ABSTRACT
The analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) gene copy numbers in wastewater samples can provide quantitative information on Coronavirus Disease-19 (COVID-19) cases within a sewer catchment. However, many wastewater-based epidemiology (WBE) studies have neglected virus decay during the wastewater transportation process in sewers while back-calculating COVID-19 prevalence. Among various sewer condition parameters, wastewater temperature and dilution by fresh/saltwater infiltration may result in a significant change to the virus decay, in terms of both infectivity and Ribonucleic Acid (RNA). This paper reviewed the literature to identify and discuss the effects of temperature and water types (i.e., wastewater, freshwater, and seawater) on coronavirus decay based on the decay rate constants that were collected from published papers. To evaluate the importance of virus decay, a sensitivity analysis was then conducted with decay rates of SARS-CoV-2 RNA based on a WBE back-calculation equation. Finally, the decay rates of coronavirus in wastewater were also compared with those of other viruses to further understand the difference among virus species. The decay of SARS-CoV-2 RNA was found to be less impacted by temperature variation than viable coronaviruses. Nevertheless, WBE back-calculation was still sensitive to the RNA decay rates increased by warm wastewater (i.e., over 26 °C), which could lead to a two-times higher relative variance in estimated COVID-19 prevalence, considering the wastewater temperature variation between 4 and 37 °C in a sewer catchment with a 12-h hydraulic retention time. Comparatively, the sensitivity of the WBE estimation to the enveloped SARS-CoV-2 was greater than nonenveloped enteric viruses, which were less easily degradable in wastewater. In addition, wastewater dilution by stormwater inflow and accompanied cold weather might alleviate the decay of coronavirus infectivity, thus increasing the potential risk of COVID-19 transmission through wastewater. Overall, this paper aims to better understand the impact of in-sewer processes on coronavirus decay and its potential implications for WBE. The outcome could quantitatively inform WBE and improve awareness of the increased risk of COVID-19 infection via wastewater during heavy rainfall events. Given the identified scarcity of data available for coronavirus decay in salt water or with chemical additions, future research on the fate of SARS-CoV-2 subjected to chemical dosing for sewer or wastewater treatment plant operations is recommended. © 2023 by the authors.
ABSTRACT
Environmental conditions and their association with COVID-19 have significantly attracted scientists' attention. The current study links COVID-19 with climate indicators by comparing two configurations: indoor infections in a University of Duhok (UOD) building and outdoor infections within the boundaries of the Duhok Governorate (DG). The collected data included temperature and relative humidity (RH) and confirmed cases for indoor and outdoor configurations over 5 and 11 months, respectively. For the indoor infections, data were collected over the period of 5 weekdays, while for the outdoor infections, they were collected on the days when statistics were published. The prospective cross-section design was used for different statistical analyses. The overall indoor infections were very low, and the maximum values for RH and temperature were approximately <24% and <20°C, respectively;in the one-sample t-test, the results were significantly correlated (p value <0.05) with the confirmed COVID-19 cases. For outdoor infections, using the correlation bivariate method, the study found that the RH and temperature results significantly correlated (p value <0.05) with the confirmed COVID-19 cases. However, for indoor configuration, other than for Tmax, the results were not associated. As for the outdoor infections, the RH and temperature averages were high enough to put in groups to employ the one-way repeated ANOVA and general linear model with the same results. The means of the RHlow, RHmedium, and RHh groups were significantly correlated (p value <0.05) with COVID-19. However, the means of the medium RH and high RH groups were not significantly associated with the increasing outdoor infections. This study will contribute to the reduction of overall COVID-19 infections. [ FROM AUTHOR] Copyright of Advances in Meteorology is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
COVID-19 remains a matter of global public health concern. Previous research suggested the association between local environmental factors and viral transmission. We present a multivariate observational analysis of SARS-CoV-2 transmission in the state of Odisha, India, hinting at a seasonal activity. We aim to investigate the demographic characteristics of COVID-19 in the Indian state of Odisha for two specific timelines in 2020 and 2021. For a comparative outlook, we chose similar datasets from the state of New York, USA. Further, we present a critical analysis pertaining to the effects of environmental factors and the emergence of variants on SARS-CoV-2 transmission and persistence. We assessed the datasets for confirmed cases, death, age, and gender for 29 February 2020 to 31 May 2020, and 1 March 2021 to 31 May 2021. We determined the case fatalities, crude death rates, sex ratio, and incidence rates for both states along with monthly average temperature analysis. A yearlong epi-curve analysis was conducted to depict the coronavirus infection spread pattern in the respective states. The Indian state of Odisha reported a massive 436,455 confirmed cases and 875 deaths during the 2021 timeline as compared to a mere 2223 cases and 7 deaths during the 2020 timeline. We further discuss the demographic and temperature association of SARS-CoV-2 transmission during early 2020 and additionally comment on the variant-associated massive rise in cases during 2021. Along with the rapid rise of variants, the high population density and population behavior seem to be leading causes for the 2021 pandemic, whereas factors such as age group, gender, and average local temperature were prominent during the 2020 spread. A seasonal occurrence of SARS-CoV-2 transmission is also observed from the yearlong epidemiological plot. The recent second wave of COVID-19 is a lesson that emphasizes the significance of continuous epidemiological surveillance to predict the relative risk of viral transmission for a specific region.
Subject(s)
COVID-19 , SARS-CoV-2 , Data Analysis , Humans , India/epidemiology , PandemicsABSTRACT
The current statistical modeling of coronavirus (COVID-19) spread has mainly focused on spreading patterns and forecasting of COVID-19 development; these patterns have been found to vary among locations. As the survival time of coronaviruses on surfaces depends on temperature, some researchers have explored the association of daily confirmed cases with environmental factors. Furthermore, some researchers have studied the link between daily fatality rates with regional factors such as health resources, but found no significant factors. As the spreading patterns of COVID-19 development vary a lot among locations, fitting regression models of daily confirmed cases or fatality rates directly with regional factors might not reveal important relationships. In this study, we investigate the link between regional spreading patterns of COVID-19 development in Italy and regional factors in two steps. First, we characterize regional spreading patterns of COVID-19 daily confirmed cases by a special patterned Poisson regression model for longitudinal count; the varying growth and declining patterns as well as turning points among regions in Italy have been well captured by regional regression parameters. We then associate these regional regression parameters with regional factors. The effects of regional factors on spreading patterns of COVID-19 daily confirmed cases have been effectively evaluated.
Subject(s)
COVID-19 , Forecasting , Humans , Italy/epidemiology , Models, Statistical , SARS-CoV-2ABSTRACT
COVID-19 is an epidemic virus arising from a freshly discovered coronavirus. Most people involved with the coronavirus will experience slight to moderate respiratory disease and recover without needing particular therapy. In this work, the atomic stability of the coronavirus at different thermodynamic properties such as temperature and pressure, was studied. For this purpose, the manner of this virus by atomic precession was described with a molecular dynamics approach. For the atomic stability of coronavirus description, physical properties such as temperature, total energy, volume variation, and atomic force of this structure were reported. In molecular dynamics approach, coronavirus is precisely simulated via S, O, N, and C atoms and performed Dreiding force field to describe these atoms interaction in the virus. Simulation results show that coronavirus stability has reciprocal relation with atomic temperature and pressure. Numerically, after 2.5 ns simulation, the potential energy varies from - 31,163 to - 26,041 eV by temperature changes from 300 to 400 K. Furthermore, this physical parameter decreases to - 28,045 eV rate at 300 K and 2 bar pressure. The volume of coronavirus is another crucial parameter to the stability description of this structure. The simulation shows that coronavirus volume 92% and 14% increases by 100 K and 2 bar variation of simulation temperature and pressure, respectively.