Variation In Infection Rates Research Articles

Prevalence and genetic diversity of Anaplasma phagocytophilum in wild small mammals from western Yunnan province, China

Anaplasma phagocytophilum (A. phagocytophilum) is an emerging zoonotic pathogen causing human granulocytic anaplasmosis, linked to small mammal reservoirs that harbor various zoonotic pathogens, underscoring their importance in public health and ecology. This study seeks to determine the prevalence of A. phagocytophilum in small mammals using PCR, then sequence and genotype positive samples, and assess infection risk factors. Small mammals were seasonally captured and a nested polymerase chain reaction (nested-PCR) was conducted targeting the 16S rRNA gene on spleen samples to detect A. phagocytophilum infection from three counties in western Yunnan province, China. Positive samples were sequenced and genotyped, revealing genetic diversity and regional clustering of the pathogen. A total of 1,605 small mammals belonging to 30 species, 18 genera, 6 families, 3 orders were captured seasonally and screened in this region, yielding a 0.93% infection rate with A. phagocytophilum (15/1605). Significant variations in infection rates were observed across different species, counties, and habitats. The 16Sr RNA genes of A. phagocytophilum were categorized into two distinct clades, indicating notable genetic diversity. The identification of genetic variants in spleen samples underscores the potential public health risk and the critical importance of the One Health approach in disease surveillance. Our findings emphasize the necessity for continuous monitoring and highlight the value of nested-PCR testing on spleen samples for accurate prevalence assessment.

School Mask Mandates and COVID-19: The Challenge of Using Difference-in-Differences Analysis of Observational Data to Estimate the Effectiveness of a Public Health Intervention.

There are considerable challenges when using difference-in-differences (DiD) analysis of ecological data to estimate the effectiveness of public health interventions in rapidly changing situations. To discuss the shortcomings of DiD methodology for the estimation of the effects of public health interventions using ecological data. As an example, the authors consider an analysis that used DiD methodology and reported a causal reduction in COVID-19 cases due to the maintenance of school mask mandates. They did alternate analyses using various control groups to assess the robustness of the prior analysis. School districts in the greater Boston area and Massachusetts during the 2021-to-2022 academic year. Students and school staff. Changes in COVID-19 case rates in districts that did and did not lift mask mandates. Important potential confounders rendered DiD methodology inappropriate for causal inference, including prior immunity, temporal variation in rates of infection, and changes in testing practices. The racial composition and income of intervention and control groups also differed substantially. Compared with maintaining the mask requirement, dropping the requirement was associated with anywhere from an increase of 5.64 cases (95% CI, 3.00 to 8.29 cases) per 1000 persons to a decrease of 2.74 cases (CI, 0.63 to 4.85 cases) per 1000 persons, depending on choice of control group and whether students or staff were examined. Ecological data were used; detailed data on all potential confounders were unavailable. Alternate analyses yielded estimates consistent with a wide range of both negative and positive associations in COVID-19 case rates after removal of mask mandates. The findings highlight the challenges of using DiD analysis of ecological data to estimate the effectiveness of interventions in divergent intervention and control groups during rapidly changing circumstances. None.

Seroprevalence of hepatitis c virus in Blood Donors in Kabul in 2023

Introduction: Understanding the prevalence and distribution of the hepatitis C virus (HCV) is crucial for the development of effective prevention and control strategies, given its significant impact on global public health. The objective of this study was to examine the seroprevalence of HCV among blood donors in Kabul and assess the possible gender-based variations in infection rates. Materials and Methods: This study analyzed blood donor records from the central blood bank in Kabul, including both male and female donors, from January to December 2023. HCV screening was performed using ELISA testing, and the data were analyzed using SPSS to determine HCV prevalence and investigate gender-based differences in infection rates. Results: In this study, 59 out of 15,080 individuals (0.39%) tested positive for HCV infection. Among the HCV-positive cases, 81.5% were male and 18.6% were female. The majority of infected males (64.4%) were in the 30-39 age range. A significant proportion of HCV-positive patients had no formal education (69.5%) and were unemployed (61.0%). Additionally, the majority of HCV-positive patients reported a low monthly income (66.1%). Discussion: The study found a low prevalence of HCV infection (0.39%) among the participants, with the highest rates observed in the 30-39 age group. Socioeconomic factors, such as lack of education, unemployment, and low income, were associated with HCV infection. Targeted interventions are needed to address gender disparities, age-specific risks, and socioeconomic determinants to improve prevention and control strategies for HCV in Kabul's blood donor population and enhance overall population health.

Comparison of two different experimental environments for resistance screenings for the leafhopper-transmitted wheat dwarf virus in wheat

Wheat dwarf virus (WDV) causes high yield losses in wheat and other cereals and is therefore an important pathogen transmitted by the leafhopper Psammotettix alienus. Climate change will increase infections by insect-transmitted viruses due to the increasing spread of vectors. In the context of integrated pest management, the cultivation of WDV-resistant/tolerant varieties is an effective way of controlling WDV. Evaluation of tolerant/resistant genotypes is based on inoculation with viruliferous leafhoppers and subsequent phenotyping in gauze houses under semi-field conditions. For successful screening, it is important to ensure the uniform and reproducible inoculation of plants. Abiotic conditions, particularly temperature, have a critical influence on inoculation success, and thus, variations in infection rates were observed within and between previous replicates in the field. Furthermore, the leafhopper population reared in the greenhouse has to be reestablished after each infection, which delays the screening process. We addressed these issues by developing an improved inoculation assay in which plants are inoculated in small infection hoods in the greenhouse before being planted out in gauze houses. This procedure allows optimal environmental conditions for WDV infection of test plants and allows the plants with WDV infection to develop under natural environmental conditions for symptom scoring. In addition, the viruliferous leafhoppers were recollected from the test plants after infection, allowing a sustainable use of the insects. The method thus enables more reliable phenotyping by increasing infection success and testing a greater number of genotypes in a shorter time.

Natural occurrence, infection dynamics, and molecular characterization of nucleopolyhedrovirus (SpfrNPV) infecting fall armyworm, Spodoptera frugiperda (J. E. Smith) from maize ecosystems in Gujarat, India

This comprehensive study investigates the stage-wise infection dynamics of Nucleopolyhedrovirus (NPV) in fall armyworm, Spodoptera frugiperda (J. E. Smith) larvae across distinct stages of maize crop in Panchmahal and Mahisagar districts of Gujarat, India during the kharif season in 2021. The examination of month-wise mean data reveals a pronounced pattern of NPV prevalence, with the highest infection observed during the cob formation stage (28.74 %), followed by flowering and tasseling (20.23 %), and the vegetative stage (13.93 %). Block specific analyses highlight variations in infection rates, with notable differences between districts and stages. Correlation coefficient analysis indicates a significant and positive relationship between specific crop stages and NPV infection. Regression equations are established, demonstrating a positive increase in natural NPV infection during different crop stages. Weather parameter analysis reveals significant correlations between temperature, humidity, sunshine hours, and NPV infection. The phylogenetic analysis of NPV polyhedrin sequences indicates species-specific clustering within S. frugiperda and a broader genus-specific association. Motif pattern analysis identifies conserved motifs in NPV polyhedrins. Protein structure predictions and Molecular docking studies predicted interactions between polyhedrin and chitinase, suggesting a potential role in the insect's defense against NPV. The bioassay results indicated increased susceptibility of early larvae to NPV, emphasizing the potential for optimizing biocontrol strategies. Overall, this study contributes valuable insights into the ecological and molecular aspects of NPV infection dynamics, offering a significance understanding for developing effective pest management strategies and also underscores its significance in promoting sustainable agriculture.

Assessment of Babesia spp. prevalence in various domestic animals across Southern Punjab, Pakistan.

Parasitic diseases, notably babesiosis, exert a substantial impact on the global cattle industry, posing challenges to commerce, economies, and human health. This study, conducted in Southern Punjab, Pakistan, aimed to assess the prevalence of Babesia spp. across various livestock species using microscopic and PCR methods. A total of 180 blood samples (60 from each district) were systematically collected from apparently healthy animals, with 36 samples obtained from each domestic animal species, including camel, cattle, buffalo, goat, and sheep, noting that 12 samples were collected from each district for each animal species. Overall prevalence was determined to be 32.8% (59/180), with varying rates among species: 25.0% in cattle, 41.66% in buffalo, 30.55% in goats, 33.3% in sheep, and 33.3% in camels. Microscopic examination revealed slightly varied infection rates among large and small domestic animals (22.2%), while PCR results indicated a 32.8% overall infection rate in both large and small domestic animals, with no statistical significance. District-wise analysis showed regional variations, with Muzaffargarh recording a prevalence rate of 23.33% through microscopic examination, while Lodhran and Bahawalpur recorded 21.67%. PCR results revealed higher rates (38.33%, 26.67%, and 33.33%, respectively), underlining the importance of employing PCR for accurate detection. Examining ruminant types, large ruminants exhibited a 32.4% infection rate, while small domestic animals showed 33.3%, with no significant difference (p=0.897). District-wise prevalence showcased significant variation, with Muzaffargarh demonstrating a 25% prevalence, Lodhran 22%, and Bahawalpur 22%, through microscopic examination. PCR results displayed 38.33%, 27%, and 33.3%, respectively, with no statistical significance. Detailed analysis of individual districts highlighted variations in infection rates among camels, cattle, buffalo, goats, and sheep. The binomial test indicated significant differences through microscopic analysis (P=0.011) but non-significant variations through PCR (P=0.065), emphasizing the precision of PCR. Regional variations in prevalence, notably with Punjab exhibiting the highest frequency (33.87%) and KPK the lowest (13.24%), suggest potential influences from varying veterinary practices and environmental factors. This study underscores the pivotal role of PCR alongside microscopy for accurate babesiosis diagnosis. These findings contribute to the broader understanding of babesiosis prevalence, emphasizing the necessity of advanced molecular techniques for informed control measures.

Variegated spatial-temporal landscape of COVID-19 infection in England: findings from spatially filtered multilevel models.

Although there are empirical studies examining COVID-19 infection from a spatial perspective, majority of them focused on the USA and China, and there has been a lacuna of systematic research to unpack the spatial landscape of infection in the UK and its related factors. England's spatial-temporal patterns of COVID-19 infection levels in 2020 were examined via spatial clustering analysis. Spatially filtered multilevel models (SFMLM), capturing both hierarchical and horizontal spatial interactive effects, were applied to identify how different demographic, socio-economic, built environment and spatial contextual variables were associated with varied infection levels over the two waves in 2020. The fragmented spatial distribution of COVID incidence in the first wave has made a rural-urban shift and resulted in a clearer north-south divide in England throughout 2020. The SFMLM results do not only identify the association between variables at different spatial scales with COVID-19 infection level but also highlight the increasing importance of spatial-dependent effect of the pandemic over time and that the locational spatial contexts also help explain variations in infection rates.

Age Disparities in Prevalence of Anxiety and Depression Among US Adults During the COVID-19 Pandemic

High levels of anxiety and depression were documented shortly after the arrival of the COVID-19 pandemic and were more prevalent in younger adults than in older adults. Knowing whether these age disparities persisted throughout multiple years of the COVID-19 pandemic and identifying associated factors will help guide health policy. To investigate age disparities in anxiety and depression during the COVID-19 pandemic. This cross-sectional study consisted of a nationally representative online survey administered between April 2020 and August 2022 and included US adults who were not incarcerated. Data were analyzed between March and September 2022. The first 27 months of the COVID-19 pandemic included wide variation in infection rates, turbulence in US political and social life, and geopolitical instability. Primary exposures include individuals' age and economic precarity and pandemic-related events (eg, weekly state-level case counts and individual vaccination status). Symptoms of anxiety and depression were assessed via responses to 2-item screeners (Generalized Anxiety Disorder 2-item for anxiety and Patient Health Questionnaire-2 for depression). An individual's symptoms were identified as clinically elevated if scores exceeded validated thresholds. This study included 3 028 923 respondents (mean [SD] age, 48.9 [17.0] years; 1 567 603 [51.8%] female). In multiple regression analyses that include state fixed effects and survey-week fixed effects, likely anxiety and depressive disorders among 291 382 (40%) and 238 505 (33%) of adults aged 18 to 39 years, respectively, compared with 357 820 (31%) and 274 534 (24%) of adults aged 40 to 59 years and 225 295 (20%) and 183 695 (16%) adults aged 60 years and older. Levels declined throughout the pandemic period for those aged 40 years and older but remained elevated for younger adults. Analyses identified several associated factors of these age disparities. Younger adults' anxiety and depression increased more than older adults' after surges in COVID-19 case counts but decreased less following vaccination against the virus. Additionally, approximately one third of the age gap among individuals with depression and anxiety was attributed to economic precarity, to which younger adults are disproportionately exposed. In this cross-sectional study of anxiety and depression during the COVID-19 pandemic, economic precarity was associated with high anxiety and depression among younger adults in the US compared with older adults in the US. These findings suggest a need for greater mental health care and economic policies targeted toward younger adults.

COVID-19 Infections and Deaths between Rural and Urban Provinces of Zimbabwe, 2020: A Spatial Variations Analysis

Zimbabwe continues to record new COVID-19 cases as is the case in other countries. Although the Ministry of Health in Zimbabwe continues to publish daily situation reports (SitRep), and regular surveillance updates, no review of existing data has been done to establish the regional trends of the disease over time. This desk review study seeks to analyze the trends (province by province) of the COVID-19 in Zimbabwe for year 2020 in order to establish if spatial variations in infection rates and deaths exist. Ultimately, the aim is to come up with appropriate context-specific prevention and control measures. The study also seeks to establish whether or not there is a difference in COVID-19 infection rates and deaths between urban and rural provinces of Zimbabwe. A historical research design that made use of available secondary data on COVID-19 in Zimbabwe was used. COVID-19 statistics for year 2020 as provided by the Zimbabwe Ministry of Health and Child Care were accessed from the website and reviewed. A hypothesis test to determine if there was a difference in COVID-19 attack rates between urban and rural provinces of Zimbabwe was also done. An independent samples t-test using Microsoft excel was done on cumulative COVID-19 cases data for the entire year 2020. The study revealed that spatial variations in COVID-19 infections and deaths between urban and rural provinces of Zimbabwe existed. Urban provinces recorded more COVID-19 cases in 2020 compared to rural provinces. Keywords: COVID-19, Infection rate, Psychological distress, Spatial, Variations, Vaccine hesitancy.

Co-infection with Leucocytozoon and Other Haemosporidian Parasites Increases with Latitude and Altitude in New World Bird Communities.

Establishing how environmental gradients and host ecology drive spatial variation in infection rates and diversity of pathogenic organisms is one of the central goals in disease ecology. Here, we identified the predictors of concomitant infection and lineage richness of blood parasites in New Word bird communities. Our multi-level Bayesian models revealed that higher latitudes and elevations played a determinant role in increasing the probability of a bird being co-infected with Leucocytozoon and other haemosporidian parasites. The heterogeneity in both single and co-infection rates was similarly driven by host attributes and temperature, with higher probabilities of infection in heavier migratory host species and at cooler localities. Latitude, elevation, host body mass, migratory behavior, and climate were also predictors of Leucocytozoon lineage richness across the New World avian communities, with decreasing parasite richness at higher elevations, rainy and warmer localities, and in heavier and resident host species. Increased parasite richness was found farther from the equator, confirming a reverse Latitudinal Diversity Gradient pattern for this parasite group. The increased rates of Leucocytozoon co-infection and lineage richness with increased latitude are in opposition with the pervasive assumption that pathogen infection rates and diversity are higher in tropical host communities.

Study on the influencing factors of piecewise multi-strain crossover epidemic spread under data contamination

The ongoing impact of the novel coronavirus disease 2019 (COVID-19) on work and daily life persists as we transition from emergency to normal circumstances. The continuous mutation of viral strains has resulted in a shift from a single strain to multiple cross-strains, contributing to the spread of the epidemic. Variations in infection rates of the same strain occur because of the implementation of diverse preventive measures at different times. This study investigated the dynamics of the pandemic in the presence of concurrent strains. Building on the classical Susceptible, Exposed, Infected, and Recovered (SEIR) model, a robust piecewise multi-strain cross-epidemic trend prediction model was proposed that employs the Hodges–Lehmann estimator to handle uncertain and contamination-prone epidemic information. A comparative analysis of epidemic spread trend curves across diverse populations using different robust methods revealed the superiority of the Hodges–Lehmann estimator-based model over the traditional method. The accurate prediction results of the model demonstrate its high reliability in tracking the changing trend of the COVID-19 outbreak, thereby supporting its implementation in subsequent epidemic prevention and control measures.

Epidemic spread on patch networks with community structure

Predicting and preparing for the trajectory of disease epidemics relies on a knowledge of environmental and socioeconomic factors that affect transmission rates on local and global spatial scales. This article discusses the simulation of epidemic outbreaks on human metapopulation networks with community structure, such as cities within national boundaries, for which infection rates vary both within and between communities. We demonstrate mathematically, through next-generation matrices, that the structures of these communities, setting aside all other considerations such as disease virulence and human decision-making, have a profound effect on the reproduction rate of the disease throughout the network. In high modularity networks, with high levels of separation between neighboring communities, disease epidemics tend to spread rapidly in high-risk communities and very slowly in others, whereas in low modularity networks, the epidemic spreads throughout the entire network as a steady pace, with little regard for variations in infection rate. The correlation between network modularity and effective reproduction number is stronger in population with high rates of human movement. This implies that the community structure, human diffusion rate, and disease reproduction number are all intertwined, and the relationships between them can be affected by mitigation strategies such as restricting movement between and within high-risk communities. We then test through numerical simulation the effectiveness of movement restriction and vaccination strategies in reducing the peak prevalence and spread area of outbreaks. Our results show that the effectiveness of these strategies depends on the structure of the network and the properties of the disease. For example, vaccination strategies are most effective in networks with high rates of diffusion, whereas movement restriction strategies are most effective in networks with high modularity and high infection rates. Finally, we offer guidance to epidemic modelers as to the ideal spatial resolution to balance accuracy and data collection costs.

Influence of habitat alteration on the structure of helminth communities in small mammals: a systematic review and critical appraisal of theory and current evidence.

Despite the extensive information on the effects of habitat alteration on the structure of helminth communities in small mammals, the evidence is still inconclusive. A systematic review was carried out using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guideline to compile and synthesize available literature on the influence of habitat alteration on the structure of helminth communities in small mammals. The aim of this review was to describe the variation in infection rates of helminth species associated with habitat alteration and to discuss the theoretical framework that may explain such changes in relation to parasite, host, and environmental features. Twenty-three scientific articles published between 2005 and 2022 were reviewed, 22 of which investigated parasite prevalence, 10 parasite burden, and 14 parasite richness in both altered and natural habitats. Information in assessed articles suggests that the structure of helminth communities in small mammals can be impacted by anthropogenic habitat alteration in various ways. Infection rates of monoxenous and heteroxenous helminths may increase or decrease in small mammals depending on whether their hosts (definitive and intermediate) are available, and environmental and host conditions modify the survival and transmission of parasitic forms. Also, given that habitat alteration may favor inter-species contacts, transmission rates of low host-specific helminths could be increased due to exposure to new reservoir hosts. In a continually changing world, it is essential to assess the spatio-temporal variations of helminth communities in wildlife inhabiting altered and natural habitats to determine potential impacts on wildlife conservation and public health.

Analysis of Pathogenic Bacteria and Drug Resistance Among Girls with Bacterial Vaginitis.

The aim of this study was to analyze the prevalence of vaginal flora and drug resistance in bacterial vaginitis among girls. A total of 3099 girls (0-10 years old) with vaginitis who visited the Beijing Children's Hospital from January 2020 to December 2021 were included in the present study. The clinical data, results of bacterial culture of vaginal secretions, and drug sensitivity reports of the subjects were collected and analyzed. Of the 3099 girls with vaginitis, 399 girls had a positive bacterial culture of vaginal secretions. Nineteen types of bacteria were cultured from the vaginal secretions of these 399 girls, with a total of 419 strains. The top three infective bacteria were Haemophilus influenzae (127 strains, 30.31%), Staphylococcus aureus (66 strains, 15.75%), and Streptococcus agalactiae (32 strains, 7.64%). Additionally, 20 girls were simultaneously infected with two types of bacteria. Staphylococcus aureus, Group G Streptococcus, Haemophilus parainfluenzae, and Pseudomonas aeruginosa more frequently occurred in mixed infections. The number and bacterial detection rate among school-age girls were higher than those of preschool-age girls. We found seasonal variation in infection rates, and vaginitis among girls was higher in summer. Recurrence of vaginitis in girls was not related to the type of pathogenic bacteria in the infection. Drug sensitivity analyses showed that the resistance rates of clindamycin and erythromycin were generally high, 70-100%. After the coronavirus disease 2019 outbreak, the resistance rates of some antibiotics had decreased to varying degrees. Improving the understanding of vaginal flora and drug resistance in girls with vaginitis will facilitate the selection of highly effective and sensitive antibacterial drugs and reduce the production of drug-resistant strains.

Relationships between building attributes and COVID-19 infection in London

In the UK, all domestic COVID-19 restrictions have been removed since they were introduced in March 2020. After illustrating the spatial-temporal variations in COVID-19 infection rates across London, this study then particularly aimed to examine the relationships of COVID-19 infection rates with building attributes, including building density, type, age, and use, since previous studies have shown that the built environment plays an important role in public health. Multisource data from national health services and the London Geomni map were processed with GIS techniques and statistically analysed. From March 2020 to April 2022, the infection rate of COVID-19 in London was 3,159.28 cases per 10,000 people. The spatial distribution across London was uneven, with a range from 1,837.88 to 4,391.79 per 10,000 people. During this period, it was revealed that building attributes played a significant role in COVID-19 infection. It was noted that higher building density areas had lower COVID-19 infection rates in London. Moreover, a higher percentage of historic or flat buildings tended to lead to a decrease in infection rates. In terms of building use, the rate of COVID-19 infection tended to be lower in public buildings and higher in residential buildings. Variations in the infection rate were more sensitive to building type; in particular, the percentage of residents living in flats contributed the most to variations in COVID-19 infection rates, with a value of 2.3%. This study is expected to provide support for policy and practice towards pandemic-resilient architectural design.

Bicondylar Tibial Plateau Fractures: What Predicts Infection?

The purpose of this study was to identify the patient, injury, and treatment factors associated with infection of bicondylar plateau fractures and to evaluate whether center variation exists. Retrospective review. Eighteen academic trauma centers. A total of 1,287 patients with 1,297 OTA type 41-C bicondylar tibia plateau fractures who underwent open reduction and internal fixation were included. Exclusion criteria were follow-up less than 120 days, insufficient documentation, and definitive treatment only with external fixation. Open reduction and internal fixation. Superficial and deep infection. One hundred one patients (7.8%) developed an infection. In multivariate regression analysis, diabetes (DM) (OR [odds ratio] 3.24; P ≤ 0.001), alcohol abuse (EtOH) (OR 1.8; P = 0.040), dual plating (OR 1.8; P ≤ 0.001), and temporary external fixation (OR 2.07; P = 0.013) were associated with infection. In a risk-adjusted model, we found center variation in infection rates (P = 0.030). In a large series of patients undergoing open reduction and internal fixation of bicondylar plateau fractures, the infection rate was 7.8%. Infection was associated with DM, EtOH, combined dual plating, and temporary external fixation. Center expertise may also play a role because one center had a statistically lower rate and two trended toward higher rates after adjusting for confounders. Level IV-Therapeutic retrospective cohort study.

Working in the Eye of the Pandemic: Local COVID-19 Infections and Daily Employee Engagement

The COVID-19 pandemic has drastically changed many aspects of our society and work life. In this study, we assess how daily variations in employees’ work engagement are affected by daily variations in infection rates in employees’ communities. Applying the conceptual framework of event system theory, we argue that surging COVID-19 cases have an impact on employee engagement, depending on the individual sensemaking processes of the pandemic. We assume that employee age and received leader support are key context factors for these sensemaking processes and that particularly older employees and employees who receive little leader consideration react with lower work engagement levels toward rising local COVID-19 infections in their proximity. We find support for most of our proposed relationships in an eight-day diary study with largely a representative data set of the German workforce, which we integrate with official COVID-19 case statistics on the county level. We discuss the implications of these results for the literature on extreme events and individual workplace behavior. Furthermore, these findings also have important implications for companies and executives who are confronted with local COVID-19 outbreaks or further pandemic waves.

A Review on Expression, Pathological Roles, and Inhibition of TMPRSS2, the Serine Protease Responsible for SARS-CoV-2 Spike Protein Activation.

SARS-CoV-2, the coronavirus responsible for the COVID-19 pandemic, uses the host cell membrane receptor angiotensin-converting enzyme 2 (ACE2) for anchoring its spike protein, and the subsequent membrane fusion process is facilitated by host membrane proteases. Recent studies have shown that transmembrane serine protease 2 (TMPRSS2), a protease known for similar role in previous coronavirus infections, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS), is responsible for the proteolytic cleavage of the SARS-CoV-2 spike protein, enabling host cell fusion of the virus. TMPRSS2 is known to be expressed in the epithelial cells of different sites including gastrointestinal, respiratory, and genitourinary system. The infection site of the SARS-CoV-2 correlates with the coexpression sites of ACE2 and TMPRSS2. Besides, age-, sex-, and comorbidity-associated variation in infection rate correlates with the expression rate of TMPRSS2 in those groups. These findings provide valid reasons for the assumption that inhibiting TMPRSS2 can have a beneficial effect in reducing the cellular entry of the virus, ultimately affecting the infection rate and case severity. Several drug development studies are going on to develop potential inhibitors of the protease, using both conventional and computational approaches. Complete understanding of the biological roles of TMPRSS2 is necessary before such therapies are applied.

Working in the Eye of the Pandemic: Local COVID-19 Infections and Daily Employee Engagement.

The COVID-19 pandemic has drastically changed many aspects of our society and work life. This study assesses how daily variations in employees' work engagement are affected by daily variations in infection rates in employees' communities. Applying the conceptual framework of event system theory, we argue that surging COVID-19 cases have an impact on employee engagement, depending on the individual sensemaking processes of the pandemic. We assume that employee age and received leader support are key context factors for these sensemaking processes and that particularly older employees and employees who receive little leader consideration react with lower work engagement levels toward rising local COVID-19 infections in their proximity. We find support for most of our proposed relationships in an 8-day diary study of German employees, which we integrate with official COVID-19 case statistics on the county level. We discuss the implications of these results for the literature on extreme events and individual workplace behavior. Furthermore, these findings have important implications for companies and executives who are confronted with local COVID-19 outbreaks or other extreme societal events.

Resistance Correlations Influence Infection by Foreign Pathogens.

AbstractReciprocal selection promotes the specificity of host-pathogen associations and resistance polymorphisms in response to disease. However, plants and animals also vary in response to pathogen species not previously encountered in nature, with potential effects on new disease emergence. Using anther smut disease, we show that resistance (measured as infection rates) to foreign pathogens can be correlated with standing variation in resistance to an endemic pathogen. In Silene vulgaris, genetic variation in resistance to its endemic anther smut pathogen correlated positively with resistance variation to an anther smut pathogen from another host, but the relationship was negative between anther smut and a necrotrophic pathogen. We present models describing the genetic basis for assessing resistance relationships between endemic and foreign pathogens and for quantifying infection probabilities on foreign pathogen introduction. We show that even when the foreign pathogen has a lower average infection ability than the endemic pathogen, infection outcomes are determined by the sign and strength of the regression of the host's genetic variation in infection rates by a foreign pathogen on variation in infection rates by an endemic pathogen as well as by resistance allele frequencies. Given that preinvasion equilibria of resistance are determined by factors including resistance costs, we show that protection against foreign pathogens afforded by positively correlated resistances can be lessened or even result in elevated infection risk at the population level, depending on local dynamics. Therefore, a pathogen's emergence potential could be influenced not only by its average infection rate but also by resistance variation resulting from prior selection imposed by endemic diseases.