Water Shortage Analysis based on Reservoir Surfaces with varying Population and Rainfall for 2011-20 at Egra in Purba Medinipur

Egra is one of the blocks of Purba Medinipur in West Bengal. The northing and easting of Egra are 21.9°N and 87.53°E respectively. The total number of reservoirs is a hundred (100) as of the year 2020. Reservoir water is utilized for irrigation and industrial purpose. According to Census report 2011, it has been observed that the total population in Egra was 345,926 and the growth of population in Egra is 2.25% p.a. In Egra the population density is more than that of West Bengal. This is enhanced many more times in the last decade i.e from 2011 to 2020. In 2011 the total perimeter of the reservoir was 18630.00m with an area of 145513.00 m 2 . But in 2020 total perimeter of reservoirs was 13752.40 m with an area of 115255.40 m2 . So the water content has been reduced in reservoirs of Egra location in Purba Medinipur. Now increases in population, irrigation and industrialization have been taken place in the Egra manifold. So the withdrawing of water from the reservoirs of Egra has been taken place in indiscriminate ways. But the filling up of water of the reservoirs is very low as the amount of precipitation in the entire Purba Medinipur is quite less. From the Indian meteorological department, it has been found that in maximum years from 1991 to 2020 in Purba Medinipur annual rainfall was around1600 mm. So abstraction is more than the recharge of reservoirs. It’s an alarming situation for Egra. If such an indiscriminate usage of water from reservoir for increasing irrigation and industrialization has been taken place then reservoirs will become dry. If irrigation and industrialization are taking place by the withdrawal of groundwater then the ground water table will be diminished. So if groundwater harvesting is adapted to store water in the reservoir to supply water required for irrigation and industrialization then it may be benefitted. Keywords: Reservoir, perimeter, area, irrigation, industrialization, population

A Partition-Based Group Testing Algorithm for Estimating the Number of Infected Individuals

The dangers of COVID-19 remain ever-present worldwide. The asymptomatic nature of COVID-19 obfuscates the signs policy makers look for when deciding to reopen public areas or further quarantine. In much of the world, testing resources are often scarce, creating a need for testing potentially infected individuals that prioritizes efficiency. This report presents an advancement to Beigel and Kasif's Approximate Counting Algorithm (ACA). ACA estimates the infection rate with a number of tests that is logarithmic in the population size. Our newer version of the algorithm provides an extra level of efficiency: each subject is tested exactly once. A simulation of the algorithm, created for and presented as part of this paper, can be used to find a linear regression of the results with R^2 > 0.999. This allows stakeholders and members of the biomedical community to estimate infection rates for varying population sizes and ranges of infection rates.

A modified age-structured SIR model for COVID-19 type viruses

We present a modified age-structured SIR model based on known patterns of social contact and distancing measures within Washington, USA. We find that population age-distribution has a significant effect on disease spread and mortality rate, and contribute to the efficacy of age-specific contact and treatment measures. We consider the effect of relaxing restrictions across less vulnerable age-brackets, comparing results across selected groups of varying population parameters. Moreover, we analyze the mitigating effects of vaccinations and examine the effectiveness of age-targeted distributions. Lastly, we explore how our model can applied to other states to reflect social-distancing policy based on different parameters and metrics.

A control framework to optimize public health policies in the course of the COVID-19 pandemic

The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.

Portugal

This chapter focuses on Portugal and its districted, closed-list proportional representation system of elections to the Assembly of the Republic. The closed party lists imply that individual candidates have little to benefit from cultivating a personal vote. Parties control the order in which their members are elected and can be expected to be relatively free to deploy their personnel in a manner that enhances the collective reputation of the party. On the other hand, Portugal’s electoral system is one in which geographic location of votes matters to seat maximization, because instead of nationwide proportional representation, the country has several regional districts of varying, population density, and district magnitude. The results show some tendency of the major parties to use both the expertise and electoral–constituency models in assigning members to legislative committees, although stronger in the Socialist Party than in the Social Democratic Party.

A fractional complex network model for novel corona virus in China

As is well known the novel coronavirus (COVID-19) is a zoonotic virus and our model is concerned with the effect of the zoonotic source of the coronavirus during the outbreak in China. We present a SEIS complex network epidemic model for the novel coronavirus. Our model is presented in fractional form and with varying population. The steady states and the basic reproductive number are calculated. We also present some numerical examples and the sensitivity analysis of the basic reproductive number for the parameters.