Impact of outdoor and indoor meteorological conditions on the COVID-19 transmission in the western region of Saudi Arabia

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.

Assessing the effects of transient weather conditions on airborne transmission risk in naturally ventilated hospitals

BACKGROUND

Many UK hospitals rely heavily on natural ventilation as their main source of airflow in patient wards. This method of ventilation can have cost and energy benefits, but it may lead to unpredictable flow patterns between indoor spaces, potentially leading to the unexpected transport of infectious material to other connecting zones. However, the effects of weather conditions on airborne transmission are often overlooked.

METHODS

A multi-zone CONTAM model of a naturally ventilated hospital respiratory ward, incorporating time-varying weather, was proposed. Coupling this with an airborne infection model, this study assessed the variable risk in interconnected spaces, focusing particularly on occupancy, disease and ventilation scenarios based on a UK respiratory ward.

RESULTS

The results suggest that natural ventilation with varying weather conditions can cause irregularities in the ventilation rates and interzonal flow rates of connected zones, leading to infrequent but high peaks in the concentration of airborne pathogens in particular rooms. This transient behaviour increases the risk of airborne infection, particularly through movement of pathogens between rooms, and highlights that large outbreaks may be more likely under certain conditions. This study demonstrated how ventilation rates achieved by natural ventilation are likely to fall below the recommended guidance, and that the implementation of supplemental mechanical ventilation can increase ventilation rates and reduce the variability in infection risks.

CONCLUSION

This model emphasises the need for consideration of transient external conditions when assessing the risk of transmission of airborne infection in indoor environments.

The effect of natural ventilation on airborne transmission of the COVID-19 virus spread by sneezing in the classroom

Since school classrooms are of vital importance due to their impact on public health in COVID-19 and similar epidemics, it is imperative to develop new ventilation strategies to reduce the risk of transmission of the virus in the classroom. To be able to develop new ventilation strategies, the effect of local flow behaviors in the classroom on the airborne transmission of the virus under the most dramatic conditions must first be determined. In this study, the effect of natural ventilation on the airborne transmission of COVID-19-like viruses in the classroom in the case of sneezing by two infected students in a reference secondary school classroom was investigated in five scenarios. Firstly, experimental measurements were carried out in the reference class to validate the computational fluid dynamics (CFD) simulation results and determine the boundary conditions. Next, the effects of local flow behaviors on the airborne transmission of the virus were evaluated for five scenarios using the Eulerian-Lagrange method, a discrete phase model, and a temporary three-dimensional CFD model. In all scenarios, immediately after sneezing, between 57 and 60.2 % of the droplets containing the virus, mostly large and medium-sized (150 μm < d < 1000 μm) settled on the infected student's desk, while small droplets continued to move in the flow field. In addition, it was determined that the effect of natural ventilation in the classroom on the travel of virus droplets in the case of Redh < 8.04 × 104 (Reynolds number, Redh=Udh/νu, dh and are fluid velocity, hydraulic diameters of the door and window sections of the class and kinematic viscosity, respectively) was negligible.

An Improvement Strategy for Indoor Air Quality Monitoring Systems

Air quality has a huge impact on the comfort and healthiness of various environments. According to the World Health Organization, people who are exposed to chemical, biological and/or physical agents in buildings with low air quality and poor ventilation are more prone to be affected by psycho-physical discomfort, respiratory tract and central nervous system diseases. Moreover, in recent years, the time spent indoors has increased by around 90%. If we consider that respiratory diseases are mainly transmitted from human to human through close contact, airborne respiratory droplets and contaminated surfaces, and that there is a strict relationship between air pollution and the spread of the diseases, it becomes even more necessary to monitor and control these environmental conditions. This situation has inevitably led us to consider renovating buildings with the aim of improving both the well-being of the occupants (safety, ventilation, heating) and the energy efficiency, including monitoring the internal comfort using sensors and the IoT. These two objectives often require opposite approaches and strategies. This paper aims to investigate indoor monitoring systems to increase the quality of life of occupants, proposing an innovative approach consisting of the definition of new indices that consider both the concentration of the pollutants and the exposure time. Furthermore, the reliability of the proposed method was enforced using proper decision-making algorithms, which allows one to consider measurement uncertainty during decisions. Such an approach allows for greater control over the potentially harmful conditions and to find a good trade-off between well-being and the energy efficiency objectives.

What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update

The climatological parameters can be different in various geographical locations. Moreover, they have possible impacts on COVID-19 incidence. Therefore, the purpose of this systematic review article was to describe the effects of climatic variables on COVID-19 pandemic in different countries. Systematic literature search was performed in Scopus, ISI Web of Science, and PubMed databases using ("Climate" OR "Climate Change" OR "Global Warming" OR "Global Climate Change" OR "Meteorological Parameters" OR "Temperature" OR "Precipitation" OR "Relative Humidity" OR "Wind Speed" OR "Sunshine" OR "Climate Extremes" OR "Weather Extremes") AND ("COVID" OR "Coronavirus disease 2019" OR "COVID-19" OR "SARS-CoV-2" OR "Novel Coronavirus") keywords. From 5229 articles, 424 were screened and 149 were selected for further analysis. The relationship between meteorological parameters is variable in different geographical locations. The results indicate that among the climatic indicators, the temperature is the most significant factor that influences on COVID-19 pandemic in most countries. Some studies were proved that warm and wet climates can decrease COVID-19 incidence; however, the other studies represented that warm location can be a high risk of COVID-19 incidence. It could be suggested that all climate variables such as temperature, humidity, rainfall, precipitation, solar radiation, ultraviolet index, and wind speed could cause spread of COVID-19. Thus, it is recommended that future studies will survey the role of all meteorological variables and interaction between them on COVID-19 spread in specific small areas such as cities of each country and comparison between them.

The association between wind speed and the risk of injuries among preschool children: New insight from a sentinel-surveillance-based study

BACKGROUND

Injuries among preschool children are an important public health concern worldwide. Significant gaps remain in understanding the potential impact of wind speed on injuries among preschoolers. We aimed to clarify the association and its variation across subgroups to capture the vulnerability features.

METHODS

Using a case-crossover design and conditional logistic regression model, we compared the exposure to wind speed right before the injury events (case period) with that of control periods to determine the excess rate (ER) of injury on each of 0-3 lag days in Guangzhou, 2016-2020. Results were also stratified by sociodemographic characteristics of patients, basic characteristics of injury events, and clinical features of injuries to identify the most vulnerable subgroups of preschoolers.

RESULTS

Higher wind speed was significantly associated with an increased risk of injuries among preschoolers on lag 0, reaching an ER of 2.93 % (95 % confidence interval [CI] = 0.87, 5.03), but not on other lag days. The results of the stratified analyses showed that children under 3-year-old (3.41 %; 95 % CI = 0.36, 6.55), boys (3.66 %; 95 % CI = 1.04, 6.35), and non-locally registered children (3.65; 95 % CI = 0.02, 7.40) were more prone to wind-related injuries. Falls (2.67 %; 95 % CI = 0.11, 5.30) were the main cause of wind-related injuries, and taking transportation was the main activity when injuries occurred (13.16 %; 95 % CI = 4.45, 22.60). Additionally, injuries involving buildings/grounds/obstacles (4.69 %; 95 % CI = 1.66, 7.81) and the occurrence of sprain/strain (7.60 %; 95 % CI = 0.64, 15.04) showed a positive association with wind speed.

CONCLUSIONS

Higher wind speed was associated with a significantly elevated rate of injuries among preschoolers without delayed effects, where children under 3-year-old, boys, and non-locally registered subgroups were more susceptible to wind-related injuries. This study may provide new insights for refining the prevention measures against wind-related injuries among preschoolers.

Is the virus-laden standing water change the transmission intensity of SARS-CoV-2 after precipitation? A framework for empirical studies

Understanding the relationship between precipitation and SARS-CoV-2 is significant for combating COVID-19 in the wet season. However, the causes for the variation of SARS-CoV-2 transmission intensity after precipitation is unclear. Starting from "the Zhengzhou event," we found that the virus-laden standing water formed after precipitation might trigger some additional routes for SARS-CoV-2 transmission and thus change the transmission intensity of SARS-CoV-2. Then, we developed an interdisciplinary framework to examine whether the health risk related to the virus-laden standing water needs to be a concern. The framework enables the comparison of the instant and lag effects of precipitation on the transmission intensity of SARS-CoV-2 between city clusters with different formation risks of the virus-laden standing water. Based on the city-level data of China between January 01, 2020, and December 31, 2021, we conducted an empirical study. The result showed that in the cities with a high formation risk of the virus-laden standing water, heavy rain increased the instant transmission intensity of SARS-CoV-2 by 6.2% (95%CI: 4.85-10.2%), while in the other cities, precipitation was uninfluential to SARS-CoV-2 transmission, revealing that the health risk of the virus-laden standing water should not be underestimated during the COVID-19 pandemic. To reduce the relevant risk, virus-laden water control and proper disinfection are feasible response strategies.

A review about COVID-19 in the MENA region: environmental concerns and machine learning applications

Coronavirus disease 2019 (COVID-19) has delayed global economic growth, which has affected the economic life globally. On the one hand, numerous elements in the environment impact the transmission of this new coronavirus. Every country in the Middle East and North Africa (MENA) area has a different population density, air quality and contaminants, and water- and land-related conditions, all of which influence coronavirus transmission. The World Health Organization (WHO) has advocated fast evaluations to guide policymakers with timely evidence to respond to the situation. This review makes four unique contributions. One, many data about the transmission of the new coronavirus in various sorts of settings to provide clear answers to the current dispute over the virus's transmission were reviewed. Two, highlight the most significant application of machine learning to forecast and diagnose severe acute respiratory syndrome coronavirus (SARS-CoV-2). Three, our insights provide timely and accurate information along with compelling suggestions and methodical directions for investigators. Four, the present study provides decision-makers and community leaders with information on the effectiveness of environmental controls for COVID-19 dissemination.

Spatio-Temporal Heterogeneity of the Relationships Between PM2.5 and Its Determinants: A Case Study of Chinese Cities in Winter of 2020

Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.

Combinatorial influence of environmental temperature, obesity and cholesterol on SARS-CoV-2 infectivity

The continuing evolution of SARS-CoV-2 variants not only causes a long-term global health concerns but also encounters the vaccine/drug effectiveness. The degree of virus infectivity and its clinical outcomes often depend on various biological parameters (e.g., age, genetic factors, diabetes, obesity and other ailments) of an individual along with multiple environmental factors (e.g., air temperature, humidity, seasons). Thus, despite the extensive search for and use of several vaccine/drug candidates, the combinative influence of these various extrinsic and intrinsic risk factors involved in the SARS-CoV-2 virus infectivity has yet to be explored. Previous studies have reported that environment temperature is negatively associated with virus infectivity for SARS-CoV-2. This study elaborates on our previous findings, investigating the link between environmental temperature and other metabolic parameters, such as average total cholesterol and obesity, with the increase in COVID-19 cases. Statistical analysis conducted on a per country basis not only supports the existence of a significant negative correlation between environmental temperature and SARS-CoV-2 infections but also found a strong positive correlation between COVID-19 cases and these metabolic parameters. In addition, a multiphase growth curve model (GCM) was built to predict the contribution of these covariates in SARS-CoV-2 infectivity. These findings, for first time, support the idea that there might be a combinatorial impact of environmental temperature, average total cholesterol, and obesity in the inflation of the SARS-CoV-2 infectivity.

Threshold dynamics of a stochastic SIHR epidemic model of COVID-19 with general population-size dependent contact rate

In this paper, we propose a stochastic SIHR epidemic model of COVID-19. A basic reproduction number $ R_{0}^{s} $ is defined to determine the extinction or persistence of the disease. If $ R_{0}^{s} < 1 $, the disease will be extinct. If $ R_{0}^{s} > 1 $, the disease will be strongly stochastically permanent. Based on realistic parameters of COVID-19, we numerically analyze the effect of key parameters such as transmission rate, confirmation rate and noise intensity on the dynamics of disease transmission and obtain sensitivity indices of some parameters on $ R_{0}^{s} $ by sensitivity analysis. It is found that: 1) The threshold level of deterministic model is overestimated in case of neglecting the effect of environmental noise; 2) The decrease of transmission rate and the increase of confirmed rate are beneficial to control the spread of COVID-19. Moreover, our sensitivity analysis indicates that the parameters $ \beta $, $ \sigma $ and $ \delta $ have significantly effects on $ R_0^s $.

Cold chain and severe acute respiratory syndrome coronavirus 2 transmission: a review for challenges and coping strategies

Since June 2020, the re-emergence of coronavirus disease 2019 (COVID-19) epidemics in parts of China was linked to the cold chain, which attracted extensive attention and heated discussions from the public. According to the typical characteristics of these epidemics, we speculated a possible route of transmission from cold chain to human. A series of factors in the supply chain contributed to the epidemics if the cold chain were contaminated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), such as temperature, humidity, personal hygiene/protection, and disinfection. The workers who worked in the cold chain at the receiving end faced a higher risk of being infected when they were not well protected. Facing the difficult situation, China put forward targeted and powerful countermeasures to block the cold chain-related risk. However, in the context of the unstable pandemic situation globally, the risk of the cold chain needs to be recognized and evaluated seriously. Hence, in this review, we reviewed the cold chain-related epidemics in China, analyzed the possible mechanisms, introduced the Chinese experience, and suggested coping strategies for the global epidemic prevention and control.

SARS-CoV-2 detection in bioaerosols using a liquid impinger collector and ddPCR

The airborne route is the dominant form of COVID-19 transmission, and therefore, the development of methodologies to quantify SARS-CoV-2 in bioaerosols is needed. We aimed to identify SARS-CoV-2 in bioaerosols by using a highly efficient sampler for the collection of 1-3 µm particles, followed by a highly sensitive detection method. 65 bioaerosol samples were collected in hospital rooms in the presence of a COVID-19 patient using a liquid impinger sampler. The SARS-CoV-2 genome was detected by ddPCR using different primer/probe sets. 44.6% of the samples resulted positive for SARS-CoV-2 following this protocol. By increasing the sampled air volume from 339 to 650 L, the percentage of positive samples went from 41% to 50%. We detected five times less positives with a commercial one-step RT-PCR assay. However, the selection of primer/probe sets might be one of the most determining factor for bioaerosol SARS-CoV-2 detection since with the ORF1ab set more than 40% of the samples were positive, compared to <10% with other sets. In conclusion, the use of a liquid impinger collector and ddPCR is an adequate strategy to detect SARS-CoV-2 in bioaerosols. However, there are still some methodological aspects that must be adjusted to optimize and standardize a definitive protocol.

Meteorological parameters and cases of COVID-19 in Brazilian cities: an observational study

Meteorological parameters modulate transmission of the SARS-Cov-2 virus, the causative agent related to coronavirus disease-2019 (COVID-19) development. However, findings across the globe have been inconsistent attributed to several confounding factors. The aim of the present study was to investigate the relationship between reported meteorological parameters from July 1 to October 31, 2020, and the number of confirmed COVID-19 cases in 4 Brazilian cities: São Paulo, the largest city with the highest number of cases in Brazil, and the cities with greater number of cases in the state of Parana during the study period (Curitiba, Londrina and Maringa). The assessment of meteorological factors with confirmed COVID-19 cases included atmospheric pressure, temperature, relative humidity, wind speed, solar irradiation, sunlight, dew point temperature, and total precipitation. The 7- and 15-day moving averages of confirmed COVID-19 cases were obtained for each city. Pearson's correlation coefficients showed significant correlations between COVID-19 cases and all meteorological parameters, except for total precipitation, with the strongest correlation with maximum wind speed (0.717, <0.001) in São Paulo. Regression tree analysis demonstrated that the largest number of confirmed COVID-19 cases was associated with wind speed (between ≥0.3381 and <1.173 m/s), atmospheric pressure (<930.5mb), and solar radiation (<17.98e⁺³). Lower number of cases was observed for wind speed <0.3381 m/s and temperature <23.86°C. Our results encourage the use of meteorological information as a critical component in future risk assessment models.

Ambient high temperature exposure and global disease burden during 1990-2019: An analysis of the Global Burden of Disease Study 2019

BACKGROUND

A warming climate throughout the 21st century makes ambient high temperature exposure a major threat to population health worldwide. Mitigating the health impact of high temperature requires a timely, comprehensive and reliable assessment of disease burden globally, regionally and temporally.

AIM

Based on Global Burden of Disease (GBD) Study 2019, this study aimed to evaluate the disease burden attributable to high temperature from various epidemiology perspectives.

METHODS

A three-stage analysis was undertaken to investigate the number and age-standardized rates of death and disability-adjusted life years (DALY) attributable to high temperature from GBD Study 2019. First, we reported the high temperature-related disease burden for the whole world and for different groups by gender, age, region, country and disease. Second, we examined the temporal trend of the disease burden attributable to high temperature from 1990 to 2019. Finally, we explored if and how the high temperature-related disease burden was modified by a number of country-level indicators.

RESULTS

Globally, high temperature accounted for 0.54% of death and 0.46% of DALY in 2019, equating to the age-standardized rates of death and DALY (per 100,000 population) of 3.99 (95% uncertainty interval (UI): 2.88, 5.93) and 156.81 (95% UI: 107.98, 261.98), respectively. In 2019, the high temperature-related DALY and death rates were the highest for lower respiratory infections, although they showed a downward trend. In contrast, during 1990-2019, high temperature-related non-communicable diseases burden exhibited an upward trend. Meanwhile, the disease burden attributable to high temperature varied spatially, with the heaviest burden in regions with low sociodemographic index (SDI) and the lightest burden in regions with high SDI. In addition, high temperature-related disease burden appeared to be higher in a country with a higher population density and PM_2.5 concentration background but lower in a country with a higher density of greenness.

CONCLUSION

This study for the first time provided a comprehensive understanding of the global disease burden attributable to high temperature, underscoring the policy priority to protect human health worldwide in the context of global warming with particular attention to vulnerable countries or regions as well as susceptible population and diseases.

Guidance plans for solid waste management during COVID-19 in Makkah, Saudi Arabia

The COVID-19 pandemic has emphasized disasters related to environmental topics, human health, social lifestyles, and economic systems around the world. COVID-19 may further spread through municipal solid waste (MSW), if it is collected, handled, transported, or disposed in an improper way. The current paper provides an overview of the multiple challenges that COVID-19 has introduced to the various tasks of MSW management including the impact of the implemented precautionary measures on MSW management, priorities and hierarchy of MSW, direct impact on the constitution, and characterization of MSW in Makkah, Saudi Arabia, based on waste management characterization guidance. In addition, specific and alternative guidance plans for the potential critical points of the infection were suggested to protect public health during the pandemic. The results of the current study revealed that the hierarchical system of MSW was modified under pandemic conditions. Implementation of control measures in Makkah has led to a change of lifestyle, which resulted in a physical change of the MSW constitution in Makkah, with the following average rates: organic matter, 57%; plastics, 31%; paper and cardboard, 9%; metals, 1%; glass, 1%; and wood, 1%. In conclusion, a specific guidance plan for MSW management during the COVID-19 pandemic was developed, aimed at handlers, pickers, collection, transportation, transfer stations, and MSW disposal. Such a guidance plan may play a vital role in controlling the pandemic, especially in the outdoor environment. The suggested guidance plan describes and specifies structured and ordered practices of MSW management in Makkah during COVID-19 and other pandemics.