Associations Between Wearing Masks and Respiratory Viral Infections: A Meta-Analysis and Systematic Review

Identifying the interplay between protective measures and settings on the SARS-CoV-2 transmission using a Bayesian network

Contact tracing played a crucial role in minimizing the onward dissemination of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the recent pandemic. Previous studies had also shown the effectiveness of preventive measures such as mask-wearing, physical distancing, and exposure duration in reducing SARS-CoV-2 transmission. However, there is still a lack of understanding regarding the impact of various exposure settings on the spread of SARS-CoV-2 within the community, as well as the most effective preventive measures, considering the preventive measures adherence in different daily scenarios. We aimed to evaluate the effect of individual protective measures and exposure settings on the community transmission of SARS-CoV-2. Additionally, we aimed to investigate the interaction between different exposure settings and preventive measures in relation to such SARS-CoV-2 transmission. Routine SARS-CoV-2 contact tracing information was supplemented with additional data on individual measures and exposure settings collected from index patients and their close contacts. We used a case-control study design, where close contacts with a positive test for SARS-CoV-2 were classified as cases, and those with negative results classified as controls. We used the data collected from the case-control study to construct a Bayesian network (BN). BNs enable predictions for new scenarios when hypothetical information is introduced, making them particularly valuable in epidemiological studies. Our results showed that ventilation and time of exposure were the main factors for SARS-CoV-2 transmission. In long time exposure, ventilation was the most effective factor in reducing SARS-CoV-2, while masks and physical distance had on the other hand a minimal effect in this ventilation spaces. However, face masks and physical distance did reduce the risk in enclosed and unventilated spaces. Distance did not reduce the risk of infection when close contacts wore a mask. Home exposure presented a higher risk of SARS-CoV-2 transmission, and any preventive measures posed a similar risk across all exposure settings analyzed. Bayesian network analysis can assist decision-makers in refining public health campaigns, prioritizing resources for individuals at higher risk, and offering personalized guidance on specific protective measures tailored to different settings or environments.

Infection Risk Prediction in Healthcare Settings: Lessons from COVID-19 Contact Tracing

Objective

Contact tracing aids epidemic control by enabling early detection and isolation without overburdening healthcare systems despite potential challenges. This study aimed to evaluate the practical application of contact and risk assessment-based models in predicting SARS-CoV-2 infection following exposure among healthcare workers in a large tertiary public university hospital in Türkiye.

Materials and Methods

The study was designed as a retrospective cohort study, including contact tracing data from 3389 exposed healthcare workers from March 23, 2020, to October 22, 2021. Contact-based (mask use, contact duration and distance) and exposure risk-assessment-based (low, medium, high-risk) models with and without having symptoms were generated using logistic regression. SARS-CoV-2 infection was defined as having a positive SARS-CoV-2 RT-PCR test result. Adjustments were made to the models for demographic and occupational variables, previous infection, and vaccination. Model parameters were compared.

Results

Of 3389 exposed healthcare workers, 2451 underwent RT-PCR testing. Among those tested, RT-PCR positivity was 5.9% (144/2451). Lack of personal protective equipment use (odds ratio [OR]=1.64, 95% confidence interval [CI]=1.03-2.66) and ≥15 minutes of contact duration (1.89, 1.21-3.09) were significantly associated with RT-PCR positivity. In the risk-assessment model, being a high-risk contact increased the odds of RT-PCR positivity (OR=2.76, 95% CI=1.61-5.03). Adding the presence of symptoms to contact-based and risk assessment models improved model parameters (Akaike information criterion [AIC]: from 1086.1 to 1083.1; Tjur's R2: from 0.016 to 0.019, respectively).

Conclusion

The inclusion of being symptomatic improved the contact-based and risk assessment-based models. Institutions should be encouraged to incorporate symptom inquiries into risk assessment protocols in response to newly emerging respiratory virus epidemics. Institutions lacking the capacity for extensive contact tracing are recommended, at minimum, to track symptomatic exposed workers for epidemic control.

Personal protective measures and settings on the risk of SARS-COV-2 community transmission: a case-control study

Background

During the SARS-CoV-2 pandemic, nurses of primary health care has been an important role in Spain. Even so, the data obtained in the tracing have been scarcely used to investigate the possible mechanisms of transmission. Few studies focused on community transmission, evaluating the effectiveness of individual protective measures and exposure environment. The main aim of the study was to evaluate the association between individual protective measures and SARS-CoV-2 transmission in the community and to compare secondary attack rates in different exposure settings.

Methods

A case-control study from contact tracing of SARS-CoV-2 index patients. COVID-19 contact tracing was led by nurses at the COVID-19 Coordinating Centre in Majorca (Spain). During the systematic tracing, additional information for this study was collected from the index patient (social-demographic variables, symptoms, the number of close contacts). And also, the following variables from their close contacts: contact place, ventilation characteristics mask-wearing, type of mask, duration of contact, shortest distance, case-contact relationship, household members, and handwashing, the test result for SARS-CoV-2 diagnostic. Close contacts with a positive test for SARS-CoV-2 were classified as "cases" and those negative as "controls."

Results

A total of 1,778 close contacts from 463 index patients were identified. No significant differences were observed between the sexes but between age groups. Overall Secondary Attack Rate (SAR) was 24.0% (95% CI: 22.0-26.0%), 36.9% (95% CI: 33.2-40.6%) in closed spaces without ventilation and 50.7% (95% CI: 45.6-55.8%) in exposure time > 24 h. A total of 49.2% of infections occurred among household members. Multivariate logistic regression analysis showed that open-air setting (OR 0.43, 95% CI: 0.27-0.71), exposure for less than 1 h (OR 0.19, 95% CI: 0.11-0.32), and wearing a mask (OR 0.49, 95% CI: 0.28-0.85) had a protective effect transmission of SARS-CoV-2 in the community.

Conclusion

Ventilation of the space, mask-wearing and shorter exposure time were associated with a lower risk of transmission in the community. The data obtained allowed an assessment of community transmission mechanisms and could have helped to improve and streamline tracing by identifying close contacts at higher risk.

Masking strategy to protect healthcare workers from COVID-19: An umbrella meta-analysis

BACKGROUND

The burden of severe disease and death due to SARS-CoV-2 (COVID-19) pandemic among healthcare workers (HCWs) worldwide has been substantial. Masking is a critical control measure to effectively protect HCWs from respiratory infectious diseases, yet for COVID-19, masking policies have varied considerably across jurisdictions. As Omicron variants began to be predominant, the value of switching from a permissive approach based on a point of care risk assessment (PCRA) to a rigid masking policy needed to be assessed.

METHODS

A literature search was conducted in MEDLINE (Ovid platform), Cochrane Library, Web of Science (Ovid platform), and PubMed to June 2022. An umbrella review of meta-analyses investigating protective effects of N95 or equivalent respirators and medical masks was then conducted. Data extraction, evidence synthesis and appraisal were duplicated.

RESULTS

While the results of Forest plots slightly favoured N95 or equivalent respirators over medical masks, eight of the ten meta-analyses included in the umbrella review were appraised as having very low certainty and the other two as having low certainty.

CONCLUSION

The literature appraisal, in conjunction with risk assessment of the Omicron variant, side-effects and acceptability to HCWs, along with the precautionary principle, supported maintaining the current policy guided by PCRA rather than adopting a more rigid approach. Well-designed prospective multi-centre trials, with systematic attention to the diversity of healthcare settings, risk levels and equity concerns are needed to support future masking policies.

Intensive care unit admissions with and without COVID-19 in Finland from 2017 to 2021: a retrospective register-based study

BACKGROUND

After the COVID-19 pandemic started, critical care resources were expanded in Finland to manage a possible surge in patients requiring intensive care. The aim of this study was to evaluate the incidence of overall ICU admissions, patient diagnoses, characteristics, and length of stay during the pandemic.

METHODS

This retrospective hospital register-based study was conducted in two large and one mid-size Finnish public hospitals. The required data were collected from ICU patient information systems and all adult patients were included. Monthly and yearly incidences with 95% confidence intervals (CI) were counted per 100 000 persons-years by Poisson exact method and compared by incidence rate ratios (IRR).

RESULTS

A total of 4407 admissions to ICUs for any cause occurred during 2020. In 2021, this figure was 4931. During the reference years (2017-2019), the mean number of admissions to ICU was 4781. In 2020 and 2021, the proportion of patients requiring intensive care due to COVID-19 was only 3%. The incidence of all-cause ICU admissions decreased during the lockdown in 2020 when compared to the reference years. Before the start of the lockdown in February 2020, the IRR of all-cause ICU admissions was 1.02 (CI: 0.89 to 1.18). During the lockdown period, however, the IRR of all-cause ICU admissions decreased to 0.78 (CI: 0.67 to 0.90) in March. When the lockdown ended, the incidence rebounded to the same level as before the lockdown. However, in 2021, the incidence of ICU admissions remained at the same level when compared to the reference years. The most prominent changes occurred in the incidence of diseases of the nervous system, which includes epilepsy and seizures and transient cerebral ischemic attacks, in diseases of the respiratory system, and neoplasms.

CONCLUSIONS

According to the findings of this study, the incidence of all-cause ICU admissions decreased after the lockdown was implemented in 2020. Furthermore, the percentage of patients requiring intensive care due to COVID-19 in Finland was only 3% in 2020 and 2021. These findings may serve to help in the planning and allocating of ICU resources during future pandemics.

Face mask use to prevent COVID-19 in clinical practice. Using a review of reviews to improve decision-making and transparency

BACKGROUND

The COVID-19 pandemic has highlighted the importance of transparency and scientific rigour in the development of clinical guidance. Rapid review methodologies were widely used in the development of guidance, and in the United Kingdom, COVID-19 guidance was criticized for methodological inadequacy and erroneous conclusions.

AIMS

To summarize the evidence looking at the use of face masks to prevent COVID-19 infection in clinical practice areas, and to show how this can be used in decision-making.

DESIGN

Overview of systematic reviews.

METHOD

Systematic reviews which included meta-analyses were sought, and data on the protective effect of face masks on COVID-19 transmission were extracted. A total of 15 papers yielded 44 effect sizes suitable for quantitative presentation, which showed wide variation in effect depending on the outcome and intervention chosen.

CONCLUSIONS

Guideline development groups need to take care to choose outcomes that are of most importance to those who are the target of guidance. Quantification of the protective effect of interventions such as different types of face mask will help nurses and others decide on the utility of their use, alongside consideration of the other factors that go into informing clinical recommendations.

IMPLICATIONS FOR PATIENT CARE AND THE PROFESSION

COVID-19 has been an unprecedented public health issue, but much clinical guidance was lacking in transparency. Nurses and other healthcare professionals have often expressed a lack of confidence in guidance. Systematic reviews reported a wide range of effect sizes. However, there was a high degree of indirectness and heterogeneity in methods and findings. To produce transparent guidance, those for whom guidance is intended should have evidence of effect where this is available.

IMPACT

Guideline authors should reflect these outcomes in their recommendations, clearly balancing both the benefits and harms of recommending face masks to prevent COVID-19.