Background Cancer is the major cause of morbidity and mortality worldwide. The cancer burden varies within the regions of India posing great challenges in its prevention and control. The national burden assessment remains as a task which relies on statistical models in many developing countries, including India, due to cancer not being a notifiable disease. This study quantifies the cancer burden in India for 2016, adjusted mortality to incidence (AMI) ratio and projections for 2021 and 2025 from the National Cancer Registry Program (NCRP) and other publicly available data sources. Methods Primary data on cancer incidence and mortality between 2012 and 2016 from 28 Population Based Cancer Registries (PBCRs), all-cause mortality from Sample Registration Systems (SRS) 2012–16, lifetables and disability weight from World Health Organization (WHO), the population from Census of India and cancer prevalence using the WHO-DisMod-II tool were used for this study. The AMI ratio was estimated using the Markov Chain Monte Carlo method from longitudinal NCRP-PBCR data (2001–16). The burden was quantified at national and sub-national levels as crude incidence, mortality, Years of Life Lost (YLLs), Years Lived with Disability (YLDs) and Disability Adjusted Life Years (DALYs). The projections for the years 2021 and 2025 were done by the negative binomial regression model using STATA. Results The projected cancer burden in India for 2021 was 26.7 million DALYsAMI and expected to increase to 29.8 million in 2025. The highest burden was in the north (2408 DALYsAMI per 100,000) and northeastern (2177 DALYsAMI per 100,000) regions of the country and higher among males. More than 40% of the total cancer burden was contributed by the seven leading cancer sites — lung (10.6%), breast (10.5%), oesophagus (5.8%), mouth (5.7%), stomach (5.2%), liver (4.6%), and cervix uteri (4.3%). Conclusions This study demonstrates the use of reliable data sources and DisMod-II tools that adhere to the international standard for assessment of national and sub-national cancer burden. A wide heterogeneity in leading cancer sites was observed within India by age and sex. The results also highlight the need to focus on non-leading sites of cancer by age and sex. These findings can guide policymakers to plan focused approaches towards monitoring efforts on cancer prevention and control. The study simplifies the methodology used for arriving at the burden estimates and thus, encourages researchers across the world to take up similar assessments with the available data.

During disasters, people share their thoughts and emotions on social media and also provide information about the event. Mining the social media messages and updates can be helpful in understanding the emotional state of people during such unforeseen events as they are real-time data. The objective of this review is to explore the feasibility of using social media data for mental health surveillance as well as the techniques used for determining mental health using social media data during disasters. PubMed, PsycINFO, and PsycARTICLES databases were searched from 2009 to November 2018 for primary research studies. After screening and analyzing the records, 18 studies were included in this review. Twitter was the widely researched social media platform for understanding the mental health of people during a disaster. Psychological surveillance was done by identifying the sentiments expressed by people or the emotions they displayed in their social media posts. Classification of sentiments and emotions were done using lexicon-based or machine learning methods. It is not possible to conclude that a particular technique is the best performing one, because the performance of any method depends upon factors such as the disaster size, the volume of data, disaster setting, and the disaster web environment.

The current study indicates that elevated levels of sST2 might be a suitable biomarker to evaluate the risk of future adverse cardiovascular events in ACS patients with diabetes.

Background This study describes regional differences and determinants on key noncommunicable disease (NCD) risk factors in adults from the National NCD Monitoring Survey (NNMS) across six geographic regions of India. Methods The NNMS was a cross-sectional multistage cluster survey conducted in 2017–18, on a representative sample of 300 urban and 300 rural primary sampling units (PSU) covering 20 households per PSU. One adult aged 18–69 years per household was selected using the KISH grid. Globally standard survey tools were adapted for data collection. To arrive at regional estimates, the country was divided into six regions (south, north, central, west, east and northeast) based on the distribution of a national sample. The results are presented as proportion with 95% confidence intervals (CI). Univariable and multivariable logistic regression analyses were performed to identify NCD risk factor determinants significant in the regions. A p-value < 0.05 was considered for statistical significance. Results The overall survey response rate was 96.3%. The prevalence of current tobacco (45.7%) and alcohol use (22.3%) was significantly high in the northeast region. The highest proportion of adults from northern India showed low levels of physical activity (49.6%). The prevalence of metabolic risk factors — obesity (12.5%), raised fasting blood glucose (21.2%) and raised blood pressure (35.6%) was highest in south India. The prevalence of raised blood pressure was high in north India (35.2%) similar in proportion to south India. Clustering of ≥3 risk factors (50.1%) and ten-year CVD risk of ≥30% or with existing CVD (18.1%) was highest in south India when compared to other regions. Older age, urban residents, alcohol consumption and overweight/obesity were significantly associated with higher odds of raised blood pressure and raised fasting blood glucose. Conclusion The NNMS presents variations in NCD risk factors within the regions of India. It contributes to robust evidence for strengthening interventions and monitoring the progress in reducing NCDs and their associated risk factors.