scholarly journals Secondhand smoke in childhood: The world‐wide burden of a major public health‐care problem

2019 ◽  
Vol 55 (11) ◽  
pp. 1397-1398 ◽  
Author(s):  
Giuseppe Lippi ◽  
Camilla Mattiuzzi
Keyword(s):  
Public Health ◽  
Health Care ◽  
Secondhand Smoke ◽  
World Wide ◽  
Public Health Care ◽  
The World

scholarly journals COVID 19 Pandemic: A Real-time Forecasts & Prediction of Confirmed Cases, Active Cases using the ARIMA model & Public Health in West Bengal, India

2020 ◽  
Author(s):  
Dibash Sarkar ◽  
Moinak Biswas
Keyword(s):  
Public Health ◽  
Health Care ◽  
Time Series ◽  
Health Care System ◽  
West Bengal ◽  
Arima Model ◽  
Public Health Care ◽  
Public Health Care System ◽  
The World ◽  
Care System

AbstractBackgroundCOVID-19 is an emerging infectious disease which has been declared a Pandemic by the World Health Organization (WHO) on March 11 2020. This pandemic has spread over the world in more than 200 countries. India is also adversely affected by this pandemic, and there are no signs of slowing down of the virus in coming time. The absence of a vaccine for COVID-19 is making the situation worse for the already overstretched Indian public health care system. As economic burden makes it increasingly difficult for our country to continue imposing control measures, it is vital for states like West Bengal to make predictions using time series forecasting for the upcoming cases, test kits, health care and estimated the requirement of Quarantine centers, isolation beds, ICU beds and ventilators for COVID-19 patients.ObjectiveThis study is forecasting the confirmed and active cases for COVID-19 until August, using time series ARIMA model & Public Health in West Bengal, India.MethodsWe used ARIMA model, and Auto ARIMA model for forecasting confirmed and active cases till the end of August month using time series data of COVID-19 cases in West Bengal, India from March 1, 2020, to June 4, 2020.ResultsWe are expecting that West Bengal will have around 62279 ± 5000 Cases by the end of August based on our forecasts. Meanwhile Maharashtra, Punjab, Gujarat and Delhi (UT) will be the most affected states, having the highest number of active and confirmed cases at the end of August.Discussion and ConclusionThis forecasts show a very crucial situation for West Bengal in coming days and, the actual numbers can go higher than our estimates of confirmed case as Lockdown 5.0 & Unlock 1.0 will be implemented from 1st June 2020 in India, West Bengal will be observing a partial lift of the lockdown and in that case, there will be a surge in the number of daily confirmed and active cases. The requirement of Health care sector needs to be further improved isolation beds, ICUs and ventilators will also be needed to increase in that scenario. Inter State & Intra State Movement restrictions are lifted. Hence, Migrants returning to their homes due to loss of livelihood and income in the lockdown period may lead to a rise in the number of cases, which could not be accounted for in our projections. We suggest more of Public-Private Partnership (PPP) model in the health sector to accommodate COVID-19 patients adequately and reduce the burden of the already overstretched Indian public health care system, which will directly or indirectly affect the States in the time of crisis.

scholarly journals Morbimortalidade por causas externas – acidentes e violência no município de Porto Velho, Rondônia

2011 ◽  
Vol 1 (3) ◽  
pp. 119-123 ◽  
Author(s):  
Maria Inês Ferreira Miranda ◽  
Rosilâine Keffer Delfino ◽  
Quéren Hapuque Carvalho ◽  
Caire Cilene Pereira Pinto ◽  
Mirlene Conceição Silva ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Public Health Care ◽  
Network Services ◽  
The Public ◽  
Department Of Health ◽  
The World ◽  
External Causes ◽  
The City ◽  
Porto Velho

As violências e os acidentes por causas externas representam modernas epidemias que assolam países do mundo inteiro, inclusive o Brasil. O trabalho objetivou analisar os casos de acidentes e violências atendidos na rede de assistência à saúde no município de Porto Velho. Trata-se de uma pesquisa quantitativa retrospectiva documental, na qual foram avaliados os prontuários dos serviços da rede. A análise estatística foi realizada no programa Epi-info 3.5.1. Os resultados identificaram 1.515 casos de acidentes e violência. Desses, 1.200 (79,2%) são de acidentes e 315 (20,8%), de violência. A idade média da população foi de 27,71 anos. O estudo trouxe uma descrição do fenômeno e também revelou a fragilidade da vigilância em saúde.Descritores: Acidentes, Violência, Serviço de Saúde e Morbimortalidade.Morbidity and Mortality from external causes – accidents and violence in Porto Velho, RondôniaThe violence and accidents due to external causes represent modern epidemics affecting countries around the world, including Brazil. The study aimed to analyze the cases of accidents and violence identified in the public health care in the city of Porto Velho. That is a documentary quantitative and retrospective research, in which we evaluated the records of network services. Statistical analysis was performed using Epi Info 3.5.1. Results identified 1515 cases of accidents and violence. Of these 1200 (79.20%) are from accidents and 315 (20.8%), violence. The median age was 27.71 years. The study brought a description of the phenomenon and also revealed the fragility of Health Surveillance.Descriptors: Accidents, Violence, Department of Health and Morbidity.La morbilidad y la mortalidad por causas externas – accidentes y la violencia en Porto Velho, RondôniaLa violencia y los accidentes por causas externas representan las epidemias modernas que afectan a países de todo el mundo, incluyendo Brasil. El estudio tuvo como objetivo analizar los casos de accidentes y la violencia identificadas en el cuidado de la salud pública en la ciudad de Porto Velho.Esta es una investigación documental retrospectiva cuantitativos, en los que se evaluaron los registros de los servicios de red. El análisis estadístico se realizó con Epi Info 3.5.1. Los resultados identificaron 1.515 casos de accidentes y la violencia. De ellos 1.200 (79.20%) son por accidentes y 315 (20,8%), la violencia. La edad media fue de 27,71 años. El estudio trajo una descripción del fenómeno y también reveló la fragilidad de Vigilancia de la Salud.Descriptores: Accidentes, Violencia, Departamento de Salud y la Morbilidad.

scholarly journals COVID 19 Pandemic: A Real-time Forecasts & Prediction of Confirmed Cases, Active Cases using the ARIMA model &Public Health in West Bengal, India.

2020 ◽  
Author(s):  
Dibash Sarkar
Keyword(s):  
Public Health ◽  
Health Care ◽  
Time Series ◽  
Health Care System ◽  
West Bengal ◽  
Arima Model ◽  
Public Health Care ◽  
Public Health Care System ◽  
The World ◽  
Care System

Abstract Background: COVID-19 is an emerging infectious disease which has been declared a Pandemic by the World Health Organization (WHO) on March 11 2020. This pandemic has spread over the world in more than 200 countries. India is also adversely affected by this pandemic, and there are no signs of slowing down of the virus in coming time. The absence of a vaccine for COVID-19 is making the situation worse for the already overstretched Indian public health care system. As economic burden makes it increasingly difficult for our country to continue imposing control measures, it is vital for states like West Bengal to make predictions using time series forecasting for the upcoming cases , test kits , health care and estimated the requirement of Quarantine centers, isolation beds, ICU beds and ventilators for COVID-19 patients .Objective: This study is forecasting the confirmed and active cases for COVID-19 until August, using time series ARIMA model & Public Health in West Bengal, India.Methods: We used ARIMA model, and Auto ARIMA model for forecasting confirmed and active cases till the end of August month using time series data of COVID-19 cases in West Bengal, India from March 1, 2020, to June 4, 2020.Discussion and Conclusion: This forecasts show a very crucial situation for West Bengal in coming days and, the actual numbers can go higher than our estimates of confirmed case as Lockdown 5.0 & Unlock 1.0 will be implemented from 1st June 2020 in India, West Bengal will be observing a partial lift of the lockdown and in that case, there will be a surge in the number of daily confirmed and active cases. The requirement of Health care sector needs to be further improved isolation beds, ICUs and ventilators will also be needed to increase in that scenario. Inter State & Intra State Movement restrictions are lifted. Hence, Migrants returning to their homes due to loss of livelihood and income in the lockdown period may lead to a rise in the number of cases, which could not be accounted for in our projections. We suggest more of Public-Private Partnership (PPP) model in the health sector to accommodate COVID-19 patients adequately and reduce the burden of the already overstretched Indian public health care system, which will directly or indirectly affect the States in the time of crisis.

scholarly journals COVID 19 Pandemic: A Real-time Forecasts & Prediction of Confirmed Cases, Active Cases using the ARIMA model & Public Health in West Bengal, India.

2020 ◽  
Author(s):  
Dibash Sarkar
Keyword(s):  
Public Health ◽  
Health Care ◽  
Time Series ◽  
Health Care System ◽  
West Bengal ◽  
Arima Model ◽  
Public Health Care ◽  
Public Health Care System ◽  
The World ◽  
Care System

Background: COVID-19 is an emerging infectious disease which has been declared a Pandemic by the World Health Organization (WHO) on March 11 2020. This pandemic has spread over the world in more than 200 countries. India is also adversely affected by this pandemic, and there are no signs of slowing down of the virus in coming time. The absence of a vaccine for COVID-19 is making the situation worse for the already overstretched Indian public health care system. As economic burden makes it increasingly difficult for our country to continue imposing control measures, it is vital for states like West Bengal to make predictions using time series forecasting for the upcoming cases , test kits , health care andestimated the requirement of Quarantine centers, isolation beds, ICU beds and ventilators for COVID-19 patients Objective: This study is forecasting the confirmed and active cases for COVID-19 until August, using time series ARIMA model & Public Health in West Bengal, India.Methods: We used ARIMA model, and Auto ARIMA model for forecasting confirmed and active cases till the end of August month using time series data of COVID-19 cases in West Bengal, India from March 1, 2020, to June 4, 2020. Results: We are expecting that West Bengal will have around 62279 ± 5000 Cases by the end of Augustbased on our forecasts. Meanwhile Maharashtra, Punjab, Gujarat and Delhi (UT) will be the most affected states, having the highest number of active and confirmed cases at the end of August.Discussion and Conclusion: This forecasts show a very crucial situation for West Bengal in coming days and, the actual numbers can go higher than our estimates of confirmed case as Lockdown 5.0 & Unlock 1.0 will be implemented from 1st June 2020 in India, West Bengal will be observing a partial liftof the lockdown and in that case, there will be a surge in the number of daily confirmed and active cases. The requirement of Health care sector needs to be further improved isolation beds, ICUs and ventilators will also be needed to increase in that scenario. Inter State & Intra State Movement restrictions are lifted. Hence, Migrants returning to their homes due to loss of livelihood and income in the lockdown period may lead to a rise in the number of cases, which could not be accounted for in our projections. We suggest more of Public-Private Partnership (PPP) model in the health sector to accommodate COVID-19 patients adequately and reduce the burden of the already overstretched Indian public health care system,which will directly or indirectly affect the States in the time of crisis.

Economic Burden of Public Health Care Was Higher than that of Hospitalization and Treatment Associated with COVID-19 In China

2020 ◽  
Author(s):  
Xiaohua Liang ◽  
Lun Xiao ◽  
Xue-Li Yang ◽  
Xuefei Zhong ◽  
Peng Zhang ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Economic Burden ◽  
Public Health Care

scholarly journals An Economic Evaluation of Disallowing Body Checking in 11- to 12-Year-Old Ice Hockey Leagues

2021 ◽  
pp. 194173812110215
Author(s):  
Gillian R. Currie ◽  
Raymond Lee ◽  
Amanda M. Black ◽  
Luz Palacios-Derflingher ◽  
Brent E. Hagel ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Health Care System ◽  
Policy Change ◽  
National Policy ◽  
Ice Hockey ◽  
Public Health Care ◽  
Public Health Care System ◽  
Body Checking ◽  
Care System

Background: After a national policy change in 2013 disallowing body checking in Pee Wee ice hockey games, the rate of injury was reduced by 50% in Alberta. However, the effect on associated health care costs has not been examined previously. Hypothesis: A national policy removing body checking in Pee Wee (ages 11-12 years) ice hockey games will reduce injury rates, as well as costs. Study Design: Cost-effectiveness analysis alongside cohort study. Level of Evidence: Level 3. Methods: A cost-effectiveness analysis was conducted alongside a cohort study comparing rates of game injuries in Pee Wee hockey games in Alberta in a season when body checking was allowed (2011-2012) with a season when it was disallowed after a national policy change (2013-2014). The effectiveness measure was the rate of game injuries per 1000 player-hours. Costs were estimated based on associated health care use from both the publicly funded health care system and privately paid health care cost perspectives. Probabilistic sensitivity analysis was conducted using bootstrapping. Results: Disallowing body checking significantly reduced the rate of game injuries (−2.21; 95% CI [−3.12, −1.31] injuries per 1000 player-hours). We found no statistically significant difference in public health care system (−$83; 95% CI [−$386, $220]) or private health care costs (−$70; 95% CI [−$198, $57]) per 1000 player-hours. The probability that the policy of disallowing body checking was dominant (with both fewer injuries and lower costs) from the perspective of the public health care system and privately paid health care was 78% and 92%, respectively. Conclusion: Given the significant reduction in injuries, combined with lower public health care system and private costs in the large majority of iterations in the probabilistic sensitivity analysis, our findings support the policy change disallowing body checking in ice hockey in 11- and 12-year-old ice hockey leagues.

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