RT Journal Article
T1 Assessing population-sampling strategies for reducing the COVID-19 incidence
A1 Guzmán Merino, Miguel
A1 Durán, Christian
A1 Marinescu, María Cristina
A1 Delgado Sanz, Concepción
A1 Gómez Barroso, Diana
A1 Carretero Pérez, Jesús
A1 Singh, David E.
AB As long as critical levels of vaccination have not been reached to ensure heard immunity, and new SARS-CoV-2 strains are developing, the only realistic way to reduce the infection speed in a population is to track the infected individuals before they pass on the virus. Testing the population via sampling has shown good results in slowing the epidemic spread. Sampling can be implemented at different times during the epidemic and may be done either per individual or for combined groups of people at a time. The work we present here makes two main contributions. We first extend and refine our scalable agent-based COVID-19 simulator to incorporate an improved socio-demographic model which considers professions, as well as a more realistic population mixing model based on contact matrices per country. These extensions are necessary to develop and test various sampling strategies in a scenario including the 62 largest cities in Spain; this is our second contribution. As part of the evaluation, we also analyze the impact of different parameters, such as testing frequency, quarantine time, percentage of quarantine breakers, or group testing, on sampling efficacy. Our results show that the most effective strategies are pooling, rapid antigen test campaigns, and requiring negative testing for access to public areas. The effectiveness of all these strategies can be greatly increased by reducing the number of contacts for infected individual.
PB ELSEVIER BV
SN 0010-4825
YR 2021
FD 2021-12
LK https://hdl.handle.net/10016/34687
UL https://hdl.handle.net/10016/34687
LA eng
NO This work has been supported by the Carlos III Institute of Health under the project grant 2020/00183/001, the project grant BCV-2021-1-0011, of the SpanishSupercomputing Network (RES) and the European Union’s Horizon 2020 JTI-EuroHPC research and innovation program under grant agreement No 956748. The roleof all study sponsors was limited to financial support and did not imply participation of any kind in the study and collection, analysis, and interpretation of data, norin the writing of the manuscript.
DS e-Archivo
RD 18 jul. 2024