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Disease outbreak simulation reveals the effects of “dissemination” by multiple infected individuals

PLOS Computational Biology , CC-BY 4.0 (creativecommons.org/licenses/by/4.0/) “width =” 800 “height =” 530 “/>

Epidemic epicenter analysis. Check the modified coefficient of determination R * correlation for peak mobility and destination incidence for each country of origin. The dark areas probably represent the areas where the spread occurred. Management boundary data was obtained from GADM (https://gadm.org) in Italy and Spain and from EuroStat (https://ec.europa.eu/eurostat) in other countries. Credit: Mazzoli M et al. , PLOS Computational Biology, CC-BY 4.0 (creativecommons.org/licenses/by/4.0/)

A new computational analysis shows that one infected person arrives and more infected people continue to arrive beyond the initial impact of spreading the disease to a previously uninfected population with advanced local outbreaks and severe illness. It suggests that it has a significant impact on the degree. Mattia Mazzoli, Jose Javier Ramasco, and colleagues publish these findings in open access journals. PLOS Computational Biology..

In the light of the ongoing COVID-19 pandemic, many studies have investigated the dynamics of local development caused by the first detected case. population, Linked to travel. However, few studies have investigated whether and how the arrival of multiple infected individuals affects the development of locals. Outbreak— A situation called “multi-seed”.

To investigate the effects of multi-seed, Mazzoli et al. First used a computational modeling approach to simulate regional outbreaks in Europe. To capture travel and sowing events, the simulation incorporated actual location data from mobile phones in March 2020, when the COVID-19 pandemic began.

These simulations suggested that there was a real association between the number of “seed” arrivals per piece. Locals And the rate of spread, the final number of infected people, and the peak incidence experienced by the population. This relationship appears complex and non-linear and depends on the details of the social contact network within the affected population, including the effects of the blockade.

To test whether the simulation accurately reflected the actual outbreak, researchers conducted mobility data and COVID- during the first wave of COVID-19 infections in the United Kingdom, France, Germany, Italy and Spain. We looked for similar associations between 19 incidence and mortality. This analysis revealed strong signs of a real-world multi-seed effect similar to that observed in the simulation.

Based on these findings, researchers suggest ways to understand and reconstruct the spatial spread patterns of major events that occur in all countries.

“Once we understand the relevance of multi-seed, it’s important to develop containment measures that take that into account,” says Lamasco. Next, researchers want to incorporate the effects of vaccination and antibodies gained from the infection into the simulation.


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For more information:
Mazzoli M, Pepe E, Mateo D, Cattuto C, Gauvin L, Bajardi P, et al. (2021) Interactions between mobility, multiseed, and blockade form the local effects of COVID-19. PLoS Comput Biol 17 (10): e1009326. doi.org/10.1371/journal.pcbi.1009326

Quote: Disease outbreak simulations for multiple infected individuals (2021) obtained on October 14, 2021 from https://medicalxpress.com/news/2021-10-disease-outbreak-simulations-reveal-seeding.html We will clarify the effect of “sowing” by (October 14)

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Disease outbreak simulation reveals the effects of “dissemination” by multiple infected individuals

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