Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities

RNA-Seq of untreated wastewater to assess COVID-19 and emerging and endemic viruses for public health surveillance

BackgroundThe COVID-19 pandemic showcased the power of genomic sequencing to tackle the emergence and spread of infectious diseases. However, metagenomic sequencing of total microbial RNAs in wastewater has the potential to assess multiple infectious diseases simultaneously and has yet to be explored.MethodsA retrospective RNA-Seq epidemiological survey of 140 untreated composite wastewater samples was performed across urban (n = 112) and rural (n = 28) areas of Nagpur, Central India. Composite wastewater samples were prepared by pooling 422 individual grab samples collected prospectively from sewer lines of urban municipality zones and open drains of rural areas from 3rd February to 3rd April 2021, during the second COVID-19 wave in India. Samples were pre-processed and total RNA was extracted prior to genomic sequencing.FindingsThis is the first study that has utilised culture and/or probe-independent unbiased RNA-Seq to examine Indian wastewater samples. Our findings reveal the detection of zoonotic viruses including chikungunya, Jingmen tick and rabies viruses, which have not previously been reported in wastewater. SARS-CoV-2 was detectable in 83 locations (59%), with stark abundance variations observed between sampling sites. Hepatitis C virus was the most frequently detected infectious virus, identified in 113 locations and co-occurring 77 times with SARS-CoV-2; and both were more abundantly detected in rural areas than urban zones. Concurrent identification of segmented virus genomic fragments of influenza A virus, norovirus, and rotavirus was observed. Geographical differences were also observed for astrovirus, saffold virus, husavirus, and aichi virus that were more prevalent in urban samples, while the zoonotic viruses chikungunya and rabies, were more abundant in rural environments.InterpretationRNA-Seq can effectively detect multiple infectious diseases simultaneously, facilitating geographical and epidemiological surveys of endemic viruses that could help direct healthcare interventions against emergent and pre-existent infectious diseases as well as cost-effectively and qualitatively characterising the health status of the population over time

A longitudinal study to assess the cost incurred by patients undergoing treatment for tuberculosis in an urban slum community

Objectives: The objective of the study was to estimate direct medical/nonmedical and indirect costs incurred by patients diagnosed with tuberculosis (TB) residing in an urban slum of Mumbai. Subjects and Methods: A longitudinal study of 16 months duration (June 2013-September 2014) was undertaken in a directly observed treatment short-course (DOTS) center of an urban slum area. The method of sampling was universal sampling and thus all the patients who were registered in the period June 2013 to December 2013 were enrolled as study participants. These subjects were then followed for their completion of treatment. All the subjects were interviewed using a semistructured questionnaire to obtain the desired information. Permission from the Institutional Ethics Committee was obtained. Statistical analysis was performed using SPSS software version 19. Results: Of the 232 patients enrolled in the study, 176 (75.9%) completed the entire course of treatment. The median direct, indirect, and total costs for 176 patients were: pretreatment direct medical cost, direct nonmedical cost, and pretreatment indirect cost was Rs. 1200 ($20), Rs. 800 ($13.3), and Rs. 1250 ($20.8), respectively. However, during the course of treatment direct medical cost, direct nonmedical cost, and indirect cost were nil, Rs. 360 ($6) and Rs. 400 ($6.6), respectively. Conclusion: Despite the free availability of diagnostic and treatment component of TB in India, the majority of the tuberculosis patients still have to spend a significant amount of money

Clinico-Epidemiological Profile of Extra-pulmonary Tuberculosis in Central India

Introduction: Tuberculosis (TB) remains a major global health issue. India being highest TB burden country needs concern. It was found that the percentage of patients with EPTB was more in tertiary care centres of India, ranging from 30% to 53%. The primary objective of this study was to describe the basic demographic, clinical characteristics and risk factors of Extrapulmonary Tuberculosis in patients, registered at DOTS centre of tertiary care teaching hospital. Materials and Methods: This is a retrospective, record-based study of patients of EPTB, at the LN Medical College and Hospital, Bhopal, from 1st January 2012 to 30th June 2014. Results: Among 491 cases registered for treatment of all forms of tuberculosis, 361(73.53%) had PTB and 130 (26.47%) had EPTB. The ratio of percentage EPTB: PTB is 1:3.6. Commonest type of EPTB was found in cases of lymph nodes and lymphatic (30.76%), followed by TB in pleural cavity (23.03%). Among different age groups studied, the age group of 20-39 years had the highest proportion of EPTB both in males and females which is the economically productive population of society. Conclusion: The frequency of EPTB in this study was higher (26.47%) with the highest proportion in lymph node (30.76%). The burden of EPTB is more among the productive age group, moreover, being male, young adults and having associated diabetes mellitus were significant risk factors for patient being EPTB positive

Dual-Sided Involvement of Energy Optimization and Strategic Bidding in Wind-PV System to Maximize Benefits for Customers and Power Providers

Global warming is causing industrial development to increase greenhouse gas emissions, impact power provider economies, and potentially pose a solution through renewable energy. In order to solve these issues, the research offers a dual strategic auction difficulty for renewable energy market clear prices (MCPs) to maximize supplier and buyer revenues while mitigating rival unpredictability and renewable vacillation power supply sources. The study uses scenario reduction techniques, including Beta and Weibull distribution of probability, forward-reduction technique, and underestimation and overestimation of the cost function to manage uncertainties in renewable energy. The Gravitation Search algorithm and a hybrid approach ordered weighted average distance (OWAD) combined, with Topsis operational gravitational search algorithm TOGSA (OWAD-TOGSA), are used to solve the multi-objective issue. The study evaluates the performance of IEEE standard 30-bus and 57-bus test systems and an Indian 75-bus operational system to solve a problem involving wind and sun energy in spite of its volatility. The proposed bidding approach is feasible and could increase revenue by nearly 10 %, potentially improving efficiency for electric energy-producing utilities and consumers, and its findings will be beneficial for similar research using optimization techniques

Chick embryo: a preclinical model for understanding ischemia-reperfusion mechanism

Ischemia-reperfusion (I/R)-related disorders, such as stroke, myocardial infarction, and peripheral vascular disease, are among the most frequent causes of disease and death. Tissue injury or death may result from the initial ischemic insult, primarily determined by the magnitude and duration of the interruption in blood supply and then by the subsequent reperfusion-induced damage. Various and models are currently available to study I/R mechanism in the brain and other tissues. However, thus far, no I/R model has been reported for understanding the I/R mechanisms and for faster drug screening. Here, we developed an Hook model of I/R by occluding and releasing the right vitelline artery of a chick embryo at 72 h of development. To validate the model and elucidate various underlying survival and death mechanisms, we employed imaging (Doppler blood flow imaging), biochemical, and blotting techniques and evaluated the cell death mechanism: autophagy and inflammation caused by I/R. In conclusion, the present model is useful in parallel with established and I/R models to understand the mechanisms of I/R development and its treatment

Single nucleotide polymorphism mining and nucleotide sequence analysis of Mx1 gene in exonic regions of Japanese quail

Aim: An attempt has been made to study the Myxovirus resistant (Mx1) gene polymorphism in Japanese quail. Materials and Methods: In the present, investigation four fragments viz. Fragment I of 185 bp (Exon 3 region), Fragment II of 148 bp (Exon 5 region), Fragment III of 161 bp (Exon 7 region), and Fragment IV of 176 bp (Exon 13 region) of Mx1 gene were amplified and screened for polymorphism by polymerase chain reaction-single-strand conformation polymorphism technique in 170 Japanese quail birds. Results: Out of the four fragments, one fragment (Fragment II) was found to be polymorphic. Remaining three fragments (Fragment I, III, and IV) were found to be monomorphic which was confirmed by custom sequencing. Overall nucleotide sequence analysis of Mx1 gene of Japanese quail showed 100% homology with common quail and more than 80% homology with reported sequence of chicken breeds. Conclusion: The Mx1 gene is mostly conserved in Japanese quail. There is an urgent need of comprehensive analysis of other regions of Mx1 gene along with its possible association with the traits of economic importance in Japanese quail

Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly April 30, 2024 1/18 higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R 0 , positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities

The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017

Summary: Background: Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational levels in India, we estimated the exposure to air pollution and its impact on deaths, disease burden, and life expectancy in every state of India in 2017. Methods: We estimated exposure to air pollution, including ambient particulate matter pollution, defined as the annual average gridded concentration of PM2.5, and household air pollution, defined as percentage of households using solid cooking fuels and the corresponding exposure to PM2.5, across the states of India using accessible data from multiple sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three Socio-demographic Index (SDI) levels as calculated by GBD 2017 on the basis of lag-distributed per-capita income, mean education in people aged 15 years or older, and total fertility rate in people younger than 25 years. We estimated deaths and disability-adjusted life-years (DALYs) attributable to air pollution exposure, on the basis of exposure–response relationships from the published literature, as assessed in GBD 2017; the proportion of total global air pollution DALYs in India; and what the life expectancy would have been in each state of India if air pollution levels had been less than the minimum level causing health loss. Findings: The annual population-weighted mean exposure to ambient particulate matter PM2·5 in India was 89·9 μg/m3 (95% uncertainty interval [UI] 67·0–112·0) in 2017. Most states, and 76·8% of the population of India, were exposed to annual population-weighted mean PM2·5 greater than 40 μg/m3, which is the limit recommended by the National Ambient Air Quality Standards in India. Delhi had the highest annual population-weighted mean PM2·5 in 2017, followed by Uttar Pradesh, Bihar, and Haryana in north India, all with mean values greater than 125 μg/m3. The proportion of population using solid fuels in India was 55·5% (54·8–56·2) in 2017, which exceeded 75% in the low SDI states of Bihar, Jharkhand, and Odisha. 1·24 million (1·09–1·39) deaths in India in 2017, which were 12·5% of the total deaths, were attributable to air pollution, including 0·67 million (0·55–0·79) from ambient particulate matter pollution and 0·48 million (0·39–0·58) from household air pollution. Of these deaths attributable to air pollution, 51·4% were in people younger than 70 years. India contributed 18·1% of the global population but had 26·2% of the global air pollution DALYs in 2017. The ambient particulate matter pollution DALY rate was highest in the north Indian states of Uttar Pradesh, Haryana, Delhi, Punjab, and Rajasthan, spread across the three SDI state groups, and the household air pollution DALY rate was highest in the low SDI states of Chhattisgarh, Rajasthan, Madhya Pradesh, and Assam in north and northeast India. We estimated that if the air pollution level in India were less than the minimum causing health loss, the average life expectancy in 2017 would have been higher by 1·7 years (1·6–1·9), with this increase exceeding 2 years in the north Indian states of Rajasthan, Uttar Pradesh, and Haryana. Interpretation: India has disproportionately high mortality and disease burden due to air pollution. This burden is generally highest in the low SDI states of north India. Reducing the substantial avoidable deaths and disease burden from this major environmental risk is dependent on rapid deployment of effective multisectoral policies throughout India that are commensurate with the magnitude of air pollution in each state. Funding: Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India