ABSTRACT
The damage of the novel Coronavirus disease (COVID-19) is reaching unprecedented scales. There are numerous classical epidemiology models trying to quantify epidemiology metrics. Usually, to forecast epidemics, classical approaches need parameter estimations, such as the contagion rate or the basic reproduction number. Here, we propose a data-driven, parameter-free, geometric approach to access the emergence of a pandemic state by studying the Forman-Ricci and Ollivier-Ricci network curvatures. Discrete Ollivier-Ricci curvature has been used successfully to forecast risk in financial networks and we suggest that those results can provide analogous results for COVID-19 epidemic time-series. We first compute both curvatures in a toy-model of epidemic time-series with delays, which allows us to create epidemic networks. By doing so, we are able to verify that the Ollivier-Ricci and Forman-Ricci curvatures can be a parameter-free estimate for identifying a pandemic state in the simulated epidemic. On this basis, we then compute both Forman-Ricci and Ollivier-Ricci curvatures for real epidemic networks built from COVID-19 epidemic time-series available at the World Health Organization (WHO). Both curvatures allow us to detect early warning signs of the emergence of the pandemic. The advantage of our method lies in providing an early geometrical data marker for the pandemic state, regardless of parameter estimation and stochastic modelling. This work opens the possibility of using discrete geometry to study epidemic networks.
ABSTRACT
Mayaro virus is an emergent alphavirus that infects humans, leading to Mayaro fever. Approximately fifty percent of infected patients develop arthritis symptoms in the recovery phase, a phase that can last up to a year. The literature about Mayaro virus infection and its immune response is scarce, which may hamper the development of treatment strategies. We summarize changes in cytokines and chemokines in the acute and recovery phase in Mayaro virus infected patients, and relate this molecular characterization with the immune response. VEGF and IL-12/p70 show pronounced changes in patients in the acute phase, suggesting the development of cellular immunity and Th1 response. IL-6, IL-7, CXCL8/IL-8, IL-13, IL-17, and IFN-γ are elevated in patients with arthritis symptoms in the long-term recovery phase, which may be related to the continuous inflammatory process, a possible Th2 inhibiting and promoting Th17 process. Although few studies discuss the issue, with a small number of patients and different backgrounds, inflammatory and immune response and manifestations seem to be closely linked. This information may help to develop the appropriate treatment strategies in Mayaro virus infection. Therefore, we analyzed and summarized data available in literature.
