The present study explores the association between weather and COVID-19 pandemic in Delhi, India. The study used the data from daily newspaper releases from the Ministry of Health and Family Welfare, Government of India. Linear regression was run to understand the effect of the number of tests, temperature, and relative humidity on the number of COVID-19 cases in Delhi. The model was significantly able to predict number of COVID-19 cases, F (4,56) = 1213.61, p \ 0.05, accounting for 99.4% of the variation in COVID-19 cases with adjusted R 2 = 98.8%. Maximum Temperature, average temperature and average relative humidity did not show statistical significance. The only number of tests was significantly associated with COVID-19 cases.

Background: Throught the world, More than 75% of adults with type 2 diabetes mellitus (T2DM) live in low and middle-income countries. Amongst which 69.2 million of these adults live in India. Its been shown that, as level of physical activity increases, risk of developing T2DM decreases by 15-60%. Many studies are conducted to find the risk of development of T2DM in the coastal areas of Karnataka. However, the screening of people living in Udupi was not carried out.Aim: To find out the risk for the development of T2DM using IDRS and physical activity levels in Udupi population.Material and Methods: In the current study, we included participants who were asymptomatic and undiagnosed to be having T2DM. The participants age ranged between 30–65 yrs. Participants with the history of any neurological conditions and women who were pregnant at the time of screening were excluded. We recorded random blood glucose levels of the participants following which the risk score was obtained using the Indian Diabetes Risk Score (IDRS) and the participants were classified as high risk (score ≥60), moderate risk score (30–50) and low risk (score <30). The level of physical ­activity was measured using Global Physical Activity Questionnaire.Results: The study included 23,960 participants from Udupi district, Karnataka. Based on IDRS risk stratification, 1.5%, 17.9%, 27.5% of the participants with the age ange of 30–35 yrs, 36–50 yrs and more than 50 yrs respectively had higher risk of developing T2DM. According to GPAQ score 14% of the participants were following sedentary lifestyle, 27.6% of the were minimally active, 53.7% were very active, and 4.6% were highly active.Conclusion: From the current study we conclude that 46.9% of participants had a higher risk of developing T2DM in future who are living in Udupi district.

This study was planned to estimate the proportion of confirmed multi-drug resistance pulmonary tuberculosis (TB) cases out of the presumptive cases referred to DTC (District Tuberculosis Center) Jodhpur for diagnosis; to identify clinical and socio-demographic risk factors associated with the multidrug-resistant pulmonary TB and to assess the spatial distribution to find out clustering and pattern in the distribution of pulmonary TB with the help of Geographic Information System (GIS). In the Jodhpur district, 150 confirmed pulmonary multi-drug resistant tuberculosis (MDR-TB) cases, diagnosed by probe-based molecular drug susceptibility testing method and categorized as MDR in DTC's register (District Tuberculosis Center), were taken. Simultaneously, 300 control of confirmed non-MDR or drug-sensitive pulmonary TB patients were taken. Statistical analysis was done with logistic regression. In addition, for spatial analysis, secondary data from 2013-17 was analyzed using Global Moran's I and Getis and Ordi (Gi*) statistics. In 2012-18, a total of 12563 CBNAAT (Cartridge-based nucleic acid amplification test) were performed. 2898 (23%) showed M. TB positive but rifampicin sensitive, and 590 (4.7%) showed rifampicin resistant. Independent risk factors for MDR TB were ≤60 years age (AOR 3.0, CI 1.3-7.1); male gender (AOR 3.4, CI 1.8-6.7); overcrowding (AOR 1.6, CI 1.0-2.7); using chulha (smoke appliance) for cooking (AOR 2.5, CI 1.2-4.9), past TB treatment (AOR 5.7, CI 2.9-11.3) and past contact with MDR patient (AOR 10.7, CI 3.7-31.2). All four urban TUs (Tuberculosis Units) had the highest proportion of drug-resistant pulmonary TB. There was no statistically significant clustering, and the pattern of cases was primarily random. Most of the hotspots generated were present near the administrative boundaries of TUs, and the new ones mostly appeared in the area near the previous hotspots. A random pattern seen in cluster analysis supports the universal drug testing policy of India. Hotspot analysis helps cross administrative border initiatives with targeted active case finding and proper follow-up.

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