Result for
Topic: Modeling and Prediction
February 11, 2020
Preparation for Possible Sustained Transmission of 2019 Novel Coronavirus: Lessons From Previous Epidemics
Swerdlow and Finelli review information from modeling studies of earlier epidemics and pandemics to assess global preparedness for sustained transmission of an emerging viral disease with high transmissibility and severity. Examples cited were H1N1, SARS-CoV, and MERS-CoV. Models suggest that: Assuming no intervention in a US population, a model mixing a range of influenza transmission…
February 10, 2020
Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases
Using clinical, travel history, and disease progression information for 46 2019-nCoV cases who traveled from Wuhan before Jan 23 and were subsequently confirmed elsewhere, researchers attempted to model transmission dynamics with more precision than previous reports by simulating infection time. Findings suggest a much higher epidemic growth rate in the early days of the outbreak…
February 7, 2020
Epidemic doubling time of the 2019 novel coronavirus outbreak by province in mainland China
Researchers estimated the epidemic doubling time of the outbreak by province in mainland China. From Jan 20 – Feb 2, doubling time ranged from 1.0 day to 3.3 days, with Hubei estimated at 2.4 days. Social distancing measures appear to have been successful in slowing but not stopping epidemic growth. Muniz-Rodriguez et al. (Feb 6,…
February 6, 2020
Getting to zero quickly in the 2019-nCov epidemic with vaccines or rapid testing
Chowell, et al. model the effects of potential control measures. With a 100% effective vaccine, 80% coverage could end the epidemic in 6 months. Absent a vaccine, testing and isolation could end the epidemic in a similar timeframe if 90% of symptomatic cases could be reached within 24 hours of symptom onset. Other scenarios are…
Epidemiological parameter review and comparative dynamics of influenza, respiratory syncytial virus, rhinovirus, human coronavirus, and adenovirus
Spencer, et al. examine five virus groups (influenza, respiratory syncytial virus (RSV), rhinovirus, adenovirus, and human coronaviruses) that often contribute to the total category of “influenza-like-illness” (ILI). They estimate human coronaviruses account for around 8.8% of ILI cases annually. Epidemiologic characteristics are compared between human coronaviruses and the other four virus groups assessed. Incubation period,…
February 5, 2020
Using predicted imports of 2019-nCoV cases to determine locations that may not be identifying all imported cases
DeSalazar, et al. use air travel volume estimates out of Wuhan to identify countries that may have undetected cases. Their primary findings indicate the Indonesia likely has undetected cases; and that Cambodia and Thailand may have an undercount of cases. Improved public health surveillance is recommended for these countries. DeSalazar, et al. (Feb 5, 2020)….
Risk assessment of novel coronavirus 2019-nCoV outbreaks outside China
Boldog, et al. model the risk for 2019-nCoV outbreaks outside China by developing local reproduction numbers (Rloc) that incorporate factors affecting epidemiology in China and new locations, and their connectivity. Countries should balance controlling spread after introduction with preventing introduction. Countries with a low ability to control spread should focus on travel restrictions and traveler…
February 4, 2020
The association between domestic train transportation and novel coronavirus (2019-nCoV) outbreak in China from 2019 to 2020: A data-driven correlational report
Train travel was correlated with the spread of 2019-nCoV through mainland China. Zhao S, et al. (in press) DOI: https://doi.org/10.1016/j.tmaid.2020.101568
Effectiveness of airport screening at detecting travelers infected with 2019-nCoV
Airport screening will likely miss about 46% of infected travelers (in line with prior estimates) Quilty, et al. Pre-print downloaded 2 Feb, 2020 at, https://www.medrxiv.org/content/10.1101/2020.01.31.20019265v1
Estimating the risk on outbreak spreading of 2019-nCoV in China using transportation data
Using information from an International Air Transport Data database, SIR modeling techniques, and R0 estimates ranging from 1.4-2.9, critical timeframes for outbreak emergence (establishing transmission in a new locale) range from about 18-30 days. To gain 30 days in these scenarios, control measures must reduce connections between locales by 87-95%. Yuan HY, et al. Pre-print…
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