Impact of hydrological factors on the dynamic of COVID-19 epidemic: A multi-region study in China

Natural and socio-environmental factors in the transmission of COVID-19: a comprehensive analysis of epidemiology and mechanisms

PURPOSE OF REVIEW

There are significant differences in the transmission rate and mortality rate of COVID-19 under environmental conditions such as seasons and climates. However, the impact of environmental factors on the role of the COVID-19 pandemic and the transmission mechanism of the SARS-CoV-2 is unclear. Therefore, a comprehensive understanding of the impact of environmental factors on COVID-19 can provide innovative insights for global epidemic prevention and control policies and COVID-19 related research. This review summarizes the evidence of the impact of different natural and social environmental factors on the transmission of COVID-19 through a comprehensive analysis of epidemiology and mechanism research. This will provide innovative inspiration for global epidemic prevention and control policies and provide reference for similar infectious diseases that may emerge in the future.

RECENT FINDINGS

Evidence reveals mechanisms by which natural environmental factors influence the transmission of COVID-19, including (i) virus survival and transport, (ii) immune system damage, (iii) inflammation, oxidative stress, and cell death, and (iiii) increasing risk of complications. All of these measures appear to be effective in controlling the spread or mortality of COVID-19: (1) reducing air pollution levels, (2) rational use of ozone disinfection and medical ozone therapy, (3) rational exposure to sunlight, (4) scientific ventilation and maintenance of indoor temperature and humidity, (5) control of population density, and (6) control of population movement. Our review indicates that with the continuous mutation of SARS-CoV-2, high temperature, high humidity, low air pollution levels, and low population density more likely to slow down the spread of the virus.

Investigation of SARS-CoV-2 RNA contamination in water supply resources of Tabriz metropolitan during a peak of COVID-19 pandemic

It is crucial to have access to clean water resources during the COVID-19 pandemic for hygiene, since virus infection through wastewater leaks in metropolitan areas can be a threat. Accurate monitoring of urban water resources during the pandemic seems to be the only way to confirm safe and infected resources. Here, in this study, the amount of Severe Acute Respiratory Syndrome Coronavirus 2's Ribonucleic Acid (SARS-CoV-2 RNA) in the Tabriz urban water network located in the northwest of Iran was investigated by an extensive sampling of the city's water sources at a severe peak of the COVID-19 pandemic. The sampling process comprised a range of water sources, including wells, qanats, water treatment facilities, dams, and reservoirs. For each sample, a combination of polyethylene glycol (PEG) and sodium chloride (NaCl) was used for concentration and a laboratory RNA-based method was conducted for quantification. Before applying the extraction and quantification procedure to real samples, the proposed concentration method was verified with synthetic serum samples for the first time. After the concentration, RNA extraction was done by the BehPrep extraction column method, and Reverse Transcription Polymerase Chain Reaction (RT-PCR) detection of the virus was done by Covitech COVID-19 RT-PCR kit. In none of the water supply resources, SARS-COV-2 RNA has been detected except in a sample grabbed from a well adjacent to an urban wastewater discharge point downstream. The results of molecular analysis for the positive sample showed that the CT value and concentration of the virus genome were equal to 32.57 and 5720 copies/L, respectively. Quantitative analysis of real samples shows that the city's water network was safe at the time of the study. However, given that the positive sample was exposed to wastewater leakage, periodic sampling from wells and qanats is suggested during the pandemic until it can be proven that the leakage to these water sources is impossible.

A comparison of COVID-19 outbreaks across US Combined Statistical Areas using new methods for estimating R0 and social distancing behaviour

We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulation Analysis (NMB-DASA) web application to fit the exponential phase of a SCLAIV+D (Susceptible, Contact, Latent, Asymptomatic infectious, symptomatic Infectious, Vaccinated, Dead) disease classes model to outbreaks, thereby allowing us to obtain an estimate of the basic reproductive number R₀ for each CSA. Values of R₀ ranged from 1.9 to 9.4, with a mean and standard deviation of 4.5±1.8. Fixing the parameters from the exponential fit, we again used NMB-DASA to estimate a set of social distancing behaviour parameters to compute an epidemic flattening index c_flatten. Finally, we applied hierarchical clustering methods using this index to divide CSA outbreaks into two clusters: those presenting a social distancing response that was either weaker or stronger. We found c_flatten to be more influential in the clustering process than R₀. Thus, our results suggest that the behavioural response after a short initial exponential growth phase is likely to be more determinative of the rise of an epidemic than R₀ itself.

Modeling the relationship between SARS-CoV-2 RNA in wastewater or sludge and COVID-19 cases in three New England regions

BACKGROUND

We aimed to compare statistical techniques estimating the association between SARS-CoV-2 RNA in untreated wastewater and sludge and reported coronavirus disease 2019 (COVID-19) cases.

METHODS

SARS-CoV-2 RNA concentrations (copies/mL) were measured from 24-h composite samples of wastewater in Massachusetts (MA) (daily; 8/19/2020-1/19/2021) and Maine (ME) (weekly; 9/1/2020-3/2/2021) and sludge samples in Connecticut (CT) (daily; 3/1/2020-6/1/2020). We fit linear, generalized additive with a cubic regression spline (GAM), Poisson, and negative binomial models to estimate the association between SARS-CoV-2 RNA concentration and reported COVID-19 cases.

RESULTS

The models that fit the data best were linear [adjusted R²=0.85 (MA), 0.16 (CT), 0.63 (ME); root-mean-square error (RMSE)=0.41 (MA), 1.14 (CT), 0.99 (ME)), GAM (adjusted R²=0.86 (MA), 0.16 (CT) 0.65 (ME); RMSE=0.39 (MA), 1.14 (CT), 0.97 (ME)], and Poisson [pseudo R²=0.84 (MA), 0.21 (CT), 0.52 (ME); RMSE=0.39 (MA), 0.67 (CT), 0.79 (ME)].

CONCLUSIONS

Linear, GAM, and Poisson models outperformed negative binomial models when relating SARS-CoV-2 RNA in wastewater or sludge to reported COVID-19 cases.

Feasibility analysis on the construction of a web solution for hydrometeorological forecasting considering water body management and indicators for the SARS-COV-2 pandemic

The current scenario of a global pandemic caused by the virus SARS-CoV-2 (COVID19), highlights the importance of water studies in sewage systems. In Brazil, about 35 million Brazilians still do not have treated water and more than 100 million do not have basic sanitation. These people, already exposed to a range of diseases, are among the most vulnerable to COVID-19. According to studies, places that have poor sanitation allow the proliferation of the coronavirus, been observed a greater number of infected people being found in these regions. This social problem is strongly related to the lack of effective management of water resources, since they are the sources for the population's water supply and the recipients of effluents stemming from sanitation services (household effluents, urban drainage and solid waste). In this context, studies are needed to develop technologies and methodologies to improve the management of water resources. The application of tools such as artificial intelligence and hydrometeorological models are emerging as a promising alternative to meet the world's needs in water resources planning, assessment of environmental impacts on a region's hydrology, risk prediction and mitigation. The main model of this type, WRF-Hydro Weather Research and Forecasting Model), represents the state of the art regarding water resources, as well as being the object of study of small and medium-sized river basins that tend to have less water availability. hydrometeorological data and analysis. Thus, this article aims to analyze the feasibility of a web tool for greater software usability and computational cost use, making it possible to use the WRF-Hydro model integrated with Artificial Intelligence tools for short and medium term, optimizing the time of simulations with reduced computational cost, so that it is able to monitor and generate a predictive analysis of water bodies in the MATOPIBA region (Maranhão-Tocantins-Piauí-Bahia), constituting an instrument for water resources management. The results obtained show that the WRF-Hydro model proves to be an efficient computational tool in hydrometeorological simulation, with great potential for operational, research and technological development purposes, being considered viable to implement the web tool for analysis and management of water resources and consequently, assist in monitoring and mitigating the number of cases related to the current COVID-19 pandemic. This research are in development and represents a preliminary results with future perspectives.

Impacts of COVID-19 on the Aquatic Environment and Implications on Aquatic Food Production

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in ecological changes of aquatic ecosystems, affected the aquatic food supply chain, and disrupted the socio-economy of global populations. Due to reduced human activities during the pandemic, the aquatic environment was reported to improve its water quality, wild fishery stocks, and biodiversity. However, the sudden surge of plastics and biomedical wastes during the COVID-19 pandemic masked the positive impacts and increased the risks of aquatic pollution, especially microplastics, pharmaceuticals, and disinfectants. The transmission of SARS-CoV-2 from wastewater treatment plants to natural water bodies could have serious impacts on the environment and human health, especially in developing countries with poor waste treatment facilities. The presence and persistence of SARS-CoV-2 in human excreta, wastewaters, and sludge and its transmission to aquatic ecosystems could have negative impacts on fisheries and aquaculture industries, which have direct implications on food safety and security. COVID-19 pandemic-related environmental pollution showed a high risk to aquatic food security and human health. This paper reviews the impacts of COVID-19, both positive and negative, and assesses the causes and consequences of anthropogenic activities that can be managed through effective regulation and management of eco-resources for the revival of biodiversity, ecosystem health, and sustainable aquatic food production.

Meteorological factors, governmental responses and COVID-19: Evidence from four European countries

With the global lockdown, meteorological factors are highly discussed for COVID-19 transmission. In this study, national-specific and region-specific data sets from Germany, Italy, Spain and the United Kingdom were used to explore the effect of temperature, absolute humidity and diurnal temperature range (DTR) on COVID-19 transmission. From February 1st to November 1st, a 7-day COVID-19 case doubling time (Td), meteorological factors with cumulative 14-day-lagged, government response index and other factors were fitted in the distributed lag nonlinear models. The overall relative risk (RR) of the 10th and the 25th percentiles temperature compared to the median were 0.0074 (95% CI: 0.0023, 0.0237) and 0.1220 (95% CI: 0.0667, 0.2232), respectively. The pooled RR of lower (10th, 25th) and extremely high (90th) absolute humidity were 0.3266 (95% CI: 0.1379, 0.7734), 0.6018 (95% CI: 0.4693, 0.7718) and 0.3438 (95% CI: 0.2254, 0.5242), respectively. While the DTR did not have a significant effect on Td. The total cumulative effect of temperature (10th) and absolute humidity (10th, 90th) on Td increased with the change of lag days. Similarly, a decline in temperature and absolute humidity at cumulative 14-day-lagged corresponded to the lower RR on Td in pooled region-specific effects. In summary, the government responses are important factors in alleviating the spread of COVID-19. After controlling that, our results indicate that both the cold and the dry environment also likely facilitate the COVID-19 transmission.