scholarly journals Assessment of Early Mitigation Measures Against COVID-19 in Puerto Rico: March 15-May 15, 2020

2020 ◽  
Author(s):  
Miguel Valencia ◽  
José E. Becerra ◽  
Juan C. Reyes ◽  
Kenneth G. Castro
Keyword(s):  
Growth Rate ◽  
Puerto Rico ◽  
Mitigation Measures ◽  
Test Collection ◽  
Initial Growth ◽  
Rt Pcr ◽  
Epidemic Curve ◽  
Cyclical Trend ◽  
The Impact ◽  
Pharmaceutical Interventions

ABSTRACTBackgroundOn March 15, 2020 Puerto Rico implemented non-pharmaceutical interventions (NPIs), including a mandatory curfew, as part of a state of emergency declaration to mitigate the community transmission of the SARS-CoV-2 virus. The strict enforcement of this curfew was extended through May 25, with a gradual relaxation beginning on May 1. This report summarizes an assessment of these early mitigation measures on the progression of COVID-19 in the island.Methods and FindingsFrom March 15 to May 15, 2020, 41,748 results of molecular (RT-PCR) tests were reported to the Puerto Rico Department of Health. Of these, 1,866 (4.5%) were positive, corresponding to 1,219 individuals with COVID-19 included in the study. We derived the epidemic growth rates (r) and the corresponding reproductive numbers (R) from the epidemic curve of these 1,219 individuals with laboratory-confirmed diagnosis of COVID-19 using their date of test collection as a proxy for symptoms onset. We then compared the observed cases with the R-based epidemic model projections had the mitigation measures not been implemented. Computations were conducted in the R packages forecast, incidence and projections.The number of daily RT-PCR-confirmed cases peaked on March 30 (84 cases), showing a weekly cyclical trend, with lower counts on weekends and a decreasing secular trend since March 30. The initial exponential growth rate (r) was 17.0% (95% CI: 8.4%, 25.6%), corresponding to a doubling of cases every 4.1 days, and to a reproduction number (Ro) of 1.89 (95% CI: 1.41, 2.39). After March 30, the r value reverted to an exponential decay rate (negative) of −3.6% (95% CI: −5.7%, −1.4%), corresponding to a halving of cases every 19.4 days and to an Ro of 0.90 (95% CI: 0.84, 0.97). Had the initial growth rate been maintained, a total of 18,699 (96%CI: 4,113, 87,438) COVID-19 cases would have occurred by April 30 compared with 1,119 observed.ConclusionsOur findings are consistent with very effective implementation of early non-pharmaceutical interventions (NPIs) as mitigation measures in Puerto Rico. These results serve as a baseline to assess the impact of the transition from mitigation to containment stages in Puerto Rico.

scholarly journals Impacts of coagulation on the appearance time method for new particle growth rate evaluation and their corrections

2021 ◽  
Vol 21 (3) ◽  
pp. 2287-2304
Author(s):  
Runlong Cai ◽  
Chenxi Li ◽  
Xu-Cheng He ◽  
Chenjuan Deng ◽  
Yiqun Lu ◽  
...  
Keyword(s):  
Growth Rate ◽  
Particle Growth ◽  
Particle Formation ◽  
Vapor Concentration ◽  
Initial Growth ◽  
New Particle Formation ◽  
Appearance Time ◽  
Condensation Growth ◽  
The Impact ◽  
New Particles

Abstract. The growth rate of atmospheric new particles is a key parameter that determines their survival probability of becoming cloud condensation nuclei and hence their impact on the climate. There have been several methods to estimate the new particle growth rate. However, due to the impact of coagulation and measurement uncertainties, it is still challenging to estimate the initial growth rate of new particles, especially in polluted environments with high background aerosol concentrations. In this study, we explore the influences of coagulation on the appearance time method to estimate the growth rate of sub-3 nm particles. The principle of the appearance time method and the impacts of coagulation on the retrieved growth rate are clarified via derivations. New formulae in both discrete and continuous spaces are proposed to correct for the impacts of coagulation. Aerosol dynamic models are used to test the new formulae. New particle formation in urban Beijing is used to illustrate the importance of considering the impacts of coagulation on the sub-3 nm particle growth rate and its calculation. We show that the conventional appearance time method needs to be corrected when the impacts of coagulation sink, coagulation source, and particle coagulation growth are non-negligible compared to the condensation growth. Under the simulation conditions with a constant concentration of non-volatile vapors, the corrected growth rate agrees with the theoretical growth rates. However, the uncorrected parameters, e.g., vapor evaporation and the variation in vapor concentration, may impact the growth rate obtained with the appearance time method. Under the simulation conditions with a varying vapor concentration, the average bias in the corrected 1.5–3 nm particle growth rate ranges from 6 %–44 %, and the maximum bias in the size-dependent growth rate is 150 %. During the test new particle formation event in urban Beijing, the corrected condensation growth rate of sub-3 nm particles was in accordance with the growth rate contributed by sulfuric acid condensation, whereas the conventional appearance time method overestimated the condensation growth rate of 1.5 nm particles by 80 %.

scholarly journals A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuanji Tang ◽  
Tamires D. A. Serdan ◽  
Amanda L. Alecrim ◽  
Diego R. Souza ◽  
Bruno R. M. Nacano ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Growth Rate ◽  
Good Accuracy ◽  
Simple Mathematical Model ◽  
Epidemic Curve ◽  
Local Characteristics ◽  
Stable Period ◽  
Long Duration ◽  
Short Period ◽  
The Impact

AbstractWe propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic.

scholarly journals Universal properties of the dynamics of the Covid-19 pandemics

2020 ◽  
Author(s):  
Piotr T. Chruściel ◽  
Sebastian J. Szybka
Keyword(s):  
Growth Rate ◽  
Lower Bound ◽  
Time Scale ◽  
Infected Individual ◽  
Initial Growth ◽  
Extinction Period ◽  
Present Evidence ◽  
Initial Growth Rate ◽  
Epidemic Curve ◽  
Universal Properties

We present evidence for existence of a universal lower bound for the initial growth rate of the epidemic curve of the SARS-CoV-2 coronavirus. This can be used to infer that, on average, an asymptomatic infected individual is infectious during 5.6 plus/minus 0.3 days. We further present evidence of an average time scale of 12 days for halving the number of new cases, or new deaths, during the extinction period of the first phase of the epidemic.

scholarly journals Analysis of the comprehensive non-pharmaceutical interventions and measures in containing the COVID-19 epidemic in Shenzhen: a retrospective study

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e044940
Author(s):  
Shule Xu ◽  
Peiyi Liu ◽  
Shujiang Mei ◽  
Qiuying Lv ◽  
Cong Cheng ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Quick Response ◽  
Epidemic Curve ◽  
Community Transmission ◽  
Three Stages ◽  
Short Time ◽  
Epidemiological Characteristics ◽  
The Impact ◽  
Pharmaceutical Interventions

ObjectiveTo analyse the epidemiological characteristics of family clusters of COVID-19 and the three stages of the comprehensive non-pharmaceutical interventions and measures implemented in Shenzhen.MethodsThe epidemic curve of COVID-19 was drawn and the impact of the comprehensive non-pharmaceutical interventions and measures was analysed by the different periods of the epidemic.ResultsA total of 427 cases (417 confirmed cases and 10 asymptomatic infectious cases) were reported in Shenzhen, of which 259 (60.7%) were clustered cases. 97 cluster events were drawn and most cluster events (97.3%) occurred in families. There were three stages of the COVID-19 epidemic in Shenzhen. The epidemic increased rapidly, but the peak lasted for a short time, while the decline in incidence was rapid and large.ConclusionsFamily clusters were the main feature of the COVID-19 outbreak in Shenzhen in 2020, and the Shenzhen government rolled out a quick response to the epidemic. Non-pharmaceutical interventions and measures were proven to have effectively contained community transmission, limit the transmission to aggregation and reduce the scale of transmission within a household.

scholarly journals Lifting mobility restrictions and the induced short-term dynamics of COVID-19

2020 ◽  
Author(s):  
Mario Santana-Cibrian ◽  
Manuel A. Acuna-Zegarra ◽  
Jorge X. Velasco-Hernandez
Keyword(s):  
Disease Transmission ◽  
High Mobility ◽  
Incidence Rates ◽  
Mitigation Measures ◽  
Epidemic Curve ◽  
Effective Contact ◽  
High Incidence ◽  
The World ◽  
And Control ◽  
The Impact

SARS-CoV-2 has now infected 15 million people and produced more than six hundred thousand deaths around the world. Due to high transmission levels, many governments implemented social-distancing measures and confinement with different levels of required compliance to mitigate the COVID-19 epidemic. In several countries, these measures were effective, and it was possible to flatten the epidemic curve and control it. In others, this objective was not or has not been achieved. In far to many cities around the world rebounds of the epidemic are occurring or, in others, plateau-like states have appeared where high incidence rates remain constant for relatively long periods of time. Nonetheless, faced with the challenge of urgent social need to reactivate their economies, many countries have decided to lift mitigation measures at times of high incidence. In this paper, we use a mathematical model to characterize the impact of short duration transmission events within the confinement period previous but close to the epidemic peak. The model describes too, the possible consequences on the disease dynamics after mitigation measures are lifted. We use Mexico City as a case study. The results show that events of high mobility may produce either a later higher peak, a long plateau with relatively constant but high incidence or the same peak as in the original baseline epidemic curve, but with a post-peak interval of slower decay. Finally, we also show the importance of carefully timing the lifting of mitigation measures. If this occurs during a period of high incidence, then the disease transmission will rapidly increase, unless the effective contact rate keeps decreasing, which will be very difficult to achieve once the population is released.

scholarly journals Determinants of RSV epidemiology following suppression through pandemic contact restrictions

2021 ◽  
Author(s):  
Mihaly Koltai ◽  
Fabienne Krauer ◽  
David Hodgson ◽  
Edwin van Leeuwen ◽  
Marina Treskova-Schwarzbach ◽  
...  
Keyword(s):  
Mitigation Measures ◽  
Transmission Model ◽  
Temporary Increase ◽  
Previous Exposure ◽  
Dynamic Transmission Model ◽  
Contact Frequency ◽  
Age Structured ◽  
Immune Maturation ◽  
The Impact ◽  
Pharmaceutical Interventions

Introduction COVID-19 related non-pharmaceutical interventions (NPIs) led to a suppression of RSV circulation in winter 2020/21 throughout Europe and an off-season resurgence in Summer 2021 in several European countries. We explore how such temporary interruption may shape future RSV epidemiology and what factors drive the associated uncertainty. Methods We developed an age-structured dynamic transmission model to simulate pre-pandemic RSV infections and hospitalisations. We sampled parameters governing RSV seasonality, immunity acquisition and duration of post-infection immunity and retained those simulations that qualitatively fit the UK's pre-pandemic epidemiology. From Spring 2020 to Summer 2021 we assumed a 50% reduced contact frequency, returning to pre-pandemic levels from mid-May 2021. We simulated transmission forwards until 2023 and evaluated the impact of the sampled parameters on the projected trajectories of RSV hospitalisations. Results Following a lifting of contact restrictions in summer 2021 the model replicated an out-of-season resurgence of RSV. If unmitigated, paediatric RSV hospitalisation incidence in the 2021/22 season was projected to increase by 32% to 67% compared to pre-pandemic levels. The size of the increase depended most on whether infection risk was primarily determined by immunity acquired from previous exposure or general immune maturation. While infants were less affected, the increase in seasonal hospitalisation incidence exceeded 100% in 1-2 year old children and 275% in 2-5 year old children, respectively, in some simulations where immunity from previous exposure dominated. Consequently, the average age of a case increased by 1 to 5 months, most markedly if there was strong immunity acquisition from previous exposure. If immunity to infection was largely determined by age rather than previous exposure, the 2021/22 season started earlier and lasted longer but with a peak incidence lower or similar to pre-pandemic levels. For subsequent seasons, simulations suggested a quick return to pre-pandemic epidemiology, with some slight oscillating behaviour possible depending on the strength of post-exposure immunity. Conclusion COVID-19 mitigation measures stopped RSV circulation in the 2020/21 season and generated immunity debt that will likely lead to a temporary increase in RSV burden in the season following the lifting of restrictions, particularly in 1 to 5 year old children. A more accurate understanding of immunity drivers for RSV is needed to better predict the size of such an increase and plan a potential expansion of pharmaceutical and non-pharmaceutical mitigation measures.

scholarly journals On the impact of early non-pharmaceutical interventions as containment strategies against the COVID-19 pandemic

2020 ◽  
Author(s):  
Andrés Hernández ◽  
Esteban Correa-Agudelo ◽  
Hana Kim ◽  
Adam J. Branscum ◽  
F. DeWolfe Miller ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Growth Rate ◽  
Growth Rates ◽  
Physical Distance ◽  
Added Value ◽  
Distance Measures ◽  
Mitigation Measures ◽  
Testing Data ◽  
The Impact ◽  
Mitigation Policies

ABSTRACTBackgroundThe novel coronavirus SARS-CoV-2 (COVID-19) emerged in December 2019 in Wuhan, China and has spread since then to around 210 countries and territories by April 2020. Consequently, countries have adopted physical distance measures in an attempt to mitigate the uncontrolled spread of the virus. A critical question for policymakers to inform evidence-based practice is if and how physical distance measures slowed the propagation of COVID-19 in the early phase of the pandemic.MethodsThis study aims to quantify the effects of physical distance mitigation measures on the propagation of the COVID-19 pandemic. Data from John Hopkins University on confirmed cases and testing data from the Our World in Data were used in an interrupted time series analysis to estimate the effects of physical distance measures on the growth rates of the pandemic in 12 countries of Asia, Africa, and Europe.FindingsWe found that physical distance measures produced a significant decrease in the growth rates of the COVID-19 pandemic in five countries (Austria, Belgium, Italy, Malaysia, and South Korea). The test-positivity rate was significant in understanding the slowing growth rate of COVID-19 cases caused by the mitigation measures, as it provides important context that is missing from analysis based only on confirmed case data.InterpretationPhysical distance interventions effectively slowed the progression of the COVID-19 pandemic. The results of this study could inform infectious disease mitigation policies based on physical distance measures by quantifying the differential health outcomes of a pandemic with and without physical distance interventions.RESEARCH IN CONTEXTEvidence before this studyThe SARS-CoV-2 is a new virus identified in December 2019 in the province of Wuhan, China and as never before, a remarkable number of studies and reports have been released since the start of the pandemic. Several studies have used confirmed COVID-19 cases to estimate the growth rate of the pandemic. However, many studies have discussed limitations of including only confirmed cases attributable to the lack of information about testing protocols and testing rates among different countries. Finally, some researchers proposed the analysis of reported deaths by COVID-19 as a potential solution. However, this metric results in biased estimates because deaths by COVID-19 are known to be underreported.Added value of this studyWe designed and implemented analytic methods based on our previous research applied to different infectious disease epidemics, to add evidence related to the impact of non-pharmaceutical containment strategies on the temporal progression of the COVID-19 pandemic. Specifically, this study adds quantitative evidence about the effects of physical distance measures on limiting the propagation of COVID-19 pandemics in different countries. Additionally, we included testing data in the analysis to assess intra- and inter-country variation in testing growth rates. We hypothesized that the test-positivity rate is an approximation to the incidence of the COVID-19 pandemics in countries with high testing rates. Additionally, we hypothesize that a significant decrease in the pandemic over time could be identified by a significant decrease in the confirmed cases along with a significant decrease in the test-positivity rate. Our results quantified the potential effects of physical distance interventions on the COVID-19 pandemic progression under different levels of testing and enforcement of mitigation policies.Implications of all the available evidenceOur analysis could lead to better approaches for estimating the effects of physical distance measures on the time course of infectious diseases. In addition, our analysis highlights the potential bias of estimated COVID-19 growth rates based only on confirmed cases. The results from our study could inform strategies for mitigating the COVID-19 or other future pandemics, especially in countries in an earlier stage of a pandemic.

scholarly journals Enhanced growth rate of atmospheric particles from sulfuric acid

2020 ◽  
Vol 20 (12) ◽  
pp. 7359-7372 ◽  
Author(s):  
Dominik Stolzenburg ◽  
Mario Simon ◽  
Ananth Ranjithkumar ◽  
Andreas Kürten ◽  
Katrianne Lehtipalo ◽  
...  
Keyword(s):  
Growth Rate ◽  
Sulfuric Acid ◽  
Growth Rates ◽  
Particle Number ◽  
Nuclear Research ◽  
Initial Growth ◽  
Atmospheric Conditions ◽  
European Organization ◽  
Dipole Interactions ◽  
The Impact

Abstract. In the present-day atmosphere, sulfuric acid is the most important vapour for aerosol particle formation and initial growth. However, the growth rates of nanoparticles (<10 nm) from sulfuric acid remain poorly measured. Therefore, the effect of stabilizing bases, the contribution of ions and the impact of attractive forces on molecular collisions are under debate. Here, we present precise growth rate measurements of uncharged sulfuric acid particles from 1.8 to 10 nm, performed under atmospheric conditions in the CERN (European Organization for Nuclear Research) CLOUD chamber. Our results show that the evaporation of sulfuric acid particles above 2 nm is negligible, and growth proceeds kinetically even at low ammonia concentrations. The experimental growth rates exceed the hard-sphere kinetic limit for the condensation of sulfuric acid. We demonstrate that this results from van der Waals forces between the vapour molecules and particles and disentangle it from charge–dipole interactions. The magnitude of the enhancement depends on the assumed particle hydration and collision kinetics but is increasingly important at smaller sizes, resulting in a steep rise in the observed growth rates with decreasing size. Including the experimental results in a global model, we find that the enhanced growth rate of sulfuric acid particles increases the predicted particle number concentrations in the upper free troposphere by more than 50 %.

scholarly journals The Impact of Non-Pharmaceutical Interventions on the Growth Rate of New COVID-19 Cases: Evidence From Kazakhstan and Kyrgyzstan.

2021 ◽  
Author(s):  
Simeon Nanovsky ◽  
Zhanibek Arynov ◽  
Aigul Alzhanova
Keyword(s):  
Growth Rate ◽  
Least Squares ◽  
Economic Impact ◽  
Growth Model ◽  
Ordinary Least Squares ◽  
Policy Recommendation ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Background: This article explores the effects of non-pharmaceutical interventions (NPIs also know as quarantine restrictions) on the reduction of the growth rate in new COVID-19 cases in Kazakhstan and Kyrgyzstan. It turns out that empirically NPIs gradually reduce the growth rate of new cases. This is theoretically backed by an epidemic growth model shown in the paper. Once this growth rate turns negative, it is only then that the actual levels of new cases begin to fall.Methods: The growth rate of new cases is regressed on NPIs. The contribution of NPIs is estimated via ordinary least squares. The paper is unique in that it uses the growth rate as the main dependent variable. Results: The regression results are able determine the impact of particular NPIs on the growth rate of new cases. In turns out that all types of NPIs are effective in reducing the growth rate. Conclusions: Interesting enough, comparing the results for the two countries, it appears that in the summer the partial-lockdown in Kyrgyzstan was just as effective as the full lockdown in Kazakhstan at reducing the growth rate. Therefore as a policy recommendation, and to avoid the economic impact of a full lockdown, these countries should stick with partial lockdowns. Lastly, a conservative counterfactual scenario indicates that total cases for 2020 would be 50% to 100% higher had the countries not imposed NPIs.

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