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Among other diseases, Covid 19 creates a critical situation around the world. Five layers have been recorded so far, resulting in the loss of millions of lives in different countries. The virus was thought to be contagious, so the government initially severely forced citizens to keep a distance from each other. Since then, several vaccines have been developed that play an important role in controlling mortality. In the case of Covid-19 mortality, the government should be forced to take significant steps in the form of lockdown, keeping you away or forcing citizens to vaccinate. In this paper, modeling of Covid-19 death rates is discussed via probability distributions. To delineate the performance of the best fitted model, the mortality rate of Pakistan and Afghanistan is considered. Numerical results conclude that the NFW model can be used to predict the mortality rate for Covid-19 patients more accurately than other probability models. [ABSTRACT FROM AUTHOR]

Despite considerable progress in the field of education science, there is currently no consensus on the components that define inclusive and equitable quality education, how they are articulated with one another, and what are the best interventions to foster inclusive and equitable quality education. Current research investigates separately components of what appears to be a complex dynamic system with feedback interactions. To characterize this system and identify structures that encompass inclusive and equitable quality education, we used a community-based system dynamics approach. This approach hypothesizes that community perceptions of the local school system is essential to define it. We therefore conducted 648 participatory Group Model Building workshops with school stakeholders (children, teachers, parents and members of school management committees) resulting in as many models in 99 schools of Afghanistan and Pakistan. To identify common components across models built by participants in two waves of schools' model building workshops, we applied techniques from multivariate analysis of ecological communities. Even across wide differences in participants' situations and roles in the educational process, their models expressed a common reinforcing feedback loop which connected child inclusive and equitable quality education to two other components: 1) child engagement in and motivation for education, and 2) child attendance. Increases in any of these three components were perceived to drive increases in the others. We also found that child focus on learning was commonly expressed as interacting with this generic structure. Any educational reform should simultaneously and primarily embrace learners' diversity, combine policy principles of ensuring easy equitable access to foster attendance, and promote student interest and engagement in learning through child centered pedagogy and non-discriminatory teaching practices while giving school communities power for implementation. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic has become a global major public health concern. Examining the meteorological risk factors and accurately predicting the incidence of the COVID-19 pandemic is an extremely important challenge. Therefore, in this study, we analyzed the relationship between meteorological factors and COVID-19 transmission in SAARC countries. We also compared the predictive accuracy of Autoregressive Integrated Moving Average (ARIMAX) and eXtreme Gradient Boosting (XGBoost) methods for precise modelling of COVID-19 incidence. We compiled a daily dataset including confirmed COVID-19 case counts, minimum and maximum temperature (°C), relative humidity (%), surface pressure (kPa), precipitation (mm/day) and maximum wind speed (m/s) from the onset of the disease to January 29, 2022, in each country. The data were divided into training and test sets. The training data were used to fit ARIMAX model for examining significant meteorological risk factors. All significant factors were then used as covariates in ARIMAX and XGBoost models to predict the COVID-19 confirmed cases. We found that maximum temperature had a positive impact on the COVID-19 transmission in Afghanistan (β = 11.91, 95% CI: 4.77, 19.05) and India (β = 0.18, 95% CI: 0.01, 0.35). Surface pressure had a positive influence in Pakistan (β = 25.77, 95% CI: 7.85, 43.69) and Sri Lanka (β = 411.63, 95% CI: 49.04, 774.23). We also found that the XGBoost model can help improve prediction of COVID-19 cases in SAARC countries over the ARIMAX model. The study findings will help the scientific communities and policymakers to establish a more accurate early warning system to control the spread of the pandemic. [ABSTRACT FROM AUTHOR]

In recent years, progress in information and communication technology (ICT) has caused many structural changes such as reorganizing of economics, globalization, and trade extension, which leads to capital flows and enhancing information availability. Moreover, ICT plays a significant role in development of each economic sector, especially during liberalization process. Growth economists predict that economic growth is driven by investments in ICT. However, empirical studies on this issue have produced mixed results, regarding to different research methodology and geographical configuration of the study. This paper examines the impact of Information and Communication Technology (ICT) use on economic growth using the Generalized Method of Moments (GMM) estimator within the framework of a dynamic panel data approach and applies it to 159 countries over the period 2000 to 2009. The results indicate that there is a positive relationship between growth rate of real GDP per capita and ICT use index (as measured by the number of internet users, fixed broadband internet subscribers and the number of mobile subscription per 100 inhabitants). We also find that the effect of ICT use on economic growth is higher in high income group rather than other groups. This implies that if these countries seek to enhance their economic growth, they need to implement specific policies that facilitate ICT use. [ABSTRACT FROM AUTHOR]