed RT-RAA assays allowed the exponential amplification of the target fragment in 20 min at a constant temperature of 39°C. The RT-RAA assays also showed good specificity for BRSV, with no cross-reactions with Infectious Bovine Rhinotracheitis Virus (IBRV), Bovine Parainfluenza Virus Type 3 (BPIV3), Bovine Viral Diarrhea Virus (BVDV) and Bovine Coronavirus (BCoV). With the standard RNA of BRSV serving as a template, the limit of detection for RT-RAA was 5 × 102 copies per reaction. Forty clinical samples collected from cattle with respiratory disease were tested, and the positive rate was 7.5% (3/40), consistent with results using the conventional PCR method reported previously.Conclusion An RT-RAA assay for BRSV detection was established in this study. The method is specific and sensitive and can be completed within 20 min at 39℃. These results ascertain that the developed RT-RAA assays are effective diagnostic tools for rapidly detecting BRSV in resource-limited settings, which may be applied for clinical detection of BRSV.

Influenza Mortality as an Indicator of the Efficacy of COVID-Related, Non-pharmaceutical Interventions to Reduce the Spread of Respiratory Infections (preprint)

Background Non-pharmaceutical interventions (NPIs) have been criticized as ineffective in preventing COVID. Because it is a new disease with NPIs introduced almost immediately, we have no way to easily and directly evaluate the counterfactual of non-intervention. We do, however, have excellent historic data on influenza, a respiratory disease with similar patterns of transmission and a well-established CDC surveillance system in the US. These data provide us an excellent way to indirectly evaluate the efficacy of these interventions and factors influencing that efficacy. Results During the three seasons prior to COVID from 2016-17 to 2018-19, the mean total US influenza mortality was 9,917 deaths per season. During the pandemic, influenza mortality was reduced by 91 percent in the 2020-21 and 69 percent in the 2021-22 influenza seasons relative to historical levels. The corresponding decreases for the pediatric population were 99 percent and 67 percent. At the state level, the average drop in mortality over the two flu seasons of the pandemic was strongly correlated with the percent of the 2020 presidential votes cast for Joe Biden in each state. Conclusions These data provide strong evidence that COVID NPIs dramatically reduced the spread of influenza. Given its similar routes of transmission, these results support the assertion that these interventions also substantially reduced COVID transmission, morbidity, and mortality. The effectiveness of NPIs increased in proportion to the size of the Democratic electorate in each state. This could reflect more effective NPI strategies in states with Democratic leanings or better compliance with NPIs in those states.

Expression and fusogenic activity of SARS CoV-2 Spike protein displayed in the HSV-1 Virion. (preprint)

Severe acute respiratory syndrome coronavirus (SARS-CoV) is a zoonotic pathogen that can cause severe respiratory disease in humans. The new SARS-CoV-2 is the cause of the current global pandemic termed coronavirus disease 2019 (COVID-19) that has resulted in many millions of deaths world-wide. The virus is a member of the Betacoronavirus family, its genome is a positive strand RNA molecule that encodes for many genes which are required for virus genome replication as well as for structural proteins that are required for virion assembly and maturation. A key determinant of this virus is the Spike (S) protein embedded in the virion membrane and mediates attachment of the virus to the receptor (ACE2). This protein also is required for cell-cell fusion (syncytia) that is an important pathogenic determinant. We have developed a pseudotyped herpes simplex virus type 1 (HSV-1) recombinant virus expressing S protein in the virion envelop. This virus has also been modified to express a Venus fluorescent protein fusion to VP16, a virion protein of HSV-1. The virus expressing Spike can enter cells and generates large multi-nucleated syncytia which are evident by the Venus fluorescence. The HSV-1 recombinant virus is genetically stable and virus amplification can be easily done by infecting cells. This recombinant virus provides a reproducible platform for Spike function analysis and thus adds to the repertoire of pseudotyped viruses expressing Spike. Impact StatementThe isolation of a pseudotyped herpes simplex virus type 1 (HSV-1) virus using the Spike protein is new and innovative. This virus can be used to study entry and fusion events mediated by the S protein as well as test antibodies for their ability to neutralize this particle. In addition, these virions can be used for screening antibody specificity using the S protein displayed in its natural membrane bound conformation.

Early warning system using primary healthcare data in the post-COVID-19-pandemic era: Brazil nationwide case-study (preprint)

BackgroundSyndromic surveillance utilising primary health care (PHC) data is a valuable tool for early outbreak detection, as demonstrated in the potential to identify COVID-19 outbreaks. However, the potential of such an early warning system in the post-COVID-19 era remains largely unexplored. MethodsWe analysed PHC encounter counts due to respiratory complaints registered in the Brazilian database of the Universal Health System between January and July 2023. We applied EARS (variation C1-C2-C3) and EVI to estimate the weekly thresholds. An alarm was determined when the number of encounters exceeded the week-specific threshold. We used data on hospitalisation due to respiratory disease to classify weeks in which the number of cases surpassed predetermined thresholds as anomalies. We compared EARS and EVIs efficacy in anticipating anomalies. FindingsA total of 119 anomalies were identified across 116 immediate regions during the study period. The EARS-C2 presented the highest early alarm rate, with 81/119 (68%) early alarms, and C1 the lowest, with 71 (60%) early alarms. The lowest true positivity was the EARS-C1 118/1354 (8.7%) and the highest EARS-C3 99/856 (11.6%). ConclusionRoutinely collected PHC data can be successfully used to detect respiratory disease outbreaks in Brazil. Syndromic surveillance enhances timeliness in surveillance strategies, albeit with lower specificity. A combined approach with other strategies is essential to strengthen accuracy, offering a proactive and effective public health response against future outbreaks.

Th2 and Th17-Associated Immunopathology Following SARS-CoV-2 Breakthrough Infection in Spike-vaccinated ACE2-humanized Mice (preprint)

Vaccines have demonstrated remarkable effectiveness in protecting against COVID-19; however, concerns regarding vaccine-associated enhanced respiratory diseases (VAERD) following breakthrough infections have emerged. Spike protein subunit vaccines for SARS-CoV-2 induce VAERD in hamsters, where aluminum adjuvants promote a Th2-biased immune response, leading to increased type 2 pulmonary inflammation in animals with breakthrough infections. To gain a deeper understanding of the potential risks and the underlying mechanisms of VAERD, we immunized ACE2-humanized mice with SARS-CoV-2 Spike protein adjuvanted with aluminum and CpG-ODN. Subsequently, we exposed them to increasing doses of SARS-CoV-2 to establish a breakthrough infection. The vaccine elicited robust neutralizing antibody responses, reduced viral titers, and enhanced host survival. However, following a breakthrough infection, vaccinated animals exhibited severe pulmonary immunopathology, characterized by a significant perivascular infiltration of eosinophils and CD4+ T cells, along with increased expression of Th2/Th17 cytokines. Intracellular flow cytometric analysis revealed a systemic Th17 inflammatory response, particularly pronounced in the lungs. Our data demonstrate that aluminum/CpG adjuvants induce strong antibody and Th1-associated immunity against COVID-19 but also prime a robust Th2/Th17 inflammatory response, which may contribute to the rapid onset of T cell-mediated pulmonary immunopathology following a breakthrough infection. These findings underscore the necessity for further research to unravel the complexities of VAERD in COVID-19 and to enhance vaccine formulations for broad protection and maximum safety.

Face masks to control the source of respiratory infections: A systematic review of the scientific literature before and after COVID-19 (preprint)

Objective: To examine the scientific literature on mask-use as source control to protect others from respiratory infections before and after the onset of the COVID-19 pandemic. Design: Systematic review. Methods: We examined primary research on mask usage as a means of source control to protect others by reducing the spread of respiratory diseases and contrasted the literature published before the onset of the COVID-19 pandemic with that published afterward. Articles were obtained through a search of PubMed and a review of article references. March 1, 2020 was selected as the cutoff date to distinguish between the pre-COVID-19 and post-COVID-19 periods. Results: 195 articles met our inclusion criteria. The sample included 55 articles on source control published before the start of the COVID-19 pandemic, and 140 articles published after the pandemic began, representing a 154.5% increase. The percentage of randomized control trials (RCT) and cluster RCTs declined by 94.9% (p<0.001), representing only 1.4% of the post-pandemic literature. The percentage of studies conducted on human subjects declined by 48.8% (p<0.001), and the percentage of studies in healthcare facilities declined by 64.5% (p=0.019). One in 5 post-pandemic studies (21.4%) were conducted in real world settings; 1 in 10 post-pandemic studies (10.0%) were done with computer modeling. Study authors were significantly more supportive of masks as source control in the post-pandemic literature. Conclusions: The quality of evidence in the published literature on masks as source control is lower after the start of the COVID-19 pandemic, with notable shifts in methodologies, research subjects, setting, and author tone.

Dynamic Contact Networks of Residents of an Urban Jail in the Era of SARS-CoV-2 (preprint)

BACKGROUND. In custodial settings such as jails and prisons, infectious disease transmission is heightened by factors such as overcrowding and limited healthcare access. Specific features of social contact networks within these settings have not been sufficiently characterized, especially in the context of a large-scale respiratory infectious disease outbreak. The study aims to quantify contact network dynamics within the Fulton County Jail in Atlanta, Georgia, to improve our understanding respiratory disease spread to informs public health interventions. METHODS. As part of the Surveillance by Wastewater and Nasal Self-collection of Specimens (SWANSS) study, jail roster data were utilized to construct social contact networks. Rosters included resident details, cell locations, and demographic information. This analysis involved 6,702 residents over 140,901 person days. Network statistics, including degree, mixing, and turnover rates, were assessed across age groups, race/ethnicities, and jail floors. We compared outcomes for two distinct periods (January 2022 and April 2022) to understand potential responses in network structures during and after the SARS-CoV-2 Omicron variant peak. RESULTS. We found high cross-sectional network degree at both cell and block levels, indicative of substantial daily contacts. While mean degree increased with age, older residents exhibited lower degree during the Omicron peak, suggesting potential quarantine measures. Block-level networks demonstrated higher mean degrees than cell-level networks. Cumulative degree distributions for both levels increased from January to April, indicating heightened contacts after the outbreak. Assortative age mixing was strong, especially for residents aged 20-29. Dynamic network statistics illustrated increased degrees over time, emphasizing the potential for disease spread, albeit with a lower growth rate during the Omicron peak. CONCLUSIONS. The contact networks within the Fulton County Jail presented ideal conditions for infectious disease transmission. Despite some reduction in network characteristics during the Omicron peak, the potential for disease spread remained high. Age-specific mixing patterns suggested unintentional age segregation, potentially limiting disease spread to older residents. The study underscores the need for ongoing monitoring of contact networks in carceral settings and provides valuable insights for epidemic modeling and intervention strategies, including quarantine, depopulation, and vaccination. This network analysis offers a foundation for understanding disease dynamics in carceral environments.