DISTRICT WISE ANALYSIS OF COVID-19 PANDEMIC TRENDS DURING SECOND WAVE IN THE STATE ANDHRA PRADESH, INDIA USING SEIR-RGS MODEL

— Andhra Pradesh is one of the south Indian states in India and having 13 districts. This is one of the most Covid-19 effected state in India during first and second waves. In India district is the major administrative block for implementing government policies and schemes under control of district collector. So, estimating or forecasting trends in district level more important than state wise or entire country wise. In this paper we are proposing Susceptible, Exposed, Infected and Recovered – Regression and Grid Search (SEIR-RGS) model for analyzing Covid -19 district wise trends during second wave. The SEIR-RGS, initially collects daily wise covid data for each district from Department of Health, medical and family welfare, AP and estimates the model parameters like contact rate, incubation rate and recovery rate. To calculate recovery rate the proposed model uses regression technique between daily active cases vs cumulative recoveries. The present model uses two phases for estimating contact rate and incubation rate using grid search approach. After that the proposed method calculates the infectious period, incubation period and basic reproduction of infection in all 13 districts to analyze trends in the state during second wave and also to predict possibility of third wave in each district.

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TRENDS AND PREDICTION OF PANDEMIC COVID-19 SITUATION IN UTTAR PRADESH, INDIA

EPRA International Journal of Multidisciplinary Research (IJMR) ◽

10.36713/epra4603 ◽

2020 ◽

pp. 19-24

Author(s):

Suraj kumar ◽

Arushi Kumar ◽

Gowrishankar Potturi ◽

Rajkumar ◽

K.B.Ranjeet Singh Chaudhary

Keyword(s):

Migrant Workers ◽

Recovery Rate ◽

Transmission Rate ◽

Uttar Pradesh ◽

Good Health ◽

Family Welfare ◽

Rapid Testing ◽

Indian States ◽

Recovery Rates ◽

Breathing Exercises

COVID-19 is a disease caused by coronavirus that was first identified in Wuhan, China and was declared pandemic. Uttar Pradesh is one of the largest Indian states which is highly populous. There were 81999 confirmed cases in India as on 15th May, 2020 of which 3902 from Uttar Pradesh. Data of confirmed cases, recoveries and death trolls were collected from Ministry of Health and Family welfare and other reliable website. There is 53.1% recovery rate in the COVID-19 cases in Uttar Pradesh. A good health infra-structure, planning, high immunity in population, adequate isolation/ quarantine facilities, confrontational testing has increased recovery rates. Institutes like UPUMS are providing Ayurvedic preparation Raj Nirwan Ras (RNR) and nutritious diet along with breathing exercises showing high recovery rates. This type of treatment model could be implemented in other hospitals for a good and faster recovery rate. The prediction of transmission rate in next 30 days in Uttar Pradesh is not feasible as the number of migrant workers influx, people attending religious congregation, citizens not following lock down properly, and rapid testing could increase the number of confirmed cases. KEYWORDS: Uttar Pradesh, COVID-19, Raj Nirwan Ras, Recovery rate

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Exploring the Usefulness of Meteorological Data for Predicting Malaria Cases in Visakhapatnam, Andhra Pradesh

Weather Climate and Society ◽

10.1175/wcas-d-19-0029.1 ◽

2020 ◽

Vol 12 (2) ◽

pp. 323-330

Author(s):

Meena Sehgal ◽

Sujit Ghosh

Keyword(s):

Andhra Pradesh ◽

Meteorological Parameters ◽

Positive Impact ◽

Meteorological Data ◽

Additive Model ◽

Smoothing Splines ◽

Maximum Temperature ◽

Family Welfare ◽

Surveillance Program ◽

Model Parameters

AbstractMalaria and dengue fever are among the most important vectorborne diseases in the tropics and subtropics. Average weekly meteorological parameters—specifically, minimum temperature, maximum temperature, humidity, and rainfall—were collected using data from 100 automated weather stations from the Indian Space Research Organization. We obtained district-level weekly reported malaria cases from the Integrated Disease Surveillance Program (IDSP), Department of Health and Family Welfare, Andhra Pradesh, India, for three years, 2014–16. We used a generalized linear model with Poisson distribution and default logarithm-link to estimate model parameters, and we used a quasi-Poisson method with a generalized additive model that uses nonparametric regression with smoothing splines. It appears that higher minimum temperatures (e.g., >24°C) tend to lead to higher malaria counts but lower values do not seem to have an impact on the malaria counts. On the other hand, higher values of maximum temperature (e.g., >32°C) seem to negatively affect the malaria counts. The relationships with rainfall and humidity appear to be not as strong once we account for smooth (weekly) trends and temperatures; both smooth curves seem to hover around zero across all of their values. We note that a rainfall amount between 40 and 50 mm seems to have a positive impact on malaria counts. Our analyses show that the incremental increase in meteorological parameters does not lead to an increase in reported malaria cases in the same manner for all of the districts within the same state. This suggests that other factors such as vegetation, elevation, and water index in the environment also influence disease occurrence.

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What Impact Have SARS-CoV-2/Covid-19 Pandemic on the Reproductive and Child Health Programme (Immunisation, Maternal Health, Family Planning) of Andhra Pradesh in India over the 3 months after nationwide Lock down announcement in March 2020? Immunisation? Maternal Health? Family Planning?

10.31219/osf.io/dphga ◽

2021 ◽

Author(s):

Piyush Kumar

Keyword(s):

Family Planning ◽

Child Health ◽

Andhra Pradesh ◽

Secondary Data ◽

The State ◽

Family Welfare ◽

Reproductive And Child Health ◽

Child Health Programme ◽

And Child Health ◽

Health Programme

ABSTRACTBackground: The delivery of reproductive and child health services is of utmost importance and prime concern in India particularly states like Andhra Pradesh with limited resources, poor infrastructure and huge demand on healthcare system. The SARS-CoV-2 pandemic had presented a challenge even for developed healthcare systems around the world. Objectives: The main aim of this research is to find out Impact of SARS-CoV-2 pandemic on the Reproductive and Child Health Programme of Andhra Pradesh in India over the 3 months after Lock down imposition countrywide in March 2020. Settings & Design: Different indicators group of RCH programme (immunisation, maternal & child health, family planning) for state of Andhra Pradesh were collected and compared from previous year. Materials & Methodology: Secondary data from HMIS of Ministry of Health & Family Welfare Government of India for 2019 & 2020 were taken for analysing and understanding impact of pandemic on RCH programme over 3 months after lock down viz. April/May/June 2020. The data obtained is analysed by using Microsoft Office software. Result: The analysis of secondary data obtained from HMIS of Ministry of Health & Family Welfare website for RCH programme of the state of Andhra Pradesh shows that the lock down period & initial early phase of SARS-CoV-2 pandemic have a negative impact over the delivery of health services as well as the indicators are also affected negatively. Besides the pandemic the state is also having lack of resources, manpower, poor infrastructure as well as positive deviance at community level. These are the barriers in fact beside the epidemic. It seems that there is lack of proper plan to deal with such pandemic situation. Conclusion: The State of Andhra Pradesh has taken various steps and strategy but it seems to be insufficient to give the desired results. The barriers of healthcare system and delivery of services should be rectified added with a proper dynamic plan to carry on usual health delivery services even in pandemics. The state of Andhra Pradesh needs to develop an exclusive plan such as separate RCH cadre to tackle such situations. Keywords- Health, Decrease, Pandemic, Services/service

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Two-Stage Water Jet Landing Point Prediction Model for Intelligent Water Shooting Robot

Sensors ◽

10.3390/s21082704 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2704

Author(s):

Yunhan Lin ◽

Wenlong Ji ◽

Haowei He ◽

Yaojie Chen

Keyword(s):

Pitch Angle ◽

Back Propagation ◽

Water Jet ◽

The State ◽

Model Parameters ◽

Propagation Time ◽

Back Propagation Algorithm ◽

Angle Error ◽

Landing Point ◽

Propagation Algorithm

In this paper, an intelligent water shooting robot system for situations of carrier shake and target movement is designed, which uses a 2 DOF (degree of freedom) robot as an actuator, a photoelectric camera to detect and track the desired target, and a gyroscope to keep the robot’s body stable when it is mounted on the motion carriers. Particularly, for the accurate shooting of the designed system, an online tuning model of the water jet landing point based on the back-propagation algorithm was proposed. The model has two stages. In the first stage, the polyfit function of Matlab is used to fit a model that satisfies the law of jet motion in ideal conditions without interference. In the second stage, the model uses the back-propagation algorithm to update the parameters online according to the visual feedback of the landing point position. The model established by this method can dynamically eliminate the interference of external factors and realize precise on-target shooting. The simulation results show that the model can dynamically adjust the parameters according to the state relationship between the landing point and the desired target, which keeps the predicted pitch angle error within 0.1°. In the test on the actual platform, when the landing point is 0.5 m away from the position of the desired target, the model only needs 0.3 s to adjust the water jet to hit the target. Compared to the state-of-the-art method, GA-BP (genetic algorithm-back-propagation), the proposed method’s predicted pitch angle error is within 0.1 degree with 1/4 model parameters, while costing 1/7 forward propagation time and 1/200 back-propagation calculation time.

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Interstate disparities in the performances in combatting COVID-19 in India: efficiency estimates across states

BMC Public Health ◽

10.1186/s12889-020-10051-6 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Shrabanti Maity ◽

Nandini Ghosh ◽

Ummey Rummana Barlaskar

Keyword(s):

Disease Management ◽

Recovery Rate ◽

Tamil Nadu ◽

Health Determinants ◽

Stochastic Production Frontier ◽

Exogenous Variables ◽

Indian States ◽

Secondary Sources ◽

Comparative Efficiency ◽

Long Run

Abstract Background Currently, the novel coronavirus or COVID-19 pandemic poses the greatest global health threat worldwide, and India is no exception. As an overpopulated developing country, it is very difficult to maintain social distancing to restrict the spread of the disease in India. Under these circumstances, it is necessary to examine India’s interstate performances to combat COVID-19. This study aims to explore twin objectives: to investigate the comparative efficiency of Indian states to combat COVID-19 and to unfold the factors responsible for interstate disparities in the efficiency in combatting COVID-19. Methods The stochastic production frontier model was utilized for data analysis. The empirical analysis was facilitated by the inefficiency effects model, revealing the factors that influence interstate variability in disease management efficiency. Three types of variables, namely, output, inputs, and exogenous, were used to measure health system efficiency. The relevant variables were compiled from secondary sources. The recovery rate from COVID-19 was the output variable and health infrastructures were considered as the input variable. On the contrary, the non-health determinants considered to have a strong influence on the efficiency of states’ disease management, but could not be considered as input variables, were recognised as exogenous variables. These exogenous variables were specifically used for the inefficiency analysis. Results The empirical results demonstrated the existence of disparities across Indian states in the level of efficiency in combatting COVID-19. A non-trivial outcome of this study was that Tamil Nadu was the best performer and Manipur was the worst performer of the investigated states. Variables such as elderly people, sex ratio, literacy rate, population density, influenced the efficiency of states, and thus, affected the recovery rate. Conclusion This study argues for the efficient utilisation of the existing health infrastructures in India. Simultaneously, the study suggests improving the health infrastructure to achieve a long-run benefit.

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Status of Agricultural Credit and Indebtedness in India: An Analysis

The Indian Economic Journal ◽

10.1177/00194662211015383 ◽

2021 ◽

pp. 001946622110153

Author(s):

Suresh Kumar Maurya ◽

Neha Vishwakarma

Keyword(s):

Andhra Pradesh ◽

Uttar Pradesh ◽

Medium Term ◽

Agricultural Credit ◽

Indian States ◽

Agricultural Household ◽

Agricultural Households ◽

Size Groups ◽

Jel Code ◽

Land Size

This article attempts to analyse status of agricultural credit and indebtedness in India. The objectives of the study are as follows: (a) to study a comparison of flow of total institutional agricultural credit among different land size groups at all India level; (b) to study a comparison of indebtedness of agricultural households between different size classes of land possessed at both states and all India level and (c) to analyse incidence of indebtedness in major Indian states. It is concluded that mostly, short- and medium-term loans of agricultural purposes are taken for marginal land size groups in India. The percentage of indebted agricultural households to total agricultural household increases as land size increases. The percentage of holdings is less than percentage of indebted agricultural households in Punjab, Uttar Pradesh, Andhra Pradesh, West Bengal, Karnataka, Odisha and Rajasthan. JEL Code: Q14

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Is Expenditure by States for Development Compromised to Ensure Compliance of Fiscal Targets? A Study of Indian States

Arthaniti-Journal of Economic Theory and Practice ◽

10.1177/0976747920966871 ◽

2020 ◽

pp. 097674792096687

Author(s):

H. K. Dwivedi ◽

Sudip Kumar Sinha

Keyword(s):

The State ◽

Capital Account ◽

General Category ◽

Fiscal Deficit ◽

Fiscal Consolidation ◽

Indian States ◽

Corrective Measures ◽

Additional Amount ◽

Three Phases

This article examines the interlinkage between fiscal consolidation targets and states’ developmental expenditure under capital account. While fiscal consolidation targets have enabled states to take corrective measures to reduce deficit under the revenue account, the effect of the same is studied on developmental expenditure under capital account. For analysis, the fiscal deficit and developmental expenditure under the capital account have been compared with the fiscal deficit targets and general category states’ average benchmarks for fiscal indicators for three phases (corresponding to the periods of three finance commissions). It is argued, that, while fiscal consolidation has helped to improve the state finances, the stringent fiscal targets have further reduced the developmental expenditure under capital account. In view of this, it is suggested that the states, which are historically stressed, should be allowed to borrow an additional amount of 0.25 per cent of GSDP each year over and above the existing limit, provided these states make efforts to reduce deficit under revenue account and spend the extra borrowings on developmental expenditure under capital account.

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Insights from Genomes and Genetic Epidemiology of SARS-CoV-2 isolates from the state of Andhra Pradesh

Epidemiology and Infection ◽

10.1017/s0950268821001424 ◽

2021 ◽

pp. 1-11

Author(s):

Pallavali Roja Rani ◽

Mohamed Imran ◽

J. Vijaya Lakshmi ◽

Bani Jolly ◽

S. Afsar ◽

...

Keyword(s):

Genetic Epidemiology ◽

Andhra Pradesh ◽

The State

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The Second Wave of COVID-19: Clinical Pharmacy Services During a Field Hospital Operation

Hospital Pharmacy ◽

10.1177/00185787211032361 ◽

2021 ◽

pp. 001857872110323

Author(s):

Jessica Mazzone ◽

Krysta Shannon ◽

Richard Rovelli ◽

Racha Kabbani ◽

Angel Amaral ◽

...

Keyword(s):

Clinical Pharmacy ◽

The State ◽

Pharmacy Services ◽

Newly Diagnosed ◽

Field Hospital ◽

Clinical Role ◽

Diagnosed Diabetes ◽

Newly Diagnosed Diabetes ◽

Second Wave

The second wave of COVID-19 emerged in the late fall months in the state of Massachusetts and inadvertently caused a rise in the number of cases requiring hospitalization. With a field hospital previously opened in central Massachusetts during the Spring of 2020, the governor decided to reimplement the field hospital. Although operations were effectively accomplished during the first wave, the reimplementation of the field hospital came with its new set of challenges for operating a satellite pharmacy. Experiences gathered include new pharmacy operation workflows, the clinical role of pharmacy services, introduction of remdesivir treatment, and pharmacy involvement in newly diagnosed diabetes patients requiring insulin teaching. Pharmacy services were successful in adapting to the rapidly growing number in patients with a total of over 600 patients served in a course of 2 months.

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