scholarly journals Tracking the Dynamics and Allocating Tests for COVID-19 in Real-Time: an Acceleration Index with an Application to French Age Groups and Départements*

2020 ◽  
Author(s):  
Christelle Baunez ◽  
Mickael Degoulet ◽  
Stéphane Luchini ◽  
Patrick A. Pintus ◽  
Miriam Teschl
Keyword(s):  
Public Health ◽  
Real Time ◽  
Age Groups ◽  
Population Based ◽  
Jel Classification ◽  
National Average ◽  
Health Policies ◽  
Age Group ◽  
Actual Distribution ◽  
Public Health Policies

AbstractAn acceleration index is proposed as a novel indicator to track the dynamics of the COVID-19 in real-time. Using French data on cases and tests for the period following the first lock-down - from May 13, 2020, onwards - our acceleration index shows that the ongoing pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration has been stronger than national average for the [59 − 68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19 − 28] age group is the lowest and is about half that of the [69 − 78], as of October 25. In addition, we propose an algorithm to allocate tests among French départements, based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France enters a second lock-down period with indeterminate duration.JEL Classification NumbersI18; H12

scholarly journals Tracking the dynamics and allocating tests for COVID-19 in real-time: An acceleration index with an application to French age groups and départements

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252443
Author(s):  
Christelle Baunez ◽  
Mickael Degoulet ◽  
Stéphane Luchini ◽  
Patrick A. Pintus ◽  
Miriam Teschl
Keyword(s):  
Public Health ◽  
Real Time ◽  
Age Groups ◽  
Population Based ◽  
National Average ◽  
Health Policies ◽  
Age Group ◽  
Actual Distribution ◽  
Public Health Policies ◽  
Using Data

An acceleration index is proposed as a novel indicator to track the dynamics of COVID-19 in real-time. Using data on cases and tests in France for the period between the first and second lock-downs—May 13 to October 25, 2020—our acceleration index shows that the pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration was stronger than national average for the [59–68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19–28] age group was the lowest and is about half that of the [69–78]. In addition, we propose an algorithm to allocate tests among French “départements” (roughly counties), based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France might possibly enter a third lock-down period with indeterminate duration.

scholarly journals The incidence of stroke in pediatric patients in Brazil

2021 ◽  
Author(s):  
Rafaela Sandes Fonseca ◽  
Louise Seixas Lordêllo ◽  
Beatriz Gusmão Azevêdo ◽  
Lara Teixeira de Oliveira ◽  
Giovanna Carvalho Sousa ◽  
...  
Keyword(s):  
Public Health ◽  
Mortality Rate ◽  
Pediatric Patients ◽  
Total Mortality ◽  
Health Policies ◽  
Limiting Factor ◽  
Age Group ◽  
Public Health Policies ◽  
Brain Stroke ◽  
Using Data

Background: Stroke is rare in pediatric patients, but it is of paramount importance due to its serious complications. The study of the incidence of strokes in these patients is important for us to be able to adequate public health policies. Objectives: To evaluate the incidence of strokes in pediatric patients in Brazil. Design and setting: Descriptive, retrospective study, carried out using data from the Hospital Information System (SIH/SUS), from 2011 to 2020. Methods: Variables: brain stroke not specific for the hemorrhagic or ischemic type, mortality, hospitalizations, sex, ethnicity and age group from 0 to 19 years of age. Results: During the period from 2011 from 2020, there were a total of 6912 cases of stroke in the age group from 0 to 19 years; the highest incidence in 2019 (10.59%) and the lowest incidence in 2020 (8.65%.) The age group from 15 to 19 accumulated the greatest number of cases (60.40%). The total mortality rate was 8.12% (561 cases). The highest mortality rate was observed between 15 and 19 years of age (62.03%), and the lowest between 5 and 9 years of age(4.63%). The incidence was slightly higher in males (50.41%). Conclusions: Similar annual stroke rates were identified during the analyzed period, demonstrating the need for interventional actions to reduce its incidence. The non-specification of the hemorrhagic or ischemic types is a limiting factor, since the prevention management is different in each case. There was a higher prevalence, as well as a higher mortality rate, from 15 to 19 years.

scholarly journals Do men need special services?

2001 ◽  
Vol 7 (2) ◽  
pp. 93-99 ◽  
Author(s):  
Harry Kennedy
Keyword(s):  
Public Health ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Special Needs ◽  
Age Groups ◽  
Health Policies ◽  
Public Health Policies ◽  
Special Services

The targeting of services to groups with special needs is today commonplace in enlightened public health policies. To list men among the ‘minorities’ in need of such special help might have the semblance of satire. This air of levity is not really reduced by listing male's shorter life expectancy, higher infant mortality and higher rates of natural and unnatural deaths in all age groups (Drever & Bunting, 1997; Kelly & Bunting, 1998).

scholarly journals Revealing the influence of national public health policies for the outbreak of the SARS-CoV-2 epidemic in Wuhan, China through status dynamic modeling

2020 ◽  
Author(s):  
Tianyi Qiu ◽  
Han Xiao
Keyword(s):  
Public Health ◽  
Real Time ◽  
Dynamic Model ◽  
Health Policies ◽  
Chinese Government ◽  
Wuhan City ◽  
Public Health Policies ◽  
Infected People ◽  
End Point ◽  
National Public Health

SummaryBackgroundThe epidemic caused by SARS-CoV-2 was first reported in Wuhan, China, and now is spreading worldwide. The Chinese government responded to this epidemic with multiple public health policies including locking down the city of Wuhan, establishing multiple temporary hospitals, and prohibiting public gathering events. Here, we constructed a new real-time status dynamic model of SEIO (MH) to reveal the influence of national public health policies and to model the epidemic in Wuhan.MethodsA real-time status dynamic model was proposed to model the population of Wuhan in status Susceptible (S), Exposed (E), Infected with symptoms (I), with Medical care (M), and Out of the system (O) daily. Model parameters were fitted according to the daily report of new infections from Jan. 27th, 2020 to Feb. 2nd, 2020. Using the fitted parameters, the epidemic under different conditions was simulated and compared with the current situation.FindingAccording to our study, the first patient is most likely appeared on Nov. 29th, 2019. There had already been 4,153 infected people and 6,536 exposed ones with the basic reproduction number R0 of 2.65 before lockdown, whereas R0 dropped to 1.98 for the first 30 days after the lockdown. The peak point is Feb. 17th, 2020 with 24,115 infected people and the end point is Jun. 17th, 2020. In total, 77,453 people will be infected. If lockdown imposed 7 days earlier, the total number of infected people would be 21,508, while delaying the lockdown by 1-6 days would expand the infection scale 1.23 to 4.94 times. A delay for 7 days would make the epidemic finally out of control. Doubling the number of beds in hospitals would decrease the total infections by 28%, and further investment in bed numbers would yield a diminishing return. Last, public gathering events that increased the transmission parameter by 5% in one single day would increase 4,243 infected people eventually.InterpretationOur model forecasted that the peak time in Wuhan was Feb. 17th, 2020 and the epidemic in Wuhan is now under control. The outbreak of SARS-CoV-2 is currently a global public health threat for all nations. Multiple countries including South Korea, Japan, Iran, Italy, and the United States are suffering from SARS-CoV-2. Our study, which simulated the epidemic in Wuhan, the first city in the world fighting against SARS-CoV-2, may provide useful guidance for other countries in dealing with similar situations.FundingNational Natural Science Foundation of China (31900483) and Shanghai Sailing program (19YF1441100).Research in contextEvidence before this studyThe epidemic of SARS-CoV-2 has been currently believed to started from Wuhan, China. The Chinese government started to report the data including infected, cured and dead since Jan 20th, 2020. We searched PubMed and preprint archives for articles published up to Feb 28th, 2020, which contained information about the Wuhan outbreak using the terms of “SARS-CoV-2”, “2019-nCoV”, “COVID-19”, “public health policies”, “coronavirus”, “CoV”, “Wuhan”, “transmission model”, etc. And a number of articles were found to forecast the early dynamics of the SARS-CoV-2 epidemic and clinical characteristics of COVID-19. Several of them mentioned the influence of city lockdown, whereas lacked research focused on revealing the impact of public health policies for the outbreak of SARS-CoV-2 through modeling study.Added value of this studyAs the first study systemically analysis the effect of three major public health policies including 1) lockdown of Wuhan City, 2) construction of temporary hospitals and 3) reduction of crowed gathering events in Wuhan city. The results demonstrated the epidemic in Wuhan from the potential first patient to the end point as well as the influence of public health policies are expected to provide useful guidance for other countries in fighting against the epidemic of SRAS-CoV-2.Implications of all the available evidenceAvailable evidence illustrated the human-to-human transmission of SARS-CoV-2, in which the migration of people in China during the epidemic may quickly spread the epidemic to the rest of the nation. These findings also suggested that the lockdown of Wuhan city may slow down the spread of the epidemic in the rest of China.

scholarly journals Real-time estimation of R0 for supporting public-health policies against COVID-19

2020 ◽  
Author(s):  
Sebastián Contreras ◽  
H. Andrés Villavicencio ◽  
David Medina-Ortiz ◽  
Claudia P. Saavedra ◽  
Álvaro Olivera-Nappa
Keyword(s):  
Public Health ◽  
Real Time ◽  
Case Reports ◽  
Mathematical Formulation ◽  
Time Estimation ◽  
Control Measures ◽  
Health Policies ◽  
Consensus Protocol ◽  
Public Health Policies ◽  
Viral Spread

AbstractBackgroundIn the absence of a consensus protocol to slow down the current SARS-CoV2 spread, policy makers are in need of real-time indicators to support decisions in public health matters. The Basic Reproduction Number (R0) represents viral spread rate and can be dramatically modified by the application of effective public control measures. However, current methodologies to calculate R0 from data remain cumbersome and unusable during an outbreak.ObjectiveTo provide a simple mathematical formulation for obtaining R0 in Real-Time, and apply it to assess the effectiveness of public-health policies in different iconic countries.Study designBy modifying the equations describing the spread of the virus, we derived a real-time R0 estimator that can be readily calculated from daily official case reports.ResultsWe show the application of a time trend analysis of the R0 estimator to assess the efficacy and promptness of public health measures that impacted on the development of the COVID-19 epidemic in iconic countries.ConclusionsWe propose our simple estimator and method as useful tools to follow and assess in real time the effectiveness of public health policies on COVID-19 evolution.

scholarly journals Emergency department use during COVID-19 as described by syndromic surveillance

2020 ◽  
Vol 37 (10) ◽  
pp. 600-604 ◽  
Author(s):  
Helen E Hughes ◽  
Thomas C Hughes ◽  
Roger Morbey ◽  
Kirsty Challen ◽  
Isabel Oliver ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Real Time ◽  
Respiratory Infection ◽  
Acute Respiratory Infection ◽  
Syndromic Surveillance ◽  
Rapid Development ◽  
Age Groups ◽  
Age Group ◽  
Syndromic Surveillance System

On 12 March 2020 the UK entered the ‘delay phase’ of the COVID-19 pandemic response. The Public Health England Emergency Department Syndromic Surveillance System (EDSSS) carries out daily (near real-time) public health surveillance of emergency department (ED) attendances across England. This retrospective observational analysis of EDSSS data aimed to describe changes in ED attendances during March–April 2020, and identify the attendance types with the largest impact. Type 1 ED attendances were selected from 109 EDs that reported data to EDSSS for the period 1 January 2019 to 26 April 2020. The daily numbers of attendances were plotted by age group and acuity of presentation. The 2020 ’COVID-19’ period (12 March 2020 to 26 April 2020) attendances were compared with the equivalent 2019 ’pre-COVID-19’ period (14 March 2019 to 28 April 2019): in total; by hour and day of the week; age group(<1, 1-4, 15-14, 15-44, 45-64 and 65+ years); gender; acuity; and for selected syndromic indicators(acute respiratory infection, gastroenteritis, myocardial ischaemia). Daily ED attendances up to 11 March 2020 showed regular trends, highest on a Monday and reduced in children during school holidays. From 12 March 2020 ED attendances decreased across all age groups, all acuity levels, on all days and times. Across age groups the greatest percentage reductions were seen in school age children (5–14 years). By acuity, the greatest reduction occurred in the less severe presentations. Syndromic indicators showed that the greatest reductions were in non-respiratory indicators, which fell by 44–67% during 2020 COVID-19, while acute respiratory infection was reduced by −4.4% (95% CI −9.5% to 0.6%). ED attendances in England have been particularly affected during the COVID-19 pandemic due to changes in healthcare seeking behaviour. EDSSS has enabled real-time daily monitoring of these changes, which are made publicly available to facilitate action. The EDSSS provides valuable surveillance of ED attendances in England. The flexibility of EDSSS allowed rapid development of new indicators (including COVID-19-like) and reporting methods.

scholarly journals Data as promise: Reconfiguring Danish public health through personalized medicine

2019 ◽  
Vol 49 (4) ◽  
pp. 531-555 ◽  
Author(s):  
Klaus Hoeyer
Keyword(s):  
Public Health ◽  
Personalized Medicine ◽  
Population Based ◽  
Data Driven ◽  
Health Policies ◽  
Public Health Policies ◽  
Roles And Responsibilities ◽  
Population Science ◽  
The Individual ◽  
Existing Data

‘Personalized medicine’ might sound like the very antithesis of population science and public health, with the individual taking the place of the population. However, in practice, personalized medicine generates heavy investments in the population sciences – particularly in data-sourcing initiatives. Intensified data sourcing implies new roles and responsibilities for patients and health professionals, who become responsible not only for data contributions, but also for responding to new uses of data in personalized prevention, drawing upon detailed mapping of risk distribution in the population. Although this population-based ‘personalization’ of prevention and treatment is said to be about making the health services ‘data-driven’, the policies and plans themselves use existing data and evidence in a very selective manner. It is as if data-driven decision-making is a promise for an unspecified future, not a demand on its planning in the present. I therefore suggest interrogating how ‘promissory data’ interact with ideas about accountability in public health policies, and also with the data initiatives that the promises bring about. Intensified data collection might not just be interesting for what it allows authorities to do and know, but also for how its promises of future evidence can be used to postpone action and sidestep uncomfortable knowledge in the present.

scholarly journals Global Temporal Patterns of Age Group and Sex Distributions of COVID-19

2021 ◽  
Vol 13 (2) ◽  
pp. 582-596
Author(s):  
Russell Leong ◽  
Tin-Suet Joan Lee ◽  
Zejia Chen ◽  
Chelsea Zhang ◽  
Jianping Xu
Keyword(s):  
Public Health ◽  
Real Time ◽  
Temporal Change ◽  
Age Groups ◽  
Age Group ◽  
Health Crisis ◽  
Public Health Crisis ◽  
Health Measures ◽  
The World ◽  
Significant Patterns

Since the beginning of 2020, COVID-19 has been the biggest public health crisis in the world. To help develop appropriate public health measures and deploy corresponding resources, many governments have been actively tracking COVID-19 in real time within their jurisdictions. However, one of the key unresolved issues is whether COVID-19 was distributed differently among different age groups and between the two sexes in the ongoing pandemic. The objectives of this study were to use publicly available data to investigate the relative distributions of COVID-19 cases, hospitalizations, and deaths among age groups and between the sexes throughout 2020; and to analyze temporal changes in the relative frequencies of COVID-19 for each age group and each sex. Fifteen countries reported age group and/or sex data of patients with COVID-19. Our analyses revealed that different age groups and sexes were distributed differently in COVID-19 cases, hospitalizations, and deaths. However, there were differences among countries in both their age group and sex distributions. Though there was no consistent temporal change across all countries for any age group or either sex in COVID-19 cases, hospitalizations, and deaths, several countries showed statistically significant patterns. We discuss the potential mechanisms for these observations, the limitations of this study, and the implications of our results on the management of this ongoing pandemic.

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