Association between risk factors and migraine in Pakistani females.

BACKGROUND: Migraine is a typical cripple issue of the brain identified with cerebral pain which is an indication of numerous health conditions. About 18% of women (27 million) and 6% of men (10 million) are afflicted by migraine in the United States. Based on a case-control study, to explore the different risk factors, causing migraine in females and examine the association between risk factors and migraine. METHODS: A sample of 1055 individuals were selected in different areas of Lahore from September 2019 to March 2020. The information was obtained by using the direct interview method and questionnaire method. Descriptive analysis, bivariate analysis and binary logistic regression analysis were carried out in data analysis. RESULTS: Among 1055 individuals 740 cases and 315 controls were included. In a binary logistic regression model, physical activities, stress, summer season, menstruation and morning were the risk factors that cause migraine and these were found to be positively significant with the odds ratios and 95% confidence interval of odds ratios (1.399; 1.122-1.746), (1.510; 1.187-1.922), (1.595; 1.374-1.851), (1.513; 1.247-1.836) and (1.309; 1.028-1.665) respectively. Nausea, isolation and back head pain were caused by migraine and these were found positively significant with the odds ratios and 95% confidence interval of odds ratios(1.290; 1.122-1.484), (1.882; 1.617-2.190) and (1.285; 1.123-1.471) respectively. CONCLUSIONS: Stress, physical Activities and Menstruation increase the risk of migraine but weight loss, Breakfast, lunch, thirst, injury and Second trimester during pregnancy reduce the risk of migraine.

Forecasting the daily deaths caused by COVID-19 using ARIMA model.

Coronavirus disease (COVID-19) pandemic has recently become a global health crisis. On the basis of this study the data reported from ten different countries on confirmed daily deaths caused by COVID-19. By fitting the linear regression models based on the data from ten countries to find the relationship between the new cases and deaths reported daily. We also used the autoregressive integrated moving average model (ARIMA) to predict the potential number of daily deaths caused by COVID-19 in these countries in the next 3 Months. The R2 value obtained for Iran (0.24) implies that 24% of daily deaths correspond to the daily cases. The R2of Pakistan 0.662 which indicates that 66.2% of daily deaths are explained by our predictor variable. In Turkey 70.2% of daily deaths are explained by daily cases and India recorded the highest number of deaths while UAE had the lowest number of deaths. Our results suggest that the pandemic is under control in China, UAE and Australia. Pakistan, Iran, Germany and Italy however, showed an upward trend in the spread of the disease, which may correlate with a high increase in death rate as the data indicated.