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Importance: Corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pandemic claiming millions of lives since the first outbreak was reported in Wuhan, China during December 2019. It is thus important to make crosscountry comparison of the relevant rates and understand the socio-demographic risk factors. Methods: This is a record based retrospective cohort study. Table 1 was extracted from https://www.worldometers.info/coronavirus/ and from the Corona virus resource center (Table 2, Figures 1-3), Johns Hopkins University. Data for Table 1 includes all countries which reported >1000 cases and Table 2 includes 20 countries reporting the largest number of deaths. The estimation of CFR, RR and PR of the infection, and disease pattern across geographical clusters in the world is presented. Results: From Table 1, we could infer that as on 4 th May 2020, COVID-19 has rapidly spread worldwide with total infections of 3,566,423 and mortality of 248,291. The maximum morbidity is in USA with 1,188,122 cases and 68,598 deaths (CFR 5.77%, RR 15% and PR 16.51%), while Spain is at the second position with 247,122 cases and 25,264 deaths (CFR 13.71%, RR 38.75%, PR 9.78%). Table 2 depicts the scenario as on 8 th October 2020, where-in the highest number of confirmed cases occurred in US followed by India and Brazil (cases per million population: 23,080, 5007 & 23,872 respectively). For deaths per million population: US recorded 647, while India and Brazil recorded 77 and 708 respectively. Conclusion: Studying the distribution of relevant rates across different geographi

Introduction: In World Health Organization's(WHO) South-East Asia region(SEAR), India accounts for >2/3rd of total deaths due to non-communicable diseases(NCD). Annually, NCDs account for ~60% of all deaths in India. Apart from the known risk factors, an individual's physical environment, behavioral and biological susceptibility are known to associated with NCDs. Social factors tend to create barriers for accessing healthcare among the poor people. Objectives: i)To screen and diagnose hypertension and diabetes among individuals aged >30 years, and its associated risk factors such as obesity and tobacco consumption. ii) To deliberate on the social determinants influencing this survey, and suggest suitable recommendations for the National Programme for prevention and control of Cancer, Diabetes, Cardiovascular disease and Stroke (NPCDCS). Methods: As a component of NPCDCS, the present survey was conducted in a few urban slums of Bangalore city during 2010. The collaborators for the conduct of this survey include the Ministry of health and family welfare, Director of health and family welfare services and Medical colleges in Bangalore city. Results: In our study, we found a prevalence proportion of 21.5% for hypertension, 13.8% for diabetes and 30.4% were co-morbid with both the diseases. Consumption of tobacco(any form) was present in 5.1% of the study subjects, overweight among 32.4% and obesity among 20.0%. The study population comprises 18.96% of the source, and the main reason for inadequate utilization was lack of Programmatic awareness. Conclusion: NPCDCS program needs to conceptualize the relevant social factors which determine access to screening and diagnostic healthcare services, including behavior change initiatives. For Program effectiveness, changes at the level of healthcare system need to adopted.

Introduction Cancer patients commonly present with antecedent addiction to tobacco consumption. Our study describes the characteristics of this substance use. Following the diagnosis of cancer, continued consumption of tobacco results in reduced tolerance to treatment, failure of treatment, tumor progression, other primary tumors, secondary cancers, and poor quality of life. The aim of our study is to enumerate the clinico-social aspects of tobacco consumption among cancer patients. Methods This cross-sectional study includes 100 cancer patients admitted to Healthcare Global cancer hospital, Bangalore, India. The study subjects were assessed for tobacco consumption, as well as other substance use such as intake of alcohol. We assessed various dimensions of exposure to tobacco consumption such as duration, intensity, and cumulative dose as independent risk factors for cancer. Results Among the study subjects, 46.2% were found to smoke filter cigarettes. The mean duration of tobacco consumption among beedi users was found to be longer (25.9 years, SD: 14.4). When stratified for exclusive consumption, the mean durations were as follows: beedis (29 ± 14.4 years), cigarettes (23.8 ± 13.3 years), and chewing (15.9 ± 9.6 years). Along with tobacco, a large proportion (59.3%) of patients consumed alcohol as well. After attempts to quit, 89.01% patients had reversal of tobacco substance use. The data did not show significance for duration, intensity, and cumulative dose of tobacco consumption. Conclusion The diagnosis of cancer is a life-altering event, which results in higher motivation to quit the use of tobacco. Smoking cessation initiatives can reduce the risk of developing tobacco-related malignancies.

Introduction: The narrated NCD program is being implemented by KHSDRP in collaboration with the World Bank, New Delhi. This pilot project will involve NCD education and mobilization at the community level, provision of screening, and treatment services at the primary health-care level and strengthening diagnostic, specialist treatment services at the secondary and tertiary levels of care. This paper lists the activities of the diabetes component of the NCD program, and the prioritization matrix describes weighting of the important criteria. Materials and Methods: “Precede-Proceed” planning model is the better fit for our Diabetes Program. The prioritization matrix will enable weighting of each criterion against another (comparing each row heading consecutively with all the column headings), in order to decide upon its importance. Results: The matrix shows that awareness activities, beneficiary enumeration, mobilization of beneficiary, and behavior change interventions are the important criteria for this health promotion program. Discussion: The matrix shows that a large proportion of the budget should be invested in field-related activities for the success of the Program. Conclusion: Prioritization matrix enables the examination of all potential opportunities in a Program, by ranking the opportunities by two characteristics: importance and changeability. It systematically compares the choices through selection, weighting, and application of criteria.