scholarly journals On the use of real-time reported mortality data in modelling and analysis during an epidemic outbreak

2020 ◽  
Vol 4 ◽  
pp. 128
Author(s):  
Per Liljenberg
Keyword(s):  
Standard Procedure ◽  
Time Dependent ◽  
Mortality Data ◽  
Epidemic Outbreak ◽  
Mathematical Relationship ◽  
Infected People ◽  
True Number ◽  
Reporting Delay ◽  
Death Data ◽  
Death Date

Background: For diseases like Covid-19, where it has been difficult to identify the true number of infected people, or where the number of known cases is heavily influenced by the number of tests performed, hospitalizations and deaths play a significant role in understanding the epidemic and in determining the appropriate response. However, the Covid-19 deaths data reported by some countries display a significant weekly variability, which can make the interpretation and use of the death data in analysis and modeling difficult. Methods: We derive the mathematical relationship between the series of new daily deaths by reporting date and the series of deaths by death date. We then apply this formalism to the corresponding time-series reported by Sweden during the Covid-19 pandemic. Results: The practice of reporting new deaths daily, as is standard procedure during an outbreak in most countries and regions, should be viewed as a time-dependent filter, modulating the underlying true death curve. After having characterized the Swedish reporting process, we show how smoothing of the Swedish reported daily deaths series results in a curve distinctly different from the true death curve. We also comment on the use of nowcasting methods. Conclusions: Modelers and analysts using the series of new daily deaths by reporting date should take extra care when it is highly variable and when there is a significant reporting delay. It might be appropriate to instead use the series of deaths by death date combined with a nowcasting algorithm as basis for their analysis.

scholarly journals Delay in death reporting affects timely monitoring and modeling of the COVID-19 pandemic

2021 ◽  
Vol 37 (7) ◽  
Author(s):  
Carolina Abreu de Carvalho ◽  
Vitória Abreu de Carvalho ◽  
Marcos Adriano Garcia Campos ◽  
Bruno Luciano Carneiro Alves de Oliveira ◽  
Eduardo Moraes Diniz ◽  
...  
Keyword(s):  
Bayesian Hierarchical Model ◽  
Epidemiological Surveillance ◽  
Mortality Data ◽  
State Health ◽  
Bayesian Hierarchical ◽  
The Impact ◽  
The City ◽  
Reporting Delay ◽  
Death Data

This study describes the COVID-19 death reporting delay in the city of São Luís, Maranhão State, Brazil, and shows its impact on timely monitoring and modeling of the COVID-19 pandemic, while seeking to ascertain how nowcasting can improve death reporting delay. We analyzed COVID-19 death data reported daily in the Epidemiological Bulletin of the State Health Secretariat of Maranhão and calculated the reporting delay from March 23 to August 29, 2020. A semi-mechanistic Bayesian hierarchical model was fitted to illustrate the impact of death reporting delay and test the effectiveness of a Bayesian Nowcasting in improving data quality. Only 17.8% of deaths were reported without delay or the day after, while 40.5% were reported more than 30 days late. Following an initial underestimation due to reporting delay, 644 deaths were reported from June 7 to August 29, although only 116 deaths occurred during this period. Using the Bayesian nowcasting technique partially improved the quality of mortality data during the peak of the pandemic, providing estimates that better matched the observed scenario in the city, becoming unusable nearly two months after the peak. As delay in death reporting can directly interfere with assertive and timely decision-making regarding the COVID-19 pandemic, the Brazilian epidemiological surveillance system must be urgently revised and notifying the date of death must be mandatory. Nowcasting has proven somewhat effective in improving the quality of mortality data, but only at the peak of the pandemic.

scholarly journals Modelling COVID-19 outbreaks in USA with distinct testing, lockdown speed and fatigue rates

2021 ◽  
Vol 8 (8) ◽  
pp. 210227
Author(s):  
J. C. Macdonald ◽  
C. Browne ◽  
H. Gulbudak
Keyword(s):  
Management Strategies ◽  
Model Parameters ◽  
Entry And Exit ◽  
Infection Level ◽  
Actual Case ◽  
True Number ◽  
Behavioural Reaction ◽  
The Usa ◽  
Death Data ◽  
Inverse Proportionality

Each state in the USA exhibited a unique response to the COVID-19 outbreak, along with variable levels of testing, leading to different actual case burdens in the country. In this study, via per capita testing dependent ascertainment rates, along with case and death data, we fit a minimal epidemic model for each state. We estimate infection-level responsive lockdown/self-quarantine entry and exit rates (representing government and behavioural reaction), along with the true number of cases as of 31 May 2020. Ultimately, we provide error-corrected estimates for commonly used metrics such as infection fatality ratio and overall case ascertainment for all 55 states and territories considered, along with the USA in aggregate, in order to correlate outbreak severity with first wave intervention attributes and suggest potential management strategies for future outbreaks. We observe a theoretically predicted inverse proportionality relation between outbreak size and lockdown rate, with scale dependent on the underlying reproduction number and simulations suggesting a critical population quarantine ‘half-life’ of 30 days independent of other model parameters.

scholarly journals A modeling of a Diphtheria epidemic in the refugees camps

2017 ◽  
Author(s):  
María Torrea ◽  
José Luis Torrea ◽  
Daniel Ortega
Keyword(s):  
Public Health ◽  
Soviet Union ◽  
Vaccine Coverage ◽  
Disease Spread ◽  
Epidemic Outbreak ◽  
High Coverage ◽  
Infected People ◽  
Vaccination Rates ◽  
Health Measures ◽  
The Soviet Union

AbstractBackgroundDiphtheria has a big mortality rate. Vaccination practically eradicated it in industrialized countries. A decrease in vaccine coverage and public health deterioration cause a reemergence in the Soviet Union in 1990. These circumstances seem to be being reproduced in refugee camps with a potential risk of new outbreak.MethodsWe constructed a mathematical model that describes the evolution of the Soviet Union epidemic outbreak. We use it to evaluate how the epidemic would be modified by changing the rate of vaccination, and improving public health conditions.ResultsWe observe that a small decrease of 15% in vaccine coverage, translates an ascent of 47% in infected people. A coverage increase of 15% and 25% decreases a 44% and 66% respectively of infected people. Just improving health care measures a 5%, infected people decreases a 11.31%. Combining high coverage with public health measures produces a bigger reduction in the amount of infected people compare to amelioration of coverage rate or health measures alone.ConclusionsOur model estimates the evolution of a diphtheria epidemic outbreak. Small increases in vaccination rates and in public health measures can translate into large differences in the evolution of a possible epidemic. These estimates can be helpful in socioeconomic instability, to prevent and control a disease spread.

Prion disease incidence in the United States: 2003–2015

Neurology ◽  
2019 ◽  
Vol 94 (2) ◽  
pp. e153-e157 ◽  
Author(s):  
Ryan A. Maddox ◽  
Marissa K. Person ◽  
Janis E. Blevins ◽  
Joseph Y. Abrams ◽  
Brian S. Appleby ◽  
...  
Keyword(s):  
United States ◽  
Cause Of Death ◽  
Prion Disease ◽  
Disease Incidence ◽  
The United States ◽  
Annual Incidence ◽  
Mortality Data ◽  
Genetic Test Results ◽  
Average Annual Incidence ◽  
Death Data

ObjectiveTo report the incidence of prion disease in the United States.MethodsPrion disease decedents were retrospectively identified from the US national multiple cause-of-death data for 2003–2015 and matched with decedents in the National Prion Disease Pathology Surveillance Center (NPDPSC) database through comparison of demographic variables. NPDPSC decedents with neuropathologic or genetic test results positive for prion disease for whom no match was found in the multiple cause-of-death data were added as cases for incidence calculations; those with cause-of-death data indicating prion disease but with negative neuropathology results were removed. Age-specific and age-adjusted average annual incidence rates were then calculated.ResultsA total of 5,212 decedents were identified as having prion disease, for an age-adjusted average annual incidence of 1.2 cases per million population (range 1.0 per million [2004 and 2006] to 1.4 per million [2013]). The median age at death was 67 years. Ten decedents were <30 years of age (average annual incidence of 6.2 per billion); only 2 of these very young cases were sporadic forms of prion disease. Average annual incidence among those ≥65 years of age was 5.9 per million.ConclusionsPrion disease incidence can be estimated by augmenting mortality data with the results of neuropathologic and genetic testing. Cases <30 years of age were extremely rare, and most could be attributed to exogenous factors or the presence of a genetic mutation. Continued vigilance for prion diseases in all age groups remains prudent.

scholarly journals Incident cardiovascular events and risk of subsequent cancer diagnosis

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A Fardman ◽  
A Oppenheim ◽  
G.D Banschick ◽  
R Rabia ◽  
S Segev ◽  
...  
Keyword(s):  
Cancer Diagnosis ◽  
Interaction Analysis ◽  
Young Patients ◽  
Time Dependent ◽  
Mortality Data ◽  
Coronary Syndrome ◽  
Increased Risk ◽  
Risk Of Cancer ◽  
Subsequent Cancer

Abstract Background Cardiovascular disease (CVD) and cancer share common risk factors. This study investigated the association of CVD diagnosis and the risk of future cancer. Methods We evaluated asymptomatic self-referred adults aged 40–79 years who participated in a screening program. All subjects were free of CVD and cancer at baseline. CVD was defined as the composite of acute coronary syndrome, percutaneous coronary intervention or stroke. Cancer and mortality data were available for all subjects from national registries. Primary end-point was development of cancer during follow up. Cox regression models were applied with CVD as a time-dependent covariate and death as a competing risk event. Results Final study population included 15,486 subjects. Median age was 50 years (Interquartile range [IQR] 44–55) and 72% were men. During median follow up time of 11 years (IQR 6–15) 1,028 (7%) subjects developed CVD, 1,281 (8%) developed cancer and 499 (3%) died. Most common cancer types were prostate among men (N=277, 1.8%) and breast among women (N=187, 1.2%). Time dependent survival analysis showed that subjects who developed CVD during follow up were 60% more likely to develop cancer (95% Confidence Interval [CI] 1.3–1.95, p&lt;0.001). However, after adjustment for known predictors of cancer, the association of incident CVD with cancer diagnosis was no longer significant (p=0.21). Interaction analysis demonstrated that the association of incident CVD with the risk of future cancer diagnosis was age dependent such that in younger subjects (&lt;50 years; N=7,649) incident CVD was associated with a significant 2 fold increased risk of subsequent cancer diagnosis (95% CI 1.2–3.6, p=0.014) while in older subjects incident CVD was not associated with increased risk of cancer in the multivariable model (p for interaction =0.035; Figure 1). Conclusions Incident CVD is independently associated with 2-fold increased risk of subsequent cancer diagnosis among young adults. Our analysis underscores the importance of cancer surveillance among young patients following a CVD event. Figure 1 Funding Acknowledgement Type of funding source: None

scholarly journals Are there sex differences in completeness of death registration and quality of cause of death statistics? Results from a global analysis

2021 ◽  
Vol 6 (10) ◽  
pp. e006660
Author(s):  
Tim Adair ◽  
U S H Gamage ◽  
Lene Mikkelsen ◽  
Rohina Joshi
Keyword(s):  
Sex Differences ◽  
Cause Of Death ◽  
Global Analysis ◽  
Age Distribution ◽  
Mortality Data ◽  
Death Registration ◽  
Quality Of Data ◽  
Uncertainty Interval ◽  
Death Data

IntroductionRecent studies suggest that more male than female deaths are registered and a higher proportion of female deaths are certified as ‘garbage’ causes (ie, vague or ill-defined causes of limited policy value). This can reduce the utility of sex-specific mortality statistics for governments to address health problems. To assess whether there are sex differences in completeness and quality of data from civil registration and vital statistics systems, we analysed available global death registration and cause of death data.MethodsCompleteness of death registration for females and males was compared in 112 countries, and in subsets of countries with incomplete death registration. For 64 countries with medical certificate of cause of death data, the level, severity and type of garbage causes was compared between females and males, standardised for the older age distribution and different cause composition of female compared with male deaths.ResultsFor 42 countries with completeness of less than 95% (both sexes), average female completeness was 1.2 percentage points (p.p.) lower (95% uncertainty interval (UI) −2.5 to –0.2 p.p.) than for males. Aggregate female completeness for these countries was 7.1 p.p. lower (95% UI −12.2 to −2.0 p.p.; female 72.9%, male 80.1%), due to much higher male completeness in nine countries including India. Garbage causes were higher for females than males in 58 of 64 countries (statistically significant in 48 countries), but only by an average 1.4 p.p. (1.3–1.6 p.p.); results were consistent by severity and type of garbage.ConclusionAlthough in most countries analysed there was no clear bias against females in death registration, there was clear evidence in a few countries of systematic undercounting of female deaths which substantially reduces the utility of mortality data. In countries with cause of death data, it was only of marginally poorer quality for females than males.

scholarly journals LOCATION DISTRIBUTION OPTIMIZATION OF PHOTOGRAPHING SITES FOR INDOOR PANORAMA MODELING

2017 ◽  
Vol IV-2/W4 ◽  
pp. 431-438
Author(s):  
S. Zhang ◽  
J. Wu ◽  
Y. Zhang ◽  
X. Zhang ◽  
Z. Xin ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Functional Relationship ◽  
Standard Procedure ◽  
Image Modeling ◽  
Panoramic Image ◽  
Mathematical Relationship ◽  
Specific Location ◽  
Camera Lens ◽  
Panoramic Images ◽  
The Relationship

Generally, panoramas image modeling is costly and time-consuming because of photographing continuously to capture enough photos along the routes, especially in complicated indoor environment. Thus, difficulty follows for a wider applications of panoramic image modeling for business. It is indispensable to make a feasible arrangement of panorama sites locations because the locations influence the clarity, coverage and the amount of panoramic images under the condition of certain device. This paper is aim to propose a standard procedure to generate the specific location and total amount of panorama sites in indoor panoramas modeling. Firstly, establish the functional relationship between one panorama site and its objectives. Then, apply the relationship to panorama sites network. We propose the Distance Clarity function (<i>F<sub>C</sub></i> and <i>F<sub>e</sub></i>) manifesting the mathematical relationship between panoramas and objectives distance or obstacle distance. The Distance Buffer function (<i>F<sub>B</sub></i>) is modified from traditional buffer method to generate the coverage of panorama site. Secondly, transverse every point in possible area to locate possible panorama site, calculate the clarity and coverage synthetically. Finally select as little points as possible to satiate clarity requirement preferentially and then the coverage requirement. In the experiments, detailed parameters of camera lens are given. Still, more experiments parameters need trying out given that relationship between clarity and distance is device dependent. In short, through the function <i>F<sub>C</sub></i>, <i>F<sub>e</sub></i> and <i>F<sub>B</sub></i>, locations of panorama sites can be generated automatically and accurately.

scholarly journals Quality of cause-of-death data in Brazil: Garbage codes among registered deaths in 2000 and 2015

2019 ◽  
Vol 22 (suppl 3) ◽  
Author(s):  
Renato Azeredo Teixeira ◽  
Mohsen Naghavi ◽  
Mark Drew Crosland Guimarães ◽  
Lenice Harumi Ishitani ◽  
Elizabeth Barboza França
Keyword(s):  
Data Quality ◽  
Cause Of Death ◽  
Age Groups ◽  
Health Assessment ◽  
Mortality Data ◽  
Laboratory Findings ◽  
Northern Regions ◽  
Icd 10 ◽  
Death Data

ABSTRACT Introduction: reliability of mortality data is essential for health assessment and planning. In Brazil, a high proportion of deaths is attributed to causes that should not be considered as underlying causes of deaths, named garbage codes (GC). To tackle this issue, in 2005, the Brazilian Ministry of Health (MoH) implements the investigation of GC-R codes (codes from chapter 18 “Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified, ICD-10”) to improve the quality of cause-of-death data. This study analyzes the GC cause of death, considered as the indicator of data quality, in Brazil, regions, states and municipalities in 2000 and 2015. Methods: death records from the Brazilian Mortality Information System (SIM) were used. Analysis was performed for two GC groups: R codes and non-R codes, such as J18.0-J18.9 (Pneumonia unspecified). Crude and age-standardized rates, number of deaths and proportions were considered. Results: an overall improvement in the quality of mortality data in 2015 was detected, with variations among regions, age groups and size of municipalities. The improvement in the quality of mortality data in the Northeastern and Northern regions for GC-R codes is emphasized. Higher GC rates were observed among the older adults (60+ years old). The differences among the areas observed in 2015 were smaller. Conclusion: the efforts of the MoH in implementing the investigation of GC-R codes have contributed to the progress of data quality. Investment is still necessary to improve the quality of cause-of-death statistics.

scholarly journals Mathematical Modelling of the Spread of the Coronavirus under Social Restrictions

2020 ◽  
Author(s):  
Mo'tassem Al-arydah ◽  
Khalid Dib ◽  
Hailay Weldegiorgis Berhe ◽  
Kalyanasundaram Madhu
Keyword(s):  
Mathematical Modelling ◽  
Confidence Intervals ◽  
Transmission Rate ◽  
Sir Model ◽  
Death Rates ◽  
Infected People ◽  
Average Value ◽  
Social Restriction ◽  
The Times ◽  
Death Data

COVID-19 has affected most countries and declared as pandemic. Most countries have implemented some social restrictions to control it. In this work we will use mathematical modelling to assess the current social restrictions in controlling the spread of the disease. We formulate a simple susceptible-infectious-recovery (SIR) model to describe the spread of the coronavirus under social restrictions. The transmission rate in this model is considered variable to catch social restrictions impact. We analyze this model, then fit the model to 160 days induced death data in Italy, Iran, USA, Germany, France, India, Spain and China. we estimate some factors that help in understanding not only the spread of the disease but also assess the current social restriction in controlling this disease. Results: We find a formula for the basic reproduction function (R(t)) and the maximum number of daily infected people. Then estimate the model's parameters with 95% confidence intervals in these countries. We notice that the model has excellent fit to the disease death data in all considered countries except Iran. The percentage of disease death estimated by the model in Germany and France are 3.8% and 1.2% respectively, which are close to reported percentages values. Finally, we estimate the time, after first reported death, spent under social restrictions to reduce the basic reproduction function (R(t)) to one unit. The times to do that in Italy, USA, Germany, France, Spain and China are 40, 50, 34,58, 31, and 15 days respectively. However, the Indian social restrictions in the 160 days were not enough to reach $R(t)=1$. The transmission rate is between 0.1035- 1.6076 and recovery rate is between 0-0.2456. The disease death rates calculated for Germany and France are more realistic than others with average value 0.0023. Extending the same social restrictions for enough time could control the disease in Italy, USA, Germany, France, India, Spain and China. While, more social restrictions are needed to control the disease in India.

scholarly journals Incidence and Relative Risk of infection with SARS-CoV-2 virus in European Soccer Players

2021 ◽  
Author(s):  
Thomas B. Andersen ◽  
Andreas B. Dahl ◽  
Jeppe B. Carstensen
Keyword(s):  
Relative Risk ◽  
Normal Population ◽  
Soccer Players ◽  
Risk Of Infection ◽  
Infected People ◽  
True Number

AbstractThe purpose of the present study was to investigate the incidence and relative risk of infection Covid-virus in soccer players. Data from five leagues was used and compared to data from the normal population in each country. Our results revealed that the relative risk was higher in soccer players in three countries when correcting for the estimated true number of infected people in the populations. We discuss that the reason for the higher incidence in soccer players is caused by the virus entering a group of players that work closely together.

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