Real-time estimation of the influenza-associated excess mortality in Hong Kong

Abstract Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

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Robust and Timely Estimation of Excess Mortality: Statistical Analysis of Cremation Data During the COVID-19 Pandemic (Preprint)

10.2196/preprints.32426 ◽

2021 ◽

Author(s):

Gemma Postill ◽

Regan Murray ◽

Andrew S Wilton ◽

Richard A Wells ◽

Renee Sirbu ◽

...

Keyword(s):

Real Time ◽

Excess Mortality ◽

Age Groups ◽

Time Estimation ◽

Vital Statistics ◽

Accurate Estimation ◽

Mortality Data ◽

Mortality Estimation ◽

Statistics Canada ◽

The Impact

BACKGROUND Early estimates of excess mortality are crucial for understanding the impact of COVID-19. However, there is a lag of several months in the reporting of vital statistics mortality data for many jurisdictions. In Ontario, a Canadian province, certification by a coroner is required before cremation can occur, creating timely mortality data that encompasses the majority of deaths within the province. OBJECTIVE Our objectives were to (1) validate the ability of cremation data in permitting real-time estimation of excess all-cause mortality, interim of vital statistics data, and (2) describe the patterns of excess mortality. METHODS Cremation records from January 2020 until April 2021 were compared to the historical records from 2017-2019, grouped according to week, age, sex, and COVID-19 status. Cremation data were compared to Ontario’s provisional vital statistics mortality data released by Statistics Canada. The 2020 and 2021 records were then compared to previous years to determine whether there was excess mortality and if so, which age groups had the greatest number of excess deaths during the COVID Pandemic, and whether deaths attributed to COVID-19 account for the entirety of the excess mortality. RESULTS Between 2017-2019, cremations were performed for 67.4% (95% CI: 67.3–67.5%) of deaths; the proportion of cremated deaths remained stable throughout 2020, establishing that the COVID-19 pandemic did not significantly alter cremation practices, even within age and sex categories. During the first wave (from April to June 2020), cremation records detected a 16.9% increase (95% CI: 14.6–19.3%) in mortality. The accuracy of this excess mortality estimation was later confirmed by vital statistics data. CONCLUSIONS The stability in the percent of Ontarians cremated and the completion of cremation data several months before vital statistics data, enables accurate estimation of all-causes mortality in near real-time with cremation data. These findings demonstrate the utility of cremation data to provide timely mortality information during public health emergencies.

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Evolution of effective serial interval of SARS-CoV-2 by non-pharmaceutical interventions

10.21203/rs.3.rs-32486/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sheikh Taslim Ali ◽

Lin Wang ◽

Eric H. Y. Lau ◽

Xiao-Ke Xu ◽

Zhanwei Du ◽

...

Keyword(s):

Mainland China ◽

Time Estimation ◽

Control Measures ◽

Reproduction Numbers ◽

Serial Interval ◽

Real Time Estimation ◽

Definition Of ◽

Novel Coronavirus ◽

The Impact ◽

Pharmaceutical Interventions

Abstract Studies of novel coronavirus disease (COVID-19) have reported varying estimates of epidemiological parameters such as serial intervals and reproduction numbers. By compiling a unique line-list database of transmission pairs in mainland China, we demonstrated that serial intervals of COVID-19 have shortened substantially from a mean of 7.8 days to 2.6 days within a month. This change is driven by enhanced non-pharmaceutical interventions, in particular case isolation. We also demonstrated that using real-time estimation of serial intervals allowing for variation over time would provide more accurate estimates of reproduction numbers, than by using conventional definition of fixed serial interval distributions. These findings are essential to improve the assessment of transmission dynamics, forecasting future incidence, and estimating the impact of control measures.

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Excess mortality during COVID-19 in five European countries and a critique of mortality data analysis

10.1101/2020.04.28.20083147 ◽

2020 ◽

Cited By ~ 6

Author(s):

J. Félix-Cardoso ◽

H. Vasconcelos ◽

P. Pereira Rodrigues ◽

R. Cruz-Correia

Keyword(s):

Excess Mortality ◽

Surveillance Data ◽

European Countries ◽

Mortality Data ◽

Surveillance Systems ◽

Policy Responses ◽

Seasonal Time Series ◽

And Gender ◽

The Impact ◽

Mortality Surveillance

AbstractINTRODUCTIONThe COVID-19 pandemic is an ongoing event disrupting lives, health systems, and economies worldwide. Clear data about the pandemic’s impact is lacking, namely regarding mortality. This work aims to study the impact of COVID-19 through the analysis of all-cause mortality data made available by different European countries, and to critique their mortality surveillance data.METHODSEuropean countries that had publicly available data about the number of deaths per day/week were selected (England and Wales, France, Italy, Netherlands and Portugal). Two different methods were selected to estimate the excess mortality due to COVID19: (DEV) deviation from the expected value from homologue periods, and (RSTS) remainder after seasonal time series decomposition. We estimate total, age- and gender-specific excess mortality. Furthermore, we compare different policy responses to COVID-19.RESULTSExcess mortality was found in all 5 countries, ranging from 10.6% in Portugal (DEV) to 98.5% in Italy (DEV). Furthermore, excess mortality is higher than COVID-attributed deaths in all 5 countries.DISCUSSIONThe impact of COVID-19 on mortality appears to be larger than officially attributed deaths, in varying degrees in different countries. Comparisons between countries would be useful, but large disparities in mortality surveillance data could not be overcome. Unreliable data, and even a lack of cause-specific mortality data undermine the understanding of the impact of policy choices on both direct and indirect deaths during COVID-19. European countries should invest more on mortality surveillance systems to improve the publicly available data.

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Dynamics of Transmission and Control of COVID-19: A Real-time Estimation Using the Kalman Filter

10.1101/2020.04.19.20071886 ◽

2020 ◽

Cited By ~ 1

Author(s):

Francisco Arroyo Marioli ◽

Francisco Bullano ◽

Carlos Rondón-Moreno

Keyword(s):

Kalman Filter ◽

South Korea ◽

Real Time ◽

Reproduction Number ◽

Time Estimation ◽

Control Measures ◽

Significant Heterogeneity ◽

Real Time Estimation ◽

And Control ◽

Over Time

AbstractThe COVID-19 pandemic has become the center of attention for both researchers and authorities. In this paper, we propose and test a methodology to estimate the daily effective reproduction number (ℛt) through the lens of the Kalman Filter and Bayesian estimation. Moreover, we apply our method to data from the current COVID-19 pandemic in China, Italy, Japan, and South Korea. We correlate our findings with the implementation of control measures in each of these countries. Our results show that China, Italy, and South Korea have been able to reduce ℛt over time. We find significant heterogeneity in the way ℛt decreases across countries. For instance, China reduced ℛt from its peak to below one in 19 days, while South Korea achieved the same reduction in 12 days. In contrast, it has taken Italy almost a month to reach similar levels. We hypothesize this is related to how strict, enforceable, and comprehensive are the implemented policies.

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A Real-Time Estimation Method of Roll Angle and Angular Rate Based on Geomagnetic Information

Mathematical Problems in Engineering ◽

10.1155/2020/9035710 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Lizhen Gao ◽

Yingying Zhang ◽

Xiaoming Zhang ◽

Yuyang Xue

Keyword(s):

Kalman Filter ◽

Real Time ◽

Angular Rate ◽

Dynamic Change ◽

Time Estimation ◽

Roll Angle ◽

Forgetting Factor ◽

Real Time Estimation ◽

High Dynamic ◽

The Impact

In the course of the guidance transformation of the rotating projectile, the accurate acquisition of the roll angle and roll angle rate is very important to the attitude determination and guidance control of the rotating projectile. However, due to the impact of high rotation and high overload of projectile, MEMS gyros have problems such as limited range, saturation, overload, and even performance degradation, which make the roll angle rate unable to be output normally. At the same time, because the MEMS gyro estimation of roll angle is in the form of angular rate integral, the roll angle cannot be estimated normally if the roll angle rate cannot be accurately obtained. In order to solve this problem, a real-time estimation of projectile roll angle and roll rate based on geomagnetic information under high dynamic and high overload conditions is presented. Firstly, according to the motion characteristics of the rotating projectile, the motion model of the projectile is established, and the roll angle and roll angle rate of the projectile are estimated by Kalman filtering algorithm under the conditions of high axial rotation and high overload. Considering the high dynamic characteristics of the rotating projectile, based on the Kalman filter, the algorithm of the forgetting filter with the forgetting factor is further adopted to estimate the roll angle and roll angle rate, so as to reduce the error caused by the estimation delay in the process of high-speed dynamic change. Simulation data and semiphysical test results show that the accuracy of roll angle estimated by this method reaches about 2° in semiphysical test, which is one time higher than that calculated by the system. In the semiphysical experiment, the accuracy of the estimated roll rotation rate reaches 5 °/s, which is more than 6 times higher than that obtained by direct derivation. In the high dynamic stage, compared with the pure Kalman filter, the accuracy of roll angle with forgetting factor estimation is improved by an order of magnitude, and the accuracy of roll angle rate is improved by 4 times, which meets the desired accuracy of rotating projectile.

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A machine for real-time estimation of the tribological characteristics of materials

Industrial laboratory Diagnostics of materials ◽

10.26896/1028-6861-2020-86-4-61-65 ◽

2020 ◽

Vol 86 (4) ◽

pp. 61-65

Author(s):

M. V. Abramchuk ◽

R. V. Pechenko ◽

K. A. Nuzhdin ◽

V. M. Musalimov

Keyword(s):

Real Time ◽

Time Estimation ◽

Tribological Characteristics ◽

Continuous Processing ◽

Friction Machine ◽

Dynamic Friction Coefficient ◽

Displacement Sensors ◽

Frictional Interaction ◽

Real Time Estimation ◽

Automated Quality Control

A reciprocating friction machine Tribal-T intended for automated quality control of the rubbing surfaces of tribopairs is described. The distinctive feature of the machine consists in implementation of the forced relative motion due to the frictional interaction of the rubbing surfaces fixed on the drive and conjugate platforms. Continuous processing of the signals from displacement sensors is carried out under conditions of continuous recording of mutual displacements of loaded tribopairs using classical approaches of the theory of automatic control to identify the tribological characteristics. The machine provides consistent visual real time monitoring of the parameters. The MATLAB based computer technologies are actively used in data processing. The calculated tribological characteristics of materials, i.e., the dynamic friction coefficient, damping coefficient and measure of the surface roughness, are presented. The tests revealed that a Tribal-T reciprocating friction machine is effective for real-time study of the aforementioned tribological characteristics of materials and can be used for monitoring of the condition of tribo-nodes of machines and mechanisms.

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