scholarly journals Toward an Early Warning System for Health Issues Related to Particulate Matter Exposure in Brazil: The Feasibility of Using Global PM2.5 Concentration Forecast Products

2020 ◽  
Vol 12 (24) ◽  
pp. 4074
Author(s):  
Emmanuel Roux ◽  
Eliane Ignotti ◽  
Nelson Bègue ◽  
Hassan Bencherif ◽  
Thibault Catry ◽  
...  

PM2.5 severely affects human health. Remotely sensed (RS) data can be used to estimate PM2.5 concentrations and population exposure, and therefore to explain acute respiratory disorders. However, available global PM2.5 concentration forecast products derived from models assimilating RS data have not yet been exploited to generate early alerts for respiratory problems in Brazil. We investigated the feasibility of building such an early warning system. For this, PM2.5 concentrations on a 4-day horizon forecast were provided by the Copernicus Atmosphere Monitoring Service (CAMS) and compared with the number of severe acute respiratory disease (SARD) cases. Confounding effects of the meteorological conditions were considered by selecting the best linear regression models in terms of Akaike Information Criterion (AIC), with meteorological features and their two-way interactions as explanatory variables and PM2.5 concentrations and SARD cases, taken separately, as response variables. Pearson and Spearman correlation coefficients were then computed between the residuals of the models for PM2.5 concentration and SARD cases. The results show a clear tendency to positive correlations between PM2.5 and SARD in all regions of Brazil but the South one, with Spearman’s correlation coefficient reaching 0.52 (p < 0.01). Positive significant correlations were also found in the South region by previously correcting the effects of viral infections on the SARD case dynamics. The possibility of using CAMS global PM2.5 concentration forecast products to build an early warning system for pollution-related effects on human health in Brazil was therefore established. Further investigations should be performed to determine alert threshold(s) and possibly build combined risk indicators involving other risk factors for human respiratory diseases. This is of particular interest in Brazil, where the COVID-19 pandemic and biomass burning are occurring concomitantly, to help minimize the effects of PM emissions and implement mitigation actions within populations.

2015 ◽  
Vol 100 ◽  
pp. 1-18 ◽  
Author(s):  
Simon C. Lin ◽  
Tso-Ren Wu ◽  
Eric Yen ◽  
Hsin-Yen Chen ◽  
John Hsu ◽  
...  

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 603 ◽  
Author(s):  
Stavroula Tsitsifli ◽  
Vasilis Kanakoudis

Drinking water supply safety is of paramount importance for human health. Disinfection is considered as one of the most significant water treatment processes as it inactivates pathogens from drinking water. However, disinfection might have adverse effects in human health, as disinfection by-products, blamed for cancer and reproductive/developmental effects, are formed. Many predictive models and optimization tools are developed in the research. However, an early warning system integrating monitoring, modelling and optimization tools is lacking. The paper reviews the disinfection methods and the models developed so far and presents the basic principles for the development of an early warning system.


Author(s):  
Panagiotis Pergantas ◽  
Nikos E. Papanikolaou ◽  
Chrisovalantis Malesios ◽  
Andreas Tsatsaris ◽  
Marios Kondakis ◽  
...  

The emergence and spread of vector-borne diseases (VBDs) is a function of biotic, abiotic and socio-economic drivers of disease while their economic and societal burden depends upon a number of time-varying factors. This work is concerned with the development of an early warning system that can act as a predictive tool for public health preparedness and response. We employ a host-vector model that combines entomological (mosquito data), social (immigration rate, demographic data), environmental (temperature) and geographical data (risk areas). The output consists of appropriate maps depicting suitable risk measures such as the basic reproduction number, R0, and the probability of getting infected by the disease. These tools consist of the backbone of a semi-automatic early warning system tool which can potentially aid the monitoring and control of VBDs in different settings. In addition, it can be used for optimizing the cost-effectiveness of distinct control measures and the integration of open geospatial and climatological data. The R code used to generate the risk indicators and the corresponding spatial maps along with the data is made available.


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