scholarly journals Modeling infection dynamics and mitigation strategies to support K-6 in-person instruction during the COVID-19 pandemic

2021 ◽  
Author(s):  
Douglas E. Morrison ◽  
Roch Nianogo ◽  
Vladimir Manuel ◽  
Onyebuchi A. Arah ◽  
Nathaniel Anderson ◽  
...  
Keyword(s):  
School Attendance ◽  
Secondary Infection ◽  
Mitigation Strategies ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
Safety Education ◽  
Vaccination Rates ◽  
Health Authorities ◽  
Infection Dynamics ◽  
Public Health Authorities

AbstractObjectiveTo support safer in-person K-6 instruction during the coronavirus disease 2019 (COVID- 19) pandemic by providing public health authorities and school districts with a practical model of transmission dynamics and mitigation strategies.MethodsWe developed an agent-based model of infection dynamics and preventive mitigation strategies such as distancing, health behaviors, surveillance and symptomatic testing, daily symptom and exposure screening, quarantine policies, and vaccination. The model parameters can be updated as the science evolves and are adjustable via an online user interface, enabling users to explore the effects of interventions on outcomes of interest to states and localities, under a variety of plausible epidemiological and policy assumptions.ResultsUnder default assumptions, secondary infection rates and school attendance are substantially affected by surveillance testing protocols, vaccination rates, class sizes, and effectiveness of safety education.ConclusionsOur model helps policymakers consider how mitigation options and the dynamics of school infection risks affect outcomes of interest. The model’s parameters can be immediately updated in response to changes in epidemiological conditions, science of COVID-19 transmission dynamics, testing and vaccination resources, and reliability of mitigation strategies.

scholarly journals The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout

2021 ◽  
Author(s):  
Alexandra Teslya ◽  
Ganna Rozhnova ◽  
Thi Mui Pham ◽  
Daphne van Wees ◽  
Hendrik Nunner ◽  
...  
Keyword(s):  
Vaccination Coverage ◽  
Vaccine Coverage ◽  
Transmission Model ◽  
Cumulative Number ◽  
Vaccination Rates ◽  
Contact Rates ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Vaccination Campaigns ◽  
The Impact

Abstract Mass vaccination campaigns against SARS-CoV-2 are under way in many countries with the hope that increasing vaccination coverage will enable reducing current physical distancing measures. Compliance with these measures is waning, while more transmissible virus variants such as B.1.1.7 have emerged. Using SARS-CoV-2 transmission model we investigated the impact of the feedback between compliance, the incidence of infection, and vaccination coverage on the success of a vaccination programme in the population where waning of compliance depends on vaccine coverage. Our results suggest that the combination of fast waning compliance, slow vaccination rates, and more transmissible variants may result in a higher cumulative number of infections than in a situation without vaccination. These adverse effects can be alleviated if vaccinated individuals do not revert to pre-pandemic contact rates, and if non-vaccinated individuals remain compliant with physical distancing measures. Both require convincing, clear and appropriately targeted communication strategies by public health authorities.

scholarly journals Evaluating the impacts of non-pharmaceutical interventions on the transmission dynamics of COVID-19 in Canada based on mobile network

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261424
Author(s):  
Ling Xue ◽  
Shuanglin Jing ◽  
Hao Wang
Keyword(s):  
Complex Dynamics ◽  
Human Mobility ◽  
Mobile Network ◽  
Mitigation Strategies ◽  
Transmission Dynamics ◽  
Mobility Data ◽  
Cross Correlation Analysis ◽  
Public Health Authorities ◽  
Canadian Provinces ◽  
Pharmaceutical Interventions

The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada’s provinces since it was first reported more than a year ago. During the COVID-19 epidemic, Canadian provinces have implemented many Non-Pharmaceutical Interventions (NPIs). However, the spread of the COVID-19 epidemic continues due to the complex dynamics of human mobility. We develop a meta-population network model to study the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies in different provinces of Canada, such as the timing of implementing NPIs, the human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences due to work and recreation. To determine which activity is most closely related to the dynamics of COVID-19, we use the cross-correlation analysis to find that the positive correlation is the highest between the mobility data of parks and the weekly number of confirmed COVID-19 from February 15 to December 13, 2020. The average effective reproduction numbers in nine Canadian provinces are all greater than one during the time period, and NPIs have little impact on the dynamics of COVID-19 epidemics in Ontario and Saskatchewan. After November 20, 2020, the average infection probability in Alberta became the highest since the start of the COVID-19 epidemic in Canada. We also observe that human activities around residences do not contribute much to the spread of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human mobility is effective in mitigating COVID-19 transmission in Canada. Our findings can provide guidance for public health authorities in projecting the effectiveness of future NPIs.

ARIMA Model Estimation Based on Genetic Algorithm for COVID-19 Mortality Rates

2021 ◽  
pp. 1-24 ◽  
Author(s):  
Mohanad A. Deif ◽  
Ahmed A. A. Solyman ◽  
Rania E. Hammam
Keyword(s):  
Genetic Algorithm ◽  
Moving Average ◽  
Arima Model ◽  
Hybrid Genetic Algorithm ◽  
Mortality Rates ◽  
Model Parameters ◽  
Efficient Manner ◽  
Contagious Diseases ◽  
Health Authorities ◽  
Public Health Authorities

This paper presents a forecasting model for the mortality rates of COVID-19 in six of the top most affected countries depending on the hybrid Genetic Algorithm and Autoregressive Integrated Moving Average (GA-ARIMA). It was aimed to develop an advanced and reliable predicting model that provides future forecasts of possible confirmed cases and mortality rates (Total Deaths per 1 million Population of COVID-19) that could help the public health authorities to develop plans required to resolve the crisis of the pandemic threat in a timely and efficient manner. The study focused on predicting the mortality rates of COVID-19 because the mortality rate determines the prevalence of highly contagious diseases. The Genetic algorithm (GA) has the capability of improving the forecasting performance of the ARIMA model by optimizing the ARIMA model parameters. The findings of this study revealed the high prediction accuracy of the proposed (GA-ARIMA) model. Moreover, it has provided better and consistent predictions compared to the traditional ARIMA model and can be a reliable method in predicting expected death rates as well as confirmed cases of COVID-19. Hence, it was concluded that combining ARIMA with GA is further accurate than ARIMA alone and GA can be an alternative to find the parameters and model orders for the ARIMA model.

scholarly journals Unraveling the COVID-19 hospitalization dynamics in Spain using publicly available data

2021 ◽  
Author(s):  
Alberto Aleta ◽  
Juan Luis Blas-Laína ◽  
Gabriel Tirado Anglés ◽  
Yamir Moreno
Keyword(s):  
Economic Status ◽  
Healthcare Services ◽  
Model Parameters ◽  
Health Authorities ◽  
Infection Dynamics ◽  
Bayesian Inference Method ◽  
Different Populations ◽  
Autonomous Regions ◽  
The Impact

SummaryBackgroundOne of the main challenges of the ongoing COVID-19 pandemic is to be able to make sense of available, but often heterogeneous and noisy data, to characterize the evolution of the SARS-CoV-2 infection dynamics, with the additional goal of having better preparedness and planning of healthcare services. This contribution presents a data-driven methodology that allows exploring the hospitalization dynamics of COVID-19, exemplified with a study of 17 autonomous regions in Spain.MethodsWe use data on new daily cases and hospitalizations reported by the Ministry of Health of Spain to implement a Bayesian inference method that allows making short and mid-term predictions of bed occupancy of COVID-19 patients in each of the autonomous regions of the country.FindingsWe show how to use given and generated temporal series for the number of daily admissions and discharges from hospital to reproduce the hospitalization dynamics of COVID-19 patients. For the case-study of the region of Aragon, we estimate that the probability of being admitted to hospital care upon infection is 0·090 [0·086-0·094], (95% C.I.), with the distribution governing hospital admission yielding a median interval of 3·5 days and an IQR of 7 days. Likewise, the distribution on the length of stay produces estimates of 12 days for the median and 10 days for the IQR. A comparison between model parameters for the regions analyzed allows to detect differences and changes in policies of the health authorities.InterpretationThe amount of data that is currently available is limited, and sometimes unreliable, hindering our understanding of many aspects of this pandemic. We have observed important regional differences, signaling that to properly compare very different populations, it is paramount to acknowledge all the diversity in terms of culture, socio-economic status and resource availability. To better understand the impact of this pandemic, much more data, disaggregated and properly annotated, should be made available.

scholarly journals The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout

2021 ◽  
Author(s):  
Alexandra Teslya ◽  
Ganna Rozhnova ◽  
Thi Mui Pham ◽  
Daphne van Wees ◽  
Hendrik Nunner ◽  
...  
Keyword(s):  
Vaccination Coverage ◽  
Vaccine Coverage ◽  
Transmission Model ◽  
Cumulative Number ◽  
Vaccination Rates ◽  
Contact Rates ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Vaccination Campaigns ◽  
The Impact

Abstract Mass vaccination campaigns against SARS-CoV-2 are under way in many countries with the hope that increasing vaccination coverage will enable reducing current physical distancing measures. Compliance with these measures is waning, while more transmissible virus variants such as B.1.1.7 have emerged. Using SARS-CoV-2 transmission model we investigated the impact of the feedback between compliance, the incidence of infection, and vaccination coverage on the success of a vaccination programme in the population where waning of compliance depends on vaccine coverage. Our results suggest that the combination of fast waning compliance, slow vaccination rates, and more transmissible variants may result in a higher cumulative number of infections than in a situation without vaccination. These adverse effects can be alleviated if vaccinated individuals do not revert to pre-pandemic contact rates, and if non-vaccinated individuals remain compliant with physical distancing measures. Both require convincing, clear and appropriately targeted communication strategies by public health authorities.

scholarly journals Phylogenomic Evidence of Reinfection and Persistence of SARS-CoV-2: First Report from Colombia

Vaccines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 282
Author(s):  
Juan David Ramírez ◽  
Marina Muñoz ◽  
Nathalia Ballesteros ◽  
Luz H. Patiño ◽  
Sergio Castañeda ◽  
...  
Keyword(s):  
Viral Persistence ◽  
Transmission Dynamics ◽  
Polymorphism Analysis ◽  
Rt Pcr ◽  
Paired Samples ◽  
Infection Dynamics ◽  
Oxford Nanopore ◽  
Novel Variants ◽  
First Time ◽  
Oxford Nanopore Technologies

The continuing evolution of SARS-CoV-2 and the emergence of novel variants have raised concerns about possible reinfection events and potential changes in the coronavirus disease 2019 (COVID-19) transmission dynamics. Utilizing Oxford Nanopore technologies, we sequenced paired samples of three patients with positive RT-PCR results in a 1–2-month window period, and subsequent phylogenetics and genetic polymorphism analysis of these genomes was performed. Herein, we report, for the first time, genomic evidence of one case of reinfection in Colombia, exhibiting different SARS-CoV-2 lineage classifications between samples (B.1 and B.1.1.269). Furthermore, we report two cases of possible viral persistence, highlighting the importance of deepening our understanding on the evolutionary intra-host traits of this virus throughout different timeframes of disease progression. These results emphasize the relevance of genomic surveillance as a tool for understanding SARS-CoV-2 infection dynamics, and how this may translate effectively to future control and mitigations efforts, such as the national vaccination program.

scholarly journals Users’ Beliefs Toward Physical Distancing in Facebook Pages of Public Health Authorities During COVID-19 Pandemic in Early 2020

2021 ◽  
pp. 109019812110144
Author(s):  
Soon Guan Tan ◽  
Aravind Sesagiri Raamkumar ◽  
Hwee Lin Wee
Keyword(s):  
Public Health ◽  
Health Belief Model ◽  
United States Public Health ◽  
Health Belief ◽  
The United States ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Control And Prevention ◽  
Belief Model ◽  
The Health Belief Model

This study aims to describe Facebook users’ beliefs toward physical distancing measures implemented during the Coronavirus disease (COVID-19) pandemic using the key constructs of the health belief model. A combination of rule-based filtering and manual classification methods was used to classify user comments on COVID-19 Facebook posts of three public health authorities: Centers for Disease Control and Prevention of the United States, Public Health England, and Ministry of Health, Singapore. A total of 104,304 comments were analyzed for posts published between 1 January, 2020, and 31 March, 2020, along with COVID-19 cases and deaths count data from the three countries. Findings indicate that the perceived benefits of physical distancing measures ( n = 3,463; 3.3%) was three times higher than perceived barriers ( n = 1,062; 1.0%). Perceived susceptibility to COVID-19 ( n = 2,934; 2.8%) was higher compared with perceived severity ( n = 2,081; 2.0%). Although susceptibility aspects of physical distancing were discussed more often at the start of the year, mentions on the benefits of intervention emerged stronger toward the end of the analysis period, highlighting the shift in beliefs. The health belief model is useful for understanding Facebook users’ beliefs at a basic level, and it provides a scope for further improvement.

scholarly journals Modeling Epidemic Spread among a Commuting Population Using Transport Schemes

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1861
Author(s):  
Daniela Calvetti ◽  
Alexander P. Hoover ◽  
Johnie Rose ◽  
Erkki Somersalo
Keyword(s):  
Network Model ◽  
Transport Theory ◽  
Optimal Transport ◽  
State Level ◽  
Compartment Model ◽  
Census Bureau ◽  
Mitigation Strategies ◽  
Mitigation Measures ◽  
Metapopulation Model ◽  
Infection Dynamics

Understanding the dynamics of the spread of COVID-19 between connected communities is fundamental in planning appropriate mitigation measures. To that end, we propose and analyze a novel metapopulation network model, particularly suitable for modeling commuter traffic patterns, that takes into account the connectivity between a heterogeneous set of communities, each with its own infection dynamics. In the novel metapopulation model that we propose here, transport schemes developed in optimal transport theory provide an efficient and easily implementable way of describing the temporary population redistribution due to traffic, such as the daily commuter traffic between work and residence. Locally, infection dynamics in individual communities are described in terms of a susceptible-exposed-infected-recovered (SEIR) compartment model, modified to account for the specific features of COVID-19, most notably its spread by asymptomatic and presymptomatic infected individuals. The mathematical foundation of our metapopulation network model is akin to a transport scheme between two population distributions, namely the residential distribution and the workplace distribution, whose interface can be inferred from commuter mobility data made available by the US Census Bureau. We use the proposed metapopulation model to test the dynamics of the spread of COVID-19 on two networks, a smaller one comprising 7 counties in the Greater Cleveland area in Ohio, and a larger one consisting of 74 counties in the Pittsburgh–Cleveland–Detroit corridor following the Lake Erie’s American coastline. The model simulations indicate that densely populated regions effectively act as amplifiers of the infection for the surrounding, less densely populated areas, in agreement with the pattern of infections observed in the course of the COVID-19 pandemic. Computed examples show that the model can be used also to test different mitigation strategies, including one based on state-level travel restrictions, another on county level triggered social distancing, as well as a combination of the two.

scholarly journals Fueling the Covid-19 pandemic: summer school holidays and incidence rates in German districts

2021 ◽  
Author(s):  
Thomas Plümper ◽  
Eric Neumayer
Keyword(s):  
Public Health ◽  
Fixed Effects ◽  
Summer School ◽  
Incidence Rates ◽  
Contact Tracing ◽  
Robert Koch Institute ◽  
Cross Sectional ◽  
Holiday Period ◽  
Health Authorities ◽  
Public Health Authorities

AbstractBackgroundThe Robert-Koch-Institute reports that during the summer holiday period a foreign country is stated as the most likely place of infection for an average of 27 and a maximum of 49% of new SARS-CoV-2 infections in Germany.MethodsCross-sectional study on observational data. In Germany, summer school holidays are coordinated between states and spread out over 13 weeks. Employing a dynamic model with district fixed effects, we analyze the association between these holidays and weekly incidence rates across 401 German districts.ResultsWe find effects of the holiday period of around 45% of the average district incidence rates in Germany during their respective final week of holidays and the 2 weeks after holidays end. Western states tend to experience stronger effects than Eastern states. We also find statistically significant interaction effects of school holidays with per capita taxable income and the share of foreign residents in a district’s population.ConclusionsOur results suggest that changed behavior during the holiday season accelerated the pandemic and made it considerably more difficult for public health authorities to contain the spread of the virus by means of contact tracing. Germany’s public health authorities did not prepare adequately for this acceleration.

scholarly journals EHEC O111:H8 strain and norovirus GII.4 Sydney [P16] causing an outbreak in a daycare center, Brazil, 2019

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Liliana Cruz Spano ◽  
Caroline Gastaldi Guerrieri ◽  
Lays Paula Bondi Volpini ◽  
Ricardo Pinto Schuenck ◽  
Jaqueline Pegoretti Goulart ◽  
...  
Keyword(s):  
Southeastern Brazil ◽  
Viral Pathogens ◽  
Daycare Center ◽  
Staff Members ◽  
Health Authorities ◽  
Single Locus Variant ◽  
Public Health Authorities ◽  
Uremic Syndrome ◽  
Norovirus Gii ◽  
Relationship Of

Abstract Background This study describes the investigation of an outbreak of diarrhea, hemorrhagic colitis (HC), and hemolytic uremic syndrome (HUS) at a daycare center in southeastern Brazil, involving fourteen children, six staff members, six family members, and one nurse. All bacterial and viral pathogens detected were genetically characterized. Results Two isolates of a strain of enterohemorrhagic Escherichia coli (EHEC) serotype O111:H8 were recovered, one implicated in a case of HUS and the other in a case of uncomplicated diarrhea. These isolates had a clonal relationship of 94% and carried the stx2a and eae virulence genes and the OI-122 pathogenicity island. The EHEC strain was determined to be a single-locus variant of sequence type (ST) 327. EHEC isolates were resistant to ofloxacin, doxycycline, tetracycline, ampicillin, and trimethoprim-sulfamethoxazole and intermediately resistant to levofloxacin and ciprofloxacin. Rotavirus was not detected in any samples, and norovirus was detected in 46.7% (14/30) of the stool samples, three of which were from asymptomatic staff members. The noroviruses were classified as the recombinant GII.4 Sydney [P16] by gene sequencing. Conclusion In this outbreak, it was possible to identify an uncommon stx2a + EHEC O111:H8 strain, and the most recent pandemic norovirus strain GII.4 Sydney [P16]. Our findings reinforce the need for surveillance and diagnosis of multiple enteric pathogens by public health authorities, especially during outbreaks.

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