Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review

A critical review of research methodologies for COVID-19 transmission in indoor built environment

The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.

A phenomenological neural network powered by the National Wastewater Surveillance System for estimation of silent COVID-19 infections

Although wastewater-based epidemiology (WBE) has emerged as an inexpensive and non-intrusive method in contrast to clinical testing to track public health at community levels, there is a lack of structured interpretative criteria to translate the SARS-CoV-2 concentrations in wastewater to COVID-19 infection cases. The difficulties lie in the uncertainties of the amount of virus shed by an infected individual to wastewater as documented in clinical studies. This situation is even worse considering the existence of a population of silent infections and many other confounding factors. In this research, a quantitative framework of a phenomenological neural network (PNN) was developed to compute silent infections. The PNN was trained using the WBE data from the National Wastewater Surveillance System (NWSS) - a program launched by the CDC of the United States in 2020. It is found that the PNN excelled with superior interpretability and reduced overfitting. A big-data perspective on virus shedding by an infected population revealed more deterministic virus-shedding dynamics compared to the clinical studies perspective on virus shedding by an infected individual. With such characteristics employed as the theoretical basis for the estimation of the silent infections, a ratio of silent to reported infections was found to be 5.7 as the national median during the studied period. The study also noted the influence of temperature, sewershed population, and per-capita flow rates on the computation of silent infections. It is expected that the proposed framework in this work would facilitate public health actions guided by the SARS-CoV-2 concentrations in wastewater. In case of a new wave emergence or a new virus disease outbreak like COVID-19, the PNN powered by the NWSS would outline consolidated and systematic information that would enable rapid deployment of public health actions.

A data-driven framework to assess population dynamics during novel coronavirus outbreaks: A case study on Xiamen Island, China

The outbreak of the Coronavirus Disease 2019 (COVID-19) has profoundly influenced daily life, necessitating the understanding of the relationship between the epidemic's progression and population dynamics. In this study, we present a data-driven framework that integrates GIS-based data mining technology and a Susceptible, Exposed, Infected and Recovered (SEIR) model. This approach helps delineate population dynamics at the grid and community scales and analyze the impacts of government policies, urban functional areas, and intercity flows on population dynamics during the pandemic. Xiamen Island was selected as a case study to validate the effectiveness of the data-driven framework. The results of the high/low cluster analysis provide 99% certainty (P < 0.01) that the population distribution between January 23 and March 16, 2020, was not random, a phenomenon referred to as high-value clustering. The SEIR model predicts that a ten-day delay in implementing a lockdown policy during an epidemic can lead to a significant increase in the number of individuals infected by the virus. Throughout the epidemic prevention and control period (January 23 to February 21, 2020), residential and transportation areas housed more residents. After the resumption of regular activities, the population was mainly concentrated in residential, industrial, and transportation, as well as road facility areas. Notably, the migration patterns into and out of Xiamen were primarily centered on neighboring cities both before and after the outbreak. However, migration indices from cities outside the affected province drastically decreased and approached zero following the COVID-19 outbreak. Our findings offer new insights into the interplay between the epidemic's development and population dynamics, which enhances the prevention and control of the coronavirus epidemic.

Macro-analysis of climatic factors for COVID-19 pandemic based on Köppen-Geiger climate classification

This study integrated dynamic models and statistical methods to design a novel macroanalysis approach to judge the climate impacts. First, the incidence difference across Köppen-Geiger climate regions was used to determine the four risk areas. Then, the effective influence of climate factors was proved according to the non-climate factors' non-difference among the risk areas, multi-source non-major component data assisting the proof. It is found that cold steppe arid climates and wet temperate climates are more likely to transmit SARS-CoV-2 among human beings. Although the results verified that the global optimum temperature was around 10 °C, and the average humidity was 71%, there was evident heterogeneity among different climate risk areas. The first-grade and fourth-grade risk regions in the Northern Hemisphere and fourth-grade risk regions in the Southern Hemisphere are more sensitive to temperature. However, the third-grade risk region in the Southern Hemisphere is more sensitive to relative humidity. The Southern Hemisphere's third-grade and fourth-grade risk regions are more sensitive to precipitation.

Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis

As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.

Estimation of Anthropogenic VOCs Emission Based on Volatile Chemical Products: A Canadian Perspective

Volatile organic compounds (VOCs) in urban areas are of great interest due to their significant role in forming ground-level ozone and adverse public health effects. Emission inventories usually compile the outdoor VOCs emission sources (e.g., traffic and industrial emissions). However, considering emissions from volatile chemical products (e.g., solvents, printing ink, personal care products) is challenging because of scattered data and the lack of an effective method to estimate the VOCs emission rate from these chemical products. This paper aims to systematically analyse potential sources of VOCs emission in Canada's built environment, including volatile chemical products. Also, spatial variation of VOCs level in the ambient atmosphere is examined to understand the VOC relationship with ozone and secondary organic aerosol formation. The study shows that VOCs level may vary among everyday microenvironments (e.g., residential areas, offices, and retail stores) depending on the frequency of product consumption, building age, ventilation condition, and background ambient concentration in the atmosphere. However, it is very difficult to establish VOC speciation and apportionment to different volatile chemical products that contribute most significantly to exposure and target subpopulations with elevated levels. Thus, tracer compounds can be used to identify inventory sources at the consumer end. A critical overview highlights the limitations of existing VOC estimation methods and possible approaches to control VOC emissions. The findings provide crucial information to establish an emission inventory framework for volatile chemical products at a national scale and enable policymakers to limit VOCs emission from various volatile chemical products.

Quantitative resilience assessment of the network-level metro rail service's responses to the COVID-19 pandemic

The metro rail system has proven to be the most efficient high-capacity carriers. During the unprecedented coronavirus disease 2019 (COVID-19) challenge, non-pharmaceutical interventions become a widely adopted strategy to limit physical movements and interactions. For situational awareness and decision support, data-driven analytics about serviceability are invaluable to metro agencies and decision-makers of cities. This paper presents a data-driven analytical framework that quantitatively evaluates COVID-19-caused resilience performance of metro rails. Several characteristics (e.g., vulnerability, robustness, rapidity, and degree to return) of the metro system's responses to the disturbance were identified and modeled with multivariate multiple regression. The applicability and rationality of the resilience evaluation model were validated by the metro transit data of the United States. The preliminary results disclosed that metro rail transit encountered more vulnerability (90.6%) in passenger trips than motorbus and light rail (around 70%). A set of statistical models were employed to disentangle the effect of socio-demographic variables and COVID-19-related factors on the metro transit. The disclosed emerging knowledge of resilience provides an in-depth understanding of mobility trends for the public and time-sensitive decision support for the policy effects, to further improve the service and management of the metro system under the spread of the epidemic.

Evolutionary dissection of monkeypox virus: Positive Darwinian selection drives the adaptation of virus-host interaction proteins

The emerging and ongoing outbreak of human monkeypox (hMPX) in 2022 is a serious global threat. An understanding of the evolution of the monkeypox virus (MPXV) at the single-gene level may provide clues for exploring the unique aspects of the current outbreak: rapidly expanding and sustained human-to-human transmission. For the current investigation, alleles of 156 MPXV coding genes (which account for >95% of the genomic sequence) have been gathered from roughly 1,500 isolates, including those responsible for the previous outbreaks. Using a range of molecular evolution approaches, we demonstrated that intra-species homologous recombination has a negligible effect on MPXV evolution. Despite the fact that the majority of the MPXV genes (64.10%) were subjected to negative selection at the whole gene level, 10 MPXV coding genes (MPXVgp004, 010, 012, 014, 044, 098, 138, 178, 188, and 191) were found to have a total of 15 codons or amino acid sites that are known to evolve under positive Darwinian selection. Except for MPXVgp138, almost all of these genes encode proteins that interact with the host. Of these, five ankyrin proteins (MPXVgp004, 010, 012, 178, and 188) and one Bcl-2-like protein (MPXVgp014) are involved in poxviruses' host range determination. We discovered that the majority (80%) of positive amino acid substitutions emerged several decades ago, indicating that these sites have been under constant selection pressure and that more adaptable alleles have been circulating in the natural reservoir. This finding was also supported by the minimum spanning networks of the gene alleles. The three positive amino acid substitutions (T/A426V in MPXVgp010, A423D in MPXVgp012, and S105L in MPXVgp191) appeared in 2019 or 2022, indicating that they would be crucial for the virus' eventual adaptation to humans. Protein modeling suggests that positive amino acid substitutions may affect protein functions in a variety of ways. Further study should focus on revealing the biological effects of positive amino acid substitutions in the genes for viral adaptation to humans, virulence, transmission, and so on. Our study advances knowledge of MPXV's adaptive mechanism and provides insights for exploring factors that are responsible for the unique aspects of the current outbreak.

Who is the biological patient? A new gradational and dynamic model for one health medicine

One Health medicine aims to improve health by focusing on the relations between the health of humans, animals, and the environment. However, One Health does not provide a clear idea of these relations, which are still represented as conceptually separated and not as one health, as the name implies. Inspired by holobiont research, I suggest a new model and conceptual framework for One Health that expands the notion of the biological patient by providing a gradational and dynamic understanding of environments, patients, and their relations. This new model conceptualizes humans and non-humans, individual organisms, and collectives, as belonging to one system that allows for more or less inclusive understandings of patients. As such, it resolves the conceptual tensions of different One Health approaches and supports the implementation of One Health as an interdisciplinary research field.

Temperature Influences the Interaction between SARS-CoV-2 Spike from Omicron Subvariants and Human ACE2

SARS-CoV-2 continues to infect millions of people worldwide. The subvariants arising from the variant-of-concern (VOC) Omicron include BA.1, BA.1.1, BA.2, BA.2.12.1, BA.4, and BA.5. All possess multiple mutations in their Spike glycoprotein, notably in its immunogenic receptor-binding domain (RBD), and present enhanced viral transmission. The highly mutated Spike glycoproteins from these subvariants present different degrees of resistance to recognition and cross-neutralisation by plasma from previously infected and/or vaccinated individuals. We have recently shown that the temperature affects the interaction between the Spike and its receptor, the angiotensin converting enzyme 2 (ACE2). The affinity of RBD for ACE2 is significantly increased at lower temperatures. However, whether this is also observed with the Spike of Omicron and sub-lineages is not known. Here we show that, similar to other variants, Spikes from Omicron sub-lineages bind better the ACE2 receptor at lower temperatures. Whether this translates into enhanced transmission during the fall and winter seasons remains to be determined.

Substantial impact of mobility restrictions on reducing COVID-19 incidence in Italy in 2020

BACKGROUND

Italy was the first country after China to be severely affected by the COVID-19 pandemic, in early 2020. The country responded swiftly to the outbreak with a nationwide two-step lockdown, the first one light and the second one tight. By analyzing 2020 national mobile phone movements, we assessed how lockdown compliance influenced its efficacy.

METHODS

We measured individual mobility during the first epidemic wave with mobile phone movements tracked through carrier networks, and related this mobility to daily new SARS-CoV-2 infections, hospital admissions, intensive care admissions and deaths attributed to COVID-19, taking into account reason for travel (work-related or not) and the means of transport.

RESULTS

The tight lockdown resulted in an 82% reduction in mobility for the entire country and was effective in swiftly curbing the outbreak as indicated by a shorter time-to-peak of all health outcomes, particularly for provinces with the highest mobility reductions and the most intense COVID-19 spread. Reduction of work-related mobility was accompanied by a nearly linear benefit in outbreak containment; work-unrelated movements had a similar effect only for restrictions exceeding 50%. Reduction in mobility by car and by airplane was nearly linearly associated with a decrease in most COVID-19 health outcomes, while for train travel reductions exceeding 55% had no additional beneficial effects. The absence of viral variants and vaccine availability during the study period eliminated confounding from these two sources.

CONCLUSIONS

Adherence to the COVID-19 tight lockdown during the first wave in Italy was high and effective in curtailing the outbreak. Any work-related mobility reduction was effective, but only high reductions in work-unrelated mobility restrictions were effective. For train travel, there was a threshold above which no further benefit occurred. These findings could be particular to the spread of SARS-CoV-2, but might also apply to other communicable infections with comparable transmission dynamics.

The COVID-19 Oral Drug Molnupiravir Is a CES2 Substrate: Potential Drug-Drug Interactions and Impact of CES2 Genetic Polymorphism In Vitro

Molnupiravir is one of the two coronavirus disease 2019 (COVID-19) oral drugs that were recently granted the emergency use authorization by the Food and Drug Administration (FDA). Molnupiravir is an ester and requires hydrolysis to exert antiviral activity. Carboxylesterases constitute a class of hydrolases with high catalytic efficiency. Humans express two major carboxylesterases (CES1 and CES2) that differ in substrate specificity. Based on the structural characteristics of molnupiravir, this study was performed to test the hypothesis that molnupiravir is preferably hydrolyzed by CES2. Several complementary approaches were used to test this hypothesis. As many as 24 individual human liver samples were tested and the hydrolysis of molnupiravir was significantly correlated with the level of CES2 but not CES1. Microsomes from the intestine, kidney, and liver, but not lung, all rapidly hydrolyzed molnupiravir and the magnitude of hydrolysis was related closely to the level of CES2 expression among these organs. Importantly, recombinant CES2 but not CES1 hydrolyzed molnupiravir, collectively establishing that molnupiravir is a CES2-selective substrate. In addition, several CES2 polymorphic variants (e.g., R180H) differed from the wild-type CES2 in the hydrolysis of molnupiravir. Molecular docking revealed that wild-type CES2 and its variant R180H used different sets of amino acids to interact with molnupiravir. Furthermore, molnupiravir hydrolysis was significantly inhibited by remdesivir, the first COVID-19 drug granted the full approval by the FDA. The results presented raise the possibility that CES2 expression and genetic variation may impact therapeutic efficacy in clinical situations and warrants further investigation. SIGNIFICANCE STATEMENT: COVID-19 remains a global health crisis, and molnupiravir is one of the two recently approved oral COVID-19 therapeutics. In this study, we have shown that molnupiravir is hydrolytically activated by CES2, a major hydrolase whose activity is impacted by genetic polymorphic variants, disease mediators, and many potentially coadministered medicines. These results presented raise the possibility that CES2 expression and genetic variation may impact therapeutic efficacy in clinical situations and warrants further investigation.

Impact of improved indoor environment on recovery from COVID-19 infections: a review of literature

Purpose

This study aims to explore the impact of the indoor environment on recovery from COVID-19 infections. Extant literature on the impact of the four key themes of the indoor environment (indoor air quality, indoor thermal quality, daylighting and visual comfort, and acoustic comfort) on COVID-19 infection and recovery rates were reviewed.

Design/methodology/approach

Data collection for this study was based on extant literature within the Scopus database and scoped to a time frame of 2020–2021 because the topical issue of indoor environmental quality (IEQ) and its impact on COVID-19 arose in the wake of the pandemic. In total, 224 documents were systematically desk reviewed from various journals.

Findings

The study identified that air pollutants such as PM2.5 and PM10 as well as air-conditioned places, low ambient temperatures, poor ventilation and no views of the outdoor environment were deteriorating factors for COVID-19 patients. On the other hand, proper ventilation, the use of air cleaners, views of the outdoor environment and allowance for ample daylighting were improvement factors for COVID-19 patients. The inter-relationship of the various concepts was presented in an ontology chart.

Practical implications

As COVID-19 still exists and keeps evolving, this study provides suggestions to industry professionals, especially health-care Facility Managers, to create a post-pandemic environment focusing on the IEQ and finding long-term and reliable solutions for the well-being of occupants. Adaptability is crucial. New, creative technology solutions are being introduced daily, but it is up to the facility managers and health-care professionals to analyse and specify the most cost- and outcome-effective technologies for their facility.

Originality/value

The study brought to light the pivotal role of the indoor environment on the health and well-being of occupants, particularly in the contraction, spread, prevention and control of infectious diseases such as COVID-19.