BACKGROUND Child Immunisation is an important activity and is carried out at all levels of health care services. At Primary Health Centres and subcentres, vaccine requirement is calculated by fixed formula. It is difficult to estimate vaccine requirement where denominator is not known as in the case of the Government Medical College. The objective of this study is to forecast Measles vaccine requirement by using time series analysis, at Government Medical College, Latur. MATERIALS AND METHODS The present study was record based; undertaken at Government Medical College, Latur. The data regarding Measles vaccine used during the years 2009-10 to 2014-15 was taken from immunisation book. This month wise data was fed in MS-excel and analysed using software SPSS version 21.0. Method used for time series analysis was Expert Modeller for best model fit. Time series analysis and forecasting was done using best-fit model i.e. Simple seasonal model for measles vaccine. RESULTS A total of 8015 doses of measles vaccine were given during the years 2009-10 to 2014-15 at Government Medical College, Latur. Ljung-Box Q statistics was not significant. Forecasting for Measles vaccine was done up to 2018-19. The vaccine requirement calculated for August 2018 is 134 with 225 and 42 as upper and lower confidence level. It was 136 for February 2019 with 231 and 40 as upper and lower confidence level respectively. CONCLUSION Simple seasonal model of Time series analysis can be used to forecast Measles vaccine requirement at Medical Colleges.
Background: Globally, micronutrient use has increased over the last few decades for disease prevention and holistic health. This article has analyzed the worldwide search trends of micronutrients in the Google Trends (GT) platform to understand the significance and correlation of search trends, comparing the search interests across countries and recognizing the factors involved.Methods: Specific search terms were used to identify the search trends of micronutrients in the GT platform. Statistical analysis was done to evaluate the outcomes of significance and correlation of search terms from 2004 to 2021 by using statistical softwares.Results: There was a rise in searches for micronutrients vitamin D, vitamin C, zinc, & iron from 2004 to June 2021 with a steep increase during 2020 correlating with the COVID-19 pandemic. A stable search has been reported in iron searches. Significance and correlation of vitamin D, vitamin C, zinc, & iron over the years and search interest popularity score of countries for micronutrient searches have been described. Conclusions:The GT tool can be a necessary tool for healthcare communities and government sectors to understand people's interests, necessities and respond to their concerns accordingly, thus helping us promote population-centric awareness and achieve better evidence-based outcomes.
Objective: COVID-19 has varying impact on different groups of people based on age, gender, race and comorbidities. Although the implications of COVID-19 on chronic pulmonary and cardiovascular disease have been extensively studied, the impact on neurological disease remains unclear. We attempt to identify the outcome and challenges of COVID-19 in patients with chronic neurological conditions. Methods: We conducted a systematic review and meta-analysis of 15 studies and 11,011 patients to compare composite poor outcome and mortality between patients with and without neurological comorbidities. We also analyzed the different clinical presentations and outcome of COVID-19 in different neurological conditions. Results: We found a markedly higher incidence of composite poor outcome (Odds Ratio: 5.57, 95% CI: 3.81-8.12, P = 0.02) and a higher mortality (Odds Ratio: 6.47, 95% CI: 3.94 - 10.63, P = 0.008) among patients with pre-existing neurological disease, and no significantly different outcomes between patients with cerebrovascular disease and dementia. Linear Meta-regression analysis revealed that the impact of chronic neurological disease on COVID-19 was independent of chronic cardiovascular disease (P=0.406), hypertension (P=0.458), diabetes mellitus (P=0.512), COPD (P=0.281), and advanced age (p=0.066). Conclusion: Patients with chronic neurological disease seem to develop moderate/severe COVID-19 more frequently, and have an increased mortality rate, independent of other comorbidities. They also show atypical clinical presentation in SARS-CoV-2 infection. Advanced age, cognitive dysfunction, immunosuppression, and respiratory muscle weakness might be responsible for the adverse COVID-19 outcomes in these patients.
Context and focusChart 2: Average diurnal temperature of the outdoor temperature and houses with different roof material.Chart 3: Average air temperature measured outdoors and indoors under different roofs (20 data loggers) Key findings• Chart 4 shows the average diurnal variation of indoor temperature in the 20 houses. The indoor temperature between 12 hrs to 16 hrs inside tin roof houses recorded up to 49°C. The temperature peaked in the afternoon in all house types. In general, the indoor room temperature was highest between 12 noon and 4pm in all types of roofs. Chart 4: Diurnal variation of temperature within the different roof types Chart 5: Percentage of individuals reporting heat-related symptoms Chart 6: Major heat-related symptoms reported during the summer of 2016 in the study sample.• Of the 326 individuals interviewed, 152 (47%) individuals reported at least one heat-related symptom; 67% of these were people who resided in tin roof houses. A higher percentage of men (57%) reported heat-related symptoms than women (42%). Among age groups, the 19-45 group (Chart 5) reported more heat-related symptoms as they spend long hours outdoors, performing livelihood activities which expose them to high temperatures and direct sunlight.• The main heat-related symptoms reported during the summer of 2016 in the study sample are: heavy sweating, leg cramps, intense thirst, fatigue and disorientation (Chart 6).
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