scholarly journals Intensity and frequency of extreme novel epidemics

2021 ◽  
Vol 118 (35) ◽  
pp. e2105482118 ◽  
Author(s):  
Marco Marani ◽  
Gabriel G. Katul ◽  
William K. Pan ◽  
Anthony J. Parolari

Observational knowledge of the epidemic intensity, defined as the number of deaths divided by global population and epidemic duration, and of the rate of emergence of infectious disease outbreaks is necessary to test theory and models and to inform public health risk assessment by quantifying the probability of extreme pandemics such as COVID-19. Despite its significance, assembling and analyzing a comprehensive global historical record spanning a variety of diseases remains an unexplored task. A global dataset of historical epidemics from 1600 to present is here compiled and examined using novel statistical methods to estimate the yearly probability of occurrence of extreme epidemics. Historical observations covering four orders of magnitude of epidemic intensity follow a common probability distribution with a slowly decaying power-law tail (generalized Pareto distribution, asymptotic exponent = −0.71). The yearly number of epidemics varies ninefold and shows systematic trends. Yearly occurrence probabilities of extreme epidemics, Py, vary widely: Py of an event with the intensity of the “Spanish influenza” (1918 to 1920) varies between 0.27 and 1.9% from 1600 to present, while its mean recurrence time today is 400 y (95% CI: 332 to 489 y). The slow decay of probability with epidemic intensity implies that extreme epidemics are relatively likely, a property previously undetected due to short observational records and stationary analysis methods. Using recent estimates of the rate of increase in disease emergence from zoonotic reservoirs associated with environmental change, we estimate that the yearly probability of occurrence of extreme epidemics can increase up to threefold in the coming decades.

2021 ◽  
Author(s):  
Marco Marani ◽  
Gabriel Katul ◽  
William Pan ◽  
Anthony Parolari

<p>Human-natural processes that generate extreme events with large financial, social, and health consequences,  are inherently non-stationary due to ever-changing anthropogenic pressures and societal exposure. The issues posed by non-stationarity are recognized and addressed in Earth system science.  However, extensive epidemiological information remains fragmented and virtually unexplored from this perspective due to the lack of approaches to leverage observations of a heterogeneous past. To address this gap, we assembled a long historical record (1600-present) of infectious disease epidemics from the literature.  This new record enabled the development and applications of methods to quantify the time-varying probability of occurrence of extreme epidemic events. We define the intensity of epidemic events, the number of deaths/time/global population, and find that observations from several hundred years, covering almost four orders of magnitude of epidemic intensity, follow a probability distribution  with a slowly-decaying power-law tail (Generalized Pareto Distribution, asymptotic exponent = -0.705). To the contrary, the yearly number of epidemics is non-stationary, implying that conventional extreme value analyses are inappropriate.  We find that the rate of occurrence of extreme epidemics varies nine-fold over centennial time scales, from about 0.4 to 3.6 epidemics/year. As a result, yearly occurrence probabilities of extreme epidemics are far from constant:  The intensity computed for the most extreme event on record – the “Spanish Influenza” of 1918-1920 – has a probability of occurrence varying from 0.27 to 1.75 %/year in the time frame from 1600 to present. When optimistically assuming that 1 year is required to develop, produce, and begin distributing a vaccine/treatment for a new disease (e.g. the recent COVID-19 case), we estimate that the average recurrence time of a pandemic killing most of the global population is now less than 12,000 years.</p>


2019 ◽  
Vol 147 ◽  
Author(s):  
F. Mboussou ◽  
P. Ndumbi ◽  
R. Ngom ◽  
Z. Kassamali ◽  
O. Ogundiran ◽  
...  

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.


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 ◽  
...  

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.


2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S340-S341
Author(s):  
Shweta Anjan ◽  
Dimitra Skiada ◽  
Miriam Andrea Duque Cuartas ◽  
Douglas Salguero ◽  
David P Serota ◽  
...  

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


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Cencetti ◽  
G. Santin ◽  
A. Longa ◽  
E. Pigani ◽  
A. Barrat ◽  
...  

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.


2021 ◽  
Vol 11 (11) ◽  
pp. 5114
Author(s):  
Hyung-Chul Rah ◽  
Hyeon-Woong Kim ◽  
Aziz Nasridinov ◽  
Wan-Sup Cho ◽  
Seo-Hwa Choi ◽  
...  

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.


Author(s):  
Steffen Unkel ◽  
C. Paddy Farrington ◽  
Paul H. Garthwaite ◽  
Chris Robertson ◽  
Nick Andrews

2021 ◽  
pp. 097325862098117
Author(s):  
Hye-Jin Paek ◽  
Thomas Hove

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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