Internal student migration in India: Impact of the COVID-19 crisis

The education sector in India was among the most affected sectors during the COVID-19 pandemic. While considerable attention has been paid to informal workers' return or reverse migration to their home communities, not much has been reported about the challenges faced by migrant students. Using a mixed-method approach, the current study presents an overview of internal student migration in India prior to the COVID-19 pandemic using data from the 2001 and 2011 Census of India and the 2007–2008 National Sample Survey Organization, and discusses challenges faced by selected migrant learners during the COVID-19 pandemic based on primary research. Based on the census data, nearly 3.3 million migrants in India move for study reasons with 2.9 million migrating within the state (with the duration of residence less than five years) from their last residence within India. The pattern of female student migration suggests an increasingly localized interdistrict migration. Findings from the qualitative data indicate that during the pandemic, students had compromised learning and placement experience, inadequate digital resources and pressure to repay loans. Student migrants experienced varying degrees of the impact of the COVID-19 pandemic based on their destination and migration stream.

SARS-CoV-2 infection dynamics and genomic surveillance to detect variants in wastewater - a longitudinal study in Bengaluru, India.

Background: Environmental surveillance (ES) of a pathogen is crucial for understanding the community load of disease. As an early warning system, ES for SARS-CoV-2 has complemented routine diagnostic surveillance by capturing near real-time virus circulation at a population level. Methods: In this longitudinal study conducted between January 2022 and June 2022 in 28 sewershed sites in Bengaluru city (∼11 million inhabitants), we quantified weekly SARS-CoV-2 RNA concentrations to track infection dynamics and provide evidence of change in the relative abundance of emerging variants. Findings: We describe an early warning system using the exponentially weighted moving average control chart and demonstrate how SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 8-14 days earlier in wastewater than in clinical data. This was further corroborated by showing that the estimated number of infections is strongly correlated with SARS-CoV-2 RNA copies detected in the wastewater. Using a deconvolution matrix, we detected emerging variants of concern up to two months earlier in wastewater samples. In addition, we found a huge diversity in variants detected in wastewater compared to clinical samples. The findings from this study have been discussed regularly with local authorities to inform policy-making decisions. Interpretation: Our study highlights that quantifying viral titre, correlating it with a known number of cases in the area, and combined with genomic surveillance helps in tracking variants of concern (VOC) over time and space, enabling timely and making informed policy decisions. Funding: This work has been supported by funding from the Rockefeller Foundation grant to National Centre for Biological Sciences, TIFR) and the Indian Council of Medical Research grant to (FI) Tata Institute for Genetics and Society and Tata Trusts.

Body-mass index COVID-19 severity: A systematic review of systematic reviews.

Objectives: Conflicting studies have resulted in several systematic reviews and meta-analyses on the relationship between COVID-19 and body mass index (BMI). Methods: This systematic review of systematic reviews followed an umbrella review design, and preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines; Medical literature analysis and retrieval system online (MEDLINE) and SCOPUS databases were searched for systematic reviews on the topic. A predefined screening and selection procedure was done for the retrieved results based on the population, intervention/interest, comparator, outcome, study (PICOS) framework. Results: The search strategy yielded 6334 citations. With the predefined selection and screening process, 23 systematic reviews were retrieved for inclusion in the present study. Twenty-three (n = 23) systematic reviews met the inclusion criteria. As expected, there was overlap across the reviews in the included primary studies. Available evidence suggests that Class III obesity (morbid obesity) is strongly associated with increased mortality risk in patients with Covid-19. It is difficult to draw a firm conclusion about Class I and Class II obesity due to conflicting outcomes of metanalyses. Increased obesity was consistently associated with increased risk of invasive mechanical ventilation (IMV) in all the reviews with low to moderate heterogeneity. Conclusions: Available evidence suggests that Class III obesity (morbid obesity) is strongly associated with increased mortality risk in patients with Covid-19. Increased BMI is positively associated with the risk of IMV and the severity of COVID- care.

Surveillance of SARS-CoV-2 genome fragment in urban, peri-urban and rural water bodies: a temporal and comparative analysis

As a result of the SARS-CoV-2 pandemic, water bodies connected to anthropogenic activities may likely reveal the presence of viral genetic material. Urban, periurban and rural water bodies in and around Hyderabad, Telangana, India, were monitored for the presence of SARS-CoV-2 gene fragments during the first and second wave of COVID-19 infection. The SARS-CoV-2 genes were not detected in peri-urban and rural lakes, whereas urban lakes having direct functional attributes from domestic activity showed prevalence. Distinct variability in viral load observed among five water bodies was in concordance with human activity in the catchment area. High viral load was observed during the peaks of the first and second waves, specifically in urban lakes. [ FROM AUTHOR]

In Silico Genome Analysis Reveals the Evolution and Potential Impact of SARS-CoV-2 Omicron Structural Changes on Host Immune Evasion and Antiviral Therapeutics.

New variants of SARS-CoV-2 continue to evolve. The novel SARS-CoV-2 variant of concern (VOC) B.1.1.529 (Omicron) was particularly menacing due to the presence of numerous consequential mutations. In this study, we reviewed about 12 million SARS-CoV-2 genomic and associated metadata using extensive bioinformatic approaches to understand how evolutionary and mutational changes affect Omicron variant properties. Subsampled global data based analysis of molecular clock in the phylogenetic tree showed 29.56 substitutions per year as the evolutionary rate of five VOCs. We observed extensive mutational changes in the spike structural protein of the Omicron variant. A total of 20% of 7230 amino acid and structural changes exclusive to Omicron's spike protein were detected in the receptor binding domain (RBD), suggesting differential selection pressures exerted during evolution. Analyzing key drug targets revealed mutation-derived differential binding affinities between Delta and Omicron variants. Nine single-RBD substitutions were detected within the binding site of approved therapeutic monoclonal antibodies. T-cell epitope prediction revealed eight immunologically important functional hotspots in three conserved non-structural proteins. A universal vaccine based on these regions may likely protect against all these SARS-CoV-2 variants. We observed key structural changes in the spike protein, which decreased binding affinities, indicating that these changes may help the virus escape host cellular immunity. These findings emphasize the need for continuous genomic surveillance of SARS-CoV-2 to better understand how novel mutations may impact viral spread and disease outcome.

Steering North African countries towards REN21’s path of sustainable solar energy development

While more countries are promising to reach net-zero carbon dioxide emissions by 2050, North Africa’s efforts and promises fall well short of what is needed to give the world a fair chance of staying below 1.5 °C global warming by 2050. Therefore, it is crucial that the nations within the region contribute to achieving the clean energy goals outlined in REN21’s latest renewable energy overview. Given the region's solar belt status, and with the Coronavirus Disease-2019 (COVID-19) undermining many of these countries’ emission goals, it has become imperative to evaluate in detail other sites within these countries to increase access to solar energy. Under the shadow of the 26th United Nations climate change conference of the parties, this goal should not seem unrealistic. This study represents the first attempt in the literature to utilize a strategic perspective to explore the viability and cost-effectiveness of adapting REN21’s targets for increasing the share of solar photovoltaic (PV) installations in North Africa. With the aid of Hybrid Optimization Model for Electric Renewables, the study indicates significant prospects for exploring solar PV across several cities in each country, in accordance with REN21’s nation-specific targets. An examination of different forms of PV technology reveals that Schneider ConextCoreXC 630 kW with Generic PV outperforms the other types investigated by delivering the lowest cost of energy among all types;alternating between US$0.01916/kWh and US$0.1574/kWh across the six nations. By performing comparisons between the proposed PV plants in each of the North African countries and power plants with similar targeted capacity utilizing diesel fuel, PV farm utilization is found to be economically practical, sustainable against volatile prices for diesel fuel, and it is anticipated to avoid nearly between 1 million tons/year and 25.5 million tons/year of pollutants and reduce energy costs by between US$0.07117/kWh and US$1.1046/kWh across the six countries. By analyzing the effects PV cost can have on the cost of energy for the top sites in each country, the anticipated continuing drop in PV costs will set the scene for PV systems to contribute to each of the countries’ energy mix even more attractive fundamentally. Either by focusing on one site and intensifying the farms at that site, or deciding on multiple sites out of the top five locations highlighted in each country and scatter the farms across them, this study offers a generalized design guideline and recommendation for government officials and policymakers to choose the best solutions based on national preferences.

Detection of SARS-CoV-2 in the air in Indian hospitals and houses of COVID-19 patients.

To understand the transmission characteristics of severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) through air, samples from different locations occupied by coronavirus disease (COVID-19) patients were analyzed. Three sampling strategies were used to understand the presence of virus in the air in different environmental conditions. In the first strategy, which involved hospital settings, air samples were collected from several areas of hospitals like COVID-intensive-care units (ICUs), nurse-stations, COVID-wards, corridors, non-COVID-wards, personal protective equipment (PPE) doffing areas, COVID rooms, out-patient (OP) corridors, mortuary, COVID casualty areas, non-COVID ICUs and doctors' rooms. Out of the 80 air samples collected from 6 hospitals from two Indian cities- Hyderabad and Mohali, 30 samples showed the presence of SARS-CoV-2 nucleic acids. In the second sampling strategy, that involved indoor settings, one or more COVID-19 patients were asked to spend a short duration of time in a closed room. Out of 17 samples, 5 samples, including 4 samples collected after the departure of three symptomatic patients from the room, showed the presence of SARS-CoV-2 nucleic acids. In the third strategy, involving indoor settings, air samples were collected from rooms of houses of home-quarantined COVID-19 patients and it was observed that SARS-CoV-2 RNA could be detected in the air in the rooms occupied by COVID-19 patients but not in the other rooms of the houses. Taken together, we observed that the air around COVID-19 patients frequently showed the presence of SARS-CoV-2 RNA in both hospital and indoor residential settings and the positivity rate was higher when 2 or more COVID-19 patients occupied the room. In hospitals, SARS-CoV-2 RNA could be detected in ICUs as well as in non-ICUs, suggesting that the viral shedding happened irrespective of the severity of the infection. This study provides evidence for the viability of SARS-CoV-2 and its long-range transport through the air. Thus, airborne transmission could be a major mode of transmission for SARS-CoV-2 and appropriate precautions need to be followed to prevent the spread of infection through the air.

Longitudinal and Long-Term Wastewater Surveillance for COVID-19: Infection Dynamics and Zoning of Urban Community.

Wastewater-based epidemiology (WBE) is emerging as a potential approach to study the infection dynamics of SARS-CoV-2 at a community level. Periodic sewage surveillance can act as an indicative tool to predict the early surge of pandemic within the community and understand the dynamics of infection and, thereby, facilitates for proper healthcare management. In this study, we performed a long-term epidemiological surveillance to assess the SARS-CoV-2 spread in domestic sewage over one year (July 2020 to August 2021) by adopting longitudinal sampling to represent a selected community (~2.5 lakhs population). Results indicated temporal dynamics in the viral load. A consistent amount of viral load was observed during the months from July 2020 to November 2020, suggesting a higher spread of the viral infection among the community, followed by a decrease in the subsequent two months (December 2020 and January 2021). A marginal increase was observed during February 2021, hinting at the onset of the second wave (from March 2021) that reached it speak in April 2021. Dynamics of the community infection rates were calculated based on the viral gene copies to assess the severity of COVID-19 spread. With the ability to predict the infection spread, longitudinal WBE studies also offer the prospect of zoning specific areas based on the infection rates. Zoning of the selected community based on the infection rates assists health management to plan and manage the infection in an effective way. WBE promotes clinical inspection with simultaneous disease detection and management, in addition to an advance warning signal to anticipate outbreaks, with respect to the slated community/zones, to tackle, prepare for and manage the pandemic.

Corrigendum to "Defining the methodological approach for wastewater-based epidemiological studies-Surveillance of SARS-CoV-2" [Environ. Technol. Innov. 23 (2021) 101696].

[This corrects the article DOI: 10.1016/j.eti.2021.101696.].

SARS-CoV-2 seroprevalence in the city of Hyderabad, India in early 2021.

Background: COVID-19 emerged as a global pandemic in 2020, spreading rapidly to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via serosurveillance, making it a valuable tool for planning control measures. Our serosurvey study aimed to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections. Methods: This cross-sectional survey, conducted in January 2021 and including males and females aged 10 years and above, used multi-stage random sampling. 9363 samples were collected from 30 wards distributed over six zones of Hyderabad, and tested for antibodies against SARS-CoV-2 nucleocapsid antigen. Results: Overall seropositivity was 54.2%, ranging from 50% to 60% in most wards. Highest exposure appeared to be among those aged 30-39 and 50-59 years, with women showing greater seropositivity. Seropositivity increased with family size, with only marginal differences among people with varying levels of education. Seroprevalence was significantly lower among smokers. Only 11% of the survey subjects reported any COVID-19 symptoms, while 17% had appeared for COVID-19 testing. Conclusion: Over half the city's population was infected within a year of onset of the pandemic. However, ∼ 46% of people remained susceptible, contributing to subsequent waves of infection.

Temporal stability and detection sensitivity of the dry swab-based diagnosis of SARS-CoV-2

The rapid spread and evolution of various strains of SARS-CoV-2, the virus responsible for COVID-19, continues to challenge the disease controlling measures globally. Alarming concern is, the number of second wave infections surpassed the first wave and the onset of severe symptoms manifesting rapidly. In this scenario, testing of maximum population in less time and minimum cost with existing diagnostic amenities is the only possible way to control the spread of the virus. The previously described RNA extraction-free methods using dry swab have been shown to be advantageous in these critical times by different studies. In this work, we show the temporal stability and performance of the dry swab viral detection method at two different temperatures. Contrived dry swabs holding serially diluted SARS-CoV-2 strains A2a and A3i at 25°C (room temperature;RT) and 4°C were subjected to direct RT-PCR and compared with standard VTM-RNA based method. The results clearly indicate that dry swab method of RNA detection is as efficient as VTM-RNA-based method in both strains, when checked for up to 72 h. The lesser CT values of dry swab samples in comparison to that of the VTM-RNA samples suggest better sensitivity of the method within 48 h of time. The results collectively suggest that dry swab samples are stable at RT for 24 h and the detection of SARS-CoV-2 RNA by RT-PCR do not show variance from VTM-RNA. This extraction free, direct RT-PCR method holds phenomenal standing in the present life-threatening circumstances due to SARS-CoV-2.

Surveillance of SARS-CoV-2 spread using wastewater-based epidemiology: Comprehensive study.

SARS-CoV-2 pandemic is having a devastating effect on human lives. Recent reports have shown that majority of the individuals recovered from COVID-19 have serious health complications, which is going to be a huge economic burden globally. Given the wide-spread transmission of SARS-CoV-2 it is almost impossible to test every individual in densely populated countries. Recent reports have shown that sewage-based surveillance can be used as holistic approach to understand the spread of the pandemic within a population or area. Here we have estimated the spread of SARS-CoV-2 in the city of Hyderabad, India, which is a home for nearly 10 million people. The sewage samples were collected from all the major sewage treatment plants (STPs) and were processed for detecting the viral genome using the standard Reverse Transcription Polymerase Chain Reaction (RT-PCR) method. Interestingly, inlet samples of STPs were positive for SARS-CoV-2, while the outlets were negative, which indicates that the standard sewage treatment methods are efficient in eliminating the SARS-CoV-2 viral particles. Based on the detected viral gene copies per litre and viral particle shedding per individual, the total number of individuals exposed to SARS-CoV-2 was estimated. Through this study we suggest that sewage-based surveillance is an effective approach to study the infection dynamics, which helps in efficient management of the SARS-CoV-2 spread.

Dispersion of virus-laden droplets in ventilated rooms: Effect of homemade facemasks

In December 2019, the SARS-CoV-2 virus emerged and rapidly spread throughout the world. It causes the respiratory disease COVID-19 via the transmission of microbial pathogens within bio-aerosols during speaking, sneezing, and coughing. Therefore, understanding bioaerosol dynamics is important for developing mitigation strategies against droplet-induced infections. Computer modelling, using Computational Fluid Dynamics, has become a useful tool in studying and visualising the spread of atomised bio-droplets but the effect of using cloth facemasks has not been fully quantified. In this study, simulations were carried out to quantify the extent of respiratory droplet transfer with and without facemasks between a pair of ventilated rooms by a mathematical model for the first time. A 600-μm pore facemask was used, representing the porosity of a typical cloth facemask. Using the discrete phase model, the transport of ejected droplets was tracked. The results show that in the facemask cases, more than 96% of all the ejected droplets in all scenarios were trapped in the recommended 2 m social distancing radius around the human source. Correspondingly, only a maximum of 80% of droplets were deposited within the social distancing radius in the no facemask scenarios, with >20% airborne and transported to the second room. One-dimensional empirical correlations were developed for droplet concentration as a function of distance from the bioaerosol source. The models show that droplet concentration decays exponentially from the source especially in the facemask cases. The study therefore reinforces the importance of face coverings in lessening the transmission of possibly infected respiratory droplets that transmit highly infectious diseases such as COVID-19.

Defining the methodological approach for wastewater-based epidemiological studies-Surveillance of SARS-CoV-2.

Since COVID-19 outbreak, wastewater-based epidemiology (WBE) studies as surveillance system is becoming an emerging interest due to its functional advantage as a tool for early warning signal and to catalyze effective disease management strategies based on the community diagnosis. An attempt was made in this study to define and establish a methodological approach for conducting WBE studies in the framework of identifying/selection of surveillance sites, standardizing sampling policy, designing sampling protocols to improve sensitivity, adopting safety protocol, and interpreting the data. Data from hourly sampling indicated a peak in the viral RNA during the morning hours (6-9 am) when the all the domestic activities are maximum. The daily sampling and processing revealed the dynamic nature of infection spread among the population. The two sampling methods viz. grab, and composite showed a good correlation. Overall, this study establishes a structured protocol for performing WBE studies that could provide useful insights on the spread of the pandemic at a given point of time. Moreover, this framework could be extrapolated to monitor several other clinically relevant diseases. Following these guidelines, it is possible to achieve measurable and reliable SARS-CoV-2 RNA concentrations in wastewater infrastructure and therefore, provides a methodological basis for the establishment of a national surveillance system.