Dataset Information

Reflections of COVID-19 cases in the wastewater loading of SARS-CoV-2 RNA: A case of three major cities of Gujarat, India

ABSTRACT: Wastewater-based epidemiology (WBE) is a promising approach to understand the actual prevalence of COVID-19 disease at the community level. Different studies have cited the presence of SARS-CoV-2 in wastewater samples. In the present study, eighteen influent wastewater samples from different sewage treatment plants and pumping stations (5 samples from Vadodara city, 4 from Gandhinagar, and 9 from Ahmedabad city) were collected and analyzed for the presence of SARS-CoV-2 RNA in Gujarat state, India. The results showed the highest SARS-CoV-2 effective gene concentration in Vadodara (3078 copies/L), followed by Ahmedabad (2968 copies/L) and Gandhinagar (354 copies/L). On comparing the virus gene concentration in wastewater samples, the SARS-CoV-2 genetic material exhibited a positive relationship with the number of confirmed and active cases in in all three cities. However, a minor variation in SARS-CoV-2 effective gene concentration was seen between Vadodara and Ahmedabad despite a >2.5 and >1.5 folds differences in the cumulative number of confirmed and active cases, respectively. This may occur primarily due to the greater test positivity ratio in Vadodara (3.30%) than Ahmedabad (1.40%) and might be the higher number of asymptomatic patients in Vadodara. The study confirms the potential of the WBE that can be used at a large scale around the globe for better dealing with the pandemic situation. Graphical abstract Image 1

SUBMITTER: Srivastava V

PROVIDER: S-EPMC8264277 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Diagnosis of TB in children is challenging, and is largely based on positive history of contact with a TB case, clinical and radiological findings, often without microbiological confirmation. Diagnostic efforts are also undermined by challenges in specimen collection and the limited availability of high sensitivity, rapid diagnostic tests that can be applied with a quick turnaround time. The current project was undertaken in four major cities of India to address TB diagnostic challenges in pediatric population, by offering free of cost Xpert testing to pediatric presumptive TB cases, thereby paving the way for better TB care.A high throughput lab was established in each of the four project cities, and linked to various health care providers across the city through rapid specimen transportation and electronic reporting linkages. Free Xpert testing was offered to all pediatric (0-14 years) presumptive TB cases (both pulmonary and extra-pulmonary) seeking care at public and private health facilities.The current project enrolled 42,238 pediatric presumptive TB cases from April, 2014 to June, 2016. A total of 3,340 (7.91%, CI 7.65-8.17) bacteriologically confirmed TB cases were detected, of which 295 (8.83%, CI 7.9-9.86) were rifampicin-resistant. The level of rifampicin resistance in the project cohort was high. Overall Xpert yielded a high proportion of valid results and TB detection rates were more than three-fold higher than smear microscopy. The project provided same-day testing and early availability of results led to rapid treatment initiation and success rates and very low rates of treatment failure and loss to follow-up.The current project demonstrated the feasibility of rolling out rapid and upfront Xpert testing for pediatric presumptive TB cases through a single Xpert lab per city in an efficient manner. Rapid turnaround testing time facilitated prompt and appropriate treatment initiation. These results suggest that the upfront Xpert assay is a promising solution to address TB diagnosis in children. The high levels of rifampicin resistance detected in presumptive pediatric TB patients tested under the project are a major cause of concern from a public health perspective which underscores the need to further prioritize upfront Xpert access to this vulnerable population.

Project description:Some of the most promising vaccines in the pipeline for tuberculosis (TB) target adolescents and adults. Unlike for childhood vaccines, high-coverage population-wide vaccination is significantly more challenging for adult vaccines. Here, we aimed to estimate the impact of vaccine delivery strategies that were targeted to high-incidence geographical 'hotspots' compared with randomly allocated vaccination. We developed a spatially explicit mathematical model of TB transmission that distinguished these hotspots from the general population. We evaluated the impact of targeted and untargeted vaccine delivery strategies in India--a country that bears more than 25% of global TB burden, and may be a potential early adopter of the vaccine. We collected TB notification data and conducted a demonstration study in the state of Gujarat to validate our estimates of heterogeneity in TB incidence. We then projected the impact of randomly vaccinating 8% of adults in a single mass campaign to a spatially targeted vaccination preferentially delivered to 80% of adults in the hotspots, with both strategies augmented by continuous adolescent vaccination. In consultation with vaccine developers, we considered a vaccine efficacy of 60%, and evaluated the population-level impact after 10 years of vaccination. Spatial heterogeneity in TB notification (per 100,000/year) was modest in Gujarat: 190 in the hotspots versus 125 in the remaining population. At this level of heterogeneity, the spatially targeted vaccination was projected to reduce TB incidence by 28% after 10 years, compared with a 24% reduction projected to achieve via untargeted vaccination--a 1.17-fold augmentation in the impact of vaccination by spatially targeting. The degree of the augmentation was robust to reasonable variation in natural history assumptions, but depended strongly on the extent of spatial heterogeneity and mixing between the hotspot and general population. Identifying high-incidence hotspots and quantifying spatial mixing patterns are critical to accurate estimation of the value of targeted intervention strategies.

Dataset Information

Reflections of COVID-19 cases in the wastewater loading of SARS-CoV-2 RNA: A case of three major cities of Gujarat, India

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets