In this paper, we describe a simple concentration method based on polyethylene glycol (PEG) precipitation, followed by RNA extraction and a one-step quantitative reverse transcription PCR (qRT-PCR) for viral detection in wastewater. However, the detection of viruses in sewage is challenging and to date there is no standard method available which has been validated for the sensitive detection of SARS-CoV-2. Wastewater-based epidemiology has become an important tool for the surveillance of SARS-CoV-2 outbreaks. The month of July showed the highest daily COVID-19 cases prior to lowering at steady rate till September illustrating the influnce of meteorological parameters. ARIMA model portrayed predictive trend of COVID-19 transmission, from its inception on 8 March 2020 to September 2020, in Bangladesh. Furthermore, both the rainfall and wind speed exhibit positive correlations. A greater number of significant positive associations (r = 0.24–0.58) is found to exist between the relative humidity and COVID-19 cases across the cities, while with temperature both positive and negative associations (r = − 0.23 to 0.72) were revealed. The basic statistical analyses and auto regressive integrated moving average (ARIMA) using SPSS tool were applied to evaluate and explore associationīetween meteorological parameters and COVID-19 cases and its transmission trend. The number of COVID-19 cases, daily records of rainfall, temperature, relative humidity and wind speed data were collected for April and May 2020 from the eight major divisions in Bangladesh. This study aims to explore the association between COVID-19 cases and meteorological parameters and to predict COVID-19 transmission for an extended period covering different climatic patterns. Understanding the influence of meteorological parameters in relation to COVID-19 transmission may be a convenient way to predict the ongoing pandemic towards its adaptive control measures. This is the first study in Botswana to highlight the occurrence and quantification of the enteric viruses in treated and untreated wastewater, as well as surface water. There was no significant association between physicochemical parameters and viral loads, except for pH which showed significant relationship with rotavirus and norovirus GII (p ≤ 0.05). The enteric viruses were detected in all the study sites with highest detection from site S1 (inlet). Detected viral loads went up to 10⁴ genome copies per liter (copies/L) for all the viruses. Rotavirus A was the most prevalent (84.4% positive samples), followed by Norovirus GI (48.9% positive samples), and Norovirus GII 46.7% positive samples). Virus detection was performed using real-time polymerase chain reaction (RT-PCR). Viruses were concentrated using polyethylene glycol/NaCl precipitation. A total of 45 samples of raw and treated sewage, and surface water, were collected from a sludge activated wastewater treatment plant in Gaborone, and after treatment from the Notwane River, Botswana, over a period of 9 months (February 2016 to October 2016). This study was done to ascertain and establish the viral load, the temporal and spatial distribution of rotavirus A and norovirus (GI and GII) in sewage and river water samples. Water testing mainly uses bacterial indicators to assess water quality, which may not fully indicate the threat from other non-bacterial pathogens like enteric viruses. Waterborne diseases remain a public health concern in developing countries where many lack access to safe water.
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