Number Of Daily Cases Research Articles

Drawing inference from nationwide lockdown as a response towards novel Cornavirus-19 (CoVID-19) epidemic in India.

Background:Lockdown effectively can only result in relative freezing of populations that is expected to slow down the disease spread rather than zeroing it. Flattening of epidemic curve Current analysis was carried out to observe a pattern in the rise of CoVID-19 cases along with concurrent announcements of strategies to control the spread of disease.Material and Methods:Data in from of daily number of cases and issued notifications were studied from the official website of Government of India from 30/01/2020 to 03/05/2020. Qualitative assessment with thematic analysis was carried out for notifications issued by the government. The fit to data on cumulative cases was observed with R2 and checked for linearity, logarithmic, polynomial, and exponential growth. Daily growth fraction (Gt) was calculated based on the difference between current and previous number of cases, thereafter daily doubling time (Td(t)) was estimated.Results:Daily reported cases were entered and cumulative growth of cases observed with a polynomial increasing pattern (third-order) with better fit (R2: 0.999). Total 108 notifications were issued, and as compared to phase-0 and 1 (87.0%), few (12.9%) notifications were issued in phase-2 of study period. As compared to phase-0 and 1, rising trend of cumulative cases and Td(t) was high in phase-2.Conclusion:Across phases of lockdown along with a rising trend of COVID-19 cases, the country has managed to increase the doubling time of cases with an effort to flatten the epidemic curve.

S&P 500 Index and COVID-19

In this paper, I study the impact of the COVID-19 on S&P 500 index using daily data from January 1, 2020, to May 12, 2020. The result shows that the number of confirmed cases, the number of deaths, and the number of recovery cases are the main parameters that affect the S&P 500 index. The first corona case in the USA is found on January 21, 2020. During March, the S&P 500 price fell by almost 31% and reached $2,237.40. The result shows that as the number of daily cases increases, it severely affects the S&P 500 index. But, as the number of deaths increases, the S&P 500 index's reduction is more severe with the rise of new cases. However, there is a little bit of positive effect of the new recovery cases on the S&P 500 Index.

Does a simple syringe applicator enhance bone cement set up time in knee arthroplasty?

The time required for polymethylmethacrylate (PMMA) cement curing or hardening can be modified by a number of variables including the mixing technique, and the temperature and pressure at which the process is taking place. Therefore, the purpose of this study was to evaluate two different methods of PMMA application in terms of set up time. Specifically, we (I) compared the PMMA set up time of cement that remained in the mixing bowl to cement that was placed in a syringe and (II) extrapolated the associated annual cost difference on the national and individual surgeon levels. The cement set up time was measured for a total of 146 consecutive patients who underwent either unicompartmental knee arthroplasty (n=136) or patellofemoral arthroplasty (n=10) between January 2016 and April 2017. One pack of PMMA powder and monomer were mixed, placed in a 300 mL small plastic bowl, and mixed with a tongue depressor. Then, 50 mL of the mixed PMMA was placed in a sterile 60 mL syringe with the tip cut to a 6-mm opening, and the syringe was used to apply the cement to the bone and the prosthesis surface. The remaining unused cement in the syringe (syringe group) and the remaining unused cement in the plastic bowl (bowl group) were removed and formed into a two separate 2 cm diameter cubes that were allowed to cure at room temperature on a sterile set of osteotomes. The two cubes of cement were timed for complete PMMA curing. A two-tailed student's t-test was used to compare the curing time for the two groups. Annual cost differences were calculated on the national and individual surgeon level. The total number of daily cases performed and the operative time savings using the syringe applicator was used to find daily and annual cost savings. The mean time for the cement to set up in the bowl group was 16.8±2.1 minutes, and the mean time for cement set up in the syringe group was 15.1±1.7 minutes. Compared to the bowl group cement set up time, the syringe group set up time was significantly lower (P<0.0001). An estimated 350,000 cemented knee arthroplasties are performed each year in the United States. With 1.7 minutes saved per case, 595,000 operating room minutes per year could be saved, resulting in a nearly $71,000,000 national and $110,000 individual surgeon annual cost savings. The results of the present study demonstrated that the utilization of a simple, inexpensive syringe applicator enhanced the cement set up time by over one and a half minutes. This may be a result of the pressure differences in the syringe applicator. In addition to the control of and precision of where the cement is placed, the syringe applicator could provide an important potential time advantage to the arthroplasty surgeon.

Impacts of extremely high temperature and heatwave on heatstroke in Chongqing, China.

Few studies have reported the quantitative association between heat and heatstroke (HS) occurrence, particularly in China. The aim of this study was to quantitatively assess the association between high temperature/heatwave and HS occurrence in Chongqing. The daily HS data from 2009 to 2013 of Chongqing were extracted from Chongqing Center for Disease Control and Prevention. A Zero-inflated Poisson regression model (ZIP) with a logistic distribution was used to quantitatively analyze the impacts of the daily maximum temperature (Tmax) over the threshold on HS occurrence by gender, age, and severity of HS, after controlling for covariates including day of the week (DOW), relative humidity, and daily temperature range. Lag effects up to 10days were analyzed. Heatwave intensity, which was classified into four levels according to the quartile of its values, was calculated by Tmax multiplied the duration of a heatwave. The excess risk of HS during heatwave with different intensity was analyzed. The Tmax threshold for HS was 34°C in Chongqing. After adjusting for potential confounders, strong associations and age-specific lag effects between Tmax and daily HS occurrence were observed. The impacts of Tmax on total HS lasted for 7days (lag0-6), with the highest excess risk (ER) value of 30.5% (95% CI 23.6 and 37.8%) on lag0 with each 1°C increment in Tmax over the threshold. A slightly stronger temperature-HS association was detected in male compared to female. The population over 65years had the highest ER and the younger adults aged 19-35 and 35-55years also showed significant heat-HS associations. The number of daily cases increased with the increasing of duration of heatwave and the peak value occurred on the eleventh day of the heatwave. The excess risk of HS during the heatwave with 1 to 4 level of intensity increased by 2.54, 2.97, 5.61, and 11.3 times, respectively, as compared with that of non-heatwave. Extreme heat is becoming a huge threat to public health due to the strong temperature-HS associations in Chongqing. Climate change with increasing temperatures may make the situation worse. Our results can provide reference for developing and improving relevant public health strategies and early extreme weather and health warning system to prevent and reduce the health risks due to extreme weather and climate change in Chongqing.

Assessing the social and environmental determinants of pertussis epidemics in Queensland, Australia: a Bayesian spatio-temporal analysis.

Pertussis epidemics have displayed substantial spatial heterogeneity in countries with high socioeconomic conditions and high vaccine coverage. This study aims to investigate the relationship between pertussis risk and socio-environmental factors on the spatio-temporal variation underlying pertussis infection. We obtained daily case numbers of pertussis notifications from Queensland Health, Australia by postal area, for the period January 2006 to December 2012. A Bayesian spatio-temporal model was used to quantify the relationship between monthly pertussis incidence and socio-environmental factors. The socio-environmental factors included monthly mean minimum temperature (MIT), monthly mean vapour pressure (VAP), Queensland school calendar pattern (SCP), and socioeconomic index for area (SEIFA). An increase in pertussis incidence was observed from 2006 to 2010 and a slight decrease from 2011 to 2012. Spatial analyses showed pertussis incidence across Queensland postal area to be low and more spatially homogeneous during 2006-2008; incidence was higher and more spatially heterogeneous after 2009. The results also showed that the average decrease in monthly pertussis incidence was 3·1% [95% credible interval (CrI) 1·3-4·8] for each 1 °C increase in monthly MIT, while average increase in monthly pertussis incidences were 6·2% (95% CrI 0·4-12·4) and 2% (95% CrI 1-3) for SCP periods and for each 10-unit increase in SEIFA, respectively. This study demonstrated that pertussis transmission is significantly associated with MIT, SEIFA, and SCP. Mapping derived from this work highlights the potential for future investigation and areas for focusing future control strategies.

Projections of hepatitis A virus infection associated with flood events by 2020 and 2030 in Anhui Province, China

Assessing and responding to health risk of climate change is important because of its impact on the natural and societal ecosystems. More frequent and severe flood events will occur in China due to climate change. Given that population is projected to increase, more people will be vulnerable to flood events, which may lead to an increased incidence of HAV infection in the future. This population-based study is going to project the future health burden of HAV infection associated with flood events in Huai River Basin of China. The study area covered four cities of Anhui province in China, where flood events were frequent. Time-series adjusted Poisson regression model was developed to quantify the risks of flood events on HAV infection based on the number of daily cases during summer seasons from 2005 to 2010, controlling for other meteorological variables. Projections of HAV infection in 2020 and 2030 were estimated based on the scenarios of flood events and demographic data. Poisson regression model suggested that compared with the periods without flood events, the risks of severe flood events for HAV infection were significant (OR=1.28, 95% CI 1.05-1.55), while risks were not significant from moderate flood events (OR=1.16, 95% CI 0.72-1.87) and mild flood events (OR=1.14, 95% CI 0.87-1.48). Using the 2010 baseline data and the flood event scenarios (one severe flood event), increased incidence of HAV infection were estimated to be between 0.126/105 and 0.127/105 for 2020. Similarly, the increased HAV infection incidence for 2030 was projected to be between 0.382/105 and 0.399/105. Our study has, for the first time, quantified the increased incidence of HAV infection that will result from flood events in Anhui, China, in 2020 and 2030. The results have implications for public health preparation for developing public health responses to reduce HAV infection during future flood events.

A mixed method to evaluate burden of malaria due to flooding and waterlogging in Mengcheng County, China: a case study.

BackgroundMalaria is a highly climate-sensitive vector-borne infectious disease that still represents a significant public health problem in Huaihe River Basin. However, little comprehensive information about the burden of malaria caused by flooding and waterlogging is available from this region. This study aims to quantitatively assess the impact of flooding and waterlogging on the burden of malaria in a county of Anhui Province, China.MethodsA mixed method evaluation was conducted. A case-crossover study was firstly performed to evaluate the relationship between daily number of cases of malaria and flooding and waterlogging from May to October 2007 in Mengcheng County, China. Stratified Cox models were used to examine the lagged time and hazard ratios (HRs) of the risk of flooding and waterlogging on malaria. Years lived with disability (YLDs) of malaria attributable to flooding and waterlogging were then estimated based on the WHO framework of calculating potential impact fraction in the Global Burden of Disease study.ResultsA total of 3683 malaria were notified during the study period. The strongest effect was shown with a 25-day lag for flooding and a 7-day lag for waterlogging. Multivariable analysis showed that an increased risk of malaria was significantly associated with flooding alone [adjusted hazard ratio (AHR) = 1.467, 95% CI = 1.257, 1.713], waterlogging alone (AHR = 1.879, 95% CI = 1.696, 2.121), and flooding and waterlogging together (AHR = 2.926, 95% CI = 2.576, 3.325). YLDs per 1000 of malaria attributable to flooding alone, waterlogging alone and flooding and waterlogging together were 0.009 per day, 0.019 per day and 0.022 per day, respectively.ConclusionFlooding and waterlogging can lead to higher burden of malaria in the study area. Public health action should be taken to avoid and control a potential risk of malaria epidemics after these two weather disasters.

Time Distribution of the Onset of Chest Pain in Subjects with Acute ST-Elevation Myocardial Infarction: An Eight-Year, Single-Center Study in China

ObjectiveThe objective of this study was to explore the time distribution patterns of the onset of chest pain in subjects with acute ST-elevation myocardial infarction in a Chinese population.MethodsA total of 1467 patients with acute ST-elevation myocardial infarction were enrolled from 2003 to 2010. The hourly, daily, monthly, seasonal and day-of-week fluctuations in the prevalence of acute ST-elevation myocardial infarction were analyzed.ResultsA peak was found between the morning hours of 07:31 and 08:30. A second peak was observed between 14:31 and 15:30, and a third peak was found between 23:31 and 00:30 (p<0.001). The monthly maximum was recorded in November and the minimum was in April (p<0.001). The number of daily cases was greatest in autumn and lowest in the spring (p = 0.001). Day-of-the-week variations of ST-elevation acute myocardial infarction were not found, except in patients more than 75-years-old.ConclusionsPeriodic variations in the frequency of ST-elevation acute myocardial infarction in Chinese patients showed significant differences with regard to diurnal, monthly and seasonal patterns. The exact mechanisms underlying these circadian variations require further study.

Weather: driving force behind the transmission of severe acute respiratory syndrome in China?

Background: The association between weather and severe acute respiratory syndrome (SARS) transmission in Beijing and Hong Kong in the 2003 epidemic was studied to examine the effect of weather on SARS transmission. Methods: Pearson’s correlation analyses and negative binomial regression analyses were used to quantify the correlations between the daily newly reported number of SARS cases and weather variables, using daily disease notification data and meteorological data from the two locations. Results: The results indicate that there were inverse association between the number of daily cases and maximum and/or minimum temperatures whereas air pressure was found to be positively associated with SARS transmission. Conclusion: The study suggests that weather might be a contributory factor in the 2003 SARS epidemic, in particular in the transmission among the community members.

Modelling influenza epidemics in the relation between black smoke and total mortality. A sensitivity analysis.

3have been studied, but not diVerent methods for modelling influenza epidemics. In previous work influenza epidemics were controlled for by means of only one dummy variable, “1” denoting the occurrence...

Winter weather conditions and myocardial infarctions

The daily number of cases of myocardial infarctions admitted to a hospital in middle Sweden over three winter seasons 1984-87 was correlated to the weather conditions on a day-to-day basis. The study encompassed 634 days and all cases younger than 70 years, living within the catchment area, in all 382 subjects. Information on temperature, wind force, precipitation and atmospheric pressure was obtained from the Swedish Institute of Meteorology and Hydrology. A low number of myocardial infarctions was seen on Saturdays and Sundays with a mild wind chill factor and on days with moderate snowfall and high atmospheric pressure. A high number was observed for workdays, especially Mondays, as day of diagnosis. Heterogeneity of the study population and a misclassification of the time relationships between dates of diagnosis and weather changes may have caused an underestimation of the impact of weather conditions. However, weather conditions do not seem to be a major triggering factor of myocardial infarctions in Sweden.

G.P. Filing System

<h3>Abstract</h3> <h3>Background</h3> The ability of countries to contain and control COVID-19 virus transmission via social distancing is critical in the absence of a vaccine. Early activation of robust measures has been shown to control the daily infection rate, and consequential pressure on the health care system. As countries begin to control COVID-19 spread an understanding of how to ease social distancing measures to prevent a rebound in cases and deaths is required. <h3>Methods</h3> Using COVID-19 transmission data from the outbreak source in Hubei Province, China prior to activation of containment measures, we adapted an established individual-based simulation model of the city of Newcastle, Australia. Simulation of virus transmission in this model, with and without, social distancing measures activated permitted us to quantify social distancing effectiveness. Optimal strategies for relaxing social distancing were determined under two settings: with high numbers of daily cases, as in New York; and where early social distancing activation resulted in limited ongoing transmission, as in Perth, Australia. <h3>Findings</h3> In countries where strong social distancing measures were activated after the COVID-19 virus had spread widely, our study found these measures are required to be maintained for significant periods before being eased, to return to a situation where daily case numbers become low. In countries where early responses to the COVID-19 pandemic have been highly successful, as in Australia, we show that a staged relaxation of social distancing prevents a rebound in cases. <h3>Interpretation</h3> Modelling studies and direct observation have shown that robust and timely social distancing have the most effect in containing the spread of the COVID-19 virus. Questions arise as to the duration of strong social distancing measures, given they are highly disruptive to society and economic activity. This study demonstrates the necessity of holding robust social distancing in place until COVID-19 virus transmission has significantly decreased, and how they may then be safely eased.