Modelling microbial infection to address global health challenges

Fitzpatrick, Meagan C.; Bauch, Chris T.; Townsend, Jeffrey P.; Galvani, Alison P.

doi:10.1038/s41564-019-0565-8

Cited by 45 publications

(32 citation statements)

References 103 publications

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“…Intervention measures adopted with the intention to mitigate the spread, are normally based in estimates of the progression of the outbreak. Mathematical models of infectious diseases are important tools for assessing the threat of a novel pathogen and offer the best information for mitigating an outbreak [5], [6]. Hence the need for epidemiological models that are able to estimate with some degree of accuracy the evolution of the outbreak to help to evaluate the impact of interventions [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Inhomogeneous mixing and asynchronic transmission between local outbreaks account for the spread of COVID-19 epidemics

Mendoza

2020

Preprint

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The ongoing epidemic of COVID-19 originated in China has reinforced the need to develop epidemiological models capable of describing the progression of the disease to be of use in the formulation of mitigation policies. Here, this problem is addressed using a metapopulation approach to show that the delay in the transmission of the spread between different subsets of the total population, can be incorporated into a SIR framework through a time-dependent transmission rate. Thus, the reproduction number decreases with time despite the population dynamics remains uniform and the depletion of susceptible individuals is small. The obtained results are consistent with the early subexponential growth observed in the cumulated number of confirmed cases even in the absence of containment measures. We validate our model by describing the evolution of the COVID-19 using real data from different countries with an emphasis in the case of Mexico and show that it describes correctly also the long-time dynamics of the spread. The proposed model yet simple is successful at describing the onset and progression of the outbreak and considerably improves accuracy of predictions over traditional compartmental models. The insights given here may probe be useful to forecast the extent of the public health risks of epidemics and thus improving public policy-making aimed at reducing such risks.

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Section: Introductionmentioning

confidence: 99%

Inhomogeneous mixing and asynchronic transmission between local outbreaks account for the spread of COVID-19 epidemics

Mendoza

2020

Preprint

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“…Diseases caused by microbial pathogens have long plagued humanity, and are responsible for over 400 million years of potential life lost (a measure of premature mortality) annually across the globe [ 1 ]. Mass-gathering built environments such as hospitals, schools, and airports can become hot spots for microbial pathogen colonization, transmission, and exposure, spreading infectious diseases among people in communities, cities, nations, and worldwide.…”

Section: Introductionmentioning

confidence: 99%

Segmenting areas of potential contamination for adaptive robotic disinfection in built environments

Zhong

Ли

et al. 2020

Building and Environment

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Mass-gathering built environments such as hospitals, schools, and airports can become hot spots for pathogen transmission and exposure. Disinfection is critical for reducing infection risks and preventing outbreaks of infectious diseases. However, cleaning and disinfection are labor-intensive, time-consuming, and health-undermining, particularly during the pandemic of the coronavirus disease in 2019. To address the challenge, a novel framework is proposed in this study to enable robotic disinfection in built environments to reduce pathogen transmission and exposure. First, a simultaneous localization and mapping technique is exploited for robot navigation in built environments. Second, a deep-learning method is developed to segment and map areas of potential contamination in three dimensions based on the object affordance concept. Third, with short-wavelength ultraviolet light, the trajectories of robotic disinfection are generated to adapt to the geometries of areas of potential contamination to ensure complete and safe disinfection. Both simulations and physical experiments were conducted to validate the proposed methods, which demonstrated the feasibility of intelligent robotic disinfection and highlighted the applicability in mass-gathering built environments.

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“…In the last few years, a serious global problem is an increase in morbidity and mortality due to infectious diseases caused by pathogenic microbes such as viruses, bacteria, and fungi. Such infections cause at least 400 million deaths annually ( Fitzpatrick et al, 2019 ). Even the Coronavirus pandemic has now infected millions of people in the world in a short time, proving that pathogenic microbes are becoming a severe problem that can threaten human life and the economic stability of many countries.…”

Section: Introductionmentioning

confidence: 99%

Excellent antimicrobial performance of co-doped magnetite double-layered ferrofluids fabricated from natural sand

Taufiq

Saputro

Yuliantika

et al. 2020

Journal of King Saud University - Science

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The preparation of Co-doped magnetite ferrofluids from natural sand was developed using a double-layer technique. The Co-doped magnetite nanoparticles formed a spinel phase with lattice parameters in the range of 8.355–8.422 Å and tended to agglomerate with the particle sizes of 7–12 nm. The presence of the first and second layers from oleic acid and DMSO was detected by the infrared spectrum as well as the olive oil used as a carrier liquid. The saturation magnetization of the superparamagnetic samples decreased from 24.4 to 4.8 emu/g with decreasing Co 2+ composition. The particle size and electrostatic forces between the magnetic particles and the microbes played an essential role in inhibiting microbial growth. Interestingly, the increasing Co 2+ composition enhanced the superior performance of the ferrofluids against E. coli, S. aureus, B. subtilis, and C. albicans . With additional extensive investigation, we believe that the prepared Co-doped magnetite double-layered ferrofluids from natural sand with superior antimicrobial performance can be new significant antimicrobial agents.

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Modelling microbial infection to address global health challenges

Cited by 45 publications

References 103 publications

Inhomogeneous mixing and asynchronic transmission between local outbreaks account for the spread of COVID-19 epidemics

Inhomogeneous mixing and asynchronic transmission between local outbreaks account for the spread of COVID-19 epidemics

Segmenting areas of potential contamination for adaptive robotic disinfection in built environments

Excellent antimicrobial performance of co-doped magnetite double-layered ferrofluids fabricated from natural sand

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