RESUMEN

Respiratory diseases, including influenza and coronaviruses, pose recurrent global threats. This study delves into the respiratory surveillance systems, focusing on the effectiveness of SARI sentinel surveillance for total and severe cases incidence estimation. Leveraging data from the COVID-19 pandemic in Chile, we examined 2020-2023 data (a 159-week period) comparing census surveillance results of confirmed cases and hospitalizations, with sentinel surveillance. Our analyses revealed a consistent underestimation of total cases and an overestimation of severe cases of sentinel surveillance. To address these limitations, we introduce a nowcasting model, improving the precision and accuracy of incidence estimates. Furthermore, the integration of genomic surveillance data significantly enhances model predictions. While our findings are primarily focused on COVID-19, they have implications for respiratory virus surveillance and early detection of respiratory epidemics. The nowcasting model offers real-time insights into an outbreak for public health decision-making, using the same surveillance data that is routinely collected. This approach enhances preparedness for emerging respiratory diseases by the development of practical solutions with applications in public health.

Asunto(s)

COVID-19 , Vigilancia de Guardia , Humanos , COVID-19/epidemiología , COVID-19/virología , Chile/epidemiología , SARS-CoV-2/aislamiento & purificación , Pandemias , Incidencia , Hospitalización/estadística & datos numéricos

RESUMEN

We propose a parsimonious, yet effective, susceptible-exposed-infected-removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of São Paulo, in Brazil and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days using out-of-sample data.

RESUMEN

After the M8.2 main-shock occurred on 7 September 2017 at the Isthmus of Tehuantepec, Mexico, the spatial distribution of seismicity has showed a clear clusterization of earthquakes along the collision region of the Tehuantepec Transform/Ridge with the Middle America Trench off Chiapas. Furthermore, nowadays, the temporal rate of occurrence in the number of earthquakes has also showed a pronounced increase. On the basis of this behavior, we studied the sequence of magnitudes of the earthquakes which occurred within the Isthmus of Tehuantepec in southern Mexico from 2010 to 2020. Since big earthquakes are considered as a phase transition, after the M8.2 main-shock, one must expect changes in the Tehuantepec ridge dynamics, which can be observed considering that the b-value in the Gutenberg-Richter law, has also showed changes in time. The goal of this paper is to characterize the behavior of the seismic activity by using the Gutenberg-Richter law, multifractal detrended fluctuation analysis, visibility graph and nowcasting method. Those methods have showed important parameters in order to assess risk, the multifractality and connectivity. Our findings indicate, first that b-value shows a dependency on time, which is clearly described by our analyses based on nowcasting method, multifractality and visibility graph.

RESUMEN

It has recently been shown in the Eastern Mediterranean that by combining natural time analysis of seismicity with earthquake networks based on similar activity patterns and earthquake nowcasting, an estimate of the epicenter location of a future strong earthquake can be obtained. This is based on the construction of average earthquake potential score maps. Here, we propose a method of obtaining such estimates for a highly seismically active area that includes Southern California, Mexico and part of Central America, i.e., the area N1035W80120. The study includes 28 strong earthquakes of magnitude M ≥7.0 that occurred during the time period from 1989 to 2020. The results indicate that there is a strong correlation between the epicenter of a future strong earthquake and the average earthquake potential score maps. Moreover, the method is also applied to the very recent 7 September 2021 Guerrero, Mexico, M7 earthquake as well as to the 22 September 2021 Jiquilillo, Nicaragua, M6.5 earthquake with successful results. We also show that in 28 out of the 29 strong M ≥7.0 EQs studied, their epicenters lie close to an estimated zone covering only 8.5% of the total area.

RESUMEN

The economic crisis triggered by COVID-19 has caused a world-wide economic downturn, and the deepest GDP contraction in Latin America since the beginning of the XX th century. One of the most dramatic outcomes of the crisis is the increase in poverty, but its extent will remain unknown until household income data is collected and analyzed. We propose a simple approach to provide early estimates, micro-simulating the short-run effect of the crisis on the poverty rate. It combines household level micro-data, estimates on the feasibility of working from home, information on key public policies (e.g., cash-transfers, unemployment insurance), and forecasts of GDP contraction. This approach, which can be easily adapted and applied to different countries, allows to nowcast the current poverty level and the poverty-reducing effect of public policies, while providing full micro-macro consistency between heterogeneous impacts on households and the shock to aggregate GDP. Moreover, it enables to estimate the effect on informal and self-employed workers, of utmost importance in developing countries. We illustrate the methodology with an application for Uruguay, finding that during the first full trimester of the crisis, the poverty rate grew by more than 38%, reaching 11.8% up from 8.5%. Moreover, cash transfers implemented by the government in the period had a positive but very limited effect in mitigating this poverty spike, which could be neutralized with additional transfers worth under 0.5% of Uruguay's annual GDP.

RESUMEN

One of the most important subduction zones in the world is located in the Mexican Pacific Coast, where the Cocos plate inserts beneath the North American plate. One part of it is located in the Mexican Pacific Coast, where the Cocos plate inserts beneath the North American plate with different dip angles, showing important seismicity. Under the central Mexican area, such a dip angle becomes practically horizontal and such an area is known as flat slab. An earthquake of magnitude M7.1 occurred on 19 September 2017, the epicenter of which was located in this flat slab. It caused important human and material losses of urban communities including a large area of Mexico City. The seismicity recorded in the flat slab region is analyzed here in natural time from 1995 until the occurrence of this M7.1 earthquake in 2017 by studying the entropy change under time reversal and the variability ß of the order parameter of seismicity as well as characterize the risk of an impending earthquake by applying the nowcasting method. The entropy change ΔS under time reversal minimizes on 21 June 2017 that is almost one week after the observation of such a minimum in the Chiapas region where a magnitude M8.2 earthquake took place on 7 September 2017 being Mexico's largest quake in more than a century. A minimum of ß was also observed during the period February-March 2017. Moreover, we show that, after the minimum of ΔS, the order parameter of seismicity starts diminishing, thus approaching gradually the critical value 0.070 around the end of August and the beginning of September 2017, which signals that a strong earthquake is anticipated shortly in the flat slab.