Author:
Nicolelis Miguel A. L.,Raimundo Rafael L. G.,Peixoto Pedro S.,Andreazzi Cecilia S.
Abstract
AbstractAlthough international airports served as main entry points for SARS-CoV-2, the factors driving the uneven geographic spread of COVID-19 cases and deaths in Brazil remain mostly unknown. Here we show that three major factors influenced the early macro-geographical dynamics of COVID-19 in Brazil. Mathematical modeling revealed that the “super-spreading city” of São Paulo initially accounted for more than 85% of the case spread in the entire country. By adding only 16 other spreading cities, we accounted for 98–99% of the cases reported during the first 3 months of the pandemic in Brazil. Moreover, 26 federal highways accounted for about 30% of SARS-CoV-2’s case spread. As cases increased in the Brazilian interior, the distribution of COVID-19 deaths began to correlate with the allocation of the country’s intensive care units (ICUs), which is heavily weighted towards state capitals. Thus, severely ill patients living in the countryside had to be transported to state capitals to access ICU beds, creating a “boomerang effect” that contributed to skew the distribution of COVID-19 deaths. Therefore, if (i) a lockdown had been imposed earlier on in spreader-capitals, (ii) mandatory road traffic restrictions had been enforced, and (iii) a more equitable geographic distribution of ICU beds existed, the impact of COVID-19 in Brazil would be significantly lower.
Funder
Duke University Medical Center Distinguished Professor Endowed Chair
Brazilian Synthesis Center on Biodiversity and Ecosystem Services
Fundação de Amparo à Pesquisa do Estado de São Paulo
CNPq
Publisher
Springer Science and Business Media LLC
Reference48 articles.
1. Coronavirus Resource Center. "COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU)." John Hopkins University & Medicine (2020). https://coronavirus.jhu.edu/map.html (2020).
2. Candido, D. et al. Routes for COVID-19 importation in Brazil. J. Travel Med. 27, taaa042 (2020).
3. Candido, D. S. et al. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science 369, 1255–1260. https://doi.org/10.1126/science.abd2161 (2020).
4. Wilson, J. R., Dormontt, E. E., Prentis, P. J., Lowe, A. J. & Richardson, D. M. Something in the way you move: Dispersal pathways affect invasion success. Trends Ecol. Evol. 24, 136–144. https://doi.org/10.1016/j.tree.2008.10.007 (2009).
5. Ogden, N. H. et al. Emerging infectious diseases and biological invasions: A call for a One Health collaboration in science and management. R. Soc. Open Sci. 6, 181577. https://doi.org/10.1098/rsos.181577 (2019).
Cited by
55 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献