Introduction to the special issue ''Environmental impacts of COVID-19 pandemic"

Environmental, meteorological and pandemic restriction-related variables affecting SARS-CoV-2 cases

Three years have passed since the outbreak of Coronavirus Disease 2019 (COVID-19) brought the world to standstill. In most countries, the restrictions have ended, and the immunity of the population has increased; however, the possibility of new dangerous variants emerging remains. Therefore, it is crucial to develop tools to study and forecast the dynamics of future pandemics. In this study, a generalized additive model (GAM) was developed to evaluate the impact of meteorological and environmental variables, along with pandemic-related restrictions, on the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Córdoba, Argentina. The results revealed that mean temperature and vegetation cover were the most significant predictors affecting SARS-CoV-2 cases, followed by government restriction phases, days of the week, and hours of sunlight. Although fine particulate matter (PM2.5) and NO2 were less related, they improved the model's predictive power, and a 1-day lag enhanced accuracy metrics. The models exhibited strong adjusted coefficients of determination (R2adj) but did not perform as well in terms of root-mean-square error (RMSE). This suggests that the number of cases may not be the primary variable for controlling the spread of the disease. Furthermore, the increase in positive cases related to policy interventions may indicate the presence of lockdown fatigue. This study highlights the potential of data science as a management tool for identifying crucial variables that influence epidemiological patterns and can be monitored to prevent an overload in the healthcare system.

Role of air pollution on seasonal distribution of Covid-19: a case study in the west of Iran

The seasonal distribution of SARS-CoV-2 might be affected by air pollution. To test the hypothesis, epidemic determinants, namely, shape, timing (Peak and Trough) and size (Peak to Trough Ratio and Excess Risk) of seasonal distribution of the outbreak were compared before and after adjusting for air pollutants in a distributed lag nonlinear model. We controlled for one-lagged outcome and meteorological parameters in the model. We also evaluated interaction effect between air pollutants and season using stratification method. The epidemic determinants were changed after adjusting for PM2.5 and O3 in the model, suggesting the existence of their association with the seasonal distribution of the outbreak. The Excess Risk of season (i.e., the proportion of confirmed Covid-19 cases that were attributed to season; AF) was increased as %4 (%95 CI  - 29, 38) after adjusting for PM2.5. Adjusting for O3 in the model resulted in % 1 (%95 CI  - 36, 34) decrease in the index. NO, NO2 and SO2 had no association with the seasonal distribution, though the interaction analysis revealed that association of NO2 and SO2 with Covid-19 confirmed cases were significantly higher in fall than winter and spring, respectively. Totally, PM2.5 has negatively associated with the seasonal distribution of the outbreak while O3 has positively associated in the region under study. Although some reasons such as wearing mask and oxidative effect might go before the negative and positive associations, but our results suggests that any association and causation between air pollution and Covid-19 should be carefully interpreted.

Air pollution in Iran: The current status and potential solutions

Air pollution has been integrated into global challenges over the last few years due to its negative impact on the health of human beings, increasing socio-economic risks, and its contribution to climate change. This study attempts to evaluate the current status of Iran's air pollution with regard to the sources of emissions, control policies, and the health and climate consequences that have resulted through available data from monitoring stations reported in the literature, official documents, and previously published papers. Many large cities in Iran surpass the permissible concentration of air pollutants, particularly particulate matter, sulfur dioxide, black carbon, and ozone. Although regulations and policies are in place and enormous efforts are being made to address air pollution issues in the country, implementation and enforcement are not as effective as they could be. The significant challenges may be regarded as the inefficiency of regulation and supervision systems, the lack of air quality monitoring systems and technology, particularly in industrial cities rather than Tehran, and the lack of continual feedback and investigations on the efficiency of regulation. Providing such an up-to-date report can bring opportunities for international collaboration, which is essential in addressing air pollution worldwide. We suggest that a way forward could be more focused on conducting systematic reviews using scientometric methods to show an accurate picture and trend in air pollution and its association in Iran, implementing an integrated approach for both climate change and air pollution issues, collaborating with international counterparts to share knowledge, tools, and techniques.

JP, I. TMB, Packiavathy SV, Gautam S. Internet of Things (IoT) based automated sanitizer dispenser and COVID-19 statistics reporter in a post-pandemic world

Purpose

Coronavirus is among the deadliest viruses of the 21st century. There is still a Coronavirus epidemic that affects most countries worldwide today. To prevent future outbreaks and protect public health, it is essential to invest in research and innovation on vaccines, treatments, diagnostic tests, public health infrastructure, and emergency response planning. Additionally, we need to work on mitigation strategies and take a comprehensive and multidisciplinary approach to prevent and fight against the virus.

Methods

For the purpose of preventing the spread of microbial organisms, it is essential to take advantage of automatic sanitizer dispensers by deploying them in public places. This is one of the most feasible and effective ways to ensure that people have easy access to hand sanitizer and can reduce the spread of germs.

Results

The proposed solution is a contactless sanitizer dispenser with an integrated temperature monitoring system, as well as an alert system for users who exhibit the symptom of infection. Moreover, the proposed solution has added advantage of interfacing with an electronic door so that we can easily implement it at the entrance of a public building/public transportation. This dispenser will also collect data that can be used to identify a symptomatic user and alert the appropriate authorities for safe quarantine. In addition, it is also used to monitor usage metrics, record user entries, and conduct statistical surveys using the ThinkSpeak platform.

Conclusions

The proposed model could be a feasible solution to prevent the entry of infected persons and asymptomatic carriers indoors. This can be achieved by implementing automated temperature screening before allowing entry into the building. This can help identify individuals who are potentially infected with the virus and prevent them from entering the premises and potentially spreading the disease to others. Overall, the proposed model is a comprehensive and practical solution that can help to prevent the entry of infected persons and asymptomatic carriers indoors and help to keep the public safe.