Vaccines: From Public Health to Big Business. / Vacinas: Da Saúde Pública ao Big Business.

The text presents and discusses the main aspects related to the current dynamics of the vaccine industry in the world and in Brazil, focusing on the demand created by the pandemic of COVID-19. At the global level, it briefly exposes the place currently occupied by Brazil within the scope of the BRICS and sets out and analyzes the options - identities and differences - of industrial policy in Brazil, China and India in the field of vaccines. Next, it analyzes the displacement of the vaccine industry, from a situation of exclusive production of immunizers to a majority control by the large pharmaceutical industry. Further on, it recovers recent fundamental aspects of the vaccine industry in Brazil, with an emphasis on Biomanguinhos / Fiocruz and the Butantan Institute. Finally, it discusses the successes and limitations of the technology transfer mechanism used by the two institutions, as well as the relevance of their historically assumed commitment to public health policies.

O texto apresenta e discute os principais aspectos relacionados à dinâmica atual da indústria de vacinas no mundo e no Brasil, com foco na demanda criada pela pandemia da COVID-19. No plano global, expõe brevemente o lugar ocupado atualmente pelo Brasil no âmbito dos BRICS e expõe e analisa as opções - identidades e diferenças - da política industrial de Brasil, China e Índia no campo das vacinas. A seguir, analisa o deslocamento da indústria de vacinas de uma situação de produção exclusiva de imunizantes para um controle majoritário da grande indústria farmacêutica. Mais adiante, recupera aspectos fundamentais recentes da indústria de vacinas no Brasil, com ênfase em Biomanguinhos/Fiocruz e no Instituto Butantan. Finalmente, discute os sucessos e limitações do mecanismo de transferência de tecnologia utilizado pelas duas instituições, bem como a relevância do compromisso historicamente assumido pelas mesmas com as políticas públicas de saúde.

Analysis and Prediction of COVID-19 Multivariate Data Using Deep Ensemble Learning Methods.

The global economy has suffered losses as a result of the COVID-19 epidemic. Accurate and effective predictive models are necessary for the governance and readiness of the healthcare system and its resources and, ultimately, for the prevention of the spread of illness. The primary objective of the project is to build a robust, universal method for predicting COVID-19-positive cases. Collaborators will benefit from this while developing and revising their pandemic response plans. For accurate prediction of the spread of COVID-19, the research recommends an adaptive gradient LSTM model (AGLSTM) using multivariate time series data. RNN, LSTM, LASSO regression, Ada-Boost, Light Gradient Boosting and KNN models are also used in the research, which accurately and reliably predict the course of this unpleasant disease. The proposed technique is evaluated under two different experimental conditions. The former uses case studies from India to validate the methodology, while the latter uses data fusion and transfer-learning techniques to reuse data and models to predict the onset of COVID-19. The model extracts important advanced features that influence the COVID-19 cases using a convolutional neural network and predicts the cases using adaptive LSTM after CNN processes the data. The experiment results show that the output of AGLSTM outperforms with an accuracy of 99.81% and requires only a short time for training and prediction.

Feasibility and acceptability pilot of video-based direct observed treatment (vDOT) for supporting antitubercular treatment in South India: a cohort study.

OBJECTIVES: The objective of this study was to assess the feasibility and acceptability of video-based anti-tuberculosis (TB) treatment adherence support in patients with TB (PwTB) in South India. DESIGN: An exploratory cohort. SETTING: Participants were recruited at the TB treatment centre (direct observed treatment short centre) of a tertiary-level teaching facility in Bangalore, Karnataka, South India. PARTICIPANTS: The study enrolled 25 PwTB, with replacement. Adult PwTB who were on drug-sensitive treatment regimens were included, while those who had drug resistant TB were excluded from the study. INTERVENTION: Participants received scheduled adherence reminders and were trained to videorecord themselves swallowing their medication via a mobile application. The application was automated to submit these videos for evaluation. Participants were followed up monthly till treatment completion or withdrawal. OUTCOME MEASURES: Adherence rate and acceptability of video-based directly observed treatment (vDOT). RESULTS: The mean±SD age of the participants was 33±14 years, majority were females (16, 64%), residing in urban areas (24,96%), married (17, 68%) and had access to smart phones (23,92%). A total of 3193 person days of follow-up was completed; of the videos submitted within the first 6 months of enrollment (2501), 94% (2354/2501) were considered 'acceptable' and 16 (64%) participants were optimally adherent (ie, ≥80%). Participant videos improved in quality and a higher proportion met acceptability criteria over time. Twenty-one (84%) participants stated that they found the application easy to learn; 13 (52%) preferred vDOT over DOT. Mixed model logistic regression showed that those who are married are more likely have daily adherence to anti-TB treatment. CONCLUSION: Video-based mobile phone interventions are acceptable to PwTB and the ease of using the application increases with time. To provide patient-centred care, vDOT is a promising option that can be offered to patients for treatment support and adherence monitoring.

HIV and its associated factors among people who inject drugs in Mizoram, Northeast India.

AIM: To estimate the prevalence and associated factors with the human immune-deficiency virus (HIV) among people who inject drugs (PWID) in Mizoram, Northeast India. METHODS: The data source for the analysis was the 2019-2020 Mizoram State AIDS Control Society (MSACS) survey from 2695 PWID registered for the Targeted Intervention (TI) services. Logistic regression analysis was conducted to examine the factors associated with HIV among PWID after adjusting for sociodemographic characteristics, injection, and sexual behaviours. RESULTS: 21.19% of the participants tested positive for HIV and the prevalence of HIV among male and female participants were 19.5% and 38.6%, respectively. Multiple logistic regression analysis revealed that female (AOR 1.74; 95% CI 1.26-2.41), 35 years or older (AOR 1.45; 95% CI 1.06-1.99), married (AOR 1.41; 95% CI1.08-1.83), divorced/separated/widowed (AOR 2.12; 95% CI 1.59-2.82) and sharing of needle/syringe (AOR 1.62; 95% CI 1.30-2.00) were all positively associated with HIV infection. We also found that concomitant alcohol use was reduced by 35% (AOR 0.65; 95% CI 0.51-0.82) among HIV positive PWID, and HIV infection was also reduced by 46% (AOR 0.54; 95% CI 0.44-0.67) among those PWID who use a condom with a regular partner. CONCLUSION: The findings of this study suggested that there is a high prevalence of HIV among PWID with 1 in 5 PWID reported to have HIV. HIV among PWID was significantly higher among those over 35 years of age, females and divorced/separated/widowed participants. Needle/syringe sharing behaviour is an important determinant of HIV infection. The high prevalence of HIV among PWID population is multifactorial. To reduce HIV among PWID in Mizoram, interventions should target those sharing needles/syringes, females, especially those over 35 years of age and unmarried participants.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India.

BACKGROUND: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.

Significant variation in air quality in South Indian cities during COVID-19 lockdown and unlock phases.

With the spread of COVID-19 pandemic worldwide, the Government of India had imposed lockdown in the month of March 2020 to curb the spread of the virus furthermore. This shutdown led to closure of various institutions, organizations, and industries, and restriction on public movement was also inflicted which paved way to better air quality due to reduction in various industrial and vehicular emissions. To brace this, the present study was carried out to statistically analyze the changes in air quality from pre-lockdown period to unlock 6.0 in South Indian cities, namely, Bangalore, Chennai, Coimbatore, and Hyderabad, by assessing the variation in concentration of PM2.5, PM10, NO2, and SO2 during pre-lockdown, lockdown, and unlock phases. Pollutant concentration data was obtained for the selected timeframe (01 March 2020-30 November 2020) from CPCB, and line graph was plotted which had shown visible variation in the concentration of pollutants in cities taken into consideration. Analysis of variance (ANOVA) was applied to determine the mean differences in the concentration of pollutants during eleven timeframes, and the results indicated a significant difference (F (10,264) = 3.389, p < 0.001). A significant decrease in the levels of PM2.5, PM10, NO2, and SO2 during the lockdown phases was asserted by Tukey HSD results in Bangalore, Coimbatore, and Hyderabad stations, whereas PM10 and NO2 significantly increased during lockdown period in Chennai station. In order to understand the cause of variation in the concentration of pollutants and to find the association of pollutants with meteorological parameters, the Pearson correlation coefficient was used to study the relationship between PM2.5, PM10, NO2, and SO2 concentrations, temperature, rainfall, and wind speed for a span of 15 months, i.e., from January 2020 to March 2021. At a significant level of 99.9%, 99%, and 95%, a significant correlation among the pollutants, rainfall had a major impact on the pollutant concentration in Bangalore, Coimbatore, Hyderabad, and Chennai followed by wind speed and temperature. No significant influence of temperature on the concentration of pollutants was observed in Bangalore station.

Suicide Following the COVID-19 Pandemic Outbreak: Variation Across Place, Over Time, and Across Sociodemographic Groups. A Systematic Integrative Review.

PURPOSE OF REVIEW: To systematically examine changes in suicide trends following the initial COVID-19 outbreak, focusing on geographical and temporal heterogeneity and on differences across sociodemographic subgroups. RECENT FINDINGS: Of 46 studies, 26 had low risk of bias. In general, suicides remained stable or decreased following the initial outbreak - however, suicide increases were detected during spring 2020 in Mexico, Nepal, India, Spain, and Hungary; and after summer 2020 in Japan. Trends were heterogeneous across sociodemographic groups (i.e., there were increases among racially minoritized individuals in the US, young adults and females across ages in Japan, older males in Brazil and Germany, and older adults across sex in China and Taiwan). Variations may be explained by differences in risk of COVID-19 contagion and death and in socioeconomic vulnerability. Monitoring geographical, temporal, and sociodemographic differences in suicide trends during the COVID-19 pandemic is critical to guide suicide prevention efforts.

Investigating asymmetric impacts of total factor energy efficiency on carbon emissions in India.

As many complex energy relations are not linear and have diminishing returns, assuming a symmetric (linear) effect of energy efficiency (ENEF) on carbon emissions (CAE) has limited our understanding of the emission-ENEF nexus. This research, therefore, initially estimates total factor energy efficiency by applying a stochastic frontier technique using sample panels for India encompassing the period from 2000 to 2014. Further, a nonlinear panel autoregressive distributed lag modelling framework is utilised in order to investigate the asymmetric (nonlinear) long- and short-run impacts of ENEF on CAE. The findings demonstrated that ENEF has asymmetric long- and short-run impacts on CAE in India. Based on the outcomes, numerous crucial implications are discussed with a particular reference to developing economies like India.

Bibliometric analysis of endocrinology, diabetes and metabolism research in South Asia from (2012-2021): Comparison with five developed countries.

BACKGROUND AND AIMS: In the present study the research output of the South Asian region (India, Pakistan, Bangladesh, Sri Lanka, Nepal, Maldives, and Bhutan) in endocrinology, diabetes and metabolism (EDM) is highlighted. It was compared with five scientifically advanced countries i.e. USA, UK, Italy, Japan and China. METHODS: On September 13, 2022, the data was retrieved from the Scopus database. The analysis focused on the number of publications, total citations (TC), citations per paper (CPP), field-weighted citations impact (FWCI), and degree of international collaboration. RESULTS: In South Asia, India produced the highest number of publications (n = 7048), followed by Pakistan (n = 799), Bangladesh (n = 345), Sri Lanka (n = 256), Nepal (n = 144), Maldives (n = 12) and Bhutan (n = 4). The highest CPP (n = 19.4) and FWCI (n = 1.18) was recorded for Sri Lanka. Furthermore, USA (n = 64022), China (n = 23991), UK (n = 21449), Italy (n = 18884), and Japan (n = 12875), published the highest number of documents with the highest citations and FWCI in the world. It was noted that India published the highest number of documents (n = 47.28%) in the quartiles (Q) 6 and Q7. Pakistan produced the highest number of documents (n = 64.22%) in the top 50% of journals (Q1 to Q5). South Asian countries produced 8332 publications, with 130382 TC, 15.6 CPP and 1.06 FWCI. Importantly 46.50% of documents from South Asian countries were published in Q6 and Q7 journals. In contrast USA, UK, Italy, Japan and China published 77% documents in top 50% journals. CONCLUSIONS: Although the South Asian research publications have increased yearly (from 2012 to 2021), but approximately 50% of the South Asian output were in the lower quartile journals. Consequently, significant measures are needed to improve the quantity and quality of EDM research produced in South Asian coutries.

COVID-19 vaccine hesitancy among school children aged 12-14 years: A cross-sectional study from Bhubaneswar, Odisha, India.

INTRODUCTION: Universal coverage of COVID-19 vaccines is of paramount importance for the prevention and control of the pandemic. World Health Organization (WHO) in 2019 declared vaccine hesitancy as one of the top ten global health threats. The study aims to find out the COVID-19 vaccine hesitancy among school children along with their parent's perspectives. METHODOLOGY: A cross-sectional study was conducted among school children (aged 12-14 years) at two schools in Bhubaneswar, Odisha. Data were collected via web-based links using a semi-structured questionnaire among students and their parents. RESULTS: Of 343 children, 79% (271) showed a strong willingness to get vaccinated. Around 91.8% (315) of parents agreed to get their children vaccinated. Fear of side effects (65.2%) was the most common reason for unwillingness. CONCLUSIONS: With only 1/5th of the children not willing to get vaccinated, policymakers should create a multi-centric effort for the universal coverage of the COVID-19 vaccination.

Managing dementia care during COVID-19 pandemic: caregivers' experiences in Odisha, India.

AIM: The present study explored the family caregivers' perspectives and elicited their experience while managing dementia care during the COVID-19 pandemic in Odisha, India. BACKGROUND: The onset of the COVID-19 pandemic has diverted the attention of health systems away from chronic disease management and health services delivery. Psychiatric care particularly for dementia and the elderly is found to be more compromised in such situation. METHODS: We adopted an inductive phenomenological approach to garner key insights into the care continuity for people living with dementia in the context of the COVID-19 pandemic. Telephonic in-depth interviews (IDIs) were carried out with 17 immediate caregivers. All IDIs were digitally recorded, transcribed, and analysed using a thematic approach. FINDINGS: Caregivers did not perceive dementia as an overwhelming challenge; instead viewed it as a part of the ageing process. Caring for dementia was being done by family members as a collective responsibility with task-sharing. The caregivers primarily relied on their usual physician for the continuity of dementia care and took utmost precautions to prevent exposure to COVID-19 risk. However, they found it more challenging to ensure adequate care for the multiple illnesses (multimorbidity) coexisting with dementia. Towards this, they adopted all possible measures to keep the chronic conditions under control, lest the vulnerability to COVID-19 infection might heighten. The fear of visiting a hospital, prevailing restrictions in mobility, and diverted attention of health systems to pandemic containment created impediments towards maintaining multimorbidity care. The support of local administration, neighbourhood pharmacy and diagnostic laboratories and teleconsultation with the physicians were vital for care continuity. Caregivers adapted by reducing or deferring physical consultation and seeking treatment via telephonic advice of the treating physicians. Our findings suggest leveraging digitally enabled health care technology and augmenting caregiver activation for home-based dementia care to cruise through any similar catastrophic situations.

Did the COVID-19 pandemic play a role in the spatial and temporal variations of microplastics? Evidence from a tropical river in southern India.

Personal protective equipment (PPE) use has increased because of COVID-19, producing more microplastics (MPs). The pandemic's impact on MP pollution in Indian rivers is little understood. In this study, the Netravathi River in Karnataka was investigated for the spatiotemporal distribution of MPs. The MPs abundance, size, and categories varied seasonally, with a higher concentration during the monsoon seasons. The reduction in rainfall during MON20 and the COVID-19 lockdown can be the reasons for the significant decrease in the MP concentration when compared to MON19. Polyethylene and polyethylene terephthalate were the most abundant polymers, with a shift from polyethylene to the latter (74 %) during post-monsoon season post-lockdown. The situation of MP pollution in Western Ghats can be mitigated with the aid of appropriate waste management of plastic trash and greater public awareness about the disposal of single-use plastics, which has risen significantly during the COVID-19 pandemic.

Evaluation of Recombinase Polymerase Amplification assay for monitoring parasite load in patients with kala-azar and post kala-azar dermal leishmaniasis.

BACKGROUND: The potential reservoirs of visceral leishmaniasis (VL) in South Asia include asymptomatic and relapsed cases of VL, along with patients with post kala-azar dermal leishmaniasis (PKDL). Accordingly, accurate estimation of their parasite load is pivotal for ensuring disease elimination, presently targeted for 2023. Serological tests cannot accurately detect relapses and/or monitor treatment effectiveness, and therefore, parasite antigen/nucleic acid based detection assays remain the only viable option. An excellent option is the quantitative polymerase chain reaction (qPCR) but the high cost, technical expertise and time involved precludes its wider acceptability. Accordingly, the recombinase polymerase amplification (RPA) assay operated in a mobile suitcase laboratory has emerged not simply as a diagnostic tool for leishmaniasis but also to monitor the disease burden. METHODOLOGY/PRINCIPAL FINDINGS: Using total genomic DNA isolated from peripheral blood of confirmed VL cases (n = 40) and lesional biopsies of PKDL cases (n = 64), the kinetoplast-DNA based qPCR and RPA assay was performed and parasite load expressed as Cycle threshold (Ct) and Time threshold (Tt) respectively. Using qPCR as the gold standard, the diagnostic specificity and sensitivity of RPA in naïve cases of VL and PKDL was reiterated. To assess the prognostic potential of the RPA, samples were analyzed immediately at the end of treatment or ≥6 months following completion of treatment. In cases of VL, the RPA assay in terms of cure and detection of a relapse case showed 100% concordance with qPCR. In PKDL following completion of treatment, the overall detection concordance between RPA and qPCR was 92.7% (38/41). At the end of treatment for PKDL, 7 cases remained qPCR positive, whereas RPA was positive in only 4/7 cases, perhaps attributable to their low parasite load. CONCLUSIONS/SIGNIFICANCE: This study endorsed the potential of RPA to evolve as a field applicable, molecular tool for monitoring parasite load, possibly at a point of care level and is worthy of consideration in resource limited settings.