scholarly journals Strategies for Vaccine Prioritization and Mass Dispensing

Vaccines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 506
Author(s):  
Eva Lee ◽  
Zhuonan Li ◽  
Yifan Liu ◽  
James LeDuc
Keyword(s):  
Mixed Strategy ◽  
Disease Outbreaks ◽  
Vaccination Strategy ◽  
Mortality Rates ◽  
General Purpose ◽  
Propagation Model ◽  
Model Parameters ◽  
Modeling Framework ◽  
Infectious Disease Outbreaks ◽  
Behavior Network

We propose a system that helps decision makers during a pandemic find, in real time, the mass vaccination strategies that best utilize limited medical resources to achieve fast containments and population protection. Our general-purpose framework integrates into a single computational platform a multi-purpose compartmental disease propagation model, a human behavior network, a resource logistics model, and a stochastic queueing model for vaccination operations. We apply the modeling framework to the current COVID-19 pandemic and derive an optimal trigger for switching from a prioritized vaccination strategy to a non-prioritized strategy so as to minimize the overall attack rate and mortality rate. When vaccine supply is limited, such a mixed vaccination strategy is broadly effective. Our analysis suggests that delays in vaccine supply and inefficiencies in vaccination delivery can substantially impede the containment effort. Employing an optimal mixed strategy can significantly reduce the attack and mortality rates. The more infectious the virus, the earlier it helps to open the vaccine to the public. As vaccine efficacy decreases, the attack and mortality rates rapidly increase by multiples; this highlights the importance of early vaccination to reduce spreading as quickly as possible to lower the chances for further mutations to evolve and to reduce the excessive healthcare burden. To maximize the protective effect of available vaccines, of equal importance are determining the optimal mixed strategy and implementing effective on-the-ground dispensing. The optimal mixed strategy is quite robust against variations in model parameters and can be implemented readily in practice. Studies with our holistic modeling framework strongly support the urgent need for early vaccination in combating the COVID-19 pandemic. Our framework permits rapid custom modeling in practice. Additionally, it is generalizable for different types of infectious disease outbreaks, whereby a user may determine for a given type the effects of different interventions including the optimal switch trigger.

scholarly journals Digital proximity tracing on empirical contact networks for pandemic control

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Cencetti ◽  
G. Santin ◽  
A. Longa ◽  
E. Pigani ◽  
A. Barrat ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Outbreaks ◽  
Physical Distance ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Modeling Framework ◽  
Infectious Disease Outbreaks ◽  
Contact Patterns ◽  
Contact Data ◽  
The Impact

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.

scholarly journals Optimizing spatial and seasonal deployment of vaccination campaigns to eliminate wildlife rabies

2019 ◽  
Vol 374 (1776) ◽  
pp. 20180280 ◽  
Author(s):  
Laurie Baker ◽  
Jason Matthiopoulos ◽  
Thomas Müller ◽  
Conrad Freuling ◽  
Katie Hampson
Keyword(s):  
Infectious Disease ◽  
Plant Pathogens ◽  
Herd Immunity ◽  
Disease Outbreaks ◽  
Vaccination Strategy ◽  
Theme Issue ◽  
Infectious Disease Outbreaks ◽  
Control Programmes ◽  
The Face ◽  
And Control

Understanding how the spatial deployment of interventions affects elimination time horizons and potential for disease re-emergence has broad application to control programmes targeting human, animal and plant pathogens. We previously developed an epidemiological model that captures the main features of rabies spread and the impacts of vaccination based on detailed records of fox rabies in eastern Germany during the implementation of an oral rabies vaccination (ORV) programme. Here, we use simulations from this fitted model to determine the best vaccination strategy, in terms of spatial placement and timing of ORV efforts, for three epidemiological scenarios representative of current situations in Europe. We found that consecutive and comprehensive twice-yearly vaccinations across all regions rapidly controlled and eliminated rabies and that the autumn campaigns had the greater impact on increasing the probability of elimination. This appears to result from the need to maintain sufficient herd immunity in the face of large birth pulses, as autumn vaccinations reach susceptible juveniles and therefore a larger proportion of the population than spring vaccinations. Incomplete vaccination compromised time to elimination requiring the same or more vaccination effort to meet similar timelines. Our results have important practical implications that could inform policies for rabies containment and elimination in Europe and elsewhere. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

scholarly journals Effect of clustering and correlation of belief systems on infectious disease outbreaks

2020 ◽  
Author(s):  
Claus Kadelka ◽  
Audrey McCombs
Keyword(s):  
Infectious Disease ◽  
Risk Mitigation ◽  
Belief Systems ◽  
Disease Outbreaks ◽  
Interaction Network ◽  
Vaccination Strategy ◽  
Individual Risk ◽  
Effective Vaccine ◽  
Relative Level ◽  
Infectious Disease Outbreaks

AbstractContact between people with similar opinions and characteristics occurs at a higher rate than among other people, a phenomenon known as homophily. The presence of clusters of unvaccinated people has been associated with increased incidence of infectious disease outbreaks despite high vaccination coverage. The epidemiological consequences of homophily regarding other beliefs and correlations among belief systems are however poorly understood. Here, we use a simple compartmental disease model as well as a more complex COVID-19 model to study how homophily and correlation of belief systems in a social interaction network affect the probability of disease outbreak and COVID-19-related mortality. We find that the current social context, characterized by the presence of homophily and correlations between who vaccinates, who engages in risk reduction, and individual risk status, corresponds to a situation with substantially worse disease burden than in the absence of heterogeneities. In the presence of an effective vaccine, relative effects of homophily and correlation of belief systems become stronger. Further, the optimal vaccination strategy depends on the degree of homophily regarding vaccination status as well as the relative level of risk mitigation high- and low-risk individuals practice. The developed methods are broadly applicable to any investigation in which node attributes in a graph might reasonably be expected to cluster or exhibit correlations.

scholarly journals Effect of homophily and correlation of beliefs on COVID-19 and general infectious disease outbreaks

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260973
Author(s):  
Claus Kadelka ◽  
Audrey McCombs
Keyword(s):  
Infectious Disease ◽  
Risk Mitigation ◽  
Disease Model ◽  
Disease Outbreaks ◽  
Interaction Network ◽  
Vaccination Strategy ◽  
Individual Risk ◽  
Effective Vaccine ◽  
Relative Level ◽  
Infectious Disease Outbreaks

Contact between people with similar opinions and characteristics occurs at a higher rate than among other people, a phenomenon known as homophily. The presence of clusters of unvaccinated people has been associated with increased incidence of infectious disease outbreaks despite high population-wide vaccination rates. The epidemiological consequences of homophily regarding other beliefs as well as correlations among beliefs or circumstances are poorly understood, however. Here, we use a simple compartmental disease model as well as a more complex COVID-19 model to study how homophily and correlation of beliefs and circumstances in a social interaction network affect the probability of disease outbreak and COVID-19-related mortality. We find that the current social context, characterized by the presence of homophily and correlations between who vaccinates, who engages in risk reduction, and individual risk status, corresponds to a situation with substantially worse disease burden than in the absence of heterogeneities. In the presence of an effective vaccine, the effects of homophily and correlation of beliefs and circumstances become stronger. Further, the optimal vaccination strategy depends on the degree of homophily regarding vaccination status as well as the relative level of risk mitigation high- and low-risk individuals practice. The developed methods are broadly applicable to any investigation in which node attributes in a graph might reasonably be expected to cluster or exhibit correlations.

scholarly journals Infectious disease outbreaks in the African region: overview of events reported to the World Health Organization in 2018

2019 ◽  
Vol 147 ◽  
Author(s):  
F. Mboussou ◽  
P. Ndumbi ◽  
R. Ngom ◽  
Z. Kassamali ◽  
O. Ogundiran ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Onset ◽  
Disease Outbreaks ◽  
Case Fatality ◽  
World Health ◽  
African Region ◽  
Regional Office ◽  
Member States ◽  
Infectious Disease Outbreaks ◽  
The World

Abstract The WHO African region is characterised by the largest infectious disease burden in the world. We conducted a retrospective descriptive analysis using records of all infectious disease outbreaks formally reported to the WHO in 2018 by Member States of the African region. We analysed the spatio-temporal distribution, the notification delay as well as the morbidity and mortality associated with these outbreaks. In 2018, 96 new disease outbreaks were reported across 36 of the 47 Member States. The most commonly reported disease outbreak was cholera which accounted for 20.8% (n = 20) of all events, followed by measles (n = 11, 11.5%) and Yellow fever (n = 7, 7.3%). About a quarter of the outbreaks (n = 23) were reported following signals detected through media monitoring conducted at the WHO regional office for Africa. The median delay between the disease onset and WHO notification was 16 days (range: 0–184). A total of 107 167 people were directly affected including 1221 deaths (mean case fatality ratio (CFR): 1.14% (95% confidence interval (CI) 1.07%–1.20%)). The highest CFR was observed for diseases targeted for eradication or elimination: 3.45% (95% CI 0.89%–10.45%). The African region remains prone to outbreaks of infectious diseases. It is therefore critical that Member States improve their capacities to rapidly detect, report and respond to public health events.

scholarly journals Antimicrobial Activity of Chitosan Oligosaccharides with Special Attention to Antiparasitic Potential

Marine Drugs ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 110
Author(s):  
Nayara Sousa da Silva ◽  
Nathália Kelly Araújo ◽  
Alessandra Daniele-Silva ◽  
Johny Wysllas de Freitas Oliveira ◽  
Júlia Maria de Medeiros ◽  
...  
Keyword(s):  
Disease Outbreaks ◽  
Biological Properties ◽  
Enzymatic Production ◽  
Infectious Disease Outbreaks ◽  
Chitosan Oligosaccharides ◽  
Lower Viscosity ◽  
Biomedical Industry ◽  
Parasite Aggregation ◽  
Hydrolysis Of

The global rise of infectious disease outbreaks and the progression of microbial resistance reinforce the importance of researching new biomolecules. Obtained from the hydrolysis of chitosan, chitooligosaccharides (COSs) have demonstrated several biological properties, including antimicrobial, and greater advantage over chitosan due to their higher solubility and lower viscosity. Despite the evidence of the biotechnological potential of COSs, their effects on trypanosomatids are still scarce. The objectives of this study were the enzymatic production, characterization, and in vitro evaluation of the cytotoxic, antibacterial, antifungal, and antiparasitic effects of COSs. NMR and mass spectrometry analyses indicated the presence of a mixture with 81% deacetylated COS and acetylated hexamers. COSs demonstrated no evidence of cytotoxicity upon 2 mg/mL. In addition, COSs showed interesting activity against bacteria and yeasts and a time-dependent parasitic inhibition. Scanning electron microscopy images indicated a parasite aggregation ability of COSs. Thus, the broad biological effect of COSs makes them a promising molecule for the biomedical industry.

scholarly journals 549. Clinical Characteristics and Outcomes of Patients with COVID-19 treated with Convalescent Plasma in Miami, Florida

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S340-S341
Author(s):  
Shweta Anjan ◽  
Dimitra Skiada ◽  
Miriam Andrea Duque Cuartas ◽  
Douglas Salguero ◽  
David P Serota ◽  
...  
Keyword(s):  
Treatment Options ◽  
Disease Outbreaks ◽  
Nasopharyngeal Swab ◽  
Rt Pcr ◽  
Health Crisis ◽  
Infectious Disease Outbreaks ◽  
Reactive Protein ◽  
High Acuity ◽  
Us Fda ◽  
Oxygen Requirements

Abstract Background The Coronavirus disease of 2019 (COVID-19) global health crisis caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in unprecedented mortality, impacted society, and strained healthcare systems, yet sufficient data regarding treatment options are lacking. Convalescent plasma, used since 1895 for infectious disease outbreaks, offers promise as a treatment option for COVID-19. Methods This is a retrospective study of patients diagnosed by a nasopharyngeal swab SARS-CoV-2 reverse transcriptase–polymerase chain reaction (RT-PCR), who received convalescent plasma between April to June 2020 at two large hospitals in Miami, Florida, as part of the US FDA Expanded Access Program for COVID-19 convalescent plasma (CCP). Results A total of 23 patients received CCP, 13 (57%) had severe COVID-19 disease, while 8 (35%) had critical or critical with multiorgan dysfunction. Median time of follow up was 26 (range, 7–79) days. Overall, 11 (48%) survived to discharge, 6 (26%) died, while 6 (26%) are currently hospitalized. All deaths reported were due to septic shock from secondary infections. 15 (65%) showed improvement in oxygen requirements 7 days post CCP transfusion. Measured inflammatory markers, c-reactive protein, lactate dehydrogenase, ferritin and d-dimer improved 7 days post transfusion in 13 (57%) patients. No adverse events due to the transfusion were reported. 10 (43.4%) patients had a negative SARS-CoV-2 RT-PCR at a median of 14.5 (range, 4–31) days after receiving convalescent plasma. Conclusion Administration of convalescent plasma was found to be safe, with favorable outcomes in this small cohort of relatively high acuity patients. Larger studies including control arms are needed to establish the efficacy of convalescent plasma on clinical and virologic outcomes for patients with COVID-19. Table Disclosures All Authors: No reported disclosures

scholarly journals Threshold Effects of Infectious Disease Outbreaks on Livestock Prices: Cases of African Swine Fever and Avian Influenza in South Korea

2021 ◽  
Vol 11 (11) ◽  
pp. 5114
Author(s):  
Hyung-Chul Rah ◽  
Hyeon-Woong Kim ◽  
Aziz Nasridinov ◽  
Wan-Sup Cho ◽  
Seo-Hwa Choi ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Infectious Diseases ◽  
Disease Outbreaks ◽  
African Swine Fever ◽  
Threshold Effect ◽  
Impact Response ◽  
Threshold Effects ◽  
Infectious Disease Outbreaks ◽  
Retail Prices ◽  
The Impact

In this paper we demonstrate the threshold effects of infectious diseases on livestock prices. Daily retail prices of pork and chicken were used as structured data; news and SNS mentions of African Swine Fever (ASF) and Avian Influenza (AI) were used as unstructured data. Models were tested for the threshold effects of disease-related news and SNS frequencies, specifically those related to ASF and AI, on the retail prices of pork and chicken, respectively. The effects were found to exist, and the values of ASF-related news on pork prices were estimated to be −9 and 8, indicating that the threshold autoregressive (TAR) model can be divided into three regimes. The coefficients of the ASF-related SNS frequencies on pork prices were 1.1666, 0.2663 and −0.1035 for regimes 1, 2 and 3, respectively, suggesting that pork prices increased by 1.1666 Korean won in regime 1 when ASF-related SNS frequencies increased. To promote pork consumption by SNS posts, the required SNS frequencies were estimated to have impacts as great as one standard deviation in the pork price. These values were 247.057, 1309.158 and 2817.266 for regimes 1, 2 and 3, respectively. The impact response periods for pork prices were estimated to last 48, 6, and 8 days for regimes 1, 2 and 3, respectively. When the prediction accuracies of the TAR and autoregressive (AR) models with regard to pork prices were compared for the root mean square error, the prediction accuracy of the TAR model was found to be slightly better than that of the AR. When the threshold effect of AI-related news on chicken prices was tested, a linear relationship appeared without a threshold effect. These findings suggest that when infectious diseases such as ASF occur for the first time, the impact on livestock prices is significant, as indicated by the threshold effect and the long impact response period. Our findings also suggest that the impact on livestock prices is not remarkable when infectious diseases occur multiple times, as in the case of AI. To date, this study is the first to suggest the use of SNS to promote meat consumption.

scholarly journals Statistical methods for the prospective detection of infectious disease outbreaks: a review

2011 ◽  
Vol 175 (1) ◽  
pp. 49-82 ◽  
Author(s):  
Steffen Unkel ◽  
C. Paddy Farrington ◽  
Paul H. Garthwaite ◽  
Chris Robertson ◽  
Nick Andrews
Keyword(s):  
Infectious Disease ◽  
Statistical Methods ◽  
Disease Outbreaks ◽  
Infectious Disease Outbreaks

scholarly journals Information Communication Technologies (ICTs), Crisis Communication Principles and the COVID-19 Response in South Korea

2021 ◽  
pp. 097325862098117
Author(s):  
Hye-Jin Paek ◽  
Thomas Hove
Keyword(s):  
Crisis Communication ◽  
Large Scale ◽  
Communication Strategies ◽  
Disease Outbreaks ◽  
Information Communication ◽  
Information And Communications Technologies ◽  
The South ◽  
South Korean ◽  
Infectious Disease Outbreaks ◽  
Control Programmes

This case study highlights several communication insights that have emerged from the South Korean national response to COVID-19. In particular, it focuses on how innovative disease control programmes and information and communications technologies (ICT) have been used in conjunction with appropriate message strategies. The South Korean government used ICTs in a variety of ways to enhance crisis communication, coordinate large-scale public health efforts and supply chains, and facilitate widespread adoption of preventive measures such as social distancing and mask wearing. The response and communication strategies were based on principles established by research in social sciences and recommended for pandemic response, including social marketing, crisis communication, and normative influence. South Korea’s COVID-19 response and communication strategies can provide useful insights for national efforts to manage COVID-19 and other possible future infectious disease outbreaks.

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