The Effects of Face Masks on the Doctor-Patient Relationship in Orthopaedics

BackgroundSince the onset of the COVID-19 pandemic, the widespread use of face masks has grown exponentially. There is limited data highlighting the patient perception of face mask use during this pandemic, specifically in orthopaedic clinics. The purpose of this study was to determine the patient’s perception of the implementation of face masks in the orthopaedic clinic during a period of mask mandates and if this change impacted the success of their interactions with physicians. The secondary aim includes measures of patient satisfaction such as the ability to understand conversation and communicate effectively with the physician.MethodsParticipants were recruited on the day of their appointment at our institution’s orthopaedic clinic and provided with instructions via email. The online, anonymous survey included the CARE questionnaire - a tool to examine patient satisfaction by assessing perception of empathy and was conducted using Qualtrics.ResultsDoes patient preference to have their physician wear a face mask impact the success of their interactions with physicians? Overall, the use of face masks by physicians did not negatively impact patient encounters. CARE scores for patients who preferred masks (37.2) were similar to those who preferred their physician did not wear a mask (37.5). Is patient satisfaction affected by the use of face masks in the orthopaedic clinic? Patients who preferred that their doctor wear a face mask stated that it had no negative impact on the effect of communication or conversation with the physician. Other factors such as how well the patients knew the physician and patient gender had a greater impact on the CARE score than masks did.ConclusionOur study determined that the preference of face masks by patients does not impact the success of their interactions with physicians using the CARE score. The findings of this study are valuable in informing orthopaedic physicians about patient attitudes towards mask use and could influence decision making for not only the COVID-19 pandemic, but also future infectious outbreaks that may arise. Level of Evidence: III     

Spatiotemporal dynamics of viral hepatitis A in Italy

Viral hepatitis A is still common in Italy, especially in Southern regions. In this study, a metapopulation model for hepatitis A virus (HAV) transmission is proposed and analyzed. Analytical results on the asymptotic and transient behaviors of the system are carried out. Based on the available Italian movement data, a national spatial contact matrix at the regional level, which could be used for new studies on the transmission dynamics of other infectious diseases, is derived for modeling fluxes of individuals. Despite the small number of fitted parameters, model simulations are in good agreement with the observed average HAV incidence in all regions. Our results suggest that the mass vaccination program introduced in one Italian region only (Puglia, the one with the highest endemicity level) could have played a role in the decline of HAV incidence in the country as a whole. The only notable exception is represented by Campania, a Southern region showing a high endemicity level, which is not substantially affected by HAV dynamics in Puglia. Finally, our results highlight that the continuation of the vaccination campaign in Puglia would have a relevant impact in decreasing long-term HAV prevalence, especially in Southern Italy.     

Can a combination of vaccination and face mask wearing contain the COVID-19 pandemic?

The COVID-19 pandemic is going into its third year with Europe again being the focus of major epidemic activity. The present review tries to answer the question whether one can come to grip with the pandemic by a combination of vaccinations and non-pharmaceutical interventions (NPIs). Several COVID-19 vaccines are of remarkable efficacy and achieve high protection rates against symptomatic disease, especially severe disease, but mathematical models suggest that the current vaccination coverage in many countries is insufficient to achieve pandemic control. NPIs are needed as complementary measures because recent research has also revealed the limits of vaccination alone. Here, we review the evidence for efficacy of face mask wearing in various settings. Overall pooled analysis showed significant reduction in COVID-19 incidence with mask wearing, although heterogeneity between studies was substantial. Controlled trials of mask wearing are difficult to conduct, separating mask wearing effects in population studies from the impact of other NPIs is challenging and the efficacy of masks depend on mask material and mask fit. The combination of vaccination and mask wearing is potentially synergistic since vaccination protects so far well from disease development (the omicron variant is currently an unknown) but immunity from infection wanes over few months after vaccination. In comparison, masks interfere with the virus transmission process at a level of a physical barrier independent of coronavirus variant. Vaccination and masks are much less costly to apply than other NPI measures which are associated with high economic and social costs, but paradoxically both measures are the target of a vocal opposition by a sizable minority of the society. In parallel with biomedical research, we need more social science research into this opposition to guide political decisions on how to end the pandemic.     

Little Italy: an agent-based approach to the estimation of contact patterns- fitting predicted matrices to serological data

Knowledge of social contact patterns still represents the most critical step for understanding the spread of directly transmitted infections. Data on social contact patterns are, however, expensive to obtain. A major issue is then whether the simulation of synthetic societies might be helpful to reliably reconstruct such data. In this paper, we compute a variety of synthetic age-specific contact matrices through simulation of a simple individual-based model (IBM). The model is informed by Italian Time Use data and routine socio-demographic data (e.g., school and workplace attendance, household structure, etc.). The model is named "Little Italy" because each artificial agent is a clone of a real person. In other words, each agent's daily diary is the one observed in a corresponding real individual sampled in the Italian Time Use Survey. We also generated contact matrices from the socio-demographic model underlying the Italian IBM for pandemic prediction. These synthetic matrices are then validated against recently collected Italian serological data for Varicella (VZV) and ParvoVirus (B19). Their performance in fitting sero-profiles are compared with other matrices available for Italy, such as the Polymod matrix. Synthetic matrices show the same qualitative features of the ones estimated from sample surveys: for example, strong assortativeness and the presence of super- and sub-diagonal stripes related to contacts between parents and children. Once validated against serological data, Little Italy matrices fit worse than the Polymod one for VZV, but better than concurrent matrices for B19. This is the first occasion where synthetic contact matrices are systematically compared with real ones, and validated against epidemiological data. The results suggest that simple, carefully designed, synthetic matrices can provide a fruitful complementary approach to questionnaire-based matrices. The paper also supports the idea that, depending on the transmissibility level of the infection, either the number of different contacts, or repeated exposure, may be the key factor for transmission.     

Bayesian time-varying autoregressive models of COVID-19 epidemics

The COVID-19 pandemic has highlighted the importance of reliable statistical models which, based on the available data, can provide accurate forecasts and impact analysis of alternative policy measures. Here we propose Bayesian time-dependent Poisson autoregressive models that include time-varying coefficients to estimate the effect of policy covariates on disease counts. The model is applied to the observed series of new positive cases in Italy and in the United States. The results suggest that our proposed models are capable of capturing nonlinear growth of disease counts. We also find that policy measures and, in particular, closure policies and the distribution of vaccines, lead to a significant reduction in disease counts in both countries.     

Epidemiological,Clinical and Serological Characteristics of Children with Coronavirus Disease 2019 in Wuhan: A Single-centered,Retrospective Study

In December 2019, SARS-CoV-2 was first detected in the samples obtained from three adult patients who suffered from an unknown viral pneumonia in Wuhan (Li et al. 2020). This unknown viral pneumonia is further named as coronavirus disease 2019 (COVID-19) by the World Health Organization. To date, the number of new COVID-19 cases has continued to skyrocket and the impact of SARS-CoV-2 on humans is far greater than any pathogen of this century in both breadth and depth. Previous studies have shown that adults with COVID-19 have symptoms of fever, dry cough, dyspnea, fatigue and lymphocytopenia. Moreover, COVID-19 is more likely to cause death in the elderly, especially those with chronic comorbidities (Huang et al. 2020). In Wuhan, more than 50, 000 COVID-19 cases have been confirmed, including over 780 pediatric patients, and only one child death case (Lu et al. 2020). Although the number of children cases was far fewer than that of adults, COVID-19 might endanger children's health and the information on children remains limited, especially in serological study. In the retrospective study, the investigators analyzed the epidemiological, clinical and serological characteristics of children with COVID-19 in Wuhan in the early stages of the outbreak, which might provide theoretical and practical help in controlling COVID-19 and similar emerging infectious diseases in the future.     

Effectiveness of social distancing interventions in containing COVID-19 incidence: International evidence using Kalman filter

The epidemiological literature has widely documented the importance of social distancing interventions in containing the spread of the COVID-19 pandemic. However, the epidemiological measure of virus reproduction, R₀, provides a myopic view of containment, especially when the absolute number of cases is still high. The paper investigates cross-country variations concerning the impact of social distancing interventions on COVID-19 incidence by employing a statistical measure of containment, which models the daily number of cases as a structural time-series, state-space vector. Countries that adopt strict lockdown policies and provide economic support in the form of income augmentations and debt relief improve the response towards the pandemic. Countries like China and South Korea have been most influential in containing the spread of infections. European nations of France, Italy, Spain and the UK are witnessing a second wave of the virus, indicating that re-opening the European economy perhaps has instigated an exponential spread.     

Mass gathering events and the spread of infectious diseases: Evidence from the early growth phase of COVID-19

This paper studies the impact on reported coronavirus 2019 (COVID-19) cases and deaths in Spain resulting from large mass gatherings that occurred from March 6 to March 8, 2020. To study these outcomes, the geographic differences in the planned pre-pandemic major events that took place on these dates were exploited, which is a quasi-random source of variation for identification purposes. We collected daily and detailed information about the number of attendees at football (soccer) and basketball matches in addition to individuals participating in the Women’s Day marches across Spain, which we merged with daily data on reported COVID-19 cases and deaths at the provincial level. Our results reveal evidence of non-negligible COVID-19 cases related to the differences in the percentage of attendees at these major events from March 6 to March 8. In a typical province, approximately 31% of the average daily reported COVID-19 cases per 100,000 inhabitants between mid-March and early April 2020 can be explained by the participation rate in those major events. A back-of-the-envelope calculation suggests that this implies almost five million euros (169,000 euros/day) of additional economic cost in the health system of a typical province with one million inhabitants in the period under consideration. Several mechanisms behind the spread of COVID-19 are also examined.     

The evolving role of preprints in the dissemination of COVID-19 research and their impact on the science communication landscape

The world continues to face a life-threatening viral pandemic. The virus underlying the Coronavirus Disease 2019 (COVID-19), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has caused over 98 million confirmed cases and 2.2 million deaths since January 2020. Although the most recent respiratory viral pandemic swept the globe only a decade ago, the way science operates and responds to current events has experienced a cultural shift in the interim. The scientific community has responded rapidly to the COVID-19 pandemic, releasing over 125,000 COVID-19–related scientific articles within 10 months of the first confirmed case, of which more than 30,000 were hosted by preprint servers. We focused our analysis on bioRxiv and medRxiv, 2 growing preprint servers for biomedical research, investigating the attributes of COVID-19 preprints, their access and usage rates, as well as characteristics of their propagation on online platforms. Our data provide evidence for increased scientific and public engagement with preprints related to COVID-19 (COVID-19 preprints are accessed more, cited more, and shared more on various online platforms than non-COVID-19 preprints), as well as changes in the use of preprints by journalists and policymakers. We also find evidence for changes in preprinting and publishing behaviour: COVID-19 preprints are shorter and reviewed faster. Our results highlight the unprecedented role of preprints and preprint servers in the dissemination of COVID-19 science and the impact of the pandemic on the scientific communication landscape.

An analysis of bioRxiv and medRxiv during the first 10 months of the COVID-19 pandemic reveals that the pandemic has resulted in a cultural shift in the use of preprints for disseminating pandemic-related science.     

Filter efficiency of commercial face masks in capturing particles and airborne bacteria

The filter efficiency of seven kinds of commercial face mask for particles and airborne bacteria was tested in the wash room of a laboratory animal facility. The filter efficiency of the masks was 19 to 50%, as measured by the weight of particles with diameters below 10 micron, 22 to 71% for particles of the 0.3 micron level, 47 to 90% for the 1 micron level, and 90 to 99.6% for the 5 micron level. The filter efficiency for airborne bacteria was 35 to 81%. Among these even masks tested, glasswool surgery masks, three-sheet synthetic fiber masks with and without charcoal, and 28-sheet gauze masks with glass filter showed generally high efficiency, and single-sheet synthetic fiber masks, 18-sheet of gauze masks and gas masks showed low efficiency.     

Genetic heterogeneity in five Italian regions: analysis of PAH mutations and minihaplotypes

Molecular analysis of 289 chromosomes has been performed in a cohort of phenylketonuria (PKU) patients whose ancestors lived in five Italian regions, Calabria, Campania, Piemonte, Puglia/Basilicata and Sicilia. Phenylalaninehydroxylase (PAH) gene mutations and minihaplotypes (combinations of PAH gene STR and VNTR systems) have been determined for 78.5 and 64%, respectively, of the chromosomes studied. 21 different minihaplotypes and 24 PKU mutations were found. Heterogeneity tests carried out for the frequencies of mutations and minihaplotypes show that the distribution of eight mutations and four minihaplotypes is statistically heterogeneous in the five Italian regions. Although the evolutionary rate of microsatellites or the age of these mutations is difficult to estimate with accuracy, our findings taken together show a genetic stratification of the Italian population. These results rule out allelic homogeneity of PKU at the molecular level between regions of Italy, yet minihaplotype data may be of practical use for a multistep approach to PAH gene genotyping.     

New distributional data of the rare endemic species Eokochia saxicola (Guss.) Freitag and G. Kadereit (Chenopodiaceae): Effects on biogeography and conservation

Eokochia saxicola (Guss.) Freitag & G. Kadereit is a very rare endemic species of southern Italy and one of the rarest plants in Europe, included as priority species in the Annex II of the Council Directive 92/43/EEC. During the floristic surveys in the Cilento e Vallo di Diano National Park (Campania region, southern Italy), with the aim to assess the conservation status of rare and/or endemic species, new sites of occurrence of E. saxicola have been recorded representing the first known mainland sites; in fact, this endemic species was previously recorded only in the insular sites of Ischia (where it is extinct) and Capri in Campania region and Strombolicchio in Sicily region. Moreover, a further site was found in Capri island. So, three new sites of occurrence of E. saxicola have been recorded, increasing the total number from the two previously known to the actual five; in Campania, the total number increased from one to four. The research also increased significantly the global population size, currently made up of about 270 individuals compared with the 150 previously known. Consequences for the biogeography of the species and practical issues for conservation are discussed.     

Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods

Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain challenging to identify. In this study, we propose the use of a novel synthetic control framework to obtain causal estimates for direct and spill-over impacts of these events. The Sabah state elections in Malaysia were used as an example for our proposed methodology and we investigate the event’s spatial and temporal impacts on COVID-19 transmission. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election’s direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election’s spill-over effects. Sensitivity analysis was further conducted by examining epidemiological pre-trends, surveillance efforts, varying synthetic control matching characteristics and spill-over specifications. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines.     

Tracking the 2009 H1N1 influenza virus in the Italian region Campania

A novel swine-origin influenza A (H1N1) virus affecting humans was detected in April 2009 in Mexico, Canada, and USA. The S-OIV infection caused a mild to severe febrile respiratory disease throughout the world. Here, we briefly review the main features of influenza A viruses, which caused also other pandemics in the past, and focus in particular on the epidemiology data of the H1N1 influenza in the Italian region Campania, which resulted the most affected by the S-OIV and the one with more lethal cases. In Campania, the peak of influenza preceded of about 2 weeks the incidence peak at the national level. Moreover, the percentage of H1N1-positive patients was much higher in the main town Naples, compared to the other Campania provinces. The age group from 7 months to 17 years was the most affected by the H1N1 infection (43.45%), similarly to what reported at the national level. Here, we discuss the possible reasons of the high H1N1 incidence in Campania and the implications that these findings could have on the future prevention campaigns.     

Use of SSR and Retrotransposon-Based Markers to Interpret the Population Structure of Native Grapevines from Southern Italy

Native grapevines are the quintessential elements of Southern Italy winemaking, and genomic characterization plays a role of primary importance for preservation and sustainable use of these unexploited genetic resources. Among the various molecular techniques available, SSR and retrotransposons-based markers result to be the most valuable for cultivars and biotypes distinctiveness. A total of 62 accessions including 38 local grape cultivars were analyzed with 30 SSR, four REMAP and one IRAP markers to assess their genetic diversity and obtain a complete genomic profiling. The use of VrZAG79, VrZAG112, VVS2, VVMD25 and VVMD5 combined with retrotransposon-based markers proved to be the most discriminating and polymorphic markers for the rapid and unambiguous identification of minority grapevines from Campania region, which is considered one of the most appreciated Italian districts for wine production. Results revealed 58 SSR marker-specific alleles, 22 genotype-specific SSR alleles, and four REMAP and IRAP private bands. Cases of synonymy and homonymy were discovered. In conclusion, we provided evidences that the integrating SSR and retrotransposon-based markers is an effective strategy to assess the genetic diversity of autochthonous grapes, allowing their easy identification.     

COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit

This paper describes a data-driven simulation study that explores the relative impact of several low-cost and practical non-pharmaceutical interventions on the spread of COVID-19 in an outpatient hospital dialysis unit. The interventions considered include: (i) voluntary self-isolation of healthcare personnel (HCPs) with symptoms; (ii) a program of active syndromic surveillance and compulsory isolation of HCPs; (iii) the use of masks or respirators by patients and HCPs; (iv) improved social distancing among HCPs; (v) increased physical separation of dialysis stations; and (vi) patient isolation combined with preemptive isolation of exposed HCPs. Our simulations show that under conditions that existed prior to the COVID-19 outbreak, extremely high rates of COVID-19 infection can result in a dialysis unit. In simulations under worst-case modeling assumptions, a combination of relatively inexpensive interventions such as requiring surgical masks for everyone, encouraging social distancing between healthcare professionals (HCPs), slightly increasing the physical distance between dialysis stations, and—once the first symptomatic patient is detected—isolating that patient, replacing the HCP having had the most exposure to that patient, and relatively short-term use of N95 respirators by other HCPs can lead to a substantial reduction in both the attack rate and the likelihood of any spread beyond patient zero. For example, in a scenario with R₀ = 3.0, 60% presymptomatic viral shedding, and a dialysis patient being the infection source, the attack rate falls from 87.8% at baseline to 34.6% with this intervention bundle. Furthermore, the likelihood of having no additional infections increases from 6.2% at baseline to 32.4% with this intervention bundle.     

The effect of lockdowns and infection rates on supermarket sales

In this paper we document the evolution of the supermarket sales in one of the European countries, Spain, that has been most hardly hit by the COVID-19 pandemic. Using a very detailed dataset at the weekly and municipality level on the sales of a supermarket chain, we are able to separately identify the effects on sales for 12 different food products and for three population age groups. Furthermore, we distinguish between the impact of the lockdown, which affected the entire territory by mid-March, from the effect of the number of new confirmed positive COVID-19 cases at the municipal level. Our results show strong stockpiling effects for most of the products in the first week of adoption of the lockdown measures. On the other hand, the number of new cases at the municipal level is associated with reductions in sales, pointing towards increased fears of being infected as the main driver of the slowdown in sales. Finally, when we do a separate analysis for different age groups, we find no effects for individuals aged 66 and over.     

Is 2020 the year when primatologists should cancel fieldwork? A reply

The aim of this article is to explore the impact of coronavirus disease (COVID-19) pandemic on primate-related conservation work. The withdrawal of primatologists and conservation staff from field research can lead to a number of detrimental effects not just on conservation but also on local communities in low- and middle-income countries. Inequalities in access to health and financial insecurities may be drivers for the illegal wildlife trade and the lack of tourism and research activity may allow poachers to work with greater ease. The paper also looks at how conservation organizations and research bodies should modify their field protocols by developing robust occupational health policies that will not only make field work safer but also support local staff as they are likely to face the greatest threats to their physical health, psychological health, and economic loss from COVID-19. By adopting a One Health approach that considers the complex interactions between human and primate health, researchers will be able to find new ways of working not only to protect primates but understand how they adapt to the COVID-19 pandemic.     

An analytical study of the factors that influence COVID-19 spread

The outbreak of the coronavirus disease 2019 (COVID-19) continues to constitute an international public health emergency. Seasonality is a long-recognized attribute of many viral infections of humans. Nevertheless, the relationship between environmental factors and the spread of infection, particularly for person-to-person communicable diseases, remains poorly understood. This study explores the relationship between environmental factors and the incidence of COVID-19 in 188 countries with reported COVID-19 cases as of April 13, 2020. Here we show that COVID-19 growth rates peaked in temperate zones in the Northern Hemisphere during the outbreak period, while they were lower in tropical zones. The relationships between COVID-19 and environmental factors were resistant to the potentially confounding effects of air pollution, sea level, and population. To prove the effect of those factors, study, and analysis of the prevalence of COVID-19 in Italy, Spain, and China was undertaken. A fuzzy logic system was designed to predict the effects of that variables on the rate of viral spread of COVID-19.