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

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.

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Real-Time Estimation of Rt for Supporting Public-Health Policies Against COVID-19

Frontiers in Public Health ◽

10.3389/fpubh.2020.556689 ◽

2020 ◽

Vol 8 ◽

Author(s):

Sebastián Contreras ◽

H. Andrés Villavicencio ◽

David Medina-Ortiz ◽

Claudia P. Saavedra ◽

Álvaro Olivera-Nappa

Keyword(s):

Public Health ◽

Real Time ◽

Reproduction Number ◽

Case Reports ◽

Mathematical Formulation ◽

Time Estimation ◽

Consensus Protocol ◽

Viral Spread ◽

Effective Interventions ◽

Secondary Infections

In the absence of a consensus protocol to slow down the spread of SARS-CoV-2, policymakers need real-time indicators to support decisions in public health matters. The Effective Reproduction Number (Rt) represents the number of secondary infections generated per each case and can be dramatically modified by applying effective interventions. However, current methodologies to calculate Rt from data remain somewhat cumbersome, thus raising a barrier between its timely calculation and application by policymakers. In this work, we provide a simple mathematical formulation for obtaining the effective reproduction number in real-time using only and directly daily official case reports, obtained by modifying the equations describing the viral spread. We numerically explore the accuracy and limitations of the proposed methodology, which was demonstrated to provide accurate, timely, and intuitive results. We illustrate the use of our methodology to study the evolution of the pandemic in different iconic countries, and to assess the efficacy and promptness of different public health interventions.

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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 ◽

10.1371/journal.pone.0252443 ◽

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.

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

10.1101/2020.03.10.20032995 ◽

2020 ◽

Cited By ~ 1

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.

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

10.1101/2020.11.05.20226597 ◽

2020 ◽

Cited By ~ 1

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

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Person, Place, and Time: Monitoring the Geographical and Temporal Context of Public Health Policies

PsycEXTRA Dataset ◽

10.1037/e507502013-086 ◽

2012 ◽

Author(s):

Michael Chaiton

Keyword(s):

Public Health ◽

Health Policies ◽

Temporal Context ◽

Public Health Policies

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Population simulations of COVID-19 outbreaks provide tools for risk assessment and continuity planning

JAMIA Open ◽

10.1093/jamiaopen/ooaa074 ◽

2021 ◽

Author(s):

Bo Peng ◽

Rowland W Pettit ◽

Christopher I Amos

Keyword(s):

Public Health ◽

Risk Assessment ◽

Emergency Response ◽

Robustness Analysis ◽

Health Policies ◽

Command Line ◽

Public Health Policies ◽

Continuity Planning ◽

Quantitative Estimates ◽

Community Infection

Abstract Objectives We developed COVID-19 Outbreak Simulator (https://ictr.github.io/covid19-outbreak-simulator/) to quantitatively estimate the effectiveness of preventative and interventive measures to prevent and battle COVID-19 outbreaks for specific populations. Materials and methods Our simulator simulates the entire course of infection and transmission of the virus among individuals in heterogeneous populations, subject to operations and influences, such as quarantine, testing, social distancing, and community infection. It provides command-line and Jupyter notebook interfaces and a plugin system for user-defined operations. Results The simulator provides quantitative estimates for COVID-19 outbreaks in a variety of scenarios and assists the development of public health policies, risk-reduction operations, and emergency response plans. Discussion Our simulator is powerful, flexible, and customizable, although successful applications require realistic estimation and robustness analysis of population-specific parameters. Conclusion Risk assessment and continuity planning for COVID-19 outbreaks are crucial for the continued operation of many organizations. Our simulator will be continuously expanded to meet this need.

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Results from the European Union MAPEC_LIFE cohort study on air pollution and chromosomal damage in children: are public health policies sufficiently protective?

Environmental Sciences Europe ◽

10.1186/s12302-020-00352-3 ◽

2020 ◽

Vol 32 (1) ◽

Cited By ~ 1

Author(s):

Elisabetta Ceretti ◽

◽

Francesco Donato ◽

Claudia Zani ◽

Milena Villarini ◽

...

Keyword(s):

Public Health ◽

Air Pollution ◽

European Union ◽

Cohort Study ◽

Health Policies ◽

The European Union ◽

Chromosomal Damage ◽

Public Health Policies

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Characterization of death from colorectal cancer in Mato Grosso State/Legal Amazon/Brazil, 2000-2016

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.1130 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

R S Caló ◽

B S N Souza ◽

N D Galvão ◽

R A G Souza ◽

J C S Oliveira ◽

...

Keyword(s):

Public Health ◽

Colorectal Cancer ◽

International Classification Of Diseases ◽

Health Policies ◽

Rectosigmoid Junction ◽

Mato Grosso ◽

Public Health Policies ◽

Goods And Services ◽

Classification Of Diseases ◽

Using Data

Abstract Background Colorectal cancer has been one of the cancers that most contributed to mortality, in both sexes in the world. In Brazil, cancer is among the top five causes of death and colorectal cancer is ranked on the fifth position. Of the Federative Units belonging to the Legal Amazon, Mato Grosso stands out for the higher adjusted incidence of colorectal cancer for both sexes. Thus, the objective is to characterize deaths from colorectal cancer, according to sociodemographic variables in Mato Grosso from 2000 to 2016. Methods A descriptive study was carried out, using data from the Mortality Information System, made available by the Department of Health of the Mato Grosso State. Deaths of all ages were selected, whose basic cause was identified by the codes from the International Classification of Diseases: (C.18) colon cancer, (C.19) rectosigmoid junction cancer, (C.20) rectal cancer or (C.21) anus cancer. Results Between 2000 and 2016, 31,607 deaths from cancer were registered. Of these, 1,750 (5.6%) were due to colorectal cancer. An increased number of deaths was observed at the end of the period, with a variation from 46 deaths in 2000 from 173 in 2016. Highest frequency was verified in men (51.3%), people aged 60 years or older (59.7%), black (54.6%), married (52.3%) and those with primary education (55.2%). According to Brazilian occupation classification options or those answers filled out on the death certificate, highest frequency were for “Retired” (26.2%), “Housewife” (23.1%), Agricultural/Forestry and Fisheries” (11.3%) and “Production of Industrial Goods and Services” (10.3%). Conclusions This study evidenced the increased number of deaths due to colorectal cancer in Mato Grosso State, and identified priority groups for interventions through public health policies which should include screening and early diagnosis to cope with the disease. Key messages Evidenced the increased number of deaths due to colorectal cancer in Mato Grosso State. Identified priority groups for interventions through public health policies.

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Epidemiological surveillance and performance assessment: the two roles of health indicators during the COVID-19 pandemic

International Journal of Law in Context ◽

10.1017/s1744552321000276 ◽

2021 ◽

Vol 17 (2) ◽

pp. 186-203

Author(s):

Nathan Genicot

Keyword(s):

Public Health ◽

Performance Assessment ◽

Health Indicators ◽

Health Policies ◽

Epidemiological Surveillance ◽

Public Health Policies ◽

History Of ◽

And Performance ◽

The One ◽

Massive Development

AbstractThe COVID-19 pandemic has given rise to the massive development and use of health indicators. Drawing on the history of international public health and of the management of infectious disease, this paper attempts to show that the normative power acquired by metrics during the pandemic can be understood in light of two rationales: epidemiological surveillance and performance assessment. On the one hand, indicators are established to evaluate and rank countries’ responses to the outbreak; on the other, the evolution of indicators has a direct influence on the content of public health policies. Although quantitative data are an absolute necessity for coping with such disasters, it is critical to bear in mind the inherent partiality and precarity of the information provided by health indicators. Given the growing importance of normative quantitative devices during the pandemic, and assuming that their influence is unlikely to decrease in the future, they call for close scrutiny.

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