Summer COVID-19 third wave: faster high altitude spread suggests high UV adaptation

Seligmann, Hervé; Vuillerme, Nicolas; Demongeot, Jacques

doi:10.1101/2020.08.17.20176628

Cited by 7 publications

(8 citation statements)

References 16 publications

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“…This ability to spread is quantified by the basic reproduction number R 0 (also called the average reproductive rate), a classical epidemiologic parameter that describes the transmissibility of an infectious disease and is equal to the number of susceptible individuals that an infectious individual can transmit the disease to during his contagiousness period. For contagious diseases, the transmissibility is not a biological constant: it is affected by numerous factors, including endogenous factors, such as the concentration of the virus in aerosols emitted by the patient (variable during his contagiousness period), and exogenous factors, such as geo-climatic, demographic, socio-behavioral and economic factors governing pathogen transmission (variable during the outbreak's history) [4][5][6][7][8].…”

Section: Introduction 1overview and Literature Reviewmentioning

confidence: 99%

Estimation of Daily Reproduction Numbers during the COVID-19 Outbreak

et al. 2021

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(1) Background: The estimation of daily reproduction numbers throughout the contagiousness period is rarely considered, and only their sum R0 is calculated to quantify the contagiousness level of an infectious disease. (2) Methods: We provide the equation of the discrete dynamics of the epidemic’s growth and obtain an estimation of the daily reproduction numbers by using a deconvolution technique on a series of new COVID-19 cases. (3) Results: We provide both simulation results and estimations for several countries and waves of the COVID-19 outbreak. (4) Discussion: We discuss the role of noise on the stability of the epidemic’s dynamics. (5) Conclusions: We consider the possibility of improving the estimation of the distribution of daily reproduction numbers during the contagiousness period by taking into account the heterogeneity due to several host age classes.

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Section: Introduction 1overview and Literature Reviewmentioning

confidence: 99%

Estimation of Daily Reproduction Numbers during the COVID-19 Outbreak

et al. 2021

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“…The mathematical characterisation by population entropy defined in (18) of the stochastic stability of the dynamics described by equation (17) has its origin in the theory of large deviations [25,26,27]. This notion of stability pertains to the rate at which the system returns to its steady state conditions after a random exogenous and/or endogenous perturbation and it could be useful to quantify the variations of the distribution of the daily reproduction rates observed for many countries.…”

Section: Discussionmentioning

confidence: 99%

“…It is easy to show that, if X o = 1 and r = 5 (inside the estimated interval of the duration of the maximal contagion period for the COVID-19 [5,6,7,8,9,10,11,12,13,14,15,16,17], we obtain: …”

Section: Methodsmentioning

confidence: 99%

Estimation of Daily Reproduction rates in COVID-19 Outbreak

Demongeot

Oshinubi

Seligmann

et al. 2021

Preprint

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Abstract(1) BackgroundThe estimation of daily reproduction rates throughout the infectivity period is rarely considered and only their sum Ro is calculated to quantify the level of virulence of an infectious agent;(2) MethodsWe give the equation of the discrete dynamics of epidemic growth and we obtain an estimation of the daily reproduction rates, by using a technique of deconvolution of the series of observed new cases of Covid-19;(3) ResultsWe give both simulation results as well as estimations for several countries for the Covid-19 outbreak;(4) ConclusionsWe discuss the role of the noise on the precision of the estimation and we open on perspectives of forecasting methods to predict the distribution of daily reproduction rates along the infectivity period.

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“…Although the United States only comprises 4% of the global population, it exceeds 20% of the global COVID-19 caseload [22]. Presently, the world is implementing policies to control the second wave of COVID-19, while the United States is responding to its third wave [23][24][25].…”

Section: Public Health Policies and Governancementioning

confidence: 99%

Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study (Preprint)

Post¹,

Issa²,

Boctor³

et al. 2020

Preprint

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BACKGROUND The emergence of SARS-CoV-2, the virus that causes COVID-19, has led to a widespread global pandemic not seen since the 1918 influenza outbreak. The empirical question is if the current pandemic would attenuate from an approach taken by President Wilson used during the Influenza Pandemic of 1918 that killed some 675,000 Americans and up to 50 million people worldwide or by the approach President Franklin Roosevelt implemented to control malaria in the 1940s. OBJECTIVE To test COVID-19 control policies at the federal and state level with surveillance metrics including 1) speed, 2) acceleration, 3) jerk, 4) 7-day persistence. We will surveil COVID transmission using standard surveillance techniques, novel rates of increase and persistence, combined with overall caseload. Novel indicators improve our understanding of where and how rapidly SARS-CoV-2 is transmitting, and quantifies shifts in the rate of acceleration or deceleration by state to inform policy targeting mitigation and prevention strategies in the U.S. METHODS Using a longitudinal trend analysis study design, we extracted 60 days of COVID data from public health registries. We use an empirical difference equation to measure daily case numbers in 50 US states and Washington D.C. as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments (GMM) approach by implementing the Arellano-Bond estimator in R. RESULTS There is variation between and within states with some exemplars of good public health practice such as VT, NH, and ME. The overall U.S. caseload and increases in rates of infection translate into the country with highest caseload of coronavirus infections and deaths. The US 7-Day Persistence rate means super spreader events such as rallies, college parties, and other social gatherings not only infect large numbers of people but those infections echo forward with additional infections. Moving forward, blaming the virus on China or Spain was neither warranted nor helpful in controlling COVID-19 or the Influenza Pandemic; nor is censorship of the media or misinformation via social media. Other obstacles to recovery such as expressing skepticism of science and overt denial of the facts didn’t work for President Wilson during the 1918 influenza pandemic nor is it helpful today. We need a Roosevelt and not a Wilson response to the pandemic to return to normal. The current U.S. response to COVID-19 parallels President Wilson’s response to the 1918 Influenza Pandemic that killed 50 million people based on 1) no national response to control the outbreak; 2) misinformation; 3) unclear communication with the public; 4) widespread mistrust and panic. CONCLUSIONS There is variation between and within states with some exemplars of good public health practice such as VT, NH, and ME. The overall U.S. caseload and increases in rates of infection translate into the country with highest caseload of coronavirus infections and deaths. The US 7-Day Persistence rate means super spreader events such as rallies, college parties, and other social gatherings not only infect large numbers of people but those infections echo forward with additional infections. Moving forward, blaming the virus on China or Spain was neither warranted nor helpful in controlling COVID-19 or the Influenza Pandemic; nor is censorship of the media or misinformation via social media. Other obstacles to recovery such as expressing skepticism of science and overt denial of the facts didn’t work for President Wilson during the 1918 influenza pandemic nor is it helpful today. We need a Roosevelt and not a Wilson response to the pandemic to return to normal. The current U.S. response to COVID-19 parallels President Wilson’s response to the 1918 Influenza Pandemic that killed 50 million people based on 1) no national response to control the outbreak; 2) misinformation; 3) unclear communication with the public; 4) widespread mistrust and panic. CLINICALTRIAL NA INTERNATIONAL REGISTERED REPORT RR2-24248

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Summer COVID-19 third wave: faster high altitude spread suggests high UV adaptation

Cited by 7 publications

References 16 publications

Estimation of Daily Reproduction Numbers during the COVID-19 Outbreak

Estimation of Daily Reproduction Numbers during the COVID-19 Outbreak

Estimation of Daily Reproduction rates in COVID-19 Outbreak

Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study (Preprint)

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